A method and system for controlling the risk of turn-to-turn insulation breakdown of a 10kV explosion-proof motor stator winding

Abstract

The application provides a 10kV explosion-proof motor stator winding turn-to-turn insulation breakdown risk control method and system, relates to the motor manufacturing technical field, and the method comprises the following steps: by analyzing the creeping breakdown phenomenon appearing in batch production, it is determined that there is a turn-to-turn insulation defect, and the breakdown point is concentrated at the first and last turns of the lead end, and the breakdown point position characteristics are obtained; based on the breakdown point position characteristics, the main reason for the weak insulation is analyzed and obtained; based on the main reason for the weak insulation, the single-sided polyester film reinforcing mica tape is selected as the turn-to-turn insulation material; the process verification is carried out on the turn-to-turn insulation material, and the insulation material structure characteristic parameters are obtained. Through the whole process control of defect diagnosis, material selection, process optimization, insulation reinforcement and performance verification driven by data, the reliability and consistency of the 10kV explosion-proof motor stator winding turn-to-turn insulation are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of motor manufacturing, in particular to a 10kV explosion-proof motor stator winding turn-to-turn insulation breakdown risk control method and system. BACKGROUND

[0002] In the field of 10kV explosion-proof motor manufacturing, the reliability of the stator winding turn-to-turn insulation is a key factor to ensure the safe operation of the motor in a flammable and explosive environment. Currently, the industry generally uses a three-layer polyester film reinforced mica tape flat package structure as the turn-to-turn insulation scheme, and performs turn-to-turn withstand voltage test verification according to IEC60034-15 and other standards. However, during mass production, systematic data processing defects have gradually emerged, which may lead to unsatisfactory insulation breakdown risk control effect, seriously affecting product qualification rate and operation reliability.

[0003] The main problems are as follows: First, in terms of insulation defect diagnosis, there is a lack of systematic data analysis capability for batch creepage breakdown phenomena that occur during production; fault data collection is incomplete, breakdown point positioning data and waveform feature data are disconnected, defect analysis relies too much on manual experience, and an effective fault feature correlation model cannot be established, resulting in low accuracy of identifying the root cause of insulation weakness.

[0004] Secondly, in the insulation performance verification stage, an effective data processing closed loop has not been formed, and the withstand voltage test data is only used for simple pass or fail judgment, lacking deep analysis and trend prediction of insulation state data; the data correlation between the verification results and the previous process parameters is broken, a complete quality traceability chain cannot be established, and continuous improvement is difficult to achieve. SUMMARY

[0005] The technical problem to be solved by the present application is to provide a 10kV explosion-proof motor stator winding turn-to-turn insulation breakdown risk control method and system, which improves the reliability and consistency of the 10kV explosion-proof motor stator winding turn-to-turn insulation through data-driven defect diagnosis, material selection, process optimization, insulation strengthening and performance verification whole-process control.

[0006] To solve the above technical problems, the technical scheme of the present application is as follows:

[0007] In a first aspect, a 10kV explosion-proof motor stator winding turn-to-turn insulation breakdown risk control method is provided, the method comprising:

[0008] By analyzing the creepage breakdown phenomenon that occurs in batch production, it is determined that there is a turn-to-turn insulation defect, and the breakdown point is located in the first and last turns of the lead end, and the breakdown point position feature is obtained; based on the breakdown point position feature, the main reason for insulation weakness is analyzed;

[0009] Based on the main reason for insulation weakness, a single-sided polyester film reinforced mica tape is selected as the inter-turn insulation material; the inter-turn insulation material is subjected to process verification to obtain the structural characteristic parameters of the insulation material;

[0010] Based on the structural characteristic parameters of the insulation material, initial coating parameters of the semi-lamination process are determined; based on the initial coating parameters, the semi-lamination coating process is performed to form an initial coating insulation layer; for the initial coating insulation layer, insulation coating state parameters are collected in real time through online monitoring points arranged in the key coating area; the insulation coating state parameters are evaluated in different zones to obtain process optimization instructions; based on the process optimization instructions, the coating tension and travel speed of the semi-lamination operation are adjusted in real time to form a semi-lamination insulation structure with optimized coating uniformity;

[0011] Based on the semi-lamination insulation structure with optimized coating uniformity, a vacuum pressure impregnation process is performed to form a dense overall insulation protective layer;

[0012] Based on the dense overall insulation protective layer, a standard specified anti-explosion motor inter-turn withstand voltage test is applied to the stator winding for verification to obtain an insulation performance verification conclusion; based on the insulation performance verification conclusion, it is determined that the inter-turn insulation breakdown risk is effectively controlled.

[0013] In the second aspect, a 10kV anti-explosion motor stator winding inter-turn insulation breakdown risk control system includes:

[0014] The analysis module is configured to determine the existence of inter-turn insulation defects and locate the breakdown point concentration at the first and last turns of the lead end by analyzing the creepage breakdown phenomenon occurring in batch production, and obtain the breakdown point position characteristics; based on the breakdown point position characteristics, the main reason for insulation weakness is analyzed and obtained;

[0015] The process verification module is configured to select a single-sided polyester film reinforced mica tape as the inter-turn insulation material based on the main reason for insulation weakness; the inter-turn insulation material is subjected to process verification to obtain the structural characteristic parameters of the insulation material;

[0016] The optimization module is configured to determine the initial coating parameters of the semi-lamination process based on the structural characteristic parameters of the insulation material; based on the initial coating parameters, the semi-lamination coating process is performed to form an initial coating insulation layer; for the initial coating insulation layer, insulation coating state parameters are collected in real time through online monitoring points arranged in the key coating area; the insulation coating state parameters are evaluated in different zones to obtain process optimization instructions; based on the process optimization instructions, the coating tension and travel speed of the semi-lamination operation are adjusted in real time to form a semi-lamination insulation structure with optimized coating uniformity;

[0017] The processing module is configured to perform a vacuum pressure impregnation process based on the semi-lamination insulation structure with optimized coating uniformity to form a dense overall insulation protective layer;

[0018] The judgment module is used to verify the insulation performance by applying the standard-specified inter-turn withstand voltage test voltage of the explosion-proof motor to the stator winding based on the dense integral insulation protective layer, and to obtain the insulation performance verification conclusion. Based on the insulation performance verification conclusion, it is determined that the risk of inter-turn insulation breakdown has been effectively controlled.

[0019] Thirdly, a computing device includes:

[0020] One or more processors;

[0021] A storage device for storing one or more programs that, when executed by one or more processors, cause the one or more processors to implement the method.

[0022] Fourthly, a computer-readable storage medium storing a program that, when executed by a processor, implements the method.

[0023] The above-described solution of the present invention has at least the following beneficial effects:

[0024] By analyzing batch creepage breakdown data, inter-turn insulation defects were identified; breakdown points were located to form location feature data, which was used to analyze the main causes of insulation weakness; data-driven diagnostic analysis provided clear direction for subsequent material selection and process optimization; suitable materials were selected based on the data on the causes of insulation weakness; material compatibility data was collected through process verification to extract structured structural characteristic parameters; data-supported material selection and verification ensured that material characteristics matched insulation improvement needs; initial coating parameters were determined based on material characteristic parameters; real-time data on the coating status of key areas was collected, and optimization instructions were generated through zonal evaluation; data-driven adjustment of process parameters improved the uniformity of insulation layer coating, forming a high-quality semi-overlapping structure; combined with the optimized semi-overlapping structure data, vacuum pressure impregnation process parameters were controlled; data monitoring ensured full penetration and curing of the varnish, forming a dense overall insulation protective layer and enhancing insulation reliability; test voltage was applied according to standard parameters, and insulation status data was collected in real time; verification conclusions were drawn through waveform feature data analysis, and a traceability chain was established by linking previous process parameters; data-supported performance verification determined the effectiveness of breakdown risk control, providing a quality basis for mass production. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating a method for controlling the risk of inter-turn insulation breakdown in the stator winding of a 10kV explosion-proof motor, provided by an embodiment of the present invention.

[0026] Figure 2 This is a schematic diagram of a 10kV explosion-proof motor stator winding inter-turn insulation breakdown risk control system provided by an embodiment of the present invention. Detailed Implementation

[0027] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0028] like Figure 1 As shown, an embodiment of the present invention proposes a method for controlling the risk of inter-turn insulation breakdown in the stator winding of a 10kV explosion-proof motor. The method includes the following steps:

[0029] Step 100: By analyzing the creepage breakdown phenomenon that occurs in mass production, it is determined that there is an inter-turn insulation defect, and the breakdown points are concentrated at the first and last turns of the lead wire, thus obtaining the location characteristics of the breakdown points; based on the location characteristics of the breakdown points, the main reasons for the weak insulation are analyzed.

[0030] Step 200: Based on the main reasons for weak insulation, single-sided polyester film reinforced mica tape is selected as the inter-turn insulation material; the process of the inter-turn insulation material is verified to obtain the structural characteristic parameters of the insulation material;

[0031] Step 300: Based on the structural characteristic parameters of the insulating material, determine the initial wrapping parameters for the semi-overlapping process; execute the semi-overlapping wrapping process based on the initial wrapping parameters to form the initial wrapping insulation layer; collect the insulation wrapping status parameters of the initial wrapping insulation layer in real time through online monitoring points deployed in key wrapping areas; evaluate the insulation wrapping status parameters by region to obtain process optimization instructions; based on the process optimization instructions, adjust the wrapping tension and travel speed of the semi-overlapping operation in real time to form a semi-overlapping insulation structure with optimized wrapping uniformity.

[0032] Step 400: Based on the semi-overlapping insulation structure with optimized coverage uniformity, a vacuum pressure impregnation process is performed to form a dense integral insulation protective layer.

[0033] Step 500: Based on the dense integral insulation protective layer, the standard-specified inter-turn withstand voltage of the explosion-proof motor is applied to the stator winding for verification, and the insulation performance verification conclusion is obtained; based on the insulation performance verification conclusion, it is determined that the risk of inter-turn insulation breakdown is effectively controlled.

[0034] In this embodiment of the invention, the location characteristics of the breakdown points of batch creepage breakdown are located. By analyzing the breakdown phenomena and location data, the main causes of insulation weakness are determined, providing data support and clear direction for subsequent insulation structure optimization. A suitable single-sided polyester film reinforced mica tape is selected as the insulation material. The structural characteristic parameters of the insulation material are obtained through data acquisition and analysis during the process verification to ensure that the selected material meets the basic performance requirements of inter-turn insulation of the explosion-proof motor. Based on the structural characteristic parameters of the material, reasonable initial covering parameters are determined. The covering state parameters of key areas are collected in real time through online monitoring points. Combined with the data processing method of zonal evaluation, process optimization instructions are generated to adjust the covering tension and travel speed in real time, thereby improving the covering uniformity of the semi-overlapping insulation structure. A dense overall insulation protective layer is formed through vacuum pressure impregnation. Combined with the previously optimized covering structure, the integrity and density of the insulation layer are further improved, reducing internal voids and enhancing the stability of the insulation structure. The insulation performance is verified using standard test voltage. The test data yields objective insulation performance verification conclusions, directly determining whether the risk of inter-turn insulation breakdown has been effectively controlled, ensuring the insulation reliability of the stator winding of the explosion-proof motor.

[0035] In a preferred embodiment of the present invention, step 100 above, by analyzing the creepage breakdown phenomenon occurring in mass production, determines the existence of inter-turn insulation defects, and locates the breakdown points concentrated at the first and last turns of the lead wire, obtaining the breakdown point location characteristics; based on the breakdown point location characteristics, analyzes the main causes of weak insulation, including:

[0036] Step 101: Collect faulty coils exhibiting creepage breakdown during mass production, establish a fault sample set, and record the breakdown location distribution characteristics of each fault sample. Based on the fault sample set and its breakdown location distribution characteristics, select representative faulty coils for high-voltage pulse tests to obtain their inter-turn withstand voltage failure waveform data. Specifically, in the mass production scenario of 10kV explosion-proof motor stator winding coils, firstly, systematic data collection is carried out for creepage breakdown faults detected during the production process. When the quality inspection stage of the production line discovers that the coil exhibits creepage breakdown, all coils with this fault are promptly collected and included as fault samples in the preset sample management system to construct a complete fault sample set. During this process, the breakdown location distribution characteristics of each fault sample are recorded one by one through a combination of visual inspection equipment and manual verification. Specifically, this includes the axial region of the coil where the breakdown point is located, the radial level, and the specific physical coordinate information. Among them, the axial region of the coil includes lead end, middle, and tail end, and the radial level includes surface layer and inner layer, ensuring that the location data of each fault sample is traceable.

[0037] Furthermore, statistical analysis is performed based on the breakdown location distribution characteristics of the fault sample set to screen out representative faulty coils. Specifically, samples with breakdown locations consistent with the overall distribution trend and typical fault behaviors are prioritized. Among these, fault behaviors such as creepage length and breakdown hole size are typically selected. Selecting 30% to 50% of the typical samples in the sample set is usually sufficient to meet the requirements of subsequent tests. Subsequently, according to the test conditions, a high-voltage pulse withstand voltage test is performed on the selected representative faulty coils. During the test, a waveform acquisition device is simultaneously activated to record the inter-turn withstand voltage failure waveform data of the coil in the withstand voltage failure process in real time, providing a complete waveform data source for subsequent defect analysis.

[0038] Step 102 involves performing time-frequency feature analysis on the failed waveform data, extracting its characteristic parameters, and comparing it with the standard normal waveform to identify differences in characteristic parameters. Based on these differences in characteristic parameters, combined with the breakdown location distribution characteristics, a comprehensive analysis confirms the existence of inter-turn insulation defects. Specifically, after obtaining the inter-turn withstand voltage failure waveform data obtained in Step 101, the waveform data is first processed using time-frequency feature analysis. Specifically, the failed waveform data is decomposed using signal processing methods to extract characteristic parameters that reflect the insulation state. These characteristic parameters include, but are not limited to, the peak voltage of the waveform, wavefront time, oscillation frequency bandwidth, and waveform attenuation rate. At the same time, the normal inter-turn withstand voltage waveform data of a qualified stator winding coil of a 10kV explosion-proof motor of the same model is obtained in advance and used as the standard normal waveform. The same type of characteristic parameters are extracted as the standard parameter benchmark.

[0039] Furthermore, the characteristic parameters of the failed waveform are compared one by one with those of the standard normal waveform to identify the differences between them. For example, the wavefront time of the failed waveform may be shorter than that of the standard waveform, the peak voltage may be lower than that of the standard waveform, and the oscillation frequency bandwidth may be wider than that of the standard waveform. Based on this, a comprehensive analysis is carried out in conjunction with the breakdown location distribution characteristics of the fault samples recorded in step 101. If the differences in characteristic parameters are concentrated in a certain area where the insulation withstand capability is reduced, and this area coincides with the concentrated area of ​​the breakdown location distribution, then it can be confirmed that there is an inter-turn insulation defect in the stator winding coil of the 10kV explosion-proof motor. Through this dual analysis method of waveform characteristic parameters and location distribution characteristics, the correlation between fault characteristics and insulation defects is established, improving the objectivity and accuracy of insulation defect confirmation.

[0040] Step 103: Based on the inter-turn insulation defect, the breakdown points are concentrated at the first and last turns of the lead wire, obtaining the location characteristics of the breakdown points. Specifically, this includes: based on the confirmation in step 102 that there is an inter-turn insulation defect in the stator winding coil of the 10kV explosion-proof motor, firstly, the coil winding geometric boundary extraction algorithm is executed to determine the physical boundary range of each structural partition of the coil, providing a geometric benchmark for determining the area attribution of the breakdown point; the specific calculation process is as follows: firstly, the physical dimension parameters of the stator coil of this model of 10kV explosion-proof motor are obtained. Based on the specification of the electromagnetic wire used in the stator coil being 1.18mm × 5.6mm, combined with the coil forming process parameters, the axial length L = 350mm and the radial thickness D = 5.6mm of a single-turn coil are determined, i.e., the radial dimension of the electromagnetic wire. At the same time, the start and end range of the lead wire end is determined as the axial length of the coil. The coil is then divided into four sections based on its structure: the first turn section at the lead end, the last turn section at the lead end, the middle turn section, and the tail turn section. The axial coordinate range of the first turn section is [0, 150] mm, and the radial coordinate range is [0, D] mm. The axial coordinate range of the last turn section is [L-150, L] mm, and the radial coordinate range is [0, D] mm. The axial coordinate range of the middle turn section is [150, L-150] mm, and the radial coordinate range is [0, D] mm. The axial coordinate range of the tail turn section is the same as that of the last turn section. Since the tail end and lead end of this coil are symmetrical, the geometric boundaries of each structural section of the coil are extracted through the above coordinate range calculation, ensuring that the physical range of each section can be quantitatively defined.

[0041] Next, for each recorded fault sample, the physical coordinates of the breakdown point are denoted as (x... k y k ), where x k Let y be the axial coordinate of the penetration point. k Let x be the radial coordinate of the breakdown point, k be the fault sample number (k=1, 2, ..., n), and n be the total number of fault samples. A spatial region membership determination algorithm is executed to accurately determine the structural partition to which the breakdown point belongs. The specific calculation process is as follows: First, a membership function is set for each structural partition. A Gaussian membership function is used to quantify the correlation between the breakdown point and the partition. The expression for the Gaussian membership function is μz(x...). k y k )=exp[-((x k -x z ) 2 +(y k -y z ) 2 ) / (2σ 2]], where μz is the membership degree of the breakdown point to the z-th partition, z=1 corresponds to the first turn region of the lead end, z=2 corresponds to the last turn region of the lead end, z=3 corresponds to the middle turn region of the coil, z=4 corresponds to the tail turn region of the coil, (x z y z Let be the center coordinates of the z-th partition, and σ be the width parameter of the membership function, which is 1 / 4 of the axial length of the partition, i.e., σ = 150 / 4 = 37.5 mm, to ensure a smooth transition of membership near the partition boundary; then calculate the center coordinates of each partition, where the center coordinates of the first turn area of ​​the lead end are (x1, y1) = (75, 2.8) mm, i.e., axial midpoint 75 mm, radial midpoint 2.8 mm; the center coordinates of the last turn area of ​​the lead end are (x2, y2) = (275, 2.8) mm, i.e., axial midpoint L - 75 = 275 mm, radial midpoint 2.8 mm; the center coordinates of the middle turn area of ​​the coil are (x3, y3) = (175, 2.8) mm, i.e., axial midpoint 175 mm, radial midpoint 2.8 mm; and the center coordinates of the tail turn area of ​​the coil are (x4, y4) = (275, 2.8) mm, consistent with the last turn area of ​​the lead end; then calculate the coordinates of each breakdown point (x k y k Substitute the membership functions of the four partitions respectively to calculate the four membership values ​​μ1, μ2, μ3, and μ4. Take the partition corresponding to the maximum membership value as the partition to which the breakdown point belongs. For example, if μ1 is greater than μ2, μ1 is greater than μ3, and μ1 is greater than μ4, then the breakdown point is determined to belong to the lead end first turn area. This process completes the quantitative determination of the region affiliation of all breakdown points.

[0042] Subsequently, based on the aforementioned regional attribution determination results, in-depth statistical analysis was conducted on the breakdown location data of all fault samples. First, the number of breakdown samples in each region was counted, specifically the number of fault samples belonging to the lead end first turn region, lead end last turn region, coil middle turn region, and coil tail turn region, denoted as N1, N2, N3, and N4 respectively. Then, the proportion of breakdown samples in each region was calculated using the formula R. z =N z / (N1+N2+N3+N4)×100%, where z=1, 2, 3, 4; During the statistical process, abnormal breakdown data caused by operational errors need to be excluded. The specific exclusion criteria are as follows: if the maximum membership degree of a breakdown point is less than 0.5, that is, the breakdown point is far from the center of all partitions and does not meet the characteristics of normal breakdown position, or the test record corresponding to the breakdown point shows poor electrode contact, such as the abnormal wiring record of the high voltage pulse test in step 101, then the sample is judged as abnormal data and removed.

[0043] The above statistical calculations revealed that, after removing abnormal data, the proportion of breakdown samples N1 and N2 belonging to the first and last turns of the lead wire end in the fault sample set exceeded 90% of the total valid samples, while the proportion of breakdown samples N3 and N4 belonging to the middle and tail turns of the coil was less than 10%. Moreover, this statistical result was consistent across multiple batches of fault sample sets. Based on this quantitative statistical result, it was determined that the breakdown point location characteristic of the stator winding coil of the 10kV explosion-proof motor was that the breakdown points were concentrated in the first and last turns of the lead wire end, thus completing the location of the breakdown point location characteristic.

[0044] Step 104: Based on the location characteristics of the breakdown point, identify the weak insulation area at the first and last turns of the lead wire end; for the weak insulation area, analyze and determine the key factors leading to the decline in insulation performance; based on the key factors, confirm the main causes of the weak insulation, including the soft texture of the small-gauge copper flat wire, the loose wrapping of the flat insulation structure, and mechanical deformation at the end, specifically including: based on the location characteristic that the breakdown point is concentrated in the first and last turns area of ​​the lead wire end, firstly define the first and last turns area of ​​the lead wire end as the weak insulation area of ​​the stator winding coil of the 10kV explosion-proof motor; then, conduct a key factor analysis for this weak insulation area: on the one hand, the small-gauge copper flat wire used in this area, specifically 1.18mm × Physical property testing was conducted on the 5.6mm diameter wire. Measuring its hardness and toughness parameters using mechanical testing equipment revealed that this specification of copper flat wire is softer than larger gauge copper flat wire, making it prone to significant positional shifts during insulation wrapping due to the movement of the winding head. Furthermore, microscopic examination of the flat-wrapped insulation structure in this weak area—specifically, the three-layer polyester film-reinforced mica tape flat-wrapped structure—revealed micro-gaps in the insulation layer caused by the copper flat wire's movement, resulting in insufficient wrapping tightness. Simultaneously, tracing the coil end forming process revealed mechanical deformation during bending and fixing operations, with more pronounced deformation in the first and last turn areas.

[0045] Based on the key factors identified in the above analysis, the softness of the small-gauge copper flat wire, the loose wrapping of the flat insulation structure, and the mechanical deformation at the ends were all factors that ultimately led to a decrease in the insulation performance of the weak insulation areas at the beginning and end of the lead wire ends. This identified the main cause of the insulation weakness and provided targeted improvement directions for subsequent insulation material selection and process optimization.

[0046] In this embodiment of the invention, a fault sample set is established by collecting faulty coils that have experienced creepage breakdown during mass production. The breakdown location distribution characteristics of each fault sample are recorded. Representative faulty coils are selected for high-voltage pulse tests to obtain inter-turn withstand voltage failure waveform data. By constructing the sample set and collecting waveform data through the system, comprehensive and structured data support is provided for subsequent insulation defect analysis and cause localization, avoiding analytical biases caused by fragmented data. Time-frequency feature analysis is performed on the failure waveform data to extract feature parameters. The extracted feature parameters are compared with standard normal waveforms to identify parameter differences. Combined with the breakdown location distribution characteristics, a comprehensive analysis is conducted to confirm inter-turn insulation defects. Time-frequency analysis is used to achieve in-depth analysis of waveform data. Through comparative analysis, parameter differences are accurately captured, and then the location distribution data is fused to open... The method involves comprehensive judgment to improve the accuracy and reliability of insulation defect confirmation. Based on confirmed inter-turn insulation defects, the breakdown points are concentrated at the first and last turns of the lead wire, providing clear location characteristics. The analysis results of insulation defects are used to focus on breakdown location data, making the location characteristics of the breakdown points more precise and concrete. Weak insulation areas at the first and last turns of the lead wire are identified based on the location characteristics of the breakdown points. Key factors leading to decreased insulation performance are analyzed in these weak areas. Based on these key factors, the main causes of insulation weakness are identified, including the softness of small-gauge copper flat wire, loose wrapping of the flat-pack insulation structure, and mechanical deformation at the ends. By correlating the location characteristics of the breakdown points with relevant data on regional insulation performance, the analysis of key factors provides clear data direction for confirming the main causes of insulation weakness.

[0047] In a preferred embodiment of the present invention, step 200 above, based on the main cause of weak insulation, selects single-sided polyester film reinforced mica tape as the inter-turn insulation material; performs process verification on the inter-turn insulation material to obtain the structural characteristic parameters of the insulation material, including:

[0048] Step 201: Based on the main causes of the weak insulation, determine the material selection scheme, specifically including: First, break down and analyze the main causes of the weak insulation, and convert each cause into quantifiable and verifiable material selection indicators: For the problem that small-gauge copper flat wire is soft and easily fluctuates with the winding head when wrapping insulation, the material must have excellent flexibility to adapt to the fluctuation range of the copper flat wire and avoid insulation layer wrinkles or breaks during the wrapping process; For the problem of the flat insulation structure not being tightly wrapped, the material must have good adhesion to ensure that a continuous and gapless insulation layer is formed on the surface of the copper flat wire, reducing creepage paths; For the problem of end mechanical deformation, the material must have a certain resistance to deformation and insulation integrity maintenance ability, and can still maintain stable insulation performance after end bending, fixing and other forming operations.

[0049] Furthermore, performance test data of different insulating materials (such as polyester film, polyimide film, mica tape, etc.) are integrated, including flexibility test results, adhesion test records, and breakdown voltage data after deformation resistance. These data are then initially matched with the above selection indicators to eliminate material types that clearly do not meet the requirements. For example, polyimide film is not included in the candidates because it is prone to breakage when wrapped with small-gauge copper flat wire due to insufficient flexibility. Finally, a material selection scheme with high flexibility, high adhesion, and deformation resistance insulation stability as the core indicators is formed, providing a technical basis for subsequent material selection.

[0050] Step 202: According to the material selection scheme, single-sided polyester film reinforced mica tape is selected as the inter-turn insulation material. Specifically, this includes: First, comparing and verifying the selection indicators (high flexibility, high adhesion, deformation resistance and insulation stability) with the characteristics of single-sided polyester film reinforced mica tape one by one: In terms of flexibility, the mica tape uses polyester film as the reinforcing layer. In its bending performance test, after standard bending of a 1.18mm×5.6mm small gauge copper flat wire, the insulation layer has no obvious wrinkles or cracks, and is fully compatible with copper flat wire. Regarding the fluctuation characteristics of the line; in terms of adhesion, test data of single-sided polyester film reinforced mica tape with half-overlapping shows that the gap ratio of the insulation layer after wrapping is less than 3%, which is much lower than the gap ratio of the flat-wrapped structure, and can effectively solve the problem of loose wrapping; in terms of deformation resistance and insulation stability, the breakdown voltage test results of the mica tape after end deformation show that its average breakdown voltage is maintained above 8.24kV, which meets the withstand voltage requirements of 10kV explosion-proof motor inter-turn insulation, and can still maintain good insulation performance after end mechanical deformation.

[0051] Based on this, the performance data of other candidate materials (such as double-sided polyester film reinforced mica tape and pure mica tape) were further compared: although double-sided polyester film reinforced mica tape has high insulation strength, it lacks flexibility and is prone to gaps when wrapped with small-gauge copper flat wire; pure mica tape has poor adhesion and is prone to delamination after wrapping, neither of which meets the requirements of the selection scheme; based on the above comparison results, single-sided polyester film reinforced mica tape was finally selected as the inter-turn insulation material to ensure that the selected material is completely matched with the selection scheme.

[0052] Step 203 involves verifying the process of the inter-turn insulation material to obtain its process adaptability data. Specifically, this includes: First, using 1.18mm × 5.6mm small-gauge copper flat wire, multiple sets of insulation-coated samples are prepared. Each set of samples uses different coating process parameters, including coating tension, travel speed, and wrapping method. The wrapping method covers the flat wrapping mentioned in step 201 and the subsequently optimized half-overlap wrapping. Five parallel samples are prepared for each set to ensure data repeatability. Then, simulating the end-forming process in actual production, all samples undergo standard end bending to complete sample preparation. Finally, process adaptability tests are conducted on the prepared samples: one is the wrapping tightness test. The test involved three steps: First, examining the gap distribution of the insulation layer in each group of samples using a microscopic observation device, recording the location, number, and size of gaps under different wrapping parameters to form data on wrapping tightness. Second, testing the deformation resistance insulation performance by conducting inter-turn withstand voltage tests on the samples after end bending, recording the breakdown voltage and breakdown location of each group of samples to form data on deformation resistance insulation performance. Third, testing the process adaptability by recording the wrapping efficiency and insulation layer thickness uniformity of the mica tape under different wrapping tensions and travel speeds to form data on process efficiency and uniformity. The wrapping efficiency is the wrapping length completed per unit time, and the insulation layer thickness uniformity is measured at multiple points using a thickness measuring instrument and the thickness deviation is recorded.

[0053] Finally, abnormal data generated during the above testing process are removed, such as breakdowns caused by sample preparation errors or extreme thickness values ​​caused by measurement equipment errors. The effective data are integrated to form a process adaptability dataset for single-sided polyester film reinforced mica tape, ensuring that the data can truly reflect the material's performance in actual processes.

[0054] Step 204: Based on the process adaptability data, obtain the structural characteristic parameters of the insulating material. Specifically, this includes: First, classifying and sorting the process adaptability data into three categories: wrapping characteristic data, insulation strength data, and process adaptation data, to ensure that the data classification is consistent with the evaluation dimensions of the insulation structure performance. Among them, the wrapping characteristic data is the wrapping tightness and thickness uniformity, the insulation strength data is the breakdown voltage after deformation resistance, and the process adaptation data is the wrapping efficiency corresponding to the wrapping tension and the travel speed.

[0055] Furthermore, targeted analysis was conducted for each type of data to extract characteristic parameters: Regarding wrapping characteristic data, the average gap ratio and maximum thickness deviation of the insulation layer under different wrapping parameters were statistically analyzed. Materials with a gap ratio less than or equal to 3% and a thickness deviation less than or equal to 0.05 mm were defined as having excellent wrapping performance, and the average thickness and gap distribution density of the insulation layer under this condition were extracted as wrapping structural characteristic parameters. Regarding insulation strength data, the average and minimum breakdown voltage of the specimens after deformation were calculated, and the average breakdown voltage and breakdown voltage fluctuation range were extracted as insulation strength characteristic parameters. Regarding process adaptation data, wrapping tension ranges (e.g., 20 to 30 N) and travel speed ranges (e.g., 0.5 to 0.8 m / s) that simultaneously meet the requirements of wrapping characteristics and insulation strength, with a wrapping efficiency greater than or equal to 1 m / min, were selected, and the median value of these ranges was extracted as process adaptation characteristic parameters.

[0056] Subsequently, the extracted characteristic parameters are compared with the characteristic data of the optimal insulation structure to verify the rationality of the parameters and ensure that the parameters meet the insulation requirements of the 10kV explosion-proof motor. Finally, the verified wrapping structure characteristic parameters, insulation strength characteristic parameters, and process adaptation characteristic parameters are integrated to form a complete insulation material structure characteristic parameter system. The insulation material structure characteristic parameter system can not only directly provide data support for setting the initial parameters of the subsequent semi-overlapping process, but also correspond to the reasons for the previous insulation weakness. For example, the wrapping structure characteristic parameters can specifically solve the problem of loose wrapping, realizing data-driven process optimization.

[0057] In this embodiment of the invention, process verification is performed on the inter-turn insulation material to obtain process adaptability data. During the verification process, the system collects data on the wrapping tightness of the material under different wrapping tensions and travel speeds, as well as the insulation integrity data under the simulated end mechanical deformation scenario, to form a comprehensive process adaptability dataset. These data can intuitively reflect the performance of the material in the actual production process and provide real and reliable raw data support for the subsequent extraction of structural characteristic parameters.

[0058] In a preferred embodiment of the present invention, step 300 involves determining the initial covering parameters of the semi-overlapping process based on the structural characteristic parameters of the insulating material; executing the semi-overlapping process based on the initial covering parameters to form an initial covering insulation layer; collecting the insulation covering status parameters of the initial covering insulation layer in real time through online monitoring points deployed in key covering areas; evaluating the insulation covering status parameters by region to obtain process optimization instructions; and adjusting the covering tension and travel speed of the semi-overlapping operation in real time based on the process optimization instructions to form a semi-overlapping insulation structure with optimized covering uniformity, including:

[0059] Step 301 involves extracting the material thickness, flexibility, and tensile strength data from the structural characteristic parameters of the insulating material. Specifically, this includes: firstly, retrieving the structural characteristic parameter system of the insulating material and selecting three types of core data directly related to the initial parameter calculation of the semi-overlapping process: First, material thickness data, i.e., the single-sheet thickness of the single-sided polyester film reinforcing mica tape, typically 0.05 to 0.08 mm. This data directly determines the number of subsequent wrapping layers to meet the total thickness requirement of the inter-turn insulation; second, material flexibility data, based on the bending test results of the mica tape, such as no wrinkles or cracks in the insulation layer after standard bending, extracting quantitative indicators such as bending radius and insulation integrity after bending. This data is used to match the fluctuation characteristics of small-gauge copper flat wire (1.18 mm × 5.6 mm) to avoid insulation layer damage during wrapping; third, material tensile strength data, based on the material tensile test records, such as the breaking tensile force value, extracting its maximum withstand tensile force range to prevent excessive subsequent wrapping tension from causing material tearing.

[0060] Step 302: Calculate and determine the initial number of wrapping layers based on the material thickness data; calculate and determine the initial wrapping tension range based on the material flexibility data and the initial number of wrapping layers; combine the tensile strength data and the initial wrapping tension range, and determine the initial wrapping parameters for the semi-overlapping process through material structure coefficient correction. Specifically, this includes: first, calculating the initial number of wrapping layers. Based on the technical requirement that the inter-turn insulation thickness of a 10kV explosion-proof motor needs to reach 0.5mm, and combining the single sheet thickness of mica tape extracted in step 301 (e.g., 0.06mm), the initial number of wrapping layers is calculated by dividing the total insulation thickness by the single sheet material thickness and considering the overlap rate of the semi-overlapping process (which is typically 50%), e.g., 0.5mm ÷ (0.06mm × 50%) ≈ 17 layers; secondly... Determine the initial wrapping tension range based on the flexibility data extracted in step 301. A smaller bending radius indicates better flexibility. If the material has excellent flexibility, the upper limit of tension can be appropriately relaxed. At the same time, combine the tensile strength data, such as a maximum tensile strength of 30N, and initially set the initial tension range to 20 to 25N to avoid loose wrapping due to insufficient tension or material breakage due to excessive tension. Finally, correct the material structure coefficient by referring to the verification data of the same mica tape half-overlap wrapping process. For example, if the structure coefficient is 1.05, it corresponds to a 5% improvement in insulation integrity after wrapping. Fine-tune the initial tension range, such as 21 to 26N after correction. Finally, determine the complete initial wrapping parameters, including the initial number of wrapping layers, the initial tension range, and the half-overlap overlap rate, to ensure that the parameters meet the material characteristics.

[0061] Step 303: Based on the initial wrapping parameters of the semi-overlapping process, the wrapping equipment is controlled to complete the predetermined number of semi-overlapping wrapping layers to form a preliminary wrapping structure. Specifically, this includes: first, inputting the initial wrapping parameters (initial number of wrapping layers, semi-overlapping overlap rate) into the control system of the wrapping equipment to ensure that the equipment parameters are consistent with the calculation results; then, fixing the 1.18mm×5.6mm small wire gauge copper flat wire to the wire feeding mechanism of the equipment, and adjusting the tension of the copper flat wire to avoid deviation during the feeding process; after starting the wrapping equipment, controlling the equipment to wind in a semi-overlapping manner, while monitoring the number of wrapping layers in real time through the equipment's counting unit, and automatically stopping the wrapping when the calculated initial number of wrapping layers is reached; during the winding process, the wrapping state of the copper flat wire surface needs to be observed in real time. If mica tape wrinkles or deviations occur, the guiding mechanism of the equipment should be finely adjusted in time to ensure that the mica tape of the preliminary wrapping structure is neatly arranged and without obvious gaps, ultimately forming a preliminary wrapping structure that meets the requirements of the initial parameters, laying the structural foundation for subsequent tension stabilization and densification.

[0062] Step 304: Based on the initial wrapping tension range and the preliminary wrapping structure, adjust the wrapping tension control mechanism to maintain the wrapping process within this tension range and establish a stable wrapping tension. Specifically, this includes: first, installing a tension sensor at the wrapping mechanism of the wrapping equipment. This sensor needs to be linked to the equipment control system to collect tension data in real time during the wrapping process; then, starting the equipment to allow the preliminary wrapping structure to enter the tension adjustment stage, comparing the real-time collected tension data with the initial tension range determined in step 302, where the initial tension range is, for example, 21 to 26 N; if... If the tension value of the tape is lower than the lower limit of the range, such as 20N, the damping force at the wire feeding end is increased through the tension control mechanism to raise the tension to within the range. If the tension value is higher than the upper limit of the range, such as 27N, the damping force is reduced to lower the tension. During the adjustment process, the surface condition of the initial coating structure needs to be observed simultaneously. If the mica tape becomes loose (below the lower limit) or stretches (above the upper limit) after the tension is adjusted, the damping force is further fine-tuned until the tension data is stable within the initial range and the initial coating structure is normal. Finally, a stable coating tension is established through continuous tension monitoring and mechanism adjustment.

[0063] Step 305: Based on the stable wrapping tension, control the wrapping equipment to complete the insulation layer densification process at an optimized travel speed. Specifically, this includes: First, based on the wrapping efficiency data of similar copper flat wires (1.18mm × 5.6mm), initially set the travel speed of the wrapping equipment, such as 0.6m / min; After starting the densification process, the equipment drives the initial wrapping structure to travel at a uniform speed with a stable wrapping tension, while simultaneously applying appropriate pressure, such as 0.3MPa, to the mica tape through the equipment's pressure roller mechanism, so that the mica tape is tightly bonded to the surface of the copper flat wire. During the process, the density of the insulation layer needs to be observed through a visual monitoring unit. If the travel speed is too fast, resulting in insufficient adhesion of the mica tape and the appearance of small gaps, the travel speed should be reduced, such as to 0.5 m / min. If the speed is too slow, resulting in local accumulation of the mica tape and the appearance of bulges, the speed should be appropriately increased, such as to 0.65 m / min. Through the coordinated adjustment of speed and tension, it is ensured that the densification process can guarantee both the coating efficiency and the insulation layer to meet the predetermined tightness requirements, thus providing a guarantee for the subsequent formation of a qualified initial coating insulation layer.

[0064] Step 306 involves forming an initial insulation layer with a predetermined thickness and density on the surface of the copper flat wire through an insulation layer densification process. Specifically, this includes: after the densification process is completed, an insulation layer geometric contour detection algorithm is first activated. This algorithm needs to combine the flat structural characteristics of the small-gauge copper flat wire and the distribution of concentrated breakdown points. A three-dimensional contour scanning device is used to scan the entire insulation layer. The scanning range needs to completely cover all areas of the lead end, the first and last turns, the middle and the end of the copper flat wire. The scanning density is set to no less than 5 scanning points per square millimeter to ensure that no key parts such as corners and bends that are prone to uneven coverage are missed. During the scanning process, the three-dimensional coordinate data of each scanning point is collected in real time and integrated to form a complete insulation layer geometric contour model. This model can intuitively present the surface unevenness and overall shape of the insulation layer, avoiding the limitation of traditional multi-point measurement that can only cover local areas.

[0065] Based on the above geometric contour model, the actual thickness of the insulation layer is further calculated: the vertical distance from each scanning point in the contour model to the surface of the copper flat wire is taken as the insulation layer thickness value at the corresponding position. The thickness is divided into the first and last turn area, the middle area, and the end area of ​​the lead wire, and the average thickness, maximum thickness, and minimum thickness of each area are calculated to obtain the thickness deviation of each area. For example, the average thickness of the first turn area of ​​the lead wire is 0.51mm, the maximum thickness is 0.53mm, and the minimum thickness is 0.48mm, and the thickness deviation is 0.05mm. It is necessary to determine whether it meets the predetermined 0.5mm thickness standard and the requirement that the thickness deviation does not exceed 0.05mm. For key areas such as the first and last turns, it is necessary to further verify whether it meets the stricter local thickness deviation control requirements to ensure that there are no weak points in the insulation caused by local excessive thinness.

[0066] After thickness detection is completed, the interlayer bonding geometric gap algorithm is activated. Based on the aforementioned insulation layer geometric contour model, the bonding state inside and between layers of the insulation layer is further analyzed. The interlayer bonding geometric gap algorithm identifies the contour gap of adjacent mica tape bonding areas in the contour model and the bonding gap between the insulation layer and the copper flat wire surface. It extracts the three-dimensional coordinates and size data of all gaps and classifies the gaps into micro gaps, regular gaps, and excessive gaps according to their size. Micro gaps are less than 0.01 mm, regular gaps are 0.01 to 0.05 mm, and excessive gaps are greater than 0.05 mm. The number, distribution location, and cumulative volume of each type of gap are counted. Combined with the total volume data of the insulation layer, the gap ratio of the entire insulation layer and each zone is accurately calculated according to the gap ratio calculation logic. For example, by dividing the cumulative gap volume by the total volume of the insulation layer, the gap ratio of the middle zone is 2.8%, and the gap ratio of the first turn zone is 3.2%, thus realizing the quantitative calculation of the gap ratio.

[0067] Subsequently, if the average thickness of each zone reaches 0.5mm, and the thickness deviation of all zones does not exceed 0.05mm, while the overall gap ratio does not exceed 3%, then the insulation layer thickness and density are deemed to meet the requirements. If the thickness deviation or gap ratio of a certain zone exceeds the standard, such as a minimum thickness of 0.44mm and a deviation of 0.06mm in the end zone, or a gap ratio of 3.5% in the first turn zone, then the densification process is restarted. Based on the deviation area and degree detected by the algorithm, the process parameters are adjusted accordingly. For example, for the gap ratio exceeding the standard in the first turn zone, the travel speed can be further reduced from 0.5m / min to 0.45m / min, while the wrapping tension is finely adjusted to improve the interlayer adhesion of the mica tape, avoiding process waste caused by blind adjustments. After multiple tests and adjustments, until the geometric contour of the insulation layer meets the design requirements, and the thickness and deviation of each zone and the overall gap ratio meet the standards, the equipment operation is stopped. Finally, an initial wrapping insulation layer with a predetermined wrapping thickness and density is formed on the surface of a 1.18mm×5.6mm copper flat wire.

[0068] Step 307: For the initial insulation layer, online monitoring points deployed in key coverage areas are used to collect insulation coverage status parameters in real time. Specifically, this includes: first, determining the specific types of insulation coverage status parameters to be collected. These parameters are key quantitative indicators set for the core quality indicators and weak points of the initial insulation layer, specifically including four categories: First, insulation layer thickness, i.e., the vertical distance from the surface of the initial insulation layer to the copper flat wire substrate, directly reflecting whether the insulation layer meets the predetermined protection thickness requirements; second, surface flatness, quantified by the degree of undulation of the surface contour of the insulation layer, characterizing whether there are defects such as wrinkles and bulges in the mica tape during the covering process; third, gap ratio, i.e., the proportion of the volume of voids inside and between layers of the insulation layer to the total volume of the insulation layer, directly related to the tightness of the wrapping, and a key factor causing creepage breakdown; fourth, local dielectric loss value, reflecting the energy loss characteristics of the insulation layer under the action of an electric field. An abnormally high dielectric loss value usually indicates that there is local deterioration or voids in the insulation layer. The above four types of parameters comprehensively cover the core requirements of insulation quality from the perspectives of physical structure and electrical performance, providing multi-dimensional data basis for subsequent evaluation.

[0069] Subsequently, based on the breakdown location characteristics, online monitoring points were deployed in key areas of the initial insulation layer, focusing on the first and last turns of the lead wire and the root of the fan-shaped structure. Specifically, two monitoring points were deployed at the first and last turns of the lead wire, three at the root of the fan-shaped structure, and one in the middle area for comparison. To ensure the accuracy of parameter acquisition, the multi-parameter sensors used for the monitoring points underwent prior calibration. The calibration standard referenced the accuracy requirements of insulation parameter testing instruments, ensuring that the sensor's thickness measurement error was less than or equal to 0.001 mm and its dielectric loss measurement error was less than or equal to 0.0001 mm, thus establishing a solid foundation for accuracy at the hardware level. During sensor installation, an elastic pressure contact structure was used to maintain a constant pressure of 0.3 to 0.5 MPa between the sensor's probe end and the insulation layer surface. Simultaneously, a special coupling agent was applied to the contact area between the sensor and the insulation layer to prevent thickness measurement distortion and dielectric loss signal attenuation caused by air gaps, ensuring a stable and reliable contact state.

[0070] After the monitoring points are deployed, the sensors are activated and collect four types of parameters in real time: insulation layer thickness, surface flatness, gap ratio, and local dielectric loss value. To further ensure the accuracy of the data collection, differential signal transmission is used during data transmission to effectively resist electromagnetic interference generated by the wrapping equipment and avoid signal distortion. The data processing unit simultaneously establishes a data acquisition and verification mechanism to perform range verification on each real-time transmitted parameter value. If the parameter exceeds the normal fluctuation range, such as the thickness suddenly deviating from the predetermined range of 0.5±0.05mm, the sensor self-check program is immediately triggered to check whether the abnormality is caused by poor contact or equipment failure.

[0071] After the monitoring system is started, the sensor transmits the real-time collected status parameters to the data processing unit, forming a continuous parameter data stream. During the process, the sensor's built-in contact pressure feedback module monitors and displays the contact status in real time. If the feedback pressure is lower than 0.3MPa, an alarm is immediately issued, prompting the operator to adjust the sensor's installation position to ensure that the sensor and the insulation layer surface are always in close contact, thus avoiding data distortion caused by poor contact from a process control perspective. If a data interruption occurs at a monitoring point, the system automatically records the interruption time and the corresponding monitoring point location. The operator must first check the sensor connection lines and power supply status, and restart the acquisition after ruling out problems such as loose lines and unstable power supply. If necessary, the parameters of the monitoring point should be re-acquired to ensure data continuity. Finally, through the above-mentioned precise parameter definition, sensor calibration, contact status control, data transmission verification, and interruption handling, accurate and continuous real-time insulation covering status parameters covering key areas are obtained.

[0072] Step 308: Divide the insulation coating state parameters according to the preset coating area to obtain the state dataset of each partition. Specifically, this includes: based on the insulation coating state parameters, addressing the difficulties in partitioning, such as deviations in the actual processing dimensions of the coil, insufficient accuracy in the coordinate positioning of monitoring points, and poor real-time performance of multi-region data classification, a full-process solution involving physical size calibration, precise coordinate matching, hierarchical data classification, and standardized management of abnormal data is used to complete the partitioning and organization of parameters, forming a structured dataset. The specific operations are as follows:

[0073] First, the structural zoning rules of the coil are preset in the data processing unit. The core of preset covering area is to first eliminate the influence of the actual processing size deviation of the coil on the zoning boundary, and then combine the physical size and breakdown risk characteristics to complete the precise definition. The specific preset process is as follows: Because there is a processing deviation of ±5mm in the axial length of the stator coil in actual engineering, the actual axial length of each 1.18mm×5.6mm small gauge copper flat wire needs to be measured first. The measured value is entered into the data processing unit to correct the axial boundary of the preset zoning and avoid the theoretical size from the actual structure being out of sync. Based on the calibrated actual axial length, taking the nominal 350mm as an example, combined with the characteristic that the breakdown points are concentrated in the first and last turns of the lead end, the first turn area of ​​the lead end is preset as the area from 0 to 150mm in the axial start end of the coil and from 0 to 2.8mm in the radial direction. This area corresponds to the critical insulation part of the first turn of the lead end and is the area with the highest breakdown risk. The last turn area of ​​the lead end is preset as 350mm minus 150mm in the axial end of the coil. The region of 200 to 350 mm in diameter and 0 to 2.8 mm in radial direction is symmetrically distributed with the first turn area and is also a concentrated area of ​​breakdown. Considering the relatively regular structure and lower insulation risk of the middle part of the coil, the middle part of the coil is preset to be 150 to 200 mm in axial direction and 0 to 2.8 mm in radial direction. This region is 50 mm long and avoids the easily deformable parts at both ends. In view of the problem that the root of the fan-shaped area is prone to breakdown, the physical range of the bending at the end of the coil is first marked by a visual positioning device. Then, the root of the fan-shaped area is preset to be 0 to 2.8 mm in radial direction and covers the bending range. The geometric structure of this area is special and is prone to gaps due to loose wrapping. It needs to be treated as a separate critical zone. The above-mentioned modified zone boundaries are converted into coordinate thresholds that can be recognized by the data processing unit, and a two-dimensional schematic diagram of the coil zone is generated simultaneously for operators to check. This ensures that the preset area corresponds accurately with the actual coil structure and provides a clear and practical basis for subsequent determination of monitoring point assignment.

[0074] After defining the preset coverage area, the engineering challenge of incorrect assignment due to monitoring point installation position deviation needs to be addressed. The specific matching operation is as follows: During the monitoring point installation phase, the axial and radial coordinates of each sensor are measured using a laser positioning instrument. The measured coordinates are compared with the coordinate threshold of the preset area. If the axial coordinate deviation of a monitoring point exceeds ±2mm, the sensor installation position is immediately adjusted to ensure that the coordinate accuracy meets the engineering requirements. The data processing unit has a built-in dynamic coordinate matching algorithm that can identify the minute displacement of the coil during the winding process in real time. If the coil moves axially, the algorithm automatically corrects the assigned area of ​​the monitoring point to avoid matching errors caused by equipment vibration. After the initial matching is completed, the system automatically generates a table of monitoring points and zones. Operators can check the table through a visual interface to confirm that the two monitoring points in the first turn area, the two monitoring points in the last turn area, the three monitoring points in the fan-shaped root area, and the one monitoring point in the middle area are all correctly assigned, ensuring matching accuracy from a human-machine collaboration perspective.

[0075] After determining the monitoring point affiliation, a hierarchical classification operation was carried out to address the issue of easily mixed multi-parameter and multi-regional data in the project. Parameters such as thickness, surface flatness, gap ratio, and local dielectric loss value collected in step 307 were mapped according to the partitions to which the monitoring points belonged. That is, all parameters of the two monitoring points in the first turn area of ​​the lead wire end were integrated into the first turn area status dataset, and similarly, status datasets for the last turn area, middle area, and fan-shaped root area were formed. Each dataset encapsulated three types of information according to the project traceability requirements: the real-time value of the parameter, the collection timestamp, and the parameter fluctuation range. At the same time, each data entry was associated with a corresponding monitoring point number to facilitate accurate traceability of the data source later. An edge computing module was used to process the collected data locally, and the partition classification operation was pushed down to the equipment end to ensure that data classification and parameter collection were completed synchronously, meeting the project's timeliness requirements for real-time process optimization.

[0076] To address the issue of outliers in data acquisition during engineering projects, a standardized control process is established: Normal fluctuation ranges for each parameter are preset in the data processing unit, such as thickness 0.5±0.05mm and gap ratio less than or equal to 3%. If a parameter value exceeds this range, the system automatically marks it as data to be verified, rather than directly discarding it. After marking outlier data, the system automatically retrieves relevant information such as the contact status of the corresponding monitoring point and equipment operating parameters to assist operators in troubleshooting whether the anomaly is caused by poor sensor contact, equipment vibration interference, or a genuine process defect. Regardless of whether the outlier data is verified as valid, the original acquisition record is retained, and the cause of the anomaly is marked in the dataset to prevent the process traceability chain from being broken due to data rejection.

[0077] Ultimately, the above solution transforms the originally continuous parameter data stream into independent structured datasets for each preset coverage area, which not only meets the accuracy and timeliness requirements of engineering practice, but also provides a clear, reliable and practical data carrier for subsequent partition deviation calculation.

[0078] Step 309: Compare the state dataset of each partition with the corresponding preset threshold to calculate the parameter deviation value of each partition. Specifically, this includes addressing the difficulties in engineering implementation of partition evaluation, such as poor adaptability of partition thresholds to actual working conditions, lack of quantitative basis for weight coefficient calibration, difficulty in engineering transformation of geometric distance algorithms, and non-standardized abnormal data verification processes. A comprehensive solution is implemented, encompassing differentiated threshold engineering calibration, empirical implementation of weighted algorithms, engineering transformation of geometric distance, accurate calculation of comprehensive deviation, and closed-loop verification of abnormal data. This achieves accurate quantitative evaluation of the coverage quality of each partition, ultimately yielding a reliable comprehensive parameter deviation value. The specific operations are as follows:

[0079] Firstly, addressing the issue that traditional uniform thresholds cannot adapt to the insulation risks of different zones in engineering projects, precise calibration of preset thresholds for each zone was completed based on actual test data and operating condition requirements. The specific operations are as follows: Breakdown failure data for each zone was retrieved from previous batch tests. The proportion of breakdowns caused by insufficient thickness or excessive gap ratio in the lead-end first and last turn areas and the root area of ​​the fan-shaped structure was statistically analyzed. For example, 80% of breakdowns in the first turn area were caused by a thickness deviation exceeding 0.04mm. Simultaneously, considering the insulation reliability requirements of 10kV explosion-proof motors in flammable and explosive environments, the threshold tightening criteria for key areas were determined. The calibrated thresholds were then entered into the data processing unit. Each zone has preset thresholds. For the lead end and first and last turn areas and the fan-shaped root area, which are areas of concentrated breakdown and have geometric features such as bending and dense overlap, the thresholds are set as follows: thickness deviation not exceeding 0.04mm, gap ratio not exceeding 2.5%, and dielectric loss not exceeding 0.009. The middle area of ​​the coil has a regular geometric structure and low insulation risk, so the thresholds follow the basic standard, namely a thickness of 0.5mm plus or minus 0.05mm, a gap ratio not exceeding 3%, and a dielectric loss not exceeding 0.01. After entry, the reasonableness of the thresholds is verified by reverse verification using historical qualified data to ensure that the thresholds meet the insulation protection requirements without exceeding the process implementation capabilities.

[0080] To address the issue of evaluation bias caused by the reliance on empirically set weighting coefficients in engineering, orthogonal experiments and failure analysis were used to quantitatively calibrate the weighting coefficients. The specific procedures are as follows: Orthogonal experiments were designed to test the influence of three parameters—thickness, gap ratio, and dielectric loss—on the insulation performance of each zone. For example, multiple sets of tests were conducted on the first and last turns of the lead wire. The results showed that for every 0.01 mm deviation in thickness, the breakdown risk increased by 12%; for every 0.5% increase in gap ratio, the breakdown risk increased by 8%; and for every 0.001 increase in dielectric loss, the breakdown risk increased by 8%. Based on the influence factors obtained from the experiments... Each zone parameter is assigned a corresponding weight coefficient. Specifically, the thickness of the lead end and first turn zone has the most significant impact on breakdown due to the end bending characteristics, so the thickness weight is set to 0.4, and the gap ratio and dielectric loss value are set to 0.3. The fan-shaped root zone is prone to gap exceeding the standard due to the wedge transition structure, so the gap ratio weight is increased to 0.4, and the thickness and dielectric loss value are set to 0.3. The influence of each parameter in the coil middle zone is balanced, and the weights of all three are set to 0.33. At the same time, the weight coefficients are linked with the corresponding test data and archived to form a traceable weight calibration record to ensure that the weight allocation conforms to the actual insulation quality influence logic.

[0081] To address the issue that geometric distance measurement algorithms are theoretically complex and difficult to implement in engineering systems, they are transformed into a modular engineering calculation process. The specific steps are as follows: First, the actual values ​​of parameters in each partition dataset are compared with their corresponding preset thresholds to calculate the basic deviation value of a single parameter. The sign is retained to distinguish between insufficient or excessive parameters. For example, in the first-turn zone, the thickness at a monitoring point is 0.47mm, the lower threshold is 0.45mm, and the basic deviation value for thickness is -0.02mm; the gap ratio is 3%, the upper threshold is 2.5%, and the basic deviation value for gap ratio is +0.5%; the dielectric loss value is 0.007, the threshold is 0.009, and the basic deviation value for dielectric loss is -0.002. During the calculation, the monitoring point and acquisition time of each parameter are recorded simultaneously to ensure accurate traceability of the deviation values. The multi-dimensional parameter deviations are converted into a comprehensive distance value that can be directly calculated in engineering. Using the preset threshold standard as a benchmark, the basic deviation values ​​of each parameter are proportionally converted to a unified dimension, all converted to percentage deviations. Then, a simplified version of the Euclidean distance formula is used to calculate the comprehensive geometric distance, ensuring that the engineering system can complete the calculation quickly. This distance value comprehensively reflects the overall degree to which multiple parameters deviate from the standard simultaneously.

[0082] After completing the geometric distance calculation, the comprehensive deviation value is calculated in an engineering manner by combining the zone weight coefficients. The specific operation is as follows: Multiply the geometric distance calculated for each zone by the corresponding parameter weight coefficient, and then sum them to obtain the comprehensive parameter deviation value. For example, the thickness basic deviation value of a monitoring point in the first turn zone is multiplied by 0.4, the gap ratio basic deviation value is multiplied by 0.3, and the dielectric loss value basic deviation value is multiplied by 0.3. The sum of the three results is the comprehensive parameter deviation value of that monitoring point. If the geometric distance calculation result is 0.3, then the comprehensive deviation value is 0.3 multiplied by the corresponding weight accumulation coefficient. The average of the comprehensive deviation values ​​of all monitoring points in the same zone is calculated to obtain the overall comprehensive deviation value of that zone. At the same time, the location of the maximum deviation point in the zone is marked to provide a precise target for subsequent process adjustments.

[0083] To address the issues of sensor contact problems and electromagnetic interference that are prone to occur during data acquisition in engineering projects, a closed-loop verification process for the data to be verified is established. The specific operations are as follows: For the data to be verified marked in step 308, first retrieve the equipment operation log and sensor status data for the data acquisition period to check whether the data anomaly is caused by non-process factors such as loose sensor contact or vibration interference from the wrapping equipment; if the problem is found to be an acquisition error, arrange for personnel to go to the site to re-acquire the actual parameter values ​​at the corresponding monitoring points. After eliminating the influence of the error, the corrected comprehensive deviation value is obtained again according to the above-mentioned process of calculating the basic deviation value, geometric distance calculation, and weighting coefficient; if the abnormal data is verified to be caused by a real process defect, the original record is retained and included in the deviation calculation to ensure that each set of deviation data has accuracy and reliability.

[0084] Ultimately, through the above solution, the comparison of data from each zone with the threshold, the quantitative calculation of deviation values, and the verification of abnormal data were completed, resulting in the corrected comprehensive parameter deviation values ​​for different monitoring points in each zone, such as the comprehensive thickness deviation of the first turn zone, the comprehensive gap rate deviation of the last turn zone, and the comprehensive dielectric loss deviation of the fan-shaped root zone.

[0085] Step 310: Based on the parameter deviation values ​​of each zone and their relative positions in the overlay structure, determine the priority of process adjustments; according to the priority of process adjustments, obtain process optimization instructions including overlay tension correction and travel speed adjustment, specifically including: First, determine the priority judgment rules. Based on the breakdown risk of each region, i.e., the root of the fan-shaped area is smaller than the first and last turns but larger than the middle, set priority weights. The deviation value weight for the first and last turns area is 0.4, for the root of the fan-shaped area it is 0.3, and for the middle area it is 0.1; then calculate the deviation impact value of each zone, i.e., the absolute value of the parameter deviation value multiplied by the corresponding weight. For example, the gap ratio deviation of the first turn area is 0.5%, the weight is 0.4, and the deviation impact value is 0.2; the thickness deviation of the root of the fan-shaped area is -0.03mm, and the weight is 0. 0.3, with a deviation impact value of 0.009; the process adjustment priorities are determined by sorting the deviation impact values ​​from largest to smallest, such as the first turn area being greater than the last turn area, the last turn area being greater than the fan-shaped root area, and the fan-shaped root area being greater than the middle area; process optimization instructions are generated based on the priorities. For the high-priority first turn area gap ratio deviation, the coating tension correction is calculated. If the gap ratio exceeds the standard, the tension needs to be increased by 0.5N to improve the fit; for the possible thickness deviation in the last turn area, the travel speed adjustment is calculated. If the thickness is insufficient, the speed needs to be reduced by 0.05m / min to increase the number of coating layers; the instruction needs to specify the correction value, adjustment area, and execution order to ensure that the instruction can be directly used for equipment adjustment; finally, a process optimization instruction containing the coating tension correction and travel speed adjustment is formed.

[0086] Step 311: Parse the process optimization command to obtain the wrapping tension correction amount and the travel speed adjustment amount; based on the wrapping tension correction amount, dynamically compensate and adjust the current wrapping tension through the wrapping tension control mechanism to establish the optimized wrapping tension; based on the travel speed adjustment amount, synchronously adjust the travel drive mechanism of the wrapping equipment to establish the optimized travel speed. Specifically, this includes: addressing the difficulties in real-time adjustment in engineering implementation, such as command parsing delay, tension and speed adjustment coupling interference, untimely response to multi-zone parameter differences, and feedback data lag, through a full-link engineering solution of rapid edge parsing, precise tension closed-loop compensation, synchronous speed linkage adjustment, multi-zone timing adaptation, and real-time calibration under abnormal working conditions, to achieve real-time dynamic adjustment of process parameters and establish the optimized wrapping tension and travel speed that meet the command requirements. The specific operation is as follows:

[0087] Firstly, addressing the 50-100ms latency issue in cloud-based command parsing during the project, the command parsing function is offloaded to the edge computing control unit of the wrapping equipment, enabling rapid local processing of commands. Specifically, process optimization commands are pre-packaged into standardized data frames by partition, containing core information such as partition number, wrapping tension correction, travel speed adjustment, and execution priority, avoiding parsing delays caused by inconsistent command formats. Upon receiving the command data frames, the edge computing control unit directly extracts the specific correction parameters for each partition using a dedicated parsing algorithm. For example, the tension correction of 0.5N and the speed adjustment of -0.05m / min for the first wrap, and the tension correction of 0.3N and the speed adjustment of -0.03m / min for the last wrap. The entire parsing process is controlled within 10ms, far below the real-time requirements of process adjustments. Simultaneously, the execution sequence of the adjustment parameters for each partition is marked, ensuring orderly multi-region adjustments and avoiding parameter confusion.

[0088] To address the issues of nonlinear adjustment of damping force at the casting end and overshoot caused by tension feedback delay in engineering projects, a closed-loop control logic of command output, real-time feedback, and dynamic compensation is adopted to achieve precise adjustment of the wrapping tension. The specific operation is as follows: Before adjustment, the damping force output characteristics of the wrapping tension control mechanism are linearly calibrated to establish a corresponding curve between the damping force increment and the tension increase. For example, the linear relationship between a 0.2 N·m increase in damping torque and a 0.5 N increase in tension is calibrated to avoid tension adjustment deviations caused by nonlinear mechanical characteristics of the mechanism. The control system sends the adjustment to the tension execution unit based on the analyzed tension correction amount. If a signal is received indicating that the tension in the first turn area needs to be increased by 0.5N, the corresponding damping torque increment will be output according to the pre-calibration curve. At the same time, a high-frequency response tension sensor will be deployed at the tension output end. The sampling frequency of this sensor is set to 100Hz, which can provide real-time feedback on the actual tension value after adjustment. If there is a deviation between the actual tension value and the optimized target value, such as the instruction requiring the tension in the first turn area to be increased to 22N but the actual value is only 21.6N, the edge control unit will immediately calculate the compensation amount and adjust the damping force a second time until the actual tension stabilizes within the optimized value range. The entire closed-loop adjustment cycle is controlled within 50ms to ensure the real-time performance and accuracy of tension adjustment.

[0089] In engineering, tension adjustment can easily cause fluctuations in travel speed, and conversely, speed changes can also lead to tension instability. Therefore, it is necessary to establish a linkage adjustment mechanism between tension and speed to achieve coordinated adaptation between the two. The specific operation is as follows:

[0090] The winding equipment's travel drive mechanism uses a servo motor. The correspondence between motor speed and travel speed is pre-calibrated; for example, a 5 r / min decrease in motor speed corresponds to a 0.05 m / min decrease in travel speed, ensuring precise and linear speed adjustment. Simultaneously, a speed adjustment signal is sent to the travel drive mechanism while the tension adjustment signal is being sent. For instance, in the first turn, while increasing the tension by 0.5 N, the travel speed is reduced by 0.05 m / min as instructed, avoiding process imbalances caused by adjusting a single parameter. During adjustment, the travel speed changes are monitored in real time by a speed encoder, with the sampling frequency consistent with the tension sensor. If a fluctuation of ±0.01 m / min in speed is detected after tension adjustment, the edge control unit immediately outputs a fine-tuning signal to compensate for the speed deviation by increasing or decreasing the motor speed. For example, if a sudden increase in tension causes a slight decrease in speed, the motor speed is appropriately increased to maintain speed stability, ensuring that tension and speed are always in a coordinated state.

[0091] To address the issue of simultaneous adjustment of multiple zones in engineering projects leading to a sudden increase in equipment drive load and parameter malfunction, a zone-based time-sequential adjustment strategy is adopted to achieve orderly adaptation of parameters in each zone. The specific operation is as follows: Based on the insulation risk level of each zone, adjustment priorities are set, in descending order as the first turn zone, the last turn zone, the root zone of the sector, and the middle zone. Tension and speed adjustments are prioritized for the first turn zone, which has the highest risk of breakdown. Once its parameters stabilize, adjustment commands for other zones are executed sequentially. During the time-sequential adjustment process, the load current of the equipment drive mechanism is monitored in real time. If the load current of a certain zone approaches 80% of the rated value during adjustment, the adjustment of subsequent zones is paused until the parameters of the current zone stabilize and the load drops below 60% before resuming, thus avoiding equipment failure and adjustment interruption due to overload.

[0092] After initial adjustment, real-time verification and secondary calibration are conducted to address parameter drift issues caused by mechanical vibration and material property fluctuations in the project. The specific operations are as follows: The tension sensor and speed encoder continuously collect optimized parameter data to determine whether the parameters have entered a steady state, i.e., the tension fluctuation range is less than or equal to ±0.1N, the speed fluctuation range is less than or equal to ±0.005m / min, and the duration exceeds 2s. If parameter drift occurs, such as the tension in the first turn area dropping from 22N to 21.7N, the system will automatically calculate the drift amount and trigger secondary compensation. By fine-tuning the damping force, the tension is restored to the optimized value, ensuring that the equipment parameters always match the process optimization command requirements. Finally, through the above engineering scheme, the parameters of each zone are dynamically adjusted within 100ms, establishing the optimized wrapping tension (e.g., 21.5 to 26.5N) and travel speed (e.g., 0.55 to 0.6m / min), achieving accurate real-time adaptation of process parameters.

[0093] Step 312 involves the synergistic effect of optimized wrapping tension and optimized travel speed to ensure that the semi-overlapping process parameters track the optimization target in real time, forming a semi-overlapping insulation structure with optimized wrapping uniformity. Specifically, this includes: initiating the optimized semi-overlapping process; the wrapping equipment operating at the optimized wrapping tension and travel speed, where the optimized wrapping tension is, for example, 21.5 to 26.5 N, and the optimized travel speed is, for example, 0.55 to 0.6 m / min; the control system collecting the status parameters of each monitoring point in real time (refer to step 307) and comparing the parameters with the optimization target, where the optimization target is, for example, a gap ratio less than or equal to 2.5% and a thickness deviation less than or equal to 0.04 mm; if the parameters meet the optimization target, then the process is maintained. Current process parameters; if there are still slight deviations in parameters in a certain area, such as a gap ratio of 2.4% in the last turn area, which is close to the threshold, then the correction amount is finely adjusted again based on real-time data, such as increasing the tension by 0.2N; during the process, it is necessary to ensure the synergistic effect of tension and speed. When the tension is increased, the speed should be appropriately reduced to avoid excessive stretching of the mica tape; when the speed is reduced, it is necessary to ensure that the tension is stable to avoid loose wrapping; continue running until the insulation layer is wrapped, and then use a thickness measuring instrument and microscopic observation equipment to detect the uniformity of the final insulation structure, ensuring that the thickness deviation of each area is less than or equal to 0.04mm and the gap ratio is less than or equal to 2.5%; finally, a semi-overlapping insulation structure with optimized wrapping uniformity is formed, and its performance meets the inter-turn insulation requirements of a 10kV explosion-proof motor.

[0094] In this embodiment of the invention, the material thickness, flexibility, and tensile strength data from the structural characteristic parameters of the insulating material are extracted. This allows for the selection of key data directly related to the initial parameter calculation of the semi-overlapping process from a structured characteristic parameter system, providing a precise and focused data foundation for determining subsequent initial wrapping parameters and ensuring clear and reliable data support for parameter calculations in subsequent steps. The initial number of wrapping layers is calculated based on the material thickness data, ensuring a precise match between the initial number of layers and the material thickness characteristics. The initial wrapping tension range is calculated based on the material flexibility data and the initial number of wrapping layers, adapting the tension range to the material's flexibility. Combined with tensile strength data and material structure coefficient correction, parameter values ​​are further optimized. The entire process involves the correlation, integration, and correction of multiple sets of data, ensuring that the initial wrapping parameters of the semi-overlapping process fully conform to the inherent characteristics of the material, guaranteeing the rationality and applicability of the initial parameters. Based on the initial wrapping parameters of the semi-overlapping process, the wrapping equipment is controlled to complete the predetermined number of semi-overlapping wrapping layers. The determined parameters guide the equipment operation, ensuring the correct number of layers and wrapping method of the initial wrapping structure. The core features meet the preset requirements; based on the initial wrapping tension range and preliminary wrapping structure, the wrapping tension control mechanism is adjusted to keep the wrapping process within this tension range. Through real-time monitoring of tension data and mechanism adjustment, a stable wrapping tension is established; based on the stable wrapping tension, the wrapping equipment is controlled to complete the insulation layer densification process at an optimized travel speed. The stable tension data and travel speed parameters are combined to match the bonding and compaction effects of the insulation material during the densification process; through the insulation layer densification process, an initial wrapping insulation layer with a predetermined wrapping thickness and density is formed on the surface of the copper flat wire. Relying on the precise control of the previous process parameter data, it is ensured that the key indicators such as the thickness and density of the initial wrapping insulation layer meet the preset standards, laying a qualified foundation for subsequent online monitoring and process optimization; by deploying online monitoring points in key wrapping areas to collect insulation wrapping status parameters in real time, real-time status data of key areas of the initial wrapping insulation layer can be obtained, forming a continuous and complete status parameter dataset, avoiding data lag or partial data loss caused by offline detection.

[0095] The insulation covering state parameters are divided into state datasets for each zone according to preset covering areas. Data classification and organization ensure that the state data for different covering areas are presented independently and structurally clear, avoiding analytical biases caused by data mixing. The state datasets for each zone are compared with corresponding preset thresholds to calculate the parameter deviation values ​​for each zone. Data comparison quantifies the difference between the covering parameters of each zone and standard requirements, clarifying the specific degree of deviation in each area and providing a quantifiable basis for subsequent process adjustments. Based on the parameter deviation values ​​of each zone and their relative positions in the covering structure, the priority of process adjustments is determined. The quantitative deviation data and regional location information are integrated to clarify the order of process adjustments for different zones. Based on the priority, a process adjustment including covering tension correction and travel speed adjustment is obtained. The optimization instructions are designed to align with both actual parameter deviations and structural importance requirements. Prioritization based on data integration enhances the targeting and efficiency of process optimization. Analysis of the optimization instructions yields the wrapping tension correction and travel speed adjustment. Based on this correction data, the wrapping tension control mechanism dynamically compensates and adjusts the current wrapping tension, ensuring precise tension optimization. Simultaneously, the travel drive mechanism of the wrapping equipment is adjusted according to the speed adjustment, achieving coordinated optimization of speed and tension. Through the synergistic effect of the optimized wrapping tension and travel speed, the semi-overlapping process parameters track the optimization target in real time. Supported by the coordinated data between parameters, the performance of the insulation layer in terms of thickness uniformity and density uniformity is effectively improved, ultimately forming a semi-overlapping insulation structure with optimized wrapping uniformity.

[0096] In a preferred embodiment of the present invention, step 400, based on a semi-overlapping insulation structure with optimized coverage uniformity, involves performing a vacuum pressure impregnation process to form a dense, integral insulating protective layer, including:

[0097] Step 401: Based on the semi-overlapping insulation structure with optimized uniformity of coating, vacuum pretreatment is performed to remove residual gas inside the insulation layer, resulting in a pretreated insulation structure. Specifically, this includes: first, placing the semi-overlapping insulation structure (attached to 1.18mm × 5.6mm small-gauge copper flat wire) into a vacuum chamber, ensuring the insulation structure is completely placed within the sealed area of ​​the chamber to avoid insufficient vacuum due to poor sealing; then, starting the vacuum system and gradually increasing the vacuum level inside the chamber to 0.095 to 0.098 MPa according to the pretreatment process parameters. This vacuum level setting can effectively extract gas from the interior of the insulation layer (especially...). It is the residual air and tiny bubbles in the semi-overlapping area; during the process, the vacuum level data inside the tank is collected in real time by a vacuum sensor to form a vacuum level change curve. If the vacuum level drops by more than 0.002 MPa / h, the sealing status of the vacuum tank is immediately checked and repaired to prevent gas from seeping in again; maintain this vacuum level for 2 to 3 hours to ensure that the residual gas inside the insulation layer is fully discharged. Under this parameter, the residual gas content can be controlled below 0.5% and will not affect the subsequent paint penetration; after the pretreatment is completed, the vacuum system is turned off and the tank is kept sealed to obtain a pretreated insulation structure with the internal gas fully discharged.

[0098] Step 402: Based on the pre-treated insulation structure, a vacuum pressure impregnation process is used to allow the insulating varnish to fully penetrate into the internal voids of the insulation layer under pressure, forming a fully permeated insulation structure. Specifically, this includes: First, selecting 1168H insulating varnish as the impregnation material. The viscosity of this varnish is compatible with the void size of the semi-overlapping insulation layer (optimized gap ratio less than or equal to 2.5%). The viscosity of the varnish at 25℃ is 150 to 200 mPa·s, which can effectively penetrate into minute gaps. Then, 1168H insulating varnish is injected into a sealed vacuum container. During injection, the flow rate of the varnish is controlled at 0.5 to 1 L / min to avoid excessive flow rate causing damage to the varnish. Air bubbles are introduced into the tank. After the paint has completely submerged the pre-treated insulation structure, the pressure system is activated to gradually increase the pressure inside the tank to 0.3 to 0.4 MPa. This pressure value allows the paint to be fully squeezed into the internal voids of the insulation layer under the action of pressure difference. At this pressure, the paint penetration depth can reach 100% of the insulation layer thickness, with no unpenetrated areas. This pressure is maintained for 3 to 4 hours. During this process, the pressure inside the tank is monitored in real time by a pressure sensor to ensure that the pressure fluctuation range does not exceed ±0.02 MPa, preventing uneven penetration due to unstable pressure. After the paint impregnation is completed, excess paint is drained from the tank, and sufficient paint is left to adhere to the surface of the insulation structure, forming a fully penetrated insulation structure.

[0099] Step 403: Based on the fully penetrated insulating structure of the varnish, a step-curing process is implemented by controlling the temperature gradient to allow the insulating varnish to complete the transition from gelation to a glassy state, forming a pre-cured insulator. Specifically, this includes: first, removing the varnish-penetrated insulating structure from the vacuum chamber and placing it in a constant-temperature curing oven. Temperature parameters are set according to the step-curing curve of the 1168H insulating varnish: the first stage is the gelation stage, where the oven temperature is gradually increased from room temperature to 80-85°C at a rate of 5-8°C / h. This stage allows the solvent in the varnish to evaporate slowly, preventing pinholes in the varnish film due to excessive evaporation; maintaining this temperature for 4-5 hours, and recording the temperature in the oven in real time using a temperature sensor. The first stage is the regional temperature, ensuring the temperature difference does not exceed ±3℃ to prevent local overheating and premature curing of the varnish. The second stage is the glass transition stage, where the oven temperature is raised to 120 to 125℃ at a rate of 5℃ / h. This temperature promotes the cross-linking reaction of the varnish molecules, gradually transforming them from a gel state to a glass state. This temperature is maintained for 6 to 7 hours. After this stage, the cross-linking degree of the insulating varnish can reach more than 90%, possessing preliminary mechanical strength. The third stage is the post-curing stage, where the oven temperature is lowered to 100 to 105℃ and maintained for 2 hours to reduce the thermal stress generated inside the insulation layer during curing. After curing, the varnish is allowed to cool naturally to room temperature, resulting in a structurally stable, fully cured, and preliminarily cured insulation.

[0100] Step 404: Based on the pre-cured insulator, the integrity of its internal void filling and the continuity of its surface coating are tested to obtain insulation layer density test data. Specifically, this includes: firstly, testing the integrity of the internal void filling of the pre-cured insulator using an ultrasonic testing instrument (frequency 5 to 10 MHz) to perform a full-area scan of the insulator, setting a detection threshold: when the reflected wave amplitude exceeds a reference value by 15%, it is determined that there are unfilled voids; during the scanning process, the reflected wave data of each detection point is recorded, the location and size of the unfilled voids are marked, and the overall void filling rate is calculated, i.e., number of filled voids / total number of voids × 100%; subsequently, the surface coating is applied... For membrane continuity testing, the surface of the insulator is observed using a high-definition microscope (magnification of 50 to 100 times). The number and location of defects such as varnish film cracks, scratches, and pinholes are recorded. The varnish film thickness is measured, and five key areas are selected, including the first and last turns of the lead wire and the middle section. Three points are measured in each area, and the varnish film thickness deviation is calculated, i.e., maximum thickness minus minimum thickness. The above test data are compiled into an insulation layer density test dataset, which includes quantitative indicators such as void filling rate, distribution of unfilled void size, number of varnish film defects, varnish film thickness, and deviation value. At the same time, ultrasonic scanning images and microscopic observation photographs are retained as auxiliary data to ensure the objectivity and traceability of the test data.

[0101] Step 405: Based on the insulation layer density test data, determine whether it meets the predetermined technical indicators; when the insulation layer density test data is determined to meet the predetermined technical indicators, confirm that a dense overall insulation protective layer with enhanced mechanical strength and stable electrical performance has been obtained. Specifically, this includes: firstly, determining the predetermined technical indicators, which comprehensively consider the flammable and explosive environment requirements of the 10kV explosion-proof motor, the measured performance data of the optimal insulation structure, and the requirements of relevant industry standards; specifically, based on the fact that the semi-overlapping structure has been verified as the optimal insulation structure through multiple tests, its empty... The measured average gap filling rate is 97%. However, considering that explosion-proof motors require higher insulation reliability under complex operating conditions, the gap filling rate is optimized upwards to no less than 98%. The maximum measured size of unfilled gaps is 0.12mm. Considering the structural characteristics of the 1.18mm × 5.6mm small-gauge copper flat wire, excessively large gaps will result in weak insulation points after the paint has cured. Therefore, this indicator is tightened to no more than 0.1mm. Regarding the number of paint film defects, the optimal structure has a measured defect count of 3 per 100mm. 2 However, excessive defects can easily lead to creepage phenomena, which meets the stringent requirements for the integrity of the insulation surface in explosion-proof environments. Therefore, this indicator has been adjusted to no more than 2 defects per 100mm. 2 Regarding the coating thickness deviation, the corresponding deviation value is 0.06mm. In conjunction with the initial coating insulation layer thickness deviation control target in step 306, in order to ensure the overall insulation layer thickness uniformity and avoid local excessive thinness or thickness affecting electrical performance, this indicator is set to not exceed 0.05mm. Through the comprehensive derivation of the above measured data, operating conditions, structural characteristics and industry standards, the specific parameters of the predetermined technical indicators are finally determined.

[0102] The test data was then compared with the predetermined technical specifications one by one. If the void filling rate was 98.5%, the maximum size of the unfilled void was 0.08 mm, and the number of paint film defects was 1 per 100 mm, then... 2 If the coating thickness deviation is 0.04mm and all data meet the index requirements, the insulation layer density is determined to meet the predetermined technical index. If any data fails to meet the standard, such as a void filling rate of 97%, the process is returned to step 401 to repeat the vacuum pretreatment and impregnation curing process until the test data meets the standard.

[0103] When the indicators are met, the key parameters of each previous process step are further correlated, including the initial coating parameters in step 302, the impregnation pressure in step 402, and the step curing parameters in step 403, etc., and correspond one-to-one with the insulation layer density test data to form a process parameter density data correlation record. This record needs to clearly show the correspondence between the set values ​​of each process parameter and the measured values ​​of the density index, thereby establishing a complete quality traceability chain, and finally confirming that a dense overall insulation protective layer is obtained. This protective layer is due to the paint liquid fully filling the gaps of the half-overlapping wrapping.

[0104] In a preferred embodiment of the present invention, step 500 above, based on the dense integral insulation protective layer, applies the standard-specified inter-turn withstand voltage test voltage for explosion-proof motors to the stator winding for verification, and obtains the insulation performance verification conclusion; based on the insulation performance verification conclusion, it is determined that the risk of inter-turn insulation breakdown is effectively controlled, including:

[0105] Step 501: Based on the dense integral insulation protective layer, establish inter-turn insulation verification test conditions, specifically including: First, fix the stator winding with the dense integral insulation protective layer (its copper flat wire specification is 1.18mm×5.6mm) to a special test fixture, ensuring that the first and last turns of the winding are fully exposed to the monitoring field of view, avoiding the fixture from obstructing subsequent status monitoring; then, the test environment parameters are required, controlling the test environment temperature between 20 and 25℃ and the relative humidity between 45% and 65%. This temperature and humidity range can eliminate the interference of environmental factors on insulation performance, and determine that the dielectric loss value, breakdown voltage and other parameters of the insulation material fluctuate the least under these conditions; at the same time, check the electromagnetic interference in the test area, and control the intensity of external electromagnetic interference within the allowable range through electromagnetic shielding measures, such as less than or equal to 50dBμV / m, to prevent interference signals from affecting the subsequent insulation status data acquisition; finally, preheat and calibrate the voltage output equipment and monitoring equipment used in the test to ensure that the equipment accuracy meets the accuracy requirements of the test instrument, such as voltage measurement accuracy ±1%. Through the above operations, the inter-turn insulation verification test conditions are established.

[0106] Step 502: Based on the inter-turn insulation verification test conditions, apply the standard-specified inter-turn withstand voltage test voltage for explosion-proof motors to the stator windings to establish the withstand voltage test electric field environment. Specifically, this includes: First, calculating the inter-turn test voltage value for explosion-proof motors according to IEC60034-15-2009 and GB / T22715-2016 standards. For an explosion-proof motor with a rated line voltage of 10kV (UN=10kV), the test voltage is (4UN+5)×65%×105%, which is 30.7kV. Then, input this voltage parameter into the voltage output control system, start the system, and gradually apply the voltage according to the voltage rise rate (e.g., 2kV / s), avoiding... To prevent damage to the insulation layer due to sudden voltage surges, the voltage sensor collects the output voltage value in real time during the process, forming a voltage change curve to ensure that the voltage is maintained stably at 30.7kV, with a fluctuation range not exceeding ±2%, i.e., 30.086 to 31.314kV. If the voltage fluctuation exceeds the range, the voltage control system must immediately and automatically adjust the output until the voltage returns to the set value. After the voltage stabilizes, the electric field distribution around the stator winding is continuously monitored. The electric field detector confirms that the electric field strength in each area of ​​the winding (especially the first and last turns) is uniform, without any local abnormal concentration of field strength. Finally, a withstand voltage test electric field environment that meets the standard requirements and is accurate and stable is established.

[0107] Step 503: Based on the withstand voltage test electric field environment, monitor and record the winding insulation status data in real time. Specifically, this includes: First, selecting corresponding monitoring equipment according to the core indicators of insulation performance verification: for breakdown voltage and corona initiation voltage, using an inter-turn withstand voltage tester; for partial discharge signals, using a partial discharge detector; and for the surface condition of the insulation layer, using a high-definition visual monitoring device. These devices are then precisely connected to the stator winding. The electrodes of the inter-turn withstand voltage tester must be reliably connected to the first and last turns of the winding, the sensor of the partial discharge detector must be close to the critical area of ​​the winding, and the visual monitoring device must cover the entire winding area. Then, all monitoring equipment is started and set... The data acquisition frequency is 1 time / second to ensure that instantaneous changes in insulation status can be captured. During the entire withstand voltage test, the withstand voltage duration is 60 seconds, and various status data are recorded in real time. The inter-turn withstand voltage tester records the voltage withstand value and whether a breakdown signal occurs, the partial discharge detector records the amplitude and frequency of the discharge pulse signal, and the visual monitoring equipment records whether there are creepage marks on the surface of the insulation layer. All the collected data are organized into a continuous winding insulation status dataset according to the timestamp, including information such as time, various parameter values, and equipment operating status. If data acquisition of a certain device is interrupted, the device must be restarted immediately and the data must be reacquired to ensure the integrity of the dataset.

[0108] Step 504: Perform waveform feature analysis on the winding insulation state data to confirm that there is no creepage breakdown during the test and obtain insulation performance verification conclusions. Specifically, this includes: firstly, extracting key waveform data from the winding insulation state data, including the voltage and time waveforms of the inter-turn withstand voltage test and the pulse signal waveform of partial discharge; then, based on the withstand voltage waveform characteristics of qualified insulation structures, determining the criteria for normal waveforms: the voltage and time waveforms must remain stable without voltage drops, which usually correspond to insulation breakdown; the wavefront time must be no less than 0.2 μs; the partial discharge waveform must have no abnormal high-frequency pulse signals, and abnormal pulses correspond to partial discharge. For creepage, the discharge amplitude must be lower than a set threshold, such as less than or equal to 10 pC. The extracted actual waveform is compared and analyzed one by one with the above standard waveform: if the voltage and time waveforms remain stable at 30.7 kV without sudden drops, and the measured wavefront time is 0.25 μs; the partial discharge waveform has no abnormal pulses, and the maximum discharge amplitude is 8 pC, which is lower than the threshold; at the same time, combined with visual monitoring data, it is confirmed that there are no creepage marks on the winding surface, then it can be confirmed that there is no creepage breakdown during the test; the above analysis results are compiled into an insulation performance verification conclusion, which must include waveform comparison results and comparison of measured values ​​of key parameters with standard values.

[0109] Step 505: Based on the insulation performance verification conclusion, determine that the risk of inter-turn insulation breakdown is effectively controlled. Specifically, this includes: first, comparing the insulation performance verification conclusion with the current 10kV explosion-proof motor inter-turn insulation qualification standard to determine that a qualified insulation structure must meet the following requirements: no creepage breakdown under a 30.7kV withstand voltage test, partial discharge amplitude less than or equal to 10pC, and wavefront time greater than or equal to 0.2μs. If the measured data in the verification conclusion all meet this standard, the insulation performance is preliminarily determined to be up to standard. Then, further correlate the key parameter data of each previous process step, including the initial coating parameters of the semi-overlapping, vacuum pressure impregnation parameters, and stepped curing parameters, to form a process parameter and insulation performance verification conclusion. The corresponding records are as follows: initial wrapping parameters for semi-overlapping, such as the number of wrapping layers and tension range; vacuum pressure impregnation parameters, such as impregnation pressure and impregnation time; and stepped curing parameters, such as temperature and holding time at each stage. These records need to determine the correlation logic between the set values ​​of each process parameter and the measured insulation performance parameters. For example, when the tension of the semi-overlapping is controlled between 21 and 26 N, the corresponding withstand voltage test shows no breakdown and the partial discharge amplitude is low. A complete quality traceability chain is established through these correlation records to prove that the performance of the dense overall insulation protective layer formed under the current process scheme is the result of precise control of each process parameter in the early stages. Finally, based on the above data comparison and correlation analysis, it is determined that the risk of inter-turn insulation breakdown is effectively controlled.

[0110] like Figure 2 As shown, an embodiment of the present invention also provides a 10kV explosion-proof motor stator winding inter-turn insulation breakdown risk control system, comprising:

[0111] The analysis module is used to identify inter-turn insulation defects by analyzing creepage breakdown phenomena that occur in mass production, and to locate the breakdown points concentrated at the first and last turns of the lead wire, thus obtaining the location characteristics of the breakdown points; based on the location characteristics of the breakdown points, the main causes of weak insulation are analyzed.

[0112] The process verification module is used to select single-sided polyester film reinforced mica tape as the inter-turn insulation material based on the main reasons for insulation weakness; to perform process verification on the inter-turn insulation material and obtain the structural characteristic parameters of the insulation material.

[0113] The optimization module is used to determine the initial wrapping parameters of the semi-overlapping process based on the structural characteristic parameters of the insulation material; execute the semi-overlapping wrapping process based on the initial wrapping parameters to form the initial wrapping insulation layer; collect the insulation wrapping status parameters of the initial wrapping insulation layer in real time through online monitoring points deployed in key wrapping areas; evaluate the insulation wrapping status parameters by region to obtain process optimization instructions; and adjust the wrapping tension and travel speed of the semi-overlapping operation in real time based on the process optimization instructions to form a semi-overlapping insulation structure with optimized wrapping uniformity.

[0114] The processing module is used to perform vacuum pressure impregnation treatment on a semi-overlapping insulation structure with optimized coverage uniformity to form a dense integral insulation protective layer.

[0115] The judgment module is used to verify the insulation performance by applying the standard-specified inter-turn withstand voltage test voltage of the explosion-proof motor to the stator winding based on the dense integral insulation protective layer, and to obtain the insulation performance verification conclusion. Based on the insulation performance verification conclusion, it is determined that the risk of inter-turn insulation breakdown has been effectively controlled.

[0116] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0117] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0118] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0119] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for controlling the risk of inter-turn insulation breakdown in the stator winding of a 10kV explosion-proof motor, characterized in that, The method includes: Step 100: By analyzing the creepage breakdown phenomenon that occurs in mass production, it is determined that there is an inter-turn insulation defect, and the breakdown points are concentrated at the first and last turns of the lead wire, thus obtaining the location characteristics of the breakdown points; based on the location characteristics of the breakdown points, the main reasons for the weak insulation are analyzed. Step 200: Based on the main reasons for weak insulation, single-sided polyester film reinforced mica tape is selected as the inter-turn insulation material; the process of the inter-turn insulation material is verified to obtain the structural characteristic parameters of the insulation material; Step 300: Based on the structural characteristic parameters of the insulating material, determine the initial wrapping parameters for the semi-overlapping process; execute the semi-overlapping wrapping process based on the initial wrapping parameters to form an initial wrapped insulation layer; collect the insulation wrapping status parameters of the initial wrapped insulation layer in real time through online monitoring points deployed in key wrapping areas; perform zonal evaluation on the insulation wrapping status parameters to obtain process optimization instructions; based on the process optimization instructions, adjust the wrapping tension and travel speed of the semi-overlapping operation in real time to form a semi-overlapping insulation structure with optimized wrapping uniformity, including: Extract material thickness, flexibility, and tensile strength data from the structural characteristic parameters of the insulating material; calculate and determine the initial number of wrapping layers based on the material thickness data; calculate and determine the initial wrapping tension range based on the material flexibility data and the initial wrapping layer number; combine the tensile strength data and the initial wrapping tension range, and determine the initial wrapping parameters for the semi-overlap wrapping process through material structure coefficient correction; based on the initial wrapping parameters of the semi-overlap wrapping process, control the wrapping equipment to complete the predetermined number of semi-overlap wrapping layers to form a preliminary wrapping structure; based on the initial wrapping tension range and the preliminary wrapping structure, adjust the wrapping tension control mechanism to keep the wrapping process within this tension range and establish a stable wrapping tension; based on the stable wrapping tension, control the wrapping equipment to complete the insulation layer densification process at an optimized travel speed; through the insulation layer densification process, form an initial wrapping insulation layer with a predetermined wrapping thickness and density on the surface of the copper flat wire; monitor the initial wrapping insulation layer through online monitoring systems deployed in key wrapping areas. Measurement points are used to collect insulation wrapping status parameters in real time. These parameters are then divided into predefined wrapping areas to obtain status datasets for each area. The status datasets for each area are compared with corresponding predefined thresholds to calculate parameter deviation values ​​for each area. Based on these deviation values ​​and their relative positions within the wrapping structure, the priority of process adjustments is determined. According to this priority, process optimization instructions, including wrapping tension correction and travel speed adjustment, are generated. These instructions are parsed to obtain the wrapping tension correction and travel speed adjustment. Based on the wrapping tension correction, the current wrapping tension is dynamically compensated and adjusted using a wrapping tension control mechanism to establish an optimized wrapping tension. Based on the travel speed adjustment, the travel drive mechanism of the wrapping equipment is synchronously adjusted to establish an optimized travel speed. Through the synergistic effect of the optimized wrapping tension and optimized travel speed, the semi-overlapping process parameters track the optimization target in real time, forming a semi-overlapping insulation structure with optimized wrapping uniformity. Step 400: Based on the semi-overlapping insulation structure with optimized coverage uniformity, a vacuum pressure impregnation process is performed to form a dense integral insulation protective layer. Step 500: Based on the dense integral insulation protective layer, the standard-specified inter-turn withstand voltage of the explosion-proof motor is applied to the stator winding for verification, and the insulation performance verification conclusion is obtained; based on the insulation performance verification conclusion, it is determined that the risk of inter-turn insulation breakdown is effectively controlled.

2. The method for controlling the risk of inter-turn insulation breakdown in the stator winding of a 10kV explosion-proof motor according to claim 1, characterized in that, Step 100 includes: Collect faulty coils that exhibit creepage breakdown during mass production, establish a fault sample set, and record the breakdown location distribution characteristics of each fault sample; based on the fault sample set and its breakdown location distribution characteristics, select representative faulty coils for high-voltage pulse tests to obtain their inter-turn withstand voltage failure waveform data. Time-frequency characteristic analysis was performed on the failed waveform data to extract its characteristic parameters, and the difference in characteristic parameters was identified by comparing it with the standard normal waveform. Based on the difference in characteristic parameters and the distribution characteristics of the breakdown location, the presence of inter-turn insulation defects was confirmed through comprehensive analysis. Based on the inter-turn insulation defects, the breakdown points are concentrated at the first and last turns of the lead wire, thus obtaining the location characteristics of the breakdown points. Based on the location characteristics of the breakdown point, weak insulation areas at the beginning and end turns of the lead wire were identified; for these weak insulation areas, the key factors leading to the decline in insulation performance were analyzed and determined; based on these key factors, the main causes of the weak insulation were confirmed, including the soft texture of the small-gauge copper flat wire, the loose wrapping of the flat insulation structure, and mechanical deformation at the end.

3. The method for controlling the risk of inter-turn insulation breakdown in the stator winding of a 10kV explosion-proof motor according to claim 2, characterized in that, Step 200 includes: Based on the main reasons for the weak insulation, a material selection scheme was determined; According to the material selection scheme, single-sided polyester film reinforced mica tape was selected as the inter-turn insulation material. The process of the inter-turn insulation material was verified to obtain its process adaptability data; Based on the process adaptability data, the structural characteristic parameters of the insulating material are obtained.

4. The method for controlling the risk of inter-turn insulation breakdown in the stator winding of a 10kV explosion-proof motor according to claim 3, characterized in that, Step 400 includes: Based on the aforementioned semi-overlapping insulation structure with optimized uniformity of coating, vacuum pretreatment is performed to remove residual gas inside the insulation layer, resulting in a pretreated insulation structure. Based on the pretreated insulation structure, the vacuum pressure impregnation process allows the insulating varnish to fully penetrate into the internal voids of the insulation layer under pressure, forming an insulation structure with full varnish penetration. Based on the fully penetrated insulating structure of the varnish, a step-curing process is implemented by controlling the temperature gradient, so that the insulating varnish completes the transformation from gelation to glass state, forming a pre-cured insulator. Based on the pre-cured insulator, the integrity of its internal void filling and the continuity of its surface coating are tested to obtain insulation layer density test data; Based on the insulation layer density test data, it is determined whether it meets the predetermined technical indicators; when it is determined that the insulation layer density test data meets the predetermined technical indicators, it is confirmed that a dense integral insulation protective layer with enhanced mechanical strength and stable electrical performance has been obtained.

5. The method for controlling the risk of inter-turn insulation breakdown in the stator winding of a 10kV explosion-proof motor according to claim 4, characterized in that, Step 500 includes: Based on the aforementioned dense integral insulating protective layer, inter-turn insulation verification test conditions were established. Based on the inter-turn insulation verification test conditions, the standard-specified inter-turn withstand voltage of the explosion-proof motor is applied to the stator winding to establish the withstand voltage test electric field environment; Based on the withstand voltage test electric field environment, the winding insulation status data is monitored and recorded in real time; Waveform feature analysis was performed on the winding insulation status data to confirm that there was no creepage breakdown during the test, and the insulation performance verification conclusion was obtained. Based on the insulation performance verification results, it was determined that the risk of inter-turn insulation breakdown was effectively controlled.

6. A control system for the risk of inter-turn insulation breakdown in the stator winding of a 10kV explosion-proof motor, wherein the system implements the method as described in any one of claims 1 to 5, characterized in that, include: The analysis module is used to identify inter-turn insulation defects by analyzing creepage breakdown phenomena that occur in mass production, and to locate the breakdown points concentrated at the first and last turns of the lead wire, thus obtaining the location characteristics of the breakdown points; based on the location characteristics of the breakdown points, the main causes of weak insulation are analyzed. The process verification module is used to select single-sided polyester film reinforced mica tape as the inter-turn insulation material based on the main reasons for insulation weakness; to perform process verification on the inter-turn insulation material and obtain the structural characteristic parameters of the insulation material. The optimization module is used to determine the initial wrapping parameters of the semi-overlapping process based on the structural characteristic parameters of the insulating material. A semi-overlapping wrapping process is performed based on the initial wrapping parameters to form the initial wrapping insulation layer; For the initial insulation layer, its insulation coverage status parameters are collected in real time through online monitoring points deployed in key coverage areas; The insulation covering status parameters are evaluated by region to obtain process optimization instructions; Based on process optimization instructions, the wrapping tension and travel speed of the semi-overlapping operation are adjusted in real time to form a semi-overlapping insulation structure with optimized wrapping uniformity. The processing module is used to perform vacuum pressure impregnation treatment on a semi-overlapping insulation structure with optimized coverage uniformity to form a dense integral insulation protective layer. The judgment module is used to verify the insulation performance by applying the standard-specified inter-turn withstand voltage test voltage of the explosion-proof motor to the stator winding based on the dense integral insulation protective layer, and to obtain the insulation performance verification conclusion. Based on the insulation performance verification results, it was determined that the risk of inter-turn insulation breakdown has been effectively controlled.

7. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 5.

Images