Elevator rope inspection system and elevator rope inspection method

Abstract

To provide an elevator rope inspection system and an elevator rope inspection method capable of determining whether or not an abnormality such as adhesion of lubricating oil to a rope occurs using a captured rope image.SOLUTION: An elevator rope inspection system comprises an imaging device to take a picture of a rope arranged in an elevator hoistway, and a clarity determination unit to detect the clarity of an image transmitted from the imaging device and to determine whether or not the rope image is clear based on the clarity. If the clarity determination unit determines that the image is clear, an abnormality determination unit determines whether or not the rope has an abnormality based on the image.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an elevator rope inspection system and an elevator rope inspection method. [Background technology]

[0002] In elevator maintenance work, there is a need to mechanize the work currently performed by inspectors in order to improve the safety of on-site work. Also, in order to maintain a huge number of elevators, it is necessary to improve the efficiency of inspection work. To meet these needs, it is necessary to install cameras inside the elevator tower and mechanize the inspections that have traditionally been performed visually by inspectors.

[0003] Patent Document 1 discloses an elevator system equipped with an image analysis system for elevator maintenance. In Patent Document 1, the elevator system includes a car in a hoistway, a camera, a network, and an image analysis system that communicates with the camera via the network. The image analysis system compares a current image captured by the camera with a reference image to detect differences, and notifies the user of maintenance information based on the difference image. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] US Patent Application Publication No. 2018 / 0346286 Summary of the Invention [Problem to be solved by the invention]

[0005] Incidentally, as elevators are used for a long time, dust and other particles adhere to the lubricating oil that has soaked into the ropes, causing the oil to stick to the surface of the ropes.

[0006] In contrast, the technology disclosed in Patent Document 1 has a problem in that if oil adheres to the rope, it is not determined to be abnormal.

[0007] Furthermore, a clear image may not be obtained due to shaking of the car caused by vibration of the car, swinging of the rope, or out-of-focus due to improper focus adjustment of the imaging device. In such cases, an accurate judgment result may not be obtained.

[0008] Therefore, the present invention provides an elevator rope inspection system and an elevator rope inspection method that can use captured rope images to determine whether the images are clear. [Means for solving the problem]

[0009] In order to solve the above problems and achieve the object of the present invention, the elevator rope inspection system of the present invention includes an imaging device that captures an image of a rope placed in an elevator shaft. The system also includes a clarity determination unit that detects the clarity of the image transmitted from the imaging device and determines whether the image of the rope is clear based on the clarity. Based on the determination of clarity, the system determines whether there is an abnormality in the rope.

[0010] The elevator rope inspection system of the present invention photographs the rope placed in the elevator shaft, detects the clarity of the image transmitted from the imaging device, and determines whether the image of the rope is clear based on the clarity. If the image is determined to be clear, it determines whether there is an abnormality in the rope based on the image. [Effects of the Invention]

[0011] According to the present invention, it is possible to determine whether or not an abnormality has occurred in the rope. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a schematic configuration diagram of an elevator to which a rope inspection system according to an embodiment of the first embodiment of the present invention is applied. [Figure 2] FIG. 2 is a block diagram showing the configuration of a control system of the rope inspection system according to the first embodiment of the present invention. [Figure 3] 1 is a flowchart showing a rope inspection method according to a first embodiment of the present invention. [Figure 4] FIG. 10 is a schematic configuration diagram of an elevator 200 to which a rope inspection system 100 according to a second embodiment of the present invention is applied. [Figure 5] FIG. 10 is a block diagram showing the configuration of a control system of a rope inspection system 100 according to a second embodiment of the present invention. [Figure 6] 10 is a flowchart showing a rope inspection method according to a second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0013] An example of an elevator rope inspection system and a rope inspection method according to an embodiment of the present invention will be described below with reference to the drawings. Note that the present invention is not limited to the following example. In each of the drawings described below, common components are assigned the same reference numerals.

[0014] 1. First embodiment 1-1. Configuration of elevator rope inspection system Fig. 1 is a schematic configuration diagram of an elevator to which a rope inspection system according to a first embodiment of the present invention (hereinafter referred to as this embodiment) is applied. Fig. 2 is a block diagram showing the configuration of a control system of the rope inspection system according to this embodiment.

[0015] As shown in FIG. 1, the elevator 1 of this embodiment includes a car 5 that moves up and down in a hoistway 7, a rope 6, and a rope inspection system 10.

[0016] [Elevator shaft] The elevator shaft 7 is a space for the elevator car 5 to ascend and descend, and is provided vertically through each floor inside the building. Guide rails (not shown) that guide the elevator car 5 as it ascends and descends are attached to the inner wall surface of the elevator shaft 7. In addition, landing doors (not shown) that lead to each floor are provided on the wall surface of the elevator shaft 7 at height positions corresponding to each floor.

[0017] [Car] The car 5 is connected to a counterweight (not shown) via a rope 6, and moves up and down within the hoistway 7. The car 5 is guided by guide rails (not shown) provided on the wall surface within the hoistway 7, and moves up and down within the hoistway 7. As will be described later, a car door (not shown) is provided on the front of the car 5 at a position corresponding to the landing door, and when the car 5 stops at each floor, the car door and landing door open, allowing people and luggage to get on and off the car 5.

[0018] [rope] The rope 6 has a middle portion wound around a pulley (not shown) below the car 5, and is connected to a hoist and a counterweight (not shown). The rope 6 is wound up by the hoist (not shown), causing the car 5 to rise and fall.

[0019] [Rope inspection system] The rope inspection system 10 includes an imaging device 2, an image processing device 3, and an output device 4.

[0020] The imaging device 2 is fixed in a position within the hoistway 7 where it can capture an image of the rope 6, and in this embodiment, it is fixed to the bottom of the hoistway 7 (near the pit). The installation location of the imaging device 2 is not limited to the bottom of the hoistway 7, and various changes are possible, such as on the side wall of the hoistway 7 or near the ceiling. The imaging device 2 is connected to the image processing device 3 by wired or wireless connection. The imaging device 2 captures an image of the rope 6 at a predetermined timing, and image data of the image captured by the imaging device 2 is transmitted to the image processing device 3.

[0021] As the imaging device 2, in addition to a commonly used visible light camera, a camera that captures other wavelengths such as near infrared, mid infrared, or far infrared can be used.

[0022] The image processing device 3 performs predetermined image processing on the image information transmitted from the imaging device 2 and determines whether or not there is an abnormality in the rope 6. In this embodiment, the image processing device 3 is installed near the imaging device 2 in the elevator shaft 7, but it may also be installed in a remote location such as an elevator management company, and various modifications are possible, such as being configured integrally with the output device 4. The image processing device 3 is connected to the imaging device 2 and the output device 4 by wired or wireless connection, and transmits and receives data between the imaging device 2 and the output device 4.

[0023] As shown in Fig. 2, the image processing device 3 includes a clarity determination unit 31 and an abnormality determination unit 32. The clarity determination unit 31 analyzes the image of the rope 6 received from the imaging device 2 and determines whether the captured image of the rope 6 is clear. The abnormality determination unit 32 determines whether an abnormality has occurred in the rope 6 when the clarity determination unit 31 determines that the image of the rope 6 is clear. A rope inspection method including the determination method in the clarity determination unit 31 and the determination method in the abnormality determination unit 32 will be described in detail later.

[0024] The output device 4 is a device that outputs the determination result regarding abnormalities in the rope 6 transmitted from the image processing device 3. The output device 4 is connected to the image processing device 3 by wireless or wired connection, and transmits and receives data to and from the image processing device 3. The output device 4 may be, for example, a personal computer operated by a manager at a management company or the like, but is preferably configured as a personal terminal such as a mobile phone terminal, smartphone, or tablet terminal that is easy for the maintenance worker P to carry when moving to the work site.

[0025] Although not shown, the output device 4 includes a display unit that can display the determination result transmitted from the image processing device 3, as well as an input unit that the maintenance personnel P can input. The output device 4 outputs the determination result from the image processing device 3 in response to an input operation by the maintenance personnel P, for example. This allows the maintenance personnel P to obtain information required for maintenance work on the rope 6 from the output device 4 at any time.

[0026] 1-2. Elevator rope inspection method Next, a rope inspection method performed by the rope inspection system 10 of this embodiment will be described. Fig. 3 is a flowchart showing the rope inspection method of this embodiment. The flowchart shown in Fig. 3 includes a clarity determination method in the clarity determination unit 31 and an abnormality determination method in the abnormality determination unit 32.

[0027] First, the imaging device 2 photographs the rope 6 in the elevator shaft 7 and acquires image data of the rope 6 (step S1). The timing at which the imaging device 2 photographs the rope 6 is determined, for example, based on a signal transmitted from the image processing device 3. Alternatively, the maintenance worker P may transmit a signal to start an inspection from the output device 4, and the imaging device 2 may photograph the image of the rope 6 based on that signal. Furthermore, the imaging device 2 may be configured to photograph the rope 6 at predetermined time intervals. In either case, the rope 6 is photographed after the car 5 has stopped. The acquired photographed image (image data) is transmitted to the image processing device 3.

[0028] Next, the image processing device 3 analyzes the captured image transmitted from the imaging device 2 in the clarity determination unit 31 and calculates the clarity (step S2). One method for calculating the clarity is to digitize and calculate the clarity by edge detection using an edge detection filter. In this case, only the area in the captured image that shows the rope is extracted, and edge detection is performed on the rope area. As the edge detection filter used for edge detection, various spatial filters such as a Laplacian filter or a Sobel filter can be applied.

[0029] The edge detection value extracted using the edge detection filter numerically represents the sharpness of the edge (contour) in the image. Therefore, by calculating the sum of the edge detection values ​​of the rope area, it is possible to quantitatively evaluate the clarity, which indicates whether the contour has been clearly captured. In this way, the clarity determination unit 31 calculates the clarity by calculating the sum of the edge detection values ​​(edge ​​detection amount) of the rope area extracted by the edge detection filter.

[0030] In this embodiment, the clarity is determined by finding the edge detection amount, but the clarity may also be determined from the chromaticity of the image.

[0031] Next, the clarity determination unit 31 determines whether the clarity calculated in step S2 is equal to or greater than a predetermined threshold (step S3). The degree of clarity varies depending on the shooting conditions (shooting environment, exposure time, etc.) of the imaging device 2. The clarity threshold used in step S3 is a value used to determine whether or not there is "oil adhesion" on the rope 6. For this reason, the threshold set in step S3 is an optimal value for each site, and is set based on the criteria for determining whether or not there is oil adhesion on the rope 6.

[0032] If the determination in step S3 is "NO," that is, if the clarity is determined to be lower than the threshold (not clear), the clarity determination unit 31 determines that there is "oil adhesion" on the rope 6 (step S6). Then, the clarity determination unit 31 transmits the determination result that there is "oil adhesion" on the rope 6 to the output device 4 (step S5).

[0033] On the other hand, if the determination in step S3 is "YES," that is, if the clarity is determined to be equal to or greater than the threshold (clear), the abnormality determination unit 32 performs an abnormality determination (step S4). In the abnormality determination performed by the abnormality determination unit 32, it is determined based on the captured image whether the rope 6 is normal or whether there is an abnormality other than "oil adhesion." Examples of abnormalities other than "oil adhesion" include "rust" attached to the rope 6 and "strand breakage." When the abnormality determination unit 32 performs rust detection to determine whether "rust" is attached to the rope 6, the rust detection can be performed by detecting hue information from the captured image.

[0034] Furthermore, when detecting a strand abnormality by detecting whether or not there is a "strand break" in the abnormality determination unit 32, the unit first calculates an autocorrelation function in the rope area shown in the captured image. Then, the unit calculates a differential value of the cross section of the rope 6 from the calculated autocorrelation function, and determines whether or not there is periodicity, thereby determining whether or not there is a strand break. In this way, the abnormality determination unit 32 can use the autocorrelation function to detect whether or not the rope 6 shown in the captured image has periodicity. Then, if there is periodicity, the abnormality determination unit 32 determines that there is no "strand break," and if there is no periodicity, it determines that there is a "strand break."

[0035] If the abnormality determination unit 32 determines that there is no "rust" or "strand breakage", it determines that there is no abnormality. Then, after the abnormality determination unit 32 detects the presence or absence of an abnormality other than "oil adhesion" and information regarding the type of abnormality, the abnormality determination unit 32 transmits the determination result to the output device 4 (step S5).

[0036] In this manner, in this embodiment, an abnormality inspection of the rope 6 is performed using the captured image. In this embodiment, the determination results transmitted to the output device 4 are displayed to the maintenance personnel P at any time. The maintenance personnel P can perform maintenance on the rope 6 based on the displayed determination results.

[0037] In this embodiment, the imaging device 2 and the image processing device 3 are fixed to the bottom of the elevator shaft 7, which limits the range in which the rope 6 can be photographed. In contrast, for example, by installing the imaging device 2 above the car 5, the range in which the rope 6 can be photographed can be expanded.

[0038] However, in this case, as described above, the blurring of the captured image caused by the "rope sway" that accompanies the movement of the car 5 and the "car sway" that accompanies the stopping of the car 5 increases. In the case of "rope sway," the rope moves up and down or left and right, causing blurring of the rope 6 portion of the image data. In the case of "car sway," the stopping of the car causes the imaging device 2 installed above the car 5 to sway, and capturing an image in this swaying state causes blurring of the entire image data. In a blurred image, the outlines of the wires and strands on the surface of the rope become unclear, resulting in a lower clarity than a normal rope image. Therefore, it is impossible to distinguish whether the reduced clarity is due to "oil buildup," "rope sway," or "car sway." In addition, if the captured image is out of focus, the clarity is also reduced, making it impossible to distinguish.

[0039] Below, as a second embodiment of the present invention, we will explain a rope inspection system that can determine (identify) whether the cause of an unclear captured image is ``oil adhesion,'' ``cage sway,'' ``rope sway,'' or ``out of focus.''

[0040] 2. Second embodiment 2-1. Rope inspection system configuration Fig. 4 is a schematic configuration diagram of an elevator 200 to which a rope inspection system 100 according to a second embodiment of the present invention is applied. Fig. 5 is a block diagram showing the configuration of a control system of the rope inspection system 100 according to this embodiment. In Figs. 4 and 5, parts corresponding to those in Figs. 1 and 2 are given the same reference numerals, and duplicated explanations will be omitted.

[0041] The rope inspection system 100 according to the second embodiment includes an imaging device 20, an image processing device 30, and an output device 4, as shown in FIG.

[0042] The imaging device 20 is fixed in a position within the elevator shaft 7 where it can capture an image of the rope 6, and in the second embodiment, it is fixed to the top of the car 5. The imaging device 20 is connected to the image processing device 30 by wired or wireless connection. The imaging device 20 captures an image of the rope 6 at a predetermined timing, and image data of the image captured by the imaging device 20 is transmitted to the image processing device 30.

[0043] 5, the imaging device 20 successively captures a plurality of images (two images in the second embodiment) with different exposure times, and transmits data of the captured images (first captured image 21, second captured image 22) acquired with different exposure times to the image processing device 30.

[0044] Here, the first captured image 21 is assumed to be an image captured with a longer exposure time than the second captured image 22. The first captured image 21 is an image captured with an exposure time set to enable capturing an image that allows the clarity of the rope 6 to be determined even in the dark environment inside the elevator shaft 7, for example. The second captured image 22 is an image captured with an exposure time set to an extent that image blurring caused by "car sway" and "rope sway" can be suppressed. In the second embodiment, for example, the exposure time for the first captured image 21 is 1 / 15 seconds, and the exposure time for the second captured image 22 is 1 / 100 seconds.

[0045] In the second embodiment, as in the first embodiment, in addition to a commonly used visible light camera, a camera that captures other wavelengths such as near-infrared, mid-infrared, or far-infrared can be applied as the imaging device 20.

[0046] The image processing device 30 performs predetermined image processing on the image information of the first captured image 21 and the second captured image 22 transmitted from the imaging device 20, and determines whether or not there is an abnormality in the rope 6. In this embodiment, the image processing device 30 is installed near the imaging device 20 in the elevator shaft 7, but it may also be installed in a remote location such as an elevator management company, and various modifications are possible, such as being configured integrally with the output device 4. The image processing device 30 is connected to the imaging device 20 and the output device 4 by wired or wireless connection, and transmits and receives data between the imaging device 20 and the output device 4.

[0047] As shown in FIG. 5, the image processing device 30 includes a clarity determination unit 31, an abnormality determination unit 32, a difference determination unit 33, and a convergence time calculation unit .

[0048] The difference determination unit 33 uses the first captured image 21 and the second captured image 22 transmitted from the imaging device 20 to identify the cause of the unclearness of the image determined to be unclear by the clarity determination unit 31. When identifying the cause of the unclearness, the following determinations are made in order: car sway determination, rope sway determination, out-of-focus determination, and oil adhesion determination. These determination procedures will be described in detail later.

[0049] The convergence time calculation unit 34 calculates the time for the shaking to converge when the difference determination unit 33 determines that there is "car shaking" or "rope shaking." The convergence time calculation unit 34 calculates the period of the shaking from the difference image between the first captured image 21 and the second captured image 22, and calculates the convergence time of the shaking based on the calculated period of the shaking.

[0050] 2-2. Rope inspection method Next, a description will be given of a rope inspection method using a rope inspection system according to Embodiment 2. Fig. 6 is a flowchart showing the rope inspection method according to the second embodiment.

[0051] First, the rope 6 in the elevator shaft 7 is photographed by the imaging device 20, and image data of the rope 6 is acquired (step S11). The timing of photographing the rope 6 by the imaging device 20 is the same as in step S1 of FIG. 3. In step S11, two sets of image data (a first photographed image 21 and a second photographed image 22) with different exposure times are successively acquired. Then, of the first photographed image 21 and the second photographed image 22 acquired in step S11, the image data of the first photographed image 21 is transmitted to the image processing device 30.

[0052] Next, the image processing device 30 analyzes the first captured image 21 transmitted from the imaging device 20 in the clarity determination unit 31 and calculates the clarity (step S12). As with step S2 in FIG. 3, a method of detecting edges in the first captured image 21 can be used to calculate the clarity. Note that, in the clarity determination in step S12, of the first captured image 21 and the second captured image 22, the first captured image 21, which has a longer exposure time, is used. Therefore, the clarity can be calculated using the first captured image 21, which has a brightness that allows the clarity to be determined even in the dark environment inside the elevator shaft 7. This makes it possible to eliminate the cause of reduced clarity, such as a dark image.

[0053] Next, the clarity determining unit 31 determines whether the calculated clarity is equal to or greater than a predetermined threshold (step S13). The criteria for determination in step S13 are the same as those for determination in step S3 in FIG.

[0054] If the determination in step S13 is "YES," that is, if the clarity determination unit 31 determines that the calculated clarity is equal to or greater than the threshold, the abnormality determination unit 32 performs an abnormality determination (step S14). The abnormality determination in step S14 is the same as step S4 in FIG. 3. That is, the abnormality determination performed by the abnormality determination unit 32 determines, based on the first captured image 21, whether the rope 6 is normal or whether there is an abnormality other than "adhered oil." Examples of abnormalities other than adhering oil include rust on the rope 6 and broken strands.

[0055] After the abnormality determination unit 32 detects the presence or absence of an abnormality other than oil adhesion and information on the type of abnormality, the abnormality determination unit 32 transmits the determination result to the output device 4 (step S15).

[0056] On the other hand, if the determination in step S13 is "NO," that is, if the clarity calculated by the clarity determination unit 31 is determined to be lower than the predetermined threshold, the clarity determination unit 31 determines that the cause of the blurring is one of oil on the rope, car swaying, rope swaying, or out-of-focus in the imaging device. If the determination in step S13 is "NO," the process proceeds to step S16. In the flow following step S16, the cause of the blurring is identified.

[0057] In step S16, the difference determination unit 33 acquires image data of the first captured image 21 and the second captured image 22 from the imaging device 20 and creates a difference image between the first captured image 21 and the second captured image 22 (step S16). The second captured image 22 is an image captured with a shorter exposure time than the first captured image 21. Therefore, the second captured image 22 is darker than the first captured image 21, but has less subject blur. Therefore, from the difference image between the first captured image 21 and the second captured image 22, information can be obtained about the area in the first captured image 21 where subject blur occurs and the width of the blur.

[0058] In this embodiment, image data of the first captured image 21 and the second captured image 22 are acquired in step S16. However, since the first captured image 21 has already been acquired in a previous stage, only the second captured image 22 may be acquired. Furthermore, the first captured image 21 and the second captured image 22 may be acquired in step S11. By configuring the second captured image 22 to be acquired only when the determination in step S13 is "NO," data communication charges can be reduced.

[0059] After creating the difference image in step S16, the difference determination unit 33 performs edge detection on the background region in the difference image (step S17). Here, the background region refers to the region in the image other than the rope 6. The edge detection in step S17 can also be performed using the same method as the edge detection in step S2 of FIG. 3.

[0060] Next, the difference determination unit 33 determines whether the edge detection amount of the background region in the difference image is equal to or greater than a threshold value (step S18). Here, the edge detection amount is calculated in the same manner as the clarity calculated in step S3. The threshold value used in step S18 is a value set according to the shooting environment, etc.

[0061] However, when "car sway" occurs, the entire captured image is blurred, and not only the rope 6 but also other components in the elevator shaft 7 that are captured in the background area are photographed out of alignment. Therefore, when "car sway" occurs, the edge detection value detected in the background area of ​​the difference image becomes higher than when there is no "car sway." For this reason, in step S18, by determining whether the edge detection value detected in the background area of ​​the difference image is equal to or greater than a predetermined threshold, it is possible to determine whether the cause of the decrease in clarity is "car sway" or some other reason.

[0062] If the determination in step S18 is "YES," that is, if it is determined that the edge detection amount in the background region of the difference image is equal to or greater than a predetermined threshold, the difference determination unit 33 determines that the cause of the low clarity (cause of unclearness) is "car shaking" (step S19). Then, if it is determined in step S19 that the cause of the low clarity is "car shaking," the process proceeds to step S23. Step S23 will be described in detail later.

[0063] On the other hand, if the determination in step S18 is "NO," that is, if it is determined that the edge detection amount in the background region of the difference image is lower than the predetermined threshold, the process proceeds to step S20.

[0064] In step S20, the difference determination unit 33 performs edge detection of the rope region in the difference image (step S20). Here, the rope region refers to the region in the image that shows the rope 6. The edge detection in step S20 can also be performed using the same method as the edge detection in step S3 of FIG.

[0065] Next, the difference determination unit 33 determines whether the edge detection amount of the rope region in the difference image is equal to or greater than a threshold value (step S21). Here, the edge detection amount is calculated in the same manner as the clarity calculated in step S3 of Fig. 3. The threshold value used in step S21 is a value set according to the shooting environment, etc.

[0066] However, when "rope sway" occurs, only the rope 6 is blurred in the captured image, and therefore the rope 6 is photographed out of alignment in the first captured image 21 and the second captured image 22, which were photographed with different exposure times. Therefore, when "rope sway" occurs, the amount of edge detection detected in the rope region in the difference image is higher than when there is no "rope sway." Furthermore, at the stage of step S21, "car sway" has already been eliminated as a cause of reduced clarity. Therefore, in step S21, by determining whether the amount of edge detection detected in the rope region in the difference image is equal to or greater than a predetermined threshold, it is possible to distinguish whether the reduced clarity is due to "rope sway" or some other reason.

[0067] If the determination in step S21 is "YES," that is, if the edge detection amount in the rope region of the difference image is determined to be equal to or greater than a predetermined threshold, the difference determination unit 33 determines that the cause of the low clarity is "rope sway" (step S22). Then, if the cause of the low clarity is determined to be "rope sway" in step S22, the process proceeds to step S23.

[0068] In step S23, the convergence time calculation unit 34 calculates the convergence time of the "car shaking" or "rope shaking" based on the differential image. For example, the period of image blur is calculated from the differential image, and the convergence time of the "car shaking" or "rope shaking" is calculated based on that period.

[0069] In step S23, after the convergence time is calculated, the convergence time calculation unit 34 transmits information relating to the convergence time to the imaging device 20. When the information relating to the convergence time is transmitted from the convergence time calculation unit 34, the imaging device 20 starts the flow from step S11 again after the convergence time has elapsed. This makes it possible to detect a rope abnormality again after the "car swaying" or "rope swaying" has converged.

[0070] On the other hand, if the determination in step S21 is "NO," that is, if it is determined that the edge detection amount in the background region of the difference image is lower than the predetermined threshold, the process proceeds to step S24.

[0071] In step S24, the difference determination unit 33 determines whether or not focus adjustment has been performed in the imaging device 20, based on the information transmitted from the imaging device 20. If the determination in step S24 is "YES," the difference determination unit 33 determines that the cause of the low clarity is "out of focus" (step S25). Then, the difference determination unit 33 transmits the determination result to the imaging device 20.

[0072] Thereafter, the imaging device 20 performs focus adjustment in the imaging device 20 based on the information transmitted from the difference determination unit 33 (step S26). Then, the flow starts again from step S11.

[0073] On the other hand, if the determination in step S24 is "NO," that is, if the difference determination unit 33 determines that focus adjustment has already been performed, the process proceeds to step S27.

[0074] In step S27, the difference determination unit 33 determines that the cause of the low clarity is “solidified oil.” Thereafter, the difference determination unit 33 transmits the determination result that the cause of the low clarity is “solidified oil” to the output device 4 (step S15).

[0075] As described above, in the second embodiment, if the cause of low clarity of the captured image is "car sway," "rope sway," or "out of focus," it is possible to perform abnormality detection again after eliminating that cause. Also, if the cause of low clarity of the captured image is not "car sway," "rope sway," or "out of focus," it is possible to detect "solidified oil" on the rope 6.

[0076] Furthermore, in the above embodiment, an example was described in which an abnormality in the main rope that suspends the car was inspected, but the present invention can also be applied to inspecting abnormalities in other ropes, such as compensating ropes, in addition to the main rope.

[0077] The above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to having all of the described configurations. For example, it is possible to replace part of the configuration of the embodiment with another configuration, or to add another configuration to the configuration of the embodiment. It is also possible to add, delete, or replace part of the configuration of the embodiment with another configuration. [Explanation of symbols]

[0078] 1... elevator, 2... imaging device, 3... image processing device, 4... output device, 5... car, 6... rope, 7... elevator shaft, 10... rope inspection system, 20... imaging device, 21... first captured image, 22... second captured image, 30... image processing device, 31... clarity determination unit, 32... abnormality determination unit, 33... difference determination unit, 34... convergence time calculation unit, 100... rope inspection system, 200... elevator

Claims

1. an imaging device that captures an image of a rope placed in the elevator shaft; a clarity determination unit that detects the clarity of the image transmitted from the imaging device and determines whether the image of the rope is clear based on the clarity; The clarity determination unit determines whether or not there is an abnormality in the rope based on the determination of whether or not the clarity is good, The clarity determination unit detects clarity based on the edge detection value of the image detected using an edge detection filter, determines whether the image is clear or not depending on whether the clarity is equal to or greater than a threshold, and determines that oil is stuck to the rope if it determines that the image is not clear. Elevator rope inspection system.

2. and a difference determination unit that creates a difference image using the image and another image that is taken by the imaging device immediately after the image and that is taken with an exposure time that is shorter than the exposure time used to take the image, and determines, from the difference image, the reason why the image is determined to be unclear.

2. The elevator rope inspection system of claim 1.

3. The difference determination unit determines whether the reason why the image is determined to be unclear is due to oil adhering to the rope, shaking of the car, shaking of the rope, or out of focus in the imaging device.

3. The elevator rope inspection system according to claim 2.

4. The difference determination unit performs edge detection using an edge detection filter in a background area other than the rope shown in the difference image, and if the amount of edge detection in the background area is equal to or greater than a predetermined threshold, determines that the reason the image is determined to be unclear is due to car sway.

4. The elevator rope inspection system according to claim 3.

5. The difference determination unit performs edge detection using an edge detection filter in the rope area shown in the difference image, and if the edge detection amount in the rope area is equal to or greater than a predetermined threshold, determines that the reason the image is determined to be unclear is due to rope swaying.

5. The elevator rope inspection system according to claim 4.

6. When the difference determination unit determines that the reason for determining that the image is not clear is neither car shaking nor rope shaking, it determines whether or not focus adjustment has been performed in the imaging device, and when focus adjustment has not been performed, it determines that the reason for determining that the image is not clear is out of focus.

6. The elevator rope inspection system according to claim 5.

7. When the difference determination unit determines that the reason why the image is determined to be unclear is not out of focus, the difference determination unit determines that the reason why the image is determined to be unclear is that oil has adhered to the rope.

7. The elevator rope inspection system according to claim 6.

8. moreover, a convergence time calculation unit that calculates a convergence time of the swinging of the car or the swinging of the rope using the differential image when it is determined that the image is not clear due to the swinging of the car or the swinging of the rope; 8. The elevator rope inspection system according to claim 7.

9. The rope placed inside the elevator shaft is photographed by an imaging device, Detecting the clarity of the image transmitted from the imaging device, and determining whether the image of the rope is clear based on the clarity; If the image is determined to be clear, it is determined whether or not there is an abnormality in the rope based on the image. The clarity of the image is detected based on the edge detection value of the image detected using an edge detection filter, and whether the image is clear or not is determined depending on whether the clarity is equal to or greater than a threshold value. If the image is determined to be unclear, it is determined that oil has adhered to the rope. Elevator rope inspection method.

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