Transformer production and manufacturing management and control method and system for improving short-circuit resistance

Abstract

The application discloses a production and manufacturing control method and system for improving the short-circuit resistance of a transformer, and the method comprises the following steps: detecting the adhesion strength of copper wires and establishing a plastic deformation threshold prediction model; when winding the coil, a three-dimensional model is established by laser scanning, the geometric offset degree is calculated according to the position and thickness deviation of the cushion block, the curvature deviation is calculated according to the S-bend point cloud coordinates, and the installation of the cushion block and the S-bend damage are controlled; when pre-pressing, the strain is monitored by an optical fiber sensor, the pre-pressing force is determined in combination with the micro-displacement change rate and the cumulative strain, the tension of the winding machine is dynamically adjusted according to the model to compensate for the insufficient pre-pressing force; when drying in a weather drying furnace, the moisture content is monitored by an internal insulation sample paper, the internal moisture is inversed in combination with the multi-physical field finite element analysis, and drying is performed to the process requirement. The application solves the problem of unstable short-circuit resistance caused by traditional experience dependence, accurately controls the key links, and improves the short-circuit resistance and operation reliability of the transformer.

Description

Technical Field

[0001] This invention relates to the field of power transformer manufacturing technology, specifically to a method and system for controlling the production and manufacturing of transformers to improve their short-circuit withstand capability. Background Technology

[0002] Power transformers are the most important electrical equipment in a power system, responsible for transforming electrical energy from one voltage level to another. During grid operation, low-voltage side short-circuit impacts are one of the most significant factors causing transformer damage. Therefore, improving the short-circuit withstand capability of transformers is crucial to ensuring the safe and stable operation of transformers and even the entire power system.

[0003] Chinese patent application number 202110263387.X, entitled "A Method for Improving the Winding Structure to Enhance the Short-Circuit Resistance of Transformers," establishes a three-dimensional field-circuit coupling model of the transformer, calculates and analyzes locations where deformation is not required at the moment of a short circuit, and replaces potentially deformable locations with heat-resistant self-adhesive transposition wires to address the problem of low transformer winding strength under short-circuit impact. It can be seen that existing technologies mainly improve the short-circuit resistance of transformers through front-end design methods such as coil materials and winding methods, and theoretically verify the short-circuit resistance of the designed windings. However, this does not consider the impact of production processes and material dispersion on the transformer's short-circuit resistance. For example, slight differences between the actual and designed positions of the interlayer spacers in the windings, and deviations between the actual process and the ideal design technology of S-bend transposition, can all affect the transformer's short-circuit resistance to some extent. Moreover, the actual transformer manufacturing process relies solely on traditional experience, without quantitative analysis of each process step, and lacks standardized and unified digital control methods. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for controlling the production and manufacturing of transformers to improve their short-circuit withstand capability, with the aim of solving the problems in the background technology.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for controlling the manufacturing of transformers to improve their short-circuit withstand capability, comprising the following steps:

[0006] Step S1: Testing the bonding strength of copper wire raw materials; using a tensile testing machine to test the yield strength of copper wire and establishing a plastic deformation threshold prediction model;

[0007] Step S2: Coil winding process control; Use a winding machine to wind copper wire into a coil. During the winding process, control is carried out based on the geometric offset of the pads in the winding and the short-circuit resistance capability of the S-bend transposition damage in the winding.

[0008] Step S3: Control of coil clamping process; The wound coil is pre-clamped to form a winding. During this process, the strain is monitored by fiber optic sensing, and the clamping force is determined to be qualified by combining the dual parameters of micro-displacement change rate and cumulative strain. An early warning is issued for coils with insufficient clamping force. At the same time, the winding machine is dynamically adjusted according to the plastic deformation threshold prediction model to compensate for the tension of copper wire material during the winding process.

[0009] Step S4: Dynamic determination of the winding drying endpoint; The prepared winding is dried using a weather drying oven. During the winding drying process, insulating samples are placed in different positions in the weather drying oven, and the moisture content of each sample is monitored in real time. The moisture content change inside the winding is inverted based on multi-physics finite element analysis, and the winding is dried to the required process level.

[0010] The specific process of using a winding machine to wind copper wire coils, and controlling the short-circuit resistance capability based on the geometric offset of the pads in the winding and the transposition damage of the S-bends in the winding, is as follows: A three-dimensional model of the winding is reconstructed using laser scanning; the geometric offset of the pads is calculated based on the positional deviation and thickness deviation of the pads, and the installation of the pads is controlled; the absolute deviation between the measured curvature and the designed curvature of each S-bend is calculated based on the three-dimensional point cloud coordinates of the S-bend region in the winding three-dimensional model, quantifying the overall deformation and insulation damage of the S-bends and controlling the current winding process.

[0011] Furthermore, the measured abscissa of the pad was obtained based on the three-dimensional model of the winding. Actual thickness of pad block ; The x-axis was measured using the pad block and pad block design x-axis Calculate the position deviation of the winding pad ; The thickness was measured by the pad block and pad block design verification thickness Calculate the thickness deviation of the winding pad ;

[0012] Calculate the geometric offset of the pad block ,in, This indicates the magnification factor for the thickness deviation of the pad block. , Indicates the total number of turns in the winding. This indicates the number of winding turns at the spacer during the current winding process;

[0013] The specific process of controlling the installation of the shims based on their geometric offset is as follows:

[0014] when The next step is to install the pad block; when... Adjust the installation position of subsequent pads; when Stop and repair the windings.

[0015] Furthermore, after each S-bend is fabricated, several line laser sensors are arranged in the S-bend area to scan the winding S-bend. Based on the comparison between the scanning results and the design values, the S-bend curvature offset is calculated. ,in, Indicates the first Measured curvature at each measurement point Indicates the first The design curvature of each measurement point Indicates the first The effective arc of the line laser sensor scan. This indicates the total number of linear laser sensors deployed within the S-curve area;

[0016] Based on S-curvature offset The specific process for determining the degree of damage during S-bend transposition and controlling the current winding process is as follows:

[0017] when At that time, the S-bend was determined to be a minor insulation damage, the process was qualified, and it was released to the next S-bend process;

[0018] when Upon investigation, the S-bend was determined to be a minor insulation damage. The insulation process for the S-bend was then reinforced by wrapping it with twice the amount of insulating paper and ensuring the geometric offset of the pads on both sides of the S-bend was maintained. ;

[0019] when At that time, it was determined that the S-bend was severely damaged in insulation and the winding process deviation exceeded the standard, and the entire winding was re-winded.

[0020] Furthermore, in step S3, the winding compression control is achieved by real-time monitoring of strain distribution and displacement changes during the compression process, and by using laser displacement sensors and distributed fiber optic sensors to control the rate of micro-displacement change and cumulative strain of the winding during the compression process.

[0021] After the winding is formed, it is moved into a hydraulic clamping platform. High-precision laser displacement sensors are installed at the four corners of the clamping plate of the hydraulic clamping platform; the rate of change of micro-displacement of the winding per unit time during the clamping process is calculated. ,in, This represents the maximum displacement deviation collected by the four distributed fiber optic sensors between adjacent counting time points. The sampling frequency of the distributed fiber optic sensor;

[0022] A distributed optical fiber sensor is spirally wound onto the axial surface of the winding, covering the entire height of the winding. The optical fiber is tightly attached to the winding surface and fixed with high-temperature resistant adhesive. During the winding compression process, a laser is emitted to one end of the optical fiber, and the other end receives the reflected laser signal. The wavelength of the reflected light shifts due to the deformation of the optical fiber. The cumulative strain during the winding compression process is calculated. ,in, To compress the time; The timing of the compaction process; for The wavelength offset is measured at the fiber optic receiver at any given time. For strain-wavelength calibration coefficients; Indicates the integral;

[0023] When satisfied and If the winding is deemed properly tightened, then the winding must be tightened again. This indicates the acceptable lower limit value for cumulative strain.

[0024] Furthermore, in step S4, after the winding is formed, the internal moisture content of the winding is retrieved by multi-source data fusion to accurately determine the drying endpoint.

[0025] Three sample sheets are arranged in an equilateral triangle pattern in the upper, middle, and lower layers of the winding inside the drying oven, covering different radial areas of the winding. Two sample sheets are arranged in the axial heat dissipation channel of the winding, near the inlet and outlet of the channel, respectively, to monitor changes in the moisture content of the airflow. The sample sheets are in close contact with the surface of the winding. Each sample sheet is connected to a data acquisition module outside the drying oven through a quartz optical fiber that can withstand temperatures up to 500°C. The acquisition module communicates with the control system via an industrial Ethernet.

[0026] Based on the temperature field, humidity field, and airflow field inside the drying furnace, a thermal-humidity coupled multiphysics model is constructed to invert the moisture content distribution inside the winding:

[0027] Input parameters include: real-time monitoring data, thermal conductivity of winding insulation material, winding moisture diffusion coefficient, specific heat capacity, and drying oven volume; real-time monitoring data includes the moisture content of each paper sample, temperature of each area inside the drying oven, and airflow velocity inside the drying oven.

[0028] A multiphysics model of transformer temperature, humidity, and airflow is built for transient analysis. The boundary conditions are updated at intervals based on the input parameters, and the output is a cloud map of the moisture content distribution inside the winding. The boundary conditions include sample data and furnace parameters.

[0029] Based on the inverted internal moisture content distribution and sample monitoring data, a multi-indicator collaborative judgment standard was formulated:

[0030] Standard 1: The moisture content in all areas inside the winding is ≤0.5%;

[0031] Standard 2: Within 30 consecutive minutes, the rate of change in moisture content of each paper sample is ≤0.01% / h;

[0032] Standard 3: The difference in internal moisture content between any two layers of the upper, middle, and lower windings is ≤0.2%;

[0033] When all three criteria are met simultaneously, the drying process is considered complete and automatically stops. If any criterion is not met, drying continues and the drying oven process parameters are dynamically adjusted.

[0034] Furthermore, the specific process of continuing drying and dynamically adjusting the drying oven process parameters is as follows: if the moisture content inside the upper layer is greater than that of the middle / lower layer, increase the temperature of the upper layer in the drying oven or increase the airflow velocity in the upper layer of the drying oven; if the moisture content in a local area of ​​the winding is too high, focus on that area and enhance the hot air circulation; if the rate of decrease in the moisture content of the sample paper is less than 0.1% / h, reduce the oven temperature.

[0035] Furthermore, the plastic deformation threshold prediction model is expressed as:

[0036] ;

[0037] In the formula, This represents the predicted value of the plastic deformation threshold. This indicates the measured yield strength of the copper conductor. Indicates ambient temperature; Indicates the operating reference temperature; Indicates the winding tension of the winding machine; Indicates the fatigue strength of copper wire; Indicates the cross-sectional area of ​​the copper conductor; The base of the natural logarithm; This represents a coefficient related to the effect of temperature.

[0038] The winding machine is dynamically adjusted based on the plastic deformation threshold prediction model to compensate for the tension of the copper wire material during the winding process, as expressed as:

[0039] ;

[0040] In the formula, Indicates the safety compensation coefficient; This indicates a command sent to the winding machine to adjust the tension.

[0041] A transformer manufacturing control system for improving short-circuit withstand capability, used in a transformer manufacturing control method for improving short-circuit withstand capability, comprising:

[0042] The strength testing module is used to test the bonding strength of copper wire raw materials; a tensile testing machine is used to test the yield strength of copper wires and to establish a plastic deformation threshold prediction model.

[0043] The coil winding process control module is used to control the coil winding process; a winding machine is used to wind copper wire into coils. During the winding process, the module controls the coil winding process based on the geometric offset of the pads in the winding and the short-circuit resistance capability of the S-bend transposition damage in the winding.

[0044] The coil clamping process control module is used to control the coil clamping process. It pre-clamps the wound coil to form a winding. During this process, it monitors the strain based on fiber optic sensors and determines whether the clamping force is qualified by combining the dual parameters of micro-displacement change rate and cumulative strain. It issues an early warning for coils with insufficient clamping force. At the same time, it dynamically adjusts the winding machine according to the plastic deformation threshold prediction model to compensate for the tension of the copper wire material during the winding process.

[0045] The winding drying endpoint dynamic determination module is used to dynamically determine the winding drying endpoint. The prepared winding is dried using a weather drying oven. During the winding drying process, insulating samples are placed in different positions in the weather drying oven to monitor the change in moisture content of each sample in real time. The change in internal moisture content of the winding is inverted based on multiphysics finite element analysis, and the winding is dried to the required process level.

[0046] An electronic device includes a processor, a memory, and a bus, wherein the processor and the memory are connected via the bus, wherein the memory is used to store a set of program code, and the processor is used to call the program code stored in the memory to execute a transformer manufacturing control method for improving short-circuit withstand capability.

[0047] A non-volatile computer storage medium storing computer-executable instructions that execute a transformer manufacturing control method to improve short-circuit withstand capability.

[0048] Compared with existing technologies, the present invention has the following advantages:

[0049] Optimize key process steps: By comprehensively controlling key aspects such as the mechanical strength of copper wire and coil winding, the problem of unstable transformer short-circuit withstand capability caused by traditional experience-based operations is solved. The bonding strength of copper wire raw materials is accurately detected and compensated to ensure mechanical strength to withstand electrodynamic forces; the coil winding process is controlled to avoid short-circuit faults caused by quality problems; the winding clamping process is precisely controlled to ensure uniform and compliant clamping force; the winding drying endpoint is accurately determined to avoid over-drying or under-drying, so as to achieve the optimal drying degree and improve the transformer's short-circuit withstand capability and operational reliability.

[0050] Achieving digital management and control: Real-time data closed-loop control changes the traditional production model that relies solely on worker experience and subjective judgment. By using sensors and monitoring equipment to acquire data in real time, and then analyzing and processing it through models and algorithms, scientific basis is provided for production decisions, achieving digital and intelligent management and control, and improving production efficiency and product quality stability. Attached Figure Description

[0051] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0052] like Figure 1 As shown, the present invention provides a technical solution: a method for controlling the production and manufacturing of transformers to improve their short-circuit withstand capability, comprising the following steps:

[0053] Step S1: Testing the bonding strength of copper wire raw materials.

[0054] The yield strength of copper wire (self-adhesive transposition wire) was tested using a tensile testing machine, and a plastic deformation threshold prediction model was established.

[0055] Step S2: Control of coil winding process.

[0056] A winding machine is used to wind copper wire into coils. During the winding process, the short-circuit resistance capability is controlled based on the geometric offset of the spacers in the winding and the transposition damage of the S-bends in the winding: a three-dimensional model of the winding is reconstructed by laser scanning; the geometric offset of the spacers is calculated based on the position deviation and thickness deviation of the spacers, and the installation of the spacers is controlled; the absolute deviation between the measured curvature and the designed curvature of each S-bend segment is calculated based on the three-dimensional point cloud coordinates of the S-bend region in the winding three-dimensional model. This allows for the quantification of the overall deformation and insulation damage of the S-bend and the control of the current winding process.

[0057] Step S3: Control of coil clamping process.

[0058] The wound coil is pre-tightened to form a winding. During this process, strain is monitored by fiber optic sensors, and the tightness is determined by combining the micro-displacement change rate and cumulative strain as dual parameters. An early warning is issued for coils with insufficient tightness. At the same time, the winding machine is dynamically adjusted according to the plastic deformation threshold prediction model to compensate for the tension of the copper wire material during the winding process.

[0059] Step S4: Dynamic determination of the winding drying end point.

[0060] The fabricated windings are dried using a weather drying oven. During the drying process, insulating samples are placed at different locations in the oven to monitor the moisture content changes of each sample in real time. The internal moisture content changes of the windings are inverted based on multiphysics finite element analysis, and the windings are dried to the required process conditions.

[0061] The plastic deformation threshold prediction model is expressed as follows:

[0062] ;

[0063] In the formula, This represents the predicted value of the plastic deformation threshold. This indicates the measured yield strength of the copper conductor. Indicates ambient temperature; Indicates the operating reference temperature (taken as 75℃); Indicates the winding tension of the winding machine; Indicates the fatigue strength of copper wire; Indicates the cross-sectional area of ​​the copper conductor; The base of the natural logarithm; This represents a coefficient related to the effect of temperature, used to describe the influence of temperature on the plastic deformation threshold.

[0064] The method of dynamically adjusting the winding machine based on the plastic deformation threshold prediction model to compensate for the tension of the copper wire material during the winding process can be expressed as follows:

[0065] ;

[0066] In the formula, This represents the safety compensation coefficient, which is usually taken as 1.2; This indicates a command sent to the winding machine to adjust the tension.

[0067] Among them, an accuracy of ±0.1 mm and a sampling density of 200 points / cm² were used. 2 A linear laser sensor scans the winding to obtain the thickness of the spacer blocks, the installation position of the spacer blocks, and the S-bend rate in the winding; the short-circuit withstand capability of the winding is improved by controlling the geometric offset of the spacer blocks and the damage of the S-bend transposition.

[0068] Among them, the position deviation of the pad block The absolute deviation between the measured position of the spacer block and the designed position of the winding spacer block is given by , where . This represents the measured x-coordinate of the pad block. The horizontal axis represents the design of the pad block; the thickness deviation of the pad block. This represents the absolute deviation between the measured thickness of the spacer block and its designed thickness. This indicates the actual measured thickness of the pad. This indicates the thickness of the pad block during design verification.

[0069] Among them, the measured x-axis of the pad block Actual thickness of pad block All of these can be obtained from the three-dimensional model of the winding.

[0070] The geometric offset of the pad block is expressed as: ,in, This indicates the amplification factor for the thickness deviation of the pad block. It mainly considers that the thickness deviation of the pad block has a greater impact on the mechanical stability of the winding, and that the pad blocks at both ends of the winding have a greater impact on the short-circuit withstand capability of the transformer winding than those at the middle of the winding. , Indicates the total number of turns in the winding. This indicates the number of winding turns at the spacer during the current winding process.

[0071] The specific process of controlling the installation of the shims based on their geometric offset can be represented as follows:

[0072] .

[0073] After each S-bend is constructed, several sampling points with an accuracy of ±0.1mm and a sampling density of 200 points / cm are arranged in the S-bend area. 2 A linear laser sensor scans the S-bend of the winding, and the S-bend rate offset is calculated by comparing the scan results with the design value. The S-curvature offset is represented as the weighted integral of the curvature deviation in the S-bend region, reflecting the overall deformation degree of the S-bend. Indicates the first Measured curvature at each measurement point Indicates the first The design curvature of each measurement point Indicates the first The effective arc of the line laser sensor scan. This indicates the total number of linear laser sensors deployed within the S-curve area.

[0074] Among them, according to the S-curvature offset The specific process for determining the degree of damage during S-bend transposition and controlling the current winding process is as follows:

[0075] 1. When If the S-bend is determined to have minor insulation damage and the process is qualified, it can be released to the next S-bend process.

[0076] 2. When If the S-bend is determined to be a minor insulation damage, the insulation process needs to be strengthened. Twice the amount of insulating paper should be used to wrap the S-bend, and the geometric offset of the pads on both sides of the S-bend should be ensured. ;

[0077] 3. When At that time, it was determined that the S-bend was severely damaged in insulation, the winding process deviation exceeded the standard, and the winding had to be rewound as a whole.

[0078] In step S3, the winding clamping control is achieved by real-time monitoring of strain distribution and displacement changes during the clamping process. Laser displacement sensors and distributed fiber optic sensors are used to control the rate of change of micro-displacement and cumulative strain of the winding during clamping, ensuring that the axial clamping force of the winding is uniform and meets the standard, thus preventing winding instability due to insufficient local clamping during a short circuit. Specifically:

[0079] After the winding is formed, it is moved into a hydraulic clamping platform. High-precision laser displacement sensors are installed at the four corners of the clamping plate of the hydraulic clamping platform; the rate of change of micro-displacement of the winding per unit time during the clamping process is measured. ,in, This represents the maximum displacement deviation collected by the four distributed fiber optic sensors between adjacent counting time points. This refers to the acquisition frequency of the distributed fiber optic sensor.

[0080] A distributed fiber optic sensor is spirally wound onto the axial surface of the winding, covering the entire height of the winding. The fiber optics are tightly attached to the winding surface and fixed with high-temperature resistant adhesive. During the winding compression process, a laser is emitted to one end of the fiber, and the other end receives the reflected laser signal. The wavelength of the reflected light shifts due to fiber deformation. The cumulative strain during the winding compression process is also considered. Represented as:

[0081] ;

[0082] In the formula, To compress the time; The timing of the compaction process; for The wavelength offset is measured at the fiber optic receiver at any given time. For strain-wavelength calibration coefficients; This represents the integral.

[0083] The rate of change of micro-displacement reflects the overall compaction of the winding. If it is not up to standard, it indicates that the overall compaction of the winding is insufficient, and the transformer will become axially unstable when an external short circuit occurs. The cumulative strain reflects the dynamic stability of the winding compaction process. If it is not up to standard, it indicates that the local winding strength is insufficient, and the transformer will become locally radially unstable when an external short circuit occurs.

[0084] When satisfied and If the winding is deemed properly tightened, it is considered acceptable; otherwise, the winding needs to be tightened again. This indicates the acceptable lower limit value for cumulative strain.

[0085] In step S4, after the winding is formed, the internal moisture content of the winding is inverted by multi-source data fusion to accurately determine the drying endpoint, avoiding insulation embrittlement due to over-drying or partial discharge caused by under-drying. Existing transformer winding drying processes represent the winding drying status by directly measuring the surface moisture content of a sample paper. However, the directly measured sample paper moisture content only represents the surface; the internal moisture content of the winding has a humidity gradient due to uneven thermal field. This invention provides a method for inverting the internal drying status of the winding using a thermal-humidity coupling model based on sample paper surface data. The specific implementation method is as follows:

[0086] Three sample sheets are arranged in an equilateral triangle (100mm spacing) in the upper, middle (center, and lower layers) of the windings inside the drying oven, covering different radial areas of the windings. Two sample sheets are placed near the axial heat dissipation channel of the windings, near the inlet and outlet respectively, to monitor changes in the moisture content of the airflow. The sample sheets are tightly fitted to the winding surface (fixed with high-temperature resistant silicone) to prevent air gaps from affecting moisture conduction. Each sample sheet is connected to a data acquisition module outside the drying oven (sampling accuracy 0.01%, resolution 0.001%) via a quartz optical fiber resistant to 500℃. The acquisition module communicates with the control system via industrial Ethernet to ensure data transmission delay ≤1s.

[0087] Based on the temperature field, humidity field, and airflow field inside the drying furnace, a thermal-humidity coupled multiphysics model is constructed to invert the moisture content distribution inside the winding:

[0088] Input parameters include: real-time monitoring data (moisture content of each paper sample, temperature of each area in the drying oven, airflow velocity in the drying oven), thermal conductivity of winding insulation material, winding moisture diffusion coefficient, specific heat capacity, and drying oven volume.

[0089] A multiphysics model of transformer temperature, humidity and airflow is built for transient analysis. The boundary conditions (sample data, furnace parameters) are updated every 5 minutes based on the input parameters, and the moisture content distribution cloud map inside the winding is output.

[0090] Based on the inverted internal moisture content distribution and sample monitoring data, a multi-indicator collaborative judgment standard was formulated:

[0091] Standard 1: The moisture content in all areas inside the winding is ≤0.5%;

[0092] Standard 2: Within 30 consecutive minutes, the rate of change in moisture content of each paper sample is ≤0.01% / h (indicating that moisture evaporation tends to stop).

[0093] Standard 3: The difference in internal moisture content between any two layers of the upper, middle, and lower windings should be ≤0.2% (to avoid excessive local humidity).

[0094] When all three conditions above are met simultaneously, the drying process is considered complete and automatically stops. If any condition is not met, drying continues while the drying oven process parameters are dynamically adjusted to ensure uniform and repeatable drying. Specifically:

[0095] 1. If the moisture content inside the upper layer is greater than that of the middle / lower layer: increase the temperature of the upper layer in the furnace (increase ≤ 5℃) or increase the airflow velocity in the upper layer (increase ≤ 0.2m / s).

[0096] 2. If the moisture content is too high in a local area (such as the end of the winding): focus on that area to enhance hot air circulation (open the directional air duct);

[0097] 3. If the moisture content of the sample paper decreases at a rate of <0.1% / h (close to the endpoint): reduce the furnace temperature (to 80±5℃) to avoid overheating and embrittlement of the insulation material.

[0098] A transformer manufacturing control system for improving short-circuit withstand capability, used in a transformer manufacturing control method for improving short-circuit withstand capability, comprising:

[0099] The strength testing module is used to test the bonding strength of copper wire raw materials; a tensile testing machine is used to test the yield strength of copper wires and to establish a plastic deformation threshold prediction model.

[0100] The coil winding process control module is used to control the coil winding process; a winding machine is used to wind copper wire into coils. During the winding process, the module controls the coil winding process based on the geometric offset of the pads in the winding and the short-circuit resistance capability of the S-bend transposition damage in the winding.

[0101] The coil clamping process control module is used to control the coil clamping process. It pre-clamps the wound coil to form a winding. During this process, it monitors the strain based on fiber optic sensors and determines whether the clamping force is qualified by combining the dual parameters of micro-displacement change rate and cumulative strain. It issues an early warning for coils with insufficient clamping force. At the same time, it dynamically adjusts the winding machine according to the plastic deformation threshold prediction model to compensate for the tension of the copper wire material during the winding process.

[0102] The winding drying endpoint dynamic determination module is used to dynamically determine the winding drying endpoint. The prepared winding is dried using a weather drying oven. During the winding drying process, insulating samples are placed in different positions in the weather drying oven to monitor the change in moisture content of each sample in real time. The change in internal moisture content of the winding is inverted based on multiphysics finite element analysis, and the winding is dried to the required process level.

[0103] An electronic device includes a processor, a memory, and a bus, wherein the processor and the memory are connected via the bus, wherein the memory is used to store a set of program code, and the processor is used to call the program code stored in the memory to execute a transformer manufacturing control method for improving short-circuit withstand capability.

[0104] A non-volatile computer storage medium storing computer-executable instructions that execute a transformer manufacturing control method to improve short-circuit withstand capability.

[0105] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for controlling the manufacturing process of transformers to improve their short-circuit withstand capability, characterized in that, Includes the following steps: Step S1: Testing the bonding strength of copper wire raw materials; using a tensile testing machine to test the yield strength of copper wire and establishing a plastic deformation threshold prediction model; Step S2: Coil winding process control; Use a winding machine to wind copper wire into a coil. During the winding process, control is carried out based on the geometric offset of the pads in the winding and the short-circuit resistance capability of the S-bend transposition damage in the winding. Step S3: Control of coil clamping process; The wound coil is pre-clamped to form a winding. During this process, the strain is monitored by fiber optic sensing, and the clamping force is determined to be qualified by combining the dual parameters of micro-displacement change rate and cumulative strain. An early warning is issued for coils with insufficient clamping force. At the same time, the winding machine is dynamically adjusted according to the plastic deformation threshold prediction model to compensate for the tension of copper wire material during the winding process. Step S4: Dynamic determination of the winding drying endpoint; The prepared winding is dried using a weather drying oven. During the winding drying process, insulating samples are placed in different positions in the weather drying oven, and the moisture content of each sample is monitored in real time. The moisture content change inside the winding is inverted based on multi-physics finite element analysis, and the winding is dried to the required process level. The specific process of using a winding machine to wind copper wire coils, and controlling the short-circuit resistance capability based on the geometric offset of the pads in the winding and the transposition damage of the S-bends in the winding, is as follows: A three-dimensional model of the winding is reconstructed using laser scanning; the geometric offset of the pads is calculated based on the positional deviation and thickness deviation of the pads, and the installation of the pads is controlled; the absolute deviation between the measured curvature and the designed curvature of each S-bend is calculated based on the three-dimensional point cloud coordinates of the S-bend area in the winding three-dimensional model, quantifying the overall deformation and insulation damage of the S-bends and controlling the current winding process; Measured x-coordinate of pad based on three-dimensional model of winding Actual thickness of pad block ; The x-axis was measured using the pad block and pad block design x-axis Calculate the position deviation of the winding pad ; The thickness was measured by the pad block and pad block design verification thickness Calculate the thickness deviation of the winding pad ; Calculate the geometric offset of the pad block ,in, This indicates the magnification factor for the thickness deviation of the pad block. , Indicates the total number of turns in the winding. This indicates the number of winding turns at the spacer during the current winding process; The specific process of controlling the installation of the shims based on their geometric offset is as follows: when Proceed to the next block installation step; when Adjust the installation position of subsequent pads; when Stop and repair the windings; The plastic deformation threshold prediction model is expressed as follows: ； In the formula, This represents the predicted value of the plastic deformation threshold. This indicates the measured yield strength of the copper conductor. Indicates ambient temperature; Indicates the operating reference temperature; Indicates the winding tension of the winding machine; Indicates the fatigue strength of copper wire; Indicates the cross-sectional area of ​​the copper conductor; The base of the natural logarithm; This represents a coefficient related to the effect of temperature. The winding machine is dynamically adjusted based on the plastic deformation threshold prediction model to compensate for the tension of the copper wire material during the winding process, as expressed as: ； In the formula, Indicates the safety compensation coefficient; This indicates a command sent to the winding machine to adjust the tension.

2. The method for controlling the production of transformers to improve short-circuit withstand capability according to claim 1, characterized in that: After each S-bend is fabricated, several line laser sensors are arranged in the S-bend area to scan the winding S-bend. Based on the comparison between the scanning results and the design values, the S-bend curvature offset is calculated. ,in, Indicates the first Measured curvature at each measurement point Indicates the first The design curvature of each measurement point Indicates the first The effective arc of the line laser sensor scan. This indicates the total number of linear laser sensors deployed within the S-curve area; Based on S-curvature offset The specific process for determining the degree of damage during S-bend transposition and controlling the current winding process is as follows: when At that time, the S-bend was determined to be a minor insulation damage, the process was qualified, and it was released to the next S-bend process; when Upon investigation, the S-bend was determined to be a minor insulation damage. The insulation process was then reinforced by wrapping the S-bend with twice the amount of insulating paper and adjusting the geometric offset of the pads on both sides of the S-bend. ; when At that time, it was determined that the S-bend was severely damaged in insulation and the winding process deviation exceeded the standard, and the entire winding was re-winded.

3. The method for controlling the production and manufacturing of a transformer to improve its short-circuit withstand capability according to claim 2, characterized in that: In step S3, the winding compression control is achieved by real-time monitoring of strain distribution and displacement changes during the compression process, and by using laser displacement sensors and distributed fiber optic sensors to control the rate of micro-displacement change and cumulative strain of the winding during the compression process. After the winding is formed, it is moved into a hydraulic clamping platform. High-precision laser displacement sensors are installed at the four corners of the clamping plate of the hydraulic clamping platform; the rate of change of micro-displacement of the winding per unit time during the clamping process is calculated. ,in, This represents the maximum displacement deviation collected by the four distributed fiber optic sensors between adjacent counting time points. The sampling frequency of the distributed fiber optic sensor; A distributed optical fiber sensor is spirally wound onto the axial surface of the winding, covering the entire height of the winding. The optical fiber is tightly attached to the winding surface and fixed with high-temperature resistant adhesive. During the winding compression process, a laser is emitted to one end of the optical fiber, and the reflected laser signal is received at the other end. The wavelength of the reflected laser signal shifts due to the deformation of the optical fiber. The cumulative strain during the winding compression process is calculated. ,in, To compress the time; The timing of the compaction process; for The wavelength offset is measured at the fiber optic receiver at any given time. For strain-wavelength calibration coefficients; Indicates the integral; When satisfied and If the winding is deemed properly tightened, then the winding must be tightened again. This indicates the acceptable lower limit value for cumulative strain.

4. The method for controlling the production and manufacturing of a transformer to improve its short-circuit withstand capability according to claim 3, characterized in that: In step S4, after the winding is formed, the moisture content inside the winding is retrieved by multi-source data fusion to determine the drying endpoint. Three sample sheets were arranged in an equilateral triangle pattern in the upper, middle, and lower layers of the winding inside the drying oven, covering different radial areas of the winding; two sample sheets were arranged in the axial heat dissipation channel of the winding, near the inlet and outlet of the channel, respectively, to monitor the change in moisture content of the airflow; the sample sheets were in close contact with the surface of the winding. Each sample sheet is connected to a data acquisition module outside the drying oven via a quartz optical fiber. The data acquisition module communicates with the control system via an industrial Ethernet. Based on the temperature field, humidity field, and airflow field inside the drying furnace, a thermal-humidity coupled multiphysics model is constructed to invert the moisture content distribution inside the winding: Input parameters include: real-time monitoring data, thermal conductivity of winding insulation material, winding moisture diffusion coefficient, specific heat capacity, and drying oven volume; real-time monitoring data includes the moisture content of each paper sample, temperature of each area inside the drying oven, and airflow velocity inside the drying oven. A multiphysics model of transformer temperature, humidity, and airflow is built for transient analysis. The boundary conditions are updated at intervals based on the input parameters, and the output is a cloud map of the moisture content distribution inside the winding. The boundary conditions include sample paper data and parameters inside the drying oven. Based on the inverted internal moisture content distribution and sample monitoring data, a multi-indicator collaborative judgment standard was formulated: Standard 1: The moisture content in all areas inside the winding is ≤0.5%; Standard 2: Within 30 consecutive minutes, the rate of change in moisture content of each paper sample is ≤0.01% / h; Standard 3: The difference in internal moisture content between any two layers of the upper, middle, and lower windings is ≤0.2%; When all three criteria are met simultaneously, the drying process is automatically stopped, marking the end of the drying process. If any criterion is not met, continue drying and dynamically adjust the drying oven process parameters.

5. The method for controlling the production and manufacturing of a transformer to improve its short-circuit withstand capability according to claim 4, characterized in that: The specific process of continuing drying and dynamically adjusting the drying oven process parameters is as follows: if the moisture content inside the upper layer is greater than that of the middle / lower layer, increase the temperature of the upper layer in the drying oven or increase the airflow velocity of the upper layer in the drying oven; if the moisture content in a local area of ​​the winding is greater than the preset value, focus on that area to enhance hot air circulation; if the moisture content of the sample paper decreases at a rate of less than 0.1% / h, lower the oven temperature.

6. A transformer manufacturing control system for improving short-circuit withstand capability, used in the transformer manufacturing control method for improving short-circuit withstand capability as described in any one of claims 1-5, characterized in that, include: The strength testing module is used to test the bonding strength of copper wire raw materials; The yield strength of copper wires was tested using a tensile testing machine, and a predictive model for the plastic deformation threshold was established. The coil winding process control module is used to control the coil winding process; a winding machine is used to wind copper wire into coils. During the winding process, the module controls the coil winding process based on the geometric offset of the pads in the winding and the short-circuit resistance capability of the S-bend transposition damage in the winding. The coil clamping process control module is used to control the coil clamping process. It pre-clamps the wound coil to form a winding. During this process, it monitors the strain based on fiber optic sensors and determines whether the clamping force is qualified by combining the dual parameters of micro-displacement change rate and cumulative strain. It issues an early warning for coils with insufficient clamping force. At the same time, it dynamically adjusts the winding machine according to the plastic deformation threshold prediction model to compensate for the tension of the copper wire material during the winding process. The winding drying endpoint dynamic determination module is used to dynamically determine the winding drying endpoint. The prepared winding is dried using a weather drying oven. During the winding drying process, insulating samples are placed in different positions in the weather drying oven to monitor the change in moisture content of each sample in real time. The change in internal moisture content of the winding is inverted based on multiphysics finite element analysis, and the winding is dried to the required process level.

7. An electronic device, characterized in that, The device includes a processor, a memory, and a bus, wherein the processor and the memory are connected via the bus, the memory is used to store a set of program code, and the processor is used to call the program code stored in the memory to execute a transformer manufacturing control method for improving short-circuit withstand capability as described in any one of claims 1-5.

8. A non-volatile computer storage medium storing computer-executable instructions, characterized in that, The computer can execute instructions to perform a transformer manufacturing control method for improving short-circuit withstand capability as described in any one of claims 1-5.

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