A wire quality detection method and device based on wire shielding performance

Abstract

The present invention discloses a wire quality detection method based on wire shielding performance, comprising the following steps: collecting electromagnetic interference source data and wire structure data; performing a matrix construction operation to obtain a magnetic interference source characteristic matrix; performing a matrix value extraction operation to obtain a first energy impact factor and a second energy impact factor; performing an interference parameter construction operation to obtain an initial interference degree sequence; performing a sequence update operation to obtain an interference degree distance sequence; performing a cluster region extraction operation to obtain a sensitive shielding region; performing a calculation to obtain a sensitive shielding factor; performing a calculation to obtain a wire shielding value; when the wire shielding value is less than a preset wire shielding performance threshold, determining that the wire shielding performance does not meet the requirements; and when the wire shielding value is greater than or equal to the preset wire shielding performance threshold, determining that the wire shielding performance meets the requirements. This method reflects the shielding performance of the wire by combining electromagnetic interference source and wire structure data, thereby improving the accuracy of wire quality detection.

Description

Technical Field

[0001] The present invention relates to the technical field of wire quality detection, and in particular to a wire quality detection method and device based on wire shielding performance. Background Art

[0002] With the rapid development of technology, various electrical devices play an important role in daily life. However, during use, these devices generate electromagnetic waves, which in turn cause electromagnetic interference to other nearby devices. Therefore, how to effectively shield electromagnetic interference has become a major research topic. The shielding efficiency of wires is a key factor in measuring their quality, and this efficiency is affected by many factors, such as the material and thickness of the wire shielding layer, as well as the wavelength of the transmitted signal.

[0003] One existing technique involves placing the wires to be tested within a shielded chamber and measuring their shielding effectiveness using a shielding effectiveness analyzer. This method involves two tests: first, testing the shielding effectiveness of the wires with both a signal harness and a shielded harness. Second, testing the shielding effectiveness of the wires with only the shielded harness removed. The shielding effectiveness of the wires is evaluated by comparing these two measured shielding effectiveness values.

[0004] In the existing technology, wire quality detection is unable to comprehensively collect and analyze the electromagnetic interference source data of the wire's surrounding environment, fails to analyze the degree of influence of the electromagnetic interference source and the wire structure on the wire interference, and cannot accurately evaluate the shielding performance of the wire, thereby affecting the accurate judgment of the wire quality. Summary of the Invention

[0005] The present invention provides a wire quality detection method and device based on wire shielding performance. By combining electromagnetic interference sources and wire structure data, the shielding performance of the wire is reflected, thereby improving the accuracy of wire quality detection.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides a wire quality detection method based on wire shielding performance, comprising:

[0007] Collect electromagnetic interference source data and wire structure data;

[0008] Performing a matrix construction operation according to the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix;

[0009] Performing a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor;

[0010] performing an interference parameter construction operation according to the first energy impact factor, the second energy impact factor, and the electromagnetic interference source data to obtain an initial interference degree sequence;

[0011] performing a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence;

[0012] According to the wire structure data, a clustering region extraction operation is performed based on an agglomerative hierarchical clustering algorithm to obtain a sensitive shielding region;

[0013] Calculating according to the interference degree distance sequence and the sensitive shielding area to obtain a sensitive shielding factor corresponding to the sensitive shielding area;

[0014] Calculating according to the interference degree distance sequence and the sensitive shielding factor to obtain a wire shielding value;

[0015] When the wire shielding value is less than the preset wire shielding performance threshold, it is determined that the shielding performance of the wire does not meet the requirements; when the wire shielding value is greater than or equal to the preset wire shielding performance threshold, it is determined that the shielding performance of the wire meets the requirements.

[0016] Preferably, performing a matrix construction operation based on the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix includes:

[0017] Performing a vector construction operation on the electromagnetic interference source data to obtain a first signal vector, a second signal vector, and a third signal vector;

[0018] The first signal vector, the second signal vector and the third signal vector are combined to obtain a magnetic interference source characteristic matrix.

[0019] Preferably, performing a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor includes:

[0020] Performing a non-negative matrix decomposition operation on the characteristic matrix of the magnetic interference source to obtain a basis matrix;

[0021] Extracting a first column value of the basis matrix, and determining the first column value as a first energy impact factor;

[0022] A value of the base matrix divided by the value of the first column is extracted, and the value divided by the value of the first column is determined as a second energy impact factor.

[0023] Preferably, performing a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence includes:

[0024] Performing a difference calculation operation based on the initial interference degree sequence and the first energy impact factor to obtain a first updated sequence;

[0025] Extracting values ​​greater than a preset update threshold from the first update sequence, and constructing a second update sequence from the values ​​greater than the preset update threshold;

[0026] The second update sequence is arranged in ascending order to obtain an interference degree distance sequence.

[0027] Preferably, the method of performing a clustering region extraction operation based on the wire structure data and an agglomerative hierarchical clustering algorithm to obtain sensitive shielding regions includes:

[0028] Standardizing the wire structure data to obtain standardized wire structure data;

[0029] Performing a similarity calculation operation on the standardized wire structure data to obtain data similarity;

[0030] Based on an agglomerative hierarchical clustering algorithm and according to the data similarity, cluster analysis is performed on the standardized wire structure data to obtain sensitive shielding areas.

[0031] Preferably, the calculation formula of the sensitive shielding factor is:

[0032]

[0033] Where r is the sensitive shielding factor; n is the number of sensitive shielding areas; F i is the i-th interference degree distance sequence value of the sensitive shielding area; CV(F) is the coefficient of variation of the interference degree sequence.

[0034] Preferably, the calculation formula of the wire shielding value is:

[0035]

[0036] Where r is the sensitive shielding factor; n is the number of sensitive shielding areas; F i is the i-th interference distance sequence value of the sensitive shielding area; f is the shielding value of the wire.

[0037] In a second aspect, the present invention provides a wire quality detection device based on wire shielding performance, comprising:

[0038] Data acquisition module, used to collect electromagnetic interference source data and wire structure data;

[0039] A matrix construction module is used to perform a matrix construction operation based on the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix;

[0040] An impact factor extraction module is used to perform a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor;

[0041] an initial sequence module, configured to perform an interference parameter construction operation according to the first energy impact factor, the second energy impact factor, and the electromagnetic interference source data to obtain an initial interference degree sequence;

[0042] a distance sequence module, configured to perform a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence;

[0043] A region extraction module is used to perform a cluster region extraction operation based on the wire structure data and an agglomerative hierarchical clustering algorithm to obtain a sensitive shielding region;

[0044] A sensitivity factor calculation module, configured to calculate, based on the interference degree distance sequence and the sensitive shielding area, a sensitive shielding factor corresponding to the sensitive shielding area;

[0045] A shielding value calculation module, configured to calculate the shielding value of the wire according to the interference degree distance sequence and the sensitive shielding factor;

[0046] The performance determination module is configured to determine that the shielding performance of the wire does not meet the requirements when the shielding value of the wire is less than a preset wire shielding performance threshold; and to determine that the shielding performance of the wire meets the requirements when the shielding value of the wire is greater than or equal to the preset wire shielding performance threshold.

[0047] In a third aspect, the present invention also provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements any one of the above-mentioned wire quality detection methods based on wire shielding performance.

[0048] In a fourth aspect, the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned wire quality detection methods based on wire shielding performance.

[0049] Compared to existing technologies, this invention combines electromagnetic interference source data with wire structure data to construct an electromagnetic interference source feature matrix and sensitive shielding factors, enabling accurate assessment of wire shielding performance. By constructing and optimizing the interference degree sequence, the invention effectively identifies sensitive shielding areas within wires, improving the accuracy of wire quality testing. Furthermore, the invention optimizes the updating process of the interference degree sequence. By calculating the first energy impact factor and performing difference analysis on the initial interference degree sequence, an update threshold is set to filter out key data, ensuring that the updated interference degree sequence more accurately reflects wire shielding performance. Furthermore, the invention constructs a wire shielding performance assessment method based on the sensitive shielding factor and interference degree distance sequence. By comparing the wire shielding value with a preset shielding performance threshold, the wire quality can be determined. Finally, the invention utilizes an agglomerative hierarchical clustering algorithm to process wire structure data, combining external interference sources with the specific structural characteristics of the wire to extract sensitive shielding areas, thereby enhancing the reliability of the test results. Furthermore, the calculation of the sensitive shielding factor simplifies the mathematical modeling process through logarithms and coefficients of variation, improving computational efficiency and reducing errors.

[0050] In summary, the present invention reflects the shielding performance of the wire by combining the electromagnetic interference source and the wire structure data, thereby improving the accuracy of wire quality detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 1 is a flow chart of a wire quality detection method based on wire shielding performance provided by a first embodiment of the present invention;

[0052] Figure 2 2 is a schematic structural diagram of a wire quality detection device based on wire shielding performance provided by a second embodiment of the present invention. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] Reference Figure 1 The first embodiment of the present invention provides a wire quality detection method based on wire shielding performance, comprising the following steps:

[0055] S11, collecting electromagnetic interference source data and wire structure data;

[0056] S12, performing a matrix construction operation according to the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix;

[0057] S13, performing a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor;

[0058] S14, performing an interference parameter construction operation according to the first energy impact factor, the second energy impact factor, and the electromagnetic interference source data to obtain an initial interference degree sequence;

[0059] S15, performing a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence;

[0060] S16, performing a clustering region extraction operation based on the wire structure data and an agglomerative hierarchical clustering algorithm to obtain a sensitive shielding region;

[0061] S17, performing calculation based on the interference degree distance sequence and the sensitive shielding area to obtain a sensitive shielding factor corresponding to the sensitive shielding area;

[0062] S18, performing calculation based on the interference degree distance sequence and the sensitive shielding factor to obtain a shielding value of the wire;

[0063] S19, when the shielding value of the wire is less than the preset wire shielding performance threshold, it is determined that the shielding performance of the wire does not meet the requirements; when the shielding value of the wire is greater than or equal to the preset wire shielding performance threshold, it is determined that the shielding performance of the wire meets the requirements.

[0064] In step S11, electromagnetic interference source data and wire structure data need to be collected, including:

[0065] In a specific embodiment, electromagnetic interference source data refers to electromagnetic wave or electric field data in the external environment that affects the shielding performance of wires. These interference sources can come from a variety of different devices or environments, including electronic devices, such as household appliances (such as televisions, air conditioners, microwave ovens, etc.) and industrial equipment (such as welding machines, electric motors, etc.), which all generate electromagnetic waves when working. These signals will propagate in the surrounding space and affect the shielding performance of wires; wireless communication signals, Wi-Fi routers, mobile phone signal towers, Bluetooth devices, etc., whose electromagnetic wave frequency bands interfere with the operating frequency of wires, affecting the anti-interference ability of wires; electromagnetic interference of power systems: the electromagnetic fields released by power lines, substations and other equipment also interfere with wires, especially high-voltage and high-frequency power transmission, which can make the shielding layer of wires ineffective.

[0066] For example, if power lines are installed in an industrial plant where large electric motors are operating, their electromagnetic radiation can affect the shielding performance of the power lines. Therefore, real-time monitoring is necessary using electromagnetic interference measurement equipment (such as electric field detectors and spectrum analyzers) at various locations near the power lines. These devices can measure the intensity, frequency, and waveform characteristics of the interference signal, thereby generating interference source data.

[0067] In a specific embodiment, wire structural data refers to the geometric and electrical properties of the wire itself. These structural parameters directly affect the wire's resistance to electromagnetic interference. Wire structural data includes the wire's geometric dimensions, such as the wire diameter, shielding thickness, and the spacing between conductors. For example, the thickness of a coaxial cable's shielding layer significantly impacts its anti-interference capabilities; a thicker shielding layer more effectively blocks external interference. Material composition—the choice of materials for the conductor, insulation, and shielding layer of a wire—affects the wire's electromagnetic shielding effectiveness. For example, copper and aluminum conductors have different electrical conductivities. Copper wire offers better conductivity, while aluminum is lighter but offers relatively poor shielding effectiveness. Electrical properties include the wire's impedance, conductivity, and dissipation factor. These properties determine the wire's immunity to external electromagnetic interference during signal transmission. For example, mismatched impedance characteristics can lead to signal reflections, increasing the impact of electromagnetic interference.

[0068] For example, for a coaxial cable, the shielding layer is made of aluminum foil or copper braid. If the cable structure is not properly designed, the shielding layer is too thin, or the distance between the conductor and the shielding layer is too large, external electromagnetic waves can penetrate the shielding layer and enter the cable, affecting the signal transmission quality. Therefore, by collecting structural data of the wire, including information such as the thickness and material of the shielding layer, and the relative position of the conductor and shielding layer, its anti-interference performance can be evaluated.

[0069] Specifically, electromagnetic interference sensors (such as near-field detectors and spectrum analyzers) can be used to collect electromagnetic interference signals in the surrounding environment. These sensors can be deployed in different locations to record key data such as electromagnetic field strength and frequency distribution. Digital measuring instruments or CAD models can be used to obtain the physical structure data of the wires. Specifically, computer-aided design (CAD) software can be used to model the wire's geometric parameters, or dedicated instruments (such as calipers and micrometers) can be used to measure the actual dimensions of the wires.

[0070] In step S12, a matrix construction operation needs to be performed based on the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix, including:

[0071] In a specific embodiment, electromagnetic interference source data has been collected and recorded in different signal forms. Assuming that interference signal data has been collected from multiple locations (such as power equipment, wireless communication equipment, etc.), the data of each interference source includes multiple parameters, such as signal strength, frequency, waveform characteristics, etc. For example, the following types of electromagnetic interference source data are obtained: signal strength (such as electric field strength, current strength, etc.), frequency range of the interference source, and time domain or frequency domain characteristics of the electromagnetic waveform.

[0072] Next, based on the collected electromagnetic interference source data, each interference source signal needs to be processed and converted into a vector form. The purpose of this is to make the data have a structured format to facilitate matrix construction and subsequent analysis.

[0073] Specifically, the signal amplitudes (such as electric field strength and magnetic field strength) of all interference sources are extracted and organized into vectors according to different interference source numbers. For example, suppose there are three interference sources, and their signal strength data are: interference source 1, signal strength is [12, 15, 20, 10] (each item represents the signal strength of the interference source at different time or spatial positions), interference source 2, signal strength is [9, 10, 15, 8], interference source 3: signal strength is [6, 8, 12, 7]. Therefore, the first signal vector can be expressed as: first signal vector = [12, 15, 20, 10], second signal vector = [9, 10, 15, 8], third signal vector = [6, 8, 12, 7]

[0074] Specifically, the frequency characteristics of each interference source are extracted, assuming that each interference source has a set of main frequency values. These frequency values ​​are used to form a second signal vector according to the interference source. For example, the frequency data of the interference source are: interference source 1, frequency is [50Hz, 60Hz, 70Hz], interference source 2, frequency is [100Hz, 110Hz, 120Hz], interference source 3, frequency is [30Hz, 40Hz, 50Hz], therefore, the second signal vector is: second signal vector = [50, 60, 70], second signal vector = [100, 110, 120], second signal vector = [30, 40, 50]

[0075] Specifically, the time domain or frequency domain features of the interference source signal are extracted, and the waveform of the signal is subjected to Fourier transform or other time domain analysis to obtain a feature vector. For example: Interference source 1, the time domain feature value is [0.2, 0.3, 0.4], interference source 2, the time domain feature value is [0.1, 0.2, 0.5], interference source 3: the time domain feature value is [0.3, 0.1, 0.2]. Therefore, the third signal vector is: third signal vector = [0.2, 0.3, 0.4], third signal vector = [0.1, 0.2, 0.5], third signal vector = [0.3, 0.1, 0.2].

[0076] Specifically, after obtaining the first, second, and third signal vectors, they are combined into a single matrix to form the magnetic interference source feature matrix. The purpose of matrix construction is to structure the multidimensional data (amplitude, frequency, time domain characteristics, etc.) of the interference source into a form that is easy to calculate and process.

[0077] In a specific embodiment, assuming that each signal vector is arranged as a column vector of a matrix, the following magnetic interference source characteristic matrix X is finally obtained:

[0078]

[0079] It should be noted that each row of the matrix corresponds to the signal characteristics of an interference source, and each column represents a different type of signal characteristics. In a specific embodiment, the first column represents the amplitude (signal strength) of each interference source, the second column represents the frequency of each interference source, and the third column represents the time domain or frequency domain characteristics of each interference source.

[0080] In step S13, it is necessary to perform a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor, including:

[0081] In a specific embodiment, non-negative matrix factorization (NMF) is a technique for decomposing a non-negative matrix into two low-rank non-negative matrices. In the steps of the present invention, NMF can extract factors reflecting the interference source characteristics from the magnetic interference source feature matrix. Through decomposition, the potential pattern of the electromagnetic interference source signal can be identified and its impact on the shielding performance of the wire can be calculated.

[0082] For example, assuming that the characteristic matrix of the magnetic interference source is XX, it is decomposed into two non-negative matrices WW and HH:

[0083] X=W·H

[0084] Where X is the characteristic matrix of the magnetic interference source, W is the basis matrix, and H is the coefficient matrix.

[0085] Specifically, it is assumed that the magnetic interference source characteristic matrix X is the following matrix:

[0086]

[0087] Apply a non-negative matrix factorization algorithm (such as ALS, gradient descent, etc.) to decompose the matrix XX to obtain two non-negative matrices W and H. For example, the decomposed matrices W and H are as follows:

[0088]

[0089] Specifically, the matrix W is the basis matrix, which contains some potential factors of the interference source signal; the matrix H is the coefficient matrix, which represents the contribution of each gene in the original matrix.

[0090] Next, extract the first column of data from the basis matrix W as the first energy impact factor. This step maps the information from the decomposed original interference source feature matrix back to a factor physically related to the electromagnetic interference intensity. For example, assuming the first column of the basis matrix W is: W1 = [0.5, 0.6, 0.7, 0.4, 0.3, 0.4, 0.6, 0.3, 0.2, 0.3, 0.5, 0.2], this column is extracted and determined as the first energy impact factor, representing the impact factor related to the amplitude or intensity of the interference source.

[0091] In a specific embodiment, for the second energy impact factor, it is necessary to extract data from other columns except the first column from the base matrix W. These columns represent other influencing factors of the electromagnetic interference source, such as frequency, time domain characteristics, etc. Therefore, the second column, the third column (and more columns) are extracted from the matrix W and combined or processed into the second energy impact factor. For example, the second and third columns of the base matrix W are:

[0092] W2=[0.3,0.4,0.5,0.3,0.1,0.2,0.5,0.4,0.1,0.3,0.4,0.3] and

[0093] W3 = [0.1, 0.2, 0.3, 0.2, 0.4, 0.3, 0.2, 0.3, 0.5, 0.2, 0.1, 0.4]. These columns can be combined (for example, taking their weighted average, maximum value, etc.) to form the second energy impact factor. Assume that the second energy impact factor after the combination is: W 2,3 =[0.3,0.35,0.4,0.3,0.25,0.25,0.35,0.3,0.25,0.3,0.3,0.3]

[0094] It should be noted that the first energy impact factor mainly reflects the main impact of the electromagnetic interference source on the shielding performance of the cable. Among the characteristics of the electromagnetic interference source, there are some main interference modes or impact factors.

[0095] This factor is closely linked to the interference source's amplitude, frequency, and other related characteristics, and therefore helps quantify the direct impact of the interference source on cable shielding. For example, a strong electromagnetic interference source will result in a large first energy impact factor value (e.g., 1.4), indicating that the cable's shielding performance in this environment does not meet requirements. The second energy impact factor, by extracting data from columns other than the first from the base matrix, reflects the secondary impact factors of the electromagnetic interference source. The impact of an electromagnetic interference source is not simply manifested in intensity or amplitude; it also involves secondary characteristics such as frequency and time variation. These secondary characteristics can further reveal the shielding performance of the cable. For example, some interference sources, although small in amplitude (0.2), can have a strong radiation impact on the cable at a high frequency (2kHz). The second energy impact factor supplements the interference information not fully captured by the first energy impact factor. For example, in some scenarios, the frequency and time-varying characteristics of the interference source have a significant impact on shielding performance, characteristics that are not fully reflected in the first energy impact factor. The introduction of the second energy impact factor makes the shielding performance assessment more comprehensive and accurate.

[0096] In step S14, an interference parameter construction operation needs to be performed based on the first energy impact factor, the second energy impact factor and the electromagnetic interference source data to obtain an initial interference degree sequence, including:

[0097] In a specific embodiment, the initial interference degree sequence is an indicator for measuring the impact of electromagnetic interference sources on the shielding performance of the wire.

[0098] The interference degree sequence can be calculated using the following formula:

[0099] D i =|E1-E2|×D s

[0100] Among them, D i represents the interference degree of the i-th interference source; E1 represents the first energy impact factor; E2 represents the second energy impact factor; D s Indicates electromagnetic interference source data (such as signal strength).

[0101] Exemplarily, for each electromagnetic interference source, based on its corresponding first energy impact factor, second energy impact factor, and interference source data, it is assumed that there are three interference source data:

[0102] Interference source 1: first energy impact factor E1 = 5.0, second energy impact factor E2 = 3.0, electromagnetic interference source data D s =2.5

[0103] D1=|5.0-3.0|×2.5=2.0×2.5=5.0

[0104] Interference source 2: first energy impact factor E1 = 4.0, second energy impact factor E2 = 3.5, electromagnetic interference source data D s =3.0

[0105] D2=|4.0-3.5|×1.5=0.5×1.5=0.75

[0106] Interference source 3: first energy impact factor E1 = 6.0, second energy impact factor E2 = 2.0, electromagnetic interference source data D s =3.0

[0107] D3=|6.0-2.0|×3.0=4.0×3.0=12.0

[0108] Next, arrange the interference values ​​of all interference sources in order to obtain the interference sequence:

[0109] Interference sequence = [D1, D2, D3] = [5.0, 0.75, 12.0]

[0110] In step S15, it is necessary to perform a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence, including:

[0111] In a specific embodiment, the preset update threshold (T thresh ) is set to filter out interference sources that have an impact on the interference calculation. In practice, this threshold is set based on statistical analysis of the initial interference sequence (such as variance and standard deviation), and the threshold is determined based on the data distribution characteristics. For example, the threshold can be set as the mean of the initial interference sequence plus a multiple of the standard deviation to ensure that the interference sources screened out are abnormal or extreme values.

[0112] For example, assuming that the mean of the first update sequence is μ=0.5 and the standard deviation is σ=1.2, the update threshold T can be set to thresh =μ+2·σ=0.5+2·1.2=2.0. The function of updating the threshold is to filter out the data items that have a greater impact on the interference sequence.

[0113] In a specific embodiment, the first update sequence is obtained by calculating the difference between the initial interference degree sequence and the first energy impact factor. The sequence reflects the potential impact of each interference source on the wire shielding performance, especially the changing relationship between the interference source and the wire shielding performance.

[0114] For example, if D1 = 5.0 and E1 = 3.0, the first item in the first update sequence is Δ1 = 5.0 - 3.0 = 2.0. For D2 = 1.5 and E1 = 3.0, the second item in the first update sequence is Δ2 = 1.5 - 3.0 = -1.5. The first update sequence provides basic data for further screening and sorting operations. A larger value in this sequence (9.0) indicates a greater impact from the interference source, and vice versa.

[0115] In one embodiment, the second update sequence is performed by filtering out items greater than a preset update threshold from the first update sequence and retaining the interference source data. This step is intended to remove noise and irrelevant interference, ensuring that subsequent steps focus on interference sources that truly affect cable shielding performance.

[0116] For example, it is assumed that the preset update threshold T thresh =1.0, then the second update sequence filtered out from the first update sequence is: the second update sequence is [2.0, -1.5, 3.0]. The second update sequence focuses on processing interference sources that affect the shielding performance of the wires, further improving the efficiency and accuracy of data analysis.

[0117] In one specific embodiment, the interference distance sequence is the ascending order of the second updated sequence, reflecting the ranking of interference sources by their impact. By ranking the impact of interference sources, it is possible to intuitively understand which interference sources have the greatest impact on cable shielding performance, facilitating further analysis and decision-making.

[0118] Assuming the second update sequence is [2.0, -1.5, 3.0], after sorting in ascending order, the interference distance sequence becomes [-1.5, 2.0, 3.0]. Sorting the interference distance sequence in ascending order places less influential interference sources at the front and more influential interference sources at the back. This sorting helps further screen or optimize shielding performance in cable designs.

[0119] In step S16, a clustering region extraction operation is performed based on the wire structure data and an agglomerative hierarchical clustering algorithm to obtain sensitive shielding regions, including:

[0120] First, the wire structure data needs to be standardized. The main purpose of standardization is to eliminate the dimensional differences between different features, so that the values ​​of each feature are on the same scale, thereby preventing certain features from having a significant impact on the analysis results due to a large numerical range or different units. Through standardization, different features in the data can participate fairly in distance calculations or cluster analysis, improving the accuracy and convergence speed of the model. Especially when multiple features are involved, it can enable the algorithm to focus more on the actual differences between features, reduce the impact of outliers, and improve the stability and reliability of the final results.

[0121] Specifically, for each characteristic value of the wire (for example, core radius, shielding layer thickness, etc.), its mean and standard deviation are calculated and converted into a standardized value. The standardization formula is:

[0122]

[0123] Among them, C is the wire structure data; C ave is the mean of the feature; C σ is the standard deviation of the feature.

[0124] It should be noted that parameters such as core radius, insulation layer thickness, and shielding layer thickness are key features of the wire structure. After standardization, their contributions at different scales are balanced, avoiding the excessive influence of certain features on the clustering results due to dimensionality issues.

[0125] Next, based on the standardized wire structure data, the similarity between data points is calculated. This step helps determine which samples are similar in wire structure by calculating the similarity between samples, thereby performing clustering. The present invention calculates the direct spatial distance between wire structure data samples using the Euclidean distance method. The Euclidean distance method is suitable for data with numerical features, such as wire core radius, insulation layer thickness, etc. The calculation formula for the spatial distance is:

[0126]

[0127] Among them, d ij is the Euclidean distance between sample i and sample j, x ik and x jk is the kth feature of sample i and sample j.

[0128] In a specific embodiment, the wire samples are first standardized to ensure that the different parameters of each wire structure (such as wire diameter, shielding layer thickness, insulation material density, etc.) have the same dimension. During the standardization process, each parameter is subtracted from its mean and divided by the standard deviation to make the units of all parameters consistent and eliminate the influence of different dimensions. Next, the similarity between the wire samples is calculated, and the Euclidean distance is used as a measure of the difference between the samples. The Euclidean distance calculation formula is the square root of the sum of the squares of the differences in each feature dimension. According to the calculated similarity matrix, the smaller the value, the higher the similarity between the wire samples, and the larger the value, the greater the difference between the wire samples. Generally speaking, a similarity value of 0 to 0.5 indicates that the samples are very similar, a value between 0.5 and 0.8 indicates similarity, and a value above 0.8 indicates a large difference.

[0129] Next, a cohesive hierarchical clustering algorithm is applied for cluster analysis. In the initial stage of the algorithm, each wire sample is regarded as an independent cluster. Based on the similarity matrix, the similarity between clusters is calculated by methods such as the single chain method (shortest distance method), the complete chain method (longest distance method) or the average distance method. For example, when using the single chain method, each time two clusters are merged, the shortest distance between them is calculated, and the two clusters with the highest similarity (smallest value) are selected for merging. After each merge, the similarity between the merged clusters and other clusters is recalculated, and this process is continued iteratively until all wire samples are clustered into a large cluster. In this process, when the similarity is large (such as above 0.8), it means that the difference between the two clusters is large, and special attention should be paid when merging to prevent excessive merging from causing information loss.

[0130] Through this process, multiple clusters of wire structures can be obtained, each cluster representing an area with similar shielding performance characteristics. Among these clusters, some clusters show areas with large differences in shielding performance, and these areas are sensitive shielding areas. For example, the wire shielding layer in some areas shows thinner (less than 1 mm) or irregular (thickness fluctuation exceeds 20%) characteristics. The electromagnetic shielding performance of these areas is relatively weak, resulting in the inability to effectively isolate electromagnetic interference, and therefore has higher sensitivity. Cluster analysis can identify these sensitive shielding areas and provide an important basis for wire design and optimization.

[0131] What is needed is that the sensitive shielding area is the part of the cable shielding performance that is most easily affected. For example, if the shielding layer in some areas is too thin or the metal layer of the cable is uneven, the interference in these areas will affect the overall electromagnetic shielding capability of the cable. For example, assuming the following standardized wire structure data (assuming the data has been standardized), the core radius of sample 1 is -0.3, the insulation thickness is 0.5, and the shielding thickness is 1.0; the core radius of sample 2 is -0.2, the insulation thickness is 0.6, and the shielding thickness is 1.1; the core radius of sample 3 is 1.1, the insulation thickness is -0.4, and the shielding thickness is -1.2; the core radius of sample 1 is 1.1, the insulation thickness is -0.4, and the shielding thickness is -1.2; the core radius of sample 4 is 0.9, the insulation thickness is -0.3, and the shielding thickness is -1.0. Through similarity calculation, the Euclidean distance between all samples is calculated to obtain a similarity matrix. Cluster analysis is then performed using an agglomerative hierarchical clustering algorithm based on the calculated similarity matrix. Assume that two clusters are ultimately obtained: Cluster 1 contains samples 1 and 2, and Cluster 2 contains samples 3 and 4. Next, sensitive shielding areas are extracted. Based on the clustering results, the samples in Cluster 2 are analyzed and found to have thin shielding layers, which are sensitive areas that are easily affected by electromagnetic interference.

[0132] In step S17, calculation is performed based on the interference degree distance sequence and the sensitive shielding area to obtain a sensitive shielding factor corresponding to the sensitive shielding area, including:

[0133] In a specific embodiment, the sensitive shielding factor is a comprehensive indicator used to indicate the sensitivity of various areas within a power line to electromagnetic interference. Calculating this factor can help identify areas within the power line structure with poor shielding performance. These areas may exhibit issues such as thin shielding layers, uneven materials, and irregular structures, making them susceptible to external electromagnetic interference.

[0134] In a specific embodiment, the coefficient of variation (CV) is an indicator that describes the degree of data dispersion and is used to quantify the degree of dispersion of the interference sequence. It is the ratio of the standard deviation to the mean and can reflect the relative degree of data variability. Specifically, the coefficient of variation (CV) is used to measure the degree of fluctuation of the interference sequence and is calculated as follows:

[0135]

[0136] Where σ(F) is the standard deviation of the noise series, and μ(F) is the mean of the noise series. The standard deviation is the square root of the sum of the squares of the differences between all noise data and the mean, and the mean is the average of all noise data.

[0137] It should be noted that the mean μ(F) of the interference sequence is calculated by summing all the values ​​in the interference sequence and dividing by the number of sequences; the standard deviation σ(F) of the interference sequence is calculated by first calculating the difference between each value in the interference sequence and the mean, squaring these differences and summing them, and then taking the square root to obtain the standard deviation.

[0138] In a specific embodiment, the sensitive shielding factor is obtained by taking the logarithm of the interference distance sequence values ​​of all sensitive shielding areas, then summing them, and then dividing them by the coefficient of variation. The calculation formula of the sensitive shielding factor is:

[0139]

[0140] Where r is the sensitive shielding factor; n is the number of sensitive shielding areas; F i is the i-th interference degree distance sequence value of the sensitive shielding area; CV(F) is the coefficient of variation of the interference degree sequence.

[0141] It should be noted that the calculated sensitive shielding factor is used to identify which areas in the wire structure have the most sensitive shielding performance and which areas cannot effectively isolate interference sources due to electromagnetic interference.

[0142] In step S18, calculation is performed based on the interference degree distance sequence and the sensitive shielding factor to obtain the wire shielding value, including:

[0143] In a specific embodiment, the shielding value (f) of a wire reflects the wire's ability to protect against electromagnetic interference. A larger value (e.g., 15.1) indicates a better shielding effect, effectively isolating the wire from electromagnetic interference; a smaller value (e.g., 1.2) indicates a poor shielding effect, making the wire more susceptible to interference.

[0144] Specifically, the calculation formula of the wire shielding value is:

[0145]

[0146] Where r is the sensitive shielding factor; n is the number of sensitive shielding areas; F i is the i-th interference distance sequence value of the sensitive shielding area; f is the shielding value of the wire.

[0147] In step S19, when the shielding value of the wire is less than a preset wire shielding performance threshold, it is determined that the shielding performance of the wire does not meet the requirements; when the shielding value of the wire is greater than or equal to the preset wire shielding performance threshold, it is determined that the shielding performance of the wire meets the requirements, including:

[0148] In a specific embodiment, the preset wire shielding performance threshold is a standard value set based on factors such as the working environment, usage requirements, and industry standards of the wire. Specifically, the preset wire shielding performance threshold is set taking into account the electromagnetic environment category, that is, the electromagnetic environment in which the wire is located affects its required shielding performance. For example, in a high-noise environment (such as an industrial environment, a data center, etc.), a higher shielding capability is required. On the contrary, in a low-noise environment (such as household electrical equipment or communication lines), a lower shielding performance is required; considering the application scenario, different wire application scenarios have different requirements for shielding capabilities. For example, medical equipment, power transmission lines, high-frequency communication lines and other fields have extremely low tolerance for electromagnetic interference, so their shielding performance requirements are relatively high.

[0149] For example, first, information about the target wire's application scenario and working environment needs to be collected, and then an appropriate shielding performance evaluation method is selected. Shielding performance can be evaluated using indicators such as the wire's conduction loss, reflection loss, external electric field, and internal current. For specific wire designs, "Electromagnetic Shielding Effectiveness" (ESE) is selected as the primary evaluation criterion. The ESE measurement standard refers to the ability of the wire or cable shield to block the propagation of electromagnetic waves, measured in decibels (dB). For example, an ESE value of 60dB means that the wire shields approximately 99.9999% of electromagnetic waves. Shielding performance thresholds are set based on the environment, application scenario, and standard specifications, combined with ESE values ​​or other measurement indicators. For low electromagnetic interference environments, such as household electrical equipment and low-frequency power transmission, the preset threshold can be 30-40dB, meaning that the wire needs to effectively isolate external electromagnetic interference within a range of 30-40dB. For medium electromagnetic interference environments, such as office environments and data communication lines, The preset threshold can be 40-60dB. For high electromagnetic interference environments, such as industrial environments, medical equipment, and high-frequency communication lines, the preset threshold can be 60-80dB, which requires stronger wire shielding capabilities to effectively isolate high-intensity electromagnetic interference.

[0150] Exemplarily, the calculated wire shielding value is compared with a set preset wire shielding performance threshold.

[0151] Based on the relationship between the shielding value and the threshold, the following judgment operation is performed: when the shielding value of the wire is less than the preset shielding performance threshold, that is, the shielding value of the wire is less than the threshold, the shielding performance of the wire is determined to be unsatisfactory, indicating that the wire's anti-interference ability is insufficient and cannot effectively shield electromagnetic interference. In this case, it is necessary to redesign the wire structure, add a shielding layer, or improve the shielding effect of the wire. When the shielding value of the wire is greater than or equal to the preset shielding performance threshold, that is, the shielding value of the wire is greater than or equal to the threshold, the shielding performance of the wire is determined to be satisfactory, indicating that the wire can effectively resist electromagnetic interference and is suitable for the specific electromagnetic environment.

[0152] In summary, the present invention combines electromagnetic interference source data with wire structure data to construct an electromagnetic interference source feature matrix and sensitive shielding factors, enabling accurate assessment of wire shielding performance. By constructing and optimizing the interference degree sequence, the sensitive shielding areas of the wire are effectively identified, improving the accuracy of wire quality testing. Furthermore, the present invention optimizes the updating process of the interference degree sequence. By calculating the first energy impact factor and performing difference analysis on the initial interference degree sequence, an update threshold is set to filter out key data, ensuring that the updated interference degree sequence more accurately reflects the wire shielding performance. Furthermore, the present invention constructs a wire shielding performance assessment method based on the sensitive shielding factor and interference degree distance sequence. By comparing the wire shielding value with a preset shielding performance threshold, the wire quality can be determined. Finally, the present invention utilizes an agglomerative hierarchical clustering algorithm to process the wire structure data, combining external interference sources with the specific structural characteristics of the wire to extract sensitive shielding areas, thereby enhancing the reliability of the test results. Furthermore, the calculation of the sensitive shielding factor simplifies the mathematical modeling process through logarithms and coefficients of variation, improving computational efficiency and reducing errors. By combining electromagnetic interference source and wire structure data, the shielding performance of the wire is reflected, improving the accuracy of wire quality testing.

[0153] Reference Figure 2 A second embodiment of the present invention provides a wire quality detection device based on wire shielding performance, comprising:

[0154] Data acquisition module, used to collect electromagnetic interference source data and wire structure data;

[0155] A matrix construction module is used to perform a matrix construction operation based on the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix;

[0156] An impact factor extraction module is used to perform a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor;

[0157] an initial sequence module, configured to perform an interference parameter construction operation according to the first energy impact factor, the second energy impact factor, and the electromagnetic interference source data to obtain an initial interference degree sequence;

[0158] a distance sequence module, configured to perform a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence;

[0159] A region extraction module is used to perform a cluster region extraction operation based on the wire structure data and an agglomerative hierarchical clustering algorithm to obtain a sensitive shielding region;

[0160] A sensitivity factor calculation module, configured to calculate, based on the interference degree distance sequence and the sensitive shielding area, a sensitive shielding factor corresponding to the sensitive shielding area;

[0161] A shielding value calculation module, configured to calculate the shielding value of the wire according to the interference degree distance sequence and the sensitive shielding factor;

[0162] The performance determination module is configured to determine that the shielding performance of the wire does not meet the requirements when the shielding value of the wire is less than a preset wire shielding performance threshold; and to determine that the shielding performance of the wire meets the requirements when the shielding value of the wire is greater than or equal to the preset wire shielding performance threshold.

[0163] Preferably, the data acquisition module is specifically used to collect electromagnetic interference source data and wire structure data.

[0164] Preferably, the matrix construction module is specifically used to perform a matrix construction operation according to the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix, including:

[0165] The matrix construction operation is performed according to the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix, including:

[0166] Performing a vector construction operation on the electromagnetic interference source data to obtain a first signal vector, a second signal vector, and a third signal vector;

[0167] The first signal vector, the second signal vector and the third signal vector are combined to obtain a magnetic interference source characteristic matrix.

[0168] Preferably, the impact factor extraction module is specifically used to perform a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor, including:

[0169] Performing a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor includes:

[0170] Performing a non-negative matrix decomposition operation on the characteristic matrix of the magnetic interference source to obtain a basis matrix;

[0171] Extracting a first column value of the basis matrix, and determining the first column value as a first energy impact factor;

[0172] A value of the base matrix divided by the value of the first column is extracted, and the value divided by the value of the first column is determined as a second energy impact factor.

[0173] Preferably, the initial sequence module is specifically configured to perform an interference parameter construction operation according to the first energy impact factor, the second energy impact factor and the electromagnetic interference source data to obtain an initial interference degree sequence.

[0174] Preferably, the distance sequence module is specifically configured to perform a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence;

[0175] The performing a sequence updating operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence includes:

[0176] Performing a difference calculation operation based on the initial interference degree sequence and the first energy impact factor to obtain a first updated sequence;

[0177] Extracting values ​​greater than a preset update threshold from the first update sequence, and constructing a second update sequence from the values ​​greater than the preset update threshold;

[0178] The second update sequence is arranged in ascending order to obtain an interference degree distance sequence.

[0179] Preferably, the region extraction module is specifically configured to perform a cluster region extraction operation based on the wire structure data and an agglomerative hierarchical clustering algorithm to obtain sensitive shielding regions, including:

[0180] The method of performing a clustering region extraction operation based on the wire structure data and agglomerative hierarchical clustering algorithm to obtain sensitive shielding regions includes:

[0181] Standardizing the wire structure data to obtain standardized wire structure data;

[0182] Performing a similarity calculation operation on the standardized wire structure data to obtain data similarity;

[0183] Based on an agglomerative hierarchical clustering algorithm and according to the data similarity, cluster analysis is performed on the standardized wire structure data to obtain sensitive shielding areas.

[0184] Preferably, the sensitivity factor calculation module is specifically configured to calculate, based on the interference degree distance sequence and the sensitive shielding area, to obtain a sensitive shielding factor corresponding to the sensitive shielding area, including:

[0185] The calculation formula of the sensitive shielding factor is:

[0186]

[0187] Where r is the sensitive shielding factor; n is the number of sensitive shielding areas; Fi is the i-th interference degree distance sequence value of the sensitive shielding area; CV(F) is the coefficient of variation of the interference degree sequence.

[0188] Preferably, the shielding value calculation module is specifically configured to calculate, based on the interference degree distance sequence and the sensitive shielding factor, to obtain the shielding value of the wire, including:

[0189] The calculation formula of the wire shielding value is:

[0190]

[0191] Where r is the sensitive shielding factor; n is the number of sensitive shielding areas; F i is the i-th interference distance sequence value of the sensitive shielding area; f is the shielding value of the wire.

[0192] Preferably, the performance judgment module is specifically used to determine that the shielding performance of the wire does not meet the requirements when the wire shielding value is less than a preset wire shielding performance threshold; when the wire shielding value is greater than or equal to the preset wire shielding performance threshold, it is used to determine that the shielding performance of the wire meets the requirements.

[0193] It should be noted that the wire quality detection device based on wire shielding performance provided in an embodiment of the present invention is used to execute all the process steps of the wire quality detection method based on wire shielding performance in the above embodiment. The working principles and beneficial effects of the two correspond one to one, so they will not be repeated here.

[0194] An embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a wire quality detection program based on wire shielding performance. When the processor executes the computer program, the steps of the above-mentioned wire quality detection method based on wire shielding performance are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are realized, such as the data acquisition module.

[0195] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0196] The electronic device may be a computing device such as a desktop computer, notebook, PDA, or smart tablet. The electronic device may include, but is not limited to, a processor and memory. Those skilled in the art will appreciate that the aforementioned components are merely examples of electronic devices and do not constitute a limitation of the electronic device. The electronic device may include more or fewer components than those described above, or a combination of certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, and the like.

[0197] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, connecting various parts of the entire electronic device using various interfaces and lines.

[0198] The memory can be used to store the computer programs and / or modules, and the processor realizes various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created based on the use of the mobile phone (such as audio data, a phone book, etc.). In addition, the memory can include a high-speed random access memory and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0199] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by a computer program to instruct the relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of each of the above-mentioned method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0200] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement the present invention without inventive effort.

[0201] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A wire quality detection method based on wire shielding performance, characterized in that include: Collect electromagnetic interference source data and wire structure data; Performing a matrix construction operation according to the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix; Performing a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor; performing an interference parameter construction operation according to the first energy impact factor, the second energy impact factor, and the electromagnetic interference source data to obtain an initial interference degree sequence; performing a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence; According to the wire structure data, a clustering region extraction operation is performed based on an agglomerative hierarchical clustering algorithm to obtain a sensitive shielding region; Calculating according to the interference degree distance sequence and the sensitive shielding area to obtain a sensitive shielding factor corresponding to the sensitive shielding area; Calculating according to the interference degree distance sequence and the sensitive shielding factor to obtain a wire shielding value; When the wire shielding value is less than a preset wire shielding performance threshold, it is determined that the shielding performance of the wire does not meet the requirements; When the wire shielding value is greater than or equal to a preset wire shielding performance threshold, it is determined that the shielding performance of the wire meets the requirements; The process of performing a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor includes: Performing a non-negative matrix decomposition operation on the characteristic matrix of the magnetic interference source to obtain a basis matrix; Extracting a first column value of the basis matrix, and determining the first column value as a first energy impact factor; Extracting a value of the basis matrix excluding the value of the first column, and determining the value excluding the value of the first column as a second energy impact factor; The calculation formula of the sensitive shielding factor is: Where, is the sensitive shielding factor; is the number of sensitive shielding areas; For sensitive shielding areas Interference distance sequence value; is the coefficient of variation of the interference sequence; The calculation formula of the wire shielding value is: Where, is the sensitive shielding factor; is the number of sensitive shielding areas; For sensitive shielding areas Interference distance sequence value; is the shielding value of the wire.

2. The wire quality detection method based on wire shielding performance according to claim 1, characterized in that: The matrix construction operation is performed according to the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix, including: Performing a vector construction operation on the electromagnetic interference source data to obtain a first signal vector, a second signal vector, and a third signal vector; The first signal vector, the second signal vector and the third signal vector are combined to obtain a magnetic interference source characteristic matrix.

3. The wire quality detection method based on wire shielding performance according to claim 1, characterized in that: The performing a sequence updating operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence includes: Performing a difference calculation operation based on the initial interference degree sequence and the first energy impact factor to obtain a first updated sequence; Extracting values ​​greater than a preset update threshold from the first update sequence, and constructing a second update sequence from the values ​​greater than the preset update threshold; The second update sequence is arranged in ascending order to obtain an interference degree distance sequence.

4. The wire quality detection method based on wire shielding performance according to claim 1, characterized in that: The method of performing a clustering region extraction operation based on the wire structure data and agglomerative hierarchical clustering algorithm to obtain sensitive shielding regions includes: Standardizing the wire structure data to obtain standardized wire structure data; Performing a similarity calculation operation on the standardized wire structure data to obtain data similarity; Based on an agglomerative hierarchical clustering algorithm and according to the data similarity, cluster analysis is performed on the standardized wire structure data to obtain sensitive shielding areas.

5. A wire quality detection device based on wire shielding performance, characterized in that: The method for detecting wire quality based on wire shielding performance according to any one of claims 1 to 4 comprises: Data acquisition module, used to collect electromagnetic interference source data and wire structure data; A matrix construction module is used to perform a matrix construction operation based on the electromagnetic interference source data to obtain a magnetic interference source characteristic matrix; An impact factor extraction module is used to perform a matrix numerical extraction operation on the magnetic interference source characteristic matrix to obtain a first energy impact factor and a second energy impact factor; an initial sequence module, configured to perform an interference parameter construction operation according to the first energy impact factor, the second energy impact factor, and the electromagnetic interference source data to obtain an initial interference degree sequence; a distance sequence module, configured to perform a sequence update operation on the initial interference degree sequence according to the first energy impact factor to obtain an interference degree distance sequence; A region extraction module is used to perform a cluster region extraction operation based on the wire structure data and an agglomerative hierarchical clustering algorithm to obtain a sensitive shielding region; A sensitivity factor calculation module, configured to calculate, based on the interference degree distance sequence and the sensitive shielding area, a sensitive shielding factor corresponding to the sensitive shielding area; A shielding value calculation module, configured to calculate the shielding value of the wire according to the interference degree distance sequence and the sensitive shielding factor; The performance determination module is configured to determine that the shielding performance of the wire does not meet the requirements when the shielding value of the wire is less than a preset wire shielding performance threshold; and to determine that the shielding performance of the wire meets the requirements when the shielding value of the wire is greater than or equal to the preset wire shielding performance threshold.

6. An electronic device, characterized in that: The invention comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for detecting wire quality based on wire shielding performance according to any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the wire quality detection method based on wire shielding performance according to any one of claims 1 to 4.

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