Rapid calibration method and system for automatic testing equipment of vehicle machine

Abstract

The invention discloses a rapid calibration method and system for automatic testing equipment of a vehicle machine, and relates to the technical field of automatic calibration, and the method comprises the steps: inputting a preset standard calibration signal to the testing equipment, and collecting the response data of each testing channel of the equipment as calibration reference data; comparing the calibration reference data with a built-in standard reference value of the equipment, and calculating deviation data of each test channel; based on the deviation data, calibration parameters of each channel are calculated, and the calibration parameters comprise a gain compensation coefficient, a frequency compensation coefficient and a phase compensation coefficient; the calibration parameters are loaded to the corresponding channels of the test equipment, a preset standard calibration signal is input for verification test, and when errors of the channels are smaller than a preset residual error threshold value, calibration is completed, and the calibration parameters are stored. By establishing the gain-frequency-phase joint compensation model and combining the parallelization verification and increment optimization algorithm, the high-precision rapid calibration of the automatic test equipment of the vehicle machine is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle computer automatic calibration, and in particular to a method and system for quickly calibrating vehicle computer automatic test equipment. Background Art

[0002] As a core tool for verifying the functions and performance of vehicle-mounted computer automated test equipment, it is necessary to ensure the accuracy and consistency of the test channels, and calibration technology directly determines the reliability of the test data. At present, the mainstream calibration methods are mainly based on static calibration or manual intervention adjustment, such as using a standard signal source to calibrate each channel, or relying on external high-precision instruments for comparison calibration. In recent years, some technologies have begun to introduce automated calibration processes, such as gain compensation based on the lookup table method or phase correction at a limited frequency point, but there are still limitations in multi-parameter joint calibration, dynamic error compensation and parallel processing. In addition, existing calibration methods usually rely on fixed compensation models, which are difficult to adapt to the nonlinear deviation characteristics in wide-band and multi-level scenarios in vehicle-mounted computer testing, making it difficult to strike a balance between calibration efficiency and accuracy.

[0003] The main deficiencies of the existing technology are reflected in three aspects: First, the traditional channel-by-channel calibration method is time-consuming, especially in large-scale multi-channel test systems, the calibration time increases linearly with the number of channels, and cannot meet the high-efficiency requirements of production line testing; second, the existing compensation models are mostly optimized independently for a single error source (such as gain or phase), and lack a joint compensation mechanism for the gain-frequency-phase coupling effect, resulting in residual error accumulation during complex signal testing; third, the calibration verification link usually uses a single threshold judgment, and no dynamic recalibration mechanism and incremental optimization algorithm are established. The full process calibration needs to be repeated when the equipment ages or the environment changes. In contrast, the multi-parameter joint fitting, parallel verification and incremental optimization methods of the present invention can significantly improve the calibration speed and accuracy. For example, the gain-level composite compensation function is constructed by the least squares method to solve the mismatch problem of traditional piecewise linear compensation in high dynamic range testing; and the phase compensation strategy based on frequency domain interpolation effectively improves the group delay characteristics under wide-band signals. Summary of the Invention

[0004] In view of the problems of low efficiency, insufficient multi-parameter coupling compensation and poor dynamic adaptability in the existing vehicle test equipment calibration technology, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to perform multi-dimensional rapid calibration of each channel of the test equipment in an efficient, accurate and traceable manner during the automated testing of the vehicle computer, so as to improve the consistency and reliability of the test results and meet the dual requirements of test accuracy and test efficiency in complex vehicle signal environments.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a method for quickly calibrating an automated vehicle test device, which includes:

[0008] Input a preset standard calibration signal into the test equipment and collect the response data of each test channel of the equipment as calibration reference data;

[0009] Compare the calibration reference data with the standard reference value built into the device to calculate the deviation data of each test channel;

[0010] Calculating calibration parameters of each channel based on the deviation data, wherein the calibration parameters include a gain compensation coefficient, a frequency compensation coefficient, and a phase compensation coefficient;

[0011] The calibration parameters are loaded into the corresponding channels of the test equipment, and the preset standard calibration signal is input to perform a verification test. When the error of each channel is less than the preset residual error threshold, the calibration is completed and the calibration parameters are saved.

[0012] As a preferred solution of the rapid calibration method of the vehicle-mounted automated test equipment of the present invention, wherein: the calibration parameters are loaded into the corresponding channels of the test equipment, the preset standard calibration signal is input to perform a verification test, and when the error of each channel is less than a preset residual error threshold, the calibration is completed and the calibration parameters are saved, including:

[0013] Reading a calibration parameter set from a non-volatile memory and performing an integrity check on the calibration parameter set;

[0014] Through the parameter configuration interface of the test equipment, the calibration parameter group is written into the corresponding field programmable gate array register according to the channel number, and a hardware reset signal is triggered to make the configuration effective;

[0015] Regenerate a preset standard calibration signal, distribute the preset standard calibration signal to all test channels through a signal routing switch, and start a parallel acquisition mode of the test equipment;

[0016] The residual error is calculated for the collected data of the test channel, and the residual error is compared with the preset residual error threshold.

[0017] As a preferred solution of the rapid calibration method of the vehicle-mounted automated test equipment of the present invention, it further includes:

[0018] If the error terms of all channels meet the requirements that the amplitude residual error is less than the amplitude threshold, the frequency residual error is less than the frequency threshold, the phase residual error is less than the phase threshold, and the level residual error is less than the level threshold, the calibration parameter verification is considered to have passed, a version identifier is generated, and written to the secure storage area of ​​the device. The calibration time, operator ID, and key performance indicators are recorded in the system log, and the calibration flag bit in the device status register is updated.

[0019] If the calibration parameters fail, the out-of-tolerance items and deviation amounts are recorded, and the local recalibration process is automatically triggered. The incremental parameter adjustment algorithm is used to optimize the compensation parameters, and data collection and error determination are repeated until verification is passed or the maximum number of retries is reached.

[0020] As a preferred solution of the rapid calibration method of the vehicle-mounted automated test equipment of the present invention, the calibration parameters of each channel are calculated based on the deviation data, including:

[0021] Extracting a deviation data set of a target channel from a deviation data matrix according to a test channel number, wherein the deviation data set includes an amplitude deviation sequence, a frequency deviation sequence, a phase deviation sequence, and a level deviation sequence;

[0022] The amplitude deviation sequence and the level deviation sequence are jointly fitted using the least squares method to establish a gain-level composite compensation function and generate a gain compensation coefficient;

[0023] Performing statistical analysis on the frequency deviation sequence, calculating an average frequency offset and a maximum frequency deviation, and generating a frequency compensation coefficient;

[0024] A phase deviation lookup table for key frequency points is established for the phase deviation sequence, and a continuous phase compensation function is constructed using a cubic spline interpolation algorithm. The interpolation node parameters are stored as phase compensation coefficients.

[0025] Inputting the gain compensation coefficient, the frequency compensation coefficient, and the phase compensation coefficient into a forward verification model to calculate a residual error, wherein the residual error includes a gain residual error, a frequency residual error, and a phase residual error;

[0026] If any residual error exceeds a preset threshold, the coefficient matrix is ​​optimized using iterative least squares for gain compensation, a second-order correction term is introduced for frequency compensation, and the interpolation node density is increased in the phase compensation table;

[0027] The verified compensation parameters are standardized and packaged to form a calibration parameter group for each channel.

[0028] As a preferred solution of the rapid calibration method of the vehicle-mounted automated test equipment of the present invention, wherein: the calibration benchmark data is compared with the standard reference value built into the equipment, and the deviation data of each test channel is calculated, including:

[0029] Reading pre-stored standard reference values ​​from a non-volatile memory of the test device, and establishing a data mapping relationship between the calibration benchmark data and the standard reference values ​​according to the test channel number and signal type;

[0030] For each test channel frequency point k, calculate the amplitude deviation value ΔA k , frequency deviation value Δf k and phase deviation At the same time, for each test channel level step l, calculate the level deviation value ΔP l ;

[0031] The amplitude deviation value ΔA k , frequency deviation value Δf k and phase deviation And the level deviation value ΔP l Integrate into deviation data matrix according to test channel number to generate structured deviation data;

[0032] Perform statistical analysis on each deviation value of the deviation data matrix, calculate the distribution characteristics and change trends of the deviation values ​​of each test channel, identify channels and frequencies with abnormal deviation values, and establish a deviation data quality assessment table;

[0033] Based on the deviation data quality evaluation table, the test channels that exceed the preset deviation range are marked as abnormal, and the valid deviation data of the deviation data matrix are transmitted to the calibration parameter calculation module.

[0034] As a preferred solution of the rapid calibration method of the vehicle-mounted automated test equipment of the present invention, the method includes: identifying channels and frequencies with abnormal deviation values, and establishing a deviation data quality evaluation table, including:

[0035] When the system detects that there are outliers in the deviation data matrix, it starts the anomaly detection process and generates a deviation data quality assessment table;

[0036] If the amplitude deviation value ΔA of any channel k >First threshold or frequency deviation value Δf k > the second threshold or the phase deviation value > the third threshold, it is marked as a level 1 abnormality, the hardware self-check process is executed and the compensation parameters are recalculated using the segmented fitting algorithm. At the same time, the batch calibration process is suspended and a red alarm is issued;

[0037] If it is detected that the continuous frequency deviation shows a monotonically increasing trend of more than 5% / MHz, it is marked as a secondary anomaly, and the frequency domain interpolation compensation mode is activated. Compensation nodes are added on both sides of the abnormal frequency band and the calibration level range is limited.

[0038] As a preferred solution of the rapid calibration method of the vehicle-mounted automated test equipment of the present invention, wherein: a preset standard calibration signal is input to the test equipment, and the response data of each test channel of the equipment is collected as calibration reference data, including:

[0039] Configure the preset standard calibration signal source to generate multi-frequency signals including discrete frequency points within the vehicle test frequency band, and generate standard level signals at the same time;

[0040] Connect the preset standard calibration signal source to the RF input port of the test equipment through a RF coaxial cable, and set the signal acquisition parameters;

[0041] Input the multi-frequency signal to each test channel, and obtain the first response data of each channel at k frequency points through the digital down-conversion module, wherein the first response data includes the amplitude value A of each frequency point. k , frequency value f k and phase value

[0042] The standard level signal is synchronously input to all test channels, and the second response data of each channel under l level steps is recorded, wherein the second response data includes the level measurement value P l And the corresponding standard level value P ref_l ;

[0043] The first response data and the second response data are preprocessed, and the preprocessed first response data and the second response data are stored as a structured data matrix according to the test channel number to generate calibration reference data.

[0044] In a second aspect, an embodiment of the present invention provides a rapid calibration system for vehicle-mounted automated testing equipment, comprising:

[0045] The standard calibration signal injection module is used to input a preset standard calibration signal into the test equipment and collect the response data of each test channel of the equipment as calibration reference data;

[0046] A response acquisition and deviation calculation module is used to compare the calibration reference data with the standard reference value built into the device and calculate the deviation data of each test channel;

[0047] a calibration parameter generation module, which calculates calibration parameters of each channel based on the deviation data, wherein the calibration parameters include a gain compensation coefficient, a frequency compensation coefficient, and a phase compensation coefficient;

[0048] The parameter loading and verification module is used to load the calibration parameters into the corresponding channels of the test equipment, input the preset standard calibration signal for verification testing, and when the error of each channel is less than the preset residual error threshold, the calibration is completed and the calibration parameters are saved.

[0049] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the rapid calibration method of the vehicle-mounted automated test equipment as described in the first aspect of the present invention are implemented.

[0050] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the rapid calibration method of the vehicle-mounted automated test equipment as described in the first aspect of the present invention are implemented.

[0051] Compared with the prior art, the beneficial effects of the present invention are as follows: by inputting multi-frequency point signals and standard level signals covering the vehicle test frequency band into the test equipment, the amplitude, frequency, phase and level response data of each test channel are collected as calibration reference data, a high-dimensional, full-band calibration basis is constructed, and a comprehensive perception of the dynamic characteristics of the test channel is achieved, which effectively improves the calibration coverage and representativeness, avoids compensation failure caused by a single signal sample, and thus enhances the adaptability of the test equipment under different working conditions; by comparing the above calibration reference data with the standard reference value built into the equipment, constructing a deviation data matrix, and identifying abnormal deviation channels and frequencies based on statistical analysis, structured modeling and quality assessment of error characteristics are achieved, and the system's early perception of equipment performance degradation or channel drift is improved, which helps to prevent test anomalies and guide subsequent compensation Precision control of compensation strategy; based on structured deviation data, least squares fitting, statistical inference and interpolation reconstruction methods are used to generate gain, frequency and phase compensation coefficients, and iterative optimization and node densification strategies are introduced for parameters that have not passed the initial verification, which significantly improves the accuracy and stability of parameter modeling; by establishing a composite compensation model, the nonlinear error characteristics can be fully captured, so that the compensation effect is more in line with the actual response characteristics of the channel; by loading the compensation parameters into the field programmable gate array register, the calibration results are judged by the error dimension threshold. If it passes, the complete calibration version, operator and indicator information are recorded; otherwise, the local recalibration process is triggered and the compensation value is dynamically adjusted using an incremental algorithm. This mechanism ensures that the calibration is not only accurate but also traceable and self-correctable, which significantly improves the maintainability, data consistency and engineering application reliability of automated test equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0053] Figure 1 This is a flow chart of the rapid calibration method of the vehicle-mounted automated test equipment in Example 1. DETAILED DESCRIPTION

[0054] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0055] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0056] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0057] As mentioned in the background technology above, the main deficiencies of the existing technology are reflected in three aspects: First, the traditional channel-by-channel calibration method is time-consuming, especially in large-scale multi-channel test systems, the calibration time increases linearly with the number of channels, and cannot meet the high-efficiency requirements of production line testing; second, the existing compensation models are mostly optimized independently for a single error source (such as gain or phase), and lack a joint compensation mechanism for the gain-frequency-phase coupling effect, resulting in residual error accumulation during complex signal testing; third, the calibration verification link usually adopts a single threshold judgment, and no dynamic recalibration mechanism and incremental optimization algorithm are established. The whole process calibration needs to be repeated when the equipment ages or the environment changes. In contrast, the multi-parameter joint fitting, parallel verification and incremental optimization methods of the present invention can significantly improve the calibration speed and accuracy. For example, the gain-level composite compensation function is constructed by the least squares method, which solves the mismatch problem of traditional piecewise linear compensation in high dynamic range testing; and the phase compensation strategy based on frequency domain interpolation effectively improves the group delay characteristics under wide-band signals.

[0058] Figure 1 FIG. 1 is a flow chart of a laboratory intelligent liquid distribution control method based on the Internet of Things according to an embodiment of the present invention. Figure 1As shown, in a laboratory intelligent liquid preparation control method based on the Internet of Things, it includes:

[0059] S1: Input a preset standard calibration signal to the test equipment and collect the response data of each test channel of the equipment as calibration reference data.

[0060] Specifically, a preset standard calibration signal source is configured to generate a multi-frequency signal including discrete frequency points within the vehicle test frequency band, and a standard level signal is generated at the same time; the preset standard calibration signal source is connected to the RF input port of the test equipment through an RF coaxial cable, and the signal acquisition parameters are set.

[0061] It should be noted that the preset standard calibration signal includes a multi-frequency point signal and a standard level signal covering the vehicle test frequency band; the frequency interval of the multi-frequency point signal is determined based on the equal division of the vehicle test frequency band width, and includes the frequency points at the frequency band boundaries; the dynamic range of the standard level signal is -10dBm to +10dBm.

[0062] Preferably, the test equipment automatically identifies and activates all N test channels to form a parallel test path; sets the signal acquisition parameters: configures the sampling rate of the test equipment to be more than 5 times the highest frequency of the multi-frequency signal, sets the quantization bit width of the analog-to-digital converter to 16 bits, and ensures that the dynamic range coverage accuracy of the standard level signal reaches ±0.1dB.

[0063] Furthermore, the multi-frequency signal is input to each test channel, and the first response data of each channel at k frequency points is obtained through the digital down-conversion module, wherein the first response data includes the amplitude value A of each frequency point. k , frequency value f k and phase value The standard level signal is synchronously input to all test channels, and the second response data of each channel under l level steps is recorded, wherein the second response data includes the level measurement value P l And the corresponding standard level value P ref_l .

[0064] Furthermore, the first response data and the second response data are preprocessed, and the preprocessed first response data and the second response data are stored as a structured data matrix according to the test channel number to generate calibration reference data.

[0065] It should be noted that data preprocessing: the amplitude value A k and level measurement value P l Perform sliding average filtering to eliminate random noise; kThe FFT interpolation algorithm is used to correct the frequency resolution and obtain accurate frequency response data; the row vectors of the data matrix correspond to the test channel number, and the column vectors correspond to the response data of different frequency points and levels.

[0066] S2: Compare the calibration benchmark data with the standard reference value built into the device to calculate the deviation data of each test channel.

[0067] Specifically, a pre-stored standard reference value is read from a non-volatile memory of the test device, and a data mapping relationship is established between the calibration benchmark data and the standard reference value according to the test channel number and signal type.

[0068] It should be noted that the standard reference value includes the multi-frequency standard amplitude value A corresponding to the calibration reference data. ref_k , standard frequency value f ref_k , standard phase value And the standard level value P ref_l .

[0069] Furthermore, for each test channel frequency point k, calculate the amplitude deviation value ΔA k , frequency deviation value Δf k and phase deviation At the same time, for each test channel level step l, calculate the level deviation value ΔP l .

[0070] Preferably, the amplitude value A k With the standard amplitude value A ref_k The difference between the two values ​​is used to obtain the amplitude deviation value ΔA k , and record the amplitude deviation value set of all frequency points {ΔA1, ΔA2,…, ΔA k}; By frequency value f k With the standard frequency value f ref_k The difference between the two values ​​is used to obtain the frequency deviation value Δf k , and record the frequency deviation value set of all frequency points {Δf1,Δf2,…,Δf k}; By phase value With the standard phase value The difference between And record the phase deviation value set of all frequency points By level measurement value P l With the standard level value P ref_l The difference between the two values ​​is used to obtain the level deviation value ΔP l , and record the level deviation value set of all level steps {ΔP1, ΔP2,…, ΔP l The row vectors of the deviation data matrix correspond to the test channel numbers, and the column vectors correspond to the deviation values ​​at different frequencies and levels.

[0071] Furthermore, a statistical analysis is performed on each deviation value of the deviation data matrix, the distribution characteristics and change trends of the deviation values ​​of each test channel are calculated, the channels and frequencies with abnormal deviation values ​​are identified, and a deviation data quality assessment table is established; based on the deviation data quality assessment table, the test channels that exceed the preset deviation range are marked as abnormal, and at the same time, the valid deviation data of the deviation data matrix is ​​transmitted to the calibration parameter calculation module.

[0072] Preferably, as shown in Table 1, when the system detects that there are abnormal values ​​in the deviation data matrix, it starts the abnormality detection process and generates a deviation data quality evaluation table; if the amplitude deviation value ΔA of any channel is k >First threshold or frequency deviation value Δf k > the second threshold or the phase deviation value > the third threshold, the channel is marked as a first-level abnormality, the hardware self-check process is executed, and the compensation parameters are recalculated using the segmented fitting algorithm. At the same time, the batch calibration process is suspended and a red alarm is issued; if it is detected that the continuous frequency point deviation shows a monotonically increasing trend of more than 5% / MHz, it is marked as a second-level abnormality, the frequency domain interpolation compensation mode is activated, compensation nodes are added on both sides of the abnormal frequency band, and the calibration level range is limited.

[0073] It should be noted that the first threshold is 0.3dB, which is determined based on 1.5 times the equipment amplitude measurement accuracy (±0.2dB) and is used to identify significant amplitude distortion; the second threshold is based on the crystal oscillator frequency stability (±1ppm) converted to the maximum allowable frequency deviation of 10Hz in the test frequency band; the third threshold is a 5° phase tolerance set according to the accuracy specifications of the phase detection chip (AD8302).

[0074] Table 1. Deviation data quality assessment table

[0075]

[0076]

[0077] Specifically, the test parameters are automatically adjusted according to different abnormality levels: an encrypted sampling mode with a 4x sampling rate is used for the first-level abnormal channel; a fine scan with a step of 0.1MHz is implemented for the second-level abnormal channel; all channels are subject to step level excitation testing; based on the verification results, a graded response is made: when the residual error is lower than the threshold of 50%, the parameter is marked as the gold standard and the aging model is updated; when the error is between the 30%-100% threshold, gradient descent optimization is initiated; when the error exceeds the standard, the hardware diagnostic protocol including items such as RF switch impedance and ADC clock jitter is triggered.

[0078] Furthermore, a knowledge base update operation is performed, the abnormal pattern feature vector of this calibration is stored in the fault knowledge graph, the equipment health index including factors such as the environmental parameter compensation curve and the hash value of the abnormal processing log is calculated, and the next calibration time is predicted based on the index calculation results.

[0079] S3: Calculating calibration parameters of each channel based on the deviation data, wherein the calibration parameters include a gain compensation coefficient, a frequency compensation coefficient, and a phase compensation coefficient.

[0080] Specifically, a deviation data set of a target channel is extracted from a deviation data matrix according to a test channel number, wherein the deviation data set includes an amplitude deviation sequence, a frequency deviation sequence, a phase deviation sequence, and a level deviation sequence; the amplitude deviation sequence and the level deviation sequence are jointly fitted using a least squares method to establish a gain-level composite compensation function and generate a gain compensation coefficient;

[0081] Preferably, the specific formula of the gain-level composite compensation function is as follows:

[0082]

[0083] Where x is the input level value; K is the total number of frequency points; w k is the normalized weight of the kth frequency point; ΔA k is the amplitude deviation value of the kth frequency point; a is the slope of the Sigmoid function; b is the center point of the Sigmoid function; c is the logarithmic compensation coefficient; d is the logarithmic scaling factor; sgn(*) is the sign function.

[0084] It should be noted that the output of this function is the compensation amount, and when the compensation amount is within ±0.3dB, it is within the effective compensation range.

[0085] Furthermore, the relevant formulas for the average frequency offset, maximum frequency deviation, and frequency compensation coefficient are as follows:

[0086] Δf avg =(∑Δf k ) / K

[0087] Δf max =max(|Δf k |)

[0088] F comp =1 / (1+Δf avg / f ref_center );

[0089] Where Δf avg is the average frequency offset; Δf max is the maximum frequency deviation; F comp is the frequency compensation coefficient; fref_cebter is the center frequency of the test band.

[0090] Furthermore, a phase deviation lookup table of key frequency points is established for the phase deviation sequence, and a continuous phase compensation function is constructed using a cubic spline interpolation algorithm, and the interpolation node parameters are stored as phase compensation coefficients; the gain compensation coefficient, the frequency compensation coefficient and the phase compensation coefficient are input into a forward verification model to calculate the residual error, wherein the residual error includes a gain residual error, a frequency residual error and a phase residual error.

[0091] It should be noted that the forward verification model is constructed based on the mapping relationship between the compensation parameters and the residual error. By substituting the gain, frequency, and phase compensation coefficients into the signal transmission link model, the difference between the theoretical output and the measured response is calculated.

[0092] Specifically, if any residual error exceeds a preset threshold, the iterative least squares method is used to optimize the coefficient matrix for gain compensation, a second-order correction term is introduced for frequency compensation, and the interpolation node density is increased in the phase compensation table until all residual errors meet the accuracy requirements of gain residual error less than the gain residual threshold of 0.1dB, frequency residual error less than the frequency threshold of 10Hz, and phase residual error less than the phase threshold of 0.5°; the verified compensation parameters are standardized and packaged to form a calibration parameter group for each channel.

[0093] Preferably, the preset threshold is obtained through Monte Carlo simulation combined with historical calibration data statistics of the equipment, where the gain residual threshold of 0.1dB corresponds to a 3σ confidence interval (σ=0.033dB), the frequency threshold of 10Hz is determined by the phase noise integration result of the phase-locked loop, and the phase threshold of 0.5° comes from the conversion requirement that the vector error (EVM) does not exceed 1%.

[0094] S4: Load the calibration parameters into the corresponding channels of the test equipment, input the preset standard calibration signal to perform a verification test, and when the error of each channel is less than the preset residual error threshold, the calibration is completed and the calibration parameters are saved.

[0095] Specifically, the calibration parameter group is read from the non-volatile memory and the integrity of the calibration parameter group is checked; through the parameter configuration interface of the test equipment, the calibration parameter group is written into the corresponding field programmable gate array register according to the channel number, and the hardware reset signal is triggered to make the configuration effective.

[0096] It should be noted that the calibration parameter group includes gain compensation parameters, frequency compensation parameters and phase compensation parameters; the field programmable gate array FPGA register writes the gain parameters to addresses 0x8000-0x800F, the frequency parameters to addresses 0x8010-0x8017, and the phase parameters to addresses 0x8020-0x803F.

[0097] Furthermore, a preset standard calibration signal is regenerated, and the preset standard calibration signal is distributed to all test channels through a signal routing switch, and a parallel acquisition mode of the test equipment is started.

[0098] It should be noted that the preset standard calibration signal includes a multi-frequency signal and a standard level signal; starting the parallel acquisition mode of the test equipment includes:

[0099] a) Amplitude value A after compensation for multi-frequency signal acquisition ′ k , frequency value f′ k and phase value

[0100] b) Collect the compensated level value P of the standard level signal ′ l ;

[0101] c) The sampling duration is set to 3 times the original calibration acquisition time.

[0102] Furthermore, the residual error of the collected data of the test channel is calculated and compared with the preset residual error threshold. If the error items of all channels meet the requirements that the amplitude residual error is less than the amplitude threshold, the frequency residual error is less than the frequency threshold, the phase residual error is less than the phase threshold, and the level residual error is less than the level threshold, the calibration parameter verification is determined to be successful, a version identifier is generated, and written into the secure storage area of ​​the device. At the same time, the calibration time, operator ID, and key performance indicators are recorded in the system log, and the calibration flag in the device status register is updated.

[0103] It should be noted that the collected data includes amplitude residual error, frequency residual error, phase residual error and level residual error; the preset residual error thresholds include amplitude threshold, frequency threshold, phase threshold and level threshold.

[0104] Specifically, if the calibration parameters fail, the out-of-tolerance items and deviation amounts are recorded, the local recalibration process is automatically triggered, and the incremental parameter adjustment algorithm is used to optimize the compensation parameters. Data collection and error judgment are repeated until verification is passed or the maximum number of retries is reached.

[0105] In summary, the present invention constructs a high-dimensional, full-band calibration basis by inputting multi-frequency signals and standard level signals covering the vehicle test frequency band into the test equipment, collecting the amplitude, frequency, phase and level response data of each test channel as calibration reference data, and realizing comprehensive perception of the dynamic characteristics of the test channel, effectively improving the calibration coverage and representativeness, avoiding compensation failure caused by a single signal sample, and thus enhancing the adaptability of the test equipment under different working conditions; by comparing the above-mentioned calibration reference data with the standard reference value built into the equipment, constructing a deviation data matrix, and identifying abnormal deviation channels and frequencies based on statistical analysis, structured modeling and quality evaluation of error characteristics are realized, and the system's early perception of equipment performance degradation or channel drift is improved, which helps to prevent test anomalies and guide the accuracy of subsequent compensation strategies. degree of control; based on structured deviation data, the gain, frequency and phase compensation coefficients are generated by least squares fitting, statistical inference and interpolation reconstruction methods, and iterative optimization and node densification strategies are introduced for parameters that have not passed the initial verification, which significantly improves the accuracy and stability of parameter modeling; by establishing a composite compensation model, the nonlinear error characteristics can be fully captured, so that the compensation effect is more in line with the actual response characteristics of the channel; by loading the compensation parameters into the field programmable gate array register, the calibration results are judged by the error dimension threshold, if it passes, the complete calibration version, operator and indicator information are recorded, otherwise the local recalibration process is triggered and the compensation value is dynamically adjusted using an incremental algorithm. This mechanism ensures that the calibration is not only accurate but also traceable and self-correctable, which significantly improves the maintainability, data consistency and engineering application reliability of automated test equipment.

[0106] Furthermore, this embodiment also provides a rapid calibration system for vehicle-mounted automated testing equipment, comprising:

[0107] The standard calibration signal injection module is used to input a preset standard calibration signal into the test equipment and collect the response data of each test channel of the equipment as calibration reference data;

[0108] A response acquisition and deviation calculation module is used to compare the calibration reference data with the standard reference value built into the device and calculate the deviation data of each test channel;

[0109] a calibration parameter generation module, which calculates calibration parameters of each channel based on the deviation data, wherein the calibration parameters include a gain compensation coefficient, a frequency compensation coefficient, and a phase compensation coefficient;

[0110] The parameter loading and verification module is used to load the calibration parameters into the corresponding channels of the test equipment, input the preset standard calibration signal for verification testing, and when the error of each channel is less than the preset residual error threshold, the calibration is completed and the calibration parameters are saved.

[0111] This embodiment also provides a computer device suitable for the rapid calibration method of vehicle-mounted automated test equipment, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the rapid calibration method of vehicle-mounted automated test equipment proposed in the above embodiment.

[0112] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0113] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A rapid calibration method for vehicle-mounted automated test equipment, characterized by: include, Input a preset standard calibration signal into the test equipment and collect the response data of each test channel of the equipment as calibration reference data; Compare the calibration reference data with the standard reference value built into the device to calculate the deviation data of each test channel; Calculating calibration parameters of each channel based on the deviation data, wherein the calibration parameters include a gain compensation coefficient, a frequency compensation coefficient, and a phase compensation coefficient; The calibration parameters are loaded into the corresponding channels of the test equipment, and the preset standard calibration signal is input to perform a verification test. When the error of each channel is less than the preset residual error threshold, the calibration is completed and the calibration parameters are saved.

2. The rapid calibration method for vehicle-mounted automated test equipment according to claim 1, wherein: The calibration parameters are loaded into the corresponding channels of the test equipment, and the preset standard calibration signal is input to perform a verification test. When the error of each channel is less than the preset residual error threshold, the calibration is completed and the calibration parameters are saved, including: Reading a calibration parameter set from a non-volatile memory and performing an integrity check on the calibration parameter set; Through the parameter configuration interface of the test equipment, the calibration parameter group is written into the corresponding field programmable gate array register according to the channel number, and a hardware reset signal is triggered to make the configuration effective; Regenerate a preset standard calibration signal, distribute the preset standard calibration signal to all test channels through a signal routing switch, and start a parallel acquisition mode of the test equipment; The residual error is calculated for the collected data of the test channel, and the residual error is compared with the preset residual error threshold.

3. The rapid calibration method for vehicle-mounted automated test equipment according to claim 2, characterized in that: Also includes, If the error terms of all channels meet the requirements that the amplitude residual error is less than the amplitude threshold, the frequency residual error is less than the frequency threshold, the phase residual error is less than the phase threshold, and the level residual error is less than the level threshold, the calibration parameter verification is considered to have passed, a version identifier is generated, and written to the secure storage area of ​​the device. The calibration time, operator ID, and key performance indicators are recorded in the system log, and the calibration flag bit in the device status register is updated. If the calibration parameters fail, the out-of-tolerance items and deviation amounts are recorded, and the local recalibration process is automatically triggered. The incremental parameter adjustment algorithm is used to optimize the compensation parameters, and data collection and error determination are repeated until verification is passed or the maximum number of retries is reached.

4. The rapid calibration method for vehicle-mounted automated test equipment according to claim 3, characterized in that: Based on the deviation data, the calibration parameters of each channel are calculated, including: Extracting a deviation data set of a target channel from a deviation data matrix according to a test channel number, wherein the deviation data set includes an amplitude deviation sequence, a frequency deviation sequence, a phase deviation sequence, and a level deviation sequence; The amplitude deviation sequence and the level deviation sequence are jointly fitted using the least squares method to establish a gain-level composite compensation function and generate a gain compensation coefficient; Performing statistical analysis on the frequency deviation sequence, calculating an average frequency offset and a maximum frequency deviation, and generating a frequency compensation coefficient; A phase deviation lookup table for key frequency points is established for the phase deviation sequence, and a continuous phase compensation function is constructed using a cubic spline interpolation algorithm. The interpolation node parameters are stored as phase compensation coefficients. Inputting the gain compensation coefficient, the frequency compensation coefficient, and the phase compensation coefficient into a forward verification model to calculate a residual error, wherein the residual error includes a gain residual error, a frequency residual error, and a phase residual error; If any residual error exceeds a preset threshold, the coefficient matrix is ​​optimized using iterative least squares for gain compensation, a second-order correction term is introduced for frequency compensation, and the interpolation node density is increased in the phase compensation table; The verified compensation parameters are standardized and packaged to form a calibration parameter group for each channel.

5. The rapid calibration method for vehicle-mounted automated test equipment according to claim 4, characterized in that: Compare the calibration reference data with the standard reference value built into the device and calculate the deviation data for each test channel, including: Reading pre-stored standard reference values ​​from a non-volatile memory of the test device, and establishing a data mapping relationship between the calibration benchmark data and the standard reference values ​​according to the test channel number and signal type; For each test channel frequency point k, calculate the amplitude deviation value ΔA k , frequency deviation value Δf k and phase deviation Δφ k At the same time, for each test channel level step l, calculate the level deviation value ΔP l ; The amplitude deviation value ΔA k , frequency deviation value Δf k and phase deviation Δφ k And the level deviation value ΔP l Integrate into deviation data matrix according to test channel number to generate structured deviation data; Perform statistical analysis on each deviation value of the deviation data matrix, calculate the distribution characteristics and change trends of the deviation values ​​of each test channel, identify channels and frequencies with abnormal deviation values, and establish a deviation data quality assessment table; Based on the deviation data quality evaluation table, the test channels that exceed the preset deviation range are marked as abnormal, and the valid deviation data of the deviation data matrix are transmitted to the calibration parameter calculation module.

6. The rapid calibration method for vehicle-mounted automated test equipment according to claim 5, characterized in that: Identify channels and frequencies with abnormal deviation values ​​and establish a deviation data quality assessment table, including: When the system detects that there are outliers in the deviation data matrix, it starts the anomaly detection process and generates a deviation data quality assessment table; If the amplitude deviation value ΔA of any channel k >First threshold or frequency deviation value Δf k > the second threshold or the phase deviation value > the third threshold, it is marked as a level 1 abnormality, the hardware self-check process is executed and the compensation parameters are recalculated using the segmented fitting algorithm. At the same time, the batch calibration process is suspended and a red alarm is issued; If it is detected that the continuous frequency deviation shows a monotonically increasing trend of more than 5% / MHz, it is marked as a secondary anomaly, and the frequency domain interpolation compensation mode is activated. Compensation nodes are added on both sides of the abnormal frequency band and the calibration level range is limited.

7. The rapid calibration method for vehicle-mounted automated test equipment according to claim 6, characterized in that: Input a preset standard calibration signal to the test equipment and collect the response data of each test channel of the equipment as calibration reference data, including: Configure the preset standard calibration signal source to generate multi-frequency signals including discrete frequency points within the vehicle test frequency band, and generate standard level signals at the same time; Connect the preset standard calibration signal source to the RF input port of the test equipment through a RF coaxial cable, and set the signal acquisition parameters; Input the multi-frequency signal to each test channel, and obtain the first response data of each channel at k frequency points through the digital down-conversion module, wherein the first response data includes the amplitude value A of each frequency point. k , frequency value f k and phase value φ k ; The standard level signal is synchronously input to all test channels, and the second response data of each channel under l level steps is recorded, wherein the second response data includes the level measurement value P l And the corresponding standard level value P ref_l ; The first response data and the second response data are preprocessed, and the preprocessed first response data and the second response data are stored as a structured data matrix according to the test channel number to generate calibration reference data.

8. A rapid calibration system for vehicle-mounted automated test equipment, based on the rapid calibration method for vehicle-mounted automated test equipment according to any one of claims 1 to 7, characterized in that: include, The standard calibration signal injection module is used to input a preset standard calibration signal into the test equipment and collect the response data of each test channel of the equipment as calibration reference data; A response acquisition and deviation calculation module is used to compare the calibration reference data with the standard reference value built into the device and calculate the deviation data of each test channel; a calibration parameter generation module, which calculates calibration parameters of each channel based on the deviation data, wherein the calibration parameters include a gain compensation coefficient, a frequency compensation coefficient, and a phase compensation coefficient; The parameter loading and verification module is used to load the calibration parameters into the corresponding channels of the test equipment, input the preset standard calibration signal for verification testing, and when the error of each channel is less than the preset residual error threshold, the calibration is completed and the calibration parameters are saved.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the rapid calibration method of vehicle-mounted automated test equipment according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the rapid calibration method of vehicle-mounted automated test equipment according to any one of claims 1 to 7 are implemented.

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