Diagnostic system

Abstract

This provides a diagnostic system that can automatically detect abnormalities in the dynamic characteristics of control cables. [Solution] The diagnostic system is a system for detecting abnormalities in the U-shaped hanging portion of an elevator control cable, and comprises a camera positioned inside the hoistway to capture an image of the moving portion between the R portion, which is the lower end of the U-shaped hanging portion of the control cable, and the car-side end, and a diagnostic device capable of communicating with the camera. The camera captures a diagnostic image that includes at least a portion of the moving portion while the car is moving in the upward or downward direction. The diagnostic device comprises a processing unit that extracts feature points included in the image of the moving portion in the diagnostic image, and a detection unit that detects abnormalities in the dynamic characteristics of the control cable while the car is moving, based on the feature points extracted by the processing unit.

Description

Technical Field

[0001] The present disclosure relates to a diagnostic system for an elevator control cable.

Background Art

[0002] Patent Document 1 discloses an elevator inspection system. In this inspection system, a camera is provided under the car. The video taken by the camera can be viewed from the outside. During regular inspections and the like, an operator can use the camera to view the video of the dynamic characteristics of the control cable.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, according to the inspection device described in Patent Document 1, it is necessary for an operator to view the video of the camera during regular inspections. Therefore, the operator needs to spend a lot of time for the inspection.

[0005] The present disclosure has been made to solve the above problems. The object of the present disclosure is to provide a diagnostic system that can automatically detect abnormalities in the dynamic characteristics of a control cable.

Means for Solving the Problems

[0006] The diagnostic system according to this disclosure is a system for detecting abnormalities in the portion of a control cable that connects an elevator car and a control panel, which hangs down in a U-shape between the car-side end fixed to the car and the control panel-side end. The system comprises a camera positioned inside the elevator shaft to capture an image of the moving portion between the R portion, which is the lower end of the U-shaped hanging portion of the control cable, and the car-side end, and a diagnostic device capable of communicating with the camera. The camera captures a diagnostic image that includes at least a portion of the moving portion while the car is moving in the upward or downward direction. The diagnostic device comprises a processing unit that extracts feature points included in the image of the moving portion in the diagnostic image, and a detection unit that detects abnormalities in the dynamic characteristics of the control cable while the car is moving, based on the feature points extracted by the processing unit. [Effects of the Invention]

[0007] According to this disclosure, the diagnostic device automatically detects abnormalities in the dynamic characteristics of the control cable based on diagnostic images captured by a camera, without requiring visual inspection by a worker. [Brief explanation of the drawing]

[0008] [Figure 1] This is a diagram showing the configuration of an elevator to which the diagnostic system in Embodiment 1 is applied. [Figure 2] This figure shows an example of a diagnostic image taken by the diagnostic system in Embodiment 1. [Figure 3] This figure shows an example of a diagnostic image taken by the diagnostic system in Embodiment 1. [Figure 4] This is a functional block diagram of the diagnostic system in Embodiment 1. [Figure 5] This figure shows an example of a diagnostic image taken by the diagnostic system in Embodiment 1. [Figure 6] This figure shows a graph of the slope calculated by the diagnostic system in Embodiment 1. [Figure 7] This figure shows an example of a diagnostic image taken by the diagnostic system in Embodiment 1. [Figure 8] This figure shows a graph of the slope calculated by the diagnostic system in Embodiment 1. [Figure 9] This is a flowchart showing the operation of the diagnostic system in Embodiment 1. [Figure 10] This figure shows a diagnostic image taken by the diagnostic system in Embodiment 2. [Figure 11] This is a hardware configuration diagram of the diagnostic device of the diagnostic system in Embodiments 1 and 2. [Modes for carrying out the invention]

[0009] The embodiments for implementing this disclosure will be described with reference to the attached drawings. In each drawing, the same or corresponding parts are denoted by the same reference numerals. The explanation of such parts will be simplified or omitted as appropriate.

[0010] Embodiment 1. Figure 1 is a diagram showing the configuration of an elevator to which the diagnostic system in Embodiment 1 is applied. Figures 2 and 3 show examples of diagnostic images taken by the diagnostic system in Embodiment 1.

[0011] In Figure 1, the elevator system 80 is installed in building 90. The hoistway 91 runs through each floor of building 90. The machine room 92 is located directly above the hoistway 91. The hoisting machine 81 of the elevator system 80 is located in the machine room 92. The main rope 82 is wound around the hoisting machine 81. The elevator car 83 is suspended from the main rope 82 inside the hoistway 91. The control panel 84 is located in the machine room 92. The control panel 84 can control the elevator system 80 as a whole.

[0012] The control cable 85 is one or more cables that bundle power lines, signal lines, etc. Hereinafter, the case where the control cable 85 is one or one of a plurality of control cables 85 will be described. The control cable 85 connects the car 83 and the control panel 84. Each device of the control panel 84 and the car 83 communicates via the control cable 85. The control cable 85 is fixed by the car-side end 85a and the fixed-side end 85b in order to connect to the control panel 84 from the connection part with the car 83.

[0013] The car-side end 85a is the part of the control cable 85 that is fixed at the lower part of the car 83. The control cable 85 hangs downwards from the car-side end 85a. The fixed-side end 85b is the end on the control panel 84 side of the control cable 85 and is the part fixed to the structure of the hoistway 91. The fixed-side end 85b is located between the car-side end 85a and the control panel 84 in the control cable 85. The control cable 85 hangs downwards from the fixed-side end 85b.

[0014] The control cable 85 hangs down in a U-shape in the part between the car-side end 85a and the fixed-side end 85b. The control cable 85 is folded back from below towards the car-side end 85a at the R part 85c which is the lower end of the part hanging down in a U-shape. The moving part 85d is the part between the car-side end 85a and the R part 85c of the control cable 85.

[0015] The remote monitoring device 86 is provided in the machine room 92 and can communicate with the control panel 84. The information center device 87 is provided in a building different from the building 90, such as the building of a company for maintenance management. The information center device 87 can communicate with the remote monitoring device 86 via a network.

[0016] When the hoist 81 rotates according to a command from the control panel 84, the main rope 82 moves. Following the movement of the main rope 82, the car 83 moves in the hoistway 91 in the upward or downward direction. The position of the car-side end 85a of the control cable 85 moves in the upward or downward direction following the movement of the car 83.

[0017] At this time, the vertical position of the R portion 85c in the control cable 85 moves as the car-side end 85a moves. For example, a portion of the control cable 85 that was located between the R portion 85c and the fixed-side end 85b in a certain state becomes the R portion 85c and the moving portion 85d as the car 83 moves upward. When the car 83 moves downward, the portion of the control cable 85 that was at the moving portion 85d becomes the R portion 85c and further moves to the portion of the fixed-side end 85b rather than the R portion 85c.

[0018] The state in which a part of the control cable 85 including the moving portion 85d moves is also referred to as the dynamic characteristic of the control cable 85. When the car 83 moves, the control cable 85 is smoothly folded back by the R portion 85c, so that the moving portion 85d maintains a substantially straight line. In this case, the dynamic characteristic of the control cable 85 is normal.

[0019] Here, a part of the control cable 85 may be twisted or deformed. In this case, when the part becomes the R portion 85c and then moves to another part, that is, when the part passes through the R portion 85c, the control cable 85 is not smoothly folded back, and the R portion 85c moves horizontally as if it bounces up. For example, the moving portion 85d moves in a wavy manner as the R portion 85c moves. In this case, the dynamic characteristic of the control cable 85 is abnormal.

[0020] The diagnostic system 1 is a system that mechanically detects an abnormality in the dynamic characteristic of the control cable 85. The diagnostic system 1 includes a camera 2 and a diagnostic device 10.

[0021] The camera 2 captures images and videos. The video is a series of continuous images with different shooting times. The camera 2 is provided inside the hoistway 91. As an example, the camera 2 is provided at the lower part of the car 83. The camera 2 is mounted at a position facing downward and capable of capturing at least a part of the moving portion 85d. Further, as in this example, the camera 2 may be capable of capturing an image including at least a part of the moving portion 85d and the R portion 85c.

[0022] Although not shown in the diagram, camera 2 may be fixed to the structure of the elevator shaft 91. In this case, multiple cameras 2 may be installed so as to be aligned vertically along the elevator shaft 91. Even in this case, one or more cameras 2 are mounted in a position that can photograph at least a portion of the moving part 85d. When multiple cameras 2 are provided, they work together to ensure that at least a portion of the moving part 85d is photographed throughout the entire range of movement of the elevator car 83.

[0023] For example, the diagnostic device 10 is installed in the machine room 92. The diagnostic device 10 can communicate with the camera 2, the control panel 84, and the remote monitoring device 86. The functions of the diagnostic device 10 may be installed inside the control panel 84 or inside the remote monitoring device 86.

[0024] For example, during diagnostic operation, the diagnostic device 10 causes the camera 2 to capture multiple diagnostic images while the elevator car 83 is moving upward or downward without stopping. In this case, it is preferable for the elevator car 83 to move at a constant speed without stopping between the top floor and the bottom floor.

[0025] Figures 2 and 3 show examples of diagnostic images. Hereafter, in the diagnostic images, the direction from the upper left to the lower right of the page corresponds to the direction from the top to the bottom of the elevator shaft 91. The diagnostic images include at least a portion of the moving part 85d. Camera 2 continuously captures the diagnostic images as video. The diagnostic image in Figure 3 was taken when the position of the elevator car 83 was lower than that of the diagnostic image in Figure 2. Depending on the position of the elevator car 83, the distance to the R section 85c, the length of the image of the moving part 85d, etc., differ. On the other hand, regardless of the position of the elevator car 83, the image of the moving part 85d is generally linear.

[0026] The diagnostic device 10 diagnoses whether or not there is an abnormality in the dynamic characteristics of the control cable 85 based on the diagnostic image. If an abnormality in the dynamic characteristics of the control cable 85 is detected, the diagnostic device 10 notifies the information center device 87, etc., of this fact via the remote monitoring device 86. For example, the information center manages the dispatch of workers to the elevator system 80 based on the notification received by the information center device 87.

[0027] Next, we will explain the diagnostic system 1 using Figure 4. Figure 4 is a functional block diagram of the diagnostic system in Embodiment 1.

[0028] As shown in Figure 4, the diagnostic device 10 includes a communication unit 11, a command unit 12, a processing unit 13, a detection unit 14, a identification unit 15, and a notification unit 16. The communication unit 11 communicates with devices such as the camera 2, the control panel 84, and the remote monitoring device 86 to transmit and receive information.

[0029] The command unit 12 transmits a command to the camera 2 to capture diagnostic images under specific conditions. The command unit 12 also instructs the control panel 84 to execute the operation for capturing diagnostic images. During the operation for capturing diagnostic images, the elevator car 83 moves at a generally constant speed without stopping, either from the top floor to the bottom floor or from the bottom floor to the top floor. The command unit 12 causes the camera 2 to continuously capture diagnostic images during the operation for capturing diagnostic images.

[0030] The processing unit 13 performs image processing on the diagnostic image to extract feature points included in the image of the moving portion 85d in the diagnostic image. The detection unit 14 detects abnormalities in the dynamic characteristics of the moving portion 85d of the control cable 85 based on the feature points extracted by the processing unit 13. The function of the detection unit 14 may be divided into a pre-processing unit 14a that performs pre-processing for detection and a determination unit 14b that determines whether or not there is an abnormality.

[0031] When the detection unit 14 detects an abnormality in the dynamic characteristics, the identification unit 15 identifies the location of the part in the control cable 85 that caused the abnormality. Several methods may be applied to the process by which the identification unit 15 identifies the location of the part causing the abnormality.

[0032] In the first example of the identification process, the identification unit 15 obtains position information of the elevator car 83 from the control panel 84 at the time when the detection unit 14 detects an abnormality in the dynamic characteristics, that is, at the time when the diagnostic image in which the abnormality was detected was taken. For example, the identification unit 15 may identify the time when the diagnostic image was taken as the time indicating the time of detection, and obtain position information of the elevator car 83 at that time. Since the portion of the control cable 85 that is located in the R portion 85c changes depending on the position of the elevator car 83, the position of the elevator car 83 basically corresponds to the portion of the control cable 85 that is located in the R portion 85c. The identification unit 15 identifies the position of the control cable 85 that was in the R portion 85c at the time of detection as the position of the causative part.

[0033] The diagnostic device 10 may also acquire the position information of the elevator car 83 from the control panel 84 at the time when the detection unit 14 detects an abnormality in the dynamic characteristics, using that time as the detection point.

[0034] A second example of the identification process can be performed when camera 2 is located at the bottom of cage 83 and camera 2 is capturing a diagnostic image that includes an image of R portion 85c. In this second example, the identification unit 15 estimates the distance from cage 83 to R portion 85c at the time of detection based on the image of R portion 85c captured in the diagnostic image at the time of detection. For example, the identification unit 15 estimates the distance from the size of the image of R portion 85c in the diagnostic image. Based on this distance, the identification unit 15 identifies the position of the control cable 85, which was R portion 85c at the time of detection, as the position of the causative part.

[0035] If the detection unit 14 detects an abnormality in the dynamic characteristics of the control cable 85, the notification unit 16 notifies the remote monitoring device 86 and the information center device 87 that the abnormality has been detected.

[0036] Next, an example of the processing performed by the diagnostic device 10 will be explained using Figures 5 to 8. Figure 5 shows an example of a diagnostic image taken by the diagnostic system in Embodiment 1. Figure 6 shows a graph of the slope calculated by the diagnostic system in Embodiment 1. Figure 7 shows an example of a diagnostic image taken by the diagnostic system in Embodiment 1. Figure 8 shows a graph of the slope calculated by the diagnostic system in Embodiment 1.

[0037] Figures 5 and 6 show information when there is no abnormality in the dynamic characteristics of the control cable 85. In this example, for the diagnostic image shown in Figure 5, the processing unit 13 first performs edge extraction processing of the control cable 85 to extract the edge portion of the control cable 85 from the diagnostic image. For example, the processing unit 13 extracts the boundary between the image of the control cable 85 and other parts as an edge portion based on differences in brightness, etc., between the image of the control cable 85 and the background portion.

[0038] Furthermore, the processing unit 13 may extract grooves or the like that provided parallel to the longitudinal direction of the control cable 85 on the flat surface of the control cable 85 as edge portions. In this case, since the brightness of the grooves of the control cable 85 and the surrounding area are known to some extent, the edge portions can be extracted more accurately and easily compared to the method of separating the boundary between the end of the control cable 85 and the background portion.

[0039] Subsequently, the processing unit 13 extracts multiple feature points P at arbitrary intervals from points on the edge portion. In this case, the feature points P are points included in the image of the moving portion 85d. Note that the feature points P only need to be extracted in the region of the image of the moving portion 85d that does not include the vicinity of the R portion 85c. Then, the processing unit 13 determines and extracts any two feature points P1 and P2 from among the multiple feature points P.

[0040] Feature points P1 and P2 may be adjacent to each other, or they may be separated by another feature point. The choice of which two points to extract should depend on the situation to be diagnosed. The closer the two feature points are, the more detailed the movement of the control cable 85 can be diagnosed. The farther the two feature points are, the more the overall movement of the control cable 85 can be diagnosed.

[0041] After feature points are extracted, the preprocessing unit 14a of the detection unit 14 calculates the slope of the line segment L connecting two feature points within the coordinate system set in the diagnostic image. This coordinate system can be any as long as it is common among multiple diagnostic images. In this example, the coordinate system is set so that the slope obtained in the linear moving portion 85d is approximately 0.

[0042] The determination unit 14b of the detection unit 14 determines that there is an abnormality in the dynamic characteristics of the control cable 85 if the absolute value of the slope calculated by the preprocessing unit 14a exceeds a predetermined slope threshold. The determination unit 14b's determination of an abnormality means that the detection unit 14 has detected an abnormality in the dynamic characteristics of the control cable 85.

[0043] The detection unit 14 may use any positive value, such as a fixed value or a variable value, as the slope threshold. The slope threshold may be a fixed value set in advance. The slope threshold may be the absolute value of the arithmetic mean of the slopes of the calculated multiple line segments L.

[0044] The slope threshold may be a value corresponding to the distance between the cage 83 and the R-section 85c at the time the diagnostic image was taken. In this case, the detection unit 14 may use a smaller value as the slope threshold as the distance between the cage 83 and the R-section 85c is greater at the time the image was taken. In this example, the closer the cage 83 and the R-section 85c are, the larger the image of the R-section 85c and the larger the amplitude of the image of the undulating moving portion 85d in the diagnostic image.

[0045] As another example, the slope threshold may be a value corresponding to the distance from the region where the two feature points are located to the image of the R portion 85c in the diagnostic image. In this case, the detection unit 14 may use a larger value as the slope threshold as the distance from the region where the two feature points are located to the image of the R portion 85c is greater, or it may use a smaller value as the slope threshold.

[0046] The processing unit 13 extracts any number of pairs of feature points. The detection unit 14 determines whether or not there is an anomaly in the extracted pair of feature points. For example, the processing unit 13 and the detection unit 14 repeat the extraction of pairs of feature points so that at least once a feature point that exists in the region of the image of the moving portion 85d that should be judged is extracted.

[0047] As shown in the example in Figure 6, for example, the processing unit 13 repeats the process of extracting two adjacent feature points so that all feature points are extracted at least once. In this example, feature points located at both ends of a group of feature points are extracted only once, while feature points located in between are extracted twice. The vertical and horizontal axes of the graph in Figure 6 represent a coordinate system conveniently set in the diagnostic image. In this example, the x-coordinate is set along the moving portion 85d. The closer to the cage end 85a, the smaller the x-coordinate. The points plotted in Figure 6 correspond to feature points P.

[0048] In this example, as shown in Figure 5, there are no abnormalities in the dynamic characteristics of the control cable 85, and the moving portion 85d is approximately linear. As shown in Figure 6, for the multiple line segments L that connect the multiple feature points P, the absolute slope of each line segment L is below the slope threshold. In this case, the detection unit 14 does not detect any abnormalities.

[0049] Figures 7 and 8 represent similar information to Figures 5 and 6, and show information when there is an abnormality in the dynamic characteristics of the control cable 85. As shown in Figure 7, the portion of the moving part 85d of the control cable 85 that is close to the R portion 85c is wavy and appears to be horizontally concave. In this case, as shown in Figure 8, the slope of the line segment L1 connecting feature points P3 and P4 is significantly different from that of other line segments L. The absolute value of the slope of line segment L1 exceeds the slope threshold. In this case, the detection unit 14 detects an abnormality in the dynamic characteristics of the control cable 85.

[0050] The processing unit 13 may extract feature points using a method other than the method of extracting feature points after extracting edge portions. In an example of the alternative method, first, the processing unit 13 extracts a base feature point included in the image of the moving portion 85d in the diagnostic image. Then, the processing unit 13 extracts the following feature points as points included in the image of the moving portion 85d that are located in a specific direction and at a specific distance from the base feature point.

[0051] Next, the processing unit 13 uses the previously extracted feature point as a base point and extracts points included in the image of the moving portion 85d that are located in a specific direction and at a specific distance from the base point as the next feature point. The processing unit 13 may repeat the same process to extract feature points in a chain reaction. In this case, the processing unit 13 may extract feature points on the image of the end of the control cable 85 in the width direction, groove-like depressions along the control cable 85, etc.

[0052] Next, we will explain the operation of the diagnostic system 1 using Figure 9. Figure 9 is a flowchart showing the operation of the diagnostic system in Embodiment 1.

[0053] The flowchart in Figure 9 is initiated, for example, during a diagnostic operation that is performed periodically on the elevator system 80.

[0054] In step S01, the diagnostic device 10 starts diagnosing the dynamic characteristics of the control cable 85. Based on a command from the command unit 12, the control panel 84 causes the cage 83 to perform an operation to capture a diagnostic image.

[0055] Subsequently, in step S02, camera 2 captures video based on commands from command unit 12, that is, captures multiple diagnostic images at different times. Camera 2 transmits the captured diagnostic images to the diagnostic device 10.

[0056] Subsequently, in step S03, the processing unit 13 performs image processing to extract feature points from the diagnostic image.

[0057] Subsequently, in step S04, the detection unit 14 determines whether or not there is an abnormality in the dynamic characteristics of the control cable 85 based on the information including the extracted feature points.

[0058] If an abnormality is determined in step S04, that is, if the detection unit 14 detects an abnormality in the dynamic characteristics of the control cable 85, then the operation in step S05 is performed. In step S05, the identification unit 15 identifies the location of the problematic portion of the control cable 85.

[0059] Subsequently, in step S06, the notification unit 16 transmits information to the remote monitoring device 86 indicating that an abnormality has been detected and the location of the cause. After that, the operation of the flowchart ends. At this time, the operation for capturing diagnostic images of the cage 83 also ends. After that, the remote monitoring device 86 transmits the information received from the diagnostic device 10 to the information center device 87 at any time.

[0060] The operation in step S04 is repeated until the elevator car 83 finishes its operation to capture diagnostic images. For example, the operation in step S04 is repeated while the elevator car 83 is moving from the lowest floor to the highest floor. For example, the operation in step S04 may be repeated while the elevator car 83 is moving from the lowest floor to the highest floor and then immediately afterwards moving from the highest floor to the lowest floor. The operation in step S05 only needs to be performed when the detection unit 14 first detects an abnormality in the dynamic characteristics.

[0061] If no abnormality is detected in step S04 before cage 83 finishes its operation to capture diagnostic images, the flowchart operation ends. At this point, it may be recorded that no abnormality was detected in this diagnosis.

[0062] According to Embodiment 1 described above, the diagnostic system 1 comprises a camera 2 and a diagnostic device 10. The diagnostic device 10 has a processing unit 13 and a detection unit 14 as its functions. The diagnostic device 10 extracts feature points from the diagnostic image captured by the camera 2 and detects abnormalities in the dynamic characteristics of the control cable 85 based on these feature points. In other words, the diagnostic device 10 can automatically detect abnormalities in the dynamic characteristics of the control cable 85 without visual inspection by a worker.

[0063] Furthermore, conventionally, the dynamic characteristics of the control cable 85 can sometimes be diagnosed by having one worker enter the pit of the elevator shaft 91 and another worker move the elevator car 83 from the lower floor to the top floor. The worker in the pit visually checks for any abnormalities in the dynamic characteristics of the control cable 85. In this case, at least two workers are required. Also, it is not possible to start the elevator car 83 from the lowest floor. It is also difficult to diagnose abnormalities in the dynamic characteristics when the elevator car 83 is moving in the downward direction. In the diagnostic system 1 of this embodiment 1, worker confirmation and dispatch of workers to the site are unnecessary. In addition, the dynamic characteristics can be diagnosed whether the elevator car 83 is moving in the upward or downward direction between the lowest and top floors. In this way, the diagnostic system 1 can perform diagnoses of types that could not be confirmed by conventional methods at a different time than conventional methods. Also, since it is not necessary to dispatch workers, diagnoses that were previously performed only once a year can be performed at a higher frequency, such as once a month.

[0064] Furthermore, the processing unit 13 extracts two feature points. The detection unit 14 detects anomalies based on the inclination of the two feature points. Depending on the position of the cage 83 when the diagnostic image is taken, the angle of the image of the control cable 85 in the diagnostic image may change slightly. However, the image of the moving part 85d that is moving normally remains straight. Because the diagnostic device 10 detects anomalies based on the inclination of the two feature points, it can detect dynamic characteristic anomalies with high accuracy regardless of the angle of the control cable 85 in the diagnostic image.

[0065] The detection unit 14 may also calculate the difference between the slope of two feature points and the slope of the line segment L connecting two other feature points. The detection unit 14 may detect an abnormality in the dynamic characteristics of the control cable 85 if the absolute value of this difference exceeds the slope threshold. Even in this case, the diagnostic device 10 can detect the abnormality in dynamic characteristics with high accuracy, regardless of the angle of the control cable 85 shown in the diagnostic image.

[0066] Furthermore, the detection unit 14 may use different slope thresholds depending on the conditions. Specifically, the detection unit 14 may use a value corresponding to the distance between the cage 83 and the R section 85c as the slope threshold. The detection unit 14 may also use a value corresponding to the distance between the region where two feature points exist in the diagnostic image and the R section 85c as the slope threshold. Abnormalities in the dynamic characteristics of the control cable 85 occur when a kinked or deformed portion passes through the R section 85c. Therefore, the control cable 85 vibrates most strongly at the R section 85c. The vibration of the control cable 85 decreases the closer it is to the cage 83. On the other hand, the amplitude of the image of the control cable 85 decreases the further it is from the camera 2. By setting the slope threshold to an appropriate value while these factors overlap, the diagnostic device 10 can detect abnormalities in dynamic characteristics with high accuracy.

[0067] Furthermore, the diagnostic device 10 is further equipped with a specific unit 15 as a function. The dynamic characteristics of the control cable 85 become abnormal when a kinking or deformed part passes through the R section 85c. The specific unit 15 identifies the position of the part that was present in the R section 85c when the abnormality in the dynamic characteristics occurred as the position of the part causing the problem. Specifically, the specific unit 15 may identify the position of the part causing the problem based on the position information of the cage 83. The specific unit 15 may also identify the position of the part causing the problem by estimating the distance between the R section 85c and the cage 83 from the image of the R section 85c captured in the diagnostic image. Therefore, when an abnormality in the dynamic characteristics is detected, workers can quickly find the part causing the problem.

[0068] Although not shown in the figures, the processes performed by the processing unit 13 and the detection unit 14 do not have to be those shown in Figures 5 to 8. As a variation of this process, a first image and a second image taken at different times are used. In this case, an anomaly in the dynamic characteristics at the time the second image was taken, which is later than the time the first image was taken, can be detected.

[0069] In the first modified example, camera 2 takes a first image as a diagnostic image, and then takes a second image as a diagnostic image. Processing unit 13 extracts a first feature point included in the image of the moving portion 85d in the first image. Processing unit 13 extracts a second feature point included in the image of the moving portion 85d in the second image.

[0070] The first feature point is a point included in the image of the moving portion 85d in the first image, and is a point with arbitrarily determined coordinates. The processing unit 13 records the position of the extracted first feature point in the moving portion 85d, which is its relative position to the moving portion 85d. The processing unit 13 extracts a second feature point, which is a point included in the image of the moving portion 85d in the second image, and which has the same relative position as the extracted first feature point in the moving portion 85d. That is, the processing unit 13 defines the point obtained by tracking the first feature point in the moving portion 85d in the second image as the second feature point.

[0071] The detection unit 14 detects an abnormality in the dynamic characteristics of the control cable 85 when the difference between the position of the first feature point and the position of the second feature point exceeds a predetermined movement threshold. Specifically, the detection unit 14 calculates the distance between the coordinates of the first feature point and the coordinates of the second feature point as the difference.

[0072] In the first modified example, for instance, the movement threshold is determined based on the difference between the time the first image was taken and the time the second image was taken. In this case, the movement threshold may also be determined based on the velocity of the cage 83.

[0073] When the speed of the elevator car 83 is a predetermined speed, the distance the elevator car 83 travels from the time the first image is taken to the time the second image is taken can be calculated. A certain point in the moving portion 85d is expected to appear in the second image at a position in the direction of movement that is the distance from its position in the first image. The movement threshold is determined based on this movement distance. Specifically, the movement threshold can be set as the value obtained by adding an acceptable disturbance value to this movement distance. Furthermore, by determining the movement distance and the movement threshold based on the speed of the elevator car 83 between the time the first image was taken and the time the second image was taken, in addition to the time the first image was taken and the time the second image was taken, the accuracy of anomaly detection can be improved.

[0074] According to the first modified example described above, the processing unit 13 extracts a first feature point from the first image and a second feature point from the second image. If there is an abnormality in the dynamic characteristics of the control cable 85, the moving portion 85d will be wavy and not straight, so the coordinates of the second feature point may differ from those of the first feature point. The detection unit 14 detects the abnormality in the dynamic characteristics based on this difference in coordinates. Therefore, the diagnostic device 10 can detect the abnormality in the dynamic characteristics with high accuracy.

[0075] In a second modified example of the processing performed by the processing unit 13 and the detection unit 14, the camera 2, similar to the first modified example, captures a first image as a diagnostic image, and then captures a second image. The processing unit 13 extracts the first and second feature points, similar to the first modified example.

[0076] In the second modified example, the detection unit 14 applies optical flow technology to calculate the change from the first image to the second image as a vector quantity. Specifically, the detection unit 14 calculates a flow vector from the coordinates of the first feature point to the coordinates of the second feature point. If the direction of this flow vector in the coordinate system of the second image, which is a diagnostic image, falls outside a specified normal range, the detection unit 14 detects an abnormality in the dynamic characteristics of the control cable 85.

[0077] Since the direction of movement of the cage 83 is fixed, and the longitudinal direction of the moving part 85d is parallel to the direction of movement of the cage 83, the overall flow of change from the first image to the second image when the dynamic characteristics of the control cable 85 are in a normal state will follow the longitudinal direction of the moving part 85d, including the background. That is, when the flow vectors of each point, including the background, are obtained from the first image to the second image in a specific region including the moving part 85d, the directions of all the flow vectors will be aligned within a certain normal range.

[0078] On the other hand, when the dynamic characteristics of the control cable 85 are abnormal, the wavy portion of the moving part 85d moves in a direction perpendicular to the longitudinal direction of the moving part 85d. In this case, if the flow vector of the wavy portion is determined from the first image to the second image, the direction of the flow vector of the wavy portion will be significantly different from the direction of the other flow vectors.

[0079] According to the second modified example described above, the detection unit 14 detects abnormalities in dynamic characteristics based on these differences in flow vectors. Generally, the process of calculating changes in the image by focusing on flow vectors has a lower computational load than the process of focusing on the differences in the details of each image that makes up the image. Through this process, the diagnostic device 10 can detect abnormalities in dynamic characteristics while keeping the computational load down.

[0080] Embodiment 2. Figure 10 shows a diagnostic image taken by the diagnostic system in Embodiment 2. Parts identical or corresponding to those in Embodiment 1 are denoted by the same reference numerals. Descriptions of these parts are omitted. Furthermore, illustrations of each component of the diagnostic device 10 are omitted as appropriate.

[0081] As shown in Figure 10, in Embodiment 2, the diagnostic system 1 further includes a marker 20. The marker 20 is provided on the surface portion of the control cable 85. In particular, the marker 20 is provided on a portion that may become a movable part 85d. The camera 2 is mounted in a position where it can photograph the marker 20.

[0082] The marker 20 has a different surface condition from the moving portion 85d of the control cable 85. For example, the marker 20 is made of a material with a different light reflectivity than the surface of the control cable 85. The marker 20 may have a higher or lower reflectivity than the surface of the control cable 85. The marker 20 may include a portion that performs retroreflective reflection.

[0083] The marker 20 may be strip-shaped and attached along the control cable 85. Figure 10 shows such a marker 20. In this case, the marker 20 may have markings such as a scale indicating the distance from the cage 83.

[0084] The marker 20 may consist of multiple partial markers. These partial markers may be arranged apart from each other in the moving section 85d. The partial markers may have different shapes depending on their distance from the cage 83.

[0085] The processing unit 13 extracts points included in the image of the marker 20 in the diagnostic image as feature points. The marker 20 is located on the control cable 85. Therefore, the feature points will be included in the image of the control cable 85.

[0086] Furthermore, if the marker 20 is provided in a manner corresponding to the distance to the cage 83, the identification unit 15 may, as a third example of the identification process, identify the location of the causative part based on the image of the marker 20 in the diagnostic image. Specifically, the identification unit 15 identifies the location of the control cable 85 corresponding to the image of the marker 20 closest to the R section 85c in the diagnostic image taken at the time of detection. This location can be identified by the distance of the marker 20 from the cage 83. The identification unit 15 considers the identified location to be the location of the causative part.

[0087] According to Embodiment 2 described above, the diagnostic system 1 further includes a marker 20. Generally, the inside of the elevator shaft 91 is dark, and the color of the control cable 85 is similar to the color of the wall surface of the elevator shaft 91, which serves as the background. For this reason, it can be difficult to distinguish the image of the control cable 85 using image processing. In particular, when edge extraction processing is applied to an image showing abnormalities in the dynamic characteristics of the control cable 85, tracking the edges of the image of the control cable 85 based on differences in brightness, the edges tend to be cut off in areas where the dynamic characteristics are abnormal and cannot be tracked. In this embodiment, the diagnostic device 10 extracts feature points based on the marker 20. The marker 20 has a different surface condition from the control cable 85. For this reason, the diagnostic device 10 can extract feature points more reliably and accurately.

[0088] Furthermore, the marker 20 may consist of multiple partial markers arranged separately from each other. Even in this case, the diagnostic device 10 can extract feature points more reliably and accurately.

[0089] Furthermore, the marker 20 may be provided in a manner corresponding to the distance to the cage 83. The identification unit 15 may identify the position on the control cable 85 corresponding to the image of the marker 20 closest to the R section 85c as the location of the faulty part. This allows workers to easily identify the location of the faulty part in subsequent work.

[0090] It should be noted that the location of the marker 20 may not precisely correspond to the location of the part where the abnormality actually occurs. However, even in this case, since the location of the causative part identified by the identification unit 15 is close to the part where the abnormality actually occurs, workers can easily identify the location of the part where the abnormality actually occurred during subsequent work.

[0091] Next, an example of the hardware that makes up the diagnostic device 10 will be explained using Figure 11. Figure 11 is a hardware configuration diagram of the diagnostic device of the diagnostic system in Embodiments 1 and 2.

[0092] Each function of the diagnostic device 10 can be realized by a processing circuit. For example, the processing circuit comprises at least one processor 100a and at least one memory 100b. For example, the processing circuit comprises at least one dedicated hardware 200.

[0093] If the processing circuit comprises at least one processor 100a and at least one memory 100b, each function of the diagnostic device 10 is realized by software, firmware, or a combination of software and firmware. At least one of the software and firmware is written as a program. At least one of the software and firmware is stored in at least one memory 100b. At least one processor 100a realizes each function of the diagnostic device 10 by reading and executing the program stored in at least one memory 100b.

[0094] If the processing circuit includes at least one dedicated hardware 200, the processing circuit may be implemented as, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, or a combination thereof. For example, each function of the diagnostic device 10 may be implemented by a processing circuit. For example, each function of the diagnostic device 10 may be implemented together by a processing circuit.

[0095] For each function of the diagnostic device 10, some may be implemented by dedicated hardware 200, and others by software or firmware. For example, the function of the processing unit 13 to perform edge extraction processing may be implemented by a processing circuit as dedicated hardware 200, while functions other than the function of the processing unit 13 to perform edge extraction processing may be implemented by at least one processor 100a reading and executing a program stored in at least one memory 100b.

[0096] In this way, the processing circuit realizes each function of the diagnostic device 10 using hardware 200, software, firmware, or a combination thereof.

[0097] Although not shown in the diagram, each function of camera 2 is implemented using processing circuits equivalent to those that implement each function of diagnostic device 10.

[0098] Furthermore, at least some of the functions of the diagnostic device 10 may be implemented on a cloud server. In this case, the processing circuit is composed of multiple sub-circuits. Each of the multiple sub-processing circuits is provided on one of the multiple devices that make up the cloud server. Each of the multiple devices that make up the cloud server may be located in a different building. In this case, the functions of the diagnostic device 10 that are implemented on the cloud server communicate with the control panel 84 and the camera 2 via the network and are involved in the control of the elevator system 80 and the diagnostic system 1.

[0099] To summarize the above explanation, the possible configurations of the technology relating to this disclosure include the configurations listed below as appendices. (Note 1) A system for detecting abnormalities in the portion of a control cable that connects an elevator car to a control panel, specifically the portion that hangs down in a U-shape between the car-side end fixed to the car and the control panel-side end, A camera is provided in the elevator shaft of the aforementioned elevator, in a position capable of capturing images of the moving portion between the R-shaped lower end of the U-shaped hanging part of the control cable and the car-side end. A diagnostic device capable of communicating with the aforementioned camera, Equipped with, The camera captures a diagnostic image that includes at least a portion of the moving part of the cage while it is moving in an upward or downward direction. The diagnostic device is A processing unit for extracting feature points included in the image of the moving portion in the diagnostic image, A detection unit that detects abnormalities in the dynamic characteristics of the control cable while the cage is moving, based on the feature points extracted by the processing unit, A diagnostic system that has [the following features]. (Note 2) The processing unit extracts two feature points included in the image of the moving portion from the diagnostic image, The detection unit detects an abnormality in the dynamic characteristics of the control cable when the absolute value of the slope of the line segment connecting the two feature points extracted by the processing unit in the diagnostic image exceeds a predetermined slope threshold. The diagnostic system described in Appendix 1. (Note 3) The detection unit uses a value corresponding to the distance between the basket and the R portion at the time the diagnostic image was captured as the slope threshold. The diagnostic system described in Appendix 2. (Note 4) The detection unit uses a value corresponding to the distance between the region containing the two feature points extracted by the processing unit and the R portion in the diagnostic image as the slope threshold. The diagnostic system described in Appendix 2. (Note 5) The camera captures a first image as a diagnostic image, and captures a second image after the first image. The processing unit extracts a first feature point included in the image of the moving portion in the first image, and extracts a second feature point included in the image of the moving portion in the second image. The detection unit detects an abnormality in the dynamic characteristics of the control cable when the difference between the position of the first feature point and the position of the second feature point exceeds a predetermined threshold. The diagnostic system described in Appendix 1. (Note 6) The processing unit extracts, in the second image, a point in the moving portion that is at the same position as the first feature point extracted in the first image, as a second feature point. The diagnostic system described in Appendix 5. (Note 7) The camera captures a first image as a diagnostic image, and captures a second image after the first image. The processing unit extracts a first feature point included in the image of the moving portion in the first image, and in the second image extracts a second feature point that indicates the same position as the first feature point extracted in the first image within the moving portion. The detection unit calculates a flow vector from the coordinates of the first feature point to the coordinates of the second feature point, and detects an abnormality in the dynamic characteristics of the control cable when the direction of the flow vector in the diagnostic image deviates from a specified normal range. The diagnostic system described in Appendix 1. (Note 8) A marker is provided on the surface of the movable portion of the control cable, having a surface condition different from that of the movable portion. Furthermore, The processing unit extracts feature points included in the image of the marker in the diagnostic image. A diagnostic system as described in any one of the items from Appendix 1 to Appendix 7. (Note 9) The markers are arranged to be spaced apart in the moving portion. The diagnostic system described in Appendix 8. (Note 10) The diagnostic device is When the detection unit detects an abnormality in the dynamic characteristics of the control cable, the identification unit identifies the location of the part of the control cable that caused the abnormality in dynamic characteristics. A diagnostic system according to any one of the appendices 1 to 9, further comprising the above. (Note 11) The identifying unit identifies the position of the control cable that was R-shaped at the time of detection as the position of the causative part, based on the position information of the cage at the time of detection when the abnormality of the control cable was detected. The diagnostic system described in Appendix 10. (Note 12) The camera is located at the bottom of the basket and captures the diagnostic image including the image of the R portion. The identifying unit estimates the distance from the cage to the R portion based on the diagnostic image, and identifies the position of the control cable that was the R portion at the time the abnormality in the dynamic characteristics of the control cable was detected as the position of the causative part. The diagnostic system described in Appendix 10. (Note 13) A marker is provided on the surface of the moving portion of the control cable, having a surface condition different from that of the moving portion, and in a manner corresponding to the distance to the cage. Furthermore, The identifying unit identifies the position of the control cable corresponding to the image of the marker closest to the R portion in the diagnostic image as the position of the causative portion. The diagnostic system described in Appendix 10. [Explanation of Symbols]

[0100] 1 Diagnostic system, 2 Camera, 10 Diagnostic device, 11 Communication unit, 12 Command unit, 13 Processing unit, 14 Detection unit, 14a Pre-processing unit, 14b Judgment unit, 15 Identification unit, 16 Notification unit, 20 Marker, 80 Elevator system, 81 Hoisting machine, 82 Main rope, 83 Car, 84 Control panel, 85 Control cable, 85a Car side end, 85b Fixed side end, 85c R section, 85d Moving section, 86 Remote monitoring device, 87 Information center device, 90 Building, 91 Hoistway, 92 Machine room, 100a Processor, 100b Memory, 200 Hardware

Claims

1. A system for detecting abnormalities in the portion of a control cable that connects an elevator car to a control panel, specifically the portion that hangs down in a U-shape between the car-side end fixed to the car and the control panel-side end, A camera is provided in the elevator shaft of the aforementioned elevator, in a position capable of capturing images of the moving portion between the R-shaped lower end of the U-shaped hanging part of the control cable and the car-side end. A diagnostic device capable of communicating with the aforementioned camera, Equipped with, The camera captures a diagnostic image that includes at least a portion of the moving part of the cage while it is moving in an upward or downward direction. The diagnostic device is A processing unit for extracting feature points included in the image of the moving portion in the diagnostic image, A detection unit that detects abnormalities in the dynamic characteristics of the control cable while the cage is moving, based on the feature points extracted by the processing unit, A diagnostic system having [a certain feature].

2. The processing unit extracts two feature points included in the image of the moving portion from the diagnostic image, The detection unit detects an abnormality in the dynamic characteristics of the control cable when the absolute value of the slope of the line segment connecting the two feature points extracted by the processing unit in the diagnostic image exceeds a predetermined slope threshold. The diagnostic system according to claim 1.

3. The detection unit uses a value corresponding to the distance between the basket and the R portion at the time the diagnostic image was captured as the slope threshold. The diagnostic system according to claim 2.

4. The detection unit uses a value corresponding to the distance between the region containing the two feature points extracted by the processing unit and the R portion in the diagnostic image as the slope threshold. The diagnostic system according to claim 2.

5. The camera captures a first image as a diagnostic image, and captures a second image after the first image. The processing unit extracts a first feature point included in the image of the moving portion in the first image, and extracts a second feature point included in the image of the moving portion in the second image. The detection unit detects an abnormality in the dynamic characteristics of the control cable when the difference between the position of the first feature point and the position of the second feature point exceeds a predetermined threshold. The diagnostic system according to claim 1.

6. The processing unit extracts, in the second image, a point in the moving portion that is at the same position as the first feature point extracted in the first image, as a second feature point. The diagnostic system according to claim 5.

7. The camera captures a first image as a diagnostic image, and captures a second image after the first image. The processing unit extracts a first feature point included in the image of the moving portion in the first image, and in the second image extracts a second feature point that indicates the same position as the position extracted as the first feature point in the first image within the moving portion. The detection unit calculates a flow vector from the coordinates of the first feature point to the coordinates of the second feature point, and detects an abnormality in the dynamic characteristics of the control cable when the direction of the flow vector in the diagnostic image falls outside a specified normal range. The diagnostic system according to claim 1.

8. A marker is provided on the surface of the movable portion of the control cable, having a surface condition different from that of the movable portion. Furthermore, The processing unit extracts feature points included in the image of the marker in the diagnostic image. A diagnostic system according to any one of claims 1 to 7.

9. The markers are arranged to be spaced apart in the moving portion. The diagnostic system according to claim 8.

10. The diagnostic device is When the detection unit detects an abnormality in the dynamic characteristics of the control cable, the identification unit identifies the location of the part of the control cable that caused the abnormality in dynamic characteristics. A diagnostic system according to any one of claims 1 to 7, further comprising the above.

11. The identifying unit identifies the position of the control cable that was part R at the time of detection as the position of the causative part, based on the position information of the cage at the time of detection when the abnormality of the control cable was detected. The diagnostic system according to claim 10.

12. The camera is located at the bottom of the basket and captures the diagnostic image including the image of the R portion. The identifying unit estimates the distance from the cage to the R portion based on the diagnostic image, and identifies the position of the control cable that was the R portion at the time the diagnostic image was taken when the abnormality in the dynamic characteristics of the control cable was detected as the position of the causative part. The diagnostic system according to claim 10.

13. A marker is provided on the surface of the moving portion of the control cable, having a surface condition different from that of the moving portion, and in a manner corresponding to the distance to the cage. Furthermore, The identifying unit identifies the position of the control cable corresponding to the image of the marker closest to the R portion in the diagnostic image as the position of the causative portion. The diagnostic system according to claim 10.

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