Electronic component fault prediction system based on electronic measurement signal processing

Abstract

The invention belongs to the field of electronic component fault prediction, relates to a data analysis technology, is used for solving the problem that the fault prediction accuracy of an electronic component cannot be verified and an early warning standard cannot be corrected in the prior art, and particularly relates to an electronic component fault prediction system based on electronic measurement signal processing. Comprising a fault test module, a standard optimization module, a contrast analysis module and a database, the fault test module, the standard optimization module and the contrast analysis module are in communication connection in sequence, and the fault test module, the standard optimization module and the contrast analysis module are all in communication connection with the database; according to the method, fault test analysis can be carried out on the electronic elements, after classification is carried out according to functions, early warning accuracy analysis is carried out on the electronic elements of various types, differential marking is carried out on the test process by analyzing the numerical values of various performance parameters in a time period, and data support is provided for a standard optimization process and a contrast analysis process.

Description

Technical Field

[0001] The present invention belongs to the field of electronic component fault prediction, involves data analysis technology, and specifically is an electronic component fault prediction system based on electronic measurement signal processing. Background Art

[0002] An electronic component fault prediction system is an intelligent system that can monitor the operating state of electronic components in real time, predict potential faults, and issue early warnings. The system uses advanced algorithms and models to analyze and learn these data, and can identify abnormal patterns and trends in the operation of electronic components to determine whether they are in a healthy state.

[0003] The invention patent with the publication number CN113033695B discloses a method for predicting faults of electronic devices. This prediction method can make full use of the chain structure of the LSTM network, enabling the model to have the ability to extract independent relationship information, improving the accuracy of predicting the voltage and current data output by electronic devices and the accuracy of fault prediction. However, this prediction method cannot verify the accuracy of electronic component fault prediction and correct the warning standard. At the same time, this method cannot comprehensively analyze the self-operating parameters of electronic components and external interference factors, resulting in the inability to guarantee the fault prediction results.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of the present invention is to provide an electronic component fault prediction system based on electronic measurement signal processing, which is used to solve the problem that the prior art cannot verify the accuracy of electronic component fault prediction and correct the warning standard.

[0006] The technical problem that the present invention needs to solve is: how to provide an electronic component fault prediction system based on electronic measurement signal processing that can verify the accuracy of electronic component fault prediction and correct the warning standard.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] An electronic component fault prediction system based on electronic measurement signal processing includes a fault test module, a standard optimization module, a comparison and analysis module, and a database. The fault test module, the standard optimization module, and the comparison and analysis module are sequentially communicatively connected, and the fault test module, the standard optimization module, and the comparison and analysis module are all communicatively connected to the database;

[0009] The fault test module is used to conduct fault test analysis on electronic components: classify the electronic components according to their functions, select several electronic components from each type as test objects, put the test objects into use and generate a test period, collect the values of the performance parameters of the test objects during the test period and mark them as performance values, retrieve the warning range corresponding to the performance parameters of the test objects, where the minimum boundary value of the warning range is the warning threshold and the maximum boundary value of the warning range is the alarm threshold; when any performance value of the test object reaches the corresponding warning threshold, generate an analysis period of L1 minutes, mark the corresponding performance parameter as an extraction parameter, mark the test process corresponding to the analysis period as a trigger process or an analysis process, conduct risk analysis on the analysis process and mark the analysis process as a trigger process or a false alarm process;

[0010] The standard optimization module is used to conduct warning standard optimization analysis on electronic components: mark the number of trigger processes and false alarm processes corresponding to the performance parameters as extraction parameters as the trigger value and the false alarm value respectively, mark the ratio of the false alarm value to the trigger value as the false alarm coefficient of the performance parameter, and determine whether the warning standard of the performance parameter meets the requirements through the false alarm coefficient;

[0011] The comparison analysis module is used to conduct comparison analysis on the performance parameters of electronic components.

[0012] Further, the specific process of marking the test process corresponding to the analysis period as a trigger process or an analysis process includes: monitoring whether the maximum value of any performance value of the test object exceeds the corresponding alarm threshold at the end of the analysis period: if so, mark the corresponding test process as a trigger process; if not, mark the corresponding test process as an analysis process.

[0013] Further, the specific process of conducting risk analysis on the analysis process includes: obtaining the risk coefficient FX of the analysis period through the numerical difference between the fault threshold corresponding to each performance parameter and the performance value during the analysis period; obtaining the risk threshold FXmin through the database, and comparing the risk coefficient FX with the risk threshold FXmin: if the risk coefficient FX is less than the risk threshold FXmin, mark the corresponding test process as a trigger process; if the risk coefficient FX is greater than or equal to the risk threshold FXmin, mark the corresponding test process as a false alarm process.

[0014] Further, the specific process for determining whether the early warning criteria for performance parameters meet the requirements includes: obtaining the false alarm threshold through the database, and comparing the false alarm coefficient with the false alarm threshold. If the false alarm coefficient is less than the false alarm threshold, it is determined that the early warning criteria for the corresponding performance parameter meet the requirements, generating a comparison analysis signal and sending the comparison analysis signal to the comparison analysis module. If the false alarm coefficient is greater than or equal to the false alarm threshold, it is determined that the early warning criteria for the corresponding performance parameter do not meet the requirements, and the numerical value of the early warning threshold for the performance parameter is optimized.

[0015] Further, the specific process for numerically optimizing the early warning threshold of performance parameters includes: obtaining the new early warning value YJnew through the formula YJnew = YJ + c1×(BJ - YJ), where YJ and BJ are the numerical values of the early warning threshold and the alarm threshold for the corresponding performance parameter respectively, c1 is the proportionality coefficient, and 1.05 ≤ c1 ≤ 1.15. A new early warning range is formed by the new early warning value YJnew and the alarm threshold, and the new early warning range replaces the original early warning range.

[0016] Further, the specific process for the comparison analysis module to conduct a comparison analysis on the performance parameters of electronic components includes: obtaining the numerical value of the corresponding comparison parameter when the performance parameter is used as the extraction parameter and marking it as the comparison value. The comparison set of the performance parameter is composed of the comparison values corresponding to all false alarm processes when the performance parameter is used as the extraction parameter. Feature extraction and analysis are performed on the comparison set to obtain the false alarm comparison range. The trigger set of the performance parameter is composed of the comparison values corresponding to all trigger processes when the performance parameter is used as the extraction parameter. Feature extraction and analysis are performed on the trigger set in the same way as the false alarm comparison range to obtain the trigger comparison range, and the false alarm comparison range and the trigger comparison range are compared and analyzed: the overlapping interval between the false alarm comparison range and the trigger comparison range is marked as the feature interval, and the feature interval is segmented and removed from the false alarm comparison range.

[0017] Further, the specific process for performing feature extraction and analysis on the comparison set includes: calculating the variance of the comparison set to obtain the false alarm feature coefficient, obtaining the false alarm feature threshold through the database, and comparing the false alarm feature coefficient with the false alarm feature threshold. If the false alarm feature coefficient is less than the false alarm feature threshold, it is determined that the retained elements in the comparison set have a unified feature, and the false alarm comparison range of the performance parameter is formed by the maximum and minimum values of the retained elements in the comparison set. If the false alarm feature coefficient is greater than or equal to the false alarm feature threshold, the maximum and minimum elements in the comparison set are removed, and then the false alarm feature coefficient is recalculated, and so on until the false alarm feature coefficient is less than the false alarm feature threshold.

[0018] Further, after completing the performance test, standard optimization, and control analysis, when any performance value of the test object reaches the corresponding warning threshold, retrieve the value of the control parameter corresponding to the performance parameter and the false alarm control range, and determine whether the value of the control parameter is within the false alarm control range: if so, do not process; if not, generate a fault warning signal and send the fault warning signal to the mobile terminal of the management personnel.

[0019] The present invention has the following beneficial effects:

[0020] 1. Through the fault test module, fault test analysis can be carried out on electronic components. After classifying according to functions, early warning accuracy analysis is carried out on each type of electronic component. When any performance value of the test object reaches the early warning standard, an analysis period is generated, and the values of each performance parameter within the analysis period are used to differentially mark the test process, providing data support for the standard optimization process and the control analysis process;

[0021] 2. Through the standard optimization module, early warning standard optimization analysis can be carried out on electronic components. The false alarm coefficient is calculated according to the marked times of the false alarm process and the trigger process, and the early warning standard of the performance parameter is determined whether it meets the requirements through the false alarm coefficient. When it does not meet the requirements, numerical optimization is carried out to improve the accuracy of the fault early warning output result;

[0022] 3. Through the control analysis module, control analysis can be carried out on the performance parameters of electronic components, the false alarm control range of the performance parameters is extracted, and fault early warning analysis is carried out in combination with the performance value and the false alarm control range, reducing the false alarm rate of the system's fault early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0024] Figure 1 It is the system block diagram of Embodiment 1 of the present invention;

[0025] Figure 2 It is the method flow chart of Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0026] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts belong to the scope of protection of the present invention.

[0027] Embodiment 1: As Figure 1 shown, an electronic component fault prediction system based on electronic measurement signal processing includes a fault test module, a standard optimization module, a comparison analysis module, and a database. The fault test module, the standard optimization module, and the comparison analysis module are communicatively connected in sequence, and the fault test module, the standard optimization module, and the comparison analysis module are all communicatively connected to the database.

[0028] The fault test module is used to perform fault test analysis on electronic components: classify the electronic components according to their functions, select several electronic components from each type as test objects, put the test objects into use and generate a test cycle, collect the numerical values of the performance parameters of the test objects during the test cycle and mark them as performance values. The performance parameters include voltage, current, and surface temperature. Retrieve the warning range corresponding to the performance parameters of the test objects. The minimum boundary value of the warning range is the warning threshold, and the maximum boundary value of the warning range is the alarm threshold; when any performance value of the test object reaches the corresponding warning threshold, generate an analysis period with a duration of L1 minutes, and mark the performance parameter whose performance value reaches the corresponding warning threshold at the start time of the analysis period as the extraction parameter. L1 is a numerical constant, and the specific value of L1 is set by the management personnel themselves; at the end time of the analysis period, monitor whether the maximum value of any performance value of the test object exceeds the corresponding alarm threshold:

[0029] If so, mark the corresponding test process as a trigger process;

[0030] If not, mark the corresponding test process as an analysis process and perform risk analysis on the analysis process: obtain the voltage risk value YF, current risk value LF, and temperature risk value WF of the analysis period. The process of obtaining the voltage risk value YF includes: mark the difference between the warning threshold corresponding to the voltage and the voltage value of the test object as the voltage difference value, and mark the minimum value of the voltage difference value during the analysis period as the voltage risk value YF; the process of obtaining the current risk value LF includes: mark the difference between the warning threshold corresponding to the current and the current value of the test object as the current difference value, and mark the minimum value of the current difference value during the analysis period as the current risk value LF; the process of obtaining the temperature risk value WF includes: mark the difference between the warning threshold corresponding to the surface temperature and the surface temperature value of the test object as the temperature difference value, and mark the minimum value of the temperature difference value during the analysis period as the temperature risk value WF;

[0031] The risk coefficient FX of the test object is obtained through the formula FX = k1×YF + k2×LF + k3×WF, where k1, k2, and k3 are all proportionality coefficients, and k1 > k2 > k3 > 1; the risk threshold FXmin is obtained through the database, and the risk coefficient FX is compared with the risk threshold FXmin: if the risk coefficient FX is less than the risk threshold FXmin, the corresponding test process is marked as a trigger process; if the risk coefficient FX is greater than or equal to the risk threshold FXmin, the corresponding test process is marked as a false alarm process; for the fault test analysis of electronic components, after classification according to functions, the warning accuracy analysis of each type of electronic component is carried out. When any performance value of the test object reaches the warning standard, an analysis period is generated, and the test process is differentially marked through the values of each performance parameter within the analysis period, providing data support for the standard optimization process and the control analysis process.

[0032] The standard optimization module is used to perform warning standard optimization analysis on electronic components: the number of trigger processes and false alarm processes corresponding to the performance parameters as extraction parameters are respectively marked as the trigger value and the false alarm value, the ratio of the false alarm value to the trigger value is marked as the false alarm coefficient of the performance parameter, the false alarm threshold is obtained through the database, and the false alarm coefficient is compared with the false alarm threshold: if the false alarm coefficient is less than the false alarm threshold, it is determined that the warning standard of the corresponding performance parameter meets the requirements, a control analysis signal is generated and sent to the control analysis module; if the false alarm coefficient is greater than or equal to the false alarm threshold, it is determined that the warning standard of the corresponding performance parameter does not meet the requirements, and the warning threshold of the performance parameter is numerically optimized:

[0033] The new warning value YJnew is obtained through the formula YJnew = YJ + c1×(BJ - YJ), where YJ and BJ are the numerical values of the warning threshold and the alarm threshold of the corresponding performance parameter respectively, c1 is a proportionality coefficient, and 1.05 ≤ c1 ≤ 1.15. A new warning range is formed by the new warning value YJnew and the alarm threshold, and the new warning range replaces the original warning range; the false alarm coefficient is calculated based on the marked times of the false alarm process and the trigger process, and it is determined whether the warning standard of the performance parameter meets the requirements through the false alarm coefficient. When it does not meet the requirements, numerical optimization is carried out to improve the accuracy of the fault warning output result.

[0034] The comparison and analysis module is used to perform comparison and analysis on the performance parameters of electronic components: obtain the numerical value of the corresponding comparison parameter when the performance parameter is used as the extraction parameter and mark it as the comparison value. When the performance parameter is current and voltage, its comparison parameter is the load value of the test object. When the performance parameter is the surface temperature, its comparison parameter is the air temperature value of the operating environment of the test object. It can be understood that when a single performance parameter, such as the surface temperature, exceeds the corresponding warning range, the numerical value of its surface temperature is also affected by the external environmental temperature. Although a higher external environmental temperature will affect the operating performance of the electronic component, an increase in the numerical value of the surface temperature caused by the external environment does not directly reflect an abnormality in the operating performance of the electronic component. Therefore, it is necessary to perform feature analysis on each performance parameter and the comparison parameter to ensure the accuracy of the fault warning output result; the comparison set of the performance parameter is composed of the comparison values corresponding to all false alarm processes when the performance parameter is used as the extraction parameter, and perform feature extraction and analysis on the comparison set:

[0035] Calculate the variance of the comparison set to obtain the false alarm feature coefficient, obtain the false alarm feature threshold through the database, and compare the false alarm feature coefficient with the false alarm feature threshold: if the false alarm feature coefficient is less than the false alarm feature threshold, it is determined that the retained elements in the comparison set have a unified feature, and the false alarm comparison range of the performance parameter is composed of the maximum value and the minimum value of the retained elements in the comparison set; if the false alarm feature coefficient is greater than or equal to the false alarm feature threshold, the maximum element and the minimum element in the comparison set are removed, and then the false alarm feature coefficient is recalculated, and so on, until the false alarm feature coefficient is less than the false alarm feature threshold.

[0036] The trigger set of the performance parameter is composed of the comparison values corresponding to all trigger processes when the performance parameter is used as the extraction parameter. Perform feature extraction and analysis on the trigger set in the same acquisition manner as the false alarm comparison range to obtain the trigger comparison range, and compare and analyze the false alarm comparison range with the trigger comparison range: mark the repeated interval of the false alarm comparison range and the trigger comparison range as the feature interval, and divide and remove the feature interval from the false alarm comparison range; after completing the performance test, standard optimization, and comparison analysis, when any performance value of the test object reaches the corresponding warning threshold, retrieve the numerical value of the comparison parameter corresponding to the performance parameter and the false alarm comparison range, and determine whether the numerical value of the comparison parameter is within the false alarm comparison range: if so, do not process; if not, generate a fault warning signal and send the fault warning signal to the mobile terminal of the management personnel; extract the false alarm comparison range of the performance parameter, and combine the performance value and the false alarm comparison range to perform fault warning analysis to reduce the false alarm rate of the system's fault warning.

[0037] Embodiment 2: As Figure 2 shown, an electronic component fault prediction method based on electronic measurement signal processing includes the following steps:

[0038] Step 1: Conduct fault test analysis on electronic components: Classify the electronic components according to their functions, select several electronic components from each type as test objects, put the test objects into use and generate a test cycle, conduct fault tests on the test objects during the test cycle and mark the test process as a trigger process or a false alarm process;

[0039] Step 2: Conduct early warning standard optimization analysis on electronic components: Mark the number of trigger processes and false alarm processes corresponding to the performance parameters as the trigger value and the false alarm value respectively when the performance parameters are used as extraction parameters, mark the ratio of the false alarm value to the trigger value as the false alarm coefficient of the performance parameter, and determine whether the early warning standard of the performance parameter meets the requirements through the false alarm coefficient;

[0040] Step 3: Conduct comparative analysis on the performance parameters of electronic components: Obtain the value of the control parameter corresponding to the performance parameter when the performance parameter is used as the extraction parameter and mark it as the control value, extract the numerical value of the control value of the control parameter to obtain the false alarm control range and the trigger control range, conduct a comparative analysis on the false alarm control range and the trigger control range and update the false alarm control range, and conduct early warning monitoring on the performance parameters of the electronic components by combining the updated early warning standard and the false alarm control range.

[0041] An electronic component fault prediction system based on electronic measurement signal processing, during operation, classifies the electronic components according to their functions, selects several electronic components from each type as test objects, puts the test objects into use and generates a test cycle, conducts fault tests on the test objects during the test cycle and marks the test process as a trigger process or a false alarm process; marks the number of trigger processes and false alarm processes corresponding to the performance parameters as the trigger value and the false alarm value respectively when the performance parameters are used as extraction parameters, marks the ratio of the false alarm value to the trigger value as the false alarm coefficient of the performance parameter, and determines whether the early warning standard of the performance parameter meets the requirements through the false alarm coefficient; obtains the value of the control parameter corresponding to the performance parameter when the performance parameter is used as the extraction parameter and marks it as the control value, extracts the numerical value of the control value of the control parameter to obtain the false alarm control range and the trigger control range, conducts a comparative analysis on the false alarm control range and the trigger control range and updates the false alarm control range, and conducts early warning monitoring on the performance parameters of the electronic components by combining the updated early warning standard and the false alarm control range.

[0042] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology make various modifications or supplements to the described specific embodiments or use similar methods to replace them. As long as they do not deviate from the structure of the invention or exceed the scope defined by this claim book, they should all fall within the protection scope of the present invention.

[0043] The above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value. The coefficients in the formula are set by those skilled in the art according to the actual situation. For example, the formula FX = k1×YF + k2×LF + k3×WF; those skilled in the art collect multiple sets of sample data and set corresponding risk coefficients for each set of sample data; substitute the set risk coefficients and the collected sample data into the formula, and any three formulas form a system of linear equations with three variables. Screen the calculated coefficients and take the average value to obtain the values of k1, k2, and k3 as 3.65, 2.83, and 2.24 respectively.

[0044] The magnitude of the coefficient is a specific value obtained by quantifying each parameter for subsequent comparison. Regarding the magnitude of the coefficient, it depends on the amount of sample data and the risk coefficients initially set by those skilled in the art for each set of sample data; as long as the proportional relationship between the parameter and the quantified value is not affected, for example, the risk coefficient is directly proportional to the voltage risk value.

[0045] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0046] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not elaborate all the details, nor do they limit the present invention to only the specific implementation manners. Obviously, many modifications and variations can be made according to the content of this specification. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An electronic component fault prediction system based on electronic measurement signal processing, characterized in that: It includes a fault testing module, a standard optimization module, a comparison analysis module and a database, wherein the fault testing module, the standard optimization module and the comparison analysis module are sequentially connected in communication, and the fault testing module, the standard optimization module and the comparison analysis module are all connected in communication with the database; The fault testing module is used to perform fault testing and analysis on electronic components: classify the electronic components according to their functions, select a number of electronic components from each type as test objects, put the test objects into use and generate a test cycle, collect the values ​​of the performance parameters of the test objects within the test cycle and mark them as performance values, retrieve the warning range corresponding to the performance parameters of the test objects, the minimum boundary value of the warning range is the warning threshold, and the maximum boundary value of the warning range is the alarm threshold; when any performance value of the test object reaches the corresponding warning threshold, an analysis period of L1 minutes is generated, and the corresponding performance parameter is marked as an extraction parameter, the test process corresponding to the analysis period is marked as a trigger process or an analysis process, a risk analysis is performed on the analysis process and the analysis process is marked as a trigger process or a false alarm process; The standard optimization module is used to optimize and analyze the early warning standard of the electronic component: the number of trigger processes and false alarm processes corresponding to the performance parameter as the extraction parameter is marked as the trigger value and the false alarm value, respectively, and the ratio of the false alarm value to the trigger value is marked as the false alarm coefficient of the performance parameter, and the false alarm coefficient is used to determine whether the early warning standard of the performance parameter meets the requirements; The comparison and analysis module is used to perform comparison and analysis on the performance parameters of the electronic components.

2. The electronic component fault prediction system based on electronic measurement signal processing according to claim 1, characterized in that: The specific process of marking the test process corresponding to the analysis period as a trigger process or an analysis process includes: monitoring whether the maximum value of any performance value of the test object exceeds the corresponding alarm threshold at the end of the analysis period: if so, marking the corresponding test process as a trigger process; if not, marking the corresponding test process as an analysis process.

3. The electronic component fault prediction system based on electronic measurement signal processing according to claim 2, characterized in that: The specific process of risk analysis of the analysis process includes: obtaining the risk coefficient FX of the analysis period through the numerical difference between the fault threshold corresponding to each performance parameter and the performance value in the analysis period; obtaining the risk threshold FXmin through the database, and comparing the risk coefficient FX with the risk threshold FXmin: if the risk coefficient FX is less than the risk threshold FXmin, the corresponding test process is marked as a trigger process; if the risk coefficient FX is greater than or equal to the risk threshold FXmin, the corresponding test process is marked as a false alarm process.

4. The electronic component fault prediction system based on electronic measurement signal processing according to claim 3, characterized in that: The specific process of determining whether the warning standard of the performance parameter meets the requirements includes: obtaining the false alarm threshold through the database, and comparing the false alarm coefficient with the false alarm threshold: if the false alarm coefficient is less than the false alarm threshold, it is determined that the warning standard of the corresponding performance parameter meets the requirements, and a control analysis signal is generated and sent to the control analysis module; if the false alarm coefficient is greater than or equal to the false alarm threshold, it is determined that the warning standard of the corresponding performance parameter does not meet the requirements, and the warning threshold of the performance parameter is numerically optimized.

5. The electronic component fault prediction system based on electronic measurement signal processing according to claim 4, characterized in that: The specific process of numerically optimizing the warning threshold of the performance parameter includes: obtaining the new warning value YJnew through the formula YJnew=YJ+c1×(BJ-YJ), wherein YJ and BJ are the values ​​of the warning threshold and the alarm threshold of the corresponding performance parameter respectively, c1 is the proportional coefficient, and 1.05≤c1≤1.15, the new warning range is formed by the new warning value YJnew and the alarm threshold, and the new warning range replaces the original warning range.

6. The electronic component fault prediction system based on electronic measurement signal processing according to claim 5, characterized in that: The specific process of the control analysis module performing control analysis on the performance parameters of electronic components includes: obtaining the numerical value of the control parameter corresponding to the performance parameter when the performance parameter is used as the extraction parameter and marking it as the control value, forming a control set of performance parameters from the control values ​​corresponding to all false alarm processes when the performance parameter is used as the extraction parameter, performing feature extraction analysis on the control set and obtaining a false alarm control range; forming a trigger set of performance parameters from the control values ​​corresponding to all trigger processes when the performance parameter is used as the extraction parameter, performing feature extraction analysis on the trigger set in the same acquisition method as the false alarm control range and obtaining a trigger control range, comparing and analyzing the false alarm control range with the trigger control range: marking the repeated intervals of the false alarm control range and the trigger control range as feature intervals, and segmenting and eliminating the feature intervals from the false alarm control range.

7. The electronic component fault prediction system based on electronic measurement signal processing according to claim 6, characterized in that: The specific process of feature extraction and analysis on the control set includes: performing variance calculation on the control set to obtain a false alarm feature coefficient, obtaining a false alarm feature threshold through a database, and comparing the false alarm feature coefficient with the false alarm feature threshold: if the false alarm feature coefficient is less than the false alarm feature threshold, it is determined that the retained elements in the control set have uniform characteristics, and the maximum and minimum values ​​of the retained elements in the control set constitute the false alarm control range of the performance parameter; if the false alarm feature coefficient is greater than or equal to the false alarm feature threshold, the maximum element and the minimum element in the control set are eliminated, and then the false alarm feature coefficient is recalculated, and so on, until the false alarm feature coefficient is less than the false alarm feature threshold.

8. The electronic component fault prediction system based on electronic measurement signal processing according to claim 7, characterized in that: After completing performance testing, standard optimization and control analysis, when any performance value of the test object reaches the corresponding warning threshold, the value of the control parameter of the corresponding performance parameter and the false alarm control range are retrieved to determine whether the value of the control parameter is within the false alarm control range: if so, no processing is performed; if not, a fault warning signal is generated and sent to the mobile phone terminal of the administrator.

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