Performance test system and method for household appliance control panel

Abstract

The invention belongs to the technical field of electrical appliance performance testing, and particularly discloses and provides a household electrical appliance control panel performance testing system and method.The method comprises the steps that adaptive electrical parameters are generated through static power operation testing of a control panel and serve as fault simulation contrast parameters of a retest assembly, and fault response data are obtained; the process coherence of different test modes and the accuracy of test results can be improved; the fault simulation test is performed on different components in the control panel by setting the fault simulation signal, and the fault test type and the fault gear of the fault simulation instruction are determined according to the abnormal response state of the component with the fault suspicion, so that the purpose of targeted test within limited conditions can be achieved, and resources can be saved; the application life cycle of the household electrical appliance control panel is speculated based on the output data of the multi-dimensional test instruction, and then the performance test report of the household electrical appliance control panel is generated, which is helpful for covering the integrity of the performance test of the control panel.

Description

Technical Field

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

[0002] Home appliances are becoming more and more versatile and more intelligent. As the core component of home appliances, the performance of the control panel directly determines the reliability, stability and user experience of home appliances. At the same time, consumers are becoming more and more demanding on the quality of home appliances, and market competition is becoming increasingly fierce, which makes the precise testing of the performance of home appliance control panels the focus of the industry.

[0003] In the prior art, there are some solutions related to electrical performance testing. For example, the Chinese patent publication number CN117075018B discloses a BMS control panel performance test intelligent analysis and management system, which performs overcurrent, overvoltage and working performance tests on the BMS control panel, analyzes the corresponding performance compliance coefficient of the BMS control panel, and provides feedback on the test results. Although the multi-dimensional analysis of the BMS control panel performance is achieved and the timeliness and optimization effect of the next batch of BMS control panel production plan optimization are improved, it is 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, which leads to a large deviation between the analysis results and the actual operation conditions, reducing the practicality of the analysis results.

[0004] Another Chinese patent with the publication number CN112014722A discloses an intelligent photoelectric control panel test system, which uniformly detects the position information, voltage and current, appearance and load information of the photoelectric control panel by setting a position detection module and a performance detection module, and compares, counts and stores the detection results by the information processing module, and feeds back through the feedback module. Although the signal simulation achieves the effect of automated and intelligent testing, the lack of fault simulation testing of different components in the control panel makes it impossible to know the impact of a certain component failure on other components and the entire control panel system, and it is impossible to determine the sensitivity of the control panel to fault conditions, which makes 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 technology, a household appliance control panel performance testing system and method are now proposed.

[0006] The purpose of the present invention can be achieved through the following technical scheme: The present invention provides a household appliance control panel performance testing system, the system comprising: a test instruction configuration module, which configures the corresponding multi-level electrical test instructions for each application component by scanning the control panel structure, wherein each electrical test instruction corresponds to multiple electrical levels of an electrical parameter.

[0007] The power detection module obtains the test data of each application component under the multi-level electrical test instructions for difference evaluation, selects the retest components whose differences do not exceed the allowable range, and outputs the adaptation electrical parameters and adaptation levels corresponding to the retest components.

[0008] The fault simulation module configures the fault gear 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] The suspected component definition module uses fault response data to perform abnormal response diagnosis to define each suspected fault component, analyze and output the sensitivity of each suspected fault component to fault simulation.

[0010] The performance diagnosis module integrates the output data of multi-dimensional test instructions and generates a performance test report for the home appliance control panel.

[0011] The second aspect of the present invention provides a method for testing the performance of a household appliance control panel, comprising the following steps: Step 1, configuring the corresponding multi-level electrical test instructions for each application component by scanning the control panel structure, wherein each electrical test instruction corresponds to multiple electrical levels of an electrical parameter.

[0012] Step 2: Obtain the test data of each application component under the multi-level electrical test instructions for difference evaluation, select the retest components whose differences do not exceed the allowable range, and output the adaptation electrical parameters and adaptation levels corresponding to the retest components.

[0013] Step 3: Under the set fault simulation type, configure the fault gear of the fault simulation type based on the adapted electrical parameters of the retest component, and output the fault response data of each retest component.

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

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

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention generates adaptive electrical parameters through static power operation test of the control board, and uses them as fault simulation control parameters of the retest components to obtain fault response data, which helps to achieve connectivity between different test modes, thereby improving the process continuity of performance testing and the accuracy of test results.

[0017] (2) The present invention performs fault simulation tests on different components in the control panel by setting fault simulation signals, and determines the fault test type and fault gear of the fault simulation instruction according to the abnormal response state of the suspected fault component, thereby achieving the purpose of targeted testing within limited conditions and saving resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

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

[0020] Figure 2 The present invention is a schematic flow chart of the steps for implementing the method.

[0021] Figure 3 It is a schematic diagram of the mapping relationship between the performance toughness indicators of various application components of the control panel of the present invention.

[0022] Figure 4 It is a schematic diagram of the corresponding relationship between each retest component, each suspected fault component and each application component of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] See also Figure 1 As shown, the present invention provides a household appliance control panel performance test system, which includes: a test instruction configuration module, a power detection module, a fault simulation module, a suspect component definition module, and a performance diagnosis module.

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

[0026] The test instruction configuration module configures the corresponding multi-level electrical test instructions of each application component by scanning the control board structure, wherein each electrical test instruction corresponds to multiple electrical levels of an electrical parameter.

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

[0028] The multi-level electrical test instruction includes control signals of each electrical parameter at each electrical level, wherein each electrical test instruction corresponds to one electrical parameter.

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

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

[0031] The power detection module obtains the test data of each application component under the multi-level electrical test instructions to perform difference evaluation, selects the retest components whose differences do not exceed the allowable range, and outputs the adaptation electrical parameters and adaptation levels corresponding to the retest components.

[0032] In a preferred embodiment, the test data of each application component under multi-level electrical test instructions is obtained for difference evaluation, and the retest components whose differences do not exceed the allowable range are screened, including: obtaining the difference between the test data of each application component under multi-level electrical test instructions and the standard value, wherein the test data is the output current or output voltage or output power, etc. that matches the electrical parameters.

[0033] It is defined that the difference between at least one electrical parameter corresponding to at least one electrical gear and the standard value is less than or equal to the allowed difference as a screening condition, and the application components that meet the screening conditions are marked as retest components, and the application components that do not meet the screening conditions are marked as defective components.

[0034] Multiple electrical parameters and electrical levels of each defective component that meet the screening criteria are counted and integrated into electrical characteristic boundary indicators of each defective component.

[0035] The electrical characteristic boundary index refers to the corresponding highest electrical level of 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, the application component will be recorded as a defective component. For example, if the voltage generated by the application component under the low gear of the current test parameter is much lower than the voltage standard value, the application component may fail to sense the voltage; if the voltage generated by the application component under the low gear of the current test parameter is much higher than the voltage standard value, the application component may be overly sensitive to voltage sensing, which will shorten the application life of the application component.

[0037] In a further preferred embodiment, the adaptation electrical parameters and adaptation gears corresponding to the re-test components are obtained as follows: the electrical gear with the smallest difference is extracted from the difference between the test data and the standard value of each re-test component under the multi-gear electrical test instruction, and recorded as the adaptation gear of each electrical parameter corresponding to each re-test component.

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

[0039] The adapted electrical parameters and adapted gear positions of each retest component are integrated into the corresponding adapted electrical parameters of each retest component.

[0040] The fault simulation module configures the fault gear 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.

[0041] In a preferred embodiment, the fault simulation type fault level is configured based on the adapted electrical parameters of the retested component under the set fault simulation type, and the content includes: defining the corresponding cumulative value of the quantitative ratio of the adapted electrical parameters compared to the total electrical parameters and the quantitative ratio of the adapted level to the baseline level among all electrical levels as the structural health rate of the retested component. The larger the quantitative ratio of the adapted electrical parameters compared to the total electrical parameters, the wider the adaptability range of the component to the electrical parameters; the larger the quantitative ratio of the adapted level to the baseline level among all electrical levels, the better the adaptability of the component to the level operation of multiple electrical parameters. Therefore, when the quantitative ratio of the adapted electrical parameters compared to the total electrical parameters and the quantitative ratio of the adapted level to the baseline level among all electrical levels are larger, the structural health rate of the component is higher.

[0042] Among them, the baseline gear of each application component is set differently through empirical fitting. Different application components have their own unique working characteristics and performance requirements. Reasonable setting of the baseline gear of each component can enable the entire test system to achieve the best collaborative working effect, such as setting the corresponding baseline gear of the voltage parameter type of the sensor component to high-end and setting the corresponding baseline gear of the voltage parameter type of the drive component to mid-range. The specific decision is based on the functional characteristics, safety requirements, working mode and other multi-dimensional factors of each application component.

[0043] Obtain the control board circuit diagram, and determine the link set components by identifying the electrical connection relationship of each application component in the circuit diagram. If two components are directly connected in the circuit or indirectly connected through some intermediate components, they may be associated 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, causing the chip to be abnormal. In this case, the two components are fault-associated components.

[0044] In the link set component, the retest components associated with each defective component are counted to determine the probability of fault propagation. Specifically, since the signal transmission path of the directly connected components is short and direct, the corresponding fault propagation probability of the directly connected retest components can be set to 1; since the intermediate components can play a certain isolation or buffering role, the corresponding fault propagation probability of the retest components indirectly connected through the intermediate components can be set lower than the corresponding fault propagation probability of the directly connected retest components, such as 0.5; for the retest components without connectivity (such as some sensors, independent storage chips), their corresponding fault propagation probability is set to a constant that is not 0 and less than the indirect connection fault propagation probability, such as 0.1. The fault propagation probability is integrated into the structural health rate of the corresponding retest component to obtain the structural health assessment index of each retest component. Since the fault propagation probability has a negative impact on the structural health assessment index, the structural health assessment index can be obtained by multiplying the inverse of the fault propagation probability with the structural health rate. For example, if the fault propagation probability of a retest component is 0.5, 1 / 0.5 is multiplied by the structural health rate of the retest component to obtain the structural health assessment index of the retest component.

[0045] The structural health assessment index of each retest component is imported into the fault command signal library to obtain the corresponding adaptive fault gear of each fault simulation type of each retest component. The fault command signal library contains simulation signals of each fault simulation type and adaptive fault gear corresponding to different application components. The various fault simulation types include electrical faults, mechanical faults, and physical and chemical contamination. Electrical faults include short circuit faults, overvoltage faults, etc. Mechanical faults include vibration or shedding faults, wear or fatigue faults, etc. Physical and chemical contamination include water immersion or overheating faults, material oxidation or contamination faults, etc. The fault gear includes a primary fault gear, a secondary fault gear..., and each fault gear corresponds to a simulation signal of different humidity, different temperature or different short circuit resistance.

[0046] The corresponding adaptive fault gears of each fault simulation type of multiple retest components associated with the link set component are counted, and the corresponding lowest adaptive fault gears of the same level of multiple retest components under the same fault simulation type are selected as the final simulated fault gear for multi-point collaborative fault simulation. For example, the adaptive fault gears of two retest components under the overvoltage fault simulation type are the first-level fault gear and the second-level fault gear, respectively. In order to avoid the second-level fault gear from causing excessive damage to one of the retest components, the first-level fault gear is used as the fault gear of the collaborative fault simulation of the two retest components under the overvoltage fault simulation type.

[0047] Further explanation: A software simulation algorithm is used to simulate fault scenarios including various fault simulation types and fault levels. For example, for electrical faults, different fault types and fault levels are simulated by changing circuit parameters through mathematical models; for mechanical faults, abnormal movement of mechanical parts can be simulated through dynamic models; for physical and chemical contamination faults, the influence of corrosion process on circuit performance is simulated through chemical reaction dynamic models. According to the adaptive electrical parameters of the retested components, the relevant parameters in the simulation algorithm are adjusted, the fault simulation type and fault level 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 time, response result, abnormal degree of temperature rise distribution and abnormal degree of temperature drop distribution.

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

[0050] A response time period is set to monitor the response results of each retest component under the corresponding fault gear simulation of each fault simulation type. The response results include valid response and invalid response. The judgment condition for invalid response is that the control board does not generate any processing measures within the set response time period. For example, when the retest component receives the fault instruction of the open circuit fault, the control board takes the processing measure of timely power off within the set response time period, which indicates that the response is valid; otherwise, the response is invalid.

[0051] When the response is valid, the response time of each retest component to the corresponding fault level of each fault simulation type is obtained. The response time is used to reflect the fault processing time of the retest component from the occurrence of the fault to the generation of processing measures.

[0052] The thermal transition point propagation paths of each retested component under the simulation of the corresponding fault level of each fault simulation type are located based on thermal images, and the average temperature change rate between all temperature transition points on the thermal transition point propagation paths is detected to determine the abnormal degree of temperature rise distribution and temperature drop distribution of each retested component for the corresponding fault level of each fault simulation type.

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

[0054] The average temperature change rate is specifically: obtaining the corresponding temperature change time of all temperature transition points from low temperature to high temperature or from high temperature to low temperature and calculating the average value.

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

[0056] The thermal transition point propagation path includes a plurality of temperature rise point distribution paths of the retest component during a temperature rise process and a plurality of temperature drop point distribution paths during a temperature drop process.

[0057] The present invention generates adaptive electrical parameters through static power operation test of the control board, and uses them as fault simulation control parameters of the retest components to obtain fault response data, which helps to achieve connectivity between different test modes, thereby improving the process continuity 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 to define each suspected fault component, and analyzes and outputs the sensitivity of each suspected fault component to the fault simulation.

[0059] In a preferred embodiment, the abnormal response diagnosis is performed using fault response data to define each suspected fault component, and the content includes: Step 4-11, due to the difference in sensitivity of different retest components to fault simulation signals, it is necessary to balance and correct the response deviation conditions of the corresponding fault simulation signals of the retest components. The response deviation conditions of each retest component to each fault simulation type are listed to determine the global response deviation compensation factor of each retest component, and the response deviation conditions include signal space conditions with the amplitude, frequency or phase difference of the signal at different positions of the component as identification indicators and signal time conditions with the fault simulation duration corresponding to the instantaneous fault or continuous fault as identification indicators.

[0060] The different positions of the components are pre-marked key points, such as the diode pin position, the chip silk screen line or graphic mark position. On the circuit board, there will be silk screen marks around the installation position of the chip. At the same time, there will 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 mark on the chip, which is convenient for installation and identification of the chip direction. The material function in the component is different, so there are differences in the sensitivity to the signal.

[0061] Specifically, the process of determining the global response deviation compensation factor of each retest component is as follows: quantify the difference of multiple identification indicators within the corresponding response deviation conditions of each retest component, for example, the amplitude of two marked positions on a retest component , and the relative change of the amplitude is expressed in percentage after calculating its deviation, which is , Represents the maximum amplitude term at two positions, which is used as a baseline parameter to measure the amplitude percentage. Similarly, the relative change in frequency or phase difference is obtained. , and then determine the compensation factor of the retest component to compensate for the unit type response deviation , Indicates the fault simulation duration. It represents the preset fault reference simulation duration, 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 weight 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 class, execution class, sensor class, etc. For example, the function weight of control class components (such as microcontrollers, digital signal processors, etc.) is set to 1.0, the function weight of execution class components (such as motor drivers, relays, solenoid valves, etc.) is set to 0.8, and the function weight of sensor class components (such as temperature sensors, pressure sensors, etc.) is set to 1.2.

[0063] Step 4-13: Unify the functional weights and fault response data to evaluate the abnormal factors of each retest component. Specifically, set the critical response time of each retest component to the corresponding fault level of each fault simulation type through empirical fitting. , which is used to map the time it takes for a component to reach the structural damage failure state from the initial fault state under the fault simulation instruction, such as , establish the abnormal factor evaluation formula for each retest component ,in Indicates The retest components are The response time of the corresponding fault position for each fault simulation type, Respectively represent The retest components are The abnormal degree of temperature rise distribution and temperature drop distribution of the corresponding fault position of each fault simulation type, They represent the preset influence proportion weights corresponding to the abnormal degree of temperature rise distribution, the abnormal degree of temperature drop distribution, and the response time, respectively, and are used to reflect the threat degree of different fault response data to the components in the fault simulation. They are set through empirical fitting, such as , Indicates the number of each retest component, , Indicates the number of each fault simulation type, The specific data examples are shown in the following table:

[0064] Table 1. Examples of abnormal factor assessment data for each retested component:

[0065] Step 4-14: Due to the differences in adaptability of different retest components under collaborative fault simulation signals, it is necessary to balance and correct the corresponding fault simulation signals of multiple retest components associated in the link set component to determine the local response deviation compensation factor of each retest component, specifically: obtain the difference level between the corresponding adaptive fault gear of each retest component in the multi-point collaborative fault simulation and the final simulated fault gear, set a compensation factor for each difference level, such as setting a compensation factor of 0.2 for one difference level between the first-level fault gear and the second-level fault gear, and setting a compensation factor of 0.4 for two difference levels between the first-level fault gear and the third-level fault gear, and then obtain the compensation factor for the corresponding difference level of each retest component, that is, the local response deviation compensation factor of each retest component.

[0066] Step 4-15, integrate the global response deviation compensation factor and the local response deviation compensation factor into the abnormal factor of each retest component, such as accumulating the global response deviation compensation factor and the local response deviation compensation factor synchronously with the abnormal factor of each retest component to obtain the abnormal response coefficient of each retest component, and define the retest component whose abnormal response coefficient exceeds the preset abnormal response coefficient threshold as a suspected fault component.

[0067] In a further preferred embodiment, the analysis and output of the sensitivity of each suspected fault component to the fault simulation includes: step 4-21, counting the retest components whose corresponding response result of at least one fault simulation instruction is an invalid response, and obtaining the fault simulation type and fault gear of the fault simulation instruction.

[0068] Step 4-22, obtaining the cumulative effect value of the fault gear of each suspected fault component when the response to the fault simulation instruction is invalid, specifically, quantizing the corresponding fault gear when the response is invalid (such as the first-level fault gear is quantized as n, the second-level fault gear is quantized as n-1, ..., the n-level fault gear is quantized as 1, and n is a set constant), and accumulating the quantized values ​​to obtain the cumulative effect value of the fault gear. The larger the cumulative effect value of the fault gear, the more likely the component is to 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 further indicates that the sensitivity of the component to the fault simulation instruction may be higher. The cumulative effect value of the fault gear is mapped to a sensitivity determination index to determine the sensitivity of each suspected fault component to the fault simulation instruction. For example, if the cumulative effect value of the fault gear of a suspected fault component when the response to the fault simulation instruction is invalid is 5, then the sensitivity of the suspected fault component to the fault simulation instruction is determined to be 5.

[0069] The present invention performs fault simulation tests on different components in the control panel by setting fault simulation signals, and determines the fault test type and fault gear of the fault simulation instruction according to the abnormal response state of the suspected fault component, thereby achieving the purpose of targeted testing within limited conditions and saving resources.

[0070] The performance diagnosis module integrates the output data of the multi-dimensional test instructions to generate a performance test report for the home appliance control panel.

[0071] In a preferred embodiment, the output data of the integrated multi-dimensional test instructions generates a household appliance control panel performance test report, the content of which includes: integrating the electrical characteristic boundary indicators of each defective component, the corresponding adaptive electrical parameters of each retest component, and the sensitivity of each suspected fault component to the fault simulation instruction into the output data of the multi-dimensional test instructions.

[0072] The electrical characteristic boundary indicators of each defective component are specifically the electrical parameters and electrical gear levels of the test conditions that trigger the defective component.

[0073] The corresponding adapted electrical parameters of each retest component specifically include the adapted electrical parameters and adapted gear positions corresponding to the retest components of each retest component.

[0074] See also Figure 3 , Figure 4 As shown in the figure, with a one-to-one correspondence between each defective component, each retest component, each suspected fault component and each application component, the output data of the multi-dimensional test instruction is mapped into the performance resilience index of each application component of the control board, wherein the electrical characteristic boundary index and the adapted electrical parameter are both positively mapped to the performance resilience index. For example, the electrical characteristic boundary index of each defective component is weighted and accumulated to obtain the performance resilience index of the corresponding application component, and the corresponding adapted electrical parameters of each retest component are weighted and accumulated to obtain the performance resilience index of the corresponding application component. The sensitivity of the fault simulation instruction to the performance resilience index is The performance indicators are in reverse mapping relationship. It is specially noted that each suspected fault component is included in each re-test component. Therefore, the sensitivity of each suspected fault component to the fault simulation instruction is used as one of the mapping features, and the corresponding adaptive electrical parameters of the suspected fault component are screened from the corresponding adaptive electrical parameters of each re-test component as another mapping feature. For example, the corresponding inverse of the sensitivity of each suspected fault component to the fault simulation instruction and the corresponding adaptive electrical parameters of each suspected fault component are obtained after weighted accumulation, and the comprehensive value of the inverse and the calculated result value is used as the performance resilience indicator of the corresponding application component.

[0075] The application life cycle of the household appliance control board can be inferred based on the performance toughness index of each application component of the control board. The correlation between the performance toughness index of each application component and different extreme life cycles can be determined based on historical experience fitting, where the extreme life cycle with the maximum correlation is the extreme life cycle of each application component, and then the minimum extreme life cycle is selected as the application life cycle of the household appliance control board. Specifically, due to different application conditions, different extreme life cycles under different operating conditions are divided into different intervals. The different operating conditions include temperature conditions, voltage conditions, load conditions, frequency of use conditions, etc. For example, the different extreme life cycles of an application component under temperature conditions may be 5 years, 8 years or 10 years, and the different extreme life cycles of the application component under voltage conditions may be 5 years or 7 years.

[0076] The output data of multi-dimensional test instructions and the application life cycle of the home appliance control board are integrated to construct a home appliance control board performance test report.

[0077] The present invention generates a household appliance control board performance test report through detailed test data and understanding of the application life cycle, which can ensure the reliability and durability of the household appliance control board in actual use, thereby providing a strong guarantee for product quality.

[0078] See also Figure 2 As shown, the second aspect of the present invention provides a household appliance control panel performance testing method, comprising the following steps: Step 1, configuring the corresponding multi-level electrical test instructions for each application component by scanning the control panel structure, wherein each electrical test instruction corresponds to multiple electrical levels of an electrical parameter.

[0079] Step 2: Obtain the test data of each application component under the multi-level electrical test instructions for difference evaluation, select the retest components whose differences do not exceed the allowable range, and output the adaptation electrical parameters and adaptation levels corresponding to the retest components.

[0080] Step 3: Under the set fault simulation type, configure the fault gear of the fault simulation type based on the adapted electrical parameters of the retest component, and output the fault response data of each retest component.

[0081] Step 4: Use the fault response data to perform abnormal response diagnosis to define each suspected fault component, analyze and output the sensitivity of each suspected fault component to the fault simulation.

[0082] Step 5: Integrate the output data of the multi-dimensional test instructions to generate a home appliance control panel performance test report.

[0083] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A household appliance control panel performance test system, characterized in that: include: A test instruction configuration module configures the corresponding multi-level electrical test instructions of each application component by scanning the control board structure, wherein each electrical test instruction corresponds to multiple electrical levels of an electrical parameter; The power detection module obtains the test data of each application component under the multi-level electrical test instructions to perform difference evaluation, selects the retest components whose differences do not exceed the allowable range, and outputs the adapted electrical parameters and adapted levels corresponding to the retest components; A fault simulation module configures the fault level 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; The suspect component definition module uses the fault response data to perform abnormal response diagnosis to define each suspected fault component, analyze and output the sensitivity of each suspected fault component to the fault simulation; The performance diagnosis module integrates the output data of multi-dimensional test instructions and generates a performance test report for the home appliance control panel.

2. A household appliance control panel performance testing system according to claim 1, characterized in that: The method of configuring the corresponding multi-level electrical test instructions for each application component by scanning the control board structure includes: scanning the control board structure by a camera device to obtain the models of each application component of the household appliance control board, and then selecting the multi-level electrical test instructions matching the models of each application component from a test instruction generation library.

3. A household appliance control panel performance testing system according to claim 1, characterized in that: The method of obtaining the test data of each application component under the multi-level electrical test instruction for difference evaluation and screening the retest components whose differences do not exceed the allowable range includes: obtaining the difference between the test data of each application component under the multi-level electrical test instruction and the standard value; Define that the difference between at least one electrical parameter corresponding to at least one electrical gear and the standard value is less than or equal to the allowable difference as a 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; Multiple electrical parameters and electrical levels of each defective component that meet the screening criteria are counted and integrated into electrical characteristic boundary indicators of each defective component.

4. A household appliance control panel performance testing system according to claim 3, characterized in that: The adaptive electrical parameters and adaptive gear positions corresponding to the retest components are obtained as follows: the electrical gear position with the smallest difference is extracted from the difference between the test data and the standard value of each retest component under the multi-gear electrical test instruction, and recorded as the adaptive gear position of each electrical parameter corresponding to each retest component; Divide the corresponding power operation constraint fluctuation range of each electrical parameter, screen out the electrical parameters whose difference between the test data and the standard value is within the constraint fluctuation range, and record them as the adaptation electrical parameters of each retest component.

5. A household appliance control panel performance testing system according to claim 4, characterized in that: The configuration of the fault level of the fault simulation type based on the adapted electrical parameters of the retest component under the set fault simulation type includes: Define the corresponding cumulative value of the proportion of the number of adapted electrical parameters compared to the total electrical parameters and the proportion of the number of adapted gears that meet the baseline gears in all electrical gears as the structural health rate of the retested component; Obtain a control board circuit diagram, and determine the link set components by identifying the electrical connection relationship between each application component in the circuit diagram; In the link set component, the retest components associated with each defective component are counted to determine the probability of fault propagation, and the fault propagation probability is integrated 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.

6. A household appliance control panel performance testing system according to claim 1, characterized in that: 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.

7. A household appliance control panel performance testing system according to claim 5, characterized in that: 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.

8. A household appliance control panel performance testing system according to claim 6, characterized in that: 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.

9. A household appliance control panel performance testing system 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: Based on the one-to-one correspondence between each defective component, each retest component, each suspected fault component and each application component, the output data of the multi-dimensional test instructions are mapped into the performance resilience index of each application component of the control board, among which the sensitivity to the fault simulation instruction is inversely mapped to the performance resilience index, and the electrical characteristic boundary index and the adapted electrical parameter are in a forward mapping relationship with the performance resilience index; Estimate the application life cycle of household appliance control panels based on the performance toughness indicators of each application component of the control panel; The output data of multi-dimensional test instructions and the application life cycle of the home appliance control board are integrated to construct a home appliance control board performance test report.

10. A method for testing the performance of a household appliance control panel, characterized in that: The following steps are involved: Step 1: configure the corresponding multi-level electrical test instructions of each application component by scanning the control board structure, wherein each electrical test instruction corresponds to multiple electrical levels of an electrical parameter; Step 2: Obtain the test data of each application component under the multi-level electrical test instructions to perform difference evaluation, select the retest components whose differences do not exceed the allowable range, and output the adapted electrical parameters and adapted levels corresponding to the retest components; Step 3: Under the set fault simulation type, configure the fault gear of the fault simulation type based on the adapted electrical parameters of the retest component, and output the fault response data of each retest component; Step 4: Use the fault response data to perform abnormal response diagnosis to define each suspected fault component, analyze and output the sensitivity of each suspected fault component to the fault simulation; Step 5: Integrate the output data of the multi-dimensional test instructions to generate a home appliance control panel performance test report.

Images