Track inspection device equipped with relaxation determination system

Abstract

To provide a relaxation determination system for fasteners, which captures a test object having a plurality of fasteners as video data, detects the fasteners, and determines relaxation of the fasteners more quickly.SOLUTION: A system M for determining relaxation of fasteners at fastening portions of a structure includes: imaging means 1 which images a structure being a test object; fastener detection means 21 which detects fasteners from the video data captured by imaging means 1; and relaxation determination means 22 which determines the relaxation state of the fasteners detected by the fastener detection means 21. The fastener detection means 21 uses AI (Artificial Intelligence) that has learned detection of the fasteners through the reference video data captured in advance at the same angle of view as the video data to detect the fasteners from the video data and generates still image data recording the fasteners. The relaxation determination means 22 determines the relaxation state of the fasteners by comparing the still image data with reference still image data obtained by capturing a state where the fastening by the fasteners is good in advance.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a relaxation determination system for a fastener that fastens at least two or more members to each other, a track inspection device equipped with the relaxation determination system, and a track inspection method.

Background Art

[0002] Conventionally, in order to determine the fastening state (whether there is looseness) of fasteners such as bolts and nuts used for fixing at least two or more members to each other, it is generally known to mark a mark called a mating mark on the fastener in advance.

[0003] Specifically, a straight line is marked with a marker or the like so as to straddle the fastener and the structure fastened by the fastener. When the fastener becomes loose, a deviation occurs between the straight line marked on the fastener and the straight line marked on the structure. By visually checking the deviation of this mating mark, it is determined that the fastener is loose.

[0004] The relaxation determination method using the mating mark has the advantage that an operator can visually determine the relaxation state of the fastener and can easily perform the inspection. However, when inspecting a structure with a large number of fastening parts, it is necessary to determine the relaxation state of the fasteners by a large number of workers, which is a drawback in that it requires a great deal of time and labor.

[0005] Therefore, Patent Document 1 and Patent Document 2 disclose a system for determining the mating mark marked on a fastener by image processing. Both Patent Document 1 and Patent Document 2 are provided with imaging means, and compare the image of the fastener taken by this imaging means with the fastener in a state where the fastening state is good recorded in advance, and determine the relaxation state from the change in the angle of the mating mark.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

[0007] The relaxation determination systems described in Patent Document 1 and Patent Document 2 can save the labor of visually judging each one by the worker by performing the determination of the relaxation state of the fastener by image processing, and can obtain a uniform determination result without being influenced by the judgment ability of the worker.

[0008] However, since the relaxation determination systems described in Patent Document 1 and Patent Document 2 perform comparison with an image having a good fastening state stored in advance, it is necessary to photograph each fastener to be detected by an imaging means. Therefore, when the number of fasteners to be detected is large, it is too laborious to perform photographing with one imaging means, or the cost increases due to providing a plurality of imaging means corresponding to each fastener, which is a problem.

[0009] In addition, since the relaxation determination systems described in Patent Document 1 and Patent Document 2 have a fastener as the detection target, only the fastener is photographed by the imaging means and the relaxation determination is performed by image processing, so it is not possible to detect other defects of the structure provided with the fastener.

[0010] The present invention has been made in view of the above problems, and photographs an inspection target having a plurality of fasteners as moving image data, and detects the fasteners from the moving image data to more quickly perform the relaxation determination of the fasteners, and when the inspection target has a defect other than the relaxation of the fasteners, it is possible to detect the defect based on the previously captured moving image data. An object of the present invention is to provide a fastener relaxation determination system, a track inspection device provided with the relaxation determination system, and a track inspection method. [Means for Solving the Problems]

[0011] In order to solve the above-mentioned conventional problems, a system for determining the loosening of a fastener at a fastening part of a structure, comprising: imaging means for photographing the structure to be inspected; fastener detection means for detecting a fastener from video data photographed by the imaging means; and loosening determination means for determining the loosening state of the fastener detected by the fastener detection means, wherein the fastener detection means uses an AI (Artificial Intelligence) that has been trained to detect the fastener based on reference video data photographed in the same field of view as the video data in advance, detects the fastener from the video data, and generates still image data recording the fastener, and the loosening determination means determines the loosening state of the fastener by comparing the still image data with reference still image data that has previously imaged a state in which the fastening by the fastener is in good condition.

[0012] Further, the imaging means is mounted on a vehicle that can be towed by a self-propelled or other self-propelled vehicle, and is also characterized in that it photographs a plurality of the fasteners provided on the structure as the vehicle travels.

[0013] Further, the vehicle travels on a track for train operation, the imaging means photographs the fasteners for connecting and fixing the rails constituting the track and the periphery of the track as the video data, and the fastener detection means is also characterized in that it detects defects determined by comparing the fastener and the reference video data from the video data.

Advantages of the Invention

[0014] According to the present invention, a plurality of fasteners provided in the structure to be inspected are photographed as video data by the imaging means, still image data recording the fasteners is generated and detected from the acquired video data using AI, and the loosening of the detected fasteners is determined by image processing, so that the loosening of the fasteners can be determined quickly.

[0015] In addition, when detecting a fastener from video data and extracting it as still image data, AI compares it with reference video data in which the detection of the fastener has been learned in advance. Therefore, the different parts of the two video data obtained by comparing the video data at the time of inspection with the reference video data, that is, the differences can be recognized and detected as defects by AI.

Brief Description of Drawings

[0016]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Embodiments for Carrying Out the Invention

[0017] The gist of the present invention is a system for determining the loosening of a fastener at a fastening part of a structure, comprising imaging means for photographing the structure to be inspected, fastener detection means for detecting the fastener from the moving image data photographed by the imaging means, and loosening determination means for determining the loosening state of the fastener detected by the fastener detection means. The fastener detection means uses AI (Artificial Intelligence) that has been trained to detect the fastener from reference moving image data photographed in the same angle of view as the moving image data in advance, detects the fastener from the moving image data, and generates still image data recording the fastener. The loosening determination means determines the loosening state of the fastener by comparing the still image data with reference still image data that has photographed a state where the fastening by the fastener is in good condition in advance.

[0018] Hereinafter, with reference to the accompanying drawings, an embodiment of a fastener loosening determination system M, a track inspection device V provided with the fastener loosening determination system M, and a track inspection method P according to the present invention will be described. The following embodiment is an example embodying the present invention and does not limit the technical scope of the present invention.

[0019] [1. About the fastener loosening determination system] First, the fastener loosening determination system M according to the present invention will be described with reference to the drawings.

[0020] As shown in FIG. 1, the fastener loosening determination system M according to the present embodiment mainly includes imaging means 1 for photographing the structure to be inspected as moving image data D1, fastener detection means 21 for detecting a fastener VN from the moving image data D1 photographed by the imaging means 1 and generating still image data G1, and loosening determination means 22 for determining the loosening state of the fastener VN from the still image data G1 generated by the fastener detection means 21.

[0021] The structure to be inspected includes a plurality of fasteners VN. For example, it includes buildings equipped with a plurality of high-strength bolts, or railway tracks of trains that have bolts and nuts for connecting rails. In this embodiment, the fastener VN composed of bolts and nuts will be described as an example. However, the fastener relaxation determination system M according to the present invention is not limited to bolts and nuts as the objects of relaxation determination. Any object that can be visually confirmed (judgment is possible by image processing) and whose abnormal conditions such as relaxation state and detachment can be judged can be the object of determination. Furthermore, the fastener VN and the structure fastened by the fastener VN are marked with straight alignment marks PM spanning the fastener VN and the rail TR as shown in FIGS. 3 and 4 in advance, taking the track TO as an example.

[0022] The imaging means 1 is composed of an imaging device such as a video camera equipped with an imaging element such as a CCD (Charge Coupled Device). The imaging means 1 photographs the plurality of fasteners VN provided in the structure in a determined order. The photographed moving image data D1 is transmitted to the fastener detection means 21.

[0023] The fastener detection means 21 performs a process of extracting and generating each fastener VN recorded in the moving image data D1 photographed by the imaging means 1 as still image data G1. This fastener detection means 21 uses AI (Artificial Intelligence) that has learned fastener detection. Specifically, the shape characteristics of the fastener VN are learned in advance from reference moving image data D2 that has photographed the fasteners VN provided in the structure. Then, the process of extracting and writing out as still image data G1 those that match the shape characteristics of the fastener VN learned from the moving image data D1 photographed by the imaging means 1 during inspection is carried out.

[0024] More specifically, as shown in FIG. 2, the fastener detection means 21 includes a video receiving unit 211 that receives the video data D1 transmitted from the imaging means 1, a reference video data storage unit 212 that stores the reference video data D2 previously captured by the imaging means 1, a fastener extraction unit 213 that detects the fastener VN from the video data D1 and extracts and generates it as still image data G1, and a still image transmission unit 214 that transmits the generated still image data G1 to the relaxation determination means 22.

[0025] The video receiving unit 211 receives the video data transmitted from the imaging means 1. The video data to be received is the reference video data D2 captured by the imaging means 1 in advance at the same viewing angle as during the inspection of the fastener VN of the structure before the inspection and the video data D1 captured by the imaging means 1 during the inspection.

[0026] The reference video data storage unit 212 stores the reference video data D2 among the video data received by the video receiving unit 211. Also, although it will be described in detail later, since the video data D1 captured during the inspection is also used for AI learning, the video data D1 captured during the inspection is also stored in this reference video data storage unit 212 after the inspection.

[0027] The fastener extraction unit 213 can mainly perform four processes: a reference video data learning process 213a, a fastener extraction process 213b, a defect detection process 213c, and a learning data storage process 213d by the learning AI.

[0028] The reference video data learning process 213a is a process of learning the shape features of the fastener VN included in the structure captured by the imaging means 1 from the reference video data D2 to correctly recognize the fastener VN, and recognizing the parts other than the fastener VN (for example, the design surface of the structure, etc.) recorded in the reference video data D2 as normal states.

[0029] The AI that constitutes the fastener detection means 21 can extract and generate the fastener VN as still image data G1 from the video data D1 captured during the inspection and transmitted in real time by the fastener extraction process 213b, which will be described next, according to the learning content of this reference video data learning process 213a. Also, by learning the content recorded in the reference video data D2, it becomes possible to recognize and process the differences as defects in the defect detection process 231c by comparing with the video data D1 captured during the inspection and transmitted in real time.

[0030] The fastener extraction process 213b is a process of extracting and generating only the fastener VN as still image data G1 from the video data D1 received by the video receiving unit 211 when actually performing the inspection. This extracted and generated still image data G1 is used to determine whether the fastener VN reflected in the still image data G1 is loose by comparing it with the reference still image data G2 through image processing, which will be described in detail later.

[0031] The defect detection process 213c is a process of detecting defects by comparing the video data D1 received by the video receiving unit 211 when actually performing the inspection with the normal state of the structure learned in advance from the reference video data D2. Specifically, if the normal state of the design surface of the structure is learned, damage such as scratches and dents on the design surface can be recognized as a difference from the reference video data D2, and the difference can be detected as a defect.

[0032] The defects detected by the defect detection process 213c are transmitted as defect information B to the terminals held by the workers performing the inspection or to the terminals held by the workers observing the inspection work remotely.

[0033] The learning data storage process 213d is a process of storing the video data D1 that has been inspected and its results together with the reference video data D2 for use in AI learning. In AI learning, the more data available for learning, the higher the accuracy of the results. Therefore, by storing the video data D1 and defect information B used in each inspection and using the stored information as the learning target for the reference video data learning process 213a, the accuracy of the fastener extraction process 213b and the defect detection process 213c can be improved. This video data D1 is stored by the reference video data storage unit 212.

[0034] The still image transmission unit 214 is for transmitting the still image data G1 generated from the video data D1 by the fastener extraction process 213b of the fastener extraction unit 213 to the relaxation determination means 22.

[0035] As shown in FIGS. 3 and 4, the relaxation determination means 22 compares the still image data G1 received from the fastener detection means 21 with the reference still image data G2 of the fastener VN in a state where the fastening by the fastener VN stored in the relaxation determination means 22 in advance is good, that is, a state where there is no deviation in the mating mark PM, and determines the relaxation state of the fastener VN provided in the inspection target.

[0036] As shown in FIG. 1, the relaxation determination means 22 is composed of a still image reception unit 221, a reference still image storage unit 222, an image comparison unit 223, and a relaxation notification unit 224.

[0037] The still image data G1 transmitted by the still image transmission unit 214 of the fastener detection means 21 is received by the still image reception unit 221 and transmitted to the image comparison unit 223 of the relaxation determination means 22.

[0038] The reference still image memory unit 222 stores reference still image data G2 in a state where the fastening by the fastener VN is good. The state where the fastening is good means that, as shown in FIGS. 3 and 4, the alignment marks PM previously marked on the structure so as to straddle the fastener VN appear in a straight line without shifting. This reference still image data G2 is a previously captured image of the fastener VN. For example, the still image data G1 of the fastener VN generated by the fastener detection means 21 or an image captured by another imaging means not included in the configuration of the fastener relaxation determination system M is used.

[0039] The image comparison unit 223 compares the still image data G1 of the fastener VN generated by the fastener detection means 21 with the reference still image data G2 when performing an inspection to determine the relaxation state of the fastener VN. The fastener VN for which relaxation is recognized as a result of the comparison transmits the information as relaxation information A to the relaxation notification unit 224. The relaxation information A transmitted to the relaxation notification unit 224 is information such as the still image data G1 of the fastener VN for which relaxation is recognized and which number of the still image data G1 the still image data G1 was determined by the image comparison unit 223.

[0040] The relaxation notification unit 224 notifies the operator who is performing the relaxation inspection of the fastener VN of the relaxation information A received from the image comparison unit 223. The notification of the relaxation information is transmitted to the terminal possessed by the operator performing the inspection or the terminal possessed by the operator observing the inspection work remotely.

[0041] The fastener detection means 21 and the relaxation determination means 22 are provided, for example, in an information processing terminal 2 such as a PC having a configuration in which a CPU (Central Processing Unit) as an arithmetic processing device that executes various arithmetic processes and controls, a storage device such as a RAM (Random Access Memory) and a ROM (Read Only Memory), an input / output device such as an input / output interface for data input / output, and peripheral circuits such as a clock circuit are connected by a bus or the like.

[0042] [Regarding the track inspection device equipped with the fastener relaxation determination system] Next, a track inspection device V equipped with a fastening member relaxation determination system M used when the structure to be inspected is a track TO for train running will be described with reference to the drawings. In the present embodiment, the track inspection device V described below is self-propelled by including an electric motor 4, but it is not necessarily required to be self-propelled. For example, it may be configured to travel on the track TO by being towed by a vehicle capable of running and perform inspections.

[0043] As shown in FIG. 6, the track inspection device V mainly includes a carriage unit 3 having wheels 34 connected to an axle 33, an electric motor 4 that outputs a rotational driving force to the axle 33 through a drive transmission means, a control unit 5 that electrically controls the electric motor 4, a plurality of imaging means 1 provided on the carriage unit 3, a lighting unit 6 disposed near each imaging means 1, and a terminal protection unit 7 that houses an information processing terminal 2 inside, which includes a fastening member detection means 21 and a relaxation determination means 22 for receiving the moving image data D1 captured by the imaging means 1 and performing a relaxation determination of the fastening member VN, and a seat unit 8 for an operator to board.

[0044] The carriage unit 3 is composed of a base frame 31 made of metal angle materials or pipe materials, a base plate 32 laid on the base frame 31, axles 33 provided at the front and rear of the base frame 31, and wheels 34 connected to both ends of the two axles 33. That is, the carriage unit 3 is a four-wheel vehicle having two structures of axles 33 and wheels 34 connected to both ends of the axles 33, front and rear. Hereinafter, the axle 33 and the wheel 34 located in front of the carriage 4 are referred to as the front wheel FW, and the axle 33 and the wheel 34 located at the rear are referred to as the rear wheel RW.

[0045] Each of the four wheels 34 is provided with a wheel detachment prevention portion 45 having a diameter larger than that of the wheel 34 body on the carriage 4 side. When the carriage 4 travels on the track TO, the wheel detachment prevention portion 45 is located inside the two rails TR constituting the track TO, so that the detachment of the wheel 34 body rotating on the rail TR can be prevented.

[0046] A front frame 36 extending upward is provided on the front side of the base frame 31. Specifically, it is composed of a support column portion 361 extending upward and rearward from the vicinity of the left and right wheels 34 constituting the front wheels FW, a ladder-shaped installation portion 362 installed on the upper part of the support column portion 361, and an auxiliary column portion 363 extending downward from the installation portion 362 and fixed to the base plate. Further, a handle portion 37 for performing operations such as speed adjustment and stop of the carriage 4 is provided on the installation portion 362.

[0047] The electric motor 4 is installed on the base plate 32 of the carriage 4, and transmits the output rotational driving force to at least one of the front wheels FW and the rear wheels RW through driving transmission means (not shown). Due to this rotational driving force, the wheels 34 rotate and the carriage 4 can run by itself. The electric motor 4 is supplied with power by a power supply unit (not shown). For example, a storage battery may be used as this power supply unit.

[0048] The control unit 5 is installed on the base plate and controls the start and stop of the electric motor 4, the speed adjustment of the carriage, etc. Also, it is connected through an electric wiring (not shown) to the handle portion 37, and an operator can perform operations such as speed adjustment and braking at hand.

[0049] The imaging means 1 is composed of a rail imaging means 11 for imaging the fastener VN connecting the rails TR and a front imaging means 12 for imaging the traveling direction of the carriage 4.

[0050] As shown in FIG. 6, the rail imaging means 11 is fixed in front of and above the left and right two wheels 34 constituting the front wheels FW by a support arm 38 connected to the base frame 31. That is, the rail imaging means 11 is arranged at a position where it can image the rail TR on which the wheel 34 body travels from above.

[0051] The front imaging means 12 is provided on the installation portion 362 of the front frame 36 and fixed so that the imaging lens faces the traveling direction of the carriage 4.

[0052] The video data D1 captured by the rail imaging means 11 and the forward imaging means 12 is transmitted to the information processing terminal 2. When transmitting this video, the information processing terminal 2 and each imaging means 1 may be connected by an electrical wiring, or may be connected by wireless communication.

[0053] The lighting unit 6 is disposed in the vicinity of each imaging means 1. Specifically, it includes a rail lighting 61 disposed above the rail imaging means 11 to illuminate the lower part and a forward lighting 62 disposed beside the forward imaging means 12 to illuminate the front.

[0054] By the way, the inspection of the train track TO is carried out at night after the train operation has ended. Therefore, it is necessary to ensure illumination during night work. Thus, the rail lighting 61 illuminates the rail TR to be imaged to surely perform the imaging by the rail imaging means 11, and the forward lighting 62 illuminates the front of the carriage 4 so that the work can be carried out safely.

[0055] The terminal protection part 7 is in the shape of a rectangular box and is installed on the base plate 32. It houses the information processing terminal 2 equipped with the fastener detection means 21 and the relaxation determination means 22 inside, and can protect the information processing terminal 2 from impacts, rain, etc. Further, the information processing terminal 2 housed inside can transmit the information from the relaxation determination means 22 to an external terminal (a terminal held by a worker or a terminal operated by a supervisor monitoring the work) by wireless communication.

[0056] Furthermore, the information processing terminal 2 is equipped with a GPS (Global Positioning System) function, so that in the inspection of the long track TO to be inspected, the current position can always be notified to the external terminal. This position information can also be collated with the video data D1 obtained from the forward imaging means 12.

[0057] [3. About the method of inspecting the track] Next, a method P for inspecting a track for train running using the track inspection device V will be described with reference to the drawings. As shown in FIGS. 3 to 5, the track TO to be inspected is previously marked with a mating mark PM for determining the relaxation of the fastener VN at the fastening part.

[0058] The track inspection method P is roughly divided into two processes: an AI learning process S1 that captures the track TO to be inspected in advance and learns the detection of fasteners VN and the state of no abnormalities in the track TO, and a track inspection process S2 that actually travels on the track TO using the track inspection device V and inspects whether there is any loosening of the fasteners VN of the track TO or any abnormalities around the track TO.

[0059] As shown in FIG. 7, the AI learning process S1 is a preparation process to be carried out before inspection, and consists of a reference video data capturing process S1-1, a reference video data storage process S1-2, and a fastener detection learning process S1-3.

[0060] The reference video data capturing process S1-1 is a process of capturing the track TO to be inspected in advance. Specifically, the track inspection device V is installed on the track TO to be inspected, and an operator rides on it and travels the same route as the actual inspection. At this time, two rail imaging means 11 mounted on the track inspection device V perform imaging from above the two rails TR. At this time, the rail imaging means 11 is arranged to image the rail TR from above by the track inspection device V, and when traveling the same route, the imaging angle can inevitably be the same each time. The imaging data captured by the rail imaging means 11 is transmitted as reference video data D2 to the fastener detection means 21 of the information processing terminal 2 and stored in the reference video data storage unit 212.

[0061] In addition, the front imaging means 12 may perform imaging simultaneously for the purpose of verification work with the position information obtained from the GPS function provided in the information processing terminal 2. In this case, the imaging data captured by the front imaging means 12 is transmitted to the functional part having the GPS function of the information processing terminal 2, and the position information obtained from the GPS is linked to the imaging data captured by the front imaging means 12, which can be used to identify the location where the fastener VN is loose during inspection or the location where a defect is found. Also, the front imaging means 12 can obtain normal state imaging data by transmitting it to the fastener detection means 21 in the same way as the imaging data captured by the track imaging means 11, and can be used for detecting defects in the subsequent defect detection process 213c. At this time, the imaging data obtained from the front imaging means 12 is transmitted to the fastener detection means 21 as the reference video data D2 together with the imaging data of the track imaging means 11 and stored in the reference video data storage unit 212.

[0062] The reference video data storage step S1-2 is a step of storing the reference video data D2 transmitted from the imaging means 1 by the fastener detection means 21 of the information processing terminal 2. Specifically, the video reception unit 211 of the fastener detection means 21 receives the reference video data D2 transmitted from the imaging means 1. The received reference video data D2 is stored by the reference video data storage unit 212.

[0063] The fastener detection learning step S1-3 is a step of performing learning for detecting the fastener VN from the reference video data D2 stored in the reference video data storage unit 212. Specifically, it is performed by causing the learning AI constituting the fastener detection means 21 to recognize the shape of the fastener VN.

[0064] The fastener detection learning process S1-3 is performed by the fastener extraction unit 213 of the fastener detection means 21, and this process becomes the reference video data learning process 213a described above. That is, it is a process of teaching the learning AI to correctly detect the fastener VN photographed in the reference video data D2 by recognizing the shape of the fastener VN and extract and generate it as the still image data G1. At this time, the generated still image data G1 may be transmitted to the relaxation determination means 22 as the reference still image data G2 used when performing relaxation determination in a later process. At this time, the reference still image data G2 transmitted to the relaxation determination means 22 is image data in a state where the mating mark PM previously marked on the fastening part appears in a straight line without shifting, as shown in FIGS. 3 and 4.

[0065] Also, at the same time as detecting the fastener VN, the AI is taught to recognize the state around the track TR, which is the part other than the fastener VN recorded in the reference video data D2, as a normal state. Also, when the imaging data captured by the forward imaging means 12 is included in the reference video data D2, the AI is taught from this imaging data as a normal state in front of the track inspection device V. Through this learning, the AI can be made to recognize the normal state that serves as the reference for defect detection in the defect detection process 213c.

[0066] By completing the AI learning process S1 described above, the track TO to be inspected in advance is photographed, and the process of preparing for inspection to learn the detection of the fastener VN and the state without abnormalities in the track TO is completed. Next, the track inspection process S2 will be described, in which the track inspection device V is actually used to travel on the track TO to inspect whether there is any relaxation of the fastener VN on the track TO or any abnormalities around the track TO.

[0067] As shown in FIG. 8, the track inspection process S2 consists of five processes: a video data acquisition process S2-1, a still image data generation process S2-2, a fastener relaxation determination process S2-3, a defect detection process S2-4, and a relaxation and defect notification process S2-5.

[0068] The video data acquisition step S2-1 is a step of acquiring video data D1 obtained by photographing the rail TR and the front of the travel while the track inspection device V travels on the track TO to be inspected by the imaging means 1. Specifically, the track inspection device V is installed on the track TO to be inspected, and an operator rides on it and travels on the track TO. While traveling, a video obtained by photographing the rail TR by the rail imaging means 11 and a video obtained by photographing the front of the travel and the inspection state by the front imaging means 12 are acquired as the video data D1.

[0069] At this time, the route for inspection is determined in advance, and it is performed so as to coincide with the route in the reference data photographing step S1-1. By doing so, it becomes possible to compare with the normal state learned by the AI from the photographed data taken in the reference video data photographing step S1-1, and in the inspection of the track TO, not only the loosening determination of the fastener VN but also the defects in the vicinity of the rail TR and the travel route can be detected.

[0070] Also, in the video data acquisition step S2-1, the front imaging means 12 simultaneously performs the front photographing at the time of inspection. The photographed data taken by the front imaging means 12 is stored as a recording video at the time of inspection or used for defect detection in the defect detection step S2-4 described later in the same manner as the video data D1.

[0071] The video data D1 photographed by the imaging means 1 is transmitted in real time to the information processing terminal 2 mounted on the track inspection device V. The information processing terminal 2 sequentially processes the received video data D1 in the next step.

[0072] The still image data generation step S2-2 is a step of generating still image data G1 by detecting only the fastener VN from the video data D1 acquired in the video data acquisition step S2-1. Specifically, the video data D1 transmitted from the rail imaging means 11 is received by the video receiving unit 211 of the fastener detection means 21 and sent to the fastener extraction unit 213. The fastener extraction unit 213 detects the fastener VN from the intermittently transmitted video data D1 and generates still image data G1 so as to cut out the detected fastener VN.

[0073] The process of generating this still image data G1 is performed as a fastener extraction process 213b by the fastener extraction unit 213 of the fastener detection means 21. That is, the fastener detection means 21 has learned in advance by the reference video data learning process 213a whether it is a fastener VN from the shape, so that the fastener VN can be detected in real time from the video data D1 intermittently received from the rail imaging means 11, and the still image data G1 can be extracted and generated. The generated still image data G1 is transmitted to the relaxation determination means 22.

[0074] The fastener relaxation determination step S2-3 is a step of determining whether or not relaxation is recognized in the fastener VN by comparing the reference still image data G2 stored in advance in the reference still image storage unit 222 of the relaxation determination means 22 with the still image data G1 generated in the still image data generation step S2-2. This process is performed by the image comparison unit 223 of the relaxation determination means 22.

[0075] As shown in FIGS. 3 and 4, the reference still image data G2 is image data in which the mating mark PM marked on the structure so as to straddle the fastener VN appears as a straight line. A state in which relaxation of the fastener VN is recognized compared with this reference still image data G2 is a state in which a shift has occurred in the mating mark PM due to the rotation of the fastener VN, as shown in FIG. 5.

[0076] As shown in FIG. 8, the defect detection step S2-4 is a step of detecting defects occurring in the track TO and its surroundings and the front part of travel recorded in the video data D1 by comparing the pre-stored reference video data D2 with the video data D1 acquired in the video data acquisition step S2-1. Specifically, AI compares the reference video data D2 captured by the rail imaging means 11 and the front imaging means 12 in the reference video data capturing step S1-1 with the video data D1 captured by the rail imaging means 11 and the front imaging means 12 in the video data acquisition step S2-1. When a difference is recognized in the comparison, the location where the difference occurs is detected as a defect. The defect detection step S2-4 is executed as a defect detection process 213c by the fastener extraction unit 213 of the fastener detection means 21.

[0077] The defect detection step S2-4 can detect defects by comparing the video taken at the same viewing angle as the video pre-learned by the learning AI as a reference with any target with the reference video data D2. The comparison can detect defects.

[0078] The relaxation and defect notification step S2-5 is a step of transmitting and notifying the relaxation information A generated when the relaxation of the fastener VN is recognized in the fastener relaxation determination step S2-3 and the defect information B obtained in the defect detection step S2-4 to the terminal device held by the worker. The relaxation information A is transmitted to the terminal device held by the worker by the relaxation notification unit 224 of the relaxation determination means 22. The defect information B is transmitted to the terminal device held by the worker by the fastener detection means 21.

[0079] The track inspection method P can quickly perform the inspection work of the track TO, which was conventionally visually inspected by a large number of workers for the deviation of the alignment mark PM, while driving on the vehicle that can travel on the track TO by using the track inspection device V equipped with the fastener relaxation determination system M. That is, it is possible to shorten the time related to the inspection and eliminate human errors.

[0080] In addition, by providing the fastener detection means 21 with a learning AI, the fastener VN can be detected in real time from the video data D1 taken at the time of inspection and generated as the still image data G1, and the relaxation determination can be performed promptly. In addition, by comparing the reference video data D2 with the video data D1 obtained at the time of inspection by the learning AI, abnormalities within the shooting angle of the imaging means 1 can be detected as defects. Therefore, it can also contribute to finding defects that were overlooked by the conventional inspection method.

[0081] The description of the above embodiments is an example of the present invention, and the present invention is not limited to the above embodiments. Therefore, even if it is other than the above-described embodiments, various changes can be made according to the design and the like as long as it does not deviate from the technical idea of the present invention. In addition, the various effects described above are merely an enumeration of the preferable effects resulting from the present invention, and the effects of the present invention are not limited to those described in this embodiment.

Explanation of Reference Numerals

[0082] M Fastener Relaxation Judgment System 1 Imaging means 2 Information processing terminal 21 Fastener detection means 22 Relaxation judgment means V Rail inspection device 3 Cart 4 Electric motor 5 Control unit 6 Lighting unit 7 Terminal protection unit 8 Seat part P Rail inspection method S1 AI learning process S2 Rail inspection process TO Rail TR Rail VN Fastener D1 Video data D2 Reference video data G1 Still image data G2 Reference still image data A Relaxation information B Defect information

Claims

1. A system for determining the loosening of a fastener at a fastening part of a structure, comprising: imaging means for photographing the structure to be inspected; fastener detection means for detecting a fastener from video data photographed by the imaging means; loosening determination means for determining the loosening state of the fastener detected by the fastener detection means; The fastener detection means uses an AI (Artificial Intelligence) that has been trained to detect the fastener using reference video data photographed in the same field of view as the video data in advance, detects the fastener from the video data and generates still image data recording the fastener, The loosening determination means compares the still image data with reference still image data obtained by imaging a state in which fastening by the fastener is in good condition, and determines the loosening state of the fastener. A fastener loosening determination system characterized by this.

2. The imaging means is mounted on a vehicle that can be towed by a self-propelled or other self-propelled vehicle, A track inspection device comprising the fastener loosening determination system according to claim 1, characterized in that a plurality of the fasteners provided on the structure are photographed as the vehicle travels.

3. The vehicle travels on a track for train travel, The imaging means photographs the fasteners for connecting and fixing the rails constituting the track and the periphery of the track as the video data, The fastener detection means detects a defect determined by comparison of the fastener with the reference video data from the video data. A track inspection method using a track inspection device comprising the loosening determination system according to claim 2. ​ ​ ​ ​ ​ ​ ​

Images