Fault detection method and device of outgoing line, computer equipment and storage medium

Abstract

The embodiment of the invention discloses a fault detection method and device for an outgoing line, computer equipment and a storage medium. The method comprises the following steps: acquiring a target image of the outgoing line containing a motor part; performing key point identification processing on the target image to obtain key point information of the outgoing line in the target image; determining an outgoing line area of the target image based on the key point information; and performing deformation fault detection on the outgoing line according to the outgoing line area to obtain a deformation fault detection result of the outgoing line. The outgoing line area in the target image can be determined through image processing, whether the outgoing line deforms or not can be determined according to the area, and whether the outgoing line has a deformation fault or not can be accurately detected.

Description

Technical Field

[0001] The present application relates to the technical field of fault detection, and in particular to a method, apparatus, computer equipment and storage medium for detecting faults of lead wires, wherein the storage medium is a computer-readable storage medium. Background Art

[0002] During motor operation, lead wires may deform, significantly impacting the motor's operational safety and stability. Currently, there are two main methods for monitoring these blind spots: First, after the motor is shut down, manual inspections using an endoscope are performed to eliminate any anomalies. This method is labor-intensive and carries significant risk of human error. Summary of the Invention

[0003] The embodiments of the present application provide a lead wire fault detection method, apparatus, computer equipment, and storage medium, which can accurately detect deformation faults of the lead wire.

[0004] An embodiment of the present application provides a method for detecting a fault in a lead-out line, comprising:

[0005] Acquire a target image including lead wires of the motor part;

[0006] Performing key point recognition processing on the target image to obtain key point information of the lead-out line in the target image;

[0007] Determining a lead-out area of ​​the target image based on the key point information;

[0008] A deformation fault detection is performed on the lead wire according to the lead wire area to obtain a deformation fault detection result of the lead wire.

[0009] Accordingly, an embodiment of the present application further provides a lead-out line fault detection device, comprising:

[0010] an acquisition unit, configured to acquire a target image including lead wires of a motor part;

[0011] an identification unit, configured to perform key point identification processing on the target image to obtain key point information of the lead-out line in the target image;

[0012] a determining unit, configured to determine a lead-out line area of ​​the target image based on the key point information;

[0013] The detection unit is used to perform deformation fault detection on the lead wire according to the area of ​​the lead wire to obtain a deformation fault detection result of the lead wire.

[0014] Correspondingly, an embodiment of the present application also provides a computer device, including a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute any lead wire fault detection method provided in the embodiment of the present application.

[0015] Accordingly, an embodiment of the present application further provides a computer-readable storage medium, which is used to store a computer program. The computer program is loaded by a processor to execute any lead-out line fault detection method provided in the embodiment of the present application.

[0016] The embodiments of the present application acquire a target image containing lead wires from a motor; perform key point recognition processing on the target image to obtain key point information of the lead wires in the target image; determine the lead wire area in the target image based on the key point information; and perform deformation fault detection on the lead wires based on the lead wire area to obtain a deformation fault detection result for the lead wires. This allows the lead wire area in the target image to be determined through image processing, and further, whether the lead wires are deformed based on the area, thereby accurately detecting whether a deformation fault has occurred in the lead wires. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 This is a flow chart of a method for detecting a fault in a lead-out line provided in an embodiment of the present application;

[0019] Figure 2 This is a schematic diagram of lead lines and corner points provided in an embodiment of the present application;

[0020] Figure 3 This is a schematic diagram of the positional relationship between the lead wires and the camera provided in an embodiment of the present application;

[0021] Figure 4 Schematic diagram of a fault detection device for lead wires provided in an embodiment of the present application;

[0022] Figure 5 It is a structural diagram of the computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0024] The present invention provides a method, device, computer equipment, and computer-readable storage medium for detecting a fault in a lead-out line. The lead-out line fault detection device can be integrated into a computer equipment, which can be a server or a terminal.

[0025] The terminal may include a mobile phone, a wearable smart device, a tablet computer, a laptop computer, a personal computer (PC), and a vehicle-mounted computer.

[0026] Among them, the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, as well as big data and artificial intelligence platforms.

[0027] It should be noted that the order of description of the following embodiments is not intended to limit the preferred order of the embodiments.

[0028] This embodiment will be described from the perspective of a lead-out line fault detection device. The lead-out line fault detection device may be integrated into a computer device, which may be a server or a terminal.

[0029] The present application provides a method for detecting a fault in a lead wire, such as Figure 1 As shown, the specific process of the lead-out line fault detection method can be as follows:

[0030] 101. Acquire a target image including lead wires of a motor part.

[0031] The motor part may be, for example, a rotor pole or winding of a generator, or other parts of the generator, or parts of other motors other than the generator, without limitation. Lead wires from the motor part may extend the internal electrical connections of the motor to the outside for connection to a power source, control system, or other equipment. In one embodiment, the motor part may be a rotor pole of a hydro-generator, and the lead wires may be wires extending from the windings of the rotor pole or other electrical components to the outside.

[0032] The target image includes lead wires of a motor portion, so that fault detection of the lead wires can be performed based on the target image.

[0033] The target image may be an image acquired by capturing the lead wires, or may be an image acquired by performing image processing on the captured image. That is, in one embodiment, before the step of "acquiring a target image including the lead wires of the motor part", the method further includes:

[0034] Acquire an original image collected for the lead-out line;

[0035] Gray-scale the original image to obtain a grayscale image corresponding to the original image;

[0036] For each pixel in the grayscale image, determining a threshold value corresponding to the pixel according to the pixel values ​​of each pixel in the target image area corresponding to the pixel;

[0037] The grayscale image is binarized according to the pixel value of each pixel in the grayscale image and the corresponding threshold value to obtain the target image.

[0038] An original image captured for the lead-out line is acquired.

[0039] The original image is grayscaled to obtain a grayscale image corresponding to the original image. Optionally, the grayscale value of each pixel can be determined by the following formula, where I gray is the grayscale value of the pixel.

[0040] I gray =0.2989×R+0.5870×G+0.1140×B

[0041] The target image area corresponding to each pixel in the grayscale image can be an image block centered on the pixel, such as a 3×3 image block. The threshold is determined based on the average grayscale value or weighted grayscale value of the target image area. The weighted grayscale value can be Gaussian weighted, etc.

[0042] The grayscale image is binarized according to the pixel value of each pixel in the grayscale image and the corresponding threshold value to obtain the target image. For example, pixels greater than the threshold value may be set to black, and pixels less than the threshold value may be set to white.

[0043] In one embodiment, the grayscale image may be binarized using an adaptive threshold algorithm to obtain a target image.

[0044] In one embodiment, the original image captured by the lead-out line, that is, the captured color image, can be grayscaled using the formula Igray=0.2989×R+0.5870×G+0.1140×B to obtain a grayscale image. Then, Gaussian Blur is used to remove noise in the image. A convolution kernel of 3x3 can be set for denoising to smooth the image and retain edge information. The denoised grayscale image is converted into a binary image using an adaptive threshold method to obtain a target image, thereby ensuring that the lead-out line portion in the target image is clearly visible.

[0045] 102. Perform key point recognition processing on the target image to obtain key point information of the lead-out line in the target image.

[0046] The target image is subjected to key point recognition processing, specifically, the image region where the lead line is located can be recognized in the target image, and the key point can be the pixel point in the target image that contains the lead line.

[0047] In one embodiment, key point recognition processing can obtain detection points on the outline of the lead line in the target image, and the key point information can include information related to the target detection point. Specifically, determining the target detection point from multiple detection points can include determining a first detection point with the highest ranking from the multiple detection points, where the first detection point can be the detection point with the smallest y value in the coordinates (x, y). The other detection points are ranked based on the angles of the vectors formed between the other detection points and the first detection point, with the detection points with smaller angles to the first detection point being ranked higher. For multiple detection points with the same angle to the vectors formed with the first detection point, the detection points with the greatest distance from the first detection point are ranked higher.

[0048] The first detection point and the second detection point are taken as target detection points, and the second detection point is ranked just after the first detection point.

[0049] Calculate the cross product of the vector formed from the first detection point to the second detection point and the vector formed from the second detection point to the third detection point (the third detection point is the next detection point of the second detection point).

[0050] If the result is not greater than zero, obtain the next detection point of the third detection point, that is, the fourth detection point, and calculate the cross product of the vector formed from the first detection point to the second detection point and the vector formed from the second detection point to the fourth detection point. If the result is greater than zero, use the fourth detection point as the target detection point.

[0051] If the cross product of the vector from the first detection point to the second detection point and the vector from the second detection point to the third detection point is greater than zero, the third detection point is selected as the target detection point. The cross product of the vector from the second detection point to the third detection point and the vector from the third detection point to the fourth detection point is calculated. If the result is greater than zero, the fourth detection point is selected as the target detection point. The fourth detection point is the detection point after the third detection point, and so on. After all detection points have been traversed, the key point information of the target image is obtained based on the determined target detection points. In other words, the key point information includes the target detection points and the order in which the target detection points are determined.

[0052] In one embodiment, the key point information may include information associated with corner points of a lead line in a target image. The step of “performing key point recognition processing on the target image to obtain key point information of the lead line in the target image” may include:

[0053] Performing corner point recognition processing on the target image to obtain multiple corner points of the lead-out lines in the target image;

[0054] Determining a first corner point from the plurality of corner points according to the coordinates of each corner point;

[0055] determining an arrangement order of the second corner points according to a positional relationship between the first corner point and a second corner point among the plurality of corner points;

[0056] The key point information is obtained according to the arrangement order and the multiple corner points.

[0057] Among them, the corner point recognition processing can identify the corner points of the lead lines from the target image, and the corner point recognition processing can be performed on the target image through corner point detection algorithms such as Shi-Tomasi and Harris to obtain multiple corner points in the target image.

[0058] A first corner point is determined from the multiple corner points according to the coordinates of each corner point. Specifically, the corner point with the largest or smallest y value can be determined as the first corner point. The second corner points are sorted according to the angles of the straight lines formed by other corner points (i.e., the second corner point) and the first corner point to obtain an arrangement order of the second corner points, wherein the smaller the angle, the higher the order, and the first corner point is sorted first. Key point information is obtained according to the arrangement order of the first corner point and the second corner point, as well as between the corner points.

[0059] For example, the shape of the lead wire can be as follows Figure 2 As shown, the corner points obtained by the corner point recognition process can be as follows Figure 2 The coordinate points shown, Figure 2 In the example, (x1, y1) is used as the first corner point, and the order of other corner points is as follows: Figure 2As shown, (x2, y2) is the second most ordered corner point, (x3, y3) is the third most ordered corner point, and so on.

[0060] In one example, the step of “performing corner point recognition processing on the target image to obtain multiple corner points of the lead lines in the target image” may specifically include:

[0061] Performing edge detection processing on the target image to obtain an edge image corresponding to the target image;

[0062] Performing contour extraction processing on the edge image to obtain a lead line contour image;

[0063] Corner points of the lead-out line contour image are extracted to obtain multiple corner points of the lead-out line in the target image.

[0064] Specifically, the target image can be subjected to edge detection processing by adopting the Canny edge detection algorithm to obtain an edge image corresponding to the target image, and then the contour can be extracted based on the edge image to obtain contour information in the target image, and contours that meet the conditions can be screened out from the extracted contour information to obtain a lead-out line contour image. The contours that meet the conditions can, for example, have an area that meets a preset area range, a perimeter that meets a preset perimeter range, a shape that is a preset shape, etc., and can be specifically set according to the structure of the lead-out line.

[0065] 103. Determine a lead-out line area of ​​the target image based on the key point information.

[0066] In one embodiment, if the key point information can indicate that the target image includes pixels of the lead-out line, step 103 can specifically determine the area of ​​the lead-out line according to the number of key points.

[0067] If the key point information includes target detection points on the lead-out line contour in the target image, step 103 may specifically be: calculating the first product of the first coordinate component of each target key point and the second coordinate component of the next target key point according to the determination order of the target key points; and calculating the second product of the second coordinate component of each target key point coordinate and the first coordinate component of the next target key point coordinate; and determining the lead-out line area according to the sum of the first products and the difference between the second products.

[0068] If the key point information includes corner points of the lead-out line in the target image and the order of arrangement between the corner points, the step of "determining the area of ​​the lead-out line of the target image based on the key point information" may include:

[0069] Calculate, in accordance with the arrangement order, a first product of the first coordinate component of each corner point and the second coordinate component of the next corner point;

[0070] Calculate, in accordance with the arrangement order, a second product of the second coordinate component of each corner point and the first coordinate component of the next corner point;

[0071] The lead-out line area is determined according to the sum of the first products and the sum of the second products of the multiple corner points.

[0072] by Figure 2 Taking the lead lines, corner points, and the order of the corner points shown in FIG. 1 as an example, the lead line area of ​​the target image is calculated as follows, where Area is the lead line area.

[0073]

[0074] 104. Perform deformation fault detection on the lead wire according to the lead wire area to obtain a deformation fault detection result of the lead wire.

[0075] The lead wire area can be compared with the preset area. If the lead wire area is significantly different from the preset area, it can be determined that the lead wire is deformed.

[0076] In one embodiment, the lead line area may be determined based on the target image and the historical lead line area to determine the lead line deformation fault detection result, that is, the step of "performing deformation fault detection on the lead line according to the lead line area to obtain the lead line deformation fault detection result" includes:

[0077] Acquire a historical lead-out line area, where the historical lead-out line area is determined based on a historical image containing the lead-out line acquired before the target image;

[0078] determining a degree of deformation of the lead wire according to a difference between the historical lead wire area and the lead wire area;

[0079] A deformation fault detection result of the lead wire is determined according to the deformation degree.

[0080] The deformation fault detection of the lead wire may be performed periodically, for example, once per second or once per hour, and the historical lead wire area may be the lead wire area determined by the last deformation fault detection.

[0081] The difference between the historical lead-out area and the lead-out area is calculated, and the degree of deformation of the lead-out line is determined according to the difference. For example, the difference may be used as the degree of deformation, or the absolute value of the difference may be used as the degree of deformation.

[0082] In one embodiment, the deformation degree includes a deformation amount, and the step of “determining the deformation degree of the lead line according to the difference between the historical lead line area and the lead line area” may include:

[0083] Determining a difference between the historical lead-out area and the lead-out area;

[0084] The deformation amount of the lead-out line is determined according to the ratio between the difference and the historical lead-out line area.

[0085] Determine the difference between the historical lead line area and the lead line area; determine the ratio between the difference and the historical lead line area as the deformation amount of the lead line, or determine the absolute value of the ratio between the difference and the historical lead line area as the deformation amount of the lead line.

[0086] If the deformation degree satisfies a preset condition, it is determined that the lead wire is deformed. In one embodiment, the step of "determining a deformation fault detection result of the lead wire according to the deformation degree" includes:

[0087] If the deformation amount is greater than a preset threshold, it is determined that a deformation fault occurs in the lead wire.

[0088] For example, the deformation amount can be determined by the following formula, where A current is the lead area determined according to the target image, A previous is the historical lead area.

[0089] R=|A current -A previous | / A previous

[0090] If the deformation amount R exceeds 5%, it is determined that the lead wire has a deformation fault. If the deformation amount R does not exceed 5%, it is determined that the lead wire has no deformation fault.

[0091] After performing deformation fault detection on the lead wire according to the lead wire area and obtaining the deformation fault detection result of the lead wire, the method further includes:

[0092] If a deformation fault occurs in the lead wire, a fault prompt message is generated.

[0093] Optionally, each monitoring result can be recorded in a database and a report can be generated for subsequent analysis.

[0094] Optionally, when a deformation fault of the lead wire is detected, the computer equipment automatically issues an abnormal reminder to remind relevant personnel to perform maintenance. For example, a prompt message can be sent to the terminal used by the relevant personnel to remind them that the lead wire is deformed.

[0095] The lead wire fault detection method provided in the embodiment of the present application can be used to detect whether the rotor pole lead wire of a hydro-turbine generator is deformed. When the hydro-turbine generator set is in high speed and high load conditions for a long time, the rotor pole lead wire part is prone to deformation. The lead wire fault detection method provided in the embodiment of the present application can ensure the safety and stability of the generator set operation. The image used for deformation fault retrieval can be obtained by capturing the rotor pole with a high-speed camera. The positional relationship between the camera and the lead wire can be as follows: Figure 3 shown.

[0096] As can be seen from the above, the embodiments of the present application obtain a target image containing lead wires from a motor; perform key point recognition processing on the target image to obtain key point information of the lead wires in the target image; determine the lead wire area in the target image based on the key point information; and perform deformation fault detection on the lead wires based on the lead wire area to obtain a lead wire deformation fault detection result. This method can determine the lead wire area in the target image through image processing, and then determine whether the lead wires are deformed based on the area, thereby accurately detecting whether the lead wires have deformation faults.

[0097] In order to facilitate better implementation of the lead wire fault detection method provided in the embodiment of the present application, a lead wire fault detection device is also provided in one embodiment. The meanings of the terms are the same as those in the lead wire fault detection method described above, and the specific implementation details can be referred to the description in the method embodiment.

[0098] The fault detection device of the lead wire can be integrated into a computer device, such as Figure 4 As shown, the lead-out line fault detection device may include: an acquisition unit 301, an identification unit 302, a determination unit 303 and a detection unit 304, specifically as follows:

[0099] (1) An acquisition unit 301 is used to acquire a target image including lead wires of a motor part.

[0100] (2) A recognition unit 302 is used to perform key point recognition processing on the target image to obtain key point information of the lead-out line in the target image.

[0101] (3) A determination unit 303, configured to determine the lead-out area of ​​the target image based on the key point information.

[0102] (4) A detection unit 304, configured to perform deformation fault detection on the lead wire according to the lead wire area, and obtain a deformation fault detection result of the lead wire.

[0103] In one embodiment, the identification unit 302 may also be used to:

[0104] Performing corner point recognition processing on the target image to obtain multiple corner points of the lead-out lines in the target image;

[0105] Determining a first corner point from the plurality of corner points according to the coordinates of each corner point;

[0106] determining an arrangement order of the second corner points according to a positional relationship between the first corner point and a second corner point among the plurality of corner points;

[0107] The key point information is obtained according to the arrangement order and the corner points.

[0108] In one embodiment, the determining unit 303 may also be configured to:

[0109] Calculate, in accordance with the arrangement order, a first product of the first coordinate component of each corner point and the second coordinate component of the next corner point;

[0110] Calculate, in accordance with the arrangement order, a second product of the second coordinate component of each corner point and the first coordinate component of the next corner point;

[0111] The lead-out line area is determined according to the sum of the first products and the sum of the second products of the multiple corner points.

[0112] In one embodiment, the identification unit 302 may also be used to:

[0113] Performing edge detection processing on the target image to obtain an edge image corresponding to the target image;

[0114] Performing contour extraction processing on the edge image to obtain a lead line contour image;

[0115] Corner points of the lead-out line contour image are extracted to obtain multiple corner points of the lead-out line in the target image.

[0116] In one embodiment, the lead-out line fault detection device may further include:

[0117] An acquisition unit, configured to acquire an original image acquired for the lead-out line;

[0118] A grayscale unit, configured to grayscale the original image to obtain a grayscale image corresponding to the original image;

[0119] a threshold determination unit, configured to determine, for each pixel in the grayscale image, a threshold corresponding to the pixel according to pixel values ​​of each pixel in the target image area corresponding to the pixel;

[0120] The binarization unit is used to perform binarization processing on the grayscale image according to the pixel value of each pixel in the grayscale image and the corresponding threshold value to obtain the target image.

[0121] In one embodiment, the detection unit 304 may also be used to:

[0122] Acquire a historical lead-out line area, where the historical lead-out line area is determined based on a historical image containing the lead-out line acquired before the target image;

[0123] determining a degree of deformation of the lead wire according to a difference between the historical lead wire area and the lead wire area;

[0124] A deformation fault detection result of the lead wire is determined according to the deformation degree.

[0125] In one embodiment, the deformation degree includes a deformation amount, and the detection unit 304 may further be used to:

[0126] Determining a difference between the historical lead-out area and the lead-out area;

[0127] determining a deformation amount of the lead-out line according to a ratio between the difference and the area of ​​the historical lead-out line;

[0128] If the deformation amount is greater than a preset threshold, it is determined that a deformation fault occurs in the lead wire.

[0129] As can be seen from the above, the lead wire fault detection device of the embodiment of the present application obtains a target image of the lead wires including the motor portion via an acquisition unit 301; an identification unit 302 performs key point recognition processing on the target image to obtain key point information of the lead wires in the target image; a determination unit 303 determines the lead wire area in the target image based on the key point information; and a detection unit 304 performs deformation fault detection on the lead wires based on the lead wire area to obtain a lead wire deformation fault detection result. This allows the lead wire area in the target image to be determined through image processing, and further, whether the lead wires are deformed based on the area, thereby accurately detecting whether a deformation fault has occurred in the lead wires.

[0130] The embodiment of the present application also provides a computer device, which can be a terminal or a server. Figure 5 , which shows a schematic diagram of the structure of the computer device involved in the embodiment of the present application, specifically:

[0131] The computer device may include one or more processing core processors 1001, one or more computer readable storage media memories 1002, a power supply 1003, an input unit 1004 and other components. Those skilled in the art will understand that Figure 5The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently.

[0132] Processor 1001 is the control center of the computer device. It connects the various components of the entire computer device using various interfaces and lines. By running or executing software programs and / or modules stored in memory 1002 and accessing data stored in memory 1002, it performs various functions of the computer device and processes data, thereby providing overall monitoring of the computer device. Optionally, processor 1001 may include one or more processing cores. Preferably, processor 1001 may integrate an application processor and a modem processor. The application processor primarily processes the operating system, user interface, and computer programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 1001.

[0133] The memory 1002 can be used to store software programs and modules. The processor 1001 executes various functional applications and data processing by running the software programs and modules stored in the memory 1002. The memory 1002 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, a computer program required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 1002 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory 1002 may also include a memory controller to provide the processor 1001 with access to the memory 1002.

[0134] The computer device also includes a power supply 1003 for supplying power to various components. Preferably, the power supply 1003 can be logically connected to the processor 1001 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. The power supply 1003 can also include one or more DC or AC power supplies, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and other arbitrary components.

[0135] The computer device may further include an input unit 1004, which may be configured to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0136] Although not shown, the computer device may further include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 1001 in the computer device will load the executable files corresponding to one or more computer program processes into the memory 1002 according to the following instructions, and the processor 1001 will run the computer programs stored in the memory 1002 to implement various functions as follows:

[0137] Acquire a target image including lead wires of the motor part;

[0138] Perform key point recognition processing on the target image to obtain key point information of the lead line in the target image;

[0139] Determine the lead-out area of ​​the target image based on the key point information;

[0140] The lead wire is subjected to deformation fault detection according to the lead wire area to obtain a deformation fault detection result of the lead wire.

[0141] The specific implementation of the above operations can be found in the previous embodiments and will not be described in detail here.

[0142] As can be seen from the above, the computer device of the embodiment of the present application can obtain a target image containing lead wires from a motor part; perform key point recognition processing on the target image to obtain key point information of the lead wires in the target image; determine the lead wire area in the target image based on the key point information; and perform deformation fault detection on the lead wires based on the lead wire area to obtain a deformation fault detection result for the lead wires. This allows the area of ​​the lead wires in the target image to be determined through image processing, and further, whether the lead wires are deformed based on the area, thereby accurately detecting whether a deformation fault has occurred in the lead wires.

[0143] According to one aspect of the present application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in various optional implementations of the above embodiments.

[0144] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by a computer program, or by controlling related hardware through a computer program. The computer program may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0145] To this end, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. The computer program can be loaded by a processor to execute any lead wire fault detection method provided in the embodiment of the present application.

[0146] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0147] The computer-readable storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0148] Since the computer program stored in the computer-readable storage medium can execute any lead wire fault detection method provided in the embodiments of the present application, the beneficial effects that can be achieved by any lead wire fault detection method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0149] The above is a detailed introduction to a lead wire fault detection method, device, computer equipment and computer-readable storage medium provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for detecting a fault of a lead wire, characterized in that: The method comprises: Acquire a target image including lead wires of the motor part; Performing key point recognition processing on the target image to obtain key point information of the lead-out line in the target image; Determining a lead-out area of ​​the target image based on the key point information; A deformation fault detection is performed on the lead wire according to the lead wire area to obtain a deformation fault detection result of the lead wire.

2. The method according to claim 1, characterized in that The performing key point recognition processing on the target image to obtain key point information of the lead-out line in the target image includes: Performing corner point recognition processing on the target image to obtain multiple corner points of the lead-out lines in the target image; Determining a first corner point from the plurality of corner points according to the coordinates of each corner point; determining an arrangement order of the second corner points according to a positional relationship between the first corner point and a second corner point among the plurality of corner points; The key point information is obtained according to the arrangement order and the multiple corner points.

3. The method according to claim 2, characterized in that The determining the lead-out line area of ​​the target image based on the key point information includes: Calculate, in accordance with the arrangement order, a first product of the first coordinate component of each corner point and the second coordinate component of the next corner point; Calculate, in accordance with the arrangement order, a second product of the second coordinate component of each corner point and the first coordinate component of the next corner point; The lead-out line area is determined according to the sum of the first products and the sum of the second products of the plurality of corner points.

4. The method according to claim 2, characterized in that The performing corner point recognition processing on the target image to obtain a plurality of corner points of the lead-out lines in the target image includes: Performing edge detection processing on the target image to obtain an edge image corresponding to the target image; Performing contour extraction processing on the edge image to obtain a lead line contour image; Corner points of the lead-out line contour image are extracted to obtain multiple corner points of the lead-out line in the target image.

5. The method according to claim 1, wherein Before acquiring the target image including the lead wires of the motor part, the method further includes: Acquire an original image collected for the lead-out line; Gray-scale the original image to obtain a grayscale image corresponding to the original image; For each pixel in the grayscale image, determining a threshold value corresponding to the pixel according to the pixel values ​​of each pixel in the target image area corresponding to the pixel; The grayscale image is binarized according to the pixel value of each pixel in the grayscale image and the corresponding threshold value to obtain the target image.

6. The method according to any one of claims 1 to 5, characterized in that The step of performing deformation fault detection on the lead wire according to the lead wire area to obtain a deformation fault detection result of the lead wire includes: Acquire a historical lead-out line area, where the historical lead-out line area is determined based on a historical image containing the lead-out line acquired before the target image; determining a degree of deformation of the lead wire according to a difference between the historical lead wire area and the lead wire area; A deformation fault detection result of the lead wire is determined according to the deformation degree.

7. The method according to claim 6, characterized in that The deformation degree includes a deformation amount, and determining the deformation degree of the lead line according to the difference between the historical lead line area and the lead line area includes: Determining a difference between the historical lead-out area and the lead-out area; determining a deformation amount of the lead-out line according to a ratio between the difference and the area of ​​the historical lead-out line; The step of determining the deformation fault detection result of the lead wire according to the deformation degree includes: If the deformation amount is greater than a preset threshold, it is determined that a deformation fault occurs in the lead wire.

8. A lead-out line fault detection device, characterized in that: include: an acquisition unit, configured to acquire a target image including lead wires of a motor part; an identification unit, configured to perform key point identification processing on the target image to obtain key point information of the lead-out line in the target image; a determining unit, configured to determine a lead-out line area of ​​the target image based on the key point information; The detection unit is used to perform deformation fault detection on the lead wire according to the area of ​​the lead wire to obtain a deformation fault detection result of the lead wire.

9. A computer device, characterized in that: It comprises a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the lead wire fault detection method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium is used to store a computer program, and the computer program is loaded by a processor to execute the lead-out line fault detection method according to any one of claims 1 to 7.

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