High-frequency spark machine calibration method based on machining precision and stability control

Abstract

The invention discloses a high-frequency spark machine calibration method based on machining precision and stability control, and relates to the field of mechanical calibration, and the method comprises the steps: analyzing collected operation data, and building a data analysis model; the resonant frequency is dynamically adjusted based on the output frequency, and electromagnetic interference is eliminated through optical fiber transmission signals; an environment compensation mathematical model is constructed, and voltage deviation caused by environment change is automatically corrected; fundamental frequency and harmonic components are detected at the same time, and frequency deviation caused by nonlinear distortion is identified and compensated; a self-adaptive sensitivity adjusting mechanism is designed, a detection threshold value is dynamically adjusted based on the defect type and size, and sensitivity parameters of the high-frequency spark machine are automatically adjusted; the stability of the mechanical structure is predicted by simulating the assembly process; damping parameters of a mechanical structure are automatically adjusted, and the stability of high-frequency spark machine equipment is improved. The product quality and the production efficiency are guaranteed by improving the performance and the stability of the high-frequency spark machine.

Description

Technical Field

[0001] The present invention relates to the field of mechanical calibration, and particularly to a calibration method for a high-frequency spark machine based on machining accuracy and stability control. Background Technique

[0002] In the fields of precision machining and quality inspection in modern manufacturing, high-frequency spark machines play a crucial role. With their unique detection principles, they can accurately identify tiny defects on the surface and inside of materials, such as cracks and inclusions, providing a key basis for product quality control. From the strict requirements for high precision and high reliability of components in the aerospace field to the zero tolerance for defects in micro-components in the electronics industry, the application of high-frequency spark machines runs through many key industrial links. Their detection accuracy and stability are directly related to the quality and performance of the final products. Once there are deviations, it may lead to unqualified products flowing into the market, causing potential safety hazards and huge economic losses.

[0003] As a key device widely used in the insulation detection of wire and cable, the machining accuracy and stability of high-frequency spark machines directly affect product quality and production efficiency. With the continuous improvement of product quality requirements in the wire and cable industry, the calibration work of high-frequency spark machines becomes particularly important. However, traditional calibration methods often focus on the adjustment of electrical parameters, ignoring the influence of various factors such as mechanical structure and operating status on machining accuracy and stability. Therefore, it is of great practical significance to propose a calibration method for high-frequency spark machines based on machining accuracy and stability control. Summary of the Invention

[0004] To solve the above technical problems, a calibration method for a high-frequency spark machine based on machining accuracy and stability control is provided, and this technical solution solves the problems raised in the above background technique.

[0005] To achieve the above purposes, the technical solution adopted by the present invention is as follows: A calibration method for a high-frequency spark machine based on machining accuracy and stability control, including: Analyze the collected operation data, establish a data analysis model, and analyze the operation trend and performance changes of the high-frequency spark machine by comparing historical data and standard data; Connect a tunable sine wave oscillation circuit in parallel at the output end of the high-frequency spark machine, dynamically adjust the resonance frequency based on the output frequency, and eliminate electromagnetic interference through optical fiber signal transmission; During the calibration process, real-time monitor the ambient temperature, humidity and air pressure, construct an environmental compensation mathematical model, and automatically correct the voltage deviation caused by environmental changes; Use 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. At the same time, detect the fundamental frequency and harmonic components, identify and compensate for the 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, design a virtual assembly simulation system, and predict the stability of the mechanical structure by simulating the assembly process; Identify the resonance 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.

[0006] Preferably, the use of a dual-channel oscilloscope, where one channel monitors the output frequency of the high-frequency spark machine, and the other channel synchronously monitors the reference frequency source, and at the same time detects the fundamental frequency and harmonic components, and identifies and compensates for the frequency deviation caused by nonlinear distortion specifically includes: Obtain a reference frequency signal whose frequency is associated with 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 channels of the dual-channel oscilloscope; Based on the output frequency range of the high-frequency spark machine and the expected harmonic components, set the sampling rate, bandwidth, and trigger mode parameters of the oscilloscope; Observe the waveform shape, amplitude, and frequency characteristics of the output signal of the high-frequency spark machine and the reference frequency source signal, and preliminarily judge whether the signal is abnormal; Conduct a spectrum analysis on the output signal of the high-frequency spark machine and the reference frequency source signal, observe the spectrogram, and determine the position and amplitude of the fundamental frequency and the distribution of harmonic components; Measure the amplitude of each harmonic, compare it with the amplitude of the fundamental frequency, and analyze whether there is an abnormal increase in the harmonic amplitude; Measure the frequencies of the output signal of the high-frequency spark machine and the reference frequency source signal respectively, calculate the difference between the output frequency of the high-frequency spark machine and the reference frequency, and output it as the frequency deviation between the two; Observe the change of the 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 the frequency deviation situation, judge whether there is nonlinear distortion in the output signal of the high-frequency spark machine. If so, check whether the circuit components of the high-frequency spark machine have nonlinear characteristics. If not, do not make an output. The circuit components include transistors, diodes, inductors, and capacitors; Adjust the circuit component parameters. Based on the results of the cause analysis, adjust the circuit component parameters of the high-frequency spark machine, and add a filter circuit at the output terminal of the high-frequency spark machine to suppress harmonic components and improve the signal purity.

[0007] Preferably, the preparation of standard samples 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 the actual detection requirements, select defect characteristics such as cracks, pores, and inclusions as the defect features of the standard samples; For crack defects, use mechanical processing methods to create at least two groups of cracks on the sample surface in terms of length, width, and depth; For pore defects, form pores inside the sample through chemical corrosion. Immerse the sample in the corrosion solution and control the corrosion time and temperature to obtain pores with the required size and distribution; For inclusion defects, add inclusions during the sample preparation process. After mixing the inclusions evenly with the matrix material, make the sample through the casting process; Conduct quality inspections on the prepared standard samples to ensure that the size, shape, and distribution of the defects meet the design requirements; Use image processing algorithms to analyze the signal images detected by the high-frequency spark machine, and extract the characteristic parameters of the defects. The characteristic parameters include the length, width, area, and shape factor of the defects; Analyze the electrical signals output by the high-frequency spark machine and extract the frequency, amplitude, and phase characteristics of the signals; Establish a defect type recognition model, and based on the extracted defect characteristic parameters, judge the type of the defects; Establish an association model between the sensitivity parameters of the high-frequency spark machine and the detection threshold. Through experiments and data analysis, determine the quantitative relationship between the sensitivity parameters and the detection threshold. The sensitivity parameters include the discharge voltage, discharge frequency, and discharge gap; Design an automatic adjustment algorithm. Based on the dynamically adjusted detection threshold, automatically calculate and adjust the sensitivity parameters of the high-frequency spark machine; During the detection process of the high-frequency spark machine, monitor the changes in the detection results and sensitivity parameters in real time. Through a closed-loop control system, compare the detection results with the preset target values, and adjust the sensitivity parameters based on the deviation magnitude.

[0008] Compared with the prior art, the beneficial effects of the present invention are as follows: By comparing historical data and standard data, accurately analyze the operation trend and performance changes of the high-frequency spark machine. Use optical fiber to transmit signals, effectively eliminate electromagnetic interference, ensure the stability of signal transmission, automatically correct the voltage deviation caused by environmental changes, improve the adaptability and stability of the equipment under different environmental conditions. At the same time, detect the fundamental frequency and harmonic components, identify and compensate for the frequency deviation caused by nonlinear distortion, improve the detection accuracy, and provide strong support for quality inspection and precision machining in the manufacturing industry. Description of the Drawings

[0009] Figure 1 It is a flowchart of the calibration method for a high-frequency spark machine based on machining accuracy and stability control according to the present invention; Figure 2 It is a flowchart of the method for analyzing the operation trend and performance change of a high-frequency spark machine according to the present invention; Figure 3 It is a flowchart of the method for dynamically adjusting the resonance frequency based on the output frequency according to the present invention; Figure 4 It is a flowchart of the method for constructing an environmental compensation mathematical model and automatically correcting the voltage deviation caused by environmental changes according to the present invention; Figure 5 It is a flowchart of the method for identifying and compensating the frequency deviation caused by nonlinear distortion according to the present invention; Figure 6 It is a flowchart of the method for designing an adaptive sensitivity adjustment mechanism according to the present invention; Figure 7 It is a flowchart of the method for predicting the stability of a mechanical structure by simulating the assembly process according to the present invention. Detailed Description of the Invention

[0010] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0011] Referring to Figure 1 shown, a calibration method for a high-frequency spark machine based on machining accuracy and stability control includes: Analyze the collected operation data, establish a data analysis model, and analyze the operation trend and performance change of the high-frequency spark machine by comparing historical data and standard data; Connect a tunable sine wave oscillation circuit in parallel at the output end of the high-frequency spark machine, dynamically adjust the resonance frequency based on the output frequency, and eliminate electromagnetic interference by transmitting signals through optical fibers; During the calibration process, real-time monitor the environmental temperature, humidity and air pressure, construct an environmental compensation mathematical model, and automatically correct the voltage deviation caused by environmental changes; Use a dual-channel oscilloscope, monitor the output frequency of the high-frequency spark machine on one channel, and synchronously monitor the reference frequency source on the other channel, simultaneously detect the fundamental frequency and harmonic components, and identify and compensate the 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, design a virtual assembly simulation system, and predict the stability of the mechanical structure by simulating the assembly process; Identify the resonance frequencies and vibration modes of the mechanical structure, automatically adjust the damping parameters of the mechanical structure, and improve the stability of the high-frequency spark machine equipment.

[0012] Refer to Figure 2 As shown, analyze the collected operation data, establish a data analysis model, and analyze the operation trend and performance changes of the high-frequency spark machine by comparing historical data and standard data, specifically including: Collect the operation data of the high-frequency spark machine through sensors, and the operation data includes voltage, current, discharge frequency, temperature, and vibration parameters; Extract historical operation records from the device log and database, and the historical operation records include processing time, efficiency, and fault logs; Align the multi-source data according to the timestamp, construct a unified data set, and fill in the missing values using the interpolation method; Extract the time series features, statistical features, and process parameter features from the unified data set; Adopt a time series model to predict the operation trends of voltage and current parameters, and establish a linear regression model between processing efficiency and voltage and current parameters to quantify the influence of each factor on performance; Construct a comparative analysis model, calculate the cosine similarity between the current data and the historical standard data, and record it as the performance deviation; Overlay the time series of the current operation data with the historical data, and observe the trend differences through the sliding window statistical method.

[0013] Calculate the time series trends of the operation data, such as average value, maximum value, minimum value, etc., to reflect the overall change trend of the data. Through methods such as Fourier transform, extract the periodic features of the time series and analyze the periodic change laws of the data; calculate statistical quantities such as the mean, variance, and standard deviation of the operation data to describe the distribution characteristics of the data, calculate the correlation coefficients between different parameters, and analyze the degree of association between the parameters; extract process parameter features such as processing time and processing efficiency from the historical operation records and analyze the influence of the processing process on the performance of the high-frequency spark machine.

[0014] Refer to Figure 3 As shown, connect a tunable sine wave oscillation circuit in parallel at the output end of the high-frequency spark machine, dynamically adjust the resonance frequency based on the output frequency, and eliminate electromagnetic interference by transmitting signals through optical fibers, specifically including: Design an inductance three-point oscillation circuit, connect the three points of the inductance coil to the three poles of the transistor respectively, and the feedback coil is a section of the inductance coil. Send the feedback voltage to the input end through the feedback coil to achieve positive feedback; The magnitude of the feedback voltage is adjusted by changing the position of the tap. Based on the current operating frequency requirement, the oscillation frequency is adjusted by changing the capacitance; A frequency detection link is introduced into the circuit to monitor the output frequency of the high-frequency spark machine in real time, and compare the detected frequency signal with the current resonance frequency of the tunable sine wave oscillation circuit; An error signal is generated based on the comparison result, and the error signal is amplified and processed as a parameter for controlling the variable capacitance, changing the resonance 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; Drive the adjustment mechanism of the variable capacitance to change the capacitance value, so that the resonance frequency of the oscillation circuit is adjusted simultaneously, and keep the two in a resonant state; Based on the requirements of signal transmission and environmental conditions, multimode optical fiber is selected for signal transmission; Convert the electrical signal generated by the tunable sine wave oscillation circuit into an optical signal for transmission. At the receiving end, the optical signal is restored to an electrical signal by using the corresponding demodulation method.

[0015] Design an inductance three-point oscillation circuit. The three points of the inductance coil in this circuit are respectively connected to the three poles of the transistor, namely the base, collector and emitter. Specifically, one end of the inductance coil is connected to the collector of the transistor, and the other end is connected to the power supply; at the same time, select a section from the inductance coil as the feedback coil, connect one end to the emitter of the transistor, and the other end to the base through a coupling capacitor to achieve positive feedback.

[0016] Refer to Figure 4 As shown, 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 including: The data acquisition system collects the output data of the temperature, humidity and air pressure sensors in real time based on the preset sampling frequency, and stores the collected data in the buffer; Select a linear regression model as the environmental compensation mathematical model to simulate the relationship between environmental parameters and voltage deviation; Use at least one set of experimental data to train the selected model. Take the environmental parameters as the input variables and the voltage deviation as the output variables. By adjusting the model parameters of the environmental compensation mathematical model, minimize the error between the output of the model and the actual voltage deviation; Input the real-time monitored environmental parameters 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.

[0017] 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 and easy to understand, high calculation efficiency, etc., a linear regression model is selected as the environmental compensation mathematical model to simulate the relationship between environmental parameters and voltage deviation.

[0018] Refer to Figure 5 As shown, 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. At the same time, the fundamental frequency and harmonic components are detected. Identifying and compensating for the frequency deviation caused by nonlinear distortion specifically includes: Obtain a reference frequency signal whose frequency is associated with 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 channels of the dual-channel oscilloscope; Based on the output frequency range of the high-frequency spark machine and the expected harmonic components, set the sampling rate, bandwidth, and trigger mode parameters of the oscilloscope; Observe the waveform shape, amplitude, and frequency characteristics of the output signal of the high-frequency spark machine and the reference frequency source signal, and preliminarily judge whether the signal is abnormal; Perform spectrum analysis on the output signal of the high-frequency spark machine and the reference frequency source signal, observe the spectrogram, and determine the position and amplitude of the fundamental frequency and the distribution of harmonic components; Measure the amplitude of each harmonic, compare it with the amplitude of the fundamental frequency, and analyze whether there is an abnormal increase in the harmonic amplitude; Measure the frequencies of the output signal of the high-frequency spark machine and the reference frequency source signal respectively, calculate the difference between the output frequency of the high-frequency spark machine and the reference frequency, and output it as the frequency deviation between the two; Observe the change of the 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 the frequency deviation situation, judge whether there is nonlinear distortion in the output signal of the high-frequency spark machine. If so, check whether the circuit elements of the high-frequency spark machine have nonlinear characteristics. If not, no output is made. The circuit elements include transistors, diodes, inductors, and capacitors; Adjust the circuit element parameters. Based on the results of the cause analysis, adjust the circuit element parameters of the high-frequency spark machine, and add a filter circuit. Add a filter circuit at the output terminal of the high-frequency spark machine to suppress harmonic components and improve the signal purity.

[0019] If the spectrum analysis shows abnormal harmonics and the standard deviation of frequency deviation > 0.1%, it is determined as non-linear distortion. Use an impedance analyzer to check the parameters of transistors, diodes, inductors, and capacitors, with a focus on whether the transconductance of the transistor has decreased, whether the junction capacitance of the diode has increased, whether the inductor value has decreased, and whether the equivalent series resistance of the capacitor has increased.

[0020] Refer to Figure 6 As shown, prepare standard samples 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. Specifically, it includes: Based on the actual detection requirements, select defect characteristics such as cracks, pores, and inclusions as the defects of the standard samples; For crack defects, use mechanical processing methods to create at least two groups of cracks on the sample surface in terms of length, width, and depth; For pore defects, form pores inside the sample through chemical corrosion. Immerse the sample in the corrosion solution, control the corrosion time and temperature, and obtain pores with the required size and distribution; For inclusion defects, add inclusions during the sample preparation process. After mixing the inclusions evenly with the matrix material, make the sample through the casting process; Conduct quality inspections on the prepared standard samples to ensure that the size, shape, and distribution of the defects meet the design requirements; Use image processing algorithms to analyze the signal images detected by the high-frequency spark machine, and extract the characteristic parameters of the defects. The characteristic parameters include the length, width, area, and shape factor of the defects; Analyze the electrical signals output by the high-frequency spark machine and extract the frequency, amplitude, and phase characteristics of the signals; Establish a defect type recognition model, and based on the extracted defect characteristic parameters, judge the type of the defects; Establish a correlation model between the sensitivity parameters of the high-frequency spark machine and the detection threshold. Through experiments and data analysis, determine the quantitative relationship between the sensitivity parameters and the detection threshold. The sensitivity parameters include the discharge voltage, discharge frequency, and discharge gap; Design an automatic adjustment algorithm. Based on the dynamically adjusted detection threshold, automatically calculate and adjust the sensitivity parameters of the high-frequency spark machine; During the detection process of the high-frequency spark machine, monitor the changes in the detection results and sensitivity parameters in real time. Through a closed-loop control system, compare the detection results with the preset target values, and adjust the sensitivity parameters based on the deviation size.

[0021] Extract the characteristic parameters of the defect, including the length of the defect (by measuring the pixel length of the defect in the image and converting it to the actual length), width, area (calculating the number of pixels in the defect area and converting it to the actual area), and shape factor (such as circularity, rectangularity, etc.).

[0022] Refer to Figure 7 As shown, scan the mechanical structure of the high-frequency spark machine, design a virtual assembly simulation system, and predict the stability of the mechanical structure through the simulation assembly process, specifically including: Based on the characteristics of the mechanical structure of the high-frequency spark machine, determine the scanning range, resolution, and scanning angle parameters, and obtain the three-dimensional information of the mechanical structure; Clean and process the surface of the mechanical structure of the high-frequency spark machine to remove oil stains, dust, and impurities, and improve the scanning accuracy and quality; Use a three-dimensional 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 the scanning is completed, import the collected three-dimensional point cloud data into three-dimensional modeling software, and use reverse engineering methods to reconstruct the mechanical structure model of the high-frequency spark machine in the three-dimensional modeling software; Based on the assembly process of the high-frequency spark machine, define the assembly relationship between each component in the virtual assembly simulation software, and the assembly relationship includes the mating relationship and the kinematic pair relationship; Optimize the constructed virtual assembly model, judge whether there are interference and collision problems in the model. If so, re-model the relevant parts. If not, do not output; According to the assembly sequence of the high-frequency spark machine, gradually carry out virtual assembly simulation. During the simulation process, observe and record the movement trajectory of the components, the stress distribution and deformation conditions during the assembly process; Adopt the finite element analysis method to calculate and analyze the stress and deformation conditions of the mechanical structure under at least one working condition, and evaluate the reliability and stability of the mechanical structure.

[0023] In the virtual assembly simulation software, define the mating relationship between each component according to the assembly process, such as interference fit, clearance fit, etc., and the kinematic pair relationship, such as revolute pair, prismatic pair, etc., set accurate assembly constraints and motion parameters for each component to ensure that the virtual assembly model can truly reflect the actual assembly process. Conduct interference and collision detection on the constructed virtual assembly model, use the interference check function in the software to analyze whether there is spatial overlap or collision between each component. If interference or collision problems are detected, re-model the relevant parts of the model, adjust the size, shape or assembly position of the components until the interference and collision problems are solved.

[0024] Further, this solution also proposes a computer-readable storage medium, on which a computer-readable program is stored. When the computer-readable program is called, it executes the above-mentioned high-frequency spark machine calibration method based on machining accuracy and stability control.

[0025] It can be understood that the storage medium can 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).

[0026] In summary, the advantages of the present invention are as follows: By comparing historical data with standard data, the operation trend and performance changes of the high-frequency spark machine are accurately analyzed. The use of optical fiber to transmit signals effectively eliminates electromagnetic interference and ensures the stability of signal transmission. The voltage deviation caused by environmental changes is automatically corrected, improving the adaptability and stability of the device under different environmental conditions. At the same time, the fundamental frequency and harmonic components are detected, and the frequency deviation caused by nonlinear distortion is identified and compensated, improving the detection accuracy and providing strong support for quality inspection and precision machining in the manufacturing industry.

[0027] 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 by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A calibration method for a high-frequency spark machine based on machining accuracy and stability control, characterized in that Including: Analyze the collected operation data, establish a data analysis model, and analyze the operation trend and performance changes of the high-frequency spark machine by comparing historical data and standard data; Connect a tunable sine wave oscillation circuit in parallel at the output end of the high-frequency spark machine, dynamically adjust the resonance frequency based on the output frequency, and eliminate electromagnetic interference by transmitting signals through optical fibers; During the calibration process, monitor the ambient temperature, humidity, and air pressure in real time, construct an environmental compensation mathematical model, and automatically correct the voltage deviation caused by environmental changes; Use a dual-channel oscilloscope, monitor the output frequency of the high-frequency spark machine on one channel, and synchronously monitor the reference frequency source on the other channel, simultaneously detect the fundamental frequency and harmonic components, and identify and compensate for the frequency deviation caused by nonlinear distortion; Prepare standard samples 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, design a virtual assembly simulation system, and predict the stability of the mechanical structure by simulating the assembly process; Identify the resonance 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.

2. A calibration method for a high-frequency spark machine based on machining accuracy and stability control according to claim 1, characterized in that, The analysis of the collected operation data, establishment of a data analysis model, and analysis of the operation trend and performance changes of the high-frequency spark machine by comparing historical data and standard data specifically include: Collect the operation data of the high-frequency spark machine through sensors, and the operation data includes voltage, current, discharge frequency, temperature, and vibration parameters; Extract historical operation records from the device log and database, and the historical operation records include processing time, efficiency, and fault log; Align the multi-source data according to the timestamp, construct a unified data set, and fill in the missing values using the interpolation method; Extract the time series features, statistical features, and process parameter features from the unified data set; Use a time series model to predict the operation trend of voltage and current parameters, and establish a linear regression model of processing efficiency with voltage and current parameters to quantify the impact of each factor on performance; Construct a comparative analysis model, calculate the cosine similarity between the current data and historical standard data, and record it as the performance deviation; Overlay the time series of the current operation data with the historical data, and observe the trend difference through the sliding window statistical method.

3. A calibration method for a high-frequency spark machine based on machining accuracy and stability control according to claim 2, characterized in that, The connection of a tunable sine wave oscillation circuit in parallel at the output end of the high-frequency spark machine, dynamic adjustment of the resonance frequency based on the output frequency, and elimination of electromagnetic interference by transmitting signals through optical fibers specifically include: Design an inductance three-point oscillation circuit, connect the three points of the inductance coil to the three poles of the transistor respectively, and the feedback coil is a section of the inductance coil. Send the feedback voltage to the input end through the feedback coil to achieve positive feedback; Adjust the magnitude of the feedback voltage by changing the position of the tap, and adjust the oscillation frequency by changing the capacitance based on the current working frequency requirement; Introduce a frequency detection link in the circuit, monitor the output frequency of the high-frequency spark machine in real time, and compare the detected frequency signal with the current resonance frequency of the tunable sine wave oscillation circuit; Generate an error signal based on the comparison result, amplify the error signal, and use it as a parameter for controlling the variable capacitor to change the resonant frequency of the oscillation circuit to be 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 section detects the change and generates a corresponding error signal; Drive the adjustment mechanism of the variable capacitor to change the capacitance value, so that the resonant frequency of the oscillation circuit is adjusted simultaneously, and keep the two in a resonant state; Based on the requirements of signal transmission and environmental conditions, select a multimode optical fiber for signal transmission; Convert the electrical signal generated by the tunable sine wave oscillation circuit into an optical signal for transmission. At the receiving end, use the corresponding demodulation method to restore the optical signal to an electrical signal.

4. A calibration method for a high-frequency spark machine based on machining accuracy and stability control according to claim 3, characterized in that, During the calibration process, the environmental 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 include: The data acquisition system collects the output data of the temperature, humidity, and air pressure sensors in real time based on a preset sampling frequency, and stores the collected data in the buffer; Select a linear regression model as the environmental compensation mathematical model to simulate the relationship between environmental parameters and voltage deviation; Use at least one set of experimental data to train the selected model, use the environmental parameters as input variables and the voltage deviation as output variables, and minimize the error between the output of the model and the actual voltage deviation by adjusting the model parameters of the environmental compensation mathematical model; Input the real-time monitored environmental parameters 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, automatically adjust the voltage output of the device through a feedback control system.

5. A calibration method for a high-frequency spark machine based on machining accuracy and stability control according to claim 4, characterized in that Using 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 include: Obtain a reference frequency signal whose frequency is associated with 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 channels of the dual-channel oscilloscope; Based on the output frequency range of the high-frequency spark machine and the expected harmonic components, set the sampling rate, bandwidth, and trigger mode parameters of the oscilloscope; Observe the waveform shape, amplitude, and frequency characteristics of the high-frequency spark machine output signal and the reference frequency source signal, and preliminarily judge whether the signal is abnormal; Perform spectral analysis on the high-frequency spark machine output signal and the reference frequency source signal, observe the spectrogram, and determine the position and amplitude of the fundamental frequency and the distribution of harmonic components; Measure the amplitude of each harmonic, compare it with the fundamental frequency amplitude, and analyze whether there is an abnormal increase in the harmonic amplitude; 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 the frequency deviation over time and analyze the stability of the high-frequency spark machine output frequency; Based on the spectrum analysis results and frequency deviation conditions, determine whether there is non-linear distortion in the output signal of the high-frequency spark machine. If so, check whether the circuit components of the high-frequency spark machine have non-linear characteristics. If not, do not make an output. The circuit components include transistors, diodes, inductors, and capacitors; Adjust the circuit component parameters. Based on the results of the cause 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.

6. A calibration method for a high-frequency spark machine based on machining accuracy and stability control according to claim 5, characterized in that The preparation of standard samples 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 the actual detection requirements, select defect characteristics such as cracks, pores, and inclusions as the defects of the standard samples; For crack defects, use mechanical processing methods to create at least two groups of cracks with lengths, widths, and depths on the sample surface; For pore defects, form pores inside the sample through chemical corrosion. Immerse the sample in the corrosion solution and control the corrosion time and temperature to obtain pores with the required size and distribution; For inclusion defects, add inclusions during the sample preparation process. After mixing the inclusions evenly with the matrix material, make the sample through a casting process; Conduct quality inspections on the prepared standard samples to ensure that the size, shape, and distribution of the defects meet the design requirements; Use image processing algorithms to analyze the signal images detected by the high-frequency spark machine and extract the characteristic parameters of the defects. The characteristic parameters include the length, width, area, and shape factor of the defects; Analyze the electrical signals output by the high-frequency spark machine and extract the frequency, amplitude, and phase characteristics of the signals; Establish a defect type recognition model and judge the type of defect 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. Through experiments and data analysis, determine the quantitative relationship between the sensitivity parameters and the detection threshold. The sensitivity parameters include discharge voltage, discharge frequency, and discharge gap; Design an automatic adjustment algorithm. Based on the dynamically adjusted detection threshold, automatically calculate and adjust the sensitivity parameters of the high-frequency spark machine; During the detection process of the high-frequency spark machine, monitor the changes in the detection results and sensitivity parameters in real time. Through a closed-loop control system, compare the detection results with the preset target values and adjust the sensitivity parameters based on the deviation size.

7. A calibration method for a high-frequency spark machine based on machining accuracy and stability control according to claim 6, characterized in that, The mechanical structure of the high-frequency spark machine is scanned, and a virtual assembly simulation system is designed. By simulating the assembly process, predict the stability of the mechanical structure, specifically including: Based on the mechanical structure characteristics of the high-frequency spark machine, determine the scanning range, resolution, and scanning angle parameters to obtain the three-dimensional information of the mechanical structure; Clean and process the surface of the mechanical structure of the high-frequency spark machine to remove oil stains, dust, and impurities, and improve the scanning accuracy and quality; Use a three-dimensional 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 the scanning is completed, the collected three-dimensional point cloud data is imported into three-dimensional modeling software, and the mechanical structure model of the high-frequency spark machine is reconstructed in the three-dimensional modeling software by using reverse engineering methods; Based on the assembly process of the high-frequency spark machine, the assembly relationships between various components are defined in virtual assembly simulation software, and the assembly relationships include mating relationships and kinematic pair relationships; Optimize the constructed virtual assembly model, and judge whether there are interference and collision problems in the model. If so, re-model the relevant parts. If not, no output is made; According to the assembly sequence of the high-frequency spark machine, gradually carry out virtual assembly simulation. During the simulation process, observe and record the movement trajectories of components, the stress distribution and deformation conditions during the assembly process; Adopt the finite element analysis method to calculate and analyze the stress and deformation conditions of the mechanical structure under at least one working condition, and evaluate the reliability and stability of the mechanical structure.

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