Foreign matter detection method and system for drag chain cable production line, medium and program product

Abstract

The invention discloses a drag chain cable production line foreign matter detection method and system, a medium and a program product, and the method comprises the steps: determining production parameters according to drag chain cable parameters in a current production line; judging whether the current weight of the drag chain cable in the first area is equal to the standard weight; if not, the laser scanning device is controlled to scan the first area within the first time, and a scanning result is obtained; judging whether scattered light intensity greater than preset light intensity exists in the scanning result or not; if yes, the drag chain cable is transferred to a first waste area; if not, controlling the multispectral camera equipment to shoot a spectral image; judging whether the spectral image is the same as a standard spectrum corresponding to the standard material or not; if not, transferring the drag chain cable to a second waste area; if yes, marking the drag chain cable as a qualified product; and if yes, controlling the multispectral camera equipment to shoot the spectral image after determining that the tow chain cable enters the second area, thereby improving the accuracy of foreign matter detection of the tow chain cable production line.

Description

Technical Field

[0001] The present application belongs to the field of foreign body detection, and in particular, relates to a method, system, medium and program product for detecting foreign bodies in a drag chain cable production line. Background Art

[0002] Drag chain cables are important components used in machine tools and mechanical equipment to protect and guide wires, air pipes, etc. Due to their complex working environment and frequent physical friction and bending, the quality requirements for cables are extremely high. Foreign body detection refers to the detection and removal of any unexpected materials or defects that may affect the performance of the cable during the cable production process. In recent years, with the development of automation and intelligent technology, the foreign body detection technology of drag chain cable production lines has also made significant progress. In modern production lines, high-resolution visual inspection systems, system X-ray inspection technology, and ultrasonic inspection technology are usually used to identify and eliminate foreign matter and defects in the production process.

[0003] However, the resolution of the camera is limited, and it is difficult to accurately detect some tiny foreign objects. In addition, some foreign objects similar to cable materials may be difficult to distinguish due to the similarities in density, refractive index or acoustic properties of cable materials. There are many kinds of foreign objects in the production line, and the related technology methods for detecting foreign objects in drag chain cable production lines are difficult to detect completely, which will reduce the accuracy of foreign object detection. Summary of the invention

[0004] The present application provides a method for detecting foreign matter in a drag chain cable production line, which is used to improve the accuracy of foreign matter detection in a drag chain cable production line.

[0005] In a first aspect, the present application provides a method for detecting foreign matter in a drag chain cable production line, wherein production parameters are determined according to the parameters of the drag chain cables in the current production line, and the production parameters include standard materials and standard weights; Determine whether the current weight of the drag chain cable in the first area is equal to the standard weight; If the current weight is not equal to the standard weight, the laser scanning device is controlled to scan the first area within a first time to obtain a scanning result, where the first time is the time required for the drag chain cable to pass through the first area; Determine whether there is scattered light intensity greater than the preset light intensity in the scanning result; If present, the drag chain cable is transferred to the first scrap area; If not, after determining that the drag chain cable enters the second area, controlling the multi-spectral camera device to capture a spectral image; Determine whether the spectrum image is the same as the standard spectrum corresponding to the standard material; If they are not the same, the drag chain cable will be transferred to the second scrap area; If they are the same, the drag chain cable will be marked as qualified; If the current weight is equal to the standard weight, the step of controlling the multi-spectral camera device to capture a spectral image is performed after determining that the drag chain cable enters the second area.

[0006] By adopting the above technical solution, in the first stage, by judging whether the actual weight of the drag chain cable is consistent with the standard weight, cables with abnormal weight can be quickly screened out. For cables with abnormal weight, laser scanning equipment is used for scanning. By analyzing the distribution of scattered light intensity, the position of foreign matter can be accurately located, providing a basis for subsequent foreign matter cleaning and cause analysis. In the second stage, by identifying cable materials through multi-spectral imaging technology, quality problems caused by material mixing or adulteration can be found, further ensuring the consistency of product quality. At the same time, by dynamically adjusting the production line speed and scanning time, while ensuring the detection accuracy, the impact of detection on production efficiency is minimized. In addition, the detection results are linked with subsequent processes such as waste transfer and qualified product marking to achieve seamless connection between foreign matter detection and quality control, improve the intelligence level of the production line, and improve the accuracy of foreign matter detection in the drag chain cable production line.

[0007] In conjunction with some embodiments of the first aspect, in some embodiments, determining whether the current weight of the drag chain cable in the first area is equal to the standard weight specifically includes: Receiving real-time monitoring video captured by monitoring equipment in the first area; After determining that the drag chain cable has completely entered the first area according to the real-time monitoring video, receiving the current weight sent by the weight detection device; Determine whether the current weight is equal to the standard weight.

[0008] By adopting the above technical solutions and introducing visual monitoring technology, the reliability and accuracy of weight detection are improved. By real-time monitoring video to determine whether the drag chain cable has completely entered the weighing area, it is possible to avoid measurement errors caused by weighing when the cable is partially entered. At the same time, by confirming the cable position through visual technology, the weighing process can be automatically triggered without manual intervention, which improves weighing efficiency. In addition, through visual monitoring, the movement status and production rhythm of the cable can be recorded in real time, providing data support for optimizing the production process. Combining weight detection with machine vision improves the accuracy of weight abnormality judgment.

[0009] In combination with some embodiments of the first aspect, in some embodiments, if the current weight is not equal to the standard weight, controlling the laser scanning device to scan the first area within a first time to obtain a scanning result specifically includes: If the current weight is not equal to the standard weight, the running speed of the production line is reduced to a first running speed, which is lower than the initial running speed of the production line; determining a run length of the first region; A first time is calculated based on the running length and the first running speed; The laser scanning device is controlled to scan the first area within a first time to obtain a scanning result.

[0010] By adopting the above technical solutions, the impact of foreign body detection on production efficiency is minimized while ensuring scanning accuracy. When abnormal weight is detected, the cable stays in the scanning area for a longer time by reducing the production line speed, thereby providing sufficient time for the laser scanning equipment to complete a comprehensive scan. At the same time, by accurately calculating the length of the scanning area and the speed of the production line, the scanning time can be optimized and controlled to avoid delays in production cycles caused by excessive scanning time. This method of dynamically adjusting scanning parameters according to actual conditions embodies the concept of equipment coordination and process optimization. While improving the foreign body detection rate, it minimizes the impact on production efficiency, thereby maximizing production benefits.

[0011] In conjunction with some embodiments of the first aspect, in some embodiments, controlling the laser scanning device to scan the first area within a first time to obtain a scanning result specifically includes: Controlling the laser scanning device to scan the first area within a first time to obtain scattered light intensity distribution data; Determine the scanned image containing the drag chain cable; The scattered light intensity distribution data is marked at the corresponding position of the scanned image to obtain the scan result.

[0012] By adopting the above technical solution and associating the scattered light intensity distribution data with the scanned image, the scattered light abnormal point can be accurately matched with the specific cable position, providing visual guidance for the location and cleaning of foreign matter. By observing the scattered light intensity distribution pattern, the type and nature of foreign matter, such as metal particles, non-metallic impurities, etc., can be preliminarily judged, providing clues for subsequent defect analysis and process improvement. At the same time, combining the scattered light data with the scanned image to intuitively present the abnormal area also facilitates production management personnel to quickly understand and make decisions, improving communication efficiency and management level. In addition, by accumulating and analyzing historical detection data, the laws and causes of foreign matter can be summarized, providing data support for optimizing production processes and improving quality management systems.

[0013] In combination with some embodiments of the first aspect, in some embodiments, after executing the step of controlling the multi-spectral camera device to capture a spectral image after determining that the drag chain cable enters the second area if the current weight is equal to the standard weight, the method further includes: Counting the number of first scraps and the number of second scraps containing drag chain cables in the first scrap area and the second scrap area respectively; When it is determined that the sum of the first waste quantity and the second waste quantity is greater than a preset threshold, the production line is controlled to stop running, and an early warning message is generated and sent to the control terminal; Determine a key area corresponding to the largest number of the first waste quantity and the second waste quantity; Send the production line sections corresponding to the key areas to the control terminal.

[0014] By adopting the above technical solutions, the number of scraps caused by abnormal weight and abnormal materials can be counted respectively, and the quality problems of the production line in different processes can be quantitatively evaluated, providing a basis for targeted improvements. At the same time, a scrap quantity threshold is set. When the scrap rate exceeds the preset level, the production line is automatically stopped to prevent the quality problem from further expanding and reduce unnecessary losses. After the line is stopped, the system will also automatically generate early warning information to notify relevant personnel to deal with it in time, thereby improving the timeliness of abnormal response. In addition, by analyzing the proportion of scrap quantity, the key problem areas of the production line can be determined, which helps managers quickly locate the root cause of the problem and optimize resource allocation. Associating quality problems with specific production line sections provides feasible solutions for carrying out quality control, process optimization, equipment maintenance, etc. at the section level, and promotes the improvement of the overall operation level of the production line.

[0015] In combination with some embodiments of the first aspect, in some embodiments, after determining that the drag chain cable enters the second area, controlling the multi-spectral camera device to capture a spectral image specifically includes: If it does not exist, determine whether the first time has ended; If the first time has ended, executing the step of controlling the multi-spectral camera device to capture the spectral image; If the first time has not ended, the step of controlling the laser scanning device to scan the first area within the first time to obtain the scanning result is continued to scan the remaining area.

[0016] By adopting the above technical solution, when the weight detection is normal, but the laser scanning finds that there is an abnormal scattered light in a local area, the system will determine whether the remaining scanning time is sufficient. If there is enough time, the unscanned area will continue to be inspected until it is fully covered to ensure the integrity of foreign body detection; if there is insufficient time, material testing will be given priority to maximize the use of existing test results while ensuring the normal production process. This practice of dynamically adjusting the detection plan according to actual conditions embodies the concept of flexible production. By flexibly coordinating multiple links such as weight detection, laser scanning, and spectral analysis, while strictly controlling product quality, it also minimizes the impact of detection on production efficiency and achieves a dynamic balance between quality and output. In addition, multi-area scanning can make up for the limitations of a single detection method and improve the accuracy and reliability of foreign body detection through comprehensive analysis of multi-dimensional data.

[0017] In conjunction with some embodiments of the first aspect, in some embodiments, determining whether the spectral image is the same as a standard spectrum corresponding to a standard material specifically includes: De-noising the spectral image to obtain a denoised spectral image; Extract the features of the denoised spectral image to obtain a spectral curve, which represents the material properties of the drag chain cable; The spectral curve is compared with the standard spectral curve corresponding to the standard spectrum to determine whether the spectral image is the same as the standard spectrum corresponding to the standard material.

[0018] By adopting the above technical solutions, the material detection method based on multispectral imaging can realize the rapid identification of the material quality of the drag chain cable through the extraction and comparison of spectral curves, and effectively ensure the consistency of product quality. Using multispectral camera equipment, real-time non-destructive detection of material composition is realized on the production line, which greatly improves the efficiency and response speed of detection. By denoising the collected spectral images, environmental interference and equipment noise can be effectively eliminated, and the signal-to-noise ratio and reliability of spectral data can be improved. On this basis, using feature extraction algorithms, the spectral curve reflecting the material properties can be accurately separated from the spectral image, and the matching degree can be compared with the standard spectrum to quickly determine whether the material meets the quality standards and realize automatic screening of defective products. By quantifying the degree of spectral deviation, the grade division of material quality can also be realized, providing data support for optimizing material procurement and supplier management. In addition, the accumulation of spectral detection data also provides an important basis for process parameter optimization, product consistency control, etc.

[0019] In the second aspect, an embodiment of the present application provides a foreign object detection system for a drag chain cable production line, the system comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0020] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a system, causes the system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a computer program product, characterized in that when the computer program product runs on a system, the system executes the method described in any possible implementation manner in the first aspect.

[0022] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. The present application provides a method for detecting foreign matter in a drag chain cable production line. In the first stage, by judging whether the actual weight of the drag chain cable is consistent with the standard weight, cables with abnormal weight can be quickly screened out. For cables with abnormal weight, a laser scanning device is used for scanning. By analyzing the distribution of scattered light intensity, the position of the foreign matter can be accurately located, providing a basis for subsequent foreign matter cleaning and cause analysis. In the second stage, the cable materials are identified by multi-spectral imaging technology, and quality problems caused by material mixing or adulteration can be found, further ensuring the consistency of product quality. At the same time, by dynamically adjusting the production line speed and scanning time, while ensuring the detection accuracy, the impact of detection on production efficiency is minimized. In addition, the detection results are linked with subsequent processes such as waste transfer and qualified product marking to achieve seamless connection between foreign matter detection and quality control, improve the intelligence level of the production line, and improve the accuracy of foreign matter detection in the drag chain cable production line.

[0023] 2. The present application provides a method for detecting foreign matter in a drag chain cable production line. The association annotation of the scattered light intensity distribution data and the scanned image can accurately correspond the scattered light abnormal points to the specific cable positions, providing visual guidance for the location and cleaning of foreign matter. By observing the scattered light intensity distribution pattern, the type and nature of the foreign matter, such as metal particles, non-metallic impurities, etc., can also be preliminarily judged, providing clues for subsequent defect analysis and process improvement. At the same time, the scattered light data is combined with the scanned image to intuitively present the abnormal area, which is also convenient for production managers to quickly understand and make decisions, improving communication efficiency and management level. In addition, by accumulating and analyzing historical detection data, the laws and causes of foreign matter generation can be summarized, providing data support for optimizing production processes and improving quality management systems.

[0024] 3. The present application provides a method for detecting foreign matter in a drag chain cable production line. The material detection method based on multi-spectral imaging realizes the rapid identification of the material quality of the drag chain cable through the extraction and comparison of spectral curves, and effectively ensures the consistency of product quality. By using multi-spectral camera equipment, real-time non-destructive detection of material components is realized on the production line, which greatly improves the efficiency and response speed of detection. By denoising the collected spectral images, environmental interference and equipment noise can be effectively eliminated, and the signal-to-noise ratio and reliability of spectral data can be improved. On this basis, using feature extraction algorithms, spectral curves reflecting material properties can be accurately separated from spectral images, and the matching degree can be compared with standard spectra to quickly determine whether the materials meet the quality standards and realize automatic screening of defective products. By quantifying the degree of spectral deviation, the grading of material quality can also be realized, providing data support for optimizing material procurement and supplier management. In addition, the accumulation of spectral detection data also provides an important basis for process parameter optimization, product consistency control, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of a method for detecting foreign matter in a drag chain cable production line in an embodiment of the present application.

[0026] Figure 2 It is another flow chart of a method for detecting foreign matter in a drag chain cable production line in an embodiment of the present application.

[0027] Figure 3 It is a schematic diagram of the physical device structure of a drag chain cable production line foreign body detection system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] An application scenario of an embodiment of the present application is described below: In the production workshop of a large machinery manufacturing company, drag chain cables are continuously manufactured on the automated production line. These cables will be used in various machine tools to provide stable and reliable power and signal transmission. However, various foreign objects are inevitably mixed in during the production process, such as metal shavings, plastic fragments, dust, etc. These foreign objects may come from the wear of raw materials, production equipment, or pollution in the environment. If these foreign objects are not discovered and removed in time, as the cables leave the factory and are used, they may cause the insulation performance of the cables to deteriorate, signal transmission to be disturbed, and even cause safety accidents, causing economic losses and safety hazards to the company and customers.

[0031] To ensure product quality, the production line is equipped with a variety of foreign body detection equipment. High-definition cameras scan the cable surface in all directions, while X-ray devices can penetrate the cable to detect internal anomalies. Ultrasonic detection systems use the differences in the propagation speed and reflection characteristics of sound waves in different media to identify the inhomogeneity of materials. These devices perform their respective duties and monitor the quality of cables in real time during the production process. Once suspicious foreign bodies are found, an alarm will be sent to the control system, and the corresponding cables will be automatically removed.

[0032] However, in actual operation, quality management personnel found that a small number of cables with foreign objects still escaped detection. By analyzing the removed cables with foreign objects, they summarized several types of foreign objects that are difficult to identify: some tiny foreign objects, such as metal dust with a diameter of less than 0.1 mm, are small in size but large in number, and will affect cable performance after accumulation; some foreign objects similar to cable materials, such as copper wire heads and insulation material debris, are difficult to effectively distinguish through conventional means because of their similar physical properties such as density and refractive index to cable materials; and some foreign objects with irregular shapes and rough surfaces will interfere with image recognition algorithms.

[0033] Faced with these thorny foreign objects, the existing foreign object detection solutions seem to be somewhat powerless. In order to further improve the foreign object detection rate, engineers decided to optimize the detection system. Their goal is to identify and remove various foreign objects in the production process to the maximum extent without affecting production efficiency, and to minimize the quality accident rate caused by foreign objects. In order to solve the above technical problems, this application provides a method for detecting foreign objects in a drag chain cable production line. Combine the following Figure 1 , a method for detecting foreign matter in a drag chain cable production line in an embodiment of the present application is described: See also Figure 1 , which is a flow chart of a method for detecting foreign matter in a drag chain cable production line in an embodiment of the present application.

[0034] S101, determining production parameters according to the drag chain cable parameters in the current production line; The system determines the production parameters based on the parameters of the drag chain cables in the current production line, including standard materials and standard weights. In this step, the system needs to set the corresponding production parameters based on the specific parameters of the drag chain cables being produced on the current production line. The parameters of the drag chain cables usually include conductor material, conductor cross-sectional area, insulation material, sheath material, cable outer diameter, etc. These parameters determine the electrical properties, mechanical properties and use environment requirements of the cable. Based on these parameters, the system needs to determine the specifications and models of the raw materials required for this production, such as the diameter of the copper wire used for the conductor, the grade of the insulation material, etc., and also set standard production process parameters, such as extrusion temperature, drawing speed, stranding tension, etc. In addition, the system also needs to calculate the standard weight of the cable per unit length based on the cable structure and material density, which serves as an important basis for subsequent quality inspection.

[0035] For example, if the production is a drag chain cable with copper conductor, PVC insulation, PUR sheath, the conductor cross-sectional area is 2.5 square millimeters, and the rated voltage is 300V, the system may determine the following production parameters: the conductor uses oxygen-free copper wire with a diameter of 1.78 mm, the insulation material uses flame-retardant PVC material, the sheath material uses polyurethane TPU, the extrusion temperature is controlled at 180℃ and 210℃ respectively, the drawing speed is set to 50 meters / minute, the stranded wire tension is maintained at 100 Newtons, and the standard weight of each meter of cable should be 120 grams. In this way, through precise parameter setting, the foundation is laid to ensure the consistency of drag chain cable products.

[0036] S102, determining whether the current weight of the drag chain cable in the first area is equal to the standard weight; The system determines whether the current weight of the drag chain cable in the first area is equal to the standard weight, specifically: receiving the real-time monitoring video captured by the monitoring equipment in the first area; After determining that the drag chain cable has completely entered the first area according to the real-time monitoring video, receiving the current weight sent by the weight detection device; Determine whether the current weight is equal to the standard weight.

[0037] In this step, the system performs real-time weight detection on the cables in production in the first area of ​​the production line to determine whether they meet the standard weight requirements. The first area is usually set after drawing and before wrapping. The cable is basically formed in this area and the weight is relatively stable. In order to achieve online weighing, the system will install a high-precision cantilever beam weighing sensor above the cable channel in the first area, and calculate the real-time cable weight by measuring the pressure of the passing cable on the sensor. At the same time, the first area is also equipped with an industrial camera to monitor the passage of the cable. The system analyzes the video screen to determine when the cable completely enters the first area, and uses this as a trigger signal to receive the output data of the weighing sensor to obtain the actual weight of the current cable. The measured weight is compared with the previously calculated standard weight. If the two are equal (a certain error range is allowed), the cable weight is determined to be qualified. Otherwise, the cable weight is considered abnormal and there may be foreign matter or defects.

[0038] For example, through video analysis, the system determined that a section of cable completely entered the first area at 09:30:25, and then received data from the weighing sensor, which showed that the actual measured weight of the cable section was 125 g / m, while the previously calculated standard weight was 120 g / m. Considering that the weighing error is generally within 1%, the system determined that the weight of the cable section obviously exceeded the standard, and initially estimated that metal foreign matter might have been mixed in. For further confirmation, the system decided to start the next step of laser scanning detection.

[0039] S103, controlling the laser scanning device to scan the first area within a first time to obtain a scanning result; If the current weight is not equal to the standard weight, the system controls the laser scanning device to scan the first area within the first time to obtain the scanning result. The first time is the time required for the drag chain cable to pass through the first area. Specifically: if the current weight is not equal to the standard weight, the running speed of the production line is reduced to the first running speed, and the first running speed is less than the initial running speed of the production line; determining a run length of the first region; A first time is calculated based on the running length and the first running speed; Controlling the laser scanning device to scan the first area within a first time to obtain a scanning result specifically includes: Controlling the laser scanning device to scan the first area within a first time to obtain scattered light intensity distribution data; Determine the scanned image containing the drag chain cable; The scattered light intensity distribution data is marked at the corresponding position of the scanned image to obtain the scan result.

[0040] After determining that the cable weight is abnormal, the system will control the laser scanning device to scan and image the suspicious cables in the first area to further analyze the cause of the abnormality. Laser scanning is a non-contact optical detection method that can obtain the three-dimensional morphology and defect information of the object by measuring the scattering and reflection characteristics of the laser on the surface of the object. In this system, the laser scanning device is composed of a line laser and a CCD camera. The laser emits a linear beam that scans across the surface of the cable, and the CCD camera captures the stripe pattern formed by the laser on the surface of the cable. Since foreign matter and defects will cause changes in the laser scattering intensity, the spatial position of foreign matter and defects can be determined by analyzing the distribution characteristics of the position, width and brightness of the stripes.

[0041] In order to ensure the timeliness and comprehensiveness of the scan, before starting the scan, the system will accurately calculate the scanning time window based on the effective length of the first area and the real-time speed of the cable, control the laser scanning device to complete the scanning of the entire first area during the cable passing, and dynamically track the scanning position as the cable moves. If an abnormality is found during the scanning process, the system will immediately reduce the running speed of the cable and extend the scanning time to obtain more complete abnormality information. After the scan is completed, the system will fuse and map the laser scattering intensity data with the cable position coordinates to generate an intuitive defect distribution map.

[0042] For example, for the cable section with abnormal weight, the system determined that it took about 5 seconds to pass through the first area, so it started the laser scan at 09:30:25 and completed the scan at 09:30:30, covering the entire 10-meter first area. During the scan, the system found that the cable section had obvious abnormal scattering from the 3rd to the 4th meter, so it reduced the cable speed from 50 meters / minute to 20 meters / minute, and focused on scanning the abnormal section, eventually forming a complete scattering distribution map, with several strong scattering points clearly visible on the map, indicating that there was a small amount of metal foreign matter there. Based on the scan results, the system can further decide the direction of the cable.

[0043] If the current weight is equal to the standard weight, step S106 is directly executed.

[0044] S104, determining whether there is a scattered light intensity greater than a preset light intensity in the scanning result; After obtaining the laser scattering distribution map, the system needs to determine whether there are abnormal scattering points, that is, points where the scattered light intensity is significantly higher than the surrounding area. This requires the system to pre-set a scattered light intensity value as a criterion based on the cable material type. Since different materials have different reflection and scattering characteristics of lasers, the distribution of scattered light intensity under normal conditions is also different, so the setting of the scattered light intensity threshold varies depending on the material. For example, for PUR materials with a rough surface, the scattering is more uniform, and the threshold can be set to 1.5 times the average scattered light intensity; while for PVC materials with a smooth surface, the scattering is weaker, and the threshold may need to be set to more than 2 times.

[0045] The system compares the scattered light intensity of each pixel on the scanned image with the preset light intensity, and any pixel that exceeds the preset light intensity will be marked as an abnormal point. If there are no abnormal points in the entire scanned image, it means that the cable surface is relatively uniform, and no obvious foreign matter or defects are found. The cable quality can be preliminarily judged to be qualified and can enter the next step of material testing. If an abnormal point is detected, it is necessary to further analyze the characteristic parameters such as the location, number and scattering intensity of the abnormal point to determine the nature and severity of the defect.

[0046] In the previous example, the system analyzed the scattering distribution map point by point and found that the scattered light intensity at 3.2 meters, 3.5 meters, and 3.8 meters reached 3 times, 2.5 times, and 3.2 times the average value, respectively, which is much higher than the abnormal threshold of PVC material by 2 times. Therefore, these three points are judged to be foreign objects. At the same time, because the foreign objects show circular scattering spots and the scattering intensity is prominent, the system preliminarily infers that the foreign objects may be highly reflective materials such as metal shavings or welding slag. Based on the distribution location and number of foreign objects, the system believes that the defects of this cable segment are relatively serious, which may affect the insulation performance and mechanical strength of the cable and need to be removed.

[0047] S105, transferring the drag chain cable to the first waste area; If it exists, the system controls the production line to transfer the drag chain cable to the first scrap area. When the system confirms that there are foreign objects or defects in the cable through laser scanning, it will immediately control the production line to automatically guide the problematic cable segment to the first scrap area. The first scrap area is located in the bypass of the production line, and there is a pneumatic switch valve between it and the main line. When the system issues a scrap rejection command, the valve opens, and the problematic cable enters the scrap area under the guidance of the guide device, and is physically isolated from the qualified cables. At the same time, the system will mark both ends of the scrap cable and record key information such as its production batch, time, and scrap reason for further quality analysis and problem tracing.

[0048] For the cable with metal foreign matter detected earlier, the system accurately calculated that the location of the foreign matter point was between 3.2 meters and 3.8 meters, a total of 0.6 meters. Subsequently, the system decided to introduce the 3-meter to 4-meter section of the cable into the scrap area, and put a red label on the 3-meter and 4-meter sections of the cable, with information such as "2023-5-10-9:30, Batch A, Weight exceeded, Metal foreign matter" printed on the label. This information can help quality personnel quickly find scrap cables, conduct anatomical analysis, find out the cause of foreign matter mixing, and formulate targeted preventive measures. Through precise elimination, it can not only avoid the outflow of unqualified products, but also minimize the waste of cable materials, which has positive significance for improving quality control and reducing production costs.

[0049] S106, after determining that the drag chain cable enters the second area, controlling the multi-spectral camera device to capture a spectral image; If it does not exist, the system controls the multi-spectral camera device to capture the spectral image after determining that the drag chain cable enters the second area. Specifically: if it does not exist, it determines whether the first time is over; If the first time has ended, executing the step of controlling the multi-spectral camera device to capture the spectral image; If the first time has not ended, the step of controlling the laser scanning device to scan the first area within the first time to obtain the scanning result is continued to scan the remaining area.

[0050] For cables that have passed both weight and appearance tests, the system will not directly determine them as high-quality products, but will conduct material composition tests in the second area to further confirm whether the cable material meets the requirements. The second testing area is adjacent to the first area and is also equipped with real-time video monitoring facilities to capture the flow of cables and accurately control the timing of testing.

[0051] Once the system determines through video analysis that the cable under test has completely entered the second area, it will immediately trigger the multispectral camera to image the cable surface. Multispectral imaging is an advanced optical detection technology that uses the interaction characteristics of light of different wavelengths with matter to obtain the spectral information of an object and analyze the composition and structure of the material based on it. The multispectral camera used in this system integrates sensors of multiple bands such as visible light, near infrared and short-wave infrared, and can capture hyperspectral images in the range of 400-2500nm. Through spectral analysis of the image, it can accurately identify the chemical composition of the cable insulation and sheath materials.

[0052] In the current case, the cable segment that had passed the weight and laser inspection entered the second zone at 09:30:35. The system immediately instructed the multi-spectral camera to shoot the cable segment and obtain a set of spectral image data. The image shows that the sheath of this cable segment exhibits typical PUR material spectral characteristics, with obvious absorption peaks near 1690nm and 2200nm, while the insulation layer exhibits the characteristic spectrum of PVC material, with a broad and strong absorption peak at 1720nm. This shows that the current sheath and insulation materials of the cable meet the design requirements, but further comparison with standard spectral data is needed to quantitatively evaluate the matching degree of the materials.

[0053] S107, judging whether the spectrum image is the same as the standard spectrum corresponding to the standard material; Although the image data obtained by spectral imaging is intuitive, it still needs to be compared with the standard spectrum to make an accurate judgment. In the early stage of production, the system collected the standard spectrum of the raw materials according to the product design requirements and stored it in the spectrum database. Whenever a new set of spectral images is obtained, the system will automatically call the corresponding standard spectrum data, compare it point by point, and calculate the spectral similarity.

[0054] Spectral similarity refers to the degree of overlap between two spectral curves, which can be quantified using indicators such as spectral angle or Euclidean distance. The smaller the angle or the closer the distance, the closer the two spectra are. Generally speaking, spectral data is affected by factors such as the composition, structure, and state of the material itself, and will have a certain degree of volatility. Therefore, if the similarity reaches more than 95%, it can be considered that the materials are basically the same. If the similarity is less than 95%, it means that the material may have composition deviations or quality problems, which require further review and processing.

[0055] For the spectral data of the above-mentioned cable, the system compared it with the standard spectra of PUR and PVC materials, and found that the spectral similarity of the sheath material was 97.2%, and the spectral similarity of the insulation material was 98.5%, both of which were within the qualified range. This shows that the material selection of the cable is correct and should be able to meet the design performance requirements of the product. However, the system also found that the spectral curve of the sheath material had a weak impurity peak at 2250nm, and it was initially speculated that it might be due to the influence of additives. Although it does not affect the overall judgment of the material, this abnormal information is also recorded by the system and can be used as a reference for process optimization.

[0056] S108, transferring the drag chain cable to the second waste area; If they are not the same, the drag chain cable will be transferred to the second scrap area. If the system finds that the spectral similarity of the material does not meet the standard during the spectral detection, it will determine that the cable material has quality risks and guide it to the second scrap area. The second scrap area is set downstream of the second detection area. Similar to the first scrap area, it is also controlled by a pneumatic valve. When the valve is opened, the cable segment with problematic materials leaves the main line under the action of the guide mechanism and enters the scrap area for temporary storage.

[0057] Compared with weight and appearance defects, material problems may bring more serious quality risks. Since the chemical properties of materials are difficult to detect through appearance inspection, once the wrong materials are used or the material ratio is unbalanced, it may cause a series of quality accidents such as insulation failure and sheath aging, and even bring safety risks to the end user. Therefore, the system is more stringent in material testing. As long as the spectral data is found to be unqualified, it will be directly judged as waste and clearly marked on the cable, and it is strictly prohibited to flow into the next process.

[0058] S109. Mark the drag chain cables as qualified products.

[0059] If they are the same, the drag chain cable will be marked as qualified. When the cable has undergone a series of tests such as weight, appearance and material, and no abnormal problems are found, the system will make a final judgment that the cable is qualified. In order to clearly indicate the qualified status of the cable, it is necessary to add corresponding marks on the surface of the cable. Unlike the unqualified mark which is printed manually, the qualified mark is usually marked by automated equipment to improve efficiency and consistency.

[0060] The above embodiments have the following beneficial effects: In the first stage, by judging whether the actual weight of the drag chain cable is consistent with the standard weight, cables with abnormal weight can be quickly screened out. For cables with abnormal weight, laser scanning equipment is used for scanning. By analyzing the distribution of scattered light intensity, the position of foreign matter can be accurately located, providing a basis for subsequent foreign matter cleaning and cause analysis. In the second stage, the cable materials are identified by multi-spectral imaging technology, and quality problems caused by material mixing or adulteration can be found, further ensuring the consistency of product quality. At the same time, by dynamically adjusting the production line speed and scanning time, while ensuring the detection accuracy, the impact of detection on production efficiency is minimized. In addition, the detection results are linked with subsequent processes such as waste transfer and qualified product marking to achieve seamless connection between foreign matter detection and quality control, improve the intelligence level of the production line, and improve the accuracy of foreign matter detection in the drag chain cable production line.

[0061] The introduction of visual monitoring technology improves the reliability and accuracy of weight detection. By monitoring the video in real time to determine whether the drag chain cable has completely entered the weighing area, it is possible to avoid measurement errors caused by weighing when the cable is partially in. At the same time, by confirming the cable position through visual technology, the weighing process can be automatically triggered without manual intervention, which improves the weighing efficiency. In addition, through visual monitoring, the movement status and production rhythm of the cable can be recorded in real time, providing data support for optimizing the production process. Combining weight detection with machine vision improves the accuracy of weight abnormality judgment.

[0062] While ensuring scanning accuracy, the impact of foreign body detection on production efficiency is minimized. When abnormal weight is detected, the production line speed is reduced and the cable stays in the scanning area for a longer time, thereby providing sufficient time for the laser scanning equipment to complete a comprehensive scan. At the same time, by accurately calculating the length of the scanning area and the speed of the production line, the scanning time can be optimized and controlled to avoid delays in production cycles caused by excessive scanning time. This method of dynamically adjusting scanning parameters according to actual conditions embodies the concept of equipment coordination and process optimization. While improving the foreign body detection rate, it minimizes the impact on production efficiency, thereby maximizing production benefits.

[0063] The associative annotation of the scattered light intensity distribution data and the scanned image can accurately correspond the scattered light abnormal points to the specific cable positions, providing visual guidance for the location and cleaning of foreign objects. By observing the scattered light intensity distribution pattern, the type and nature of foreign objects, such as metal particles, non-metallic impurities, etc., can be preliminarily judged, providing clues for subsequent defect analysis and process improvement. At the same time, combining the scattered light data with the scanned image to intuitively present the abnormal area also facilitates production management personnel to quickly understand and make decisions, improving communication efficiency and management level. In addition, by accumulating and analyzing historical detection data, the laws and causes of foreign matter can be summarized, providing data support for optimizing production processes and improving quality management systems.

[0064] When the weight detection is normal, but the laser scanning finds that there is an abnormal scattered light in a local area, the system will determine whether the remaining scanning time is sufficient. If there is enough time, the unscanned area will continue to be inspected until it is fully covered to ensure the integrity of foreign body detection; if there is insufficient time, material testing will be given priority to maximize the use of existing test results while ensuring the normal production process. This practice of dynamically adjusting the detection plan according to actual conditions embodies the concept of flexible production. By flexibly coordinating multiple links such as weight detection, laser scanning, and spectral analysis, while strictly controlling product quality, it also minimizes the impact of detection on production efficiency and achieves a dynamic balance between quality and output. In addition, multi-area scanning can make up for the limitations of a single detection method and improve the accuracy and reliability of foreign body detection through comprehensive analysis of multi-dimensional data.

[0065] Further, if the current weight is equal to the standard weight, after executing the step of controlling the multi-spectral camera device to capture the spectral image after determining that the drag chain cable enters the second area, the method further includes: Counting the number of first scraps and the number of second scraps containing drag chain cables in the first scrap area and the second scrap area respectively; When it is determined that the sum of the first waste quantity and the second waste quantity is greater than a preset threshold, the production line is controlled to stop running, and an early warning message is generated and sent to the control terminal; Determine a key area corresponding to the largest number of the first waste quantity and the second waste quantity; Send the production line sections corresponding to the key areas to the control terminal.

[0066] In the above embodiment, the number of scraps caused by weight abnormalities and material abnormalities is counted separately, which can quantitatively evaluate the quality problems of the production line in different processes and provide a basis for targeted improvements. At the same time, a scrap quantity threshold is set. When the scrap rate exceeds the preset level, the production line is automatically stopped to prevent the quality problem from further expanding and reduce unnecessary losses. After the line is stopped, the system will also automatically generate early warning information to notify relevant personnel to deal with it in time, thereby improving the timeliness of abnormal response. In addition, by analyzing the proportion of scrap quantity, the key problem areas of the production line can be determined, which helps managers quickly locate the root cause of the problem and optimize resource allocation. Associating quality problems with specific production line sections provides a feasible solution for carrying out quality control, process optimization, equipment maintenance, etc. at the section level, and promotes the improvement of the overall operation level of the production line.

[0067] In addition, in the step of judging whether the spectral image is the same as the standard spectrum corresponding to the standard material, the received spectral image needs to be processed to ensure the reliability of the data. Figure 2 , another method for detecting foreign matter in a drag chain cable production line in an embodiment of the present application is described: See also Figure 2 , is another flow chart of a method for detecting foreign matter in a drag chain cable production line in an embodiment of the present application.

[0068] S201, performing denoising processing on the spectral image to obtain a denoised spectral image; After acquiring the spectral image of the cable material, the system needs to perform a series of preprocessing on the image to improve the data quality. De-noising is a key step, which can effectively eliminate random noise and background interference in the image, laying the foundation for subsequent feature extraction. The noise of the spectral image mainly comes from the dark current of the imaging device itself, the thermal noise of the readout circuit, and the interference of ambient light, which will produce randomly distributed bright and dark spots on the image, causing fluctuations in the spectral data. To remove these noises, the system uses a median filtering algorithm to scan the image point by point, and replace the original pixel value in the center of the window with the median of the pixel value in the filter window, thereby smoothing the sharp fluctuations caused by noise.

[0069] For example, for the spectral image of a certain cable section near the wavelength of 1800nm, the original data shows obvious jaggedness, and two peak noise points appear at 1810nm and 1815nm, with pixel values ​​reaching 90 and 100 respectively, which are obviously deviated from the normal range. The system uses a 5×5 filter window to perform median filtering on the area. When scanning a noise point, it extracts the 25 pixel values ​​centered on it, sorts them, and takes the middle value 62 to replace the original value, and finally obtains a smooth spectral curve. The pixel value of the noise point is adjusted to about 65, which is close to the surrounding data points. Through reasonable denoising processing, the signal-to-noise ratio of the spectral image is greatly improved, which is conducive to the subsequent accurate extraction of spectral features and reliable determination of material properties.

[0070] S202, extracting the features of the denoised spectral image to obtain a spectral curve; The system extracts the features of the denoised spectral image and obtains the spectral curve, which represents the material properties of the drag chain cable. After completing the image denoising, the system needs to extract the spectral features that can reflect the material properties from the image to form a standard spectral curve to provide a basis for material identification. Due to differences in their chemical structure and elemental composition, different materials have different absorption, reflection, and transmission characteristics for light of different wavelengths, which is reflected in the difference in the shape of the spectral curve. Therefore, by analyzing the characteristics of the spectral curve, such as the position, intensity, and shape of the absorption peak, the type and quality of the material can be determined. In order to extract spectral features, the system adopts a filtering analysis method based on Fourier transform. By performing spectral decomposition on the denoised image, the characteristic frequency components that can represent the material properties are found and reconstructed, and finally a smooth and accurate spectral characteristic curve is generated.

[0071] Taking PVC material as an example, it has multiple characteristic absorption peaks in the 900-1700nm band, which are related to the stretching vibrations of groups such as CH and C-Cl. The system performs Fourier analysis on the denoised spectral image of PVC material and finds that the energy is most concentrated in the frequency range of 0.2-0.3, corresponding to the main components of the spectral characteristics. Therefore, the system extracts the components within this frequency range and performs an inverse Fourier transform to remove the interference of high-frequency noise and baseline drift, and obtains a clear PVC spectral characteristic curve. The curve has two obvious absorption peaks near 1200nm and 1450nm, corresponding to the frequency-doubled stretching vibration and combined stretching vibration of the CH bond in the PVC material, which are consistent with the molecular structure characteristics of PVC. Using spectral feature extraction technology, the system can accurately separate the spectral curve that reflects the essential properties of the material from the complex spectral image, providing reliable data support for the accurate determination of material quality.

[0072] S203, comparing the spectrum curve with a standard spectrum curve corresponding to the standard spectrum, and determining whether the spectrum image is the same as the standard spectrum corresponding to the standard material.

[0073] Although the material spectrum curve obtained by spectral feature extraction removes most of the noise interference, it still retains the difference information of material quality and status. The final judgment of material conformity can only be made by comparing with the standard spectrum. The system collects standard spectra of various raw materials at the beginning of production to form a complete spectral fingerprint library as a benchmark for material quality judgment. After the spectrum detection of a batch of cables is completed, the system automatically calls the standard spectrum data of the corresponding material, compares it with the measured spectrum using the spectral similarity algorithm, and calculates the matching degree of the two curves. If the matching degree exceeds the set threshold, it is judged that the spectral characteristics of the batch of materials are consistent with those of the standard materials, the material selection is correct, and the quality is qualified.

[0074] The above embodiments have the following beneficial effects: The material detection method based on multi-spectral imaging can realize the rapid identification of the material quality of the drag chain cable by extracting and comparing the spectral curve, and effectively ensure the consistency of product quality. The multi-spectral camera equipment can realize the real-time non-destructive detection of material composition on the production line, which greatly improves the efficiency and response speed of detection. By denoising the collected spectral images, the environmental interference and equipment noise can be effectively eliminated, and the signal-to-noise ratio and reliability of the spectral data can be improved. On this basis, the feature extraction algorithm can be used to accurately separate the spectral curve reflecting the material properties from the spectral image, and the matching degree can be compared with the standard spectrum to quickly determine whether the material meets the quality standards and realize the automatic screening of defective products. By quantifying the degree of spectral deviation, the grade division of material quality can also be realized, providing data support for optimizing material procurement and supplier management. In addition, the accumulation of spectral detection data also provides an important basis for process parameter optimization, product consistency control, etc.

[0075] The following describes the system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the physical device structure of a foreign body detection system for a drag chain cable production line provided in an embodiment of the present application.

[0076] It should be noted that Figure 3 The structure of the system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0077] like Figure 3 As shown, the system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (Raccess Memory, Raccess Memory) 303, such as executing the method in the above embodiment. In the Raccess Memory 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and Raccess Memory 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0078] The following components are connected to the I / O interface 305: an input section 306 including a camera, an infrared sensor, etc.; an output section 307 including a liquid crystal display (LCD) and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a Local Area Network (LAN) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0079] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0080] It should be noted that the computer-readable medium shown in the embodiment of the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (R), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact DiscRe-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.

[0081] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0082] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the system described in the above embodiment; or may exist independently without being assembled into the system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of a system, the system implements the method provided in the above embodiment.

[0083] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0084] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0085] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0086] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be realized by a computer program to instruct the relevant hardware to complete the process, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. The aforementioned storage medium includes: ROM or random access memory R, ​​magnetic disk or optical disk and other media that can store program codes.

Claims

1. A method for detecting foreign matter in a drag chain cable production line, characterized in that: include: Determine production parameters according to the drag chain cable parameters in the current production line, wherein the production parameters include standard materials and standard weights; Determining whether the current weight of the drag chain cable in the first area is equal to the standard weight; If the current weight is not equal to the standard weight, controlling the laser scanning device to scan the first area within a first time to obtain a scanning result, wherein the first time is the time required for the drag chain cable to pass through the first area; Determine whether there is a scattered light intensity greater than a preset light intensity in the scanning result; If so, the drag chain cable is transferred to a first waste area; If not, after determining that the drag chain cable enters the second area, controlling the multi-spectral camera device to capture a spectral image; Determining whether the spectrum image is the same as a standard spectrum corresponding to the standard material; If they are not the same, the drag chain cable is transferred to a second waste area; If they are the same, the drag chain cable is marked as a qualified product; If the current weight is equal to the standard weight, the step of controlling the multi-spectral camera device to capture a spectral image after determining that the drag chain cable enters the second area is performed.

2. The method according to claim 1, characterized in that The determining whether the current weight of the drag chain cable in the first area is equal to the standard weight specifically includes: Receiving real-time surveillance video captured by surveillance equipment in the first area; After determining that the drag chain cable has completely entered the first area according to the real-time monitoring video, receiving the current weight sent by the weight detection device; Determine whether the current weight is equal to the standard weight.

3. The method according to claim 1, characterized in that If the current weight is not equal to the standard weight, controlling the laser scanning device to scan the first area within the first time to obtain a scanning result specifically includes: If the current weight is not equal to the standard weight, reducing the running speed of the production line to a first running speed, wherein the first running speed is less than an initial running speed of the production line; determining a running length of the first region; Calculate the first time according to the running length and the first running speed; The laser scanning device is controlled to scan the first area within the first time to obtain the scanning result.

4. The method according to claim 3, characterized in that The controlling the laser scanning device to scan the first area within the first time to obtain the scanning result specifically includes: Controlling the laser scanning device to scan the first area within the first time to obtain scattered light intensity distribution data; Determining a scanned image containing the drag chain cable; The scattered light intensity distribution data is marked at a corresponding position of the scanned image to obtain the scan result.

5. The method according to claim 1, characterized in that After the step of controlling the multi-spectral camera device to capture a spectral image after determining that the drag chain cable enters the second area if the current weight is equal to the standard weight, the method further includes: Counting the number of first scraps and the number of second scraps containing drag chain cables in the first scrap area and the second scrap area respectively; When it is determined that the sum of the first number of scraps and the second number of scraps is greater than a preset threshold, the production line is controlled to stop running, and an early warning message is generated and sent to a control terminal; Determine a key area corresponding to the largest number of the first waste quantity and the second waste quantity; The production line section corresponding to the key area is sent to the control terminal.

6. The method according to claim 1, characterized in that If it does not exist, after determining that the drag chain cable enters the second area, controlling the multi-spectral camera device to capture a spectral image specifically includes: If not, determining whether the first time has ended; If the first time has ended, executing the step of controlling the multi-spectral camera device to capture a spectral image; If the first time has not ended, the step of controlling the laser scanning device to scan the first area within the first time to obtain a scanning result is continued to scan the remaining area.

7. The method according to claim 1, characterized in that The determining whether the spectrum image is the same as the standard spectrum corresponding to the standard material specifically includes: Performing denoising processing on the spectral image to obtain a denoised spectral image; Extracting features of the denoised spectral image to obtain a spectral curve, wherein the spectral curve represents material properties of the drag chain cable; The spectrum curve is compared with a standard spectrum curve corresponding to the standard spectrum to determine whether the spectrum image is the same as the standard spectrum corresponding to the standard material.

8. A foreign body detection system for a drag chain cable production line, characterized in that: The system comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the system to execute the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a system, the system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a system, the system is caused to execute the method according to any one of claims 1 to 7.

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