Power integrity automated test system based on multi-parameter intelligent collaboration

Abstract

The application discloses a power integrity automatic test system based on multi-parameter intelligent cooperation, and belongs to the technical field of power test. The power type recognition and configuration module automatically recognizes the power type and calls preset test parameters from a database to generate a test scheme; the multi-parameter acquisition module synchronously acquires multi-modal data output by the power, and the multi-modal data comprises test parameters of various powers; the intelligent scoring module standardizes and scores each test parameter of the power; the automatic evaluation module constructs a three-dimensional correlation matrix and dynamically adjusts the weight of each scored test parameter to calculate an evaluation index of the power integrity; and the feedback module generates feedback information and a visual report of the power integrity test according to a visual template. The application realizes the automation of the power integrity test through the cooperation of the above modules, saves manpower, and improves the objectivity of the evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply testing, and in particular to a power supply integrity automated testing system based on multi-parameter intelligent collaboration. Background Art

[0002] Power integrity testing is designed to ensure that the power system can operate normally under various operating conditions and provide stable power to the load. This test covers multiple aspects to ensure the reliability, stability, and adaptability of the power supply.

[0003] With the rapid development of cutting-edge fields such as high-speed digital circuits, 5G communications, artificial intelligence, electric vehicles, and aerospace, electronic devices are placing higher demands on power supply quality. However, traditional power supply testing technologies are no longer able to meet these demands. On the one hand, traditional testing methods often rely on isolated single-parameter testing, with limited coverage and neglecting the synergistic effects of multiple parameters. On the other hand, existing testing processes are overly manual. From test plan development and instrument setup to compensation network adjustment during testing, all steps rely on manual operation and empirical judgment by professional technicians. This not only significantly prolongs test cycles and reduces test efficiency, but also easily introduces errors due to human factors, affecting the accuracy and reliability of test results. Furthermore, existing test systems lack dynamic adaptability, making it difficult to flexibly adjust test strategies based on the real-time status and performance changes of the test object, thus failing to meet the complex and ever-changing test requirements. Furthermore, existing automated testing systems lack intelligent decision-making capabilities, making it difficult to effectively analyze parameter correlations in complex scenarios, resulting in low test efficiency.

[0004] Therefore, there is an urgent need for an automated power integrity testing system based on multi-parameter intelligent collaboration to overcome the above defects. Summary of the Invention

[0005] The purpose of the present invention is to provide a power integrity automated testing system based on multi-parameter intelligent collaboration to solve the problems raised in the above background technology.

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

[0007] A power integrity automated test system based on multi-parameter intelligent collaboration, which includes a power type identification and configuration module, a multi-parameter acquisition module, an intelligent scoring module, an automated evaluation module, and a feedback module;

[0008] The power type identification and configuration module is used to automatically identify the power type according to the preset interface and call the preset test parameters from the database to generate a test plan;

[0009] A multi-parameter acquisition module is used to synchronously collect multi-modal data output by the power supply according to the test plan. The multi-modal data includes test parameters of multiple power supplies;

[0010] Intelligent scoring module, used to standardize the scoring of various test parameters of the power supply;

[0011] An automated assessment module that constructs a three-dimensional correlation matrix, dynamically adjusts the weights of each scored test parameter, and calculates the power integrity assessment index.

[0012] The feedback module is used to generate feedback information according to the evaluation index and generate a visual report of the power integrity test according to a visual template.

[0013] As a preferred solution of the present invention, the multi-parameter acquisition module includes an acquisition unit and a synchronization unit:

[0014] The acquisition unit is used to collect multimodal data output by the power supply through an anti-interference cooperative working mechanism. The multimodal data includes voltage, current, efficiency, ripple noise, temperature distribution and electromagnetic compatibility parameters, wherein: the voltage of the power supply is extracted by a wide-band differential probe and a high-precision analog-to-digital converter; the current of the power supply is collected by a current transformer; the temperature distribution of the power supply is monitored by an infrared thermal imaging sensor; the efficiency of the power supply is monitored by a power analyzer; the ripple noise of the power supply is captured by a high-frequency magnetoelectric coupling probe; and the electromagnetic compatibility parameters of the power supply are monitored by a near-field electromagnetic probe and a spectrum analyzer.

[0015] It should be noted that the anti-interference mechanism includes a differential amplifier stage that eliminates the common-mode voltage between the power ground and the sensor ground point, such as the ground potential difference in the motor drive scenario; automatically switches the gain according to the signal amplitude, such as using high-gain mode to capture microvolt ripple when the power supply is lightly loaded, and switching to low gain to avoid saturation when heavily loaded; the overload protection circuit instantly limits the output amplitude when the load changes suddenly, such as in a short-circuit test, to protect the analog-to-digital converter input; the adaptive LMS algorithm tracks environmental noise in real time, such as the 10kHz-1MHz harmonics generated by the inverter, and generates an anti-phase cancellation signal; the frequency domain noise reduction engine automatically identifies and filters out periodic interference, such as the switching frequency of the DC-DC converter and its harmonics.

[0016] The synchronization unit is used to integrate a wide-band differential probe, a high-precision analog-to-digital converter, a current transformer, an infrared thermal imaging sensor, a power analyzer, a high-frequency magnetoelectric coupling probe, a near-field electromagnetic probe and a spectrum analyzer by setting a wide-band composite sensor array, align the time of each sensor through a unified clock signal, and correct the multimodal data collected by the wide-band composite sensor array in real time based on temperature.

[0017] As a preferred solution of the present invention, the intelligent scoring module is used to perform standardized scoring on various test parameters of the power supply:

[0018] The power supply voltage is normalized and rated by the power supply voltage tolerance requirement, which is calculated as:

[0019]

[0020] Among them, S V Indicates voltage rating, V′ indicates rated voltage, V rate Indicates real-time voltage, ΔV max Indicates the maximum allowable deviation;

[0021] Ripple noise is scored in sections according to the ripple test specification. The calculation formula is:

[0022]

[0023] Among them, S Ripple Ripple noise score, Ripple pp represents the peak-to-peak value;

[0024] It's important to explain that the peak-to-peak value is a key parameter that describes the amplitude of signal fluctuations. For ripple noise, the peak-to-peak value refers to the difference between the maximum and minimum values ​​of the ripple noise signal. It reflects the magnitude of the ripple noise and is one of the most intuitive metrics for measuring ripple noise. By measuring the peak-to-peak value of the ripple noise signal, we can clearly understand the fluctuation range of the ripple noise in the power supply output. For example, if the peak-to-peak value of a power supply's ripple noise is 50mV, this means that a fluctuating signal with a maximum amplitude of 50mV is superimposed on the DC voltage output of the power supply. In power supply design and application, the peak-to-peak value directly affects the quality and stability of the power supply. Excessive peak-to-peak values ​​can cause malfunctions in subsequent circuits, such as affecting the accuracy of analog circuits and causing false triggering in digital circuits. The peak-to-peak value of ripple noise can vary across different frequency ranges. Generally speaking, in switching power supplies, the peak-to-peak value of ripple is relatively large at the switching frequency and its harmonic frequencies, as these frequencies are directly related to the operation of the switching diode. The peak-to-peak value of noise, on the other hand, is more randomly distributed over a wide frequency range. However, at certain frequencies, it may exhibit larger peak-to-peak values ​​due to resonance of circuit components or external interference. For example, in a switching power supply with a switching frequency of 100kHz, the peak-to-peak ripple may be more pronounced at multiples of the switching frequency, such as 100kHz and 200kHz. Furthermore, the peak-to-peak noise may increase in frequency bands with strong external electromagnetic interference. The parameters of components such as capacitors and inductors in the circuit affect the peak-to-peak value of the ripple noise. Capacitors provide filtering, smoothing the output voltage and reducing the peak-to-peak value of the ripple noise. For example, connecting a larger capacitor in parallel with the power supply output can enhance the circuit's low-frequency filtering capability, thereby reducing the peak-to-peak value of the ripple noise. The inductor, through its energy storage and release properties, can suppress high-frequency ripple noise. Properly selecting the parameters of the capacitor and inductor can optimize the power supply's filtering effectiveness and ensure that the peak-to-peak value of the ripple noise meets design requirements.

[0025] The temperature gradient is scored according to the heat distribution uniformity requirement, and the calculation formula is:

[0026]

[0027] Among them, S T represents the score of the temperature gradient, represents the temperature gradient, Indicates the standard value of temperature gradient;

[0028] The electromagnetic compatibility parameters are scored according to the electromagnetic compatibility standard, and the calculation formula is:

[0029]

[0030] Among them, S EMIIndicates the score of the electromagnetic compatibility parameter, w(f) indicates the preset frequency band weight, Limit(f) indicates the CISPR 32 Class B limit, and EMI(f) indicates the electromagnetic compatibility parameter;

[0031] The dynamic response time is scored according to the power supply design guidelines and is calculated as:

[0032]

[0033] Among them, S response represents the response time score, t rise Indicates the actual rise time, t min represents the theoretical minimum value, t max Indicates the maximum value allowed;

[0034] It should be explained that the actual rise time usually refers to the time required for the signal to rise from 10% to 90% of the steady-state value. For example, when the load suddenly decreases, the output voltage recovers from a falling state to the target value; when the load suddenly increases, the output current climbs from a low value to the required value. The trigger condition is a load step change.

[0035] As a preferred solution of the present invention, the automated evaluation module includes a preprocessing unit, a matrix construction unit, a dynamic adjustment unit and an evaluation unit:

[0036] The preprocessing unit is used to extract the multimodal data collected by the multi-parameter acquisition module, perform data alignment, and preprocess the multimodal data; including: converting the voltage and current into per-unit values, wherein the reference value is 110% of the rated parameter; and normalizing the temperature based on the thermal resistance model.

[0037] Where, T represents the normalized temperature value, T al Indicates the actual measured temperature value, T an Indicates the reference value of temperature, R th represents the thermal resistance coefficient;

[0038] High-frequency interference in ripple noise is removed through wavelet transform; the db4 wavelet basis and the number of decomposition layers are selected; multi-level wavelet decomposition is performed on the noisy signal to obtain approximate coefficients and detail coefficients of each layer; threshold rules such as hard thresholding or soft thresholding are applied to the high-frequency detail coefficients to remove noise-dominated coefficients; and the denoised signal is reconstructed using the processed coefficients.

[0039] It should be noted that the purpose of performing data alignment is to avoid timing deviations caused by differences in sensor response times. The purpose of the preprocessing unit is to convert heterogeneous sensor data into comparable data in a unified mathematical space; eliminate system errors caused by hardware sampling asynchrony; and meet the standardized requirements of machine learning algorithms for input data distribution to prepare for model input.

[0040] The matrix construction unit is used to construct a three-dimensional correlation matrix based on the processed multimodal data, which is expressed as follows:

[0041]

[0042] Among them, V(t) represents the real-time voltage value, Represents the partial derivative of current with respect to voltage, reflecting the dynamic characteristics of the load; Φ T (V) represents the voltage-temperature transfer function, which quantifies the effect of voltage fluctuation on the temperature field; represents the temperature gradient, represents the spatial rate of change of temperature per unit time, η(V,I) represents the efficiency of the power supply, ψ EMI (f) represents the EMI coupling coefficient, which describes the correlation strength between the voltage spectrum and electromagnetic interference; Ripple pp Indicates the peak-to-peak ripple, which characterizes the output voltage fluctuation range. Indicates the power change rate, reflecting the transient load response capability; Γ THD Represents the total harmonic distortion correlation factor, quantifying the impact of harmonic distortion on system stability;

[0043] The dynamic adjustment unit is used for the weight coefficient of each scored test parameter;

[0044] The evaluation unit is used to calculate an evaluation index of the power supply.

[0045] As a preferred solution of the present invention, the dynamic adjustment unit includes:

[0046] Set the basic weights of each scored test parameter and predefine n types of working condition templates, where each working condition template includes a corresponding weight adjustment coefficient table;

[0047] Extract key indicators from the three-dimensional correlation matrix and use the k-nearest neighbor algorithm to match the current matrix features with the feature vectors in the working condition template;

[0048] The weight coefficients are updated according to the matching working condition templates, and the updated weight coefficients are normalized so that the weighted sum of all weight coefficients is equal to 1, thus completing the comprehensive normalization of weights;

[0049] The standardized scores of each test parameter of the power supply calculated by the intelligent scoring module are weighted and integrated to calculate the comprehensive score of the power supply. The formula is as follows:

[0050]

[0051] Among them, KA represents the comprehensive score of the power supply, S i represents the standardized score of the real-time test parameters of the i-th power supply, wi represents the weight coefficient of the i-th power real-time test parameter, and n represents the total number of power real-time test parameter types with comprehensive scores.

[0052] As a preferred solution of the present invention, the feedback module includes a response unit and a visualization unit;

[0053] The response unit is configured to output a prompt message indicating that the power integrity is good when the comprehensive score of the power supply is greater than or equal to a score threshold; and output a warning message indicating that there is a power failure when the comprehensive score of the power supply is less than the score threshold;

[0054] The visualization unit is used to generate a power integrity test report based on a visualization template and display it in a graphical interface based on all data generated by the power type identification and configuration module, the multi-parameter acquisition module, the intelligent scoring module, the automated evaluation module and the feedback module.

[0055] As a preferred solution of the present invention, the power type identification and configuration module is used to automatically identify the power type according to the preset interface and generate a unique identification code, and call the corresponding preset test parameters from the database according to the unique identification code to generate a test plan.

[0056] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: in the power integrity automated test system based on multi-parameter intelligent collaboration provided by the present invention, the power type is automatically identified by the power type identification and configuration module and the preset test parameters are called from the database to generate a test plan; the multi-parameter acquisition module synchronously acquires multimodal data of the power supply output, and the multimodal data includes test parameters of multiple power supplies; the intelligent scoring module performs standardized scoring on each test parameter of the power supply; the automated evaluation module constructs a three-dimensional correlation matrix and dynamically adjusts the weights of each scored test parameter to calculate the power integrity evaluation index; the feedback module generates feedback information and generates a visual report of the power integrity test according to the visual template; the present invention realizes the automation of power integrity testing through the mutual cooperation of the above modules, which not only saves manpower but also improves the objectivity of the evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0058] Figure 1 It is a structural diagram of the power integrity automatic testing system based on multi-parameter intelligent collaboration of the present invention. DETAILED DESCRIPTION

[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0060] See also Figure 1 , in this embodiment 1: a power integrity automated testing system based on multi-parameter intelligent collaboration is provided, the system including a power type identification and configuration module, a multi-parameter acquisition module, an intelligent scoring module, an automated evaluation module and a feedback module;

[0061] The power type identification and configuration module is used to automatically identify the power type according to the preset interface and call the preset test parameters from the database to generate a test plan;

[0062] A multi-parameter acquisition module is used to synchronously collect multi-modal data output by the power supply according to the test plan. The multi-modal data includes test parameters of multiple power supplies;

[0063] Intelligent scoring module, used to standardize the scoring of various test parameters of the power supply;

[0064] An automated assessment module that constructs a three-dimensional correlation matrix, dynamically adjusts the weights of each scored test parameter, and calculates the power integrity assessment index.

[0065] The feedback module is used to generate feedback information according to the evaluation index and generate a visual report of the power integrity test according to a visual template.

[0066] Preferably, the multi-parameter acquisition module includes an acquisition unit and a synchronization unit:

[0067] The acquisition unit is used to acquire multimodal data output by the power supply through an anti-interference cooperative working mechanism. The multimodal data includes test parameters of multiple power supplies, including voltage, current, efficiency, ripple noise, temperature distribution, and electromagnetic compatibility parameters, wherein: the voltage of the power supply is extracted by a wide-band differential probe and a high-precision analog-to-digital converter; the current of the power supply is acquired by a current transformer; the temperature distribution of the power supply is monitored by an infrared thermal imaging sensor; the efficiency of the power supply is monitored by a power analyzer; the ripple noise of the power supply is captured by a high-frequency magnetoelectric coupling probe; and the electromagnetic compatibility parameters of the power supply are monitored by a near-field electromagnetic probe and a spectrum analyzer.

[0068] The synchronization unit is used to integrate a wide-band differential probe, a high-precision analog-to-digital converter, a current transformer, an infrared thermal imaging sensor, a power analyzer, a high-frequency magnetoelectric coupling probe, a near-field electromagnetic probe and a spectrum analyzer by setting a wide-band composite sensor array, align the time of each sensor through a unified clock signal, and correct the multimodal data collected by the wide-band composite sensor array in real time based on temperature.

[0069] Preferably, the intelligent scoring module is used to perform standardized scoring on various test parameters of the power supply:

[0070] The power supply voltage is normalized and rated by the power supply voltage tolerance requirement, which is calculated as:

[0071]

[0072] Among them, S V Indicates voltage rating, V′ indicates rated voltage, V rate Indicates real-time voltage, ΔV max Indicates the maximum allowable voltage deviation;

[0073] Ripple noise is scored in sections according to the ripple test specification. The calculation formula is:

[0074]

[0075] Among them, S Ripple Ripple noise score, Ripple pp represents the peak-to-peak value;

[0076] The temperature gradient is scored according to the heat distribution uniformity requirement, and the calculation formula is:

[0077]

[0078] Among them, S T represents the score of the temperature gradient, represents the temperature gradient, Indicates the standard value of temperature gradient;

[0079] The electromagnetic compatibility parameters are scored according to the electromagnetic compatibility standard, and the calculation formula is:

[0080]

[0081] Among them, S EMI Indicates the score of the electromagnetic compatibility parameter, w(f) indicates the preset frequency band weight, Limit(f) indicates the CISPR 32 Class B limit, and EMI(f) indicates the electromagnetic compatibility parameter;

[0082] The dynamic response time is scored according to the power supply design guidelines and is calculated as:

[0083]

[0084] Among them, S response represents the response time score, t rise Indicates the actual rise time, t min represents the theoretical minimum value, t max Indicates the maximum value allowed.

[0085] Preferably, the automated evaluation module includes a preprocessing unit, a matrix construction unit, a dynamic adjustment unit and an evaluation unit:

[0086] The preprocessing unit is used to extract the multimodal data collected by the multi-parameter acquisition module, perform data alignment, and preprocess the multimodal data; including: converting voltage and current into per-unit values; normalizing temperature based on a thermal resistance model; and removing high-frequency interference in ripple noise through wavelet transform;

[0087] The matrix construction unit is used to construct a three-dimensional correlation matrix based on the processed multimodal data, which is expressed as follows:

[0088]

[0089] Among them, V(t) represents the real-time voltage value, Represents the partial derivative of current with respect to voltage, which reflects the dynamic characteristics of the load; Φ T (V) represents the voltage-temperature transfer function used to quantify the effect of voltage fluctuation on the temperature field; It represents the temperature gradient used to reflect the spatial rate of change of temperature per unit time, η(V,I) represents the efficiency of the power supply, ψ EMI (f) represents the electromagnetic compatibility coupling coefficient used to describe the correlation strength between voltage spectrum and electromagnetic interference; Ripple pp Indicates the peak-to-peak value used to characterize the output voltage fluctuation range. Indicates the power change rate used to reflect the transient load response capability; Γ THD represents the total harmonic distortion correlation factor used to quantify the impact of harmonic distortion on system stability;

[0090] The dynamic adjustment unit is used to dynamically adjust the weight coefficients of the test parameters after scoring;

[0091] The evaluation unit is used to calculate an evaluation index of the power supply.

[0092] Preferably, the dynamic adjustment unit includes:

[0093] Set the basic weights of each scored test parameter and predefine n working condition templates, each of which includes a corresponding weight adjustment coefficient table;

[0094] Extract key indicators from the three-dimensional correlation matrix and use the k-nearest neighbor algorithm to match the current matrix features with the feature vectors in the working condition template;

[0095] For example: In the three-dimensional correlation matrix of transient conditions (power change rate) increases significantly, triggering the increase of voltage / current weight in the dynamic weight model; in the three-dimensional correlation matrix of thermal stress conditions (Temperature gradient) increases abnormally, and the analysis weight of the temperature gradient is automatically enhanced.

[0096] The weight coefficients are updated according to the matching working condition templates, and the updated weight coefficients are normalized so that the weighted sum of all weight coefficients is equal to 1, thus completing the comprehensive normalization of weights;

[0097] The standardized scores of each test parameter of the power supply calculated by the intelligent scoring module are weighted and integrated to calculate the comprehensive score of the power supply. The formula is as follows:

[0098]

[0099] Among them, KA represents the comprehensive score of the power supply, S i represents the standardized score of the real-time test parameters of the i-th power supply, w i represents the weight coefficient of the i-th power real-time test parameter, and n represents the total number of power real-time test parameter types with comprehensive scores.

[0100] Preferably, the feedback module includes a response unit and a visualization unit;

[0101] The response unit is configured to output a prompt message indicating that the power integrity is good when the comprehensive score of the power supply is greater than or equal to a score threshold; and output a warning message indicating that there is a power failure when the comprehensive score of the power supply is less than the score threshold;

[0102] The visualization unit is used to generate a power integrity test report based on a visualization template and display it in a graphical interface based on all data generated by the power type identification and configuration module, the multi-parameter acquisition module, the intelligent scoring module, the automated evaluation module and the feedback module.

[0103] Preferably, the power type identification and configuration module is used to automatically identify the power type according to a preset interface and generate a unique identification code, and call corresponding preset test parameters from a database according to the unique identification code to generate a test plan.

[0104] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0105] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. The power integrity automated test system based on multi-parameter intelligent collaboration is characterized by: The system includes a power type identification and configuration module, a multi-parameter acquisition module, an intelligent scoring module, an automated evaluation module, and a feedback module; The power type identification and configuration module is used to automatically identify the power type according to the preset interface and call the preset test parameters from the database to generate a test plan; A multi-parameter acquisition module is used to synchronously collect multi-modal data output by the power supply according to the test plan. The multi-modal data includes test parameters of multiple power supplies; Intelligent scoring module, used to standardize the scoring of various test parameters of the power supply; An automated assessment module that constructs a three-dimensional correlation matrix, dynamically adjusts the weights of each scored test parameter, and calculates the power integrity assessment index. The automated evaluation module includes a pre-processing unit, a matrix building unit, a dynamic adjustment unit and an evaluation unit; A preprocessing unit is used to extract the multimodal data collected by the multi-parameter acquisition module, perform data alignment, and preprocess the multimodal data; including: converting voltage and current into per-unit values; normalizing temperature based on a thermal resistance model; and removing high-frequency interference in ripple noise through wavelet transform; A matrix construction unit, used to construct a three-dimensional correlation matrix based on the processed multimodal data; A dynamic adjustment unit, used to dynamically adjust the weight coefficients of each scored test parameter; Set the basic weights of each scored test parameter and predefine n working condition templates, each of which includes a corresponding weight adjustment coefficient table; Extract key indicators from the three-dimensional correlation matrix and use the k-nearest neighbor algorithm to match the current matrix features with the feature vectors in the working condition template; The weight coefficients are updated according to the matching working condition templates, and the updated weight coefficients are normalized so that the weighted sum of all weight coefficients is equal to 1, thus completing the comprehensive normalization of weights; an evaluation unit for calculating an evaluation index of a power supply; The feedback module is used to generate feedback information according to the evaluation index and generate a visual report of the power integrity test according to a visual template.

2. The power integrity automated testing system based on multi-parameter intelligent collaboration according to claim 1, characterized in that: The multi-parameter acquisition module includes an acquisition unit and a synchronization unit: The acquisition unit is used to acquire multimodal data output by the power supply through an anti-interference cooperative working mechanism. The multimodal data includes test parameters of multiple power supplies, including voltage, current, efficiency, ripple noise, temperature distribution, and electromagnetic compatibility parameters, wherein: the voltage of the power supply is extracted by a wide-band differential probe and a high-precision analog-to-digital converter; the current of the power supply is acquired by a current transformer; the temperature distribution of the power supply is monitored by an infrared thermal imaging sensor; the efficiency of the power supply is monitored by a power analyzer; the ripple noise of the power supply is captured by a high-frequency magnetoelectric coupling probe; and the electromagnetic compatibility parameters of the power supply are monitored by a near-field electromagnetic probe and a spectrum analyzer. The synchronization unit is used to integrate a wide-band differential probe, a high-precision analog-to-digital converter, a current transformer, an infrared thermal imaging sensor, a power analyzer, a high-frequency magnetoelectric coupling probe, a near-field electromagnetic probe and a spectrum analyzer by setting a wide-band composite sensor array, align the time of each sensor through a unified clock signal, and correct the multimodal data collected by the wide-band composite sensor array in real time based on temperature.

3. The power integrity automated testing system based on multi-parameter intelligent collaboration according to claim 2, characterized in that: The intelligent scoring module is used to perform standardized scoring on various test parameters of the power supply: The power supply voltage is normalized and rated by the power supply voltage tolerance requirement, which is calculated as: Among them, S V Indicates voltage rating, V′ indicates rated voltage, V rate Indicates real-time voltage, ΔV max Indicates the maximum allowable voltage deviation; Ripple noise is scored in sections according to the ripple test specification. The calculation formula is: Among them, S Ripple Ripple noise score, Ripple pp represents the peak-to-peak value; The temperature gradient is scored according to the heat distribution uniformity requirement, and the calculation formula is: Among them, S T represents the score of the temperature gradient, represents the temperature gradient, Indicates the standard value of temperature gradient; The electromagnetic compatibility parameters are scored according to the electromagnetic compatibility standard, and the calculation formula is: Among them, S EMI Indicates the score of the electromagnetic compatibility parameter, w(f) indicates the preset frequency band weight, Limit(f) indicates the CISPR32 Class B limit, and EMI(f) indicates the electromagnetic compatibility parameter; The dynamic response time is scored according to the power supply design guidelines and is calculated as: Among them, S response represents the response time score, t rise Indicates the actual rise time, t min represents the theoretical minimum value, t max Indicates the maximum value allowed.

4. The power integrity automated testing system based on multi-parameter intelligent collaboration according to claim 3, characterized in that: The automated evaluation module includes a pre-processing unit, a matrix construction unit, a dynamic adjustment unit, and an evaluation unit: The preprocessing unit is used to extract the multimodal data collected by the multi-parameter acquisition module, perform data alignment, and preprocess the multimodal data; including: converting voltage and current into per-unit values; normalizing temperature based on a thermal resistance model; and removing high-frequency interference in ripple noise through wavelet transform; The matrix construction unit is used to construct a three-dimensional correlation matrix based on the processed multimodal data, which is expressed as follows: Among them, V(t) represents the real-time voltage value, Represents the partial derivative of current with respect to voltage, which reflects the dynamic characteristics of the load; Φ T (V) represents the voltage-temperature transfer function used to quantify the effect of voltage fluctuation on the temperature field; It represents the temperature gradient used to reflect the spatial rate of change of temperature per unit time, η(V,I) represents the efficiency of the power supply, ψ EMI (f) represents the electromagnetic compatibility coupling coefficient used to describe the correlation strength between voltage spectrum and electromagnetic interference; Ripple pp Indicates the peak-to-peak value used to characterize the output voltage fluctuation range. Indicates the power change rate used to reflect the transient load response capability; Γ THD represents the total harmonic distortion correlation factor used to quantify the impact of harmonic distortion on system stability; The dynamic adjustment unit is used to dynamically adjust the weight coefficients of the test parameters after scoring; The evaluation unit is used to calculate an evaluation index of the power supply.

5. The power integrity automated testing system based on multi-parameter intelligent collaboration according to claim 4, characterized in that: The dynamic adjustment unit includes: Set the basic weights of each scored test parameter and predefine n working condition templates, each of which includes a corresponding weight adjustment coefficient table; Extract key indicators from the three-dimensional correlation matrix and use the k-nearest neighbor algorithm to match the current matrix features with the feature vectors in the working condition template; The weight coefficients are updated according to the matching working condition templates, and the updated weight coefficients are normalized so that the weighted sum of all weight coefficients is equal to 1, thus completing the comprehensive normalization of weights; The standardized scoring values ​​of each test parameter of the power supply calculated by the intelligent scoring module are weighted and integrated to calculate the evaluation index of the power supply. The formula is as follows: Among them, KA represents the evaluation index of the power supply, S i represents the standardized score of the real-time test parameters of the i-th power supply, w i represents the weight coefficient of the i-th power real-time test parameter, and n represents the total number of power real-time test parameter types with comprehensive scores.

6. The power integrity automated testing system based on multi-parameter intelligent collaboration according to claim 5, characterized in that: The feedback module includes a response unit and a visualization unit; The response unit is configured to output a prompt message indicating that the power integrity is good when the evaluation index of the power supply is greater than or equal to the scoring threshold; and output a warning message indicating that there is a power failure when the evaluation index of the power supply is less than the scoring threshold; The visualization unit is used to generate a power integrity test report based on a visualization template and display it in a graphical interface based on all data generated by the power type identification and configuration module, the multi-parameter acquisition module, the intelligent scoring module, the automated evaluation module and the feedback module.

7. The power integrity automated testing system based on multi-parameter intelligent collaboration according to claim 6, characterized in that: The power type identification and configuration module is used to automatically identify the power type according to the preset interface and generate a unique identification code, and call the corresponding preset test parameters from the database according to the unique identification code to generate a test plan.

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