Non-contact elevator steel wire rope wear one-time detection method

Abstract

The application discloses a kind of non-contact elevator wire rope wear disposable detection methods, it is related to machine vision technical field, solve the problem of low detection efficiency and detection accuracy of elevator wire rope, including the conversion coefficient between the corresponding pixel of industrial camera and actual size is calculated, and then the multiple images to be identified of the target elevator corresponding to the wire rope to be detected are collected;The multiple images to be identified of the wire rope to be detected are processed, and the wire rope profile of the multiple wire ropes to be detected corresponding to the target elevator is extracted;Combining the wire rope profile of the multiple wire ropes to be detected in multiple images to be identified is calculated, to obtain the full-length wear curve diagram corresponding to each wire rope to be detected;The wear condition of the corresponding wire rope to be detected is judged based on full-length wear curve diagram, and the corresponding response is made, the full-length wear curve of the wire rope to be detected is constructed by the wire rope profile, and the full-length, continuous and accurate wear evaluation of the multiple wire ropes to be detected is realized.

Description

Technical Field

[0001] This invention belongs to the field of machine vision technology, specifically a non-contact, one-time detection method for elevator wire rope wear. Background Technology

[0002] Elevator wire rope is a crucial load-bearing component in elevator systems. It is made of multiple twisted steel wires and possesses characteristics such as high strength, wear resistance, and fatigue resistance. It is directly related to the safety and stability of elevator operation. The wire rope connects the elevator car and the counterweight device and is wound around the traction sheave. Because it bears the weight of the elevator itself and the counterweight while rolling on the traction sheave, it is extremely prone to wear.

[0003] However, at present, when inspecting the wear of elevator wire ropes, inefficient and error-prone methods such as manually inspecting each wire rope one by one and measuring with calipers are often used. Therefore, the identification of defects such as the degree of wear, wear location, and reduction in rope diameter of multiple wire ropes at one time cannot guarantee the inspection efficiency and accuracy.

[0004] Therefore, this invention proposes a non-contact, one-time detection method for elevator wire rope wear. Summary of the Invention

[0005] The purpose of this invention is to propose a non-contact, one-time detection method for elevator wire rope wear, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A non-contact, one-time detection method for elevator wire rope wear, the method comprising:

[0008] Step S1: Calculate the conversion coefficient between the corresponding pixels of the industrial camera and the actual size, and then acquire multiple images of the steel wire rope to be inspected corresponding to the target elevator.

[0009] Step S2: Process the multiple images of the steel wire rope to be inspected to extract the outline of the steel wire rope corresponding to the target elevator.

[0010] Step S3: Combine the wire rope profiles of multiple wire ropes to be inspected in multiple images to be identified, and calculate to obtain the full-length wear curve of each wire rope to be inspected.

[0011] Step S4: Determine the wear condition of the corresponding wire rope to be inspected based on the full-length wear curve and take appropriate measures.

[0012] Further, step S1 includes the following sub-steps:

[0013] Step S11: Install the industrial camera, fixed-focus lens and parallel backlight source on the detection station in the elevator shaft, and adjust the object distance, angle and aperture to the actual detection settings.

[0014] Step S12: Select a reference steel wire rope with known actual length and actual diameter and place it on the uniform object distance plane of the steel wire rope to be inspected, and make the axial direction of the reference steel wire rope consistent with that of the steel wire rope to be inspected.

[0015] Step S13: Acquire multiple wire rope images corresponding to the reference wire rope using an industrial camera, read the length and diameter of the reference wire rope in the wire rope image, and obtain the alternative conversion coefficient of the wire rope image in the horizontal direction by dividing the diameter of the reference wire rope in the wire rope image by the actual diameter.

[0016] The alternative conversion factor for the steel wire rope image in the vertical direction is obtained by dividing the length of the steel wire rope in the steel wire rope image by the actual length.

[0017] Step S14: Calculate the candidate conversion coefficients of all wire rope images in the horizontal direction in sequence, add up the candidate conversion coefficients of all wire rope images in the horizontal direction and take the average value to obtain the conversion coefficient between pixels and actual size in the horizontal direction; similarly, calculate the conversion coefficient between pixels and actual size in the vertical direction.

[0018] Furthermore, step S1 also includes the following sub-steps:

[0019] Step S15: Install a rotary encoder on the traction sheave of the target elevator and connect the rotary encoder to the industrial camera for data transmission.

[0020] Step S16: Set the expected sampling interval of the wire rope to be inspected, read the circumference of the traction sheave and the encoder pulses per revolution of the rotary encoder, and calculate the number of trigger pulses corresponding to the industrial camera by combining the expected sampling interval, the circumference of the traction sheave and the encoder pulses per revolution.

[0021] Step S17: When the number of pulses accumulated by the encoder reaches the number of trigger pulses, a start signal is generated, and the start signal is bound to the trigger pin of the industrial camera to trigger an image acquisition operation of the industrial camera.

[0022] In step S18, when the target elevator is running, the industrial camera acquires multiple images of the steel wire rope to be inspected.

[0023] Further, step S2 includes the following sub-steps:

[0024] Step S21: Acquire multiple images of the steel wire rope to be inspected, then sort the images according to the acquisition time, and number each image.

[0025] Step S22: Select the image to be identified with the first number, read the pixel value of each pixel in the image to be identified, and then divide the pixel value of each pixel into R value component, G value component and B value component.

[0026] Step S23: Calculate the pixel grayscale value of the corresponding pixel based on the R value component, G value component and B value component of the pixel.

[0027] Step S24: Set a fixed-size mean window, align the center of the mean window with any pixel, record the pixels inside the mean window but not in the center as adjacent pixels, sum the gray values ​​of the adjacent pixels and take the average to obtain the optimized gray value, and replace the gray value of the pixel corresponding to the center position with the optimized gray value.

[0028] Furthermore, step S2 also includes the following sub-steps:

[0029] Step S25: Use the mean window to traverse all pixels to obtain the optimized grayscale value of all pixels; compare the optimized grayscale value with the grayscale threshold. If the optimized grayscale value is less than or equal to the grayscale threshold, the corresponding pixel is recorded as a contour pixel. If the optimized grayscale value is greater than the grayscale threshold, the corresponding pixel is recorded as a non-contour pixel.

[0030] Step S26: Connect all adjacent contour pixels to obtain multiple candidate contours, construct the minimum bounding rectangle corresponding to each candidate contour, compare the width of the minimum bounding rectangle with the filtering interval, if the width of the minimum bounding rectangle is within the filtering interval, then record the corresponding candidate contour as a wire rope contour, otherwise discard the corresponding candidate contour; thus obtaining multiple wire rope contours in the corresponding image to be identified.

[0031] Step S27: Based on the process of obtaining the wire rope contour in step S26, obtain multiple wire rope contours in all images to be identified.

[0032] Further, step S3 includes the following sub-steps:

[0033] Step S31: Acquire multiple images to be identified, read the outlines of multiple steel wire ropes to be inspected in the images to be identified, count the number of steel wire rope outlines in each image to be identified, identify the mode of the number of steel wire rope outlines, discard the images to be identified whose number of steel wire rope outlines is different from the mode, and keep the remaining images to be identified.

[0034] Step S32: Select the leftmost wire rope outline in the image to be identified with the first number, and identify the top pixel and bottom pixel of the corresponding wire rope outline.

[0035] Step S33: Calculate the outline length of the corresponding wire rope profile based on the top and bottom pixels; draw two trisection lines according to the outline length, and intersect the trisection lines with the wire rope profile to obtain two detection sections of the wire rope profile.

[0036] Furthermore, step S3 also includes the following sub-steps:

[0037] Step S34: Extract the pixel coordinates of the left edge point and the right edge point of the detection section above, and then calculate the pixel cross-section diameter of the detection section.

[0038] Step S35: Obtain the conversion factor between the pixel and the actual size, and multiply the conversion factor by the pixel cross-section diameter to obtain the actual cross-section diameter of the corresponding detection cross-section; multiply the ordinate of the corresponding left edge point of the detection cross-section by the conversion factor to obtain the relative position of the detection cross-section with respect to the steel wire rope to be inspected.

[0039] Step S36: Extract the pixel coordinates of the left edge point and the right edge point of another detection section and calculate the pixel section diameter of the corresponding detection interface. Then, calculate the actual section diameter of the corresponding detection section and the relative position of the detection section with respect to the steel wire rope to be inspected.

[0040] Furthermore, step S3 also includes the following sub-steps:

[0041] Step S37: Select the leftmost wire rope outline in the second-ranked image to be identified, and then calculate the actual cross-sectional diameter and the relative position of the detection cross-section to the wire rope to be inspected for the two detection cross-sections in the corresponding image to be identified; then calculate the actual cross-sectional diameter and the relative position of the detection cross-section to the wire rope to be inspected for the two detection cross-sections in all images to be identified.

[0042] Step S38: Read the nominal diameter of the steel wire rope to be inspected, and calculate the wear rate at each inspection section based on the nominal diameter;

[0043] Step S39: Collect Greek letters to mark the wire rope outline in each image to be identified, and regard the wire rope outline with the same mark in different images to be identified as the wire rope outline of the same wire rope to be inspected.

[0044] The wear rate curve of the entire length of the steel wire rope under test is obtained by plotting the relative position of the test section with respect to the test section on the x-axis and the wear rate at each test section on the y-axis.

[0045] Further, step S4 includes the following sub-steps:

[0046] Step S41: Obtain the full-length wear curves of all the wire ropes to be inspected, and plot a qualified state curve and a warning state curve on the full-length wear curve of each wire rope to be inspected.

[0047] Step S42: For any wire rope to be inspected, if the wear curve of the entire length of the wire rope to be inspected intersects with the warning state curve, then the state of the corresponding wire rope to be inspected is recorded as scrapped state.

[0048] Step S43: If the full-length wear curve of the steel wire rope to be inspected does not intersect with the warning state curve, then identify the intersection of the full-length wear curve of the steel wire rope to be inspected with the qualified state curve. If there is an intersection, then record the state of the corresponding steel wire rope to be inspected as the warning state, and the area of ​​the full-length wear curve after the odd number of intersections is recorded as the warning area.

[0049] Step S44: If the wear curve of the entire length of the wire rope to be inspected does not intersect with the qualified state curve, then the state of the corresponding wire rope to be inspected is recorded as qualified state.

[0050] Step S45: Perform corresponding operations on the steel wire rope to be inspected based on its condition.

[0051] Furthermore, if the steel wire rope to be inspected is in a scrapped state, the corresponding steel wire rope to be inspected shall be replaced immediately; if the steel wire rope to be inspected is in a warning state, the warning area of ​​the steel wire rope to be inspected shall be maintained; if the steel wire rope to be inspected is in a qualified state, no operation shall be performed.

[0052] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0053] 1. This invention calculates the conversion coefficient between the corresponding pixels of the industrial camera and the actual size, and then acquires multiple images of the steel wire rope to be inspected corresponding to the target elevator; processes the multiple images of the steel wire rope to be inspected to extract the outline of the steel wire rope corresponding to the target elevator, thereby achieving accurate extraction of the outline of the steel wire rope to be inspected.

[0054] 2. This invention combines the wire rope contours of multiple wire ropes to be inspected in multiple images to calculate and obtain the full-length wear curve of each wire rope to be inspected; based on the full-length wear curve, the wear condition of the corresponding wire rope to be inspected is determined and corresponding measures are taken; by constructing the full-length wear curve of the wire rope to be inspected, the wear assessment of multiple wire ropes to be inspected can be carried out in a full-length, continuous and accurate manner. Attached Figure Description

[0055] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0056] Figure 1This is a flowchart illustrating the overall method of the present invention;

[0057] Figure 2 This is a schematic diagram of the mean window in this invention;

[0058] Figure 3 This is a schematic diagram of the detection cross section in this invention;

[0059] Figure 4 This is a full-length wear curve diagram from the present invention;

[0060] Figure 5 This is a schematic diagram of the electronic device in this invention. Detailed Implementation

[0061] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Example 1: Please refer to Figures 1-4 As shown, the technical solution provided by this invention is as follows: a non-contact method for one-time detection of elevator wire rope wear, which involves using a conversion coefficient between the corresponding pixels and the actual size of an industrial camera to acquire multiple images of the wire rope to be inspected during the operation of the target elevator; extracting the wire rope contour of each wire rope in the image based on the images; analyzing the wire rope contour to draw a full-length wear curve for each wire rope; and determining and adjusting the wear state of each wire rope based on the full-length wear curve.

[0063] The method for one-time detection of elevator wire rope wear in this invention is as follows:

[0064] Step S1: Calculate the conversion coefficient between the corresponding pixels of the industrial camera and the actual size, and then acquire multiple images of the steel wire rope to be inspected corresponding to the target elevator.

[0065] In this invention, step S1 includes the following example steps:

[0066] Step S11: Install the industrial camera, fixed-focus lens and parallel backlight source on the inspection station in the elevator shaft or elevator machine room, and adjust them to the object distance, angle and aperture for actual inspection.

[0067] Among them, object distance refers to the vertical distance between the front end of the lens of the industrial camera and the steel wire rope to be inspected; angle refers to the angle between the center line of the industrial camera and the length direction of the steel wire rope to be inspected, including the pitch angle between vertical planes and the rotation angle in the horizontal plane.

[0068] Step S12: Select a reference steel wire rope with known actual length and actual diameter and place it on the uniform object distance plane of the steel wire rope to be inspected, and make the axial direction of the reference steel wire rope consistent with that of the steel wire rope to be inspected.

[0069] Step S13: Acquire multiple wire rope images corresponding to the reference wire rope using an industrial camera, read the length and diameter of the reference wire rope in the wire rope image, and obtain the alternative conversion coefficient of the wire rope image in the horizontal direction by dividing the diameter of the reference wire rope in the wire rope image by the actual diameter.

[0070] The alternative conversion factor for the steel wire rope image in the vertical direction is obtained by dividing the length of the steel wire rope in the steel wire rope image by the actual length.

[0071] Step S14: Calculate the candidate conversion coefficients of all wire rope images in the horizontal direction in sequence, add up the candidate conversion coefficients of all wire rope images in the horizontal direction and take the average value to obtain the conversion coefficient between the pixel and the actual size in the horizontal direction; similarly, calculate the conversion coefficient between the pixel and the actual size in the vertical direction.

[0072] It should be noted that for industrial cameras where all camera sensor pixels are oriented positively, the conversion factor between pixels and actual size is the same in both the horizontal and vertical directions, and only needs to be calculated once.

[0073] Step S15: Install a rotary encoder on the traction sheave of the target elevator and connect the rotary encoder to the industrial camera for data transmission.

[0074] The traction sheave is a metal wheel with a groove. The traction steel wire rope passes around the groove of the traction sheave, and the traction force is transmitted by the friction between the groove and the steel wire rope, thereby driving the elevator car to move up and down. The rotary encoder is a sensor that converts the angular displacement of a rotating shaft into a series of digital pulse signals.

[0075] Step S16: Set the expected sampling interval for the wire rope to be inspected, read the circumference of the traction sheave and the encoder pulses per revolution of the rotary encoder, and calculate the trigger pulse count corresponding to the industrial camera by combining the expected sampling interval, the circumference of the traction sheave, and the encoder pulses per revolution; the specific formula is as follows:

[0076] Number of trigger pulses = expected sampling interval × encoder pulses per revolution ÷ traction sheave circumference;

[0077] The expected sampling interval refers to the physical distance between two adjacent image acquisitions along the length of the steel wire rope under inspection. Simply put, if we want to acquire an image at fixed intervals along the entire length of the steel wire rope under inspection, then this fixed interval is the expected sampling interval. The trigger pulse count is used to control the industrial camera to acquire the image to be identified of the steel wire rope under inspection. Specifically, when the cumulative number of pulses of the rotary encoder reaches the trigger pulse count, the industrial camera is triggered to acquire an image.

[0078] Step S17: When the number of pulses accumulated by the encoder reaches the number of trigger pulses, a start signal is generated, and the start signal is bound to the trigger pin of the industrial camera to trigger an image acquisition operation of the industrial camera.

[0079] In step S18, when the target elevator is running, the industrial camera acquires multiple images of the steel wire rope to be inspected.

[0080] Step S2: Process the multiple images of the steel wire rope to be inspected to extract the outline of the steel wire rope corresponding to the target elevator.

[0081] In this invention, step S2 includes the following sub-steps:

[0082] Step S21: Acquire multiple images of the steel wire rope to be inspected, and then sort the images according to the acquisition time. Number each image as i, i=1, 2, ..., z, where z is a positive integer. Specifically, the earlier the image was acquired, the earlier it is sorted.

[0083] Step S22: Select the image to be identified with the first number, read the pixel value of each pixel in the image to be identified, and then divide the pixel value of each pixel into R value component, G value component and B value component.

[0084] Step S23: Calculate the pixel grayscale value of the corresponding pixel based on its R, G, and B components; the specific formula for calculating the pixel grayscale value is as follows:

[0085] Pixel grayscale value = A1 × R value component + A2 × G value component + A3 × B value component; A1, A2, and A3 are weighting coefficients; preferably, A1 = 0.299, A2 = 0.587, and A3 = 0.114.

[0086] Step S24, please refer to Figure 2As shown, a fixed-size mean window is set, and the center of the mean window is aligned with any pixel. Pixels located inside the mean window but not at the center are recorded as adjacent pixels. The gray values ​​of the adjacent pixels are summed and averaged to obtain an optimized gray value. The optimized gray value replaces the gray value of the pixel corresponding to the center position. Preferably, the size of the mean window is 3×3.

[0087] Step S25: Use the mean window to traverse all pixels to obtain the optimized grayscale value of all pixels; compare the optimized grayscale value with the grayscale threshold. If the optimized grayscale value is less than or equal to the grayscale threshold, the corresponding pixel is recorded as a contour pixel; if the optimized grayscale value is greater than the grayscale threshold, the corresponding pixel is recorded as a non-contour pixel. The grayscale threshold is a constant, generally between 120 and 130, preferably 127.

[0088] Step S26: Connect all adjacent contour pixels to obtain multiple candidate contours, construct the minimum bounding rectangle corresponding to each candidate contour, compare the width of the minimum bounding rectangle with the filtering interval, if the width of the minimum bounding rectangle is within the filtering interval, then record the corresponding candidate contour as a wire rope contour, otherwise discard the corresponding candidate contour; thus obtaining multiple wire rope contours in the corresponding image to be identified.

[0089] The screening range is a pre-defined range, generally from 0.8 times the nominal diameter to 1.2 times the engineering diameter; the nominal diameter is the uniform size corresponding to the wire rope to be inspected.

[0090] Step S27: Based on the process of obtaining the wire rope contour in step S26, obtain multiple wire rope contours in all images to be identified.

[0091] Step S3: Combine the wire rope profiles of multiple wire ropes to be inspected in multiple images to be identified, and calculate to obtain the full-length wear curve of each wire rope to be inspected.

[0092] In this invention, step S3 includes the following sub-steps:

[0093] Step S31: Acquire multiple images to be identified, read the outlines of multiple steel wire ropes to be inspected in the images to be identified, count the number of steel wire rope outlines in each image to be identified, identify the mode of the number of steel wire rope outlines, discard the images to be identified whose number of steel wire rope outlines is different from the mode, and keep the remaining images to be identified.

[0094] Step S32: Select the leftmost wire rope outline in the image to be identified with the first number, and identify the top pixel and bottom pixel of the corresponding wire rope outline.

[0095] Step S33, please refer to Figure 3As shown, the contour length of the corresponding wire rope contour is calculated based on the top and bottom pixels; two trisection lines are drawn according to the contour length, and the trisection lines are intersected with the wire rope contour to obtain two detection sections of the wire rope contour.

[0096] Step S34: Extract the pixel coordinates of the left and right edge points of the detection section above, and then calculate the pixel cross-section diameter XZ1 of the detection section; the formula for the cross-section diameter is as follows:

[0097] In the formula, u1 is the x-coordinate of the pixel coordinate corresponding to the left edge point, v1 is the y-coordinate of the pixel coordinate corresponding to the left edge point; u2 is the x-coordinate of the pixel coordinate corresponding to the right edge point, v2 is the y-coordinate of the pixel coordinate corresponding to the right edge point; generally speaking, v2 is equal to v1.

[0098] Step S35: Obtain the conversion factor between the pixel and the actual size, and multiply the conversion factor by the pixel cross-section diameter to obtain the actual cross-section diameter of the corresponding detection cross-section; multiply the ordinate of the corresponding left edge point of the detection cross-section by the conversion factor to obtain the relative position of the detection cross-section with respect to the steel wire rope to be inspected.

[0099] Step S36: Extract the pixel coordinates of the left edge point and the right edge point of another detection section and calculate the pixel section diameter of the corresponding detection interface, and then calculate the actual section diameter of the corresponding detection section and the relative position of the detection section with respect to the steel wire rope to be inspected.

[0100] Step S37: Select the leftmost wire rope outline in the second-ranked image to be identified, and then calculate the actual cross-sectional diameter and the relative position of the detection cross-section to the wire rope to be inspected for the two detection cross-sections in the corresponding image to be identified; then calculate the actual cross-sectional diameter and the relative position of the detection cross-section to the wire rope to be inspected for the two detection cross-sections in all images to be identified.

[0101] It should be noted that for images with a number greater than or equal to 2 to be identified, the relative position of the detection section corresponding to the wire rope contour with respect to the wire rope to be inspected needs to be corrected; specifically:

[0102] Corrected relative position = initial relative position + (number - 1) × expected sampling interval.

[0103] Step S38: Read the nominal diameter of the steel wire rope to be inspected, and calculate the wear rate at each inspection section based on the nominal diameter; the specific formula is as follows:

[0104] Wear rate = (nominal diameter - actual cross-sectional diameter of the test section) / nominal diameter × 100%;

[0105] Step S39: Collect Greek letters to mark the wire rope outline in each image to be identified. The wire rope outline with the same mark in different images to be identified is regarded as the wire rope outline of the same wire rope to be inspected. Plot the full-length wear rate curve of the corresponding wire rope to be inspected with the relative position of the detection section relative to the wire rope to be inspected as the abscissa and the wear rate at the location of each detection section as the ordinate.

[0106] It should be noted that, in practice, Greek letters can be used to mark the outline of the steel wire rope in the image to be identified in different ways, and the full-length wear rate curve is used to show the degree of wear at different positions along the length of the corresponding steel wire rope to be inspected.

[0107] Step S4: Determine the wear condition of the corresponding wire rope to be inspected based on the full-length wear curve and take appropriate measures.

[0108] In this invention, step S4 includes the following sub-steps:

[0109] Step S41, please refer to Figure 4 As shown, the full-length wear curves of all steel wire ropes to be inspected are obtained. For each steel wire rope to be inspected, a qualified state curve and a warning state curve are plotted on the full-length wear curve. The qualified state curve is a straight line with a wear rate of 3%, and the warning state curve is a straight line with a wear rate of 6%. Specifically, 3% and 6% are wear rate judgment thresholds obtained according to the standards provided by "Technical Conditions for Scrapping of Major Elevator Components" and "Steel Wire Ropes for Elevators".

[0110] Step S42: For any wire rope to be inspected, if the wear curve of the entire length of the wire rope to be inspected intersects with the warning state curve, then the state of the corresponding wire rope to be inspected is recorded as scrapped state.

[0111] Step S43: If the full-length wear curve of the steel wire rope to be inspected does not intersect with the warning state curve, then identify the intersection of the full-length wear curve of the steel wire rope to be inspected with the qualified state curve. If there is an intersection, then record the state of the corresponding steel wire rope to be inspected as the warning state, and the area of ​​the full-length wear curve after the odd number of intersections is recorded as the warning area.

[0112] Step S44: If the wear curve of the entire length of the wire rope to be inspected does not intersect with the qualified state curve, then the state of the corresponding wire rope to be inspected is recorded as qualified state.

[0113] Step S45: Perform corresponding operations on the steel wire rope to be inspected based on its condition.

[0114] Specifically, if the wire rope to be inspected is in a scrapped state, the corresponding wire rope to be inspected will be replaced immediately; if the wire rope to be inspected is in a warning state, the warning area of ​​the wire rope to be inspected will be maintained; if the wire rope to be inspected is in a qualified state, no operation will be performed.

[0115] Example 2: Figure 5 As shown, this embodiment provides an electronic device, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The processor can call logical instructions in the memory to execute a non-contact, one-time detection method for elevator wire rope wear. This method includes: calculating the conversion coefficient between the corresponding pixels of an industrial camera and the actual size; then acquiring multiple images of the wire rope to be inspected corresponding to the target elevator; processing the multiple images of the wire rope to be inspected to extract the wire rope contours of the multiple wire ropes to be inspected corresponding to the target elevator; calculating the full-length wear curve of each wire rope to be inspected by combining the wire rope contours of the multiple images; judging the wear condition of the corresponding wire rope based on the full-length wear curve and taking corresponding actions.

[0116] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0117] On the other hand, this application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by the computer, the computer can execute a non-contact elevator wire rope wear detection method provided by the above methods. The method includes: calculating the conversion coefficient between the corresponding pixels of the industrial camera and the actual size, and then acquiring multiple images of the wire rope to be inspected corresponding to the target elevator; processing the multiple images of the wire rope to be inspected to extract the wire rope contours of the multiple wire ropes to be inspected corresponding to the target elevator; calculating the full-length wear curve of each wire rope to be inspected by combining the wire rope contours of the multiple wire ropes to be inspected in the multiple images; judging the wear condition of the corresponding wire rope based on the full-length wear curve and taking corresponding measures.

[0118] Furthermore, this application also provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program performs a non-contact, one-time detection method for elevator wire rope wear described above. This method includes: calculating the conversion coefficient between the corresponding pixels of an industrial camera and the actual size; then acquiring multiple images of the wire rope to be inspected corresponding to the target elevator; processing the multiple images of the wire rope to be inspected to extract the wire rope contours of the multiple wire ropes to be inspected corresponding to the target elevator; calculating the full-length wear curve of each wire rope to be inspected by combining the wire rope contours of the multiple wire ropes to be inspected in the multiple images; and determining the wear condition of the corresponding wire rope based on the full-length wear curve and taking corresponding actions.

[0119] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0120] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0121] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A non-contact, one-time detection method for elevator wire rope wear, characterized in that, The methods include: Step S1: Calculate the conversion coefficient between the corresponding pixels of the industrial camera and the actual size, and then acquire multiple images of the steel wire rope to be inspected corresponding to the target elevator. Step S2: Process the multiple images of the steel wire rope to be inspected to extract the outline of the steel wire rope corresponding to the target elevator. Step S3: Combine the wire rope profiles of multiple wire ropes to be inspected in multiple images to be identified, and calculate to obtain the full-length wear curve of each wire rope to be inspected. Step S4: Determine the wear condition of the corresponding wire rope to be inspected based on the full-length wear curve and take appropriate measures.

2. The non-contact, one-time detection method for elevator wire rope wear according to claim 1, characterized in that, Step S1 includes the following sub-steps: Step S11: Install the industrial camera, fixed-focus lens and parallel backlight source on the detection station in the elevator shaft, and adjust the object distance, angle and aperture to the actual detection settings. Step S12: Select a reference steel wire rope with known actual length and actual diameter and place it on the uniform object distance plane of the steel wire rope to be inspected, and make the axial direction of the reference steel wire rope consistent with that of the steel wire rope to be inspected. Step S13: Acquire multiple wire rope images corresponding to the reference wire rope using an industrial camera, read the length and diameter of the reference wire rope in the wire rope image, and obtain the alternative conversion coefficient of the wire rope image in the horizontal direction by dividing the diameter of the reference wire rope in the wire rope image by the actual diameter. The alternative conversion factor for the steel wire rope image in the vertical direction is obtained by dividing the length of the steel wire rope in the steel wire rope image by the actual length. Step S14: Calculate the candidate conversion coefficients of all wire rope images in the horizontal direction in sequence, add up the candidate conversion coefficients of all wire rope images in the horizontal direction and take the average value to obtain the conversion coefficient between pixels and actual size in the horizontal direction; similarly, calculate the conversion coefficient between pixels and actual size in the vertical direction.

3. The non-contact, one-time detection method for elevator wire rope wear according to claim 2, characterized in that, Step S1 further includes the following sub-steps: Step S15: Install a rotary encoder on the traction sheave of the target elevator and connect the rotary encoder to the industrial camera for data transmission. Step S16: Set the expected sampling interval of the wire rope to be inspected, read the circumference of the traction sheave and the encoder pulses per revolution of the rotary encoder, and calculate the number of trigger pulses corresponding to the industrial camera by combining the expected sampling interval, the circumference of the traction sheave and the encoder pulses per revolution. Step S17: When the number of pulses accumulated by the encoder reaches the number of trigger pulses, a start signal is generated, and the start signal is bound to the trigger pin of the industrial camera to trigger an image acquisition operation of the industrial camera. In step S18, when the target elevator is running, the industrial camera acquires multiple images of the steel wire rope to be inspected.

4. The non-contact method for one-time detection of elevator wire rope wear according to claim 1, characterized in that, Step S2 includes the following sub-steps: Step S21: Acquire multiple images of the steel wire rope to be inspected, then sort the images according to the acquisition time, and number each image. Step S22: Select the image to be identified with the first number, read the pixel value of each pixel in the image to be identified, and then divide the pixel value of each pixel into R value component, G value component and B value component. Step S23: Calculate the pixel grayscale value of the corresponding pixel based on the R value component, G value component and B value component of the pixel. Step S24: Set a fixed-size mean window, align the center of the mean window with any pixel, record the pixels inside the mean window but not in the center as adjacent pixels, sum the gray values ​​of the adjacent pixels and take the average to obtain the optimized gray value, and replace the gray value of the pixel corresponding to the center position with the optimized gray value.

5. The non-contact, one-time detection method for elevator wire rope wear according to claim 4, characterized in that, Step S2 further includes the following sub-steps: Step S25: Use the mean window to traverse all pixels to obtain the optimized grayscale value of all pixels; compare the optimized grayscale value with the grayscale threshold. If the optimized grayscale value is less than or equal to the grayscale threshold, the corresponding pixel is recorded as a contour pixel. If the optimized grayscale value is greater than the grayscale threshold, the corresponding pixel is recorded as a non-contour pixel. Step S26: Connect all adjacent contour pixels to obtain multiple candidate contours, construct the minimum bounding rectangle corresponding to each candidate contour, compare the width of the minimum bounding rectangle with the filtering interval, if the width of the minimum bounding rectangle is within the filtering interval, then record the corresponding candidate contour as a wire rope contour, otherwise discard the corresponding candidate contour; thus obtaining multiple wire rope contours in the corresponding image to be identified. Step S27: Based on the process of obtaining the wire rope contour in step S26, obtain multiple wire rope contours in all images to be identified.

6. The non-contact method for one-time detection of elevator wire rope wear according to claim 1, characterized in that, Step S3 includes the following sub-steps: Step S31: Acquire multiple images to be identified, read the outlines of multiple steel wire ropes to be inspected in the images to be identified, count the number of steel wire rope outlines in each image to be identified, identify the mode of the number of steel wire rope outlines, discard the images to be identified whose number of steel wire rope outlines is different from the mode, and keep the remaining images to be identified. Step S32: Select the leftmost wire rope outline in the image to be identified with the first number, and identify the top pixel and bottom pixel of the corresponding wire rope outline. Step S33: Calculate the outline length of the corresponding wire rope profile based on the top and bottom pixels; draw two trisection lines according to the outline length, and intersect the trisection lines with the wire rope profile to obtain two detection sections of the wire rope profile.

7. The non-contact, one-time detection method for elevator wire rope wear according to claim 6, characterized in that, Step S3 further includes the following sub-steps: Step S34: Extract the pixel coordinates of the left edge point and the right edge point of the detection section above, and then calculate the pixel cross-section diameter of the detection section. Step S35: Obtain the conversion factor between the pixel and the actual size, and multiply the conversion factor by the pixel cross-section diameter to obtain the actual cross-section diameter of the corresponding detection cross-section; multiply the ordinate of the corresponding left edge point of the detection cross-section by the conversion factor to obtain the relative position of the detection cross-section with respect to the steel wire rope to be inspected. Step S36: Extract the pixel coordinates of the left edge point and the right edge point of another detection section and calculate the pixel section diameter of the corresponding detection interface. Then, calculate the actual section diameter of the corresponding detection section and the relative position of the detection section with respect to the steel wire rope to be inspected.

8. The non-contact method for one-time detection of elevator wire rope wear according to claim 7, characterized in that, Step S3 further includes the following sub-steps: Step S37: Select the leftmost wire rope outline in the second-ranked image to be identified, and then calculate the actual cross-sectional diameter and the relative position of the detection cross-section to the wire rope to be inspected for the two detection cross-sections in the corresponding image to be identified; then calculate the actual cross-sectional diameter and the relative position of the detection cross-section to the wire rope to be inspected for the two detection cross-sections in all images to be identified. Step S38: Read the nominal diameter of the steel wire rope to be inspected, and calculate the wear rate at each inspection section based on the nominal diameter; Step S39: Collect Greek letters to mark the wire rope outline in each image to be identified, and regard the wire rope outline with the same mark in different images to be identified as the wire rope outline of the same wire rope to be inspected. The wear rate curve of the entire length of the steel wire rope under test is obtained by plotting the relative position of the test section with respect to the test section on the x-axis and the wear rate at each test section on the y-axis.

9. The non-contact method for one-time detection of elevator wire rope wear according to claim 1, characterized in that, Step S4 includes the following sub-steps: Step S41: Obtain the full-length wear curves of all the wire ropes to be inspected, and plot a qualified state curve and a warning state curve on the full-length wear curve of each wire rope to be inspected. Step S42: For any wire rope to be inspected, if the wear curve of the entire length of the wire rope to be inspected intersects with the warning state curve, then the state of the corresponding wire rope to be inspected is recorded as scrapped state. Step S43: If the full-length wear curve of the steel wire rope to be inspected does not intersect with the warning state curve, then identify the intersection of the full-length wear curve of the steel wire rope to be inspected with the qualified state curve. If there is an intersection, then record the state of the corresponding steel wire rope to be inspected as the warning state, and the area of ​​the full-length wear curve after the odd number of intersections is recorded as the warning area. Step S44: If the wear curve of the entire length of the wire rope to be inspected does not intersect with the qualified state curve, then the state of the corresponding wire rope to be inspected is recorded as qualified state. Step S45: Perform corresponding operations on the steel wire rope to be inspected based on its condition.

10. A non-contact, one-time detection method for elevator wire rope wear according to claim 9, characterized in that, If the steel wire rope to be inspected is in a scrapped state, the corresponding steel wire rope to be inspected shall be replaced immediately; if the steel wire rope to be inspected is in a warning state, the warning area of ​​the steel wire rope to be inspected shall be maintained; if the steel wire rope to be inspected is in a qualified state, no operation shall be performed.

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