An automatic testing method and system for a circuit board of a multifunctional car washer

Abstract

The present application provides an automatic testing method and system for a multi-functional car wash machine circuit board, which relates to the technical field of circuit board detection. The method includes: collecting in real time the feedback response instructions of the output ports of the car wash machine circuit board; determining the dynamic timing deviation of the car wash machine in each working mode, and determining the failure loss level when the car wash machine circuit board fails during operation according to the dynamic timing deviations of the car wash machine in all working modes; identifying the failure distribution information when the car wash machine circuit board fails during operation and performing segmented isolation to obtain the failure isolation degree of the car wash machine circuit board when it fails during operation, and determining the homomorphic offset period during the test of the car wash machine circuit board based on the failure isolation degree and the failure loss level; and performing automatic compensation testing on the car wash machine circuit board according to the homomorphic offset period. The present application can perform failure detection in the test of the multi-functional car wash machine circuit board by applying dynamic test signals and combining heat source scanning and timing matching, so as to improve the real-time performance of circuit board testing.

Description

Technical Field

[0001] This application relates to the technical field of circuit board detection. More specifically, this application relates to an automatic test method and system for a circuit board of a multi-functional car wash machine. Background Art

[0002] Circuit board detection refers to checking the performance, stability, and reliability of a circuit board under different working conditions through a series of test means and techniques. It includes the evaluation of multiple aspects such as signal transmission, temperature change, and power consumption of the circuit board to ensure the normal operation of the circuit board in actual applications. Common detection methods include applying test signals using a signal generator, real-time monitoring of the circuit board response through sensors, and collecting and analyzing the output signals of the circuit board. Especially in multi-functional devices such as complex systems like car wash machines, the reliability of the circuit board is crucial, and any small failure may cause abnormal operation of the device and affect the performance of the car wash machine.

[0003] However, in the existing automatic test methods and systems for circuit boards of multi-functional car wash machines, they rely on static testing and a single signal acquisition method, lacking comprehensive detection of the dynamic changes of the circuit board under multiple working modes, resulting in the inability to accurately capture the performance fluctuations of the circuit board under different loads, temperature changes, etc., and thus unable to evaluate the dynamic timing deviation and failure mode of the system in real time. Therefore, the existing test methods cannot effectively identify the failure risks and dynamic changes that may occur in the circuit board during actual use, reducing the accuracy and reliability of the test. Therefore, how to perform failure detection by applying dynamic test signals and combining heat source scanning and timing matching in the circuit board test of a multi-functional car wash machine to improve the real-time performance of the circuit board test is a problem faced by the industry. Summary of the Invention

[0004] This application provides an automatic test method and system for a circuit board of a multi-functional car wash machine, which can perform failure detection by applying dynamic test signals and combining heat source scanning and timing matching in the circuit board test of a multi-functional car wash machine to improve the real-time performance of the circuit board test.

[0005] In a first aspect, this application provides an automatic test method for a circuit board of a multi-functional car wash machine, and the test method includes the following steps:

[0006] Apply a test signal to the input port of the car wash machine circuit board through a signal generator, and collect the feedback response instruction of the output port of the car wash machine circuit board in real time;

[0007] Perform timing matching on the feedback response instruction under various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine under each working mode, and then determine the failure loss level when the car wash machine circuit board fails to operate according to the dynamic timing deviations of the car wash machine under all working modes;

[0008] Perform regional heat source scanning on the car wash machine circuit board, identify the failure distribution information when the car wash machine circuit board fails to operate, segment and isolate the failure distribution information to obtain the failure isolation degree of the car wash machine circuit board when it fails to operate, and then determine the homomorphic offset period during the test of the car wash machine circuit board based on the failure isolation degree and the failure loss level;

[0009] Perform an automatic compensation test on the car wash machine circuit board according to the homomorphic offset period.

[0010] In this embodiment, the feedback response instruction refers to the electrical signal output communication response of the car wash machine circuit board after receiving an input signal.

[0011] In this embodiment, performing timing matching on the feedback response instruction under various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine under each working mode specifically includes:

[0012] Obtain the timing execution data of the feedback response instruction under various working modes of the car wash machine, and extract the dynamic time characteristics between the instruction trigger and the mechanical action.

[0013] Based on the control logic requirements of different modes and the timing execution data, determine the response threshold boundary for the car wash machine instruction to be transmitted to the execution terminal;

[0014] Align the delay fluctuation range of the car wash machine under each working mode with the dynamic time characteristics to obtain the instruction matching degree of the car wash machine under various working modes;

[0015] Determine the dynamic timing deviation of the car wash machine under each working mode according to the instruction matching degree and the response threshold boundary.

[0016] In this embodiment, determining the failure loss level of the car wash machine circuit board when it fails to operate based on the dynamic timing deviation of the car wash machine under all working modes specifically includes:

[0017] Determine the timing correlation characteristics of abnormal instruction transmission and execution signals of the car wash machine circuit board according to the dynamic timing deviation;

[0018] Determine the operation state deviation degree and failure impact attribute of different sub-modules of the car wash machine under operation deviation according to the timing correlation characteristics;

[0019] Determine the failure loss level of the car wash machine circuit board when it fails to operate according to the operation state deviation degree and the failure impact attribute.

[0020] In this embodiment, performing regional heat source scanning on the car wash machine circuit board to identify the failure distribution information when the car wash machine circuit board fails to operate specifically includes:

[0021] Use an infrared thermal imager to perform regional heat source scanning on the circuit board of the car wash machine, and obtain the dynamic temperature gradient distribution data of each area of the circuit board under different working modes;

[0022] Based on the heat conduction model, determine the heat source aggregation degree in the area of abnormal temperature rise in the circuit board;

[0023] Determine the failure distribution information when the circuit board of the car wash machine fails to operate through the dynamic temperature gradient distribution data and the heat source aggregation degree.

[0024] In this embodiment, segmenting and isolating the failure distribution information to obtain the failure isolation degree of the circuit board of the car wash machine during failure to operate specifically includes:

[0025] Perform spatial clustering segmentation on the area of abnormal heat source of the circuit board of the car wash machine according to the failure distribution information, and generate a failure isolation interval based on the heat source aggregation degree;

[0026] Determine the cross-region signal correlation quantity of the failure characteristics within the failure isolation interval;

[0027] Determine the failure isolation degree of the circuit board of the car wash machine during failure to operate through the cross-region signal correlation quantity.

[0028] In this embodiment, determining the homomorphic offset period during the test of the circuit board of the car wash machine from the failure isolation degree and the failure loss level specifically includes:

[0029] Extract the homomorphic offset baseline parameters of abnormal heat source and signal failure in the circuit board test through the correlation weight between the failure isolation degree and the failure loss level;

[0030] Based on the failure isolation degree and the failure loss quantification model, construct a dynamic time-varying mapping function for heat source-signal collaborative failure;

[0031] Combined with the dynamic time-varying mapping function, determine the timing drift correction factor of abnormal heat source and signal failure in the circuit board test;

[0032] Determine the homomorphic offset period during the test of the circuit board of the car wash machine according to the homomorphic offset baseline parameters and the timing drift correction factor.

[0033] In this embodiment, automatically compensating and testing the circuit board of the car wash machine according to the homomorphic offset period specifically includes:

[0034] Generate an adaptive compensation pulse sequence for the circuit board test signal according to the homomorphic offset period;

[0035] Construct a signal integrity verification matrix in the compensation test by real-time collecting the response signal attenuation gradient of the circuit board;

[0036] Generate a closed-loop compensation mapping relationship under the failure scenario of the car wash machine circuit board based on the signal integrity verification matrix and the adaptive compensation pulse sequence.

[0037] In this embodiment, when performing regional heat source scanning on the car wash machine circuit board, a high-precision infrared thermal imager is used to comprehensively scan the car wash machine circuit board.

[0038] In a second aspect, the present application provides an automatic test system for a multi-functional car wash machine circuit board, which is used to execute an automatic test method for a multi-functional car wash machine circuit board. The test system includes:

[0039] A test input module, which is used to apply a test signal to the input port of the car wash machine circuit board through a signal generator and collect the feedback response instructions of the output port of the car wash machine circuit board in real time;

[0040] An operation test module, which is used to perform timing matching on the feedback response instructions in various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine in each working mode, and then determine the failure loss level of the car wash machine circuit board when it fails during operation according to the dynamic timing deviations of the car wash machine in all working modes;

[0041] An offset test module, which is used to perform regional heat source scanning on the car wash machine circuit board, identify the failure distribution information when the car wash machine circuit board fails during operation, segment and isolate the failure distribution information to obtain the failure isolation degree of the car wash machine circuit board when it fails during operation, and then determine the homomorphic offset period during the test of the car wash machine circuit board based on the failure isolation degree and the failure loss level;

[0042] A compensation test module, which is used to perform an automatic compensation test on the car wash machine circuit board according to the homomorphic offset period.

[0043] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects:

[0044] Apply a test signal to the input port of the car wash machine circuit board through a signal generator and collect the feedback response instructions of the output port of the car wash machine circuit board in real time; perform timing matching on the feedback response instructions in various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine in each working mode, and then determine the failure loss level of the car wash machine circuit board when it fails during operation according to the dynamic timing deviations of the car wash machine in all working modes; perform regional heat source scanning on the car wash machine circuit board, identify the failure distribution information when the car wash machine circuit board fails during operation, segment and isolate the failure distribution information to obtain the failure isolation degree of the car wash machine circuit board when it fails during operation, and then determine the homomorphic offset period during the test of the car wash machine circuit board based on the failure isolation degree and the failure loss level; perform an automatic compensation test on the car wash machine circuit board according to the homomorphic offset period.

[0045] It can be seen that in this application, the performance fluctuations of the circuit board under different loads, temperature changes and other conditions can be accurately captured. Among them, by applying dynamic test signals and collecting feedback response instructions in real time, the actual operation conditions of the circuit board under different working modes can be accurately simulated, which helps to discover and analyze the performance fluctuations of the circuit board under different loads and environmental conditions. Through timing matching and dynamic timing deviation analysis, the timing changes of the circuit board in each working mode can be accurately identified, so as to deeply analyze the failure mode, which helps to accurately evaluate the failure loss level of the circuit board and ensure the stability and safety of the circuit board operation. Through heat source scanning and segmented isolation of failure distribution information, the abnormal heat source area in the circuit board can be located and the impact of its on system failure can be quantified, which helps to identify and isolate potential fault areas in the early stage and improve the stability and reliability of the circuit board. By dynamically adjusting the homomorphic offset period of the test signal, the signal failure caused by timing deviation or heat source abnormality can be compensated in real time, so as to ensure the accuracy of the test process and signal integrity, further optimize the automatic compensation performance of the circuit board, and improve the automation degree and test accuracy of the system.

[0046] In summary, the technical solution adopted in this application can perform failure detection in the circuit board test of the multi-functional car washer by applying dynamic test signals and combining heat source scanning and timing matching to improve the real-time performance of the circuit board test. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts.

[0048] Figure 1 is a flowchart of an automatic test method for a circuit board of a multi-functional car washer provided by the present application;

[0049] Figure 2 is a schematic flowchart for determining dynamic timing deviation provided by the present application;

[0050] Figure 3 is a schematic flowchart for determining the homomorphic offset period provided by the present application;

[0051] Figure 4 is a module structure diagram of an automatic test for a circuit board of a multi-functional car washer provided by the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0053] The embodiment of the present application provides an automatic test method and system for a multi-functional car wash machine circuit board. The core is to apply a test signal to the input port of the car wash machine circuit board through a signal generator and collect the feedback response instructions at the output port of the car wash machine circuit board in real time; perform timing matching on the feedback response instructions in various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine in each working mode, and then determine the failure loss level when the car wash machine circuit board fails during operation according to the dynamic timing deviations of the car wash machine in all working modes; perform regional heat source scanning on the car wash machine circuit board to identify the failure distribution information when the car wash machine circuit board fails during operation, perform segmented isolation on the failure distribution information to obtain the failure isolation degree when the car wash machine circuit board fails during operation, and then determine the homomorphic offset period during the test of the car wash machine circuit board from the failure isolation degree and the failure loss level; perform automatic compensation testing on the car wash machine circuit board according to the homomorphic offset period.

[0054] Embodiment 1. To better understand the above technical solutions, the above technical solutions will be described in detail below in combination with the accompanying drawings of the specification and specific implementation manners. Refer to Figure 1 As shown, this figure is an exemplary flowchart of the automatic test method for the multi-functional car wash machine circuit board according to this embodiment of the present application. The test method includes the following steps:

[0055] In step S1, a test signal is applied to the input port of the car wash machine circuit board through a signal generator, and the feedback response instructions at the output port of the car wash machine circuit board are collected in real time.

[0056] In specific implementation, first, a programmable signal generator is selected and the required types of test signals are configured, including square waves, pulse signals, sine waves, CAN bus instructions, etc. The output terminal of the signal generator is connected to the input port of the car wash machine circuit board, such as the GPIO port, PWM control port or CAN communication interface. Then, the amplitude, frequency and duty cycle of the test signal are set to ensure that the signal parameters meet the working requirements of the car wash machine circuit board. Next, at the output port of the car wash machine circuit board, that is, the relay output, PWM modulation signal, CAN data frame, etc., a high-precision data acquisition device is connected, such as an oscilloscope, a logic analyzer or a CAN bus analyzer. Then, the trigger condition is set, and the trigger condition can be the rising edge, falling edge or voltage threshold value to accurately capture the feedback response instruction. After collecting the data, the signal is stored in the computer and analyzed through data processing software (such as MATLAB, LabVIEW or Python processing scripts), and the output result of the data processing software is used as the feedback response instruction for the output port of the car wash machine circuit board.

[0057] It should be noted that in this application, the signal generator is an electronic device that generates various electrical signals; the test signal represents a table or document that records and displays the parameter configurations of different test signal types, frequencies, amplitudes, etc.; the feedback response instruction refers to the electrical signal output communication response of the car wash machine circuit board after receiving the input signal.

[0058] In step S2, the feedback response instructions are subjected to timing matching under various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine under each working mode. Furthermore, the failure loss level of the car wash machine circuit board during operation failure is determined based on the dynamic timing deviations of the car wash machine under all working modes.

[0059] Preferably, in this embodiment, the feedback response instructions are subjected to timing matching under various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine under each working mode. Referring to Figure 2 As shown in the figure, which is a schematic flowchart of determining the dynamic timing deviation in some embodiments of this application. The determination of the dynamic timing deviation in this embodiment can be implemented by the following steps:

[0060] In step S21, the timing execution data of the feedback response instructions under various working modes of the car wash machine are obtained, and the dynamic time characteristics between the instruction trigger and the mechanical action are extracted.

[0061] In step S22, based on the control logic requirements of different modes and the timing execution data, the response threshold boundary for the car wash machine instruction to be transmitted to the execution terminal is determined;

[0062] In step S23, align the time delay fluctuation range of the car washer in each working mode with the dynamic time feature to obtain the instruction matching degree of the car washer in various working modes;

[0063] In step S24, determine the dynamic timing deviation of the car washer in each working mode according to the instruction matching degree and the response threshold boundary.

[0064] When specifically implemented, first, input a standardized test signal to the car washer through a signal generator, and use a high-precision data acquisition device to capture the feedback response instruction of the output port in real time. Then, use a motion sensor or a high-frame-rate industrial camera to monitor the mechanical actions of the key components of the car washer and record the timestamps of the mechanical responses. According to the input trigger time of the test signal and the start time of the mechanical action, calculate and extract the dynamic time feature between the instruction trigger and the mechanical action. The specific method can adopt the dynamic time warping (DTW) algorithm for time series data matching and delay analysis. Next, analyze the control requirements of different working modes of the car washer. Different working modes refer to the automatic car washing mode, the manual adjustment mode, the abnormal detection mode, etc. According to the task requirements in each mode, determine the response time for the instruction to be transmitted from the circuit board to the execution terminals, such as motors, sensors, valves, etc. According to the time series data of the feedback response instruction, set a time boundary range as the response threshold boundary for the instruction to be transmitted to the execution terminal. Then, analyze the dynamic time features in different working modes and evaluate the possible time delay fluctuation range during the instruction transmission process, including the time changes caused by load changes, environmental factors, etc. Based on the time delay fluctuation range and the actual dynamic time feature, through a time alignment algorithm, which can be the least squares method, dynamic time warping, adjust the time deviation between the two, and use the rhythm output by the alignment algorithm as the instruction matching degree in each mode. Finally, use the deviation percentage calculation, that is, quantify the difference between the instruction matching degree and the response threshold boundary as a deviation value, which is the dynamic timing deviation of the car washer in each working mode. According to the calculated deviation value, analyze the dynamic timing deviation in each working mode to determine the possible timing mismatch or delay problems in the system during operation.

[0065] It should be noted that in this application, the timing execution data represents the execution time, order, and related dynamic response characteristics of each operation instruction; the dynamic time feature represents the time delay and fluctuation change between the instruction trigger and the mechanical action; the response threshold boundary represents the range between the expected shortest response time and the longest response time; the instruction matching degree represents the timing alignment degree between the instruction transmission and the mechanical response; the dynamic timing deviation represents the time difference between the instruction execution and the mechanical action response.

[0066] In this embodiment, the implementation of determining the failure loss level of the car wash machine circuit board when it fails to operate based on the dynamic timing deviation of the car wash machine in all working modes can be achieved through the following steps:

[0067] Determine the timing correlation characteristics of abnormal instruction transmission and execution signals of the car wash machine circuit board according to the dynamic timing deviation;

[0068] Determine the operating state deviation degree and failure impact attribute of different sub-modules of the car wash machine under the operating deviation according to the timing correlation characteristics;

[0069] Determine the failure loss level of the car wash machine circuit board when it fails to operate according to the operating state deviation degree and the failure impact attribute.

[0070] Specifically, when implementing, first, according to the timing data of the feedback response instruction, analyze the time deviation from the instruction transmission to the execution signal, such as between motor startup and sensor feedback. By comparing with the timing in the normal working mode, identify the abnormal deviations outside the timing fluctuation range, and statistically model the relationship between these abnormal deviations and signal abnormalities using correlation analysis or regression analysis to form the timing correlation characteristics. Then, based on the timing correlation characteristics, analyze the operating states of sub-modules such as the car wash machine motor drive, sensor feedback system, and controller under the influence of timing deviation. For example, the deviation degree of the motor drive system can be evaluated through signal attenuation analysis, or the stability of the control system can be evaluated through an error conduction model. According to the functional importance of the sub-module and its response ability under timing anomalies, determine the failure impact attribute of each sub-module. The failure impact of the module can be quantitatively evaluated using methods such as fault tree analysis (FTA) or failure mode and effects analysis (FMEA). Finally, combining the operating state deviation degree and the failure impact attribute, perform weighted calculations using methods such as the analytic hierarchy process AHP and fuzzy mathematical models, and synthetically weight the operating state deviation degree and the failure impact attribute of each sub-module to determine the overall failure loss level of the car wash machine circuit board. According to the weighted impacts of each sub-module, divide different failure loss levels. These failure loss levels include minor losses, moderate losses, and severe losses, and finally output the failure loss level through the model.

[0071] It should be noted that in this application, the timing correlation characteristics represent the time relationship between instruction transmission and execution signals, including abnormal fluctuations, delays, and their impacts on system performance; the operating state deviation degree represents the degree of performance change of each sub-module under the influence of timing deviation; the failure impact attribute represents the degree of impact of each sub-module on the overall performance and function when a failure occurs; the failure loss level represents the different levels of impact of the failure on the overall function and performance when the operation fails.

[0072] In step S3, perform regional heat source scanning on the car wash machine circuit board, identify the failure distribution information when the car wash machine circuit board fails during operation, segment and isolate the failure distribution information to obtain the failure isolation degree of the car wash machine circuit board during operation failure, and then determine the homomorphic offset period during the test of the car wash machine circuit board based on the failure isolation degree and the failure loss level.

[0073] In this embodiment, the regional heat source scanning of the car wash machine circuit board and the identification of the failure distribution information when the car wash machine circuit board fails during operation can be implemented by the following steps:

[0074] Use an infrared thermal imager to perform regional heat source scanning on the car wash machine circuit board to obtain the dynamic temperature gradient distribution data of each area of the circuit board under different working modes;

[0075] Based on the heat conduction model, determine the heat source aggregation degree of the abnormal temperature rise area in the circuit board;

[0076] Determine the failure distribution information when the car wash machine circuit board fails during operation through the dynamic temperature gradient distribution data and the heat source aggregation degree.

[0077] Specifically, when implementing, first, when performing regional heat source scanning on the car wash machine circuit board, use a high-precision infrared thermal imager to comprehensively scan the car wash machine circuit board to ensure that the resolution, temperature range, and measurement accuracy of the thermal imager meet the requirements. Place the circuit board in the scanning area of the thermal imager under different working modes, including the standby mode, working mode, and abnormal mode, record the temperature data of each area of the circuit board, obtain the dynamic temperature gradient distribution map under each working mode through the thermal imager, record the temperature changes in different areas, and generate the dynamic temperature gradient distribution data. Then, use the heat conduction formula and numerical analysis method to model the heat conduction characteristics of the circuit board, simulate the heat distribution on the circuit board, and establish a heat conduction equation through the thermal conductivity of known circuit board materials such as PCB boards and copper wires. Combining the dynamic temperature gradient distribution data, analyze the temperature change rate and heat source concentration of each area, and use a linear fitting algorithm to calculate the heat source aggregation degree. High-aggregation areas usually represent high-load areas or potential fault sources in the circuit board. Finally, combining the heat source aggregation degree and the dynamic temperature gradient distribution data, use the K-means clustering algorithm or anomaly detection algorithm for data mining, process the temperature data, identify the areas on the circuit board where the temperature rises significantly and has aggregation characteristics, compare the heat source aggregation areas with the functional modules of the circuit board, judge whether there are potential failure risks, and based on the identified abnormal heat source areas, draw the failure distribution map of the circuit board, clearly mark the high-temperature areas or heat source aggregation areas where faults may occur, and use the information of this area as the failure distribution information when the car wash machine circuit board fails during operation.

[0078] It should be noted that in this application, the dynamic temperature gradient distribution data represents the spatial distribution and change rate of temperature changes in each area of the circuit board under different working modes; the heat source aggregation degree represents the degree of heat concentration in the area with abnormal temperature rise in the circuit board; the failure distribution information represents the potential failure areas on the circuit board due to abnormal temperature or heat source aggregation.

[0079] In this embodiment, the failure isolation degree of the car wash machine circuit board during operation failure can be obtained by segmenting and isolating the failure distribution information, which can be achieved by the following steps:

[0080] Perform spatial clustering segmentation on the abnormal heat source area of the car wash machine circuit board according to the failure distribution information to generate a failure isolation interval based on the heat source aggregation degree;

[0081] Determine the cross-region signal correlation quantity of the failure characteristics within the failure isolation interval;

[0082] Determine the failure isolation degree of the car wash machine circuit board during operation failure through the cross-region signal correlation quantity.

[0083] Specifically, first, according to the failure distribution information, use the K-means clustering algorithm to perform spatial clustering on the abnormal heat source area of the car wash machine circuit board. The clustering algorithm can divide the abnormal heat source area into different categories or intervals according to the temperature change characteristics of the area. Then, through the analysis of the heat source aggregation degree, determine the heat source density of each clustering interval. For example, an area with a higher heat source aggregation degree indicates a greater possibility of a fault occurring on the circuit board. According to the clustering results, different failure isolation intervals are divided. The failure risk and heat source concentration degree within each interval are similar, while different intervals are relatively independent, forming an effective isolation area, that is, the failure isolation interval based on the heat source aggregation degree. Then, analyze the signal response characteristics between different failure isolation intervals, especially through the signal propagation path or temperature change propagation path, to determine the degree of association between the intervals. Statistical methods can be used, such as correlation coefficients and cross-correlation, to analyze the interaction of signals in different regions. The calculation results are used as the cross-region signal correlation quantity. Then, combined with the functional modules of the circuit board, evaluate the failure characteristics within each failure isolation interval. The failure characteristics can be temperature changes, heat source concentration degrees, etc., and analyze how these characteristics affect other regions across regions. Finally, according to the obtained cross-region signal correlation quantity, design an evaluation criterion for the failure isolation degree. The failure isolation degree is usually measured by mutual information, correlation coefficient and other correlation metrics. If the correlation quantity between two intervals is relatively high, it means that the propagation of failure is stronger and the failure isolation degree is lower; on the contrary, if the correlation quantity is lower, the failure isolation degree is higher; the correlation quantities between all failure isolation intervals are combined to generate an overall failure isolation degree index.

[0084] It should be noted that in the present application, the failure isolation interval represents the area on the circuit board that isolates potential fault propagation regions; the cross-region signal correlation quantity represents the degree of mutual influence of signal responses between different failure isolation intervals; the failure isolation degree represents the degree of isolation of fault propagation between different regions when the circuit board fails during operation.

[0085] Preferably, in this embodiment, the homomorphic offset period during the testing of the car wash machine circuit board is determined by the failure isolation degree and the failure loss level. Refer to Figure 3 As shown, this figure is a schematic flowchart of determining the homomorphic offset period in some embodiments of the present application. The homomorphic offset period in this embodiment can be implemented by the following steps:

[0086] In step S31, through the correlation weight between the failure isolation degree and the failure loss level, the homomorphic offset baseline parameters of heat source anomaly and signal failure during the circuit board testing are extracted;

[0087] In step S32, based on the failure isolation degree and the failure loss quantification model, a dynamic time-varying mapping function of heat source-signal collaborative failure is constructed;

[0088] In step S33, in combination with the dynamic time-varying mapping function, the timing drift correction factor of heat source anomaly and signal failure during the circuit board testing is determined;

[0089] In step S34, the homomorphic offset period during the testing of the car wash machine circuit board is determined according to the homomorphic offset baseline parameter and the timing drift correction factor.

[0090] In specific implementation, first, a relationship model between the two is established through the quantified failure isolation degree and the failure loss level. The failure isolation degree reflects the fault propagation ability between different regions, while the failure loss level reflects the severity of the fault. The correlation weight between the two is determined through the weighted average method or the regression analysis method. Then, based on the correlation weight, the homomorphic offset baseline parameters of the circuit board during heat source anomaly and signal failure are extracted, which usually involves the synchronous change mode of heat source anomaly and signal failure, as well as their impacts under different working modes. Next, a dynamic heat source-signal collaborative failure quantification model is constructed through the failure isolation degree and the failure loss level. This model takes into account how temperature anomaly and signal failure interact and jointly affect the performance of the circuit board. Then, a dynamic time-varying mapping function is established. This dynamic time-varying mapping function describes the time-varying relationship between the heat source and signal failure. The dynamic time-varying mapping function considers the rate of temperature change, signal transmission delay, and the time-varying characteristics of their interaction. For example, the dynamic time-varying mapping function depends on the signal delay varying with time and the change in heat source aggregation degree. These factors jointly affect the failure process of the circuit board. Then, based on the dynamic time-varying mapping function, the timing drift between heat source anomaly and signal failure is analyzed. By measuring the change in signal delay of the circuit board during the test process, the timing drift between heat source anomaly and signal failure is calculated. By comparing the signal responses in the normal working mode and the fault mode, a correction factor is calculated. This correction factor is used as the timing drift correction factor to adjust the time difference of signal failure caused by heat source anomaly. The timing drift correction factor can help compensate for the timing drift, thereby reducing the error of the test results. Finally, by combining the homomorphic offset baseline parameters and the timing drift correction factor, the homomorphic offset period during the test of the car wash machine circuit board is calculated. The product of the homomorphic offset baseline parameters and the timing drift correction factor can be used as the homomorphic offset period, or it can be calculated through other formulas or numerical simulations and verified and adjusted according to the actual test data, which is not limited here.

[0091] It should be noted that in this application, the homomorphic offset baseline parameter represents the reference time relationship between heat source anomaly and signal failure; the dynamic time-varying mapping function is a relationship model that describes the time-varying relationship between heat source anomaly and signal failure; the timing drift correction factor represents the correction value used to adjust the time difference of signal failure caused by heat source anomaly; the homomorphic offset period represents the time period of the response change of the circuit board under the collaborative action of heat source anomaly and signal failure.

[0092] In step S4, the car wash machine circuit board is automatically compensated and tested according to the homomorphic offset period.

[0093] In this embodiment, the automatic compensation test of the car wash machine circuit board according to the homomorphic offset period can be implemented by the following steps:

[0094] Generate an adaptive compensation pulse sequence for the circuit board test signal according to the homomorphic offset period;

[0095] Construct a signal integrity verification matrix in the compensation test by collecting the attenuation gradient of the response signal of the circuit board in real time;

[0096] Generate a closed-loop compensation mapping relationship in the failure scenario of the car wash machine circuit board based on the signal integrity verification matrix and the adaptive compensation pulse sequence.

[0097] In specific implementation, first, according to the homomorphic offset period, generate a corresponding compensation pulse sequence for the circuit board test signal. The adaptive compensation pulse sequence should take into account the timing drift of the signal and be able to adjust the test signal to make up for the timing deviation caused by abnormal heat sources and signal failures. The adaptive compensation pulse sequence calculates the correction pulse to be applied by comparing the timing response in the failure mode with the timing response in the normal mode. This correction pulse will be adaptively combined with the original test signal to make it as close to the normal state as possible. Then, during the test, by monitoring the attenuation of the response signal of the circuit board in real time and recording the change of the signal intensity over time, this helps to evaluate the attenuation characteristics of the signal under different conditions such as temperature and load. Based on the collected signal attenuation data, construct a signal integrity verification matrix. Each element of this signal integrity verification matrix represents the signal attenuation under specific conditions, so as to compare the signal quality in the normal state and the failure state. For example, the matrix can show whether the signal intensity of the circuit board response meets the expectation under different working modes and can verify whether the signal is transmitted completely through the matrix data. Finally, use an algorithm to establish a closed-loop compensation mapping relationship, which is used to adjust the compensation pulse sequence in real time to make it adaptively adjusted according to the attenuation of the response signal of the circuit board. Among them, the mapping relationship can be generated by machine learning or optimization algorithms, taking into account the data of the signal integrity verification matrix and the effectiveness of the compensation pulse sequence. For example, if the signal attenuation is relatively severe, the closed-loop compensation mapping relationship will indicate a stronger compensation pulse output to ensure the restoration of signal integrity. That is, the automatic compensation test of the car wash machine circuit board is completed.

[0098] It should be noted that in this application, the adaptive compensation pulse sequence refers to the data sequence of the timing drift of the circuit board response and the timing error of the corrected test signal in the failure mode; the attenuation gradient of the response signal represents the attenuation rate of the signal intensity over time or state change of the circuit board under different working conditions. The signal integrity verification matrix represents the data structure for recording and analyzing signal attenuation and transmission quality, and is used to evaluate the integrity and stability of the circuit board response signal under different conditions.

[0099] It can be seen that in the present application, the performance fluctuations of the circuit board under different loads, temperature changes and other conditions can be accurately captured. Among them, by applying a dynamic test signal and collecting the feedback response instructions in real time, the actual operating conditions of the circuit board under different working modes can be accurately simulated, which helps to discover and analyze the performance fluctuations of the circuit board under different loads and environmental conditions. Through timing matching and dynamic timing deviation analysis, the timing changes of the circuit board in each working mode can be accurately identified, so as to conduct in-depth analysis of the failure mode, which helps to accurately evaluate the failure loss level of the circuit board and ensure the stability and safety of the circuit board operation. Through heat source scanning and segmented isolation of the failure distribution information, the abnormal heat source area in the circuit board can be located and the impact of the heat source on system failure can be quantified, which helps to identify and isolate potential fault areas at an early stage and improve the stability and reliability of the circuit board. By dynamically adjusting the homomorphic offset period of the test signal, the signal failure caused by timing deviation or heat source abnormality can be compensated in real time, so as to ensure the accuracy of the test process and signal integrity, further optimize the automatic compensation performance of the circuit board, and improve the automation level and test accuracy of the system.

[0100] In summary, the technical solution adopted in the present application can perform failure detection in the circuit board test of the multi-functional car washer by applying a dynamic test signal and combining heat source scanning and timing matching to improve the real-time performance of the circuit board test.

[0101] Embodiment 2, the present application provides an automatic test system for a multi-functional car washer circuit board, refer to Figure 4 As shown in the figure, which is a module structure diagram of the automatic test system for the multi-functional car washer circuit board according to the present embodiment of the present application, the test system includes:

[0102] A test input module 100, configured to apply a test signal to the input port of the car washer circuit board through a multi-channel signal generator and collect the feedback response instructions of the output port of the car washer circuit board in real time;

[0103] An operation test module 200, configured to perform timing matching on the feedback response instructions in various working modes of the car washer to obtain the dynamic timing deviation of the car washer in each working mode, and further determine the failure loss level of the car washer circuit board when it fails to operate according to the dynamic timing deviation of the car washer in all working modes;

[0104] An offset test module 300, configured to perform regional heat source scanning on the car washer circuit board, identify the failure distribution information when the car washer circuit board fails to operate, perform segmented isolation on the failure distribution information to obtain the failure isolation degree of the car washer circuit board when it fails to operate, and further determine the homomorphic offset period during the test of the car washer circuit board according to the failure isolation degree and the failure loss level;

[0105] The compensation test module 400 is used to automatically perform a compensation test on the car wash machine circuit board according to the homomorphic offset period.

[0106] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 block or multiple blocks.

[0107] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable storage medium, which includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), or other optical disc memories, magnetic disk memories, tape memories, or any other medium that can be used to carry or store data and is computer-readable.

[0108] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

Claims

1. An automatic testing method for a circuit board of a multifunctional car washer, characterized in that, The described test method includes the following steps: Apply a test signal to the input port of the car wash machine circuit board through a signal generator, and collect the feedback response instructions of the output port of the car wash machine circuit board in real time; Perform timing matching on the feedback response instructions in various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine in each working mode, and then determine the failure loss level of the car wash machine circuit board when it fails during operation according to the dynamic timing deviations of the car wash machine in all working modes; Among them, performing timing matching on the feedback response instructions in various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine in each working mode specifically includes: Obtain the timing execution data of the feedback response instructions in various working modes of the car wash machine, and extract the dynamic time characteristics between instruction triggering and mechanical actions; Based on the control logic requirements of different modes and the timing execution data, determine the response threshold boundary for the car wash machine instructions to be transmitted to the execution terminal; Align the delay fluctuation range of the car wash machine in each working mode with the dynamic time characteristics to obtain the instruction matching degree of the car wash machine in various working modes; Determine the dynamic timing deviation of the car wash machine in each working mode according to the instruction matching degree and the response threshold boundary; Determining the failure loss level of the car wash machine circuit board when it fails during operation according to the dynamic timing deviations of the car wash machine in all working modes specifically includes: Determine the timing correlation characteristics of abnormal instruction transmission and execution signals of the car wash machine circuit board according to the dynamic timing deviation; Determine the operation state deviation degree and failure impact attribute of different sub-modules of the car wash machine under operation deviation according to the timing correlation characteristics; Determine the failure loss level of the car wash machine circuit board when it fails during operation according to the operation state deviation degree and the failure impact attribute; Perform regional heat source scanning on the car wash machine circuit board, identify the failure distribution information when the car wash machine circuit board fails during operation, perform segmented isolation on the failure distribution information to obtain the failure isolation degree of the car wash machine circuit board when it fails during operation, and then determine the homomorphic offset period during the test of the car wash machine circuit board from the failure isolation degree and the failure loss level; Among them, performing segmented isolation on the failure distribution information to obtain the failure isolation degree of the car wash machine circuit board when it fails during operation specifically includes: Perform spatial clustering segmentation on the heat source abnormal area of the car wash machine circuit board according to the failure distribution information to generate a failure isolation interval based on the heat source aggregation degree; Determine the cross-region signal correlation quantity of the failure characteristics within the failure isolation interval; Determine the failure isolation degree of the car wash machine circuit board when it fails during operation through the cross-region signal correlation quantity; Determining the homomorphic offset period during the test of the car wash machine circuit board from the failure isolation degree and the failure loss level specifically includes: Extract the homomorphic offset baseline parameters of heat source abnormality and signal failure in the circuit board test through the correlation weight between the failure isolation degree and the failure loss level; Based on the failure isolation degree and the failure loss quantization model, construct a dynamic time-varying mapping function for heat source-signal collaborative failure; Determine the timing drift correction factor for the heat source anomaly and signal failure in the circuit board test in combination with the described dynamic time-varying mapping function; Determine the homomorphic offset period during the circuit board test of the car wash machine according to the homomorphic offset baseline parameter and the timing drift correction factor; Perform an automatic compensation test on the circuit board of the car wash machine according to the homomorphic offset period; Among them, performing an automatic compensation test on the circuit board of the car wash machine according to the homomorphic offset period specifically includes: Generate an adaptive compensation pulse sequence for the circuit board test signal according to the homomorphic offset period; Construct a signal integrity verification matrix in the compensation test by real-time collecting the response signal attenuation gradient of the circuit board; Generate a closed-loop compensation mapping relationship in the failure scenario of the circuit board of the car wash machine based on the signal integrity verification matrix and the adaptive compensation pulse sequence.

2. The automatic testing method for the circuit board of a multifunctional car washer according to claim 1, characterized in that, The feedback response instruction refers to the electrical signal output communication response of the circuit board of the car wash machine after receiving the input signal.

3. The automatic test method for a circuit board of a multifunctional car washer according to claim 1, characterized in that, Performing a regional heat source scan on the circuit board of the car wash machine and identifying the failure distribution information when the circuit board of the car wash machine has a running failure specifically includes: Use an infrared thermal imager to perform a regional heat source scan on the circuit board of the car wash machine to obtain the dynamic temperature gradient distribution data of each area of the circuit board under different working modes; Determine the heat source aggregation degree of the abnormal temperature rise area in the circuit board based on the heat conduction model; Determine the failure distribution information when the circuit board of the car wash machine has a running failure through the dynamic temperature gradient distribution data and the heat source aggregation degree.

4. The automatic test method for the circuit board of a multi-functional car washer according to claim 1, characterized in that, When performing a regional heat source scan on the circuit board of the car wash machine, use a high-precision infrared thermal imager to perform a comprehensive scan on the circuit board of the car wash machine.

5. An automatic test system for a circuit board of a multi-functional car washer, which is used to execute an automatic test method for a circuit board of a multi-functional car washer according to any one of claims 1 to 4, characterized in that, The test system includes: A test input module for applying a test signal to the input port of the circuit board of the car wash machine through a signal generator and real-time collecting the feedback response instruction of the output port of the circuit board of the car wash machine; An operation test module for performing timing matching on the feedback response instruction in various working modes of the car wash machine to obtain the dynamic timing deviation of the car wash machine in each working mode, and then determining the failure loss level of the circuit board of the car wash machine when it has a running failure according to the dynamic timing deviation of the car wash machine in all working modes; An offset test module for performing a regional heat source scan on the circuit board of the car wash machine, identifying the failure distribution information when the circuit board of the car wash machine has a running failure, segmenting and isolating the failure distribution information to obtain the failure isolation degree of the circuit board of the car wash machine when it has a running failure, and then determining the homomorphic offset period during the circuit board test of the car wash machine from the failure isolation degree and the failure loss level; A compensation test module for performing an automatic compensation test on the circuit board of the car wash machine according to the homomorphic offset period.

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