Fault detection method for electronic component

Abstract

The invention discloses a fault detection method for an electronic component, and relates to the field of fault detection. According to the fault detection method of the electronic component, historical voltage data, historical current data and historical frequency data of the electronic component are acquired and preprocessed; based on preset standard voltage, standard current and frequency error ranges, the historical voltage data, the historical current data and the historical frequency data of the preprocessed electronic component are analyzed respectively, and a voltage fault index, a current fault index and a frequency fault index of the electronic component are obtained; and judging whether the voltage fault index, the current fault index and the frequency fault index of the electronic component respectively accord with the corresponding set fault thresholds, and by continuously monitoring and analyzing historical data, potential faults can be found before the problem develops to a more serious stage, so that the accidental shutdown time of equipment is shortened, and the working efficiency of the equipment is improved. And planned maintenance is facilitated, so that the cost is saved, and the service life of equipment is prolonged.

Description

[0001] This application is a divisional application of the application filed on October 21, 2024, with application number 202411468099.8 and invention name “A fault detection method and system for electronic components”. Technical Field

[0002] The invention relates to the field of fault detection, and in particular to a fault detection method for an electronic component. Background Art

[0003] In the field of modern industry and technology, electronic components are the basic components of various electronic equipment and systems. The reliability of these components directly affects the stable operation and efficiency of the entire system. With the development of technology, electronic components have become more complex and miniaturized in function, making their fault detection and diagnosis particularly important and challenging. Traditional fault detection methods mainly rely on manual inspection and experience-based preventive maintenance strategies. These methods are not only time-consuming and labor-intensive, but also often fail to detect faults in real time, resulting in sudden equipment shutdown and reduced production efficiency. In addition, traditional methods have limited effectiveness in identifying hidden faults. Such faults often gradually deteriorate without being noticed, and may eventually lead to serious equipment damage or safety accidents.

[0004] In the prior art, traditional fault detection methods usually lack comprehensiveness. They usually only focus on a single indicator for fault monitoring, which makes it difficult to comprehensively evaluate the health status of components. In addition, traditional fault detection methods usually rely on manual inspection, which often leads to missed detections and delayed fault diagnosis. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a fault detection method for electronic components, which solves the problem that traditional fault detection methods are usually lacking in comprehensiveness. They usually only focus on a single indicator for fault monitoring, which makes it difficult to comprehensively evaluate the health status of components. In addition, traditional fault detection methods usually rely on manual inspection, which often leads to missed detections and delayed fault diagnosis.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a fault detection method for electronic components, comprising the following steps: obtaining historical voltage data, historical current data, and historical frequency data of the electronic components, and preprocessing them; based on preset standard voltage, standard current, and frequency error ranges, analyzing the preprocessed historical voltage data, historical current data, and historical frequency data of the electronic components, respectively, to obtain voltage fault indicators, current fault indicators, and frequency fault indicators of the electronic components; judging whether the voltage fault indicators, current fault indicators, and frequency fault indicators of the electronic components meet the corresponding set fault thresholds, respectively, and marking the corresponding fault indicators that do not meet the set fault thresholds as fault characteristics.

[0007] Furthermore, the historical voltage data specifically refers to the historical input voltage value and the historical output voltage value of the electronic component at each historical time point, the historical current data specifically refers to the historical measured current value of each internal energized conductor of the electronic component at each historical time point, the historical frequency data specifically refers to the historical frequency value of the electronic component at each historical time point, and the frequency fault indicator specifically refers to the number of time points with abnormal frequencies.

[0008] Furthermore, the preset standard voltage includes a standard input voltage and a standard output voltage, and the specific process of obtaining the voltage fault index of the electronic component is as follows: read the historical input voltage value and the historical output voltage value of the electronic component at each historical time point; based on the preset standard input voltage and standard output voltage, perform mean analysis on the historical input voltage value and the historical output voltage value at each historical time point to obtain a historical input voltage difference index and a historical output voltage difference index; perform a comprehensive analysis on the historical input voltage difference index and the historical output voltage difference index to obtain the voltage fault index of the electronic component.

[0009] Furthermore, the specific formula for calculating the voltage fault index of electronic components is as follows: ; It is the voltage fault indicator of electronic components. The first electronic component in history The historical input voltage value at a time point, is the preset standard input voltage, is the proportionality coefficient of the average difference between the historical input voltage value of the preset electronic component at each time point and the preset standard input voltage, The first electronic component in history The historical output voltage value at a time point, is the preset standard output voltage, is the proportionality coefficient of the average difference between the historical output voltage value of the preset electronic component at each time point and the preset standard output voltage, , , The number of historical time points of the historical input voltage value and the historical output voltage value obtained.

[0010] Furthermore, the specific process of obtaining the current fault index of the electronic component is as follows: read the historical measured current value of each energized wire inside the electronic component at each historical time point, and perform error analysis based on the moving exponential averaging method and the preset standard current to obtain the historical current error mean of each energized wire; perform weighted analysis on the historical current error mean of each energized wire to obtain the current fault index of the electronic component.

[0011] Furthermore, the specific formula for calculating the current fault index of electronic components is as follows: ;in, is the current fault indicator of electronic components, For the The historical current error mean of each energized conductor, For the preset The proportionality coefficient of the mean historical current error of each energized conductor, The number of internal power-carrying wires in electronic components.

[0012] Furthermore, the calculation formula for the historical current error mean of the energized conductor is as follows: ;in, is the historical current error mean of the energized conductor, The first in the history of conducting wires The historical measured current value at each time point, is the preset standard current, The history of the pre-set energized conductor The proportional coefficient of the difference between the historical measured current value at a time point and the preset standard current, The first in the history of conducting wires The historical measured current value at each time point, The history of the pre-set energized conductor The proportional coefficient of the difference between the historical measured current value at a time point and the preset standard current, , , The number of historical time points of the historical measured current values ​​obtained.

[0013] Furthermore, the specific process of obtaining the frequency fault index of the electronic component is as follows: read the historical frequency value of the electronic component at each historical time point and analyze the median value of the historical frequency; perform abnormal time point detection on the historical frequency data based on the Grubbs test method, and the specific process is to calculate the fault score of each data point, that is, to calculate the difference between the historical frequency value of each historical time point and the median value of the historical frequency, to obtain the frequency difference between the historical frequency value of each historical time point and the median value of the historical frequency, and to determine whether the frequency difference is within the frequency error range. If the frequency difference is outside the frequency error range, it is regarded as an abnormal time point; count the number of abnormal time points and record them as the frequency fault index of the electronic component.

[0014] A fault detection system for electronic components comprises: a data acquisition subsystem, a data preprocessing subsystem, a fault analysis subsystem, and a fault diagnosis subsystem; the data acquisition subsystem is used to acquire historical voltage data, historical current data, and historical frequency data of the electronic components; the data preprocessing subsystem is used to preprocess the historical voltage data, historical current data, and historical frequency data of the electronic components; the fault analysis subsystem is used to analyze the preprocessed historical voltage data, historical current data, and historical frequency data of the electronic components based on preset standard voltage, standard current, and frequency error ranges, respectively, to obtain voltage fault indicators, current fault indicators, and frequency fault indicators of the electronic components; the fault diagnosis subsystem is used to determine whether the voltage fault indicators, current fault indicators, and frequency fault indicators of the electronic components meet the corresponding set fault thresholds, respectively, and mark the corresponding fault indicators that do not meet the set fault thresholds as fault characteristics.

[0015] Furthermore, the fault analysis subsystem includes: a voltage analysis module, a current analysis module, and a frequency analysis module; the voltage analysis module is used to analyze historical voltage data based on a preset standard voltage and calculate a voltage difference index; the current analysis module is used to perform error analysis on current data based on a moving exponential average method and a standard current value; the frequency analysis module is used to read frequency data and perform median analysis, use the Grubbs test method to detect abnormal time points, and mark frequency fault indicators.

[0016] The present invention has the following beneficial effects: (1) The fault detection method of the electronic components can detect potential faults before the problem develops to a more serious stage by continuously monitoring and analyzing historical data. This not only reduces the unexpected downtime of the equipment, but also helps in planned maintenance, thereby saving costs and extending the service life of the equipment.

[0017] (2) This electronic component fault detection method provides a comprehensive way to judge the component status through multi-dimensional analysis of voltage, current and frequency. Compared with the traditional method that relies on a single data point, this comprehensive analysis helps technicians accurately locate the root cause of the problem, improve maintenance efficiency and reduce misjudgment.

[0018] (3) The fault detection system of electronic components provides a data-driven decision support platform by integrating and analyzing historical voltage, current and frequency data. This systematic analysis helps the maintenance team not only identify immediate faults, but also predict long-term equipment performance trends. Therefore, maintenance decisions can be transformed from reactive to preventive and predictive, thereby optimizing equipment maintenance plans and resource allocation.

[0019] (4) The fault detection system of the electronic components includes data acquisition, preprocessing, analysis and diagnosis subsystems through a modular structure. This modularity not only makes the system easy to maintain and upgrade, but also facilitates integration with other systems, such as linkage with a wider equipment health monitoring platform or enterprise-level resource planning system. As technology advances and corporate needs change, the system can flexibly add new functional modules or upgrade existing modules to adapt to new monitoring and analysis needs, thereby maintaining the advancement and competitiveness of technology.

[0020] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The present invention is a flow chart of a method for detecting a fault of an electronic component.

[0022] Figure 2 The present invention is a flowchart of the specific steps of obtaining a voltage fault index of an electronic component in a fault detection method of an electronic component.

[0023] Figure 3 The present invention is a block diagram of a fault detection system for electronic components. DETAILED DESCRIPTION

[0024] The embodiment of the present application solves the problem that traditional fault detection methods are usually lacking in comprehensiveness through a fault detection method for electronic components. They usually only focus on a single indicator for fault monitoring, making it difficult to comprehensively evaluate the health status of components. In addition, traditional fault detection methods usually rely on manual inspection, which often leads to missed detections and delayed fault diagnosis.

[0025] The overall idea of ​​the problem in the embodiment of this application is as follows: First, the system obtains the historical voltage, current and frequency data of electronic components. These data are preprocessed to remove noise and outliers to ensure the accuracy of the analysis. Then, based on the set standard voltage, current and frequency error range, the preprocessed data is analyzed in detail, the voltage, current and frequency differences are calculated, and these differences are compared with the standard values ​​to generate their respective fault indicators. Finally, the system determines whether each fault indicator is abnormal based on the preset fault threshold. If an indicator exceeds the threshold, it will be marked as a fault feature, providing a clear direction for subsequent maintenance or further analysis.

[0026] See also Figure 1 The embodiment of the present invention provides a technical solution: a fault detection method for electronic components, comprising the following steps: obtaining historical voltage data, historical current data, and historical frequency data of the electronic components, and performing preprocessing; based on preset standard voltage, standard current, and frequency error ranges, respectively analyzing the preprocessed historical voltage data, historical current data, and historical frequency data of the electronic components to obtain voltage fault indicators, current fault indicators, and frequency fault indicators of the electronic components; judging whether the voltage fault indicators, current fault indicators, and frequency fault indicators of the electronic components meet the corresponding set fault thresholds, and marking the corresponding fault indicators that do not meet the set fault thresholds as fault features.

[0027] The historical voltage data specifically refers to the historical input voltage value and historical output voltage value of the electronic component at each historical time point. The historical current data specifically refers to the historical measured current value of each energized conductor inside the electronic component at each historical time point. The historical frequency data specifically refers to the historical frequency value of the electronic component at each historical time point. The frequency fault index specifically refers to the number of time points with abnormal frequencies.

[0028] Specifically, Figure 2 As shown, the preset standard voltage includes a standard input voltage and a standard output voltage, and the specific process of obtaining the voltage fault index of the electronic component is as follows: read the historical input voltage value and the historical output voltage value of the electronic component at each historical time point; based on the preset standard input voltage and standard output voltage, perform mean analysis on the historical input voltage value and the historical output voltage value at each historical time point to obtain the historical input voltage difference index and the historical output voltage difference index; conduct a comprehensive analysis on the historical input voltage difference index and the historical output voltage difference index to obtain the voltage fault index of the electronic component.

[0029] The specific formula for calculating the voltage fault index of electronic components is as follows: ; It is the voltage fault indicator of electronic components. The first electronic component in history The historical input voltage value at a time point, is the preset standard input voltage, is the proportionality coefficient of the average difference between the historical input voltage value of the preset electronic component at each time point and the preset standard input voltage, The first electronic component in history The historical output voltage value at a time point, is the preset standard output voltage, is the proportionality coefficient of the average difference between the historical output voltage value of the preset electronic component at each time point and the preset standard output voltage, , , The number of historical time points of the historical input voltage value and the historical output voltage value obtained.

[0030] In this implementation scheme, historical input voltage and output voltage data are regularly collected from electronic components. This step ensures that there are enough data points for accurate analysis, covering various operating conditions and possible abnormal situations. The collected voltage data is cleaned, such as removing abnormal peaks and obviously erroneous data points. This step improves data quality and ensures the accuracy of the analysis. The difference between the input voltage and output voltage at each time point and the standard voltage is calculated, and then the mean of these differences is calculated. This step can smooth random fluctuations through mean analysis and more clearly see the long-term trend of the voltage difference. The mean of the difference between the input and output voltages is multiplied by their proportional coefficients respectively, and these data are combined to obtain a comprehensive voltage fault index. This step can more comprehensively evaluate the performance of electronic components under different working conditions by weighting the means of different voltage differences, and compare the voltage fault index with the preset fault. Threshold, this step determines whether there is a voltage-related fault and the severity of the fault. Through detailed analysis of the input and output voltages, this method can accurately identify small voltage changes that may indicate the development of an early fault, helping the maintenance team to intervene before the problem becomes an expensive failure, thereby avoiding equipment damage and production stagnation. Continuous data collection and analysis make the monitoring process more dynamic and timely, supporting trend-based predictive maintenance strategies, which reduce traditional time-based or cycle-based maintenance activities and adopt more effective condition-based maintenance methods. This method only intervenes when a potential fault is detected. The standardized analysis process simplifies the fault diagnosis process and makes problem solving more efficient and systematic. This method provides a quantifiable and repeatable analysis method for fault diagnosis, improving the quality and reliability of the entire maintenance process.

[0031] Specifically, the specific process of obtaining the current fault index of the electronic component is as follows: read the historical measured current value of each energized conductor inside the electronic component at each historical time point, and perform error analysis based on the moving exponential averaging method and the preset standard current to obtain the historical current error mean of each energized conductor; perform weighted analysis on the historical current error mean of each energized conductor to obtain the current fault index of the electronic component.

[0032] The specific formula for calculating the current fault index of electronic components is as follows: ;in, is the current fault indicator of electronic components, For the The historical current error mean of each energized conductor, For the preset The proportionality coefficient of the mean historical current error of each energized conductor, The number of internal power-carrying wires in electronic components.

[0033] The calculation formula for the mean historical current error of the energized conductor is as follows: ;in, is the historical current error mean of the energized conductor, The first in the history of conducting wires The historical measured current value at each time point, is the preset standard current, The history of the pre-set energized conductor The proportional coefficient of the difference between the historical measured current value at a time point and the preset standard current, The first in the history of conducting wires The historical measured current value at each time point, The history of the pre-set energized conductor The proportional coefficient of the difference between the historical measured current value at a time point and the preset standard current, , , The number of historical time points of the historical measured current values ​​obtained.

[0034] In this implementation scheme, historical current data is periodically obtained from each energized conductor of the electronic component. This step ensures that there is sufficient data to support accurate fault analysis. The moving exponential averaging method is applied to the measured current value at each time point to smooth the data and reduce the impact of instantaneous noise. This step provides more stable and reliable current data to facilitate accurate analysis of current trends and anomalies. The difference between the measured current value at each time point and the preset standard current is calculated, and the weighted average of these differences is calculated. This step identifies and quantifies the deviation of the current on each conductor to determine whether the current is within the normal operating range. The current error mean of each conductor is weighted according to a preset proportionality coefficient to obtain a comprehensive current fault index of the electronic component. This step comprehensively evaluates the current health of the component by comprehensively analyzing the current conditions of all conductors. Status, through continuous monitoring and precise analysis of the current of each conductor, this method can accurately diagnose current-related problems, even if these problems may be very minor in the early stages, enabling the maintenance team to intervene before the problem develops into a serious fault, thereby significantly reducing maintenance costs and equipment downtime. Accurate current fault analysis can prevent equipment damage caused by abnormal current, such as overload, short circuit, etc., enhance the overall reliability and safety of the system, avoid possible accidents and equipment losses, and ensure the stable operation of the production line. By continuously monitoring current data and performing trend analysis, this method supports condition-based maintenance rather than time-based maintenance, making maintenance decisions more data-driven and precise, reducing unnecessary maintenance activities, improving resource utilization efficiency, and optimizing operating costs.

[0035] Specifically, the specific process of obtaining the frequency fault index of the electronic component is as follows: read the historical frequency value of the electronic component at each historical time point and analyze the median value of the historical frequency; perform abnormal time point detection on the historical frequency data based on the Grubbs test method, and the specific process is to calculate the fault score of each data point to identify abnormal points that deviate from the average level, that is, to calculate the difference between the historical frequency value of each historical time point and the median value of the historical frequency, to obtain the frequency difference between the historical frequency value of each historical time point and the median value of the historical frequency, and to determine whether the frequency difference is within the frequency error range. If the frequency difference is outside the frequency error range, it is regarded as an abnormal time point; count the number of abnormal time points and record them as the frequency fault index of the electronic component.

[0036] In this embodiment, the frequency data of electronic components at various time points are continuously recorded. This step ensures that there are sufficient data points to cover various working conditions of the components, providing a basis for accurate analysis. The median value of the collected frequency data is calculated as a benchmark for evaluating frequency stability. The median value in this step is insensitive to extreme values ​​and is suitable as a benchmark for stability analysis, which helps to reduce the impact of accidental fluctuations. The Grubbs test method is used to analyze the difference between the frequency value and the median value at each time point to detect statistically significant abnormal points. This step effectively identifies those frequency values ​​that deviate from the normal operating range. These abnormalities may indicate potential failures or performance degradation. The number of frequency points that are considered abnormal is counted and used as a frequency failure indicator. This step provides a quantitative indicator to evaluate the component. The frequency stability and health status of the device. By continuously monitoring and timely identifying abnormal changes in frequency, this method can provide early warning before the problem leads to serious failure. This early warning capability allows the maintenance team to intervene in time and take necessary preventive measures to avoid costly repairs or replacements. Through systematic data analysis and abnormal point statistics, maintenance decisions can rely more on data rather than empirical judgment. This data-driven decision support system improves the scientific nature and effectiveness of maintenance strategies, helps optimize resource allocation and reduce operation and maintenance costs. Frequent abnormal frequency monitoring ensures that the equipment operates in the optimal state. Timely fault handling can reduce unplanned downtime of equipment. By reducing equipment failures and unplanned downtime, this method significantly improves production efficiency and the overall reliability of equipment.

[0037] See also Figure 3 The embodiment of the present invention provides a technical solution: a fault detection system for electronic components, including: a data acquisition subsystem, a data preprocessing subsystem, a fault analysis subsystem, and a fault diagnosis subsystem; the data acquisition subsystem is used to acquire historical voltage data, historical current data, and historical frequency data of electronic components; the data preprocessing subsystem is used to preprocess the historical voltage data, historical current data, and historical frequency data of electronic components; the fault analysis subsystem is used to analyze the preprocessed historical voltage data, historical current data, and historical frequency data of electronic components based on preset standard voltage, standard current, and frequency error ranges, respectively, to obtain voltage fault indicators, current fault indicators, and frequency fault indicators of electronic components; the fault diagnosis subsystem is used to determine whether the voltage fault indicators, current fault indicators, and frequency fault indicators of electronic components meet the corresponding set fault thresholds, respectively, and mark the corresponding fault indicators that do not meet the set fault thresholds as fault features.

[0038] Specifically, the fault analysis subsystem includes: a voltage analysis module, a current analysis module, and a frequency analysis module; the voltage analysis module is used to analyze historical voltage data based on a preset standard voltage and calculate a voltage difference index; the current analysis module is used to perform error analysis on current data based on a moving exponential average method and a standard current value; the frequency analysis module is used to read frequency data and perform median analysis, use the Grubbs test method to detect abnormal time points, and mark frequency fault indicators.

[0039] In this implementation scheme, the voltage analysis module obtains historical voltage data from the device, including input and output voltages, and calculates the difference between the voltage data at each time point and the preset standard voltage. The difference data is used to generate a voltage difference index to ensure that the voltage is within the safe operating range specified by the device, prevent excessively high or low voltages from damaging the device, and identify voltage fluctuations that may cause failures in advance, so as to take preventive measures. By continuously monitoring and analyzing voltage changes, the operating stability of the system and the reliability of the equipment are improved. The current analysis module collects current measurement values ​​at each time point, applies the moving exponential averaging method to smooth the current data, reduces the impact of instantaneous peaks or noise, calculates the difference between the smoothed current value and the standard current value, and generates a current error index. By continuously monitoring the stability of the current, Early detection of equipment problems caused by abnormal current, such as overload or current leakage. Moving exponential averaging provides more accurate current trend analysis, which helps to identify long-term changes, enhance equipment safety, and avoid failures or accidents caused by current problems. The frequency analysis module records the operating frequency data of the equipment, determines the median value of the frequency data as the benchmark for stability analysis, and applies the Grubbs test method to identify abnormal frequency points that are significantly different from the median value. The number of abnormal frequency points is counted as a frequency fault indicator. Frequency analysis helps to identify operating problems caused by frequency abnormalities, such as synchronization errors or vibration abnormalities. The use of the Grubbs test method can accurately identify real abnormal points rather than occasional fluctuations, which improves the real-time monitoring capability of the equipment health status and enhances the efficiency of preventive maintenance and fault diagnosis.

[0040] In summary, this application has at least the following effects: By continuously monitoring and analyzing historical data, potential failures can be detected before problems develop into more serious stages, which not only reduces unexpected equipment downtime but also facilitates planned maintenance, thereby saving costs and extending equipment life.

[0041] Through multi-dimensional analysis of voltage, current and frequency, a comprehensive way to judge the status of components is provided. Compared with the traditional method that relies on a single data point, this comprehensive analysis helps technicians accurately locate the root cause of the problem, improve maintenance efficiency and reduce misjudgment.

[0042] By integrating and analyzing historical voltage, current and frequency data, a data-driven decision support platform is provided. This systematic analysis helps maintenance teams not only identify immediate faults, but also predict long-term equipment performance trends. Therefore, maintenance decisions can be transformed from reactive to preventive and predictive, thereby optimizing equipment maintenance plans and resource allocation.

[0043] Through a modular structure, it includes data acquisition, preprocessing, analysis and diagnosis subsystems. This modularity not only makes the system easy to maintain and upgrade, but also facilitates integration with other systems, such as linkage with a wider equipment health monitoring platform or enterprise-level resource planning system. As technology advances and corporate needs change, the system can flexibly add new functional modules or upgrade existing modules to adapt to new monitoring and analysis needs, thereby maintaining technological advancement and competitiveness.

[0044] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0045] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for detecting a fault of an electronic component, characterized in that: The following steps are involved: Obtain historical voltage data, historical current data, and historical frequency data of electronic components and perform preprocessing; Based on the preset standard voltage, standard current, and frequency error range, the preprocessed historical voltage data, historical current data, and historical frequency data of the electronic components are analyzed respectively to obtain the voltage fault index, current fault index, and frequency fault index of the electronic components; Determine whether the voltage fault index, current fault index, and frequency fault index of the electronic component meet the corresponding set fault thresholds, and mark the corresponding fault index that does not meet the set fault threshold as a fault feature; The historical voltage data is specifically the historical input voltage value and the historical output voltage value of the electronic component at each historical time point, the historical current data is specifically the historical measured current value of each energized wire inside the electronic component at each historical time point, the historical frequency data is specifically the historical frequency value of the electronic component at each historical time point, and the frequency fault indicator is specifically the number of time points with abnormal frequency; The preset standard voltage includes a standard input voltage and a standard output voltage. The specific process of obtaining the voltage fault index of the electronic component is as follows: Read the historical input voltage value and historical output voltage value of electronic components at each time point; Based on the preset standard input voltage and standard output voltage, the historical input voltage value and the historical output voltage value at each historical time point are respectively analyzed for mean value, so as to obtain the historical input voltage difference index and the historical output voltage difference index; Comprehensively analyze the historical input voltage difference index and the historical output voltage difference index to obtain the voltage fault index of the electronic components; The specific formula for calculating the voltage fault index of electronic components is as follows: ； is the voltage fault indicator of electronic components. The first electronic component in history The historical input voltage value at a time point, is the preset standard input voltage, is the proportionality coefficient of the average difference between the historical input voltage value of the preset electronic component at each time point and the preset standard input voltage, The first electronic component in history The historical output voltage value at a time point, is the preset standard output voltage, is the proportionality coefficient of the average difference between the historical output voltage value of the preset electronic component at each time point and the preset standard output voltage, , , The number of historical time points of the historical input voltage value and the historical output voltage value obtained.

2. The electronic component fault detection method according to claim 1, characterized in that: The specific process of obtaining the current fault index of electronic components is as follows: Read the historical measured current value of each energized wire inside the electronic component at each historical time point, and perform error analysis based on the moving exponential average method and the preset standard current to obtain the historical current error mean value of each energized wire; Perform weighted analysis on the historical current error mean of each energized wire to obtain the current fault index of the electronic components; The specific formula for calculating the current fault index of electronic components is as follows: ； in, is the current fault indicator of electronic components. For the The historical current error mean of each energized conductor, For the preset The proportionality coefficient of the mean historical current error of each energized conductor, The number of internal power-carrying wires in electronic components.

3. The electronic component fault detection method according to claim 1, characterized in that: The specific process of obtaining the frequency fault index of electronic components is as follows: Read the historical frequency value of electronic components at each historical time point and analyze the median value of the historical frequency; Based on the Grubbs test method, abnormal time points of historical frequency data are detected. The specific process is to calculate the fault score of each data point, that is, to calculate the difference between the historical frequency value of each historical time point and the historical frequency median value, and obtain the frequency difference between the historical frequency value of each historical time point and the historical frequency median value, and judge whether the frequency difference is within the frequency error range. If the frequency difference is outside the frequency error range, it is regarded as an abnormal time point; The number of abnormal time points is counted and recorded as the frequency failure index of the electronic components.

4. The electronic component fault detection method according to claim 3, characterized in that: The calculation formula for the mean historical current error of the energized conductor is as follows: ； in, is the historical current error mean of the energized conductor, The first in the history of conducting wires The historical measured current value at each time point, is the preset standard current, The history of the pre-set energized conductor The proportional coefficient of the difference between the historical measured current value at a time point and the preset standard current, The first in the history of conducting wires The historical measured current value at each time point, The history of the pre-set energized conductor The proportional coefficient of the difference between the historical measured current value at a time point and the preset standard current, , , The number of historical time points of the historical measured current values ​​obtained.

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