CN114802354B - Intrusion detection system, method and early warning system for track construction section - Google Patents
Intrusion detection system, method and early warning system for track construction section Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/06—Control, warning or like safety means along the route or between vehicles or trains for warning men working on the route
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/22—Control, warning or like safety means along the route or between vehicles or trains for controlling traffic in two directions over the same pair of rails
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Abstract
The invention relates to an intrusion detection system, an intrusion detection method and an early warning system for a track construction section, wherein the intrusion detection system comprises: a detection device which is arranged at the end of the track construction section and is used for detecting whether an invader entering the track construction section exists or not; and a signal processing module coupled to the detection device and configured to, in response to the detection device detecting an intrusion, perform feature extraction on a detected data point associated with the intrusion to determine whether the intrusion is a train. According to the intrusion detection system provided by the embodiment of the invention, the real-time detection of the train entering the track construction section through the end part can be realized, so that the early warning can be carried out on the staff in the track construction section, and the safety and the automatic management of the track construction section are ensured.
Description
Technical Field
The present invention relates generally to the field of Shi Gongyun-dimensional security technology. More particularly, the invention relates to an intrusion detection system, an intrusion detection method and an early warning system for a track construction section.
Background
Along with the continuous increase of the passenger and cargo traffic of the railways in China, the workload of railway construction, rail laying and electrified installation is increased. Besides the construction of the railway track in the railway construction period, the maintenance and the maintenance of the railway track and the supporting facilities are required in the operation windowing period (or the emptying window period, namely the time period when the train is in a suspension operation) so as to ensure the operation safety of the train. In the construction process, as constructors, tools and engineering vehicles are in cross operation, great difficulty is brought to the safety management of construction. Therefore, how to improve the construction safety management measures is a technical problem to be solved at present when the track is constructed.
Disclosure of Invention
In view of the above-mentioned technical problems, the technical solution of the present invention provides, in various aspects, an intrusion detection system, an early warning system and an intrusion detection method for a track construction area.
In a first aspect of the present invention, there is provided an intrusion detection system for a track construction area, comprising: a detection device which is arranged at the end of the track construction section and is used for detecting whether an invader entering the track construction section exists or not; and a signal processing module coupled to the detection device and configured to, in response to the detection device detecting an intrusion, perform feature extraction on a detected data point associated with the intrusion to determine whether the intrusion is a train.
In one embodiment of the invention, the signal processing module is further configured to: in response to the detection device detecting an intrusion, determining whether the intrusion is above a track based on a first distance between the intrusion and the detection device and a second distance between the detection device and the track; and in response to detecting that the intruding object is above the track, performing feature extraction on the detected data points above the track to determine whether the intruding object is a train.
In another embodiment of the present invention, in performing feature extraction on the detected data points above the track, the signal processing module is further configured to: and carrying out feature extraction on the data points in the preset height range above the track.
In yet another embodiment of the present invention, the signal processing module is further configured to, prior to feature extraction of the detected data points related to the intrusion: and in response to the detection device detecting the invader, performing background elimination processing on each group of section data obtained by vertical scanning of the detection device by using a background elimination algorithm so as to judge the invader based on data points after eliminating background noise.
In one embodiment of the invention, in feature extraction of data points above the track, the signal processing module is further configured to: determining a first-order linear correlation coefficient of each group of section data according to distance information between each data point in each group of section data above the track and the detection equipment and angle information of the detection equipment, wherein the distance information is obtained by vertical scanning of the detection equipment; and determining that the invaded object is a train in response to the first-order linear correlation coefficients of the continuous multiple sets of section data being greater than a first preset threshold.
In another embodiment of the present invention, the continuous sets of section data comprise continuous at least 10 sets of section data, and the first preset threshold comprises 0.9 to 0.95.
In yet another embodiment of the present invention, the signal processing module is further configured to: a first order linear correlation coefficient for each set of cross-sectional data is calculated according to the following formula:
Where R represents a first order linear correlation coefficient, x i represents the lateral distance of the ith data point in each set of cross-sectional data detected by the detection device, y i represents the height of the ith data point in each set of cross-sectional data detected by the detection device, For the average of the lateral distances of n data points in each set of cross-sectional data,Mean value of the heights of n data points in each set of section data; and x i＝L*sinθ,yi = L x cos θ, where L represents distance information of the i-th data point and θ represents angle information of the detection device.
In one embodiment of the invention, the signal processing module is further configured to: and determining the advancing direction of the invaded object according to the ascending and descending direction of the track where the invaded object is positioned.
In another embodiment of the present invention, the detection device includes a first laser radar and a second laser radar, which are respectively disposed at both ends of the track construction section and are located at the same side of the track or are respectively located at both sides of the track; the signal processing module is further configured to: and responding to the first laser radar or the second laser radar to detect an invaded object, and determining the travelling direction of the invaded object according to the up-down direction of the track where the invaded object is located and the relative position relation between the first laser radar and the second laser radar.
In yet another embodiment of the present invention, further comprising: and the alarm module is connected with the signal processing module and is configured to respond to the determination that the invaded object is a train and send out corresponding type alarm information according to the advancing direction of the invaded object.
In a second aspect of the present invention, an early warning system for a track construction section is provided, including the intrusion detection system according to the above-described embodiment of the present invention; and an alarm terminal communicatively connected to an alarm module in the intrusion detection system and configured to: and responding to the received alarm information, and sending out a corresponding early warning signal according to the type of the alarm information.
In yet another embodiment of the present invention, the alarm terminals are plural, and the jump point transmission is performed between the plural alarm terminals.
In another embodiment of the present invention, the method further includes a cloud platform connected to the alarm terminal, and the alarm terminal is further configured to: and in response to receiving the alarm information, uploading at least one of the alarm information, the time of receiving the alarm information and the position information of the alarm terminal to the cloud platform.
In a third aspect of the present invention, there is provided an intrusion detection method for a track construction section, comprising: arranging a detection device at the end of a track construction section for detecting whether an intruding object entering the track construction section exists; and in response to the detection device detecting an intrusion, performing feature extraction on the detected data points related to the intrusion to determine whether the intrusion is a train.
From the above description of the technical solution of the present invention and its various embodiments, those skilled in the art can understand that the intrusion detection system of the present invention may be configured to detect an intrusion that may enter a track construction area in real time by arranging a detection device at an end of the track construction area, and may further configure a signal processing module to perform feature extraction on the detected data points to determine whether the intrusion is a train. According to the arrangement, the real-time detection of the train entering the track construction section through the end part can be realized, so that the early warning can be carried out on the staff in the track construction section, and the safety and the automatic management of the track construction section are guaranteed.
Drawings
The above, as well as additional purposes, features, and advantages of exemplary embodiments of the present invention will become readily apparent from the following detailed description when read in conjunction with the accompanying drawings. In the drawings, several embodiments of the invention are illustrated by way of example and not by way of limitation, and like or corresponding reference numerals indicate like or corresponding parts and in which:
fig. 1 is a schematic view showing an intrusion detection system for a track construction section according to an embodiment of the present invention;
FIG. 2 is a 3D contour image showing an invader according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a scenario of determining an intrusion above a track according to an embodiment of the invention;
FIG. 4 is a schematic diagram illustrating feature extraction of point cloud data according to an embodiment of the invention;
FIG. 5 is a schematic diagram illustrating a first lidar and a second lidar on the same side of a track in accordance with an embodiment of the present invention;
FIG. 6 is a schematic diagram showing a first lidar and a second lidar located on either side of a track, respectively, in accordance with an embodiment of the present invention;
FIG. 7 is a schematic block diagram illustrating an intrusion detection system including an alarm module according to an embodiment of the invention;
FIG. 8 is a schematic block diagram illustrating an early warning system according to an embodiment of the present invention;
Fig. 9 is a schematic diagram showing an application scenario of an early warning system according to an embodiment of the present invention;
FIG. 10 is a schematic block diagram illustrating an early warning system according to another embodiment of the present invention; and
Fig. 11 is a flowchart illustrating an intrusion detection method according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the terms "first," "second," "third," and "fourth," etc. in the claims, specification and drawings of the present invention are used for distinguishing between different objects and not for describing a particular sequential order. The terms "comprises" and "comprising" when used in the specification and claims of the present invention are taken to specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification and claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should be further understood that the term "and/or" as used in the present specification and claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
Specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic view showing an intrusion detection system for a track construction area according to an embodiment of the present invention. As shown in fig. 1, an intrusion detection system 100 for a track construction section may include: a detection device 110 which may be disposed at an end of the track construction section and which detects whether an intruding object entering the track construction section exists; and a signal processing module 120, which may be coupled to the detection device 110, and configured to, in response to the detection device 110 detecting an intrusion, perform feature extraction on the detected data points associated with the intrusion to determine whether the intrusion is a train.
In some embodiments, the detection device 110 may include at least one of an image acquisition device, a lidar, an electromagnetic wave radar, and the like. The detection device 110 is used for detecting surrounding environment information and obstacle information, thereby realizing detection of an invaded object. In other embodiments, the detection device 110 may be disposed at one end of the track construction section. In some application scenarios, the arrangement position of the detection device 110 may be determined according to the traveling direction (i.e., the up-down direction) of the train traveling on the track. For example, when the train traveling direction on the track is in the direction indicated by the arrow in the figure, the detection device 110 may be disposed at an end of the track construction section opposite to the train traveling direction so as to timely detect an intruding object entering the track construction section.
In still other embodiments, the intrusion detection system 100 may include a plurality of detection devices 110 to be respectively disposed at both ends of the track construction section, and may detect an intrusion that may exist at both ends of the track construction area, so that the track construction section can be set as a closed area, which is advantageous for improving accuracy and safety of intrusion detection of the track construction section. In some embodiments, the plurality of detection devices 110 disposed at both ends of the track construction section may be located at the same side of the track, or may be located at both sides of the track, respectively. In some application scenarios, the track construction section may include one or more track routes. In other application scenarios, the track construction section may be a construction section of a railway track, a construction section of a subway track, or a track construction section of a tramcar.
In some embodiments, the signal processing module 120 and the detection device 110 may be connected by a wired or wireless connection. In other embodiments, the signal processing module 120 may be directly or indirectly coupled to the detection device 110. In still other embodiments, the signal processing module 120 may be communicatively coupled to the detection device 110. The signal processing module 120 may be configured to receive signal data detected by the detection device 110 and analyze and process it to determine the type of intrusion. In other embodiments, the signal processing module 120 may include signal processing circuitry for executing programs in the signal processing module 120 to implement a determination method for determining whether an intrusion is a train.
In some embodiments, the data points associated with the invasiveness may include data points that directly reflect characteristics of the invasiveness, and may also include data points associated with environmental information surrounding the invasiveness. For example, in some application scenarios, where the detection device 110 includes a lidar, and the point cloud data including the invader information obtained by the lidar may also include surrounding environmental information, such as a fixed facility like a track, a building, or the like, or the point cloud data of a moving object like a float, an insect, or the like in the air, the signal processing module 120 may perform an operation such as feature extraction on each frame data point in the point cloud data in which the invader is detected, so as to determine the type of the invader. In some embodiments, the 3D contour image of the invader shown in fig. 2 may be formed by performing operations such as three-dimensional model reconstruction on the point cloud data acquired in real time, and the vehicle type (e.g., truck, train, car, etc.) of the invader may be accurately identified by performing feature extraction and machine learning on the 3D contour image.
Because the construction environment is complex, floating, moving foreign objects, constructors and pedestrians in the field can generate echoes of point clouds when passing through the detection device 110 (such as a laser radar), and therefore, by extracting features of detected data points, namely identifying types of imaging objects (i.e. invaders), whether trains or other disturbances pass through the detection device 110 can be judged.
In yet another embodiment of the present invention, the signal processing module 120 may be further configured to, prior to feature extraction of the detected data points related to the intrusion: in response to detection of an intrusion by the detection device 110, each set of cross-sectional data obtained by the vertical scanning of the detection device 110 is subjected to a background rejection process using a background rejection algorithm to make a decision of the intrusion based on the data points after the background noise is rejected. In some application scenarios, the detection device 110 may perform a vertical scan (i.e. perpendicular to the track direction) at preset intervals (e.g. 10 ms), and when an invaded object passes, each vertical scan will obtain a set of section data of the invaded object, so when the invaded object passes completely, a large amount of section data may be obtained, and complete profile information of the invaded object may be obtained by processing each set of section data. In some embodiments, the vertical scanning may be achieved by a vertical light curtain of a lidar.
In other embodiments, the background culling algorithm may include, for example, a gaussian mixture model based algorithm, a frame difference method, and the like. Taking a frame difference method as an example, the essence of the algorithm is subtraction operation between images, and pixels with the same gray level in the two images are used as black points when the difference is zero. Because the time interval between two adjacent frames of the detection device 110 is very short, the background model using the previous frame image as the current frame has instantaneity, and the current frame image is only related to the previous frame image, so that the image background is not accumulated, and the method has the advantages of high updating speed, simple algorithm and small calculation amount. And carrying out background elimination processing on each group of section data by adopting a frame difference method, and carrying out difference on the section data of the current frame and the section data of the previous frame so as to obtain data points of the section data of the current frame after eliminating background noise. After background noise is removed, each group of section data can clearly display the outline of an invaded object and characteristic data, and the accuracy of subsequent processing is improved.
In yet another embodiment of the present invention, the signal processing module 120 may be further configured to: and determining the advancing direction of the invaded object according to the ascending and descending direction of the track where the invaded object is positioned. For example, the upward and downward direction of the track (i.e., the train traveling direction on the track) is the arrow direction shown in fig. 1, and when the detection device 110 is disposed at an end of the track construction section opposite to the upward and downward direction of the track (e.g., the position shown in fig. 1), the signal processing module 120 may determine that the traveling direction of the intruding object is the direction of entering the track construction section in response to the detection device 110 detecting the intruding object. Accordingly, when the detection device 110 is disposed at the same end of the track construction section as the up-down direction of the track, in response to the detection device 110 detecting an intruding object, it is possible to determine that the traveling direction of the intruding object is the direction away from the track construction section.
While an intrusion detection system according to an embodiment of the present invention has been described above with reference to fig. 1 and 2, it is to be understood that the above description is by way of example and not limitation, and for example, the signal processing module 120 may not be limited to performing feature extraction on all data points detected related to an intrusion, but may perform feature extraction only on data points determined to be above a track, which is advantageous in reducing data throughput and improving data processing accuracy. An exemplary description will be made below in connection with fig. 3.
Fig. 3 is a schematic diagram illustrating a scenario of determining an intrusion above a track according to an embodiment of the invention. For ease of illustration, fig. 3 is a top view from above the track. As shown in fig. 3, the signal processing module 120 may be further configured to: in response to detection of an intruding object 310 by detection device 110, determining whether an intruding object 310 is above track 320 based on a first distance D1 between an intruding object 310 and detection device 110 and a second distance D2 between detection device 110 and track 320; and in response to detecting that the intruding object 310 is above the track 320, performing feature extraction on the data points above the detected track 320 to determine whether the intruding object 310 is a train. The signal processing module 120 may also be configured to: in response to detecting that an intruding object 310 is not above the track 320, no subsequent processing is performed on the data points associated with the intruding object 310.
Since the detection device 110 has a ranging function, the detection device 110 can rapidly detect the first distance D1 between the intruding object 310 and the detection device 110 when the intruding object 310 passes through the detection range (e.g., vertical light curtain) of the detection device 110. Depending on the arrangement position of the detection device 110, a second distance D2 between the detection device 110 and the track 320 may be obtained. Since the width of the train is generally greater than the width of the track, it is possible to determine whether the invader 310 is on the track 320 by setting a predetermined distance range. For example, when the second distance D2 is 2m, the preset distance range may be set to 1 to 2m; if the detection device 110 detects that the first distance D1 is within the preset distance range of 1-2 m, the signal processing module 120 may determine that the intruding object 310 is above the track 320; if the detection device 110 detects that the first distance D1 is not within the preset distance range of 1-2 m, the signal processing module 120 may determine that the intruding object 310 is not above the track 320.
In some application scenarios, when there are multiple tracks in the detection range of the detection device 110, a preset distance range corresponding to each track may be determined according to the second distance D2 between each track and the detection device 110, so as to determine whether the invader 310 is on one of the tracks according to whether the first distance D1 of the detected invader 310 is within any preset distance range. In other application scenarios, when there are multiple tracks within the detection range of the detection device 110 and the detection device 110 detects multiple invaders 310, it may be determined whether each invader 310 is on a corresponding track according to the first distance D1 of each invader 310 detected.
In other embodiments, the signal processing module 120 determining whether the intruding object 310 is above the track 320 may include: the real-time determination is performed on each set of section data detected by the detection device 110, for example, by receiving the section data detected by the detection device 110 in real time, and determining whether the section of the invader in each set of section data is above the track according to the first distance D1 between the section of the invader in each set of section data and the detection device 110. In some embodiments, the first distance D1 between the cross-section of the intruding object and the detection device 110 in each set of cross-section data may be the distance of the closest data point on the cross-section of the intruding object to the detection device 110, or may be an average of the distances of the data points on the cross-section of the intruding object to the detection device 110. In still other embodiments, the signal processing module 120 may be further configured to: responding to the invading object section in the current section data above the track, and performing feature extraction on data points above the track in the current section data; and in response to the section of the invader in the current section data not being above the track, not performing the feature extraction operation on the current section data.
In another embodiment of the present invention, in performing feature extraction on the data points above the detected track 320, the signal processing module 120 may be further configured to: the data points within a preset height range above the track 320 are feature extracted. The preset height range may be set according to the train height. For example, in some embodiments, the preset height range may include 0-4 m. According to the arrangement, the height of the train is basically not more than 4m, so that only the data points in the preset height range are subjected to feature extraction, the data processing amount is further reduced, the recognition range is reduced, and the accuracy and the recognition speed for recognizing the vehicle type are further improved.
While the determination of whether an intruding object is on a track has been described above with reference to fig. 3, it is to be understood that the above description is illustrative and not limiting, and that the preset height range may be not limited to 0-4 meters, or may be adjusted according to practical situations. For example, feature extraction of data points may be performed by determining a first order linear correlation coefficient for each set of cross-sectional data. This will be described below with reference to fig. 4.
Fig. 4 is a schematic diagram illustrating feature extraction of point cloud data according to an embodiment of the present invention. In one embodiment of the present invention, in performing feature extraction on the data points above the track, the signal processing module may be further configured to: determining a first-order linear correlation coefficient of each group of section data according to distance information between each data point in each group of section data above a track obtained by vertical scanning of the detection equipment and angle information of the detection equipment; and determining that the invaded object is a train in response to the first-order linear correlation coefficients of the continuous multiple sets of section data being greater than a first preset threshold.
Fig. 4 illustrates a point cloud data map formed by multiple sets of section data, and as illustrated in fig. 4, the height of the effective area 410 may be determined according to a preset height range above the track, and the width position of the effective area 410 may be determined according to whether the first-order linear correlation coefficient of the continuous multiple sets of section data in the height range is greater than a first preset threshold. In another embodiment of the present invention, the consecutive sets of cross-sectional data comprise consecutive at least 10 sets of cross-sectional data, and the first preset threshold may comprise 0.9 to 0.95 (e.g., 0.9, 0.91, 0.92, 0.93, 0.94, 0.95, etc.).
For example, as shown in fig. 4, taking setting the first preset threshold to 0.9 as an example, when the first-order linear correlation coefficient R 1 =0.98 of the first set of section data appears, that is, greater than the first preset threshold by 0.9, the first-order linear correlation coefficient R 2 =0.95 of the second set of section data adjacent thereto, and the first-order linear correlation coefficients of the third to tenth sets of section data adjacent thereto in sequence are ：R3＝0.95、R4＝0.93、R5＝0.97、R6＝0.98、R7＝0.97、R8＝0.96、R9＝0.95、R10＝0.98, respectively, which are all greater than the first preset threshold by 0.9, it can be determined that the invader in the effective zone 410 is a train.
The principle of the method is as follows: when the first-order linear correlation coefficient is greater than the first preset threshold value 0.9, the recognition program in the signal processing module considers that the object (such as a person, an animal, a rolling stone and the like) with the non-natural cross section is detected, and when 10 groups of cross section data obtained continuously are all the first-order linear correlation coefficient which is greater than 0.9, the object cross section with the non-natural cross section is determined to be the cross section with the non-natural cross section, so that the passing of a train can be determined.
It should be noted that, when the set threshold value of the number of sets of continuous multi-set section data is too small and/or the set first preset threshold value is too small, a condition of judging oversensitivity may occur, that is, an invader other than a train may occur and be judged as a train, so that a false alarm problem occurs. When the set threshold value of the set continuous multi-set section data is too large and/or the set first preset threshold value is too large, the problem of train report missing can occur. Therefore, the threshold value of the number of groups is set to be 10 groups, and the first preset threshold value is set to be 0.9-0.95, so that the probability of missing report and false report can be effectively reduced, and the accuracy of judging the vehicle type result is improved obviously. According to the scheme of the embodiment, the accuracy of judging the train can reach more than 97%.
In another embodiment of the present invention, the signal processing module may be further configured to: determining the transverse distance and the height of each data point according to the distance information between each data point and the detection device in each group of section data above the track obtained by vertical scanning of the detection device and the angle information of the detection device; and determining a first-order linear correlation coefficient of each set of section data according to the transverse distance and the height of each data point in each set of section data.
In yet another embodiment of the present invention, the signal processing module may be further configured to: a first order linear correlation coefficient for each set of cross-sectional data is calculated according to the following formula:
Where R represents a first order linear correlation coefficient, x i represents the lateral distance of the ith data point in each set of cross-sectional data detected by the detection device, y i represents the height of the ith data point in each set of cross-sectional data detected by the detection device, For the average of the lateral distances of n data points in each set of cross-sectional data,Mean value of the heights of n data points in each set of section data; and x i＝L*sinθ,yi = L x cos θ, where L represents distance information of the i-th data point and θ represents angle information (i.e., angular resolution) of the detection device.
Having described exemplary feature extraction in accordance with an embodiment of the present invention in conjunction with fig. 4, exemplary determination of the direction of travel of an intruding object by a signal processing module will be described in conjunction with fig. 5 and 6.
In another embodiment of the present invention, the detection apparatus may include a first laser radar and a second laser radar, which may be disposed at both ends of the track construction section, respectively, and located at the same side of the track or at both sides of the track, respectively; the signal processing module may be further configured to: and responding to the first laser radar or the second laser radar to detect an invaded object, and determining the travelling direction of the invaded object according to the up-down direction of the track where the invaded object is located and according to the relative position relation between the first laser radar and the second laser radar.
In some embodiments, the signal processing module determines whether the track on which the invader is located may be the same or similar to the process of determining whether the invader is located on the track described above in conjunction with fig. 3, that is, may determine whether the first distance is within a preset distance range of a second distance between a certain track and the laser radar according to a first distance between the laser radar that detects the invader and the invader, so as to determine whether the invader is located on a certain track, which is not repeated herein.
Fig. 5 is a schematic diagram showing that the first lidar and the second lidar are located on the same side of the track according to an embodiment of the present invention. As shown in fig. 5, the first and second lidars 510 and 520 may be disposed at both ends of a track construction section, respectively, and may be located at the same side of the same track 531. The signal processing module (not shown in the figure) may also be configured to: in response to the first lidar 510 detecting the intruding object 541, the traveling direction of the intruding object 541 may be determined as the direction entering the track construction section according to the upward and downward directions of the track 531 where the intruding object 541 is located, taking the direction indicated by the solid arrow in fig. 5 as an example, i.e., the track 531 is used for the train passing in the upward direction, and according to the relative positional relationship between the first lidar 510 and the second lidar 520, for example, the second lidar 520 shown in fig. 5 is located in the upward direction of the first lidar 510.
As further shown in fig. 5, in another application scenario, when second lidar 520 detects an intrusion 542, a signal processing module (not shown) may be configured to: in response to the detection of the intruding object 542 by the second lidar 520, the traveling direction of the intruding object 542 can be determined as the direction entering the track construction section according to the upward and downward directions of the track 532 in which the intruding object 542 is located, taking the direction indicated by the dotted arrow in fig. 5 as an example, i.e., the direction in which the track 532 is used for the train passing in the downward direction, and according to the relative positional relationship between the first lidar 510 and the second lidar 520, for example, the first lidar 510 is located in the downward direction of the second lidar 520 as shown in fig. 5.
Similarly, assuming that the second lidar 520 detects the presence of an intruding object on the track 531, since the track 531 is in the upward direction and the second lidar 520 is located in the upward direction of the first lidar 510, the signal processing module may determine that the traveling direction of the intruding object is out of the track construction section. Assuming that the first lidar 510 detects the presence of an intruding object on the track 532, the signal processing module may determine that the traveling direction of the intruding object is out of the track construction section because the track 532 is in the downstream direction and the first lidar 510 is located in the downstream direction of the second lidar 520.
Fig. 6 is a schematic view showing that a first laser radar and a second laser radar are respectively located at both sides of a track according to an embodiment of the present invention. As shown in fig. 6, the first and second lidars 510 and 520 may be disposed at both ends of the track construction section, respectively, and may be located at both sides of the track 531 and the track 532, respectively. The signal processing module (not shown in the figure) may also be configured to: in response to the first lidar 510 detecting the intruding object 541, the traveling direction of the intruding object 541 can be determined as the direction entering the track construction section according to the upward and downward directions of the track 531 where the intruding object 541 is located, taking the direction indicated by the solid arrow in fig. 6 as an example, i.e., the track 531 is used for the train passing in the upward direction, and according to the relative positional relationship between the first lidar 510 and the second lidar 520, for example, the second lidar 520 shown in fig. 6 is located in the upward direction of the first lidar 510.
As further shown in fig. 6, in another application scenario, when the second lidar 520 detects an intrusion 542, a signal processing module (not shown) may be configured to: in response to the detection of the intruding object 542 by the second lidar 520, the traveling direction of the intruding object 542 can be determined as the direction entering the track construction section according to the upward and downward directions of the track 532 in which the intruding object 542 is located, taking the direction indicated by the dotted arrow in fig. 6 as an example, i.e., the direction in which the track 532 is used for the train passing in the downward direction, and according to the relative positional relationship between the first lidar 510 and the second lidar 520, for example, the first lidar 510 is located in the downward direction of the second lidar 520 as shown in fig. 6.
Similarly, assuming that the second lidar 520 detects the presence of an intruding object on the track 531, since the track 531 is in the upward direction and the second lidar 520 is located in the upward direction of the first lidar 510, the signal processing module may determine that the traveling direction of the intruding object is out of the track construction section. Assuming that the first lidar 510 detects the presence of an intruding object on the track 532, the signal processing module may determine that the traveling direction of the intruding object is out of the track construction section because the track 532 is in the downstream direction and the first lidar 510 is located in the downstream direction of the second lidar 520.
While the embodiments of determining the traveling direction of the intruding object based on the two laser radars disposed at both ends of the track construction section have been described above with reference to fig. 5 and 6, it is to be understood that the above description is not limited, and for example, the number of tracks in the track construction section may not be limited to two as shown in fig. 5 and 6, and a greater or lesser number of tracks may occur according to the actual application, and the manner of determining the traveling direction may be the same or similar, for example, the traveling direction of the intruding object may be determined according to whether the positional relationship between the laser radars detecting the intruding object and the laser radars at the other end of the track construction section coincides with the up-down direction of the track where the intruding object is located, which is not repeated herein.
For example, in some embodiments, the signal processing module may be configured to process the point cloud data of both the first lidar and the second lidar. In other embodiments, the number of signal processing modules may be the same as the number of lidars, and the plurality of signal processing modules may be in one-to-one correspondence with the lidars, such that each signal processing module processes point cloud data of one lidar. Further, after determining the traveling direction of the intruding object, the corresponding type of alarm information may be determined according to the traveling direction of the intruding object. An exemplary description will be given below with reference to fig. 7.
Fig. 7 is a schematic block diagram illustrating an intrusion detection system including an alarm module according to an embodiment of the present invention. As shown in fig. 7, intrusion detection system 700 may include: the detection device 110, the signal processing module 120 and the alarm module 710, wherein the alarm module 710 may be connected with the signal processing module 120. In some embodiments, the alarm module 710 may be directly or indirectly connected to the signal processing module 120. In other embodiments, the alarm module 710 and the signal processing module 120 may be connected wirelessly or by a wire. In other embodiments, the alarm module 710 may be communicatively coupled to the signal processing module 120.
In one embodiment of the invention, the alarm module 710 may be configured to issue a corresponding type of alarm information based on the direction of travel of the intrusion in response to determining that the intrusion is a train. For example, in some application scenarios, in response to the direction of travel of an intrusion being a direction into a track construction section, the alert module 710 may issue hazard alert information indicating that the train is entering the track construction section. In other applications, in response to the direction of travel of the intrusion being the direction away from the track construction site, the alert module 710 may issue alert information indicating a disarmed hazard or disarmed alert for the train exiting the track construction site. In some embodiments, the alarm module 710 may be configured to: and (5) carrying out corresponding type alarm coding according to the advancing direction of the invaded object.
In other embodiments, the alarm module 710 may employ a lora communication protocol to actively send alarm information via the concentrator. In still other embodiments, the alarm module 710 may employ spread spectrum communications such that the transmission distance may reach 3km. In some application scenarios, at least two alarm modules can be set and respectively arranged at two ends of the track construction section, and as the signal transmission distance of each alarm module 710 can reach 3km, the track construction section can be set to 6km, so that the signal transmission full coverage in the track construction section can be ensured, and the constructor can also have enough construction space and evacuation time.
While an intrusion detection system including an alarm module according to an embodiment of the present invention has been described above with reference to fig. 7, it will be appreciated that more detailed and accurate operating condition information can be provided to a construction site by the alarm module sending out different types of alarm information. It will also be appreciated that the intrusion detection system may not be limited to only including a detection device, a signal processing module, and an alarm module, and in some embodiments, the intrusion detection system may also include, for example, a battery powered module that may be used to provide power support for the intrusion detection system, an interface operating system that may be used to enable human-machine interaction, and the like. Further, in order to facilitate understanding of the working principle of the lidar, the following description will be made in detail.
The basic principle of laser radar ranging is as follows: the laser generates and emits a laser pulse or continuous laser beam, which after being reflected against the object generates an echo signal, which is received by the receiver, and the time interval t between the emission of the laser pulse and the reception of the echo signal is then accurately measured. Since the laser light propagates in the medium at a light velocity c, the distance d between the target and the lidar, i.e. d=c×t/2, can be calculated from the data in the medium for which the light velocity is known. The basic principle of laser radar pulse rotation radar scanning is as follows: the laser emits a beam of laser pulse to the inclined mirror, and the laser pulse is reflected by the inclined mirror rotating through the fixed shaft, so that the laser pulse is detected within a certain range in a plane.
In some embodiments, a lidar according to embodiments of the present invention may include a sensor head, a scanner, a data processor, and an internal rotating electrical machine. The laser radar can be arranged at the tops of the H-shaped steel columns at the two sides of the track, the distance from the laser radar to the ground is about 1-2 m, and the radar host can be tightly connected with the steel columns in a magnetic attraction mode. By setting the scanning angle and the triggering distance of the laser radar, the passing train can be detected. In other embodiments, the angle of the lidar may be adjusted by a laser angle positioning device to determine that the detected range is within the light curtain, i.e., to ensure that the light curtain angle covers the train height. In still other embodiments, the lidar may perform 60 scan data readings per second. In other embodiments, the detection distance of the lidar may be up to 20 meters. The laser beam in the mirror surface of the laser radar can be vertically scanned once in each scanning period, namely a vertical light curtain is formed, and the distance data of the point cloud can be transmitted to the signal processing module through the data interface of the laser radar after each scanning.
Compared with detection equipment such as cameras, the laser radar has the advantages of high accuracy, easy development of pattern recognition algorithms and the like. According to the scheme of adopting the laser radar as the detection equipment, the false alarm rate of whether an invader pair is an on-track locomotive is far lower than that of a visible light scheme, and the accuracy rate is far higher than that of intelligent identification capture rate of a camera. Compared with other radars with electromagnetic waves as carriers, the laser radar which adopts a laser as a laser emitting device has the following advantages: (1) higher operating frequency; (2) The measuring precision is high, the laser directivity and accuracy are not easy to be interfered by external environment; (3) The laser radar has strong penetrating power, concentrated laser energy and extremely strong penetrating power in certain substances, so that the laser radar can realize target detection under certain shielding conditions; (4) high resolution: lidar typically has extremely high range and angular resolution; and (5) the low-altitude detection performance is good.
As a person skilled in the art can understand that the intrusion detection system according to the embodiment of the invention can determine the type of the intrusion by arranging the detection device at the end of the track construction section and extracting the characteristics of the data points related to the intrusion detected by the detection device through the signal processing module, the intrusion detection system has the characteristics of high recognition accuracy and the like, can provide accurate information for determination of the lower rail of the constructor, and is beneficial to improving the working safety of the constructor in the track construction area and the windowing period.
Fig. 8 is a schematic block diagram illustrating an early warning system according to an embodiment of the present invention. As shown in fig. 8, an early warning system 800 for a track construction section may include an intrusion detection system 700 such as shown in fig. 7, and one or more alarm terminals 810, wherein the intrusion detection system 700 may include a detection device 110, a signal processing module 120, and an alarm module 710, the alarm module 710 may be communicatively connected with the alarm terminals 810, and the alarm terminals 810 may be configured to: and responding to the received alarm information, and sending out a corresponding early warning signal according to the type of the alarm information.
In some embodiments, the alarm terminal 810 may include a wireless receiving module for receiving alarm information sent by the alarm module 710. In other embodiments, the alarm terminal 810 and the alarm module 710 may communicate using a lora communication protocol, and since the lora operates in a low power consumption state when receiving data, the power consumption is low, and by using an efficient cyclic error correction algorithm, the coding efficiency is high, the error correction capability is strong, and the anti-interference performance and the high stability of the wireless receiving module are greatly improved. In other embodiments, the alarm terminal 810 may obtain the type of alarm information by decoding the alarm information after receiving the alarm information.
In some embodiments, the alert signal may include a signal emitted in an audible or visual form, such as a voice signal, an acousto-optic signal, etc., and may also include a tactile signal, etc., such as a vibration, etc. In other embodiments, the alert terminal 810 may be further configured to: in response to receiving an alarm signal that a train is about to enter a track construction section, an early warning signal for warning danger can be sent out; in response to receiving an alert signal that the train is leaving the track construction zone, an alert signal for releasing the hazard warning may be sent. For example, in some application scenarios, the alarm terminal 810 may distinguish the type of alarm information by emitting audible and visual signals of different intensities. In other application scenarios, the alarm terminal 810 may distinguish the types of alarm information by sending out different voice signals, such as sending out a voice of "train in, please leave the track quickly" or "train out, danger releasing", etc. In still other application scenarios, in a normal operating state without alarm information, the alarm terminal 810 may provide a green light strobe to determine that field networking is normal.
In still other embodiments, the alarm terminal may be a fixed setting, which may be disposed in the track construction section, for example, the alarm terminal may be fixedly disposed at a middle position of the track construction section, and early warning broadcast is performed to all staff in the track construction section in the form of a broadcast notification. In other embodiments, the alarm terminal may be a portable device and may be worn on the body of each staff member, so as to be capable of sending an early warning signal to the wearer in a targeted manner when the alarm information is received. In yet another embodiment of the present invention, the alarm terminals may be plural, and the skip point transmission may be performed between the plural alarm terminals. An exemplary description is provided below in connection with fig. 9.
Fig. 9 is a schematic diagram showing an application scenario of an early warning system according to an embodiment of the present invention. As shown in fig. 9, the first lidar 510 and the second lidar 520 may be disposed at two ends of the track construction section, respectively, when the first lidar 510 detects the invader 930, the signal processing module (not shown in the drawing) may determine whether the invader 930 is a train according to the echo point cloud data of the first lidar 510, and when the invader 930 is determined to be a train, the alarm module (not shown in the drawing) may send alarm information to the alarm terminal 911 within the communication range, and at this time, the alarm terminal 911 may send the alarm information to the other alarm terminals 912 through the trip point transmission 920. According to such a configuration, even if the alarm terminal 912 is not within the communication range of the alarm module, the alarm information can still be received via the other alarm terminals 911, so that each alarm terminal has a chance of receiving the same alarm information twice, thereby effectively reducing the probability that a certain alarm terminal is not reported when a plurality of alarm terminals exist.
Fig. 10 is a schematic block diagram illustrating an early warning system according to another embodiment of the present invention. As shown in fig. 10, the early warning system 1000 may include an intrusion detection system 700, an alarm terminal 810, and a cloud platform 1010, wherein the cloud platform 1010 may be communicatively connected to each alarm terminal 810, and each alarm terminal 810 may be further configured to: in response to receiving the alert information, at least one of the alert information, a time at which the alert information was received, and location information of the alert terminal, etc. is uploaded to the cloud platform 1010. In some embodiments, the alert terminal 810 may include a mobile data transmission module for communicating with the cloud platform over, for example, a 2G or 3G or 4G or 5G mobile network. In other embodiments, the alarm terminal 810 may further include a positioning module, such as a GPS positioning module or a beidou positioning module, to obtain position information of the alarm terminal 810.
In still other embodiments, the cloud platform 1010 may employ web framework development, such as Spring IOC, myBatis, servlet, maven framework, or the like. In some embodiments, cloud platform 1010 may also be communicatively coupled to an intrusion detection system to obtain location information of the placement of the detection device. The cloud platform 1010 may draw a GIS map of the track construction section according to the obtained arrangement position information of the detection device, the position information of the alarm terminal 810, the track information, and the like, so as to display the GIS map, and the supervisory personnel may view more detailed information by clicking the position information of the staff located by the alarm terminal 810. Through the setting of high in the clouds platform, can help the supervisor to trace back the warning reason of producing, be favorable to improving early warning system's safety control ability and informatization ability to and realize carrying out intelligent management to discrete and removal personnel.
Through the description of the early warning system in the embodiment of the invention, those skilled in the art can understand that in the early warning system, by utilizing the detection result of the intrusion detection system and the communication between the alarm module and the alarm terminal, the early warning prompt is carried out on constructors in the track construction section, different types of early warning signals can be sent out, and the constructors can be separated from the on-track construction site immediately after receiving the on-site early warning signals, so that the management efficiency of construction safety is improved, the automatic construction safety management is realized, and the possibility is provided for the non-safety guard during railway construction.
In a third aspect of the present invention, there is also provided an intrusion detection method for a track construction section, which will be exemplarily described below with reference to fig. 11. Fig. 11 is a flowchart illustrating an intrusion detection method according to an embodiment of the present invention. As shown in fig. 11, an intrusion detection method 1100 may include: in step 1110, a detection device is arranged at an end of the track construction section for detecting whether an intruding object entering the track construction section exists; and in step 1120, in response to the detection device detecting the intrusion, performing feature extraction on the detected data points associated with the intrusion to determine whether the intrusion is a train.
The above intrusion detection method has been described in detail in connection with the intrusion detection system, and will not be described here.
Although the embodiments of the present invention are described above, the description is only an embodiment adopted for the purpose of facilitating understanding of the present invention, and is not intended to limit the scope and application of the present invention. Any person skilled in the art can make any modification and variation in form and detail without departing from the spirit and scope of the present disclosure, but the scope of the present disclosure is defined by the appended claims.
Claims (8)
1. An intrusion detection system for a track construction section, comprising:
A detection device which is arranged at the end of the track construction section and is used for detecting whether an invader entering the track construction section exists or not; and
A signal processing module connected with the detection device and configured to,
In response to the detection device detecting an intrusion, performing feature extraction on detected data points related to the intrusion to determine whether the intrusion is a train;
Wherein the signal processing module is further configured to:
In response to the detection device detecting an intrusion, determining whether the intrusion is above a track based on a first distance between the intrusion and the detection device and a second distance between the detection device and the track; and
In response to detecting that the intruding object is above the track, performing feature extraction on the detected data points above the track to determine whether the intruding object is a train;
in feature extraction of data points above the detected track, the signal processing module is further configured to:
Carrying out feature extraction on data points in a preset height range above the track;
the signal processing module is further configured to, prior to feature extraction of the detected data points related to the intrusion:
in response to the detection device detecting an invader, performing background rejection processing on each group of section data obtained by vertical scanning of the detection device by using a background rejection algorithm so as to judge the invader based on data points after background noise rejection;
Wherein in feature extraction of data points above the track, the signal processing module is further configured to:
Determining a first-order linear correlation coefficient of each group of section data according to distance information between each data point in each group of section data above the track and the detection equipment and angle information of the detection equipment, wherein the distance information is obtained by vertical scanning of the detection equipment; and
Determining that the invaded object is a train in response to the first-order linear correlation coefficients of the continuous multiple sets of section data are all larger than a first preset threshold value;
The continuous multiple sets of section data comprise continuous at least 10 sets of section data, and the first preset threshold comprises 0.9-0.95.
2. The intrusion detection system according to claim 1, wherein the signal processing module is further configured to:
a first order linear correlation coefficient for each set of cross-sectional data is calculated according to the following formula:
Where R represents a first order linear correlation coefficient, x i represents the lateral distance of the ith data point in each set of cross-sectional data detected by the detection device, y i represents the height of the ith data point in each set of cross-sectional data detected by the detection device, For the average of the lateral distances of n data points in each set of cross-sectional data,Mean value of the heights of n data points in each set of section data; and x i＝L*sinθ,yi = L x cos θ, where L represents distance information of the i-th data point and θ represents angle information of the detection device.
3. An intrusion detection system according to any one of claims 1-2 the signal processing module being further configured to:
Determining the advancing direction of an invaded object according to the up-down direction of a track where the invaded object is positioned;
The detection equipment comprises a first laser radar and a second laser radar which are respectively arranged at two ends of the track construction section and are positioned at the same side of the track or at two sides of the track;
The signal processing module is further configured to:
and responding to the first laser radar or the second laser radar to detect an invaded object, and determining the travelling direction of the invaded object according to the up-down direction of the track where the invaded object is located and the relative position relation between the first laser radar and the second laser radar.
4. An intrusion detection system according to claim 3 further comprising:
An alarm module connected with the signal processing module and configured for,
And responding to the determination that the invader is a train, and sending out corresponding type of alarm information according to the advancing direction of the invader.
5. An early warning system for a track construction section, comprising the intrusion detection system according to claim 4; and
An alarm terminal communicatively connected to an alarm module in the intrusion detection system and configured to:
And responding to the received alarm information, and sending out a corresponding early warning signal according to the type of the alarm information.
6. The early warning system of claim 5, wherein the alarm terminals are plural and a skip point transmission is performed between the plural alarm terminals.
7. The early warning system of claim 5 or 6, further comprising a cloud platform connected with the alarm terminal, and the alarm terminal is further configured to:
And in response to receiving the alarm information, uploading at least one of the alarm information, the time of receiving the alarm information and the position information of the alarm terminal to the cloud platform.
8. An intrusion detection method for a track construction section using the intrusion detection system according to any one of claims 1 to 4 or the early warning system according to any one of claims 5 to 7, comprising:
arranging a detection device at the end of a track construction section for detecting whether an intruding object entering the track construction section exists; and
In response to the detection device detecting an intrusion, feature extraction is performed on detected data points associated with the intrusion to determine whether the intrusion is a train.
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