A detection method and system for isolated mineral insulated flexible cable

Abstract

The present invention relates to the field of intelligent detection technology, and discloses an isolated mineral insulated flexible cable detection method and system, the method comprising: fixing a sample to be detected on a rotatable platform, arranging a linear laser transmitter; collecting size information of the sample to be detected to determine the rotation speed of the rotatable platform, turning on the linear laser transmitter to run the rotatable platform, and collecting image data of at least two samples to be detected under the irradiation of the linear laser transmitter to obtain the appearance evaluation value of the sample to be detected; using an infrared parallel light source to horizontally irradiate the sample to be detected, obtaining an infrared image of the sample to be detected, judging whether there is a mineral filling defect inside the sample to be detected, and obtaining the internal evaluation value of the sample to be detected; determining the comprehensive evaluation value of the sample to be detected based on the appearance evaluation value and the internal evaluation value to determine the quality grade of the sample to be detected. The present application realizes the synchronous detection of internal and external defects of the cable, reduces human errors, and improves the degree of automation of detection.

Description

Technical Field

[0001] The present invention relates to the field of intelligent detection technology, and in particular to an isolated mineral insulated flexible cable detection method and system. Background Art

[0002] Isolated mineral insulated flexible cables are widely used in key projects and high-demand occasions due to their excellent fire resistance, high temperature resistance and insulation. However, during the manufacturing process of the cable, especially in the extrusion step of the mineral filling, problems such as uneven filling and unreasonable distribution of mineral particles may occur, which directly affect the overall performance and service life of the cable. Therefore, ensuring the uniformity of mineral filling and the surface quality of the cable is crucial to improving the production quality of the cable.

[0003] Traditional cable testing methods usually rely only on electrical performance testing or basic appearance inspections, which makes it difficult to fully evaluate the internal filling quality and surface defects of cables. Moreover, testing the electrical performance of cables cannot effectively evaluate the emergency response capabilities of cables, and cannot fully test the fire resistance of isolated mineral insulated flexible cables. In addition, appearance testing is more dependent on the experience level of the testers, and the test results of different testers vary greatly, resulting in poor reliability of the test results and the inability to avoid detection errors caused by human factors.

[0004] Therefore, it is necessary to design an isolated mineral insulated flexible cable detection method and system to solve the problems existing in the current technology. Summary of the invention

[0005] In view of this, the present invention proposes an isolated mineral insulated flexible cable detection method and system, aiming to solve the problems of low detection accuracy, poor reliability of detection results and time-consuming and labor-intensive detection in the current isolated mineral insulated flexible cable detection technology.

[0006] In one aspect, the present invention provides an isolated mineral insulated flexible cable detection method, comprising:

[0007] A sample to be tested is cut from the cable to be tested, the sample to be tested is fixed on a rotatable platform, a linear laser emitter is fixed above the sample to be tested, the linear laser emitter is tilted to irradiate the sample to be tested, and the linear laser is parallel to the axis of the sample to be tested;

[0008] Collecting size information of the sample to be detected, determining the rotation speed of the rotatable platform according to the size information, turning on the linear laser emitter to operate the rotatable platform at the determined rotation speed, and collecting image data of at least two samples to be detected under the irradiation of the linear laser emitter based on a CCD camera, and obtaining an appearance evaluation value of the sample to be detected according to the image data;

[0009] The sample to be tested is horizontally illuminated by an infrared parallel light source, and an infrared image is collected based on an infrared camera. The infrared parallel light source and the infrared camera move horizontally synchronously to obtain an infrared image of the sample to be tested, and the infrared image is analyzed to determine whether there are mineral filling defects inside the sample to be tested, and an internal evaluation value of the sample to be tested is obtained according to the infrared image;

[0010] A comprehensive evaluation value of the sample to be detected is determined according to the appearance evaluation value and the internal evaluation value, and a quality grade of the sample to be detected is determined according to the comprehensive evaluation value.

[0011] Further, the determining of the rotation speed of the rotatable platform according to the size information includes:

[0012]

[0013] Wherein, v represents the rotation speed, T represents the time taken by the rotating platform to rotate idly for one circle, L represents the length of the sample to be tested, M represents the mass of the sample to be tested, Cf represents the accuracy coefficient of the CCD camera, η represents the mechanical efficiency of the rotating platform, E represents the elastic modulus of the sample to be tested, and τ represents the yield strength of the sample to be tested.

[0014] Furthermore, when obtaining the appearance evaluation value of the sample to be detected according to the image data, it includes:

[0015] Determine the surface defects of the sample to be inspected according to the line laser image in the image data;

[0016] When the line laser image is a continuous straight line, it is determined that there is no defect on the surface of the sample to be inspected;

[0017] When there are breakpoints in the line laser image, the straight line with the largest proportion in the same straight line in the line laser image is used as the reference line, and the number and size of defects on the surface of the sample to be detected are determined according to the reference line and the position of the breakpoints;

[0018] The appearance evaluation value of the sample to be inspected is determined according to the defect quantity and defect size.

[0019] Further, when the appearance evaluation value of the sample to be tested is determined according to the defect quantity and defect size, the appearance evaluation value is calculated by the following formula:

[0020]

[0021] Wherein, N represents the number of defects, qi represents the defect length, L represents the length of the sample to be tested, wi represents the weight coefficient of the defect position, γ represents the distribution influence coefficient, and S represents the appearance evaluation value.

[0022] Furthermore, when analyzing the infrared image to determine whether there is a mineral filling defect inside the sample to be tested, it includes:

[0023] Segmenting the infrared image to obtain a2 sub-images, obtaining mineral density data according to each sub-image and establishing a mineral density matrix;

[0024] A point is randomly selected in the mineral density matrix as a center point;

[0025] The verification range is determined with the central point as the center and r as the radius;

[0026] Obtaining a mineral density verification value according to the mineral density data within the verification range;

[0027] Compare the mineral density data corresponding to the center point with the mineral density verification value, and determine whether there is a mineral filling defect inside the sample to be tested according to the comparison result;

[0028] When the mineral density data corresponding to the center point is greater than 1.2 times the mineral density verification value, or the mineral density data corresponding to the center point is less than 0.8 times the mineral density verification value, it is determined that there is a mineral filling defect inside the sample to be tested.

[0029] Furthermore, the mineral density verification value is calculated by the following formula:

[0030]

[0031] Among them, K y represents the verification value of mineral density, r represents the radius of the verification range, (x 0 ,y 0 ) represents the coordinates of the center point, and K(m, n) represents the mineral density data of point (m, n) in the mineral density matrix.

[0032] Further, when it is determined that there are mineral filling defects inside the sample to be tested, and the internal evaluation value of the sample to be tested is obtained according to the infrared image, the internal evaluation value is calculated by the following formula:

[0033]

[0034] Wherein, W represents the internal evaluation value, M represents the total number of mineral filling defects, Kj represents the mineral density data corresponding to the center point of the j-th defect, Ky represents the mineral density verification value, ej represents the weight coefficient of the j-th defect, Rj represents the distance from the center point of the j-th defect to the center axis of the cable, Rmax represents the maximum distance between the outer diameter of the cable and the center axis of the cable, and β represents the position influence coefficient.

[0035] Further, when determining the comprehensive evaluation value of the sample to be tested according to the appearance evaluation value and the internal evaluation value, it includes:

[0036] The comprehensive evaluation value is obtained by weighted summing the appearance evaluation value and the internal evaluation value, and the weight coefficient of the appearance evaluation value and the weight coefficient of the internal evaluation value add up to 1.

[0037] Further, when determining the quality level of the sample to be detected according to the comprehensive evaluation value, it includes:

[0038] The comprehensive evaluation value is compared with a first preset comprehensive evaluation value and a second preset comprehensive evaluation value respectively, and the quality level of the sample to be tested is determined according to the comparison result, and the first preset comprehensive evaluation value is less than the second preset comprehensive evaluation value;

[0039] When the comprehensive evaluation value is less than or equal to a first preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the third level; when the comprehensive evaluation value is greater than the first preset comprehensive evaluation value and less than or equal to the second preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the second level; when the comprehensive evaluation value is greater than the second preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the first level, the first level is greater than the second level, and the second level is greater than the third level.

[0040] Compared with the prior art, the beneficial effect of the present invention is that the synchronous detection of internal and external defects of isolated mineral insulated flexible cables is realized through the comprehensive detection means of linear laser and infrared light. The surface defect information and appearance evaluation value are obtained by using linear laser oblique irradiation and collecting sample surface image data based on CCD camera. The linear laser enhances the defect recognition ability of CCD camera and reduces the influence of environmental shadow on the detection results. Through the combination of infrared parallel light source and infrared camera, the uniformity and density of the mineral filling inside the cable can be detected, the internal defects can be identified, and the internal evaluation value can be generated. By comprehensively analyzing the appearance evaluation value and the internal evaluation value, the overall quality of the cable can be effectively determined. By rotating the platform and multi-light source synchronous detection, the human detection error is effectively reduced, and the objectivity and consistency of the evaluation results are ensured. The automation degree of the detection process is improved.

[0041] On the other hand, the present application also provides an isolated mineral insulated flexible cable detection system, which is used to apply the above-mentioned isolated mineral insulated flexible cable detection method, including:

[0042] A rotatable platform, a linear laser transmitter, an infrared parallel light source, an infrared camera and a control module, wherein:

[0043] The rotatable platform is used to fix the sample to be detected, the linear laser emitter is used to emit a linear laser to the surface of the sample to be detected, the infrared parallel light source is used to emit infrared light to the sample to be detected, and the infrared camera is used to collect infrared images; the control module is connected to the rotatable platform, the linear laser emitter, the infrared parallel light source and the infrared camera, and the control module includes:

[0044] A collection unit is configured to collect size information of the sample to be tested, determine the rotation speed of the rotatable platform according to the size information, turn on the linear laser emitter, operate the rotatable platform at the determined rotation speed, and collect image data of at least two samples to be tested under the irradiation of the linear laser emitter based on a CCD camera, and obtain an appearance evaluation value of the sample to be tested according to the image data;

[0045] A processing unit is configured to horizontally illuminate the sample to be detected with an infrared parallel light source, and collect infrared images based on an infrared camera, wherein the infrared parallel light source and the infrared camera move horizontally synchronously to obtain an infrared image of the sample to be detected, analyze the infrared image to determine whether there are mineral filling defects inside the sample to be detected, and obtain an internal evaluation value of the sample to be detected based on the infrared image;

[0046] The evaluation unit is configured to determine a comprehensive evaluation value of the sample to be detected according to the appearance evaluation value and the internal evaluation value, and determine a quality grade of the sample to be detected according to the comprehensive evaluation value.

[0047] It is understandable that the above-mentioned isolated mineral insulated flexible cable detection method and system have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0049] Figure 1 A flow chart of a detection method for an isolated mineral insulated flexible cable provided in an embodiment of the present invention;

[0050] Figure 2 This is a structural block diagram of an isolated mineral insulated flexible cable detection system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0052] In modern engineering and high-demand applications, isolated mineral insulated flexible cables have become the first choice in critical power systems due to their excellent fire resistance, high temperature resistance and excellent insulation performance. Its core technology is to use inorganic metal hydrates, such as Al(OH) 3 Mg(OH) 2 , to replace the traditional polypropylene (PP) tear film rope or glass fiber filling. Under the high temperature of flame, Al(OH) 3 Dissolved into Al 2 O 3 and H 2 O, water can cool down, steam can discharge oxygen, and the remaining Al 2 O 3 It is tightly wrapped around the cross-linked insulation core, becoming a barrier to block the attack of hot oxygen, so that the oxygen-insulating cable has higher flame retardancy and fire resistance. In the cable production process, especially in the extrusion step of mineral filling, due to the complexity of the process and the characteristics of the material, problems such as uneven mineral filling and unreasonable particle distribution may occur. These problems will not only affect the physical structure of the cable, but may also lead to a decline in cable performance, shorten its service life, and even cause serious safety hazards under extreme conditions. Therefore, how to ensure the uniformity of mineral filling and optimize the surface quality of the cable has become a key issue in improving the quality of cable production.

[0053] Traditional cable inspection methods mainly rely on electrical performance tests and basic appearance inspections. Although these methods can reflect the external state and electrical performance of the cable to a certain extent, they have significant deficiencies in evaluating the internal filling quality and surface defects of the cable. For example, electrical performance tests cannot effectively judge the internal structural defects of the cable, especially in the case of uneven mineral filling, and these test results often do not have sufficient accuracy. In addition, traditional appearance inspections rely heavily on the experience of the inspectors, and the test results are easily affected by human factors, resulting in poor consistency and reliability. These deficiencies significantly limit the comprehensive quality control of isolated mineral insulated flexible cables, especially in ensuring their emergency response capabilities and fire resistance.

[0054] Therefore, it is necessary to design an isolated mineral insulated flexible cable detection method and system to solve the problems existing in the current technology.

[0055] In some embodiments of the present application, see Figure 1 As shown, a detection method for an isolated mineral insulated flexible cable comprises:

[0056] S100: Cut a sample to be tested from the cable to be tested, fix the sample to be tested on a rotatable platform, fix a linear laser emitter above the sample to be tested, and the linear laser emitter is tilted to illuminate the sample to be tested, and the linear laser is parallel to the axis of the sample to be tested.

[0057] S200: Collect size information of the sample to be tested, determine the rotation speed of the rotatable platform according to the size information, turn on the linear laser emitter, run the rotatable platform at the determined rotation speed, and collect image data of at least two samples to be tested under the irradiation of the linear laser emitter based on the CCD camera, and obtain the appearance evaluation value of the sample to be tested according to the image data.

[0058] S300: Use an infrared parallel light source to horizontally illuminate the sample to be tested, and collect infrared images based on an infrared camera. The infrared parallel light source and the infrared camera move horizontally synchronously to obtain an infrared image of the sample to be tested, analyze the infrared image to determine whether there are mineral filling defects inside the sample to be tested, and obtain the internal evaluation value of the sample to be tested based on the infrared image.

[0059] S400: Determine a comprehensive evaluation value of the sample to be tested according to the appearance evaluation value and the internal evaluation value, and determine the quality level of the sample to be tested according to the comprehensive evaluation value.

[0060] Specifically, in the present application, the structure of the cable to be tested is mineral tape, mineral filling, mineral insulation and twisted conductor from outside to inside. In practical application, the outside of the cable to be tested also includes a copper sheath isolation layer and a flame retardant sheath layer.

[0061] Specifically, in S100, a sample to be tested is cut from the isolated mineral insulated flexible cable to be tested, and the sample is fixed on a rotatable platform. A linear laser emitter is fixed above the sample so that it is tilted to irradiate the sample, and the laser beam is parallel to the axis of the sample. Through the tilted linear laser irradiation, a laser line can be formed on the surface of the sample, and the shape and continuity of this laser line reflect the geometric morphology and smoothness of the sample surface. In this way, the detection equipment can scan the sample surface with high precision and capture its tiny surface defects. In S200, the size information of the sample to be tested is collected to determine the optimal rotation speed of the rotating platform. Then, the linear laser emitter is turned on, and the rotating platform is rotated at a predetermined speed, and the CCD camera collects image data of the sample under laser irradiation. By processing and analyzing the image data at multiple angles, the appearance evaluation value of the sample is obtained. The speed of the rotating platform is accurately calculated based on the sample size information to ensure that the sample can be scanned evenly when the image is collected. By capturing the image formed by the laser line on the sample surface by the CCD camera, it can be determined whether there are defects on the sample surface, such as protrusions, depressions, etc. Combining these image data, an appearance evaluation value is calculated to quantitatively evaluate the surface quality of the sample. In S300, an infrared parallel light source is used to horizontally illuminate the sample to be tested, and an infrared camera is used to synchronously move and collect infrared images of the sample. By analyzing these infrared images, it is determined whether there are mineral filling defects inside the sample, and the internal evaluation value of the sample is calculated based on the analysis results. Infrared light can penetrate the outer layer of the sample and reflect the internal structure. Through infrared image analysis, areas with uneven mineral filling or unreasonable particle distribution can be detected. This information is used to evaluate the internal quality of the sample, generate an internal evaluation value, and quantify the severity of internal defects. In S400, the appearance evaluation value obtained in the previous step is combined with the internal evaluation value to calculate a comprehensive evaluation value. Finally, based on the comprehensive evaluation value, the overall quality level of the sample to be tested is determined. The appearance evaluation value and the internal evaluation value represent the surface quality and internal filling quality of the sample respectively, and the combination of the two forms a more comprehensive quality evaluation index. The comprehensive evaluation value can more accurately reflect the overall performance of the sample and ensure the accuracy and reliability of quality assessment.

[0062] It is understandable that by combining linear laser and infrared light detection methods, a comprehensive assessment of the internal and external quality of isolated mineral insulated flexible cables is achieved. Compared with the traditional method of relying only on appearance or electrical performance detection, it effectively identifies the problem of uneven mineral filling during the cable production process and avoids potential quality risks. At the same time, it has the advantage of automated detection, reduces the influence of human factors, and improves the reliability and consistency of the test results.

[0063] In some embodiments of the present application, when determining the rotation speed of the rotatable platform according to the size information, it includes:

[0064]

[0065] Wherein, v represents the rotation speed, T represents the time taken by the rotating platform to rotate idly for one circle, L represents the length of the sample to be tested, M represents the mass of the sample to be tested, Cf represents the accuracy coefficient of the CCD camera, η represents the mechanical efficiency of the rotating platform, E represents the elastic modulus of the sample to be tested, and τ represents the yield strength of the sample to be tested.

[0066] Specifically, the precision coefficient of the CCD camera represents the detection accuracy of the CCD camera, which affects the quality of image acquisition and the adjustment of the rotation speed. According to the camera resolution and detection requirements, it is preferably between 0.8 and 1.2. The mechanical efficiency of the rotating platform reflects the mechanical efficiency of the rotating platform, which refers to the degree of loss during energy transmission. It is preferably between 0.85 and 0.95. The elastic modulus of the sample to be tested represents the rigidity of the material of the sample to be tested, reflecting the degree of deformation of the material when subjected to force. The yield strength of the sample to be tested represents the yield strength of the material of the sample to be tested, that is, the maximum stress that the material can withstand before plastic deformation occurs.

[0067] It is understandable that when determining the rotation speed of the rotatable platform based on the size information, a variety of influencing factors are taken into consideration, including the physical properties of the sample (such as mass, length, elastic modulus, yield strength), the mechanical properties of the rotating platform, and the accuracy requirements of the CCD camera. The rotation speed is precisely controlled by these parameters, thereby improving the accuracy and efficiency of image acquisition, ensuring that the sample remains stable during rotation, and avoiding image distortion or mechanical damage caused by improper speed. In addition, by considering the elastic modulus and yield strength, it can also better adapt to the samples to be tested with different material properties, and improve the adaptability and reliability of the overall detection method.

[0068] In some embodiments of the present application, obtaining the appearance evaluation value of the sample to be inspected according to the image data includes: determining the surface defects of the sample to be inspected according to the line laser image in the image data.

[0069] Specifically, when the line laser image is a continuous straight line, it is determined that there are no defects on the surface of the sample to be tested. When there are breakpoints in the line laser image, the straight line with the largest proportion of the same straight line in the line laser image is used as the reference line, and the number and size of defects on the surface of the sample to be tested are determined based on the reference line and the breakpoint positions. The appearance evaluation value of the sample to be tested is determined based on the number and size of defects.

[0070] In some embodiments of the present application, when determining the appearance evaluation value of the sample to be inspected according to the number of defects and the defect size, the appearance evaluation value is calculated by the following formula:

[0071]

[0072] Wherein, N represents the number of defects, qi represents the defect length, L represents the length of the sample to be tested, wi represents the weight coefficient of the defect position, γ represents the distribution influence coefficient, and S represents the appearance evaluation value.

[0073] Specifically, the weight coefficient of the defect position indicates the importance of the defect position on the sample surface. Defects at different positions may have different effects on the overall appearance. Defects in key areas may have a greater impact, and the weight coefficient will increase accordingly. The preferred value range is 0.8 to 1.2, for example, the weight coefficient of defects in the central area is 1.2, and the weight coefficient of defects in the edge area is 0.8. The distribution influence coefficient indicates the influence of the distribution of defects on the sample surface on the appearance evaluation value. The distribution influence coefficient of concentrated distribution is preferably 1.5, and the distribution influence coefficient of dispersed distribution is preferably 0.5.

[0074] It is understandable that by introducing the weight coefficients and distribution influence coefficients of multiple defect positions, the accuracy and precision of appearance evaluation are improved. The number and size of defects are taken into account, the location and distribution of defects on the sample surface are analyzed, and a more comprehensive appearance quality evaluation is provided. The reliability of the test results is improved, and the subjective error of relying solely on experience is reduced.

[0075] In some embodiments of the present application, when analyzing the infrared image to determine whether there is a mineral filling defect inside the sample to be tested, it includes:

[0076] The infrared image is segmented to obtain a2 sub-images, and mineral density data is obtained based on each sub-image and a mineral density matrix is ​​established.

[0077] A point is randomly selected in the mineral density matrix as the center point.

[0078] The verification range is determined with the center point as the center of the circle and r as the radius.

[0079] Based on the mineral density data within the verification range, the mineral density verification value is obtained.

[0080] The mineral density data corresponding to the center point is compared with the mineral density verification value, and the comparison result is used to determine whether there are mineral filling defects inside the sample to be tested.

[0081] When the mineral density data corresponding to the center point is greater than 1.2 times the mineral density verification value, or the mineral density data corresponding to the center point is less than 0.8 times the mineral density verification value, it is determined that there is a mineral filling defect inside the sample to be tested.

[0082] In some embodiments of the present application, the mineral density verification value is calculated by the following formula:

[0083]

[0084] Among them, K y represents the verification value of mineral density, r represents the radius of the verification range, (x 0 ,y 0 ) represents the coordinates of the center point, and K(m, n) represents the mineral density data of point (m, n) in the mineral density matrix.

[0085] Specifically, the mineral density verification value calculation formula determines the normal mineral density level of the area through the average mineral density data of the sampling area, so as to judge whether there is an abnormality at a specific point. For example, when the mineral density of the center point is larger, it means that the minerals at the center point are concentrated, and when the mineral density of the center point is smaller, it means that the mineral gaps at the center are larger and there are pores.

[0086] In some embodiments of the present application, when it is determined that there are mineral filling defects inside the sample to be tested, and the internal evaluation value of the sample to be tested is obtained according to the infrared image, the internal evaluation value is calculated by the following formula:

[0087]

[0088] Wherein, W represents the internal evaluation value, M represents the total number of mineral filling defects, Kj represents the mineral density data corresponding to the center point of the j-th defect, Ky represents the mineral density verification value, ej represents the weight coefficient of the j-th defect, Rj represents the distance from the center point of the j-th defect to the center axis of the cable, Rmax represents the maximum distance between the outer diameter of the cable and the center axis of the cable, and β represents the position influence coefficient.

[0089] In some embodiments of the present application, when determining the comprehensive evaluation value of the sample to be tested based on the appearance evaluation value and the internal evaluation value, it includes: obtaining the comprehensive evaluation value by weighted summation of the appearance evaluation value and the internal evaluation value, and the weight coefficient of the appearance evaluation value and the weight coefficient of the internal evaluation value add up to 1.

[0090] Specifically, ej represents the weight of the defect's impact on the overall assessment value. For example, when there are large gaps in the minerals inside the cable, the weight is 1.2, and when the density distribution inside the minerals is large, the weight is 0.8. The position influence coefficient is related to the distance of the defect from the center of the cable, and the preferred value is 0.5-1.

[0091] It can be understood that by combining infrared image data with precise mineral density analysis, a highly accurate and detailed evaluation method is provided for the detection of internal filling defects in cables. By calculating the mineral density verification value and the comprehensive evaluation value, the presence or absence of internal filling defects can be accurately identified, and their severity can also be quantified. This overcomes the limitations of traditional detection methods, reduces the influence of human factors, and improves the reliability and objectivity of the detection results.

[0092] In some embodiments of the present application, when determining the quality level of the sample to be tested based on the comprehensive evaluation value, it includes: comparing the comprehensive evaluation value with a pre-set first preset comprehensive evaluation value and a second preset comprehensive evaluation value, respectively, and determining the quality level of the sample to be tested based on the comparison result, the first preset comprehensive evaluation value is less than the second preset comprehensive evaluation value.

[0093] Specifically, when the comprehensive evaluation value is less than or equal to the first preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the third level. When the comprehensive evaluation value is greater than the first preset comprehensive evaluation value and less than or equal to the second preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the second level. When the comprehensive evaluation value is greater than the second preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the first level, the first level is greater than the second level, and the second level is greater than the third level.

[0094] It is understandable that by setting multiple preset comprehensive evaluation values, the quality of the sample to be tested can be accurately divided into multiple levels. This improves the accuracy of quality evaluation and makes the testing process more hierarchical and operational. By comparing the comprehensive evaluation value with the preset value, the quality level of the sample can be determined quickly and objectively, reducing the influence of subjective judgment. At the same time, clear grading makes quality control more targeted, helps optimize the production process, and improves the overall quality of the cable.

[0095] In the above embodiment, the integrated detection method of linear laser and infrared light is used to realize the synchronous detection of internal and external defects of isolated mineral insulated flexible cables. By using linear laser oblique irradiation and collecting sample surface image data based on CCD camera, surface defect information and appearance evaluation value are obtained. Linear laser enhances the defect recognition ability of CCD camera and reduces the influence of environmental shadow on the detection results. Through the combination of infrared parallel light source and infrared camera, the uniformity and density of mineral filling inside the cable can be detected, internal defects can be identified, and internal evaluation value can be generated. By comprehensively analyzing the appearance evaluation value and the internal evaluation value, the overall quality of the cable can be effectively determined. By rotating the platform and multi-light source synchronous detection, the human detection error is effectively reduced, and the objectivity and consistency of the evaluation results are ensured. The automation degree of the detection process is improved.

[0096] In another preferred embodiment based on the above embodiment, refer to Figure 2 As shown, this embodiment provides an isolated mineral insulated flexible cable detection system, which is used to apply the above-mentioned isolated mineral insulated flexible cable detection method, including:

[0097] A rotatable platform, a linear laser transmitter, an infrared parallel light source, an infrared camera and a control module, wherein:

[0098] The rotatable platform is used to fix the sample to be detected, the linear laser emitter is used to emit a linear laser to the surface of the sample to be detected, the infrared parallel light source is used to emit infrared light to the sample to be detected, and the infrared camera is used to collect infrared images; the control module is connected to the rotatable platform, the linear laser emitter, the infrared parallel light source and the infrared camera, and the control module includes:

[0099] A collection unit is configured to collect size information of the sample to be tested, determine the rotation speed of the rotatable platform according to the size information, turn on the linear laser emitter, run the rotatable platform at the determined rotation speed, and collect image data of at least two samples to be tested under the irradiation of the linear laser emitter based on a CCD camera, and obtain an appearance evaluation value of the sample to be tested according to the image data;

[0100] The processing unit is configured to use an infrared parallel light source to horizontally illuminate the sample to be tested, and collect infrared images based on an infrared camera, the infrared parallel light source and the infrared camera move horizontally synchronously to obtain an infrared image of the sample to be tested, analyze the infrared image to determine whether there are mineral filling defects inside the sample to be tested, and obtain an internal evaluation value of the sample to be tested based on the infrared image;

[0101] The evaluation unit is configured to determine a comprehensive evaluation value of the sample to be detected according to the appearance evaluation value and the internal evaluation value, and determine a quality grade of the sample to be detected according to the comprehensive evaluation value.

[0102] It can be understood that the synchronous detection of internal and external defects of isolated mineral insulated flexible cables is achieved through the comprehensive detection means of linear laser and infrared light. By using linear laser oblique irradiation and collecting sample surface image data based on CCD camera, surface defect information and appearance evaluation values ​​are obtained. Linear laser enhances the CCD camera's ability to identify defects and reduces the impact of environmental shadows on the detection results. Through the combination of infrared parallel light source and infrared camera, the uniformity and density of the mineral filling inside the cable can be detected, internal defects can be identified, and internal evaluation values ​​can be generated. By comprehensively analyzing the appearance evaluation value and the internal evaluation value, the overall quality of the cable can be effectively determined. Through the rotating platform and multi-light source synchronous detection, the human detection error is effectively reduced, ensuring the objectivity and consistency of the evaluation results. The automation of the detection process is improved.

[0103] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0104] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0105] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0106] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A detection method for isolated mineral insulated flexible cables, characterized in that: include: A sample to be tested is cut from the cable to be tested, the sample to be tested is fixed on a rotatable platform, a linear laser emitter is fixed above the sample to be tested, the linear laser emitter is tilted to irradiate the sample to be tested, and the linear laser is parallel to the axis of the sample to be tested; Collecting size information of the sample to be detected, determining the rotation speed of the rotatable platform according to the size information, turning on the linear laser emitter to operate the rotatable platform at the determined rotation speed, and collecting image data of at least two samples to be detected under the irradiation of the linear laser emitter based on a CCD camera, and obtaining an appearance evaluation value of the sample to be detected according to the image data; The sample to be tested is horizontally illuminated by an infrared parallel light source, and an infrared image is collected based on an infrared camera. The infrared parallel light source and the infrared camera move horizontally synchronously to obtain an infrared image of the sample to be tested, and the infrared image is analyzed to determine whether there are mineral filling defects inside the sample to be tested, and an internal evaluation value of the sample to be tested is obtained according to the infrared image; Determine a comprehensive evaluation value of the sample to be tested according to the appearance evaluation value and the internal evaluation value, and determine the quality grade of the sample to be tested according to the comprehensive evaluation value; When analyzing the infrared image to determine whether there is a mineral filling defect inside the sample to be tested, it includes: Segmenting the infrared image to obtain a2 sub-images, obtaining mineral density data according to each sub-image and establishing a mineral density matrix; A point is randomly selected in the mineral density matrix as a center point; The verification range is determined with the central point as the center and r as the radius; Obtaining a mineral density verification value according to the mineral density data within the verification range; Compare the mineral density data corresponding to the center point with the mineral density verification value, and determine whether there is a mineral filling defect inside the sample to be tested according to the comparison result; When the mineral density data corresponding to the center point is greater than 1.2 times the mineral density verification value, or the mineral density data corresponding to the center point is less than 0.8 times the mineral density verification value, it is determined that there is a mineral filling defect inside the sample to be tested; The mineral density verification value is calculated by the following formula: ； in, Represents the verification value of mineral density, r represents the radius of the verification range, ( , ) represents the coordinates of the center point, Represents the mineral density matrix Mineral density data of the point; When the appearance evaluation value of the sample to be tested is determined according to the number of defects and the defect size, the appearance evaluation value is calculated by the following formula: ； Where N represents the number of defects, qi represents the defect length, L represents the length of the sample to be tested, and wi represents the weight coefficient of the defect position. represents the distribution influence coefficient, and S represents the appearance evaluation value; When it is determined that there are mineral filling defects inside the sample to be tested, and the internal evaluation value of the sample to be tested is obtained according to the infrared image, the internal evaluation value is calculated by the following formula: ； Wherein, W represents the internal evaluation value, M represents the total number of mineral filling defects, Kj represents the mineral density data corresponding to the center point of the j-th defect, Ky represents the mineral density verification value, ej represents the weight coefficient of the j-th defect, Rj represents the distance from the center point of the j-th defect to the center axis of the cable, Rmax represents the maximum distance between the outer diameter of the cable and the center axis of the cable, and β represents the position influence coefficient.

2. The detection method of isolated mineral insulated flexible cable according to claim 1, characterized in that: When obtaining the appearance evaluation value of the sample to be detected according to the image data, it includes: Determine the surface defects of the sample to be inspected according to the line laser image in the image data; When the line laser image is a continuous straight line, it is determined that there is no defect on the surface of the sample to be inspected; When there are breakpoints in the line laser image, the straight line with the largest proportion in the same straight line in the line laser image is used as the reference line, and the number and size of defects on the surface of the sample to be detected are determined according to the reference line and the position of the breakpoints; The appearance evaluation value of the sample to be inspected is determined according to the defect quantity and defect size.

3. The detection method of isolated mineral insulated flexible cable according to claim 2, characterized in that: When determining the comprehensive evaluation value of the sample to be tested according to the appearance evaluation value and the internal evaluation value, it includes: The comprehensive evaluation value is obtained by weighted summing the appearance evaluation value and the internal evaluation value, and the weight coefficient of the appearance evaluation value and the weight coefficient of the internal evaluation value add up to 1.

4. The detection method of isolated mineral insulated flexible cable according to claim 3, characterized in that: When determining the quality level of the sample to be tested according to the comprehensive evaluation value, it includes: The comprehensive evaluation value is compared with a first preset comprehensive evaluation value and a second preset comprehensive evaluation value respectively, and the quality level of the sample to be tested is determined according to the comparison result, and the first preset comprehensive evaluation value is less than the second preset comprehensive evaluation value; When the comprehensive evaluation value is less than or equal to a first preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the third level; when the comprehensive evaluation value is greater than the first preset comprehensive evaluation value and less than or equal to the second preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the second level; when the comprehensive evaluation value is greater than the second preset comprehensive evaluation value, the quality level of the sample to be detected is determined to be the first level, the first level is greater than the second level, and the second level is greater than the third level.

5. An isolated mineral insulated flexible cable detection system, used for applying the isolated mineral insulated flexible cable detection method according to any one of claims 1 to 4, characterized in that: include: A rotatable platform, a linear laser transmitter, an infrared parallel light source, an infrared camera and a control module, wherein: The rotatable platform is used to fix the sample to be detected, the linear laser emitter is used to emit a linear laser to the surface of the sample to be detected, the infrared parallel light source is used to emit infrared light to the sample to be detected, and the infrared camera is used to collect infrared images; the control module is connected to the rotatable platform, the linear laser emitter, the infrared parallel light source and the infrared camera, and the control module includes: A collection unit is configured to collect size information of the sample to be tested, determine the rotation speed of the rotatable platform according to the size information, turn on the linear laser emitter, operate the rotatable platform at the determined rotation speed, and collect image data of at least two samples to be tested under the irradiation of the linear laser emitter based on a CCD camera, and obtain an appearance evaluation value of the sample to be tested according to the image data; A processing unit is configured to horizontally illuminate the sample to be detected with an infrared parallel light source, and collect infrared images based on an infrared camera, wherein the infrared parallel light source and the infrared camera move horizontally synchronously to obtain an infrared image of the sample to be detected, analyze the infrared image to determine whether there are mineral filling defects inside the sample to be detected, and obtain an internal evaluation value of the sample to be detected based on the infrared image; The evaluation unit is configured to determine a comprehensive evaluation value of the sample to be detected according to the appearance evaluation value and the internal evaluation value, and determine a quality grade of the sample to be detected according to the comprehensive evaluation value.

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