A performance testing system and method for a control board of a household appliance

Abstract

The present invention belongs to the technical field of electrical appliance performance testing, and specifically discloses a performance testing system and method for a control board of a household appliance, including: generating adapted electrical parameters through static power operation testing of the control board as fault simulation reference parameters for a retesting component to obtain fault response data, which helps to improve the process coherence of different testing modes and the accuracy of test results; performing fault simulation testing on different components in the control board by setting fault simulation signals, and determining the fault test type and fault level of the fault simulation instruction based on the abnormal response status of the components suspected of having faults, which can not only achieve the purpose of targeted testing within limited conditions but also save resources; inferring the application life cycle of the control board of the household appliance based on the output data of multi-dimensional testing instructions, and then generating a performance testing report for the control board of the household appliance, which helps to cover the integrity of the control board performance testing.

Description

Technical Field

[0001] The present invention belongs to the technical field of electrical appliance performance testing, and relates to a performance testing system and method for a control board of a household appliance. Background Art

[0002] The functions of household appliances are becoming increasingly rich, and the degree of intelligence is constantly improving. As the core component of household appliances, the performance of the control board directly determines the reliability, stability and user experience of household appliances. At the same time, consumers' requirements for the quality of household appliances are becoming more and more stringent, and the market competition is becoming more and more fierce, which makes the accurate testing of the performance of household appliance control boards the focus of industry attention.

[0003] In the prior art, there have been some solutions related to electrical appliance performance testing. For example, the patent with the Chinese patent publication number CN117075018B discloses an intelligent analysis and management system for the performance testing of a BMS control board, which tests the overcurrent, overvoltage and working performance of the BMS control board, analyzes the corresponding performance compliance coefficient of the BMS control board, and feeds back the test results. Although it realizes the multi-dimensional analysis of the performance of the BMS control board and improves the timeliness and optimization effect of the production plan optimization of the next batch of BMS control boards, it is only limited to the separate testing of multi-dimensional data, the test environment is relatively single and stable, and there is a lack of a subsequent test parameter connection mechanism based on the previous test data, resulting in a large deviation between the analysis result and the actual operation situation, and reducing the practicality of the analysis result.

[0004] Another patent with the Chinese patent publication number CN112014722A discloses an intelligent optoelectronic control board testing system, which uniformly detects the position information, voltage and current, appearance and load information of the optoelectronic control board by setting a position detection module and a performance detection module, and the information processing module compares, statistically processes and stores the detection results, and feeds them back through a feedback module. Although it achieves the effect of automated and intelligent testing through signal simulation, it lacks the fault simulation testing of different components in the control board, so that it is impossible to know the influence degree of a certain component failure on other components and the entire control board system, and it is impossible to determine the sensitivity of the control board to the fault conditions, thus making the test results lack comprehensiveness. Summary of the Invention

[0005] In view of this, in order to solve the problems raised in the above background art, a performance testing system and method for a control board of a household appliance are proposed.

[0006] The object of the present invention can be achieved by the following technical solutions: The present invention provides a performance testing system for a household appliance control board, which system includes: a test instruction configuration module that configures corresponding multi-gear electrical test instructions for each application component by scanning the control board structure, where each electrical test instruction corresponds to multiple electrical gears of an electrical parameter.

[0007] A power detection module that obtains test data of each application component under multi-gear electrical test instructions for differential evaluation, screens retest components whose differences do not exceed the allowable range, and outputs the adapted electrical parameters and adapted gears corresponding to the retest components.

[0008] A fault simulation module that configures fault gears of the fault simulation type based on the adapted electrical parameters of the retest components under the set fault simulation type, and outputs the fault response data of each retest component.

[0009] A suspected component definition module that uses the fault response data for abnormal response diagnosis to define each fault suspected component, and analyzes and outputs the sensitivity of each fault suspected component to the fault simulation.

[0010] A performance diagnosis module that integrates the output data of multi-dimensional test instructions to generate a performance test report for the household appliance control board.

[0011] A performance testing method for a household appliance control board provided in the second aspect of the present invention includes the following steps: Step 1: Configure corresponding multi-gear electrical test instructions for each application component by scanning the control board structure, where each electrical test instruction corresponds to multiple electrical gears of an electrical parameter.

[0012] Step 2: Obtain test data of each application component under multi-gear electrical test instructions for differential evaluation, screen retest components whose differences do not exceed the allowable range, and output the adapted electrical parameters and adapted gears corresponding to the retest components.

[0013] Step 3: Configure fault gears of the fault simulation type based on the adapted electrical parameters of the retest components under the set fault simulation type, and output the fault response data of each retest component.

[0014] Step 4: Use the fault response data for abnormal response diagnosis to define each fault suspected component, and analyze and output the sensitivity of each fault suspected component to the fault simulation.

[0015] Step 5: Integrate the output data of multi-dimensional test instructions to generate a performance test report for the household appliance control board.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) By generating adapted electrical parameters through the static power operation test of the control board and using them as the fault simulation comparison parameters for the retest components to obtain fault response data, the present invention helps to achieve the connectivity between different test modes, thereby improving the process coherence of performance testing and the accuracy of test results.

[0017] (2) By setting fault simulation signals to conduct fault simulation tests on different components in the control board and determining the fault test type and fault gear of the fault simulation instruction based on the abnormal response status of the components suspected of having faults, the present invention can not only achieve the purpose of targeted testing within limited conditions but also save resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0019] Figure 1 It is a schematic diagram of the connection of the system modules of the present invention.

[0020] Figure 2 It is a schematic diagram of the flow of the implementation steps of the method of the present invention.

[0021] Figure 3 It is a schematic diagram of the mapping relationship of the performance toughness indexes of each application component of the control board of the present invention.

[0022] Figure 4 It is a schematic diagram of the corresponding relationship between each retest component and each component suspected of having faults and each application component of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0024] Please refer to Figure 1 As shown, the present invention provides a performance test system for a household appliance control board, which includes: a test instruction configuration module, a power detection module, a fault simulation module, a suspected component definition module, and a performance diagnosis module.

[0025] The test instruction configuration module, power detection module, fault simulation module, and suspected component definition module are connected in sequence, and the performance diagnosis module is connected to the power detection module, fault simulation module, and suspected component definition module respectively.

[0026] The test instruction configuration module configures corresponding multi-gear electrical test instructions for each application component through scanning the control board structure, where each electrical test instruction corresponds to multiple electrical gears of one electrical parameter.

[0027] In a preferred implementation, the configuration of corresponding multi-gear electrical test instructions for each application component through scanning the control board structure includes: scanning the control board structure through a camera device to obtain the model numbers of each application component of the household appliance control board, and then screening multi-gear electrical test instructions matching the model numbers of each application component from the test instruction generation library. The model numbers of each application component such as microcontroller, power management component, capacitor component, communication component, drive component (such as motor or relay drive), user interface component (such as touch screen or button), and memory, etc., are specifically determined according to the type of household appliance product.

[0028] The multi-gear electrical test instructions contain control signals of each electrical parameter at each electrical gear, where each electrical test instruction corresponds to one electrical parameter.

[0029] The multi-gear electrical test refers to testing the adaptation characteristics of different application components to electrical parameters such as current, voltage, and power at different electrical gears by adjusting the control signal. For example, set the electrical parameter set H = {H1, H2, H3}, where H1, H2, and H3 correspond to voltage parameter, current parameter, and power parameter respectively; set the electrical gear set G = {G1, G2, G3}, where G1, G2, and G3 correspond to low, medium, and high respectively. For the current parameter, the low gear corresponds to the device standby current (75% rated current), the medium gear corresponds to the rated working current (100% rated current), and the high gear corresponds to the short-term overload operating current (125% rated current).

[0030] Specifically: Install the household appliance control board on the automated test platform, use a programmable power supply to simulate different voltage / load conditions, and control the gear switching (such as relay matrix) through a PLC or industrial control computer to achieve electrical gear switching.

[0031] The power detection module obtains the test data of each application component under the multi-gear electrical test instructions for differential evaluation, screens the retest components whose differences do not exceed the allowable range, and outputs the adapted electrical parameters and adapted gears corresponding to the retest components.

[0032] In a preferred embodiment, obtaining the test data of each application component under multi-gear electrical test instructions for differential evaluation, and screening the retest components with differences not exceeding the allowable range, which includes: obtaining the difference between the test data of each application component under multi-gear electrical test instructions and the standard value, and the test data being the output current or output voltage or output power, etc. that matches the electrical parameters.

[0033] Define that there is at least one electrical parameter corresponding to at least one electrical gear with the difference from the standard value less than or equal to the allowable difference as the screening condition, mark the application components that meet the screening condition as retest components, and mark the application components that do not meet the screening condition as defective components.

[0034] Count the multiple electrical parameters and electrical gears of each defective component that meet the screening condition, and integrate them into the electrical characteristic boundary index of each defective component.

[0035] The electrical characteristic boundary index refers to the highest electrical gear corresponding to the electrical parameter that causes damage and failure of the application component.

[0036] Specifically, if the difference between the test data generated by a certain application component under a certain electrical test instruction and the standard value exceeds the allowable difference, then mark this application component as a defective component. For example, if the voltage generated by an application component at the low gear of the current test parameter is much lower than the voltage standard value, there may be a phenomenon that the application component is insensitive to voltage induction; if the voltage generated by an application component at the low gear of the current test parameter is much higher than the voltage standard value, there may be a phenomenon that the application component is overly sensitive to voltage induction, which will further reduce the service life of the application component.

[0037] In a further preferred embodiment, the method for obtaining the adapted electrical parameters and adapted gears corresponding to the retest components is as follows: extract the electrical gear with the smallest difference from the differences between the test data of each retest component under multi-gear electrical test instructions and the standard value, and record it as the adapted gear of each electrical parameter of each retest component.

[0038] Divide the power operation constraint fluctuation range corresponding to each electrical parameter, and screen out the electrical parameters with the difference between the test data and the standard value within the constraint fluctuation range, and record them as the adapted electrical parameters of each retest component. For example, set the power operation constraint fluctuation range of the voltage test parameter to [0 - 0.05]. If the output voltage difference of a certain retest component under the voltage test parameter is 0.04, then record the voltage operation parameter as the adapted electrical parameter of this retest component; similarly, if the output current difference of this retest component under the current test parameter is within the constraint fluctuation range, then record the current operation parameter as the adapted electrical parameter of this retest component; summarize the voltage test parameter and the current test parameter as the adapted electrical parameters of this retest component.

[0039] Integrate the adapted electrical parameters and adapted gears of each retest component into the corresponding adapted electrical parameters of each retest component.

[0040] The fault simulation module configures the fault gears of the fault simulation type based on the adapted electrical parameters of the retest component under the set fault simulation type, and outputs the fault response data of each retest component.

[0041] In a preferred implementation manner, the configuration of the fault gears of the fault simulation type based on the adapted electrical parameters of the retest component under the set fault simulation type includes: defining the cumulative value of the ratio of the number of adapted electrical parameters to the total electrical parameters and the ratio of the number of adapted gears that meet the baseline gears in all electrical gears as the structural health rate of the retest component. The larger the ratio of the number of adapted electrical parameters to the total electrical parameters, the wider the adaptation range of the component to the electrical parameters; the larger the ratio of the number of adapted gears that meet the baseline gears in all electrical gears, the better the adaptability of the component to the operation of multiple electrical parameter gears. Therefore, when the cumulative value of the ratio of the number of adapted electrical parameters to the total electrical parameters and the ratio of the number of adapted gears that meet the baseline gears in all electrical gears is larger, it indicates that the structural health rate of the component is higher.

[0042] Among them, the difference setting of the baseline gears of each application component is carried out through empirical fitting. Different application components have their own unique working characteristics and performance requirements. Reasonably setting the baseline gears of each component can enable the entire test system to achieve the best collaborative working effect. For example, setting the corresponding baseline gear of the voltage parameter type of the sensor component to the high gear and setting the corresponding baseline gear of the voltage parameter type of the drive component to the middle gear are specifically determined based on multi-dimensional factors such as the functional characteristics, safety requirements, and working modes of each application component.

[0043] Obtain the control board circuit diagram, and determine the link set components by identifying the electrical connection relationships of each application component in the circuit diagram. The electrical connection relationships are such that if two components are directly connected in the circuit or indirectly connected through some intermediate elements, they may be related when a fault occurs. For example, a resistor is connected to the pin of a chip. When the resistor fails, it may affect the working voltage or signal transmission of the chip, resulting in an abnormality of the chip. Then these two components are fault-related components.

[0044] Statistically determine the probability of fault spread for each retest component associated with each defective component in the link set component. Specifically: Since the signal transmission path of directly connected components is short and direct, the corresponding fault spread probability of directly connected retest components can be set to 1; Since intermediate components can play a certain isolation or buffering role, the corresponding fault spread probability of retest components indirectly connected through intermediate components can be set to be lower than that of directly connected retest components, such as 0.5; For retest components without connectivity (such as some sensors, independent memory chips), set their corresponding fault spread probability to a constant that is not 0 and less than the fault spread probability of indirectly connected components, such as 0.1. Integrate the fault spread probability into the structural health rate of the corresponding retest component to obtain the structural health assessment index of each retest component. Since the fault spread probability has a negative impact on the structural health assessment index, the structural health assessment index can be obtained by multiplying the reciprocal of the fault spread probability by the structural health rate. For example, if the fault spread probability of a certain retest component is 0.5, then multiply 1 / 0.5 by the structural health rate of this retest component to obtain the structural health assessment index of this retest component.

[0045] Import the structural health assessment indexes of each retest component into the fault command signal library to obtain the corresponding adapted fault levels for each fault simulation type of each retest component. The fault command signal library contains simulation signals of different application components corresponding to each fault simulation type and adapted fault levels. The various fault simulation types include electrical faults, mechanical faults, physical and chemical contamination. Electrical faults such as open circuit faults, overvoltage faults, etc., mechanical faults such as vibration or detachment faults, wear or fatigue faults, etc., physical and chemical contamination such as water immersion or overheating faults, material oxidation or contamination faults, etc. The fault levels include first-level fault levels, second-level fault levels..., and the various fault levels correspond to simulation signals of different humidity, different temperature or different open circuit resistances.

[0046] Statistically determine the corresponding adapted fault levels for each fault simulation type of multiple retest components associated in the link set component, and select the lowest same-level adapted fault level of multiple retest components under the same fault simulation type as the finally simulated fault level for multi-point collaborative fault simulation. For example, the adapted fault levels of a certain two retest components under the overvoltage fault simulation type are the first-level fault level and the second-level fault level respectively. In order to avoid excessive damage to one of the retest components caused by the second-level fault level, the first-level fault level is used as the fault level for the collaborative fault simulation of these two retest components under the overvoltage fault simulation type.

[0047] Furthermore, a software simulation algorithm is used to simulate fault scenarios including various fault simulation types and fault gears. For example, for electrical faults, circuit parameters are changed through a mathematical model to simulate different fault types and fault gears; mechanical faults can be simulated by a dynamics model for abnormal movements of mechanical components; physicochemical contamination faults are simulated by a chemical reaction kinetics model for the impact of the corrosion process on circuit performance. According to the adapted electrical parameters of the retest components, relevant parameters in the simulation algorithm are adjusted, the fault simulation types and fault gears are set, and the fault response data of each component is obtained and output.

[0048] In a further preferred embodiment, the fault response data includes response duration, response result, abnormal degree of temperature rise distribution, and abnormal degree of temperature drop distribution.

[0049] The output of the fault response data of each retest component includes: collecting thermal images of each retest component for the corresponding fault gears of each fault simulation type.

[0050] A response period is set, and the response results of each retest component under the simulation of the corresponding fault gears of each fault simulation type are monitored. The response results include response valid and response invalid. The determination condition for response invalid is that no processing measure is generated by the control board within the set response period. For example: when the retest component receives a fault instruction for an open circuit fault, if the control board takes a timely power-off measure within the set response period, it indicates a valid response; otherwise, it is an invalid response.

[0051] In the case of a valid response, the response duration of each retest component for the corresponding fault gears of each fault simulation type is obtained. The response duration is used to reflect the fault handling duration of the retest component from the occurrence of the fault to the generation of a processing measure.

[0052] Based on the thermal image, the spread path of the thermal jump points of each retest component under the simulation of the corresponding fault gears of each fault simulation type is located, and the average temperature change rate between all temperature jump points on the spread path of the thermal jump points is detected to determine the abnormal degree of temperature rise distribution and the abnormal degree of temperature drop distribution of each retest component for the corresponding fault gears of each fault simulation type.

[0053] The temperature jump point refers to the point on the component where the temperature changes significantly, including jumping from a low temperature to a high temperature and jumping from a high temperature to a low temperature.

[0054] The average temperature change rate is specifically: obtaining the temperature change durations corresponding to all temperature jump points jumping from a low temperature to a high temperature or from a high temperature to a low temperature and calculating the mean value.

[0055] Specifically, the average temperature change rate generated during the process of jumping from a low temperature to a high temperature is defined as the abnormal degree of temperature rise distribution, and the average temperature change rate generated during the process of jumping from a high temperature to a low temperature is defined as the abnormal degree of temperature drop distribution.

[0056] The heat jump point spreading path includes the distribution paths of multiple temperature rise change points of the retest component during the temperature rise process and the distribution paths of multiple temperature drop change points during the temperature drop process.

[0057] The present invention generates adapted electrical parameters through the static power operation test of the control board, and uses them as the fault simulation control parameters of the retest component to obtain fault response data, which helps to achieve the connectivity between different test modes, and further improves the process coherence of performance testing and the accuracy of test results.

[0058] The suspected component definition module uses the fault response data to perform abnormal response diagnosis, thereby defining each fault suspected component, and analyzing and outputting the sensitivity of each fault suspected component to fault simulation.

[0059] In a preferred embodiment, the using the fault response data to perform abnormal response diagnosis to define each fault suspected component includes: Step 4-11. Due to the sensitivity differences of different retest components to the fault simulation signal, it is necessary to perform balance correction processing on the response deviation conditions of the corresponding fault simulation signals of the retest components. List the response deviation conditions of each retest component for each fault simulation type to determine the global response deviation compensation factor of each retest component. The response deviation conditions include the signal space conditions identified by the amplitude, frequency or phase differences of the signal at different positions of the component and the signal time conditions identified by the corresponding fault simulation duration of instantaneous faults or continuous faults.

[0060] The different positions of the component are pre-marked key point positions, such as the diode pin positions, the chip silk screen lines or graphic identification positions. On the circuit board, there will be silk screen marks around the installation position of the chip. At the same time, there will also be some silk screen lines or graphics to indicate the pin direction of the chip, such as a small triangle or notch, corresponding to the specific pin identification on the chip, which is convenient for installing and identifying the direction of the chip. Their material functions in the component are different, so their sensitivities to signals are different.

[0061] Specifically, the determination process of the global response deviation compensation factor of each retest component is as follows: Quantify the differences of multiple identification indicators within the corresponding response deviation conditions of each retest component. For example, for the amplitudes at two marked positions on a certain retest component , calculate their deviation and express the relative change degree of the amplitude in percentage as , represents the maximum amplitude term of the two positions, as the baseline parameter for measuring the amplitude percentage. In the same way, obtain the relative change degree of the frequency or phase difference , and then determine the compensation factor of the retest component for compensating the response deviation of the unit type. Indicates the duration of fault simulation Indicates the preset reference simulation duration of the fault, which is used to map the duration of the fault simulation. In this way, the response deviation compensation factors of each retest component under each fault simulation type are accumulated in turn to obtain the global response deviation compensation factor of each retest component.

[0062] Step 4-12: Determine the functional weights of each retest component in the control board structure by identifying the component structure functions in the control board circuit diagram The component structure functions include control type, execution type, sensor type, etc. For example, for control type components (such as microcontrollers, digital signal processors, etc.), the functional weight is set to 1.0; for execution type components (such as motor drivers, relays, solenoid valves, etc.), the functional weight is set to 0.8; for sensor type components (such as temperature sensors, pressure sensors, etc.), the functional weight is set to 1.2.

[0063] Step 4-13: Uniformly collect and process the functional weights and fault response data to evaluate the abnormal factors of each retest component. Specifically: Set the response critical duration of each retest component for each fault gear of each fault simulation type through empirical fitting which is used to map the duration from the initial fault state to the structural damage failure state of the component under the fault simulation instruction. For example Establish an abnormal factor evaluation formula for each retest component where represents the th retest component's response duration to the th fault gear of the th fault simulation type respectively represent the abnormal degree of the temperature rise distribution and the abnormal degree of the temperature drop distribution of the th retest component for the th fault gear of the th fault simulation type respectively represent the preset influence proportion weights corresponding to the abnormal degree of the temperature rise distribution, the abnormal degree of the temperature drop distribution, and the response duration, which are used to reflect the threat degree of different fault response data to the component during the fault simulation and are set through empirical fitting. For example represents the number of each retest component

[0064] Table 1: Example of abnormal factor evaluation data for each retest component

[0065]

[0066] ​​Step 4-14: Due to the adaptability differences of different retest components under the collaborative fault simulation signal, it is necessary to perform balance correction processing on the corresponding fault simulation signals of multiple retest components associated in the link set component to determine the local response deviation compensation factors of each retest component. Specifically: Obtain the difference level between the corresponding adapted fault gear of each retest component in the multi-point collaborative fault simulation and the finally simulated fault gear, and set a compensation factor for each difference level. For example, set the compensation factor to 0.2 for a difference level between the first-level fault gear and the second-level fault gear, and set the compensation factor to 0.4 for two difference levels between the first-level fault gear and the third-level fault gear. Then, obtain the compensation factors for the corresponding difference levels of each retest component, which are the local response deviation compensation factors of each retest component.

[0067] Step 4-15: Integrate the global response deviation compensation factor and the local response deviation compensation factor into the anomaly factor of each retest component. For example, synchronously accumulate the global response deviation compensation factor and the local response deviation compensation factor with the anomaly factor of each retest component to obtain the anomaly response coefficient of each retest component. Define the retest component with the anomaly response coefficient exceeding the preset anomaly response coefficient threshold as the fault suspect component.

[0068] In a further preferred embodiment, analyzing and outputting the sensitivity of each fault suspect component to the fault simulation includes: Step 4-21: Count the retest components with the response result of at least one fault simulation instruction being response invalid, and obtain the fault simulation type and fault gear of the fault simulation instruction.

[0069] Step 4-22: Obtain the cumulative effect value of the fault gear for each fault suspect component's response invalidity to the fault simulation instruction. Specifically, quantify the corresponding fault gear when the response is invalid (for example, quantify the first-level fault gear as n, the second-level fault gear as n-1,..., the nth-level fault gear as 1, where n is a set constant), and accumulate the quantified values to obtain the cumulative effect value of the fault gear. The larger the cumulative effect value of the fault gear, the more likely it is that the component will have an invalid response when facing a lower-level fault gear, that is, the worse the response effect of the component to the fault simulation instruction, and thus the higher the sensitivity of the component to the fault simulation instruction may be. Map the cumulative effect value of the fault gear to a sensitivity determination index to determine the sensitivity of each fault suspect component to the fault simulation instruction. For example, if the cumulative effect value of the fault gear for a certain fault suspect component's response invalidity to the fault simulation instruction is 5, then determine that the sensitivity of this fault suspect component to the fault simulation instruction is 5.

[0070] The present invention conducts fault simulation tests on different components in the control board by setting fault simulation signals, and determines the fault test type and fault level of the fault simulation instruction based on the abnormal response status of the components suspected of having faults, which can not only achieve the purpose of targeted testing within limited conditions, but also save resources.

[0071] The performance diagnosis module integrates the output data of multi-dimensional test instructions to generate a performance test report for the household appliance control board.

[0072] In a preferred embodiment, the integration of the output data of multi-dimensional test instructions to generate a performance test report for the household appliance control board includes: integrating the electrical characteristic boundary indexes of each defective component, the corresponding adapted electrical parameters of each retested component, and the sensitivity of each component suspected of having a fault to the fault simulation instruction as the output data of the multi-dimensional test instructions.

[0073] The electrical characteristic boundary indexes of each defective component are specifically the electrical parameters and electrical level grades for each defective component to trigger the test conditions.

[0074] The corresponding adapted electrical parameters of each retested component are specifically the adapted electrical parameters and adapted levels corresponding to the retested components of each retested component.

[0075] Please refer to Figure 3 、 Figure 4 As shown, with the one-to-one correspondence between each defective component, each retested component, each component suspected of having a fault and each application component, the output data of the multi-dimensional test instructions are mapped to the performance resilience indexes of each application component of the control board. Among them, the electrical characteristic boundary indexes and the adapted electrical parameters are both in a positive mapping relationship with the performance resilience indexes. For example, after weighting and accumulating the electrical characteristic boundary indexes of each defective component, the performance resilience index of the corresponding application component is obtained, and at the same time, after weighting and accumulating the corresponding adapted electrical parameters of each retested component, the performance resilience index of the corresponding application component is obtained; the sensitivity to the fault simulation instruction is in an inverse mapping relationship with the performance resilience index. Specifically, each component suspected of having a fault is included in each retested component. Therefore, the sensitivity of each component suspected of having a fault to the fault simulation instruction is used as one of the mapping features, and the corresponding adapted electrical parameters of the corresponding component suspected of having a fault are selected from the corresponding adapted electrical parameters of each retested component as another mapping feature. For example, the reciprocal of the sensitivity of each component suspected of having a fault to the fault simulation instruction and the calculated result value after weighting and accumulating the corresponding adapted electrical parameters of each component suspected of having a fault are obtained, and the comprehensive value of this reciprocal and the calculated result value is used as the performance resilience index of the corresponding application component.

[0076] Based on the performance resilience indicators of each application component on the control board, the application life cycle of the household appliance control board can be inferred. The correlation between the performance resilience indicators of each application component and different limit life cycles can be determined by fitting according to historical experience. Among them, the limit life cycle with the maximum correlation is the limit life cycle of each application component. Furthermore, the minimum limit life cycle is selected as the application life cycle of the household appliance control board. Specifically, due to different application conditions, the intervals for different limit life cycles in different working condition scenarios are different. The different working condition scenarios include temperature working condition, voltage working condition, load working condition, usage frequency working condition, etc. For example, the different limit life cycles of a certain application component under the temperature working condition may be 5 years, 8 years, or 10 years, then the different limit life cycles of this application component under the voltage working condition may be 5 years or 7 years.

[0077] Integrate the output data of multi-dimensional test instructions and the application life cycle of the household appliance control board to construct a performance test report for the household appliance control board.

[0078] Through detailed test data and understanding of the application life cycle, the present invention generates a performance test report for the household appliance control board, which can ensure the reliability and durability of the household appliance control board in actual use, and thus provide a strong guarantee for product quality.

[0079] Please refer to Figure 2 As shown, a performance test method for a household appliance control board provided in the second aspect of the present invention includes the following steps: Step 1: Configure corresponding multi-gear electrical test instructions for each application component by scanning the control board structure, where each electrical test instruction corresponds to multiple electrical gears of an electrical parameter.

[0080] Step 2: Obtain the test data of each application component under the multi-gear electrical test instructions for differential evaluation, screen the retest components whose differences do not exceed the allowable range, and output the adapted electrical parameters and adapted gears corresponding to the retest components.

[0081] Step 3: Configure the fault gears of the fault simulation type based on the adapted electrical parameters of the retest components under the set fault simulation type, and output the fault response data of each retest component.

[0082] Step 4: Use the fault response data for abnormal response diagnosis to define each fault suspect component, and analyze and output the sensitivity of each fault suspect component to the fault simulation.

[0083] Step 5: Integrate the output data of multi-dimensional test instructions to generate a performance test report for the household appliance control board.

[0084] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of the present technology can make various modifications, supplements, or use similar methods to replace the specific embodiments described, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall fall within the protection scope of the present invention.

Claims

1. A performance testing system for a control board of a household appliance, characterized in that, Including: A test instruction configuration module that configures multi-gear electrical test instructions for each application component by scanning the control board structure, where each electrical test instruction corresponds to multiple electrical gears of an electrical parameter; A power detection module that obtains test data of each application component under multi-gear electrical test instructions for differential evaluation, screens retest components whose differences do not exceed the allowable range, and outputs the adapted electrical parameters and adapted gears corresponding to the retest components; A fault simulation module that configures the fault gears of the fault simulation type based on the adapted electrical parameters of the retest components under the set fault simulation type, and outputs the fault response data of each retest component; A suspected component definition module that uses the fault response data for abnormal response diagnosis to define each fault suspected component, and analyzes and outputs the sensitivity of each fault suspected component to the fault simulation; A performance diagnosis module that integrates the output data of multi-dimensional test instructions to generate a performance test report for the household appliance control board; The method for obtaining the adapted electrical parameters and adapted gears corresponding to the retest components is as follows: Extract the electrical gear with the minimum difference amount from the difference amounts between the test data of each retest component under multi-gear electrical test instructions and the standard value, and record it as the adapted gear of each retest component corresponding to each electrical parameter; Divide the power operation constraint fluctuation intervals corresponding to each electrical parameter, and screen out the electrical parameters whose difference amounts between the test data and the standard value are within the constraint fluctuation intervals, and record them as the adapted electrical parameters of each retest component.

2. The performance testing system for a household appliance control board according to claim 1, wherein The configuration of multi-gear electrical test instructions for each application component by scanning the control board structure includes: Scanning the control board structure through a camera device to obtain the model numbers of each application component of the household appliance control board, and then screening out the multi-gear electrical test instructions that match the model numbers of each application component from the test instruction generation library.

3. The performance testing system for a household appliance control board according to claim 1, characterized in that, The obtaining of test data of each application component under multi-gear electrical test instructions for differential evaluation and screening of retest components whose differences do not exceed the allowable range includes: Obtaining the difference amounts between the test data of each application component under multi-gear electrical test instructions and the standard value; Define that there is at least one electrical parameter corresponding to at least one electrical gear with a difference amount from the standard value less than or equal to the allowable difference amount as the screening condition, mark the application components that meet the screening condition as retest components, and mark the application components that do not meet the screening condition as defective components; Count the multiple electrical parameters and electrical gears of each defective component that meet the screening condition, and integrate them into the electrical characteristic boundary index of each defective component.

4. The performance testing system for a household appliance control board according to claim 1, characterized in that, The configuration of the fault gears of the fault simulation type based on the adapted electrical parameters of the retest components under the set fault simulation type includes: Define the cumulative value of the ratio of the number of adapted electrical parameters to the total electrical parameters and the ratio of the number of adapted gears that meet the baseline gear among all electrical gears as the structural health rate of the retest component; Obtain the control board circuit diagram, and determine the link set components by identifying the electrical connection relationships of each application component in the circuit diagram; Judge the fault spread probability by counting the retest components associated with each defective component in the link set components, and integrate the fault spread probability into the structural health rate of the corresponding retest component to obtain the structural health assessment index of each retest component. Importing the structural health assessment index of each retest component into the fault command signal library to obtain the corresponding adaptive fault gear of each fault simulation type of each retest component, wherein the fault command signal library contains simulation signals of each fault simulation type and adaptive fault gear corresponding to different application components; The corresponding adaptive fault levels of each fault simulation type of multiple retest components associated with the link set component are counted, and the corresponding lowest adaptive fault level of the same level of multiple retest components under the same fault simulation type is selected as the final simulated fault level.

5. The performance testing system for a home appliance control board according to claim 1, wherein The fault response data includes response time, response result, abnormal degree of temperature rise distribution and abnormal degree of temperature drop distribution; The output of the fault response data of each retest component includes: Collect thermal images of the corresponding fault positions of each retest component for each fault simulation type; Setting a response period, monitoring the response results of each retest component under the corresponding fault gear simulation of each fault simulation type, wherein the response results include a valid response and an invalid response; When the response is valid, obtain the response time of each retest component to the corresponding fault level of each fault simulation type; Based on the thermal images, the propagation path of the thermal transition points of each re-tested component under the simulation of the corresponding fault level of each fault simulation type is located to determine the abnormal degree of temperature rise distribution and temperature drop distribution of each re-tested component for the corresponding fault level of each fault simulation type.

6. The performance testing system for a household appliance control board according to claim 4, wherein The abnormal response diagnosis using the fault response data is used to define each suspected fault component, including: List the response deviation conditions of each retest component to each fault simulation type to determine the global response deviation compensation factor of each retest component, wherein the response deviation conditions include signal space conditions using the amplitude, frequency or phase difference of the signal at different positions of the component as identification indicators and signal time conditions using the fault simulation duration corresponding to an instantaneous fault or a continuous fault as identification indicators; By identifying the component structure functions in the control board circuit diagram, the functional weight of each retest component in the control board structure is determined; The function weights and fault response data are uniformly aggregated and processed to assess the abnormal factors of each retested component; Performing balance correction processing on the corresponding fault simulation signals of multiple retest components associated with the link set component to determine the local response deviation compensation factor of each retest component; The global response deviation compensation factor and the local response deviation compensation factor are integrated into the abnormal factor of each retest component to obtain the abnormal response coefficient of each retest component. The retest component whose abnormal response coefficient exceeds the preset abnormal response coefficient threshold is defined as a suspected fault component.

7. The performance testing system for a household appliance control board according to claim 5, wherein The analysis and output of the sensitivity of each suspected fault component to the fault simulation includes: Counting the retest components for which there is at least one fault simulation instruction corresponding response result is invalid response, and obtaining the fault simulation type and fault gear of the fault simulation instruction; Obtain the cumulative effect value of the fault gear in which each suspected fault component has an invalid response to the fault simulation instruction, and map the cumulative effect value of the fault gear to a sensitivity determination index to determine the sensitivity of each suspected fault component to the fault simulation instruction.

8. The performance testing system for a home appliance control board according to claim 3, characterized in that, The output data of the multi-dimensional test instructions are integrated to generate a household appliance control panel performance test report, including: With the one-to-one correspondence between each defective component, each retest component, each suspected faulty component and each application component, map the output data of the multi-dimensional test instructions to the performance resilience indicators of each application component on the control board, where the sensitivity to the fault simulation instructions has an inverse mapping relationship with the performance resilience indicators, and the electrical characteristic boundary indicators and the adapted electrical parameters have a positive mapping relationship with the performance resilience indicators; Estimate the application life cycle of the household appliance control board based on the performance resilience indicators of each application component on the control board; Integrate the output data of the multi-dimensional test instructions and the application life cycle of the household appliance control board to construct a performance test report for the household appliance control board.

9. A method for testing the performance of a control board of a household appliance, characterized in that, It includes the following steps: Step 1: Configure the multi-gear electrical test instructions corresponding to each application component by scanning the control board structure, where each electrical test instruction corresponds to multiple electrical gears of an electrical parameter; Step 2: Obtain the test data of each application component under the multi-gear electrical test instructions for differential evaluation, screen the retest components whose differences do not exceed the allowable range, and output the adapted electrical parameters and adapted gears corresponding to the retest components; The method for obtaining the adapted electrical parameters and adapted gears corresponding to the retest components is as follows: Extract the electrical gear with the minimum difference amount from the difference amounts between the test data of each retest component under the multi-gear electrical test instructions and the standard value, and record it as the adapted gear of each electrical parameter corresponding to each retest component; Divide the power operation constraint fluctuation intervals corresponding to each electrical parameter, and screen out the electrical parameters whose difference amounts between the test data and the standard value are within the constraint fluctuation intervals, and record them as the adapted electrical parameters of each retest component; Step 3: Configure the fault gears of the fault simulation type based on the adapted electrical parameters of the retest components under the set fault simulation type, and output the fault response data of each retest component; Step 4: Use the fault response data for abnormal response diagnosis to define each suspected faulty component, and analyze and output the sensitivity of each suspected faulty component to the fault simulation; Step 5: Integrate the output data of the multi-dimensional test instructions to generate a performance test report for the household appliance control board.

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