JP7558878B2 - Deterioration detection system, deterioration detection method, and deterioration detection device - Google Patents

Description

The present invention relates to a deterioration detection system, a deterioration detection method, and a deterioration detection device, which are suitable for detecting deterioration of a track on which a vehicle runs.

Train cars and other vehicles that run on tracks require less energy for transportation because they run on tracks with little friction, making them an important part of social infrastructure. However, if an abnormality occurs on the track, other vehicles running on the same track must be stopped. This can have a serious impact on safe and secure passenger services, so damage to the track is prevented by regular maintenance.

In particular, the top surface of the track is repeatedly subjected to loads from the wheels, and as a result fatigue damage and wear are likely to accumulate and progress. In straight sections of the track, fatigue damage can cause cracks below the top surface, and if these progress and lead to breakage, vehicle operation will be hindered. For this reason, regular rail grinding is carried out to remove the fatigue layer on the top surface, preventing damage to the track and extending the track life. In curved sections of the track, wear is likely to progress due to lateral pressure from the wheels and sliding contact with the wheel flanges, so the head of the track is heat-treated to harden it and reduce wear. Extending the track life with such preventive measures reduces the labor and costs required for track replacement.

Patent Document 1 also discloses that a threshold exceedance time, which indicates the time when a characteristic value of a physical quantity of a drive system installed in a track-traveling vehicle exceeds a threshold, and a drive system position, which indicates the position of the drive system relative to the track-traveling vehicle at the threshold exceedance time, are acquired, and if it is determined that there is a correlation between multiple threshold exceedance times and the drive system positions at the threshold exceedance times for multiple drive systems installed in the track-traveling vehicle, a track abnormality signal is output indicating that there is an abnormality in the track.

Patent No. 6743304

However, currently, regular maintenance such as rail grinding is carried out according to uniform standards regardless of the individual state of deterioration of the track. Furthermore, this maintenance work is carried out at night, avoiding commercial operation hours. Therefore, major issues remain in terms of improving the efficiency of maintenance work and reducing the burden on workers.

Specifically, the current rail grinding cycle is based on an index called cumulative passing tonnage, which is the cumulative value of the axle load passing over the track. For example, rail grinding can be carried out when it reaches 50 million tons. However, the degree of deterioration of the track, such as fatigue damage and wear, varies greatly depending on the load conditions from the wheels, as well as the track construction conditions and environmental conditions. Furthermore, these conditions also vary greatly depending on the timing of the trains passing over.

Patent Document 1 discloses technology to detect track anomalies, but does not mention any specific measures to visualize the degree of deterioration of the track top surface, which determines the replacement life of the track. Other devices include ultrasonic flaw detectors, magnetic sensor flaw detectors, and image collection devices that use cameras. However, all of these devices are only able to detect track anomalies once they become apparent, so they have not yet replaced the regular maintenance mentioned above.

The present invention has been made in consideration of the above points, and aims to provide a deterioration detection system, a deterioration detection method, and a deterioration detection device that can more accurately detect the degree of deterioration of the track on which a vehicle runs.

To achieve the above object, one representative deterioration detection system of the present invention is a deterioration detection system that detects deterioration of a track on which a vehicle runs, and includes a running position acquisition unit that acquires the running position of the vehicle, an axle load acquisition unit that acquires the weight applied vertically downward on the wheel axle that drives the vehicle, an impact force input condition acquisition unit that acquires information on the conditions of the impact force on the track when the wheels of the vehicle pass through the track, a stress calculation condition acquisition unit that acquires information on the stress calculation conditions for calculating the stress generated when the wheels of the vehicle pass through the track, and a track deterioration progress calculation unit. The track deterioration progress calculation unit calculates and outputs a deterioration progress degree that indicates the progress of deterioration of the track using the weight information acquired by the axle load acquisition unit, the information acquired by the impact force input condition acquisition unit, and the information acquired by the stress calculation condition acquisition unit in correspondence with the position information acquired by the running position acquisition unit, and the deterioration progress degree is calculated using information for one or more wheel axles for each train for two or more trains including a vehicle that passes through the track.

Furthermore, one of the deterioration detection methods of the present invention is a deterioration detection method for detecting deterioration of a track on which a vehicle runs, and includes a running position acquisition step for acquiring the running position of the vehicle, an axle load acquisition step for acquiring the weight applied vertically downward on the wheel axle that drives the vehicle, an impact force input condition acquisition step for acquiring information on the input conditions of the impact force on the track when the wheels of the vehicle pass through the track, a stress calculation condition acquisition step for acquiring information on the stress calculation conditions for calculating the stress generated when the wheels of the vehicle pass through the track, and a track deterioration progress calculation step, in which the track deterioration progress calculation step calculates and outputs a deterioration progress degree indicating the progress of deterioration of the track using the weight information acquired in the axle load acquisition step, the information acquired in the impact force input condition acquisition step, and the information acquired in the stress calculation condition acquisition step in correspondence with the position information acquired in the running position acquisition step, and the deterioration progress degree is calculated using information for one or more wheel axles for each train for two or more trains including a vehicle that passes through the track.

According to the present invention, the deterioration detection system, deterioration detection method, and deterioration detection device can more accurately detect the degree of deterioration of the track on which a vehicle runs. Problems, configurations, and effects other than those described above will become clear from the description of the embodiments below.

FIG. 1 is an explanatory diagram of a vehicle and a track in a first embodiment of the present invention. FIG. 2 is a block diagram illustrating an output section of the deterioration detection device according to the first embodiment of the present invention. FIG. 3 is a block diagram illustrating a deterioration detection device according to a first embodiment of the present invention. FIG. 4 is a diagram illustrating an example of a flow of a determination process of the deterioration detection device according to the first embodiment of the present invention. FIG. 5 is a diagram for explaining a first example of a load acting on a track in the first embodiment of the present invention. FIG. 6 is a diagram for explaining a second example of the load acting on the track in the first embodiment of the present invention. FIG. 7 is a cross-sectional view of a track for explaining a load acting on the track in the first embodiment of the present invention. FIG. 8 is a diagram for explaining a first example of orbital position calculation in the first embodiment of the present invention. FIG. 9 is a diagram for explaining a second example of the orbit position calculation in the first embodiment of the present invention. FIG. 10 is a diagram showing a first example of the relationship between the vehicle speed and the traveling position in the first embodiment of the present invention. FIG. 11 is a diagram showing a second example of the relationship between the vehicle speed and the traveling position in the first embodiment of the present invention. FIG. 12 is a diagram illustrating a first example of a current acquisition unit in the first embodiment of the present invention. FIG. 13 is a diagram illustrating a second example of the current acquisition unit in the first embodiment of the present invention. FIG. 14 is a diagram illustrating an example of distances between points in the first embodiment of the present invention. FIG. 15 is a diagram illustrating an example of the relationship between the actual distance and the estimated distance in the first embodiment of the present invention. FIG. 16 is a diagram showing an example of a method for visualizing the degree of deterioration between points in the first embodiment of the present invention. FIG. 17 is a diagram illustrating a first example of a deterioration detection system according to the second embodiment of the present invention. FIG. 18 is a diagram illustrating a second example of a deterioration detection system according to the second embodiment of the present invention.

The following describes the form for implementing the present invention.

Each embodiment of the present invention will be described below with reference to the drawings. In the following description, identical components are given the same symbols. Their names and functions are the same, so duplicate explanations will be avoided. In addition, the following description focuses on railway vehicles, but the effects of the present invention are not limited to this and can be applied to all vehicles that run on tracks.

(First embodiment)
A first embodiment of the present invention will be described below with reference to FIGS.

Figure 1 is an explanatory diagram of a vehicle and track in a first embodiment of the present invention. The vehicle and track in this embodiment will be described with reference to Figure 1. A vehicle 100 is composed of wheels 10a, 10b, 10c, and 10d, and runs on a track 20. The top surface 21 of the track 20 is repeatedly subjected to loads from the wheels, which causes fatigue damage and wear to accumulate and progress. For example, in a straight section of the track 20, fatigue damage can cause cracks to form below the top surface 21, and if this progresses and leads to breakage, it can cause problems in the operation of the vehicle.

In the first embodiment, various conditions such as the load conditions when the vehicle 100 passes, track construction conditions, environmental conditions, etc. are quantified and calculated as the track deterioration progress degree in correspondence with the track position. By calculating the track deterioration progress degree, it becomes possible to visualize the deterioration state of the track. Specific means are explained below using Figures 2 to 16.

Figure 2 is a block diagram illustrating the output unit of the deterioration detection device in the first embodiment of the present invention. As shown in Figure 2, the track deterioration progress degree is calculated by the output unit 200. The output unit 200 includes a running position acquisition unit 300 and an axle load acquisition unit 310. The output unit 200 also includes at least one of a tangential force acquisition unit 320, a speed acquisition unit 330, a wheel flatness acquisition unit 340, a gradient acquisition unit 350, a curvature acquisition unit 360, a watering presence/absence acquisition unit 370, an environmental temperature acquisition unit 380, and a track stiffness acquisition unit 390. Furthermore, the output unit 200 includes a track deterioration progress degree calculation unit 400.

The running position acquisition unit 300 acquires running position information 301, which is information on the running position of the vehicle 100. The axle load acquisition unit 310 acquires axle load information 311, which is information on the weight applied vertically downward on the wheel axle (axle used for the wheel 10) that drives the vehicle 100. The tangential force acquisition unit 320 acquires tangential force information 321, which is information on the tangential force transmitted to the wheel axle by the drive system mechanically connected to the wheel axle. The speed acquisition unit 330 acquires speed information 331 of the vehicle 100 based on the rotation speed of the wheel axle, etc. The wheel flatness acquisition unit 340 acquires wheel flatness information 341, which is information on the size of the flat part on the wheel tread of the vehicle 100, etc. The gradient acquisition unit 350 acquires gradient information 351, which is information on the gradient of the track 20. The curvature acquisition unit 360 acquires curvature information 361, which is information on the curvature of the track 20. The watering presence/absence acquisition unit 370 acquires watering presence/absence information 371, which is information on the presence/absence of watering on the top surface 21 of the track 20. The environmental temperature acquisition unit 380 acquires environmental temperature information 381, which is information on the environmental temperature at the running position of the vehicle 100. The track stiffness acquisition unit 390 acquires track stiffness information 391, which is information on the stiffness of the track 20 at the running position of the vehicle 100.

The track deterioration progress calculation unit 400 also calculates the degree of deterioration of the track 20. Specifically, the track deterioration progress calculation unit 400 calculates the degree of deterioration of the track 20 based on the axle load information 311 acquired by the axle load acquisition unit 310 in correspondence with the running position information 301 acquired by the running position acquisition unit 300, and at least one of the acquired tangential force information 321, speed information 331, wheel flatness information 341, gradient information 351, curvature information 361, watering information 371, environmental temperature information 381, and track stiffness information 391.

The traveling position information 301 may be information obtained from a global positioning system (GPS) installed in the vehicle 100, or may be information obtained by calculating the traveling distance from the stopping position by integrating the vehicle speed (the speed of the vehicle 100), or may be other position information. Note that the vehicle speed here may be the speed information 331.

The axle load information 311 may be information calculated from the design weight of the vehicle 100, or may be information calculated taking into account the occupancy rate and loading rate, or may be other weight information. The occupancy rate of the vehicle may be calculated, for example, by detecting the flow of people at the station with a camera or the like and estimating the number of people on board the vehicle. The axle load acts as a vertical downward load on the track 20, and is therefore an important factor in the progression of fatigue damage to the track top surface 21.

The tangential force information 321 may be information calculated from a notch command from the vehicle cab, information calculated from the current value of the rotating machine that serves as the driving force source, or driving force information obtained from the vehicle weight and speed change rate. The tangential force includes the force generated on the track 20 when the wheels 10 are driven. Since the tangential force is applied as a horizontal load in the extension direction of the track 20, it is an important factor in the progression of fatigue damage to the track top surface 21.

The speed information 331 may be speed information used in vehicle operation control, information acquired by a speed sensor of the rotating machine that serves as the driving force source, information calculated from the current value of the rotating machine that serves as the driving force source, or other speed information. The faster the speed, the greater the impact load when the wheel 10 passes over the track 20, so speed is an important factor in the progression of fatigue damage to the track top surface 21. In addition, sudden braking and sudden acceleration that accelerate damage to the track 20 can be calculated from the rate of change of speed, and the speed information may be used from this perspective.

The wheel flatness information 341 may be information obtained from a detection system in the vehicle cab, information obtained from a vibration sensor installed near the wheel, information calculated from the current value of the rotating machine that serves as the driving force source, or other information. The wheel flatness is a flat surface formed on the wheel 10, and an angle is formed between this flat surface and the circumference of the wheel 10. As a result, when the rotational end of the flat surface contacts the track 20, a concentrated load is generated at this contact point for each rotation of the wheel 10. For this reason, the wheel flatness is an important factor that advances fatigue damage to the top surface 21 of the track 20. For example, when slipping occurs during braking, the wheel 10 slides against the track 20, and a flat surface is formed due to friction. When this slip state is detected by the vehicle cab, it can be treated as wheel flatness information 341. Also, when the wheel 10 slides against the track 20, the current value of the motor drops once. Then, in order to make the top surface 21 of the track 20 of the wheel 10 adhere again, the current is increased, and this behavior remains as current information, so it can be treated as wheel flatness information 341.

The slope information 351 and curvature information 361 may be information obtained from geographic information recorded on a computer, or may be information obtained from other geographic information. Furthermore, the watering information 371 and the environmental temperature information 381 may be information predicted on a computer, or information obtained from meteorological information recorded on a computer, or may be other information. The information obtained from a computer here includes information obtained via a network such as the Internet. For example, information on the topography, weather, temperature, etc. for each area obtained from the Internet.

Regarding the gradient information 351, when there is a gradient, the way in which the load is applied to the top surface 21 of the track 20 differs from when there is no gradient. This is because the vector of the vertical load due to the axle load and the vector of the load in the extension direction of the track 20 due to the tangential force are not perpendicular to each other. Therefore, the gradient information is an important factor in calculating the degree of progression of fatigue damage.

Regarding the curvature information 361, when the curvature is large, in addition to the vertical load due to the axle load and the load in the extension direction of the track 20 due to the tangential force, a load due to the lateral pressure of the wheels 10 occurs. Therefore, the way in which the load is applied to the track top surface 21 differs from that in a straight section due to the curvature. Therefore, the curvature information is an important factor in calculating the degree of progression of fatigue damage.

Regarding the watering information 371, if water is sprayed onto the track 20, thermal fatigue of the track 20 will progress. This is because friction when the wheels 10 pass over the track 20 causes a localized temperature rise in the top surface 21, and furthermore, moisture adhering to the top surface 21 rapidly removes heat, resulting in a large thermal shock. Therefore, the watering information is an important factor in calculating the degree of progress of fatigue damage.

In addition, with regard to the environmental temperature information 381, when there is no watering of the track 20 and the environmental temperature is high, the temperature of the track top surface 21 rises due to the effects of solar radiation, and a high temperature state is maintained. As a result, the thermal shock caused by friction when the wheels 10 pass over the track 20 is mitigated compared to when the environmental temperature is low. In addition, as described below, the material properties of the track base material change depending on the environmental temperature, so the internal stress of the track 20 changes when the wheels 10 pass over it. Therefore, the environmental temperature information is an important factor in calculating the degree of progression of fatigue damage.

The track stiffness information 391 may be stiffness information calculated based on the material properties of the track and the state of laying of the sleepers supporting the track 20, or may be information indicating other stiffness. When the track stiffness is high, the amount of deformation of the track 20 is small, so the internal stress of the top surface 21 of the track 20 when the wheel 10 passes is large. This is because the track 20 is less flexible between the sleepers and is more susceptible to local stress from the wheel 10. On the other hand, when the track stiffness is low, the amount of deformation of the track 20 is large, so the internal stress of the top surface 21 of the track is small. This is because the track 20 is more flexible between the sleepers and is more susceptible to local stress from the wheel 10. Therefore, the track stiffness information is an important factor in calculating the progress of fatigue damage. The material properties of the track base material also change depending on the above-mentioned environmental temperature, and the internal stress of the track 20 changes accordingly. For this reason, the environmental temperature information 381 may be used. The track stiffness information 391 can be obtained from a database.

Of the above, tangential force information 321, speed information 331, curvature information 361, and watering information 371 are considered to be information that has a very large effect on the degree of deterioration of the track 20. In addition, wheel flatness information 341, gradient information 351, environmental temperature information 381, and track stiffness information 391 are also considered to be information that has a certain degree of influence on the degree of deterioration of the track 20.

The tangential force information 321, the speed information 331, and the wheel flatness information 341 are information related to the input conditions under which the wheel 10 applies an impact force to the track 20 when the wheel 10 passes over the track 20. Therefore, this information corresponds to the impact force input conditions or the stress input conditions. The tangential force acquisition unit 320, the speed acquisition unit 330, and the wheel flatness acquisition unit 340 can be considered as an impact force input condition acquisition unit. In other words, the impact force input condition acquisition unit includes at least one of the tangential force acquisition unit 320, the speed acquisition unit 330, and the wheel flatness acquisition unit 340.

Furthermore, the gradient information 351, curvature information 361, watering presence/absence information 371, environmental temperature information 381, and track stiffness information 391 are conditions for calculating the stress generated when the wheel 10 passes over the track 20. Therefore, these pieces of information correspond to the stress calculation conditions. The gradient acquisition unit 350, curvature acquisition unit 360, watering presence/absence acquisition unit 370, environmental temperature acquisition unit 380, and track stiffness acquisition unit 390 can be considered as a stress calculation condition acquisition unit. In other words, the stress calculation condition acquisition unit includes at least one of the gradient acquisition unit 350, curvature acquisition unit 360, watering presence/absence acquisition unit 370, environmental temperature acquisition unit 380, and track stiffness acquisition unit 390.

Here, it is preferable that the output unit 200 includes both an impact force input condition acquisition unit and a stress calculation condition acquisition unit.

Figure 3 is a block diagram illustrating a deterioration detection device in a first embodiment of the present invention.

The deterioration of the track 20 progresses as multiple vehicles with multiple wheels 10 repeatedly pass over it. Therefore, the output unit 200 shown in FIG. 2 is provided individually for each of the wheel axles of the multiple wheels 10a, 10b, 10c, 10d, etc. of the vehicle 100. This makes it possible to integrate and output the deterioration progress of the multiple output units in accordance with the track position information, and to calculate the track deterioration progress with high accuracy. This configuration is shown in FIG. 3.

Figure 3 shows the overall configuration of the deterioration detection device 1. In the deterioration detection device 1, output units 200a, 200b, 200c... are provided individually corresponding to the wheels 10a, 10b, 10c.... Then, the track deterioration progress calculated by each track deterioration progress calculation unit 400a, 400b, 400c... of the output units 200a, 200b, 200c... is output to the output unit 401. The output unit 401 accumulates and outputs a track deterioration progress integrated value f(x) based on the track deterioration progress output for each wheel axle.

The deterioration detection device 1 is composed of an FPGA (Field-Programmable Gate Array), a personal computer, etc. The functions of the deterioration detection device 1 (acquisition unit, judgment unit, output unit, etc.) may be realized, for example, by an integrated circuit whose configuration can be set by a designer, by a CPU (Central Processing Unit) reading and executing a program from memory, by hardware such as a dedicated circuit, or by other methods. The deterioration detection device 1 may be installed at a specified train stop, or may be installed at a station or train depot instead of a train stop.

ただし、ｘは軌道の位置、Ｎは車輪軸の軸数、ｐ１は軸重情報３１１を数値化したものを示す。さらに、ｐｊ（ｊ≧２）は接線力情報３２１、速度情報３３１、車輪平たん情報３４１、勾配情報３５１、曲率情報３６１、散水有無情報３７１、環境温度情報３８１、軌道剛性情報３９１のうち少なくとも一つの情報を数値化したものを示す。また、ｈ１はｐ１に関する重み関数、ｈｊ（ｊ≧２）はｐｊに関する重み関数を示す。 The track deterioration progress integrated value f(x) is calculated by the following formula.

where x is the track position, N is the number of wheel axles, and p1 is a quantified value of the axle load information 311. Furthermore, pj (j≧2) is a quantified value of at least one of the tangential force information 321, the speed information 331, the wheel flatness information 341, the gradient information 351, the curvature information 361, the watering information 371, the environmental temperature information 381, and the track stiffness information 391. Furthermore, h1 is a weighting function related to p1, and hj (j≧2) is a weighting function related to pj.

gi is the degree of track deterioration calculated by the output unit 200 provided for each wheel axle, and is a function of p1(x)h1(x), p2(x)h2(x), ..., pj(x)hj(x). gi is not calculated when the vehicle is stopped (when the time change of the wheel position x is zero). This is because when the vehicle is stopped, damage to the track hardly progresses. N gi are set from g1 to gN corresponding to the number of axles N. The function gi can be an appropriate function. For example, the function gi may be a function obtained by multiplying the products of the values based on each information and the weighting function. In this case, the function is gi = p1(x)h1(x) x p2(x)h2(x) x ... x pj(x)hj(x).

The track position x is determined based on the resolution at which the track deterioration progress is monitored. For example, if monitoring is performed for every 25 m track unit length, x should have a resolution of 25 m. If the sampling and resolution of pj are fine, the resolution of x can be set to smaller increments.

The number of axles N is determined by the number of vehicles operating in the entire line area of the target track and the number of wheel axles of each vehicle. For example, if each vehicle has 4 wheel axles and there are 100 vehicles, then N = 400. Normally, multiple formations operate in the line area of the target track, and it is possible to take into account all of the vehicles in these multiple formations. When a vehicle is stopped at a depot or station and not in operation, the wheel position x remains in a fixed position, so gi is not accumulated as described above. Note that when a wheel has no driving force, the tangential force is considered to be zero, and other information is used to calculate the degree of track deterioration.

The weighting functions h1, h2, ..., hj may be changed depending on the type of vehicle, such as train, passenger car, locomotive, and freight car, and on the route. For example, different weighting functions h1, h2, ..., hj may be set for trains, passenger cars, locomotives, and freight cars, even on the same route. Also, different weighting functions h1, h2, ..., hj may be set for vehicles with the same configuration when the routes are different. Furthermore, the weighting functions h1 and hj may be adjusted appropriately in response to the state of fatigue damage of the track 20. In this way, by allowing freedom in the setting values of the weighting functions h1, h2, ..., hj, the track deterioration progress integrated value f(x) can be adjusted to match the actual deterioration state with high accuracy for various vehicles, routes, and operation patterns.

The determination unit 500 determines whether or not there is a track abnormality using f(x) calculated by the output unit 401. The determination unit 500 sets a threshold value using track base material strength information 501. The track base material strength information 501 is information about the strength of the track base material. For example, it is information such as yield stress, tensile strength, and S-N curve, and these are used as necessary. If f(x) exceeds the threshold value, a track abnormality signal 601 is output. The determination unit 500 also ranks the degree of deterioration according to the magnitude of f(x) and outputs it to the visualization unit 600. The visualization unit 600 can be applied as a display device that displays the degree of deterioration. Examples of display devices that can be used include a liquid crystal display (LCD), an organic electroluminescence (OEL) display, and a touch panel.

Figure 4 is a diagram showing an example of the flow of the judgment process of the deterioration detection device in the first embodiment of the present invention. Figure 4 shows the judgment flow in the judgment unit 500 in Figure 3.

The determination unit 500 determines two thresholds U1 and U2 (U1>U2) based on the track base material strength information 501 (S101). If it is determined that the f(x) calculated by the output unit 401 is greater than the threshold U1, it outputs f(x) to the visualization unit 600 as a degradation level of "high" (S102, S103). If it is determined that f(x) is equal to or less than the threshold U1, it compares the magnitude relationship between f(x) and the threshold U2 (S102, S105). Here, if f(x) is greater than the threshold U2, it outputs f(x) to the visualization unit 600 as a degradation level of "medium" (S105, S106). Also, if f(x) is equal to or less than the threshold U2, it outputs f(x) to the visualization unit 600 as a degradation level of "low" (S105, S108).

The visualization unit 600 performs a process of visualization on a map or chart according to the level of the deterioration level described above. If the deterioration level of f(x) is "high", the track deterioration level of point x is visualized as "high" (S104). If the deterioration level of f(x) is "medium", the track deterioration level of point x is visualized as "medium" (S107). If the deterioration level of f(x) is "low", the track deterioration level of point x is visualized as "low" (S109). If the deterioration level of f(x) is "high", a track abnormality signal 601 is output. This allows a warning to be issued to the user. In the above explanation, the thresholds are two, U1 and U2, but three or more thresholds may be used to divide the deterioration level into more detailed stages.

Figure 5 is a diagram illustrating a first example of the load applied to the track in the first embodiment of the present invention. Figure 6 is a diagram illustrating a second example of the load applied to the track in the first embodiment of the present invention. Figure 7 is a cross-sectional view of the track illustrating the load applied to the track in the first embodiment of the present invention.

A method for calculating the degree of track deterioration using tangential force information 321 will be explained using Figures 5 to 7. Wheel 10a will be used here as a representative example, but the same applies to the other wheels. In the following explanation, running resistance is not considered necessary. Because running resistance acts in the opposite direction to the vehicle's propulsive force, the force that contributes to the vehicle's propulsion is the tangential force minus running resistance, but running resistance is irrelevant to the transmission of tangential force from the wheels to the track. Note that axle load information can be obtained from axle load information 311, and tangential force information can be obtained from tangential force information 321.

In a track with no gradient as shown in FIG. 5, the axle load 30 acts perpendicularly to the top surface 21 of the track 20. The tangential force 40 is a force applied in the direction of travel along the top surface 21 of the track 20. Therefore, the axle load 30 and the tangential force 40 act at right angles, and a resultant force 50 of these is applied to the top surface 21 of the track 20 as a load from the wheels 10a. Therefore, the resultant force 50 is used in calculating the degree of track deterioration.

In a track 20 with an upward gradient θ as shown in FIG. 6, the axle load 31 acts as a surface inclined by θ with respect to the top surface 21 of the track 20. The tangential force 41 is a force applied in the direction of travel along the top surface 21 of the track 20. Therefore, the axle load 31 and the tangential force 41 form an angle of "90° + θ". Taking into account the gradient θ, a resultant force 51 of the axle load 31 and the tangential force 41 is applied to the track top surface 21 as a load from the wheels 10a. Therefore, the resultant force 51 is used in calculating the degree of track deterioration.

In a track 20 with a curve as shown in FIG. 7, a resultant force 52 of the axle load 32 and the lateral force 62 is applied to the track top surface 21 as a load from the wheels 10a. The lateral force 62 is a lateral force according to the curvature of the track 20. Therefore, the resultant force 52 that takes the curvature into account is used to calculate the degree of track deterioration. Note that in sections where gradient and curvature occur simultaneously, the combination of the resultant forces 51 and 52 is calculated.

Figure 8 is a diagram illustrating a first example of trajectory position calculation in the first embodiment of the present invention. Figure 9 is a diagram illustrating a second example of trajectory position calculation in the first embodiment of the present invention.

A method for accurately calculating the positions of multiple wheels is shown using FIG. 8. As shown in FIG. 8, the position x0a (=x0) of the front wheel 10a of the leading vehicle 100 at a stop position at a station or the like is used as a reference. The positions x0b, x0c, x0d, ... of the other wheels 10b, 10c, 10d, ... of the leading vehicle 100 are invariant with respect to the position x0a of the wheel 10a. Therefore, it is possible to accurately calculate these positions x0b, x0c, x0d, ... from the reference position x0. For example, even if the position of the wheel 10a of the leading vehicle moves from x0 to x1, the positions x0b, x0c, x0d, ... of the wheels 10b, 10c, 10d, ... can be calculated from the position x0a of the wheel 10a. Once the reference position x0 and the positions x0b, x0c, x0d, ... of the other wheels are determined based on the structural drawings of the vehicle, there is no need to change them during subsequent operation.

The same is true for multiple vehicles 100-1, 100-2, ... as shown in Figure 9. In this case, if the position x0a (=x0) of the wheel 10a of the leading vehicle 100-1 is used as the reference, the positions of the wheels 10e, 10f, 10g, and 10h of the next vehicle 100-2 can also be determined from the position x0a.

Figure 10 is a diagram showing a first example of the relationship between vehicle speed and running position in the first embodiment of the present invention. Figure 11 is a diagram showing a second example of the relationship between vehicle speed and running position in the first embodiment of the present invention.

The upper graph in Figure 10 shows the relationship between time and vehicle speed. The lower graph in Figure 10 shows the relationship between time and running position. If the change in vehicle speed over time is known, as in the upper graph in Figure 10, it is possible to calculate the change in running position over time, as in the lower graph in Figure 10, by integrating it. This method makes it possible to accurately obtain the wheel position x even when the GPS is not functioning. This makes it possible to calculate the track deterioration progress integrated value f(x) with high accuracy. Vehicle speed information can be obtained from speed information 331.

The upper graph in FIG. 11 shows the relationship between time and vehicle speed. The lower graph in FIG. 11 shows the relationship between time and running position for each axle. As shown in FIG. 11, the running positions of multiple wheels 10a, 10b, 10c, etc. can be obtained accurately from the relationship between time and vehicle speed. For example, the running position of wheel 10a can be calculated based on the position x0a of wheel 10a of the leading vehicle at a stop position at a station or the like. For the other wheels 10b, 10c, etc., the running positions can be calculated with high accuracy from the relationship between x0b, x0c, etc. based on position x0a (as explained in FIG. 8 and FIG. 9). In this way, by using the positions x0a, x0b, x0c, etc. corresponding to wheels 10a, 10b, 10c, etc., the track deterioration progress integrated value f(x) can be calculated more accurately.

Figure 12 is a diagram illustrating a first example of a current acquisition unit in the first embodiment of the present invention. Using Figure 12, we will explain a configuration for calculating tangential force information 321 and the like with higher accuracy using current data from the electric drive device 2 and the current measurement device 9.

As shown in FIG. 12, the electric drive system 2 of the vehicle 100 is mainly composed of a drive power source 5 consisting of a power conversion device such as an inverter, rotating machines 3 (3a, 3b, ..., 3n) that generate driving force, and mechanical devices 4 (4a, 4b, ..., 4n) consisting of gear boxes. AC power is supplied from the drive power source 5 to each of the rotating machines 3a, 3b, ..., 3n, which rotate the rotating machines 3a, 3b, ..., 3n. Driving force is transmitted from the rotating machines 3a, 3b, ..., 3n to each of the wheels 10 via the corresponding mechanical devices 4a, 4b, ..., 4n, thereby controlling the running of the vehicle 100. The drive power source 5 consisting of a power conversion device such as an inverter is electrically connected to the rotating machines 3 (3a, 3b, ..., 3n) by main wiring 11.

Figure 12 shows a 1CnM electric drive unit 2 that supplies power to n rotating machines 3a, 3b, ..., 3n from one drive power source 5. The electric drive unit 2 may be, for example, a 1C4M (four rotating machines for one drive power source) common in railway vehicles, a 1C2M (two rotating machines for one drive power source), or a 1C1M (one rotating machine for one drive power source), or any other combination of electric drive units.

The current measuring device 9 uses the current data supplied from the drive power source 5 to the rotating machine 3 to calculate the running position information 301, tangential force information 321, speed information 331, wheel flatness information 341, etc. A current sensor 6 is installed in the main wiring 11, and the current data obtained by the current sensor 6 is collected by a current acquisition unit 7 of the current measuring device 9. The current sensor 6 is installed at a point where the main wiring 11 does not branch, and measures this current value. The current measuring device 9 also includes a calculator 8. The calculator 8 uses the current data collected by the current acquisition unit 7 to calculate at least one of the running position information 301, tangential force information 321, speed information 331, and wheel flatness information 341.

The current measuring device 9 may be installed separately from the drive power source 5, or may be configured to be included as part of the drive power source 5. The traveling position information 301, tangential force information 321, speed information 331, and wheel flatness information 341 may be transmitted directly from the current measuring device 9 to the deterioration detection device 1 shown in FIG. 3 by wireless communication, or may be transmitted to the deterioration detection device 1 via a transmission means installed in the vehicle 100.

Here, the speed information 331 can be calculated from the fundamental frequency component of the current data. Also, the running position information 301 can be calculated by integrating the time change in speed obtained from the speed information 331. The data sampling period of the current measuring device 9 can be freely set in the range of several kHz to MHz. This makes it possible to obtain the speed information 331 and the running position information 301 with higher resolution by acquiring and calculating the current data.

The tangential force information 321 can be calculated from the magnitude of the current amplitude. When using information from the notch command of the vehicle cab, the magnitude of the tangential force actually generated by the wheels is unknown. In contrast, by using the current data, the magnitude of the tangential force can be determined with high accuracy from the magnitude of the current amplitude.

Furthermore, the wheel flatness information 341 can be calculated from the steep current changes contained in the current data. The information obtained from the detection system in the vehicle cab is related to the occurrence or non-occurrence of skidding and sliding, which are factors that cause wheel flatness, so the extent of the wheel flatness generated on the wheels is unknown. In contrast, by using the current data, the extent of the wheel flatness can be determined with high accuracy from the degree of current change.

The actual rotational speed of the wheels is reduced by the "slip" of the rotating machine 3 (induction machine) relative to the fundamental frequency component of the current. There is also a difference between the speed of the vehicle 100 and the rotational speed of the wheels 10 by the "slip rate (creep rate)". Therefore, there is a difference between the running position calculated using the speed information 331 obtained from the current data and the actual running position of the wheels by an amount equivalent to the above-mentioned "slip" or "slip rate". This difference can be corrected using the methods of Figures 14 and 15 described below.

The accuracy of the tangential force information 321 and the wheel flatness information 341 can be further improved by converting the current data collected in AC by the current sensor 6 into DC by the calculator 8 and using it as the d-axis current and the q-axis current. This utilizes the property that the torque of the rotating machine 3 is proportional to the q-axis current. By monitoring the q-axis current, the tangential force information 321 can be calculated without analyzing the amplitude of the AC current. Furthermore, by monitoring the q-axis current, the wheel flatness information 341 can be calculated from the amount of change in the q-axis current without analyzing the sudden change in the AC current. Furthermore, it is also possible to detect foreign objects on the track 20 from the amount of change in the q-axis current.

In addition, the accuracy can be further improved by using the d-axis current command deviation and the q-axis current command deviation, which are control software variables, in the calculator 8. Here, the d-axis current command deviation is, for example, one of the control software variables of the control circuit, and is the deviation between the d-axis current command, which is also a control software variable, and the d-axis current (actual measured value) of the rotating machine 3. The same is true for the q-axis current command deviation. Control software variables that indicate the deviation between a control command and a controlled object quantity, such as the d-axis current command deviation and the q-axis current command deviation, are zero in a normal state and increase when transitioning to a deteriorated state, and are therefore suitable as observation targets for deterioration detection.

With the configuration shown in FIG. 12, the running position information 301, tangential force information 321, speed information 331, and wheel flatness information 341 required for calculating the track deterioration progress integrated value f(x) can be obtained with high accuracy by using current data. In addition, the above four pieces of information can be obtained with only the current sensor 6. This eliminates the need to add other sensors, simplifies the sensor installation work, and significantly reduces the maintenance of the sensor itself. The current sensor 6 is installed in the main wiring 11 on the output side of the drive power source 5 as shown in FIG. 12, and current data for n rotating machines 3 can be collected collectively.

In the case of the configuration of FIG. 12, each piece of information, row position information 301, tangential force information 321, speed information 331, and wheel flatness information 341, is calculated as an average value of the rotating machines 3a, 3b, ..., 3n that use the current acquired by the current sensor 6. This information based on the average value is output to the corresponding output unit 200 as information of the corresponding wheel axle.

Figure 13 is a diagram illustrating a second example of the current acquisition unit in the first embodiment of the present invention.

Instead of the configuration of FIG. 12, the configuration shown in FIG. 13 may be used. Here, current sensors 6a, 6b, ..., 6n are installed on the main wiring 11a, 11b, ..., 11n on the branch side of the input side of the rotating machines 3a, 3b, ..., 3n, and current data of the rotating machines 3a, 3b, ..., 3n are collected individually. This makes it possible to collect information of the rotating machines 3a, 3b, ..., 3n individually. Therefore, it becomes possible to calculate the tangential force information 321, the speed information 331, and the wheel flatness information 341 for each wheel axle with higher accuracy. This information is output to the corresponding output unit 200 as information for each wheel axle.

According to the configurations shown in Figures 12 and 13, the track deterioration state can be visualized by calculating the track deterioration progress integrated value f(x) with high accuracy using the running position information 301, tangential force information 321, speed information 331, and wheel flatness information 341 calculated from the current data, as well as the load conditions and environmental conditions. This makes it possible to optimize the maintenance cycle based on the track deterioration state, thereby improving the efficiency of maintenance work and reducing the burden on workers.

Figure 14 shows an example of the distance between points in the first embodiment of the present invention. Figure 15 shows an example of the relationship between the actual distance and the estimated distance in the first embodiment of the present invention.

14 and 15, a method of correcting the difference between the travel position calculated using the speed information 331 obtained from the current data and the actual travel position of the wheels will be described. As shown in FIG. 14, a case where the points P0 and P1 are connected by a route R is taken as an example. In this case, as shown in FIG. 15, the actual distance between the points P0 and P1 is (x1-x0). On the other hand, the estimated distance calculated using the speed information 331 obtained from the current data is (y1-y0), which is larger than the actual distance (x1-x0) by Δx. This is because the estimated distance calculated using the speed information 331 obtained from the current data does not include the difference due to the "slip" of the rotating machine 3 (induction machine) or the "slip rate (creep rate)" between the speed of the vehicle 100 and the wheel 10. Therefore, in order to correct the difference between the actual distance (x1-x0) and the estimated distance (y1-y0), a correction coefficient C shown below is introduced.
C=(x1-x0)/(y1-y0)
8 and 9, x0 is based on the position of the wheels 10a of the leading vehicle at a stopping position at a station or the like, and the stopping position is based on data obtained from position information such as GPS. In this case, the estimated distance y0 is set to a value equal to x0.

By using the correction coefficient C, it is possible to obtain the actual distance x from the estimated distance y calculated from the current data as shown in the following equation.
x=C(y-y0)+x0

The track deterioration progress integrated value f(x) can be calculated using the estimated distance y as follows:
f(x)=f{C(y-y0)+x0}

x0 and x1 are updated sequentially based on data obtained from GPS or other location information when the train stops at a station, etc. This makes it possible to minimize errors in the running position x, and to calculate the track deterioration progress integrated value f(x) with high accuracy.

Figure 16 shows an example of a method for visualizing the degree of deterioration between locations in the first embodiment of the present invention.

The visualization unit 600 performs a process to visualize f(x) calculated as above according to the level of deterioration. Figure 16 shows an example of visualizing the degree of deterioration for each position on the route R. As an example, Figure 16 shows a case where the degree of deterioration is visualized for each point by corresponding to the color intensity of the circle. This type of visualization process makes the deterioration state of the track clear at a glance. Therefore, by prioritizing rail grinding in sections with a high degree of deterioration, it is possible to optimize the maintenance cycle, as well as to improve the efficiency of maintenance work and reduce the burden on workers.

Second Example
Fig. 17 is a diagram for explaining a first example of a deterioration detection system in a second embodiment of the present invention. Fig. 18 is a diagram for explaining a second example of a deterioration detection system in a second embodiment of the present invention. The second embodiment is a modification of the first embodiment. In explaining this embodiment, explanations of contents common to the first embodiment will be omitted.

As shown in Figs. 17 and 18, the deterioration detection system 900 is composed of a deterioration detection device 1 and a command transmission unit 700. A track abnormality signal 601 is output from the deterioration detection device 1 to the command transmission unit 700. The command transmission unit 700, which receives the track abnormality signal 601, transmits a command to each of the trains 100-1, 100-2, ..., 100-n to stop operation or to operate in a degenerate manner. At this time, in Fig. 17, the command transmission unit 700 transmits a command to each of the trains 100-1, 100-2, ..., 100-n via the traffic control system 800. Also, in Fig. 18, a command is transmitted directly from the command transmission unit 700 to each of the trains 100-1, 100-2, ..., 100-n. With this configuration, it is possible to appropriately control each of the trains based on the track abnormality signal 601.

The functions of the deterioration detection system 900 (such as the command unit) may be realized by the CPU reading and executing a program from memory, or may be realized by hardware such as a dedicated circuit, or may be realized by other methods. The deterioration detection system 900 is also communicatively connected to the traffic control system 800 that manages the operation of the railway, and transmits and receives various information such as the track abnormality signal 601.

The deterioration detection system 900 may be included in the traffic control system 800, or may be configured separately from the traffic control system 800 as shown in FIG. 17. In addition, for example, in order to realize safer vehicle operation, when the deterioration detection device 1 outputs a track abnormality signal 601 as shown in FIG. 18, a stop or degenerate operation command may be sent directly from the command transmission unit 700 to the vehicles 100-1, 100-2, ..., 100-n via the command transmission unit 700. In addition, the target vehicles to which the command in FIG. 18 is sent may be limited to vehicles close to the section where the track abnormality has occurred.

Here, a data center (data server, etc.) is constructed in the deterioration detection system 900, and the data center aggregates the recorded data of multiple vehicles. After the data is aggregated, data compression technology is applied. In this way, for example, by finding and compressing data related to deterioration detection that is common to several vehicles, the overall amount of data can be reduced compared to the case where data compression technology is applied to each vehicle. In addition to the recorded data, the data center may also aggregate output logs such as track abnormality signals. The data center may be constructed within a building or on a specific vehicle.

The deterioration detection device 1 also operates during specific times or locations. For example, the deterioration detection device 1 may operate only on the first train or the last train, or may operate only in locations where wear of the track 20 is likely to progress, such as on uphill sections or curves.

The deterioration detection device 1 may also target only specific vehicles.

(effect)
As described above, in the above embodiment, the deterioration degree of the track 20 can be calculated accurately. In particular, the deterioration degree of each wheel axle of the wheel 10 can be calculated more accurately by considering the deterioration degree of each wheel axle of the wheel 10. In addition, by using at least one of the tangential force information 321, the speed information 331, the wheel flatness information 341, the gradient information 351, the curvature information 361, the watering information 371, the environmental temperature information 381, and the track stiffness information 391 in addition to the running position information 301 and the axle load information 311, the deterioration degree can be calculated accurately. In particular, by using both the impact force input condition and the stress calculation condition described above, the deterioration degree can be calculated more accurately. In addition, by outputting the track abnormality signal 601 using a threshold based on the track base material strength information 501, the manager can be made aware of the abnormality of the track 20 as soon as possible.

The present invention is not limited to the above-described embodiments, but includes various modified examples. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those having all of the configurations described. It is also possible to replace part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

For example, in the above embodiment, the deterioration degree of the track 20 based on the wheel axles of all the wheels 10 has been described, but this is not limiting, and the deterioration degree based on the wheel axles of a number of representative wheels 10 may be calculated. In this case, for two or more trains including a vehicle 100 passing through the track 20, the deterioration degree can be calculated using information on one or more wheel axles for each train. In this case, the obtained value can be used as a representative value, and calculations can be performed to estimate the influence of the other wheel axles.

1...deterioration detection device, 2...electric drive device, 3...rotating machine, 4...mechanical device, 5...driving power supply, 6...current sensor, 7...current acquisition unit, 8...calculator, 9...current measurement device, 10...wheel, 11...main wiring, 20...track, 100...vehicle, 200...output unit, 310...axle load acquisition unit, 320...tangential force acquisition unit, 330...speed acquisition unit, 340...wheel flatness acquisition unit, 350...gradient acquisition unit, 360...curvature acquisition unit, 370...watering presence/absence acquisition unit, 380...ambient temperature acquisition unit, 390...track stiffness acquisition unit, 400...track deterioration progress calculation unit, 500...determination unit, 600...visualization unit, 601...output unit, 700...command transmission unit, 800...traffic management system, 900...deterioration detection system

Claims (15)

A deterioration detection system for detecting deterioration of a track on which a vehicle runs, comprising:
the system comprises a running position acquisition unit that acquires the running position of the vehicle, an axle load acquisition unit that acquires a weight applied vertically downward on a wheel axle that drives the vehicle, an impact force input condition acquisition unit that acquires information regarding conditions of an impact force on the track when the wheels of the vehicle pass over the track, a stress calculation condition acquisition unit that acquires information regarding stress calculation conditions for calculating stress generated when the wheels of the vehicle pass over the track, and a track deterioration progress calculation unit,
a track deterioration progress calculation unit that calculates and outputs a deterioration progress degree indicating a degree of deterioration of the track by using the weight information acquired by the axle load acquisition unit, the information acquired by the impact force input condition acquisition unit, and the information acquired by the stress calculation condition acquisition unit in association with the position information acquired by the traveling position acquisition unit;
A deterioration detection system characterized in that the degree of deterioration is calculated using information for one or more wheel axles of each of two or more trains including vehicles passing through the track. 2. The deterioration detection system according to claim 1,
The deterioration detection system, characterized in that the impact force input condition acquisition unit includes at least one of a tangential force acquisition unit that acquires a tangential force transmitted from the wheel to the track, a speed acquisition unit that acquires the rotational speed of the wheel axle, and a wheel flatness acquisition unit that acquires the size of a flat portion on the wheel tread of the vehicle. 3. The deterioration detection system according to claim 1,
The stress calculation condition acquisition unit includes at least one of a gradient acquisition unit that acquires the gradient of the track, a curvature acquisition unit that acquires the curvature of the track, a watering presence/absence acquisition unit that acquires the presence or absence of watering on the top surface of the track, an environmental temperature acquisition unit that acquires information on the environmental temperature at the running position of the vehicle, and a track stiffness acquisition unit that acquires information including material property values of the track. The deterioration detection system according to any one of claims 1 to 3,
a determination unit that determines whether the degree of deterioration is greater than a threshold value, and when it is determined that the degree of deterioration is greater than the threshold value, the determination unit outputs a track abnormality signal indicating that there is an abnormality in the track. 3. The deterioration detection system according to claim 2,
The deterioration detection system is characterized in that the vehicle is driven by electric energy generated by an electric drive unit, and is equipped with a current acquisition unit that acquires current data generated by the electric drive unit, and at least one of the information acquired by the driving position acquisition unit, the information acquired by the tangential force acquisition unit, the information acquired by the speed acquisition unit, and the information acquired by the wheel flatness acquisition unit is calculated based on the current data acquired by the current acquisition unit. 6. The deterioration detection system according to claim 5,
A deterioration detection system characterized in that the electric drive device is composed of one power conversion device and a plurality of rotating machines, and the current acquisition unit is configured to acquire the current of each of the plurality of rotating machines. 5. The deterioration detection system according to claim 4,
a command unit that issues a command to the vehicle, wherein the command unit issues a command to the vehicle to stop operation or to operate in a degraded manner on the track related to the track abnormality signal, based on the track abnormality signal transmitted from the determination unit. A deterioration detection method for detecting deterioration of a track on which a vehicle runs, comprising:
the method includes a running position acquisition step for acquiring a running position of the vehicle, an axle load acquisition step for acquiring a weight applied vertically downward on an axle which drives the vehicle, an impact force input condition acquisition step for acquiring information regarding input conditions for an impact force to the track when the wheels of the vehicle pass over the track, a stress calculation condition acquisition step for acquiring information regarding stress calculation conditions for calculating stress generated when the wheels of the vehicle pass over the track, and a track deterioration progress calculation step,
the track deterioration progress calculation step calculates and outputs a deterioration progress degree indicating a degree of deterioration of the track by using the weight information acquired in the axle load acquisition step, the information acquired in the impact force input condition acquisition step, and the information acquired in the stress calculation condition acquisition step in association with the position information acquired in the traveling position acquisition step;
A deterioration detection method characterized in that the deterioration progress degree is calculated using information for one or more wheel axles of each of two or more trains including vehicles passing through the track. 9. The deterioration detection method according to claim 8,
A deterioration detection method characterized in that the impact force input condition acquisition step includes at least one of a tangential force acquisition step of acquiring a tangential force transmitted from the wheel to the track, a speed acquisition step of acquiring a rotational speed of the wheel axle, and a wheel flatness acquisition step of acquiring the size of a flat portion on the wheel tread of the vehicle. The deterioration detection method according to claim 8 or 9,
The deterioration detection method, wherein the stress calculation condition acquisition step includes at least one of a gradient acquisition step of acquiring a gradient of the track, a curvature acquisition step of acquiring a curvature of the track, a watering presence acquisition step of acquiring the presence or absence of watering on the top surface of the track, an environmental temperature acquisition step of acquiring information on the environmental temperature at the running position of the vehicle, and a track stiffness acquisition step of acquiring information including material property values of the track. The deterioration detection method according to any one of claims 8 to 10,
A deterioration detection method comprising a determination step of determining whether the degree of deterioration is greater than a threshold value, wherein the determination step outputs a track abnormality signal indicating that there is an abnormality in the track when it is determined that the degree of deterioration is greater than the threshold value. 10. The deterioration detection method according to claim 9,
A deterioration detection method comprising: a current acquisition step of acquiring current data generated by an electric drive unit that drives the vehicle; and at least one of the information acquired in the driving position acquisition step, the information acquired in the tangential force acquisition step, the information acquired in the speed acquisition step, and the information acquired in the wheel flatness acquisition step is calculated based on the current data acquired in the current acquisition step. The deterioration detection method according to claim 12,
The deterioration detection method, wherein the current acquisition step acquires currents of each of a plurality of rotating machines included in the electric drive device. The deterioration detection method according to claim 11,
a step of issuing a command to the vehicle to stop or reduce operation on the track related to the track abnormality signal, based on the track abnormality signal transmitted in the determination step. A deterioration detection device that detects deterioration of a track on which a vehicle runs, comprising:
Acquire position information of the running position of the vehicle, axle load information of the weight acting vertically downward on the wheel axle that drives the vehicle, information on input conditions of impact force to the track when the wheels of the vehicle pass through the track, and information on stress calculation conditions for calculating stress generated when the wheels of the vehicle pass through the track,
calculating and outputting a deterioration progress degree indicating a progress degree of deterioration of the track by using the axle load information, information on the input conditions of the impact force, and information on the stress calculation conditions in correspondence with the position information of the traveling position;
A deterioration detection system characterized in that the degree of deterioration is calculated using information for one or more wheel axles of each of two or more trains including vehicles passing through the track.

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