JP7575350B2 - Bearing diagnostic device and bearing diagnostic method - Google Patents

Description

The present invention relates to a bearing diagnostic device and a bearing diagnostic method.

There is a known technology for diagnosing the condition of a bearing that supports a rotating shaft of a drive unit that drives equipment. For example, Patent Document 1 discloses a bearing information analysis device that includes a magnetic sensor that detects magnetism generated from components of a bearing, a vibration sensor that detects vibrations generated in the bearing, a signal collection unit that collects magnetic signals detected by the magnetic sensor and vibration signals detected by the vibration sensor at the same timing from the bearing, a signal processing unit that calculates a theoretical natural frequency that is a theoretical natural frequency of the bearing based on the specification values of the bearing and calculates a detected natural frequency that is a natural frequency based on the detection results of the bearing from the signals collected by the signal collection unit, and a display unit that displays the information calculated by the signal processing unit (claim 1).

JP 2020-143934 A

The technology described in Patent Document 1 assumes that an analysis device is temporarily installed on a bearing when inspecting equipment, etc. Therefore, it is not possible to grasp trends related to the continuous behavior of the bearing over a certain number of days. Even if the analysis device of Patent Document 1 is continuously installed on the bearing, it is difficult to accurately analyze the state of the bearing because the influence of noise generated other than the bearing becomes large during normal operation of the equipment.
An object of the present invention is to provide a bearing diagnostic device and a bearing diagnostic method that can continuously and accurately diagnose the condition of a bearing.

In order to solve the above problems, the present invention provides a bearing diagnostic device that has a magnetic sensor and a vibration sensor and diagnoses the condition of a bearing that supports a rotating shaft of a drive unit that performs cyclic operation of equipment. The device includes a bearing rotation period calculation unit that calculates the rotation period of the bearing using a magnetic signal detected by the magnetic sensor, a natural frequency calculation unit that calculates the natural frequency of the bearing using the magnetic signal detected by the magnetic sensor, a diagnosis unit that diagnoses the condition of the bearing based on the natural frequency of the bearing, an equipment vibration period calculation unit that calculates an equipment vibration period, which is the period of vibration that is repeatedly generated from the equipment other than the bearing due to the cyclic operation, based on the rotation period of the bearing, a vibration level determination unit that determines whether the vibration signals detected by the vibration sensor, excluding the vibration signal corresponding to the equipment vibration period, are equal to or lower than a predetermined vibration level, and a scheduling unit that changes the time period detected by the magnetic sensor when the predetermined vibration level is exceeded.

The present invention provides a bearing diagnostic device and a bearing diagnostic method that can continuously and accurately diagnose the condition of a bearing. Problems, configurations, and effects other than those described above will become clear from the description of the embodiment of the invention below.

1 is a schematic configuration diagram of an escalator according to an embodiment of the present invention. FIG. 1 is a functional block diagram showing a configuration of a bearing diagnosis device according to a first embodiment; 4 is a flowchart for explaining a bearing diagnosis method. This is an example of a peak diagram obtained by performing a fast Fourier transform on the magnetic signal detected by the magnetic sensor when the bearing condition is normal, with the horizontal axis representing frequency and the vertical axis representing signal intensity. 4 is a flowchart illustrating a method for diagnosing trends in a bearing condition. FIG. 11 is a functional block diagram showing a configuration of a passenger conveyor diagnostic system according to a second embodiment.

The following describes embodiments of the present invention with reference to the drawings. The examples are illustrative for explaining the present invention, and some parts have been omitted or simplified as appropriate for clarity of explanation. The present invention can also be implemented in various other forms. Unless otherwise specified, each component may be singular or plural.

When there are multiple components with the same or similar functions, they may be described using the same reference numerals with different subscripts. Also, when there is no need to distinguish between these multiple components, the subscripts may be omitted.

In the embodiments, the processing performed by executing a program may be described. Here, the computer executes the program using a processor (e.g., CPU, GPU), and performs the processing defined by the program using storage resources (e.g., memory) and interface devices (e.g., communication ports). Therefore, the subject of the processing performed by executing the program may be the processor. Similarly, the subject of the processing performed by executing the program may be a controller, device, system, computer, or node having a processor. The subject of the processing performed by executing the program may be a calculation unit, and may include a dedicated circuit that performs specific processing. Here, the dedicated circuit is, for example, an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), or a CPLD (Complex Programmable Logic Device).

The program may be installed on the computer from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is a program distribution server, the program distribution server may include a processor and a storage resource that stores the program to be distributed, and the processor of the program distribution server may distribute the program to be distributed to other computers. In addition, in the embodiments, two or more programs may be realized as one program, and one program may be realized as two or more programs.

In an embodiment of the present invention, the natural frequency of components of equipment in operation is calculated, and the trends in the condition of bearings are diagnosed by capturing changes over time. In this embodiment, an escalator is used as an example of equipment. Other than escalators, other passenger conveyors such as moving walkways may be used, and other equipment may be used as long as it is equipment that is operated in a circulating manner by a drive unit.

First, an escalator in which the bearing diagnosis device according to this embodiment is installed will be described. FIG. 1 is a schematic diagram of an escalator 1 according to this embodiment. As shown in FIG. 1, the escalator 1 according to this embodiment includes a frame 2 installed in an architectural structure (not shown), a control panel 3, a balustrade 4, steps 5, a rail 13, a handrail 6, a drive mechanism 7, a transmission chain 8, a step chain 9, a handrail drive device 10, a drive sprocket 11, and a driven sprocket 12.

The control panel 3, drive mechanism 7 and drive sprocket 11 are arranged on the upper floor side of the frame body 2, and the driven sprocket 12 is arranged on the lower floor side.

The drive mechanism 7 is composed of an electric motor and a reduction gear. Power is supplied to the electric motor from the control panel 3, and the operation of the electric motor is controlled by the control panel 3. A belt member 14 is wrapped around the electric motor and the reduction gear, and the rotational force of the electric motor is transmitted to the reduction gear via the belt member 14.

Furthermore, a transmission chain 8 is wound around the reducer and the drive sprocket 11, and the driving force of the drive mechanism 7 is transmitted to the drive sprocket 11 via the transmission chain 8, causing the drive sprocket 11 to rotate.

A pair of step chains 9 are wound around the drive sprocket 11 and the driven sprocket 12, and as the drive sprocket 11 rotates, the driven sprocket 12 and the step chain 9 rotate.

A handrail drive chain 15 is wound around the drive sprocket 11. The handrail drive chain 15 is wound around multiple transmission pulleys 16 and also around the handrail drive device 10.

A pair of rails 13 are arranged in the width direction of the frame body 2, and the steps 5 are supported movably on the pair of rails 13. The steps 5 are connected endlessly via a pair of step chains 9, and are guided by the rails 13 to move between the outbound and inbound sides, circulating between the boarding and alighting entrances.

The balustrade 4 is supported on the top of the frame 2 and is arranged on both sides of the frame 2 in the width direction. An endless handrail 6 is attached to the balustrade 4. The handrail 6 is supported movably on the balustrade 4 and moves in a circular motion in the same direction as the multiple steps 5 in sync with them by the handrail drive device 10. This allows the escalator 1 to safely transport passengers standing on the steps 5 and holding onto the handrail 6.

In addition, both ends of the rotating shaft of the driving sprocket 11 and the driven sprocket 12, which are the driving parts, are supported by bearings (not shown). The bearings are fixed by a housing (not shown).

Now, the structure of the bearing will be explained. Figure 2 is a cross-sectional view showing the structure of a rolling bearing. As shown in Figure 2, the bearing comprises an outer ring 17 fixed to a housing, ball-shaped rolling elements 18, a cage 19 that holds the rolling elements 18 rotatably, and an inner ring 20 that is disposed inside the cage 19 and comes into point contact with the rolling elements 18. The rotating shaft of the driving sprocket 11 or driven sprocket 12 is inserted inside the inner ring 20, and the rotating shaft and the inner ring 20 are fixed. Therefore, when the rotating shaft rotates, the components of the bearing, the inner ring 20, the rolling elements 18, and the cage 19, also rotate.

Below, we will explain the bearing diagnosis device for diagnosing the condition of bearings based on each embodiment.

In Example 1, it is assumed that an operator will transport and install the bearing diagnosis device 30 to the escalator to be diagnosed as necessary, continue diagnosis by the bearing diagnosis device 30 for a certain period of time, and check the diagnosis results on-site at the time of the next inspection. FIG. 3 is a functional block diagram showing the configuration of the bearing diagnosis device according to Example 1. As shown in FIG. 3, the bearing diagnosis device 30 according to Example 1 has a sensor module 31 and a control module 32, and the sensor module 31 and the control module 32 are connected by a cable so as to be able to communicate with each other.

The sensor module 31 is attached to a housing to which the bearing is fixed, and includes a magnetic sensor 311, a vibration sensor 312, an amplifier filter unit 313, and an ADC (Analog-to-Digital Converter) 314. The output signal of the magnetic sensor 311 is processed by the amplifier filter unit 313 and then digitized by the ADC 314, and the converted magnetic signal is output to the control module 32 via a cable. On the other hand, the output signal of the vibration sensor 312 is processed by the amplifier filter unit 313 and then digitized by the ADC 314, and the converted vibration signal is output to the control module 32 via a cable. The vibration sensor 312 may be any sensor that can detect a vibration signal caused by the rotation of the bearing or a vibration signal mixed in from another power system, and may include, for example, a piezoelectric element, an acceleration sensor, an acoustic microphone, etc.

The control module 32 includes a natural frequency calculation unit 321, a bearing rotation period calculation unit 322, a diagnosis unit 323, an equipment vibration period calculation unit 324, a vibration level determination unit 325, a scheduling unit 326, a memory unit 327, and an output unit 328. The natural frequency calculation unit 321 calculates the natural frequency of the bearing (such as the inner ring 20) using the magnetic signal detected by the magnetic sensor 311. The bearing rotation period calculation unit 322 calculates the rotation period of the bearing using the magnetic signal detected by the magnetic sensor 311. The diagnosis unit 323 diagnoses the state of the bearing based on the natural frequency of the bearing. The equipment vibration period calculation unit 324 calculates the equipment vibration period, which is the period of normal vibrations that are repeatedly generated from parts of the escalator 1 other than the bearings due to the circulation operation of the steps 5, etc., based on the natural frequency of the inner ring 20. The vibration level determination unit 325 determines whether the vibration signals detected by the vibration sensor 312, excluding the vibration signal corresponding to the equipment vibration period, are equal to or lower than a predetermined vibration level. The scheduling unit 326 changes the time period detected by the sensor module 31 when the predetermined vibration level is exceeded. The output unit 328 outputs the diagnosis result by the diagnosis unit 323, etc. The memory unit 327 stores the diagnosis result by the diagnosis unit 323, as well as the model number information of the escalator 1 to be diagnosed and information regarding the specification values of the bearings linked to the model number information. In addition, the natural frequency calculation unit 321 calculates the theoretical natural frequency, which is the theoretical natural frequency of each component of the bearing (the inner ring 20, the rolling element 18, and the cage 19) based on the specification values stored in the memory unit 327 as a pre-processing of the bearing diagnosis, and stores it in the memory unit 327.

Next, we will explain the diagnosis method using the bearing diagnosis device 30 according to this embodiment. Figure 4 is a flowchart for explaining the bearing diagnosis method.

When a pre-specified time period arrives, the magnetic sensor 311 and the vibration sensor 312 of the sensor module 31 detect a magnetic signal and a vibration signal and output them to the control module 32 (step S101).

Next, the natural frequency calculation unit 321 performs fast Fourier transform calculation processing on the magnetic signal detected by the magnetic sensor 311 to obtain the frequency characteristics of the magnetic signal (step S102). Furthermore, the natural frequency calculation unit 321 analyzes this frequency characteristic to identify the natural frequency of the bearing, specifically, the natural frequency of the inner ring 20, the rolling elements 18, and the cage 19 (step S103). Also, in step S103, the bearing rotation period calculation unit 322 calculates the rotation period of the bearing (inner ring 20) from the analysis result of the frequency characteristics.

Figure 5 is an example of a peak diagram in which the magnetic signal detected by the magnetic sensor 311 is subjected to a fast Fourier transform when the bearing is in a normal state, with the horizontal axis representing frequency and the vertical axis representing signal strength. As shown in Figure 5, it can be seen that the inner ring 20, rolling elements 18, and cage 19 of the bearing in a normal state each rotate at a fixed natural frequency (0.4 Hz and 0.8 Hz for the inner ring, 1.7 Hz for the rolling elements, and 0.17 Hz for the cage). Note that in the example of Figure 5, there are two peak values corresponding to the inner ring, with a fundamental wave of 0.4 Hz and a second harmonic component of 0.8 Hz.

Next, the diagnosis unit 323 compares the detected natural frequency detected in step S103 with the theoretical natural frequency calculated in pre-processing (step S104).

If the two natural frequencies do not match, for example, if the difference between the detected natural frequency and the theoretical natural frequency is equal to or greater than a predetermined threshold, the diagnostic unit 323 diagnoses that the bearing condition is not normal, and registers the detected magnetic signal and detected natural frequency together with the detection time in the memory unit 327 as diagnostic target data (step S105). The diagnostic target data registered in the memory unit 327 is used for trend diagnosis. Note that multiple thresholds may be set, and for example, if the frequency is equal to or greater than a high threshold, it may be diagnosed as a serious malfunction that requires emergency action, and if the frequency is equal to or greater than a low threshold but not equal to the high threshold, it may be diagnosed as an early stage of malfunction that requires progress monitoring. In addition, it is also possible to identify which part of the bearing has an abnormality depending on which of the inner ring 20, rolling element 18, and cage 19 has a natural frequency equal to or greater than the threshold.

Here, in addition to vibrations caused by the bearings, the vibration sensor 312 also detects periodic vibrations that occur repeatedly from parts of the escalator 1 other than the bearings as the escalator 1 operates in a circulating manner, and vibrations from the external environment, including passengers getting on and off. In particular, since vibrations from the external environment become noise when the diagnosis unit 323 diagnoses the condition of the bearings, it is desirable to use sensor data when the vibration level of the external environment is low for diagnosis. For this reason, in this embodiment, when determining the vibration level of the external environment, first, the vibrations that are periodically generated by the escalator 1 itself are removed (separated) from the vibration signal detected by the vibration sensor 312.

First, the method by which the equipment vibration period calculation unit 324 calculates the period of vibration (equipment vibration period) that occurs with the circulating operation of the escalator 1 (equipment) will be described. The rotating shaft of the sprocket of the escalator 1 basically rotates integrally with the inner ring 20 of the bearing. Therefore, the equipment vibration period calculation unit 324 uniquely determines the operating speed of the escalator 1 from the rotation period of the inner ring 20 identified in step S103. Once the operating speed of the escalator 1 is determined, the equipment vibration period calculation unit 324 calculates the timing (interval) of the vibrations that are periodically generated by the escalator 1 (mainly the vibrations caused by the steps colliding with the rail 13 when reversing between the forward and backward directions) (step S106).

Next, the vibration level determination unit 325 removes the vibration signal detected by the vibration sensor 312 at a timing corresponding to the equipment vibration period (step S107).

Then, the vibration level determination unit 325 uses the vibration signal data obtained in step S107 to determine whether or not the vibration level is below a predetermined level (step S108). For example, when there are few passengers and the load on the escalator 1 is light, the vibration level is below the predetermined level.

If the vibration level is below a predetermined level, the detected magnetic signal and the detected natural frequency are registered in the memory unit 327 as diagnostic target data together with the detection time (step S109). The diagnostic target data registered in the memory unit 327 is used for trend diagnosis.

On the other hand, if the vibration level exceeds the predetermined level, the scheduling unit 326 changes the time period during which the sensor module performs detection from the next day onward (step S110). One possible method for changing the time period is to shift it one hour later than the current time period.

Figure 6 is a flow chart explaining a method for diagnosing the trend of the bearing condition. As shown in Figure 6, in trend diagnosis in this embodiment, first, the diagnosis unit 323 extracts diagnosis target data for the same time period from the storage unit 327 (step S201). Next, the diagnosis unit 323 calculates the difference between the detected natural frequency and the theoretical natural frequency (step S202). Here, the diagnosis unit 323 determines whether or not there are consecutive days on which the difference is equal to or greater than a predetermined threshold (step S203). If there are not consecutive days, the diagnosis result is displayed by the output unit (step S204). On the other hand, if there are consecutive days, an abnormality diagnosis is performed (step S205), and then the diagnosis result is displayed by the output unit 328 (step S204).

In this way, according to this embodiment, since the sensor module 31 performs detection only during times when the vibration level is below a predetermined level and the influence of external noise is small, continuous, high-quality data can be obtained over a certain number of days even in a limited power supply environment. In addition, by capturing the time-series changes in the detected natural frequency of the bearing, it is possible to perform diagnosis based on long-term trends, such as when the bearing temporarily falls outside the normal range (the difference between the detected natural frequency and the theoretical natural frequency is less than a predetermined threshold) but then returns to the normal range. Furthermore, in this embodiment, even without obtaining the operation schedule of the escalator 1, it is possible to automatically avoid times when the influence of external noise is large, and to achieve highly accurate diagnosis using data from times when there are few passengers.

In the second embodiment, a bearing diagnostic device (mainly a sensor module 31) is installed on a passenger conveyor to be diagnosed (e.g., an escalator), and then a monitoring server 51 connected to and communicating with the bearing diagnostic device is used to perform continuous diagnosis for a certain period of time, with the results being confirmed at a monitoring center. FIG. 7 is a functional block diagram showing the configuration of a passenger conveyor diagnostic system according to the second embodiment. As shown in FIG. 7, the passenger conveyor diagnostic system according to the second embodiment includes a passenger conveyor 41 and a monitoring server 51 used by a monitoring center or the like, which is a base for remotely monitoring the state of the passenger conveyor. The monitoring server 51 may be used by a management office of a facility such as a building in which the passenger conveyor 41 is installed.

As described above, the passenger conveyor 41 has the steps 5 that move cyclically between the boarding and alighting entrances, the endless step chain 9 connected to the steps 5, a drive unit that drives the step chain 9, a bearing that supports the rotating shaft of the drive unit, a sensor module 31, and a control module 32. The sensor module 31, like in the first embodiment, is composed of a magnetic sensor 311, a vibration sensor 312, etc., but unlike in the first embodiment, the control module 32 is composed of a communication unit 43 for connecting to the monitoring server 51 via a communication line.

The monitoring server 51 has a communication unit 329 for connecting to the passenger conveyor 41 via a communication line, and like the control module 32 of the first embodiment, has a natural frequency calculation unit 321, a bearing rotation period calculation unit 322, a diagnosis unit 323, an equipment vibration period calculation unit 324, a vibration level determination unit 325, a scheduling unit 326, an output unit 328, and a memory unit 327.

According to this embodiment, signals from the magnetic sensor 311 and vibration sensor 312 installed on the passenger conveyor 41 are sent to the monitoring server 51, which can diagnose the bearings and confirm the results. This makes it easier to plan the implementation of maintenance, including the timing of the next inspection, and prevents unnecessary visits to the installation site of the passenger conveyor 41. Note that some of the functions of the monitoring server 51 may be installed in the control module 32.

In Example 3, it is assumed that the bearing diagnosis device is pre-installed on the passenger conveyor to be diagnosed. The passenger conveyor may be permanently equipped with the bearing diagnosis device 30 according to Example 1, or may be permanently equipped with mainly the sensor module 31 as in Example 2. In the former case, the output unit 328 of the control module 32 of the bearing diagnosis device 30 allows a worker to check the diagnosis results at the installation site of the passenger conveyor. In the latter case, the monitoring server 51 connected to and communicating with the communication unit 329 of the control module 32 allows a monitor to check the diagnosis results at the monitoring center. In either case, there is an advantage in that it is not necessary to attach or remove the sensor module 31 from the passenger conveyor.

The present invention is not limited to the above-mentioned embodiments, and various modifications are possible. The above-mentioned embodiments are provided as examples to explain the present invention in an easy-to-understand manner, 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.

1... Escalator, 2... Frame, 3... Control panel, 4... Parapet, 5... Step, 6... Handrail, 7... Drive mechanism, 8... Transmission chain, 9... Step chain, 10... Handrail drive device, 11 Drive sprocket, 12... Driven sprocket, 13... Rail, 14... Belt member, 15... Handrail drive chain, 16... Transmission pulley, 17... Outer ring, 18... Rolling body, 19... Cage, 20... Inner ring, 30... Bearing diagnostic device, 31... Sensor module, 31 1...magnetic sensor, 312...vibration sensor, 313...amplifier filter section, 314...ADC, 32...control module, 321 natural frequency calculation section, 322...bearing rotation period calculation section, 323...diagnosis section, 324...equipment vibration period calculation section, 325...vibration level determination section, 326...scheduling section, 327...storage section, 328...output section, 41...passenger conveyor, 42...drive section, 43...communication section, 329...communication section, 51...monitoring server

Claims (6)

A bearing diagnostic device that has a magnetic sensor and a vibration sensor and diagnoses the condition of a bearing that supports a rotating shaft of a drive unit that performs circulating operation of equipment,
a bearing rotation period calculation unit that calculates a rotation period of the bearing using a magnetic signal detected by the magnetic sensor;
a natural frequency calculation unit that calculates a natural frequency of the bearing using a magnetic signal detected by the magnetic sensor;
a diagnosis unit that diagnoses a state of the bearing based on a natural frequency of the bearing;
an equipment vibration period calculation unit that calculates an equipment vibration period, which is a period of vibration repeatedly generated from the equipment other than the bearing during the circulation operation, based on the rotation period of the bearing;
a vibration level determination unit that determines whether or not the vibration signals detected by the vibration sensor, excluding the vibration signal corresponding to the equipment vibration period, are equal to or lower than a predetermined vibration level;
a scheduling unit that changes a time period during which the magnetic sensor detects the vibration when the predetermined vibration level is exceeded;
A bearing diagnostic device comprising: 2. The bearing diagnostic device according to claim 1,
The bearing includes an inner ring, a rolling element, a cage that holds the rolling element, and an outer ring,
the natural frequency calculation unit calculates a theoretical natural frequency, which is a theoretical natural frequency of at least one of the inner ring, the rolling elements, and the cage, using a specification value of the bearing;
The diagnosing unit is a bearing diagnosing device that diagnoses a condition of the bearing by comparing a detected natural frequency calculated using a magnetic signal detected by the magnetic sensor with the theoretical natural frequency. 3. The bearing diagnostic device according to claim 2,
the magnetic sensor and the vibration sensor detect the magnetic signal and the vibration signal during the same time period over a certain number of days,
The diagnosis unit is a bearing diagnosis device that determines whether there are consecutive days in which the difference between the detected natural frequency and the theoretical natural frequency is equal to or greater than a predetermined threshold value. A step that circulates between the boarding and alighting gates,
An endless chain connected to the steps;
A drive unit that drives the chain;
a bearing diagnostic device according to claim 1 for diagnosing a condition of a bearing supporting a rotating shaft of the drive unit;
A passenger conveyor comprising: A passenger conveyor diagnostic system including: a passenger conveyor; and a monitoring server connected to the passenger conveyor via a communication line to diagnose the passenger conveyor,
The passenger conveyor includes:
A step that circulates between the boarding and alighting gates,
An endless chain connected to the steps;
A drive unit that drives the chain;
A bearing for supporting a rotation shaft of the drive unit;
A magnetic sensor;
A vibration sensor;
having
The monitoring server includes:
a bearing rotation period calculation unit that calculates a rotation period of the bearing using a magnetic signal detected by the magnetic sensor;
a natural frequency calculation unit that calculates a natural frequency of the bearing using a magnetic signal detected by the magnetic sensor;
a diagnosis unit that diagnoses a state of the bearing based on a natural frequency of the bearing;
an equipment vibration period calculation unit that calculates an equipment vibration period, which is a period of vibration repeatedly generated from the passenger conveyor other than the bearing in association with the cyclic movement of the steps, based on the rotation period of the bearing;
a vibration level determination unit that determines whether or not the vibration signals detected by the vibration sensor, excluding the vibration signal corresponding to the equipment vibration period, are equal to or lower than a predetermined vibration level;
a scheduling unit that changes a time period during which the magnetic sensor detects the vibration when the predetermined vibration level is exceeded;
A passenger conveyor diagnostic system having A bearing diagnosis method for diagnosing a condition of a bearing that supports a rotating shaft of a drive unit that performs circulating operation of equipment, comprising:
calculating a rotation period and a natural frequency of the bearing using a magnetic signal detected by the magnetic sensor;
a diagnosis step of diagnosing a condition of the bearing based on a natural frequency of the bearing;
calculating an equipment vibration period, which is a period of vibration repeatedly generated from the equipment other than the bearing during the circulation operation, based on the rotation period of the bearing;
A step of determining whether or not the vibration signals detected by the vibration sensor, excluding the vibration signal corresponding to the equipment vibration period, are equal to or lower than a predetermined vibration level.
changing a time period during which the magnetic sensor detects the vibration when the predetermined vibration level is exceeded;
A bearing diagnostic method comprising:

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