A calibration method for high-frequency spark machines based on machining accuracy and stability control

Abstract

The present invention discloses a high-frequency spark machine calibration method based on machining accuracy and stability control, which relates to the field of mechanical calibration. The method includes: analyzing collected operating data and establishing a data analysis model; dynamically adjusting the resonant frequency based on the output frequency, and eliminating electromagnetic interference through optical fiber signal transmission; constructing an environmental compensation mathematical model to automatically correct voltage deviations caused by environmental changes; simultaneously detecting fundamental frequency and harmonic components to identify and compensate for frequency deviations caused by nonlinear distortion; designing an adaptive sensitivity adjustment mechanism to dynamically adjust the detection threshold based on defect type and size, and automatically adjust the sensitivity parameters of the high-frequency spark machine; predicting the stability of the mechanical structure by simulating the assembly process; and automatically adjusting the damping parameters of the mechanical structure to improve the stability of the high-frequency spark machine equipment. By improving the performance and stability of the high-frequency spark machine, product quality and production efficiency are guaranteed.

Description

Technical Field

[0001] The invention relates to the field of mechanical calibration, and in particular to a high-frequency spark machine calibration method based on processing accuracy and stability control. Background Art

[0002] High-frequency spark machines play a crucial role in precision machining and quality inspection in modern manufacturing. Leveraging their unique detection principles, they can accurately identify minute surface and internal defects, such as cracks and inclusions, within materials, providing a key basis for product quality control. From the aerospace sector's stringent requirements for high-precision and high-reliability components to the electronics industry's zero tolerance for minor component defects, high-frequency spark machines are used throughout numerous key industrial sectors. Their detection accuracy and stability are directly linked to the quality and performance of the final product. Any deviation can lead to substandard products entering the market, posing safety risks and causing significant economic losses.

[0003] High-frequency spark machines are a key piece of equipment widely used for insulation testing of wires and cables. Their machining accuracy and stability directly impact product quality and production efficiency. As the wire and cable industry continues to demand higher quality, the calibration of high-frequency spark machines has become increasingly important. However, traditional calibration methods often focus on adjusting electrical parameters, overlooking the impact of various factors, such as mechanical structure and operating status, on machining accuracy and stability. Therefore, proposing a high-frequency spark machine calibration method based on machining accuracy and stability control is of great practical significance. Summary of the Invention

[0004] In order to solve the above technical problems, a high-frequency spark machine calibration method based on processing accuracy and stability control is provided. This technical solution solves the problems raised in the above background technology.

[0005] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0006] A high-frequency spark machine calibration method based on processing accuracy and stability control, comprising:

[0007] Analyze the collected operating data, establish a data analysis model, and analyze the operating trends and performance changes of the high-frequency spark machine by comparing historical data with standard data;

[0008] A tunable sinusoidal oscillation circuit is connected in parallel to the output end of the high-frequency spark machine to dynamically adjust the resonant frequency based on the output frequency, and transmit the signal through optical fiber to eliminate electromagnetic interference;

[0009] During the calibration process, the ambient temperature, humidity and air pressure are monitored in real time, and an environmental compensation mathematical model is constructed to automatically correct voltage deviations caused by environmental changes.

[0010] A dual-channel oscilloscope is used, one channel monitors the output frequency of the high-frequency spark machine, and the other channel synchronously monitors the reference frequency source, simultaneously detecting the fundamental frequency and harmonic components, identifying and compensating for frequency deviation caused by nonlinear distortion;

[0011] Prepare a standard sample containing at least one type of defect, design an adaptive sensitivity adjustment mechanism, dynamically adjust the detection threshold based on the defect type and size, and automatically adjust the sensitivity parameters of the high-frequency spark machine;

[0012] Scan the mechanical structure of the high-frequency spark machine and design a virtual assembly simulation system to predict the stability of the mechanical structure by simulating the assembly process;

[0013] Identify the resonant frequency and vibration mode of the mechanical structure, automatically adjust the damping parameters of the mechanical structure, and improve the stability of the high-frequency spark machine equipment.

[0014] Preferably, the dual-channel oscilloscope is used, one channel monitors the output frequency of the high-frequency spark machine, and the other channel synchronously monitors the reference frequency source, and simultaneously detects the fundamental frequency and harmonic components, and identifies and compensates for the frequency deviation caused by nonlinear distortion. Specifically, the method includes:

[0015] Obtaining a reference frequency signal, the frequency of which is related to the expected output frequency of the high-frequency spark machine;

[0016] Connect the output terminal of the high-frequency spark machine, the reference frequency source and the input channel of the dual-channel oscilloscope;

[0017] Set the oscilloscope's sampling rate, bandwidth, and trigger mode parameters based on the high-frequency spark machine's output frequency range and expected harmonic content;

[0018] Observe the waveform shape, amplitude and frequency characteristics of the high-frequency spark machine output signal and the reference frequency source signal to preliminarily determine whether the signal is abnormal;

[0019] Perform spectrum analysis on the high-frequency spark machine output signal and the reference frequency source signal, observe the spectrum diagram, and determine the position and amplitude of the fundamental frequency and the distribution of harmonic components;

[0020] Measure the amplitude of each harmonic and compare it with the amplitude of the fundamental frequency to analyze whether the harmonic amplitude increases abnormally;

[0021] Measure the frequencies of the high-frequency spark machine output signal and the reference frequency source signal respectively, calculate the difference between the high-frequency spark machine output frequency and the reference frequency, and output it as the frequency deviation between the two;

[0022] Observe the change of frequency deviation over time and analyze the stability of the output frequency of the high-frequency spark machine;

[0023] Based on the spectrum analysis results and frequency deviation, determine whether the output signal of the high-frequency spark machine has nonlinear distortion. If so, check whether the circuit elements of the high-frequency spark machine have nonlinear characteristics. If not, do not output. The circuit elements include transistors, diodes, inductors and capacitors.

[0024] Adjust the circuit component parameters. Based on the results of spectrum analysis, adjust the circuit component parameters of the high-frequency spark machine and add a filter circuit. Add a filter circuit at the output end of the high-frequency spark machine to suppress harmonic components and improve signal purity.

[0025] Preferably, the preparation of a standard sample containing at least one type of defect, designing an adaptive sensitivity adjustment mechanism, dynamically adjusting the detection threshold based on the defect type and size, and automatically adjusting the sensitivity parameters of the high-frequency spark machine specifically include:

[0026] Based on actual testing requirements, cracks, pores and inclusions are selected as defect characteristics of standard samples;

[0027] For crack defects, at least two sets of cracks with different lengths, widths, and depths were created on the sample surface using mechanical processing methods;

[0028] For pore defects, pores are formed inside the sample by chemical etching. The sample is immersed in a corrosion solution, and the etching time and temperature are controlled to obtain pores of the desired size and distribution.

[0029] For inclusion defects, inclusions are added during sample preparation, and after the inclusions are evenly mixed with the matrix material, the sample is made through a casting process;

[0030] Conduct quality inspection on the prepared standard samples to ensure that the size, shape and distribution of defects meet the design requirements;

[0031] Analyze the signal image detected by the high-frequency spark machine using an image processing algorithm to extract characteristic parameters of the defect, including the length, width, area and shape factor of the defect;

[0032] Analyze the electrical signal output by the high-frequency spark machine and extract the frequency, amplitude and phase characteristics of the signal;

[0033] Establish a defect type recognition model and determine the defect type based on the extracted defect characteristic parameters;

[0034] Establish a correlation model between the sensitivity parameters of the high-frequency spark machine and the detection threshold, and determine the quantitative relationship between the sensitivity parameters and the detection threshold through experiments and data analysis. The sensitivity parameters include discharge voltage, discharge frequency and discharge gap.

[0035] Design an automatic adjustment algorithm to automatically calculate and adjust the sensitivity parameters of the high-frequency spark machine based on the dynamically adjusted detection threshold;

[0036] During the high-frequency spark machine inspection process, the inspection results and changes in sensitivity parameters are monitored in real time. Through a closed-loop control system, the inspection results are compared with the preset target values, and the sensitivity parameters are adjusted based on the deviation.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] By comparing historical data with standard data, the operating trends and performance changes of high-frequency spark machines are accurately analyzed. Optical fiber is used to transmit signals, effectively eliminating electromagnetic interference and ensuring the stability of signal transmission. Voltage deviations caused by environmental changes are automatically corrected, improving the adaptability and stability of equipment under different environmental conditions. At the same time, the fundamental frequency and harmonic components are detected, frequency deviations caused by nonlinear distortion are identified and compensated, and detection accuracy is improved, providing strong support for quality inspection and precision processing in the manufacturing industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of a high-frequency spark machine calibration method based on machining accuracy and stability control according to the present invention;

[0040] Figure 2 A flow chart of a method for analyzing the operating trend and performance change of a high-frequency spark machine according to the present invention;

[0041] Figure 3 This is a flow chart of the method for dynamically adjusting the resonant frequency based on the output frequency of the present invention;

[0042] Figure 4 This is a flow chart of the method for constructing an environmental compensation mathematical model and automatically correcting voltage deviations caused by environmental changes in the present invention;

[0043] Figure 5 This is a flow chart of the method for identifying and compensating for frequency deviation caused by nonlinear distortion of the present invention;

[0044] Figure 6 Flowchart of the method for designing an adaptive sensitivity adjustment mechanism of the present invention;

[0045] Figure 7 This is a flow chart of the method for predicting the stability of a mechanical structure by simulating the assembly process of the present invention. DETAILED DESCRIPTION

[0046] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0047] Reference Figure 1 As shown, a high-frequency spark machine calibration method based on processing accuracy and stability control includes:

[0048] Analyze the collected operating data, establish a data analysis model, and analyze the operating trends and performance changes of the high-frequency spark machine by comparing historical data with standard data;

[0049] A tunable sinusoidal oscillation circuit is connected in parallel to the output end of the high-frequency spark machine to dynamically adjust the resonant frequency based on the output frequency, and transmit the signal through optical fiber to eliminate electromagnetic interference;

[0050] During the calibration process, the ambient temperature, humidity and air pressure are monitored in real time, and an environmental compensation mathematical model is constructed to automatically correct voltage deviations caused by environmental changes.

[0051] A dual-channel oscilloscope is used, one channel monitors the output frequency of the high-frequency spark machine, and the other channel synchronously monitors the reference frequency source, simultaneously detecting the fundamental frequency and harmonic components, identifying and compensating for frequency deviation caused by nonlinear distortion;

[0052] Prepare a standard sample containing at least one type of defect, design an adaptive sensitivity adjustment mechanism, dynamically adjust the detection threshold based on the defect type and size, and automatically adjust the sensitivity parameters of the high-frequency spark machine;

[0053] Scan the mechanical structure of the high-frequency spark machine and design a virtual assembly simulation system to predict the stability of the mechanical structure by simulating the assembly process;

[0054] Identify the resonant frequency and vibration mode of the mechanical structure, automatically adjust the damping parameters of the mechanical structure, and improve the stability of the high-frequency spark machine equipment.

[0055] Reference Figure 2 As shown, the collected operating data is analyzed, and a data analysis model is established. By comparing historical data with standard data, the operating trends and performance changes of the high-frequency spark machine are analyzed. Specifically, the following are included:

[0056] The operating data of the high-frequency spark machine is collected by a sensor, wherein the operating data includes voltage, current, discharge frequency, temperature and vibration parameters;

[0057] Extracting historical operation records from equipment logs and databases, wherein the historical operation records include processing time, efficiency, and fault logs;

[0058] Align multi-source data by timestamp to build a unified data set, and use interpolation to fill in missing values;

[0059] Extract time series features, statistical features, and process parameter features from a unified data set;

[0060] A time series model is used to predict the operating trends of voltage and current parameters, and a linear regression model is established between processing efficiency and voltage and current parameters to quantify the impact of each factor on performance;

[0061] Build a comparative analysis model, calculate the cosine similarity between the current data and the historical standard data, and record it as performance deviation;

[0062] Overlay the time series of current operating data with historical data, and observe trend differences through sliding window statistical methods.

[0063] Calculate the time series trend of the operating data, such as the average, maximum, and minimum values, to reflect the overall change trend of the data. Through methods such as Fourier transform, extract the periodic characteristics of the time series and analyze the periodic change pattern of the data. Calculate the mean, variance, standard deviation and other statistical quantities of the operating data to describe the distribution characteristics of the data, calculate the correlation coefficient between different parameters, and analyze the degree of association between the parameters. Extract the process parameter characteristics such as processing time and processing efficiency from the historical operation records, and analyze the impact of the processing technology on the performance of the high-frequency spark machine.

[0064] Reference Figure 3 As shown, a tunable sinusoidal oscillation circuit is connected in parallel to the output end of the high-frequency spark machine. The resonant frequency is dynamically adjusted based on the output frequency. The signal is transmitted through an optical fiber to eliminate electromagnetic interference. Specifically, the following steps are involved:

[0065] Design an inductor three-point oscillator circuit. The three points of the inductor coil are connected to the three poles of the transistor respectively. The feedback coil is a section of the inductor coil. The feedback voltage is sent to the input end through the feedback coil to achieve positive feedback.

[0066] The feedback voltage is adjusted by changing the position of the tap, and the oscillation frequency is adjusted by changing the capacitance based on the current operating frequency requirement.

[0067] A frequency detection link is introduced into the circuit to monitor the output frequency of the high-frequency spark machine in real time, and the detected frequency signal is compared with the current resonant frequency of the tunable sinusoidal oscillation circuit;

[0068] An error signal is generated based on the comparison result, and the error signal is amplified and used as a parameter for controlling the variable capacitor to change the resonant frequency of the oscillation circuit to make it consistent with the output frequency of the high-frequency spark machine;

[0069] When the output frequency of the high-frequency spark machine changes, the frequency detection link detects the change and generates a corresponding error signal;

[0070] The adjustment mechanism of the variable capacitor is driven to change the capacitance value, so that the resonant frequency of the oscillation circuit is adjusted at the same time, and the two are kept in a resonant state;

[0071] Based on the signal transmission requirements and environmental conditions, multimode optical fiber is selected for signal transmission;

[0072] The electrical signal generated by the tunable sinusoidal oscillation circuit is converted into an optical signal for transmission. At the receiving end, the optical signal is restored to an electrical signal using a corresponding demodulation method.

[0073] Design an inductor three-point oscillation circuit, in which the three points of the inductor coil are connected to the three poles of the transistor, the base, the collector and the emitter, respectively. Specifically, one end of the inductor coil is connected to the collector of the transistor, and the other end is connected to the power supply; at the same time, a section of the inductor coil is selected as the feedback coil, one end of which is connected to the emitter of the transistor, and the other end is connected to the base through a coupling capacitor, so as to achieve positive feedback.

[0074] Reference Figure 4 As shown in the figure, during the calibration process, the ambient temperature, humidity, and air pressure are monitored in real time, and an environmental compensation mathematical model is constructed to automatically correct the voltage deviation caused by environmental changes. Specifically, the following are included:

[0075] The data acquisition system collects the output data of temperature, humidity and air pressure sensors in real time based on the preset sampling frequency and stores the collected data in the cache;

[0076] The linear regression model is selected as the environmental compensation mathematical model to simulate the relationship between environmental parameters and voltage deviation;

[0077] Using at least one set of experimental data to train the selected model, taking environmental parameters as input variables and voltage deviation as output variables, and adjusting the model parameters of the environmental compensation mathematical model to minimize the error between the model output and the actual voltage deviation;

[0078] The real-time monitored environmental parameters are input into the trained environmental compensation mathematical model to calculate the voltage deviation caused by environmental changes under the current environmental conditions;

[0079] Based on the calculated voltage deviation, the voltage output of the device is automatically adjusted through a feedback control system.

[0080] Considering that there may be a certain linear relationship between environmental parameters and voltage deviation, and the linear regression model has the advantages of being simple to understand and having high computational efficiency, the linear regression model is selected as the environmental compensation mathematical model to simulate the relationship between environmental parameters and voltage deviation.

[0081] Reference Figure 5 As shown in the figure, a dual-channel oscilloscope is used, one channel monitors the output frequency of the high-frequency spark machine, and the other channel synchronously monitors the reference frequency source, and simultaneously detects the fundamental frequency and harmonic components, identifies and compensates for the frequency deviation caused by nonlinear distortion. Specifically, it includes:

[0082] Obtaining a reference frequency signal, the frequency of which is related to the expected output frequency of the high-frequency spark machine;

[0083] Connect the output terminal of the high-frequency spark machine, the reference frequency source and the input channel of the dual-channel oscilloscope;

[0084] Set the oscilloscope's sampling rate, bandwidth, and trigger mode parameters based on the high-frequency spark machine's output frequency range and expected harmonic content;

[0085] Observe the waveform shape, amplitude and frequency characteristics of the high-frequency spark machine output signal and the reference frequency source signal to preliminarily determine whether the signal is abnormal;

[0086] Perform spectrum analysis on the high-frequency spark machine output signal and the reference frequency source signal, observe the spectrum diagram, and determine the position and amplitude of the fundamental frequency and the distribution of harmonic components;

[0087] Measure the amplitude of each harmonic and compare it with the amplitude of the fundamental frequency to analyze whether the harmonic amplitude increases abnormally;

[0088] Measure the frequencies of the high-frequency spark machine output signal and the reference frequency source signal respectively, calculate the difference between the high-frequency spark machine output frequency and the reference frequency, and output it as the frequency deviation between the two;

[0089] Observe the change of frequency deviation over time and analyze the stability of the output frequency of the high-frequency spark machine;

[0090] Based on the spectrum analysis results and frequency deviation, determine whether the output signal of the high-frequency spark machine has nonlinear distortion. If so, check whether the circuit elements of the high-frequency spark machine have nonlinear characteristics. If not, do not output. The circuit elements include transistors, diodes, inductors and capacitors.

[0091] Adjust the circuit component parameters. Based on the results of spectrum analysis, adjust the circuit component parameters of the high-frequency spark machine and add a filter circuit. Add a filter circuit at the output end of the high-frequency spark machine to suppress harmonic components and improve signal purity.

[0092] If the spectrum analysis shows abnormal harmonics and the standard deviation of the frequency deviation is greater than 0.1%, it is determined to be nonlinear distortion. Use an electrical impedance analyzer to check the parameters of the transistor, diode, inductor, and capacitor, paying special attention to whether the transconductance of the transistor decreases, the junction capacitance of the diode increases, the inductance decreases, and the equivalent series resistance of the capacitor increases.

[0093] Reference Figure 6 As shown, a standard sample containing at least one type of defect is prepared, and an adaptive sensitivity adjustment mechanism is designed to dynamically adjust the detection threshold based on the defect type and size, and automatically adjust the sensitivity parameters of the high-frequency spark machine. Specifically, the following are included:

[0094] Based on actual testing requirements, cracks, pores and inclusions are selected as defect characteristics of standard samples;

[0095] For crack defects, at least two sets of cracks with different lengths, widths, and depths were created on the sample surface using mechanical processing methods;

[0096] For pore defects, pores are formed inside the sample by chemical etching. The sample is immersed in a corrosion solution, and the etching time and temperature are controlled to obtain pores of the desired size and distribution.

[0097] For inclusion defects, inclusions are added during sample preparation, and after the inclusions are evenly mixed with the matrix material, the sample is made through a casting process;

[0098] Conduct quality inspection on the prepared standard samples to ensure that the size, shape and distribution of defects meet the design requirements;

[0099] Analyze the signal image detected by the high-frequency spark machine using an image processing algorithm to extract characteristic parameters of the defect, including the length, width, area and shape factor of the defect;

[0100] Analyze the electrical signal output by the high-frequency spark machine and extract the frequency, amplitude and phase characteristics of the signal;

[0101] Establish a defect type recognition model and determine the defect type based on the extracted defect characteristic parameters;

[0102] Establish a correlation model between the sensitivity parameters of the high-frequency spark machine and the detection threshold, and determine the quantitative relationship between the sensitivity parameters and the detection threshold through experiments and data analysis. The sensitivity parameters include discharge voltage, discharge frequency and discharge gap.

[0103] Design an automatic adjustment algorithm to automatically calculate and adjust the sensitivity parameters of the high-frequency spark machine based on the dynamically adjusted detection threshold;

[0104] During the high-frequency spark machine inspection process, the inspection results and changes in sensitivity parameters are monitored in real time. Through a closed-loop control system, the inspection results are compared with the preset target values, and the sensitivity parameters are adjusted based on the deviation.

[0105] Extract characteristic parameters of the defect, including defect length (by measuring the pixel length of the defect in the image and converting it into actual length), width, area (calculating the number of pixels within the defect area and converting it into actual area), and shape factor (such as circularity, rectangularity, etc.).

[0106] Reference Figure 7As shown in the figure, the mechanical structure of the high-frequency spark machine is scanned, and a virtual assembly simulation system is designed. By simulating the assembly process, the stability of the mechanical structure is predicted, including:

[0107] Based on the mechanical structure characteristics of the high-frequency spark machine, determine the scanning range, resolution and scanning angle parameters to obtain three-dimensional information of the mechanical structure;

[0108] Clean and treat the mechanical surface of the high-frequency spark machine to remove oil, dust and impurities to improve the accuracy and quality of scanning;

[0109] Use a 3D scanner to scan the mechanical structure of the high-frequency spark machine according to the scanning plan. During the scanning process, keep the scanner stable and the scanning angle consistent;

[0110] After scanning, the collected 3D point cloud data is imported into the 3D modeling software, and the mechanical structure model of the high-frequency spark machine is reconstructed in the 3D modeling software using the reverse engineering method;

[0111] Based on the assembly process of the high-frequency spark machine, the assembly relationship between the various parts is defined in the virtual assembly simulation software, and the assembly relationship includes the matching relationship and the kinematic pair relationship;

[0112] Optimize the constructed virtual assembly model to determine whether there are interference and collision issues in the model. If so, remodel the relevant parts. If not, no output is made.

[0113] According to the assembly sequence of the high-frequency spark machine, virtual assembly simulation is carried out step by step. During the simulation, the movement trajectory of the parts, the stress distribution and deformation during the assembly process are observed and recorded;

[0114] Finite element analysis is used to calculate and analyze the stress and deformation of a mechanical structure under at least one working condition, and to evaluate the reliability and stability of the mechanical structure.

[0115] In virtual assembly simulation software, the fitting relationship between components, such as interference fit, clearance fit, etc., and the kinematic pair relationship, such as rotational pair, translation pair, etc., are defined according to the assembly process. Accurate assembly constraints and motion parameters are set for each component to ensure that the virtual assembly model can truly reflect the actual assembly process. Interference and collision detection is performed on the constructed virtual assembly model. The interference check function in the software is used to analyze whether there is spatial overlap or collision between components. If interference or collision problems are detected, the model of the relevant parts is remodeled, and the size, shape or assembly position of the components are adjusted until the interference and collision problems are resolved.

[0116] Furthermore, the present solution also proposes a computer-readable storage medium on which a computer-readable program is stored. When the computer-readable program is called, the high-frequency spark machine calibration method based on machining accuracy and stability control is executed.

[0117] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state disk (SSD).

[0118] To sum up, the advantages of the present invention are: by comparing historical data and standard data, the operating trends and performance changes of the high-frequency spark machine can be accurately analyzed, and the signal can be transmitted by optical fiber to effectively eliminate electromagnetic interference, ensure the stability of signal transmission, automatically correct the voltage deviation caused by environmental changes, and improve the adaptability and stability of the equipment under different environmental conditions. At the same time, the fundamental frequency and harmonic components can be detected, the frequency deviation caused by nonlinear distortion can be identified and compensated, and the detection accuracy can be improved, providing strong support for quality inspection and precision processing in the manufacturing industry.

[0119] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A high-frequency spark machine calibration method based on processing accuracy and stability control, characterized in that: include: Analyze the collected operating data, establish a data analysis model, and analyze the operating trends and performance changes of the high-frequency spark machine by comparing historical data with standard data; A tunable sinusoidal oscillation circuit is connected in parallel to the output end of the high-frequency spark machine to dynamically adjust the resonant frequency based on the output frequency, and transmit the signal through optical fiber to eliminate electromagnetic interference; During the calibration process, the ambient temperature, humidity and air pressure are monitored in real time, and an environmental compensation mathematical model is constructed to automatically correct voltage deviations caused by environmental changes. A dual-channel oscilloscope is used, one channel monitors the output frequency of the high-frequency spark machine, and the other channel synchronously monitors the reference frequency source, simultaneously detecting the fundamental frequency and harmonic components, identifying and compensating for frequency deviation caused by nonlinear distortion; Prepare a standard sample containing at least one type of defect, design an adaptive sensitivity adjustment mechanism, dynamically adjust the detection threshold based on the defect type and size, and automatically adjust the sensitivity parameters of the high-frequency spark machine; Scan the mechanical structure of the high-frequency spark machine and design a virtual assembly simulation system to predict the stability of the mechanical structure by simulating the assembly process; Identify the resonant frequency and vibration mode of the mechanical structure, automatically adjust the damping parameters of the mechanical structure, and improve the stability of the high-frequency spark machine equipment; The method of connecting a tunable sinusoidal wave oscillation circuit in parallel to the output end of the high-frequency spark machine, dynamically adjusting the resonant frequency based on the output frequency, and eliminating electromagnetic interference by transmitting signals through optical fibers specifically includes: Design an inductor three-point oscillator circuit. The three points of the inductor coil are connected to the three poles of the transistor respectively. The feedback coil is a section of the inductor coil. The feedback voltage is sent to the input end through the feedback coil to achieve positive feedback. The feedback voltage is adjusted by changing the position of the tap, and the oscillation frequency is adjusted by changing the capacitance based on the current operating frequency requirement. A frequency detection link is introduced into the circuit to monitor the output frequency of the high-frequency spark machine in real time, and the detected frequency signal is compared with the current resonant frequency of the tunable sinusoidal oscillation circuit; An error signal is generated based on the comparison result, and the error signal is amplified and used as a parameter for controlling the variable capacitor to change the resonant frequency of the oscillation circuit to make it consistent with the output frequency of the high-frequency spark machine; When the output frequency of the high-frequency spark machine changes, the frequency detection link detects the change and generates a corresponding error signal; The adjustment mechanism of the variable capacitor is driven to change the capacitance value, so that the resonant frequency of the oscillation circuit is adjusted at the same time, and the two are kept in a resonant state; Based on the signal transmission requirements and environmental conditions, multimode optical fiber is selected for signal transmission; The electrical signal generated by the tunable sinusoidal oscillation circuit is converted into an optical signal for transmission. At the receiving end, the optical signal is restored to an electrical signal using a corresponding demodulation method.

2. A high-frequency spark machine calibration method based on processing accuracy and stability control according to claim 1, characterized in that: The analysis of the collected operating data, establishment of a data analysis model, and analysis of the operating trends and performance changes of the high-frequency spark machine by comparing historical data with standard data specifically include: The operating data of the high-frequency spark machine is collected by a sensor, wherein the operating data includes voltage, current, discharge frequency, temperature and vibration parameters; Extracting historical operation records from equipment logs and databases, wherein the historical operation records include processing time, efficiency, and fault logs; Align multi-source data by timestamp to build a unified data set, and use interpolation to fill in missing values; Extract time series features, statistical features, and process parameter features from a unified data set; A time series model is used to predict the operating trends of voltage and current parameters, and a linear regression model is established between processing efficiency and voltage and current parameters to quantify the impact of each factor on performance; Build a comparative analysis model, calculate the cosine similarity between the current data and the historical standard data, and record it as performance deviation; Overlay the time series of current operating data with historical data, and observe trend differences through sliding window statistical methods.

3. A high-frequency spark machine calibration method based on processing accuracy and stability control according to claim 2, characterized in that: During the calibration process, the environmental temperature, humidity and air pressure are monitored in real time, an environmental compensation mathematical model is constructed, and the voltage deviation caused by environmental changes is automatically corrected. Specifically, the following steps are performed: The data acquisition system collects the output data of temperature, humidity and air pressure sensors in real time based on the preset sampling frequency and stores the collected data in the cache; The linear regression model is selected as the environmental compensation mathematical model to simulate the relationship between environmental parameters and voltage deviation; Using at least one set of experimental data to train the selected model, taking environmental parameters as input variables and voltage deviation as output variables, and adjusting the model parameters of the environmental compensation mathematical model to minimize the error between the model output and the actual voltage deviation; The real-time monitored environmental parameters are input into the trained environmental compensation mathematical model to calculate the voltage deviation caused by environmental changes under the current environmental conditions; Based on the calculated voltage deviation, the voltage output of the device is automatically adjusted through a feedback control system.

4. A high-frequency spark machine calibration method based on processing accuracy and stability control according to claim 3, characterized in that: The method uses a dual-channel oscilloscope, one channel monitors the output frequency of the high-frequency spark machine, and the other channel synchronously monitors the reference frequency source, and simultaneously detects the fundamental frequency and harmonic components, and identifies and compensates for the frequency deviation caused by nonlinear distortion. Specifically, the method includes: Obtaining a reference frequency signal, the frequency of which is related to the expected output frequency of the high-frequency spark machine; Connect the output terminal of the high-frequency spark machine, the reference frequency source and the input channel of the dual-channel oscilloscope; Set the oscilloscope's sampling rate, bandwidth, and trigger mode parameters based on the high-frequency spark machine's output frequency range and expected harmonic content; Observe the waveform shape, amplitude and frequency characteristics of the high-frequency spark machine output signal and the reference frequency source signal to preliminarily determine whether the signal is abnormal; Perform spectrum analysis on the high-frequency spark machine output signal and the reference frequency source signal, observe the spectrum diagram, and determine the position and amplitude of the fundamental frequency and the distribution of harmonic components; Measure the amplitude of each harmonic and compare it with the amplitude of the fundamental frequency to analyze whether the harmonic amplitude increases abnormally; Measure the frequencies of the high-frequency spark machine output signal and the reference frequency source signal respectively, calculate the difference between the high-frequency spark machine output frequency and the reference frequency, and output it as the frequency deviation between the two; Observe the change of frequency deviation over time and analyze the stability of the output frequency of the high-frequency spark machine; Based on the spectrum analysis results and frequency deviation, determine whether the output signal of the high-frequency spark machine has nonlinear distortion. If so, check whether the circuit elements of the high-frequency spark machine have nonlinear characteristics. If not, do not output. The circuit elements include transistors, diodes, inductors and capacitors. Adjust the circuit component parameters. Based on the results of spectrum analysis, adjust the circuit component parameters of the high-frequency spark machine and add a filter circuit. Add a filter circuit at the output end of the high-frequency spark machine to suppress harmonic components and improve signal purity.

5. The high-frequency spark machine calibration method based on processing accuracy and stability control according to claim 4 is characterized in that: The method of preparing a standard sample containing at least one type of defect, designing an adaptive sensitivity adjustment mechanism, dynamically adjusting the detection threshold based on the defect type and size, and automatically adjusting the sensitivity parameters of the high-frequency spark machine specifically includes: Based on actual testing requirements, cracks, pores and inclusions are selected as defect characteristics of standard samples; For crack defects, at least two sets of cracks with different lengths, widths, and depths were created on the sample surface using mechanical processing methods; For pore defects, pores are formed inside the sample by chemical etching. The sample is immersed in a corrosion solution, and the etching time and temperature are controlled to obtain pores of the desired size and distribution. For inclusion defects, inclusions are added during sample preparation, and after the inclusions are evenly mixed with the matrix material, the sample is made through a casting process; Conduct quality inspection on the prepared standard samples to ensure that the size, shape and distribution of defects meet the design requirements; Analyze the signal image detected by the high-frequency spark machine using an image processing algorithm to extract characteristic parameters of the defect, including the length, width, area and shape factor of the defect; Analyze the electrical signal output by the high-frequency spark machine and extract the frequency, amplitude and phase characteristics of the signal; Establish a defect type recognition model and determine the defect type based on the extracted defect characteristic parameters; Establish a correlation model between the sensitivity parameters of the high-frequency spark machine and the detection threshold, and determine the quantitative relationship between the sensitivity parameters and the detection threshold through experiments and data analysis. The sensitivity parameters include discharge voltage, discharge frequency and discharge gap. Design an automatic adjustment algorithm to automatically calculate and adjust the sensitivity parameters of the high-frequency spark machine based on the dynamically adjusted detection threshold; During the high-frequency spark machine inspection process, the inspection results and changes in sensitivity parameters are monitored in real time. Through a closed-loop control system, the inspection results are compared with the preset target values, and the sensitivity parameters are adjusted based on the deviation.

6. A high-frequency spark machine calibration method based on processing accuracy and stability control according to claim 5, characterized in that: The scanning of the mechanical structure of the high-frequency spark machine, designing a virtual assembly simulation system, and predicting the stability of the mechanical structure by simulating the assembly process specifically include: Based on the mechanical structure characteristics of the high-frequency spark machine, determine the scanning range, resolution and scanning angle parameters to obtain three-dimensional information of the mechanical structure; Clean and treat the mechanical surface of the high-frequency spark machine to remove oil, dust and impurities to improve the accuracy and quality of scanning; Use a 3D scanner to scan the mechanical structure of the high-frequency spark machine according to the scanning plan. During the scanning process, keep the scanner stable and the scanning angle consistent; After scanning, the collected 3D point cloud data is imported into the 3D modeling software, and the mechanical structure model of the high-frequency spark machine is reconstructed in the 3D modeling software using the reverse engineering method; Based on the assembly process of the high-frequency spark machine, the assembly relationship between the various parts is defined in the virtual assembly simulation software, and the assembly relationship includes the matching relationship and the kinematic pair relationship; Optimize the constructed virtual assembly model to determine whether there are interference and collision issues in the model. If so, remodel the relevant parts. If not, no output is made. According to the assembly sequence of the high-frequency spark machine, virtual assembly simulation is carried out step by step. During the simulation, the movement trajectory of the parts, the stress distribution and deformation during the assembly process are observed and recorded; Finite element analysis is used to calculate and analyze the stress and deformation of a mechanical structure under at least one working condition, and to evaluate the reliability and stability of the mechanical structure.

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