CN115455089A - Performance evaluation method and system of passive component and storage medium - Google Patents
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Abstract
The invention discloses a performance evaluation method, a system and a storage medium of a passive component, comprising the following steps: acquiring basic information of a passive component to be tested, determining a performance test index, and configuring a test scene through the performance test index; acquiring environmental information required by testing in a test scene, analyzing the environmental information to generate multidimensional environmental stress data, and correcting a test error caused by environmental change; the obtained test data after error correction is compared with the standard of each performance test index, a performance evaluation model of the passive component is constructed, a performance evaluation result of the passive component to be tested is obtained, and label information is set according to the performance evaluation result; and constructing a performance evaluation test database of the passive component, and performing historical data playback of the same passive component and standard adjustment of each performance index of the passive component. The invention detects, analyzes and evaluates the performance index of the passive component by constructing a multidimensional space environment, improves the system testing efficiency, and supports the design research and development, production and test verification of the passive component.
Description
Technical Field
The present invention relates to the field of performance testing and evaluating technologies, and in particular, to a method, a system, and a storage medium for evaluating performance of a passive component.
Background
Microwave passive components are indispensable important components in microwave circuits and systems, have very wide application in wireless communication systems, and with the rise and the gradual popularization of fifth-generation mobile communication, the development of microwave passive components also gets more and more attention. Therefore, the research aiming at the high-performance passive component has quite important scientific research significance and practical application value for the development of the modern wireless communication system.
The passive component is a large class of important components in electronic information products, and forms a core part of a circuit together with the active component, thereby being the basis of various electronic information products. Since passive components are burdened with many design constraints and performance specifications, different passive components have different requirements for materials and design performance depending on the power requirements of the application. For example, in high power telecommunications and military radar jamming applications, high performance levels are required as well as extremely high power levels, and therefore specialized component and performance test evaluation techniques must be used to meet these extreme application requirements. The index requirement of satisfying inherent characteristic test among the present performance test must carry out manual debugging, and the work load greatly increased who brings the production from this, in addition when examining passive device, easily receive the influence of external test environment condition, and connect poor stability. In order to satisfy the high performance test of the passive component without reducing the test efficiency, a high-efficiency passive component performance test system is urgently needed.
Disclosure of Invention
In order to solve the above technical problem, the present invention provides a method, a system and a storage medium for evaluating performance of a passive component.
The invention provides a performance evaluation method of a passive component, which comprises the following steps:
acquiring basic information of a passive component to be tested, determining a performance test index according to the basic information, and configuring a test scene through the performance test index;
acquiring environmental information required by testing in a testing scene, analyzing the environmental information required by testing to generate multi-dimensional environmental stress data, and correcting a testing error caused by environmental change;
obtaining the test data after error correction, constructing a performance evaluation model of the passive component, comparing the test data with the standard of each performance test index to obtain the performance evaluation result of the passive component to be tested, and setting label information according to the performance evaluation result;
and constructing a performance evaluation test database of the passive component, playing back historical data of the passive component to be tested according to the database, and performing standard adjustment on each performance test index of the passive component through comparison.
In the scheme, basic information of a passive component to be tested is obtained, a performance test index is determined according to the basic information, and a test scene is configured through the performance test index, and the method specifically comprises the following steps:
extracting keywords through basic information of the passive component to be tested, classifying the keywords according to preset classification conditions to obtain category information of the passive component, and obtaining a corresponding performance test index according to the category information;
reading a performance test standard according to the performance test index, initializing a test resource through the performance test standard, and configuring a test scene according to the test resource;
acquiring application conditions of a passive component to be tested, extracting application environment information in the application conditions, and comparing extreme values of the application environment information with guiding working environment information of the passive component to be tested;
acquiring a change interval of the multi-dimensional environmental information in the test scene according to the comparison result, and reading environmental data in the change interval of the multi-dimensional environmental information to configure the test scene;
and segmenting the multi-dimensional environment information change interval, and respectively setting corresponding index thresholds of each evaluation index for the segmented multi-dimensional environment information change interval according to the performance test standard of the passive component to be tested.
In this scheme, carry out analysis to the required environmental information of test and generate multidimensional environmental stress data to revise the test error that environmental change leads to, specifically do:
generating multi-dimensional environmental stress data of the passive component at the current moment according to the required environmental information, and generating a test environment sequence;
executing a test environment condition in a test scene according to the test environment sequence, judging whether the test environment condition meets corresponding environment data in a multi-dimensional information change interval, if not, performing environment compensation on the test environment condition, and if so, triggering a test link;
acquiring a time stamp of testing environment change in the environment change of a testing link of the passive component to be tested, acquiring a time difference according to the environment change starting time stamp and the environment change finishing time stamp, and reading a corresponding testing data time sequence through the time difference;
labeling the test data time sequence according to the test type, acquiring an environmental error source of the performance test of the passive component to be tested through the test type label, and extracting a compensation optimization relation between environmental factors and errors in the environmental error source;
and correcting the test data time sequence corresponding to the acquired time difference through the compensation optimization relation.
In this scheme, obtaining the test data after error correction specifically includes:
setting a test channel according to the quantity information of the performance test indexes of the passive component to be tested, establishing a switch matrix through the test channel, and performing multi-port information and management of multi-port signals according to the switch matrix;
acquiring multi-port test data, and correcting errors according to an error compensation optimization relation matched with a test channel in advance;
extracting the distribution characteristics of the corrected test numbers of each channel, and performing similarity calculation with historical test data of the passive components of the same type in the performance evaluation database under the same test environment condition;
and if the similarity of the distribution characteristics is smaller than a preset similarity threshold, the test data is proved to be in accordance with a preset standard, and the performance evaluation of the passive component to be tested is carried out.
In the scheme, a performance evaluation model of the passive component is constructed, and the performance evaluation result of the passive component to be tested is obtained by comparing the test data with the standard of each performance test index, and the method specifically comprises the following steps:
generating a performance test vector of the passive component to be tested according to the test data after error correction, and reading standard test data of different performance test indexes from performance test standards corresponding to the test environment condition of the current timestamp under the performance test indexes of the passive component to be tested to construct a standard performance matrix;
learning based on a standard performance matrix to construct a performance evaluation model of the passive component, and inputting a performance test vector of the passive component to be tested into the performance evaluation model;
performing comparison and weighting calculation on the performance test vector and a standard performance matrix to obtain a performance evaluation vector of the passive component to be tested, calculating residual values of the evaluation vector and the performance test vector, and judging whether the performance of the passive component to be tested reaches the performance standard of the current test environment condition or not according to the residual values;
acquiring a performance evaluation result of the passive component to be tested according to the judgment result of each timestamp in the testing link;
the expression of the performance evaluation model specifically includes:
wherein,
a performance evaluation vector representing the passive component under test,
a standard performance matrix is represented that represents,
representation matrixThe operation of transposition is carried out,
the expression of the euclidean distance operation,
representing performance test vectors.
In this scheme, the performance evaluation test database of passive subassembly is found, carries out the historical data playback of the passive subassembly that awaits measuring according to the database to carry out the standard adjustment of each performance test index of passive subassembly through the contrast, specifically do:
after the passive component to be tested completes the preset test flow, matching the test data with the test environment condition, obtaining a performance evaluation result according to the performance test index, and storing the performance evaluation result into a performance evaluation test database;
analyzing the product performance change of the passive components to be tested of the same type, generating a oscillogram according to the product performance change, comparing the amplitude in the oscillogram with the test data corresponding to the time stamp, judging the accuracy of data playback, and realizing the visual processing of the product performance change;
acquiring a test data set of each performance test index of the same type of passive components within preset time, selecting a target performance test index and a corresponding test data subset, and acquiring the mean square deviation of each test data in the test data subset and the threshold standard of the target performance test index;
and judging whether the mean square deviation is greater than a deviation threshold value, if so, adjusting the threshold value standard of the target performance test index according to the test data average value in the test data subset.
The second aspect of the present invention also provides a performance evaluation system for a passive component, the system including: a memory and a processor, wherein the memory includes a program of a method for evaluating performance of a passive component, and the program of the method for evaluating performance of a passive component implements the following steps when executed by the processor:
acquiring basic information of a passive component to be tested, determining a performance test index according to the basic information, and configuring a test scene through the performance test index;
acquiring environmental information required by testing in a testing scene, analyzing the environmental information required by testing to generate multi-dimensional environmental stress data, and correcting a testing error caused by environmental change;
obtaining the test data after error correction, constructing a performance evaluation model of the passive component, comparing the test data with the standard of each performance test index to obtain the performance evaluation result of the passive component to be tested, and setting label information according to the performance evaluation result;
and constructing a performance evaluation test database of the passive component, playing back historical data of the passive component to be tested according to the database, and performing standard adjustment on each performance test index of the passive component through comparison.
The third aspect of the present invention also provides a computer-readable storage medium, which includes a program of a method for evaluating performance of a passive component, and when the program of the method for evaluating performance of a passive component is executed by a processor, the method for evaluating performance of a passive component implements the steps of the method for evaluating performance of a passive component as described in any one of the above.
The invention discloses a performance evaluation method, a system and a storage medium of a passive component, comprising the following steps: acquiring basic information of a passive component to be tested, determining a performance test index, and configuring a test scene through the performance test index; acquiring environmental information required by testing in a test scene, analyzing the environmental information to generate multidimensional environmental stress data, and correcting a test error caused by environmental change; the obtained test data after error correction is compared with the standard of each performance test index, a performance evaluation system of the passive component is constructed, a performance evaluation result of the passive component to be tested is obtained, and label information is set according to the performance evaluation result; and constructing a performance evaluation test database of the passive component, and performing historical data playback of the same passive component and standard adjustment of each performance index of the passive component. The invention detects, analyzes and evaluates the performance index of the passive component by constructing a multidimensional space environment, improves the system testing efficiency, and supports the design research and development, production and test verification of the passive component.
Drawings
FIG. 1 shows a flow diagram of a method of performance evaluation of a passive component of the present invention;
FIG. 2 is a flow chart illustrating a method of correcting test errors based on multi-dimensional environmental stress data in accordance with the present invention;
FIG. 3 illustrates a flow diagram of a method of performance evaluation by a performance evaluation model of passive components in accordance with the present invention;
fig. 4 shows a block diagram of a performance evaluation system of a passive component of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a flow chart of a method for evaluating the performance of a passive component according to the invention.
As shown in fig. 1, a first aspect of the present invention provides a performance evaluation method for a passive component, including:
s102, acquiring basic information of a passive component to be tested, determining a performance test index according to the basic information, and configuring a test scene through the performance test index;
s104, acquiring environment information required by testing in a testing scene, analyzing the environment information required by the testing to generate multi-dimensional environmental stress data, and correcting a testing error caused by environmental change;
s106, obtaining the test data after error correction, constructing a performance evaluation model of the passive component, comparing the test data with the standard of each performance test index to obtain a performance evaluation result of the passive component to be tested, and setting label information according to the performance evaluation result;
and S108, constructing a performance evaluation test database of the passive component, replaying historical data of the passive component to be tested according to the database, and performing standard adjustment on each performance test index of the passive component through comparison.
It should be noted that the passive components include multiplexers, directional couplers, circulators, filters, microwave switch components, microwave radio frequency cables, and the like, and the keywords are extracted from the basic information of the passive components to be tested, and are classified according to preset classification conditions according to the keywords, so as to obtain the category information of the passive components, and obtain the corresponding performance test indexes according to the category information; reading a performance test standard according to a performance test index, initializing a test resource through the performance test standard, configuring a test scene according to the test resource, and automatically completing test data acquisition and storage through the test scene in the test processes of temperature circulation, thermal vacuum, high-temperature aging and the like of the passive component; the test scene is flexibly configured according to different application scenes, wherein system hardware comprises a main control computer, a general test instrument (general test instrument equipment containing multi-parameter test basic technical capability, such as a vector network analyzer), a switch interface device (such as a series switch matrix), special equipment (such as a microwave switch special controller and a real-time calibration module) and the like;
acquiring application conditions of a passive component to be tested, extracting application environment information in the application conditions, and comparing extreme values of the application environment information with guiding working environment information of the passive component to be tested; acquiring a change interval of the multi-dimensional environmental information in the test scene according to the comparison result, and reading environmental data in the change interval of the multi-dimensional environmental information to configure the test scene; and segmenting the multi-dimensional environment information change interval, and respectively setting corresponding index thresholds of each evaluation index for the segmented multi-dimensional environment information change interval according to the performance test standard of the passive component to be tested.
FIG. 2 is a flow chart illustrating a method for correcting test errors based on multi-dimensional environmental stress data in accordance with the present invention.
According to the embodiment of the invention, the environmental information required by the test is analyzed to generate the multidimensional environmental stress data, and the test error caused by the environmental change is corrected, which specifically comprises the following steps:
s202, generating multi-dimensional environmental stress data of the passive component at the current moment according to the required environmental information, and generating a test environment sequence;
s204, executing a test environment condition in a test scene according to the test environment sequence, judging whether the test environment condition meets corresponding environment data in a multi-dimensional information change interval, if not, performing environment compensation on the test environment condition, and if so, triggering a test link;
s206, acquiring a time stamp of the test environment change in the environment change of the test link of the passive component to be tested, acquiring a time difference according to the environment change starting time stamp and the environment change finishing time stamp, and reading a corresponding test data time sequence according to the time difference;
s208, labeling the test data time sequence according to the test type, acquiring an environmental error source of the performance test of the passive component to be tested through the test type label, and extracting a compensation optimization relation between environmental factors and errors in the environmental error source;
and S210, correcting the test data time sequence corresponding to the acquired time difference through the compensation optimization relation.
It should be noted that, the obtaining of the test data after error correction specifically includes: setting a test channel according to the quantity information of the performance test indexes of the passive component to be tested, establishing a switch matrix through the test channel, and performing multi-port information and management of multi-port signals according to the switch matrix; acquiring multi-port test data, and correcting errors according to an error compensation optimization relation matched with a test channel in advance; extracting the distribution characteristics of the corrected test numbers of each channel, and performing similarity calculation with historical test data of the passive components of the same type in the performance evaluation database under the same test environment condition; and if the similarity of the distribution characteristics is smaller than a preset similarity threshold, the test data is proved to be in accordance with a preset standard, and the performance evaluation of the passive component to be tested is carried out.
FIG. 3 shows a flow chart of a method for performance evaluation by a performance evaluation model of a passive component according to the present invention.
According to the embodiment of the invention, a performance evaluation model of the passive component is constructed, and the performance evaluation result of the passive component to be tested is obtained by comparing the test data with the standard of each performance test index, which specifically comprises the following steps:
s302, generating a performance test vector of the passive component to be tested according to the test data after error correction, and reading standard test data of different performance test indexes from the performance test standard corresponding to the test environment condition of the current timestamp under the performance test indexes of the passive component to be tested to construct a standard performance matrix;
s304, learning based on the standard performance matrix to construct a performance evaluation model of the passive component, and inputting a performance test vector of the passive component to be tested into the performance evaluation model;
s306, comparing the performance test vector with the standard performance matrix to obtain a performance evaluation vector of the passive component to be tested through weighted calculation, calculating residual values of the evaluation vector and the performance test vector, and judging whether the performance of the passive component to be tested reaches the performance standard of the current test environment condition or not according to the residual values;
and S308, acquiring a performance evaluation result of the passive component to be tested according to the judgment result of each timestamp in the testing link.
It should be noted that, the test data under the current test environment condition is selected to generate the performance test vector
Reading standard test data of different performance test indexes from the performance test standard corresponding to the test environment condition of the current timestamp under the performance test indexes of the passive component to be tested to construct a standard performance matrix
Each column represents the test state of different performance test indexes at the same time, each row represents the test state of the same performance test index at different times, and the expression of the performance evaluation model specifically comprises the following steps:
wherein,
a performance evaluation vector representing the passive component under test,
a standard performance matrix is represented that represents,
a matrix transpose is represented by a matrix transpose,
the expression of the euclidean distance operation,
representing a performance test vector;
obtaining a weight vector by minimizing the residual calculation between the performance evaluation vector and the performance evaluation vector, and simultaneously performing operation optimization by using Euclidean distance operation to enlarge the application range; the performance test vector of the passive component to be tested is in a standard performance space represented by the standard performance matrix, the Euclidean distance between the performance test vector and the standard performance space is close, the weight vector is smaller when the performance evaluation model is calculated, the performance evaluation vector and the performance test vector of the passive component to be tested are basically the same, and the representation performance meets the preset standard; when the performance of the passive component to be tested is abnormal, the performance test vector deviates from the standard performance space represented by the standard performance matrix, the Euclidean distance between the performance test vector and the standard performance space is increased, the residual error is increased, and the performance condition of the passive component to be tested is evaluated according to the residual error.
It should be noted that, after the passive component to be tested completes the preset test flow, the test data is matched with the test environment conditions, the performance evaluation result is obtained according to the performance test index, and the performance evaluation result is stored in the performance evaluation test database; analyzing the product performance change of the passive components to be tested of the same type, generating a oscillogram according to the product performance change, comparing the amplitude in the oscillogram with the test data corresponding to the time stamp, judging the accuracy of data playback, and realizing the visual processing of the product performance change; acquiring a test data set of each performance test index of the same type of passive components within preset time, selecting a target performance test index and a corresponding test data subset, and acquiring the mean square deviation of each test data in the test data subset and the threshold standard of the target performance test index; and judging whether the mean square deviation is greater than a deviation threshold value, if so, adjusting the threshold value standard of the target performance test index according to the test data average value in the test data subset.
According to the embodiment of the invention, the passive components to be tested are classified according to the performance evaluation result, and the method specifically comprises the following steps:
acquiring a performance evaluation result of the passive component to be tested, setting a grading system according to the application condition of the passive component to be tested, and primarily screening the passive component to be tested according to the performance evaluation result;
marking the passive components which do not meet the performance threshold corresponding to the application condition, generating a grading result by the marked passive components through a grading system, and setting corresponding performance grade labels;
establishing data retrieval in the current service demand information through the performance level tags, generating retrieval tags according to the types of any performance level tag and any passive component, and acquiring the service demand information with the similarity greater than a preset similarity standard with the retrieval tags from the current service demand information;
matching the passive component corresponding to the performance level label in the retrieval label with the retrieved service requirement information;
if the current business data does not have the business requirement information meeting the similarity standard, the storage position under the performance grade label is temporarily suspended, and the prior matching is carried out when the corresponding business requirement information exists.
Fig. 4 shows a block diagram of a performance evaluation system of a passive component of the present invention.
The second aspect of the present invention also provides a performance evaluation system 4 for passive components, the system comprising: a memory 41 and a processor 42, wherein the memory includes a program for a method of evaluating performance of a passive component, and the program for a method of evaluating performance of a passive component implements the following steps when executed by the processor:
acquiring basic information of a passive component to be tested, determining a performance test index according to the basic information, and configuring a test scene through the performance test index;
acquiring environmental information required by testing in a testing scene, analyzing the environmental information required by the testing to generate multi-dimensional environmental stress data, and correcting a testing error caused by environmental change;
acquiring test data after error correction, constructing a performance evaluation model of the passive component, comparing the test data with standards of various performance test indexes to acquire a performance evaluation result of the passive component to be tested, and setting label information according to the performance evaluation result;
and constructing a performance evaluation test database of the passive component, playing back historical data of the passive component to be tested according to the database, and performing standard adjustment on each performance test index of the passive component through comparison.
It should be noted that the passive components include multiplexers, directional couplers, circulators, filters, microwave switch components, microwave radio frequency cables, and the like, and the keywords are extracted from the basic information of the passive components to be tested, and are classified according to preset classification conditions according to the keywords, so as to obtain the category information of the passive components, and obtain the corresponding performance test indexes according to the category information; reading a performance test standard according to a performance test index, initializing a test resource through the performance test standard, configuring a test scene according to the test resource, and automatically completing test data acquisition and storage through the test scene in the test processes of temperature circulation, thermal vacuum, high-temperature aging and the like of the passive component; the test scene is flexibly configured according to different application scenes, wherein system hardware comprises a main control computer, a universal test instrument (universal test instrument equipment containing multi-parameter test basic technical capability, such as a vector network analyzer), a switch interface device (such as a series switch matrix), special equipment (such as a microwave switch special controller and a real-time calibration module) and the like;
acquiring application conditions of a passive component to be tested, extracting application environment information in the application conditions, and comparing extreme values of the application environment information with guiding working environment information of the passive component to be tested; acquiring a change interval of the multi-dimensional environmental information in the test scene according to the comparison result, and reading environmental data in the change interval of the multi-dimensional environmental information to configure the test scene; and segmenting the multi-dimensional environment information change interval, and respectively setting corresponding index thresholds of each evaluation index for the segmented multi-dimensional environment information change interval according to the performance test standard of the passive component to be tested.
According to the embodiment of the invention, the environmental information required by the test is analyzed to generate the multidimensional environmental stress data, and the test error caused by the environmental change is corrected, which specifically comprises the following steps:
generating multi-dimensional environmental stress data of the passive component at the current moment according to the required environmental information, and generating a test environment sequence;
executing a test environment condition in a test scene according to the test environment sequence, judging whether the test environment condition meets corresponding environment data in a multi-dimensional information change interval, if not, performing environment compensation on the test environment condition, and if so, triggering a test link;
acquiring a time stamp of testing environment change in the environment change of a testing link of a passive component to be tested, acquiring a time difference according to the environment change starting time stamp and the environment change finishing time stamp, and reading a corresponding testing data time sequence through the time difference;
labeling the test data time sequence according to the test type, acquiring an environmental error source of the performance test of the passive component to be tested through the test type label, and extracting a compensation optimization relation between environmental factors and errors in the environmental error source;
and correcting the test data time sequence corresponding to the acquired time difference through the compensation optimization relation.
It should be noted that, the obtaining of the test data after error correction specifically includes: setting a test channel according to the quantity information of the performance test indexes of the passive component to be tested, establishing a switch matrix through the test channel, and performing multi-port information and management of multi-port signals according to the switch matrix; acquiring multi-port test data, and correcting errors according to an error compensation optimization relation matched with a test channel in advance; extracting the distribution characteristics of the corrected test numbers of each channel, and performing similarity calculation with historical test data of the passive components of the same type in the performance evaluation database under the same test environment condition; and if the similarity of the distribution characteristics is smaller than a preset similarity threshold, the test data is proved to be in accordance with a preset standard, and the performance evaluation of the passive component to be tested is carried out.
According to the embodiment of the invention, a performance evaluation model of the passive component is constructed, and the performance evaluation result of the passive component to be tested is obtained by comparing the test data with the standard of each performance test index, which specifically comprises the following steps:
generating a performance test vector of the passive component to be tested according to the test data after error correction, and reading standard test data of different performance test indexes from performance test standards corresponding to the test environment conditions of the current timestamp under the performance test indexes of the passive component to be tested to construct a standard performance matrix;
learning based on a standard performance matrix to construct a performance evaluation model of the passive component, and inputting a performance test vector of the passive component to be tested into the performance evaluation model;
performing comparison and weighting calculation on the performance test vector and a standard performance matrix to obtain a performance evaluation vector of the passive component to be tested, calculating residual values of the evaluation vector and the performance test vector, and judging whether the performance of the passive component to be tested reaches the performance standard of the current test environment condition or not according to the residual values;
and acquiring a performance evaluation result of the passive component to be tested according to the judgment result of each timestamp in the testing link.
It should be noted that, the test data under the current test environment condition is selected to generate the performance test vector
Reading different performance tests from the performance test standard corresponding to the test environment condition of the current timestamp under the performance test index of the passive component to be testedStandard performance matrix is constructed by standard test data of test indexes
Each column represents the test state of different performance test indexes at the same time, each row represents the test state of the same performance test index at different times, and the expression of the performance evaluation model specifically comprises the following steps:
wherein,
a performance evaluation vector representing the passive component under test,
a standard performance matrix is represented that represents,
the transpose of the matrix is represented,
the expression of the euclidean distance operation,
representing a performance test vector;
obtaining a weight vector by minimizing the residual calculation between the performance evaluation vector and the performance evaluation vector, and simultaneously performing operation optimization by using Euclidean distance operation to enlarge the application range; the performance test vector of the passive component to be tested is in a standard performance space represented by the standard performance matrix, the Euclidean distance between the performance test vector and the standard performance space is close, the weight vector is smaller when the performance evaluation model is calculated, the performance evaluation vector and the performance test vector of the passive component to be tested are basically the same, and the performance is expressed to accord with the preset standard; when the performance of the passive component to be tested is abnormal, the performance test vector deviates from the standard performance space represented by the standard performance matrix, the Euclidean distance between the performance test vector and the standard performance space is increased, the residual error is increased, and the performance condition of the passive component to be tested is evaluated according to the residual error.
After the passive component to be tested completes the preset test process, matching the test data with the test environment conditions, obtaining a performance evaluation result according to the performance test index, and storing the performance evaluation result into a performance evaluation test database; analyzing the product performance change of the passive components to be tested of the same type, generating a oscillogram according to the product performance change, comparing the amplitude in the oscillogram with the test data corresponding to the time stamp, judging the accuracy of data playback, and realizing the visual processing of the product performance change; acquiring a test data set of each performance test index of the same type of passive components within preset time, selecting a target performance test index and a corresponding test data subset, and acquiring the mean square deviation of each test data in the test data subset and the threshold standard of the target performance test index; and judging whether the mean square deviation is greater than a deviation threshold value, if so, adjusting the threshold value standard of the target performance test index according to the test data average value in the test data subset.
The third aspect of the present invention also provides a computer-readable storage medium, which includes a program of a method for evaluating performance of a passive component, and when the program of the method for evaluating performance of a passive component is executed by a processor, the method for evaluating performance of a passive component implements the steps of the method for evaluating performance of a passive component as described in any one of the above.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only one logical function division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps of implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer-readable storage medium, and when executed, executes the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method of evaluating the performance of a passive component, comprising the steps of:
acquiring basic information of a passive component to be tested, determining a performance test index according to the basic information, and configuring a test scene through the performance test index;
acquiring environmental information required by testing in a testing scene, analyzing the environmental information required by the testing to generate multi-dimensional environmental stress data, and correcting a testing error caused by environmental change;
obtaining the test data after error correction, constructing a performance evaluation model of the passive component, comparing the test data with the standard of each performance test index to obtain the performance evaluation result of the passive component to be tested, and setting label information according to the performance evaluation result;
and constructing a performance evaluation test database of the passive component, playing back historical data of the passive component to be tested according to the database, and performing standard adjustment on each performance test index of the passive component through comparison.
2. The method for evaluating the performance of the passive component according to claim 1, wherein basic information of the passive component to be tested is acquired, a performance test index is determined according to the basic information, and a test scenario is configured according to the performance test index, specifically:
extracting keywords through basic information of the passive component to be tested, classifying the keywords according to preset classification conditions to obtain category information of the passive component, and obtaining a corresponding performance test index according to the category information;
reading a performance test standard according to the performance test index, initializing a test resource through the performance test standard, and configuring a test scene according to the test resource;
acquiring application conditions of a passive component to be tested, extracting application environment information in the application conditions, and comparing extreme values of the application environment information with guiding working environment information of the passive component to be tested;
acquiring a change interval of the multi-dimensional environmental information in the test scene according to the comparison result, and reading environmental data in the change interval of the multi-dimensional environmental information to configure the test scene;
and segmenting the multi-dimensional environment information change interval, and respectively setting corresponding index thresholds of all evaluation indexes in the segmented multi-dimensional environment information change interval according to the performance test standard of the passive component to be tested.
3. The performance evaluation method of the passive component according to claim 1, wherein the environmental information required for the test is analyzed to generate multidimensional environmental stress data, and test errors caused by environmental changes are corrected, specifically:
generating multi-dimensional environmental stress data of the passive component at the current moment according to the required environmental information, and generating a test environment sequence;
executing a test environment condition in a test scene according to the test environment sequence, judging whether the test environment condition meets corresponding environment data in a multi-dimensional information change interval, if not, performing environment compensation on the test environment condition, and if so, triggering a test link;
acquiring a time stamp of testing environment change in the environment change of a testing link of a passive component to be tested, acquiring a time difference according to the environment change starting time stamp and the environment change finishing time stamp, and reading a corresponding testing data time sequence through the time difference;
labeling the test data time sequence according to the test type, acquiring an environmental error source of the performance test of the passive component to be tested through the test type label, and extracting a compensation optimization relation between environmental factors and errors in the environmental error source;
and correcting the test data time sequence corresponding to the acquired time difference through the compensation optimization relation.
4. The method for evaluating the performance of a passive component according to claim 1, wherein the obtaining of the error-corrected test data specifically comprises:
setting a test channel according to the quantity information of the performance test indexes of the passive component to be tested, establishing a switch matrix through the test channel, and performing multi-port information and management of multi-port signals according to the switch matrix;
acquiring multi-port test data, and correcting errors according to an error compensation optimization relation matched with a test channel in advance;
extracting the distribution characteristics of the corrected test numbers of each channel, and performing similarity calculation with historical test data of the passive components of the same type in the performance evaluation database under the same test environment condition;
and if the similarity of the distribution characteristics is smaller than a preset similarity threshold, the test data is proved to be in accordance with a preset standard, and the performance evaluation of the passive component to be tested is carried out.
5. The method for evaluating the performance of the passive component according to claim 1, wherein a performance evaluation model of the passive component is constructed, and a performance evaluation result of the passive component to be tested is obtained by comparing test data with standards of various performance test indexes, and specifically the method comprises the following steps:
generating a performance test vector of the passive component to be tested according to the test data after error correction, and reading standard test data of different performance test indexes from performance test standards corresponding to the test environment conditions of the current timestamp under the performance test indexes of the passive component to be tested to construct a standard performance matrix;
learning based on a standard performance matrix to construct a performance evaluation model of the passive component, and inputting a performance test vector of the passive component to be tested into the performance evaluation model;
performing comparison and weighting calculation on the performance test vector and a standard performance matrix to obtain a performance evaluation vector of the passive component to be tested, calculating residual values of the evaluation vector and the performance test vector, and judging whether the performance of the passive component to be tested reaches the performance standard of the current test environment condition or not according to the residual values;
acquiring a performance evaluation result of the passive component to be tested according to the judgment result of each timestamp in the testing link;
the expression of the performance evaluation model specifically includes:
wherein,
a performance evaluation vector representing the passive component under test,
a standard performance matrix is represented that represents,
a matrix transpose is represented by a matrix transpose,
the expression of the euclidean distance operation,
representing performance test vectors.
6. The performance evaluation method of the passive component according to claim 1, wherein a performance evaluation test database of the passive component is constructed, historical data playback of the passive component to be tested is performed according to the database, and standard adjustment of each performance test index of the passive component is performed through comparison, specifically:
after the passive component to be tested completes the preset test flow, matching the test data with the test environment condition, obtaining a performance evaluation result according to the performance test index, and storing the performance evaluation result into a performance evaluation test database;
analyzing the product performance change of the passive components to be tested of the same type, generating a oscillogram according to the product performance change, comparing the amplitude in the oscillogram with the test data corresponding to the time stamp, judging the accuracy of data playback, and realizing the visual processing of the product performance change;
acquiring a test data set of each performance test index of the same type of passive components within preset time, selecting a target performance test index and a corresponding test data subset, and acquiring the mean square deviation of each test data in the test data subset and the threshold standard of the target performance test index;
and judging whether the mean square deviation is greater than a deviation threshold value, if so, adjusting the threshold value standard of the target performance test index according to the test data average value in the test data subset.
7. A performance evaluation system for a passive component, the system comprising: a memory and a processor, wherein the memory includes a program of a method for evaluating performance of a passive component, and the program of the method for evaluating performance of a passive component implements the following steps when executed by the processor:
acquiring basic information of a passive component to be tested, determining a performance test index according to the basic information, and configuring a test scene through the performance test index;
acquiring environmental information required by testing in a testing scene, analyzing the environmental information required by testing to generate multi-dimensional environmental stress data, and correcting a testing error caused by environmental change;
obtaining the test data after error correction, constructing a performance evaluation model of the passive component, and obtaining a performance evaluation result of the passive component to be tested by comparing the test data with the standards of various performance test indexes;
and constructing a performance evaluation test database of the passive component, playing back historical data of the passive component to be tested according to the database, and performing standard adjustment on each performance test index of the passive component through comparison.
8. The performance evaluation system of a passive component according to claim 7, wherein the environmental information required for testing is analyzed to generate multidimensional environmental stress data, and test errors caused by environmental changes are corrected, specifically:
generating multi-dimensional environmental stress data of the passive component at the current moment according to the required environmental information, and generating a test environment sequence;
executing a test environment condition in a test scene according to the test environment sequence, judging whether the test environment condition meets corresponding environment data in a multi-dimensional information change interval, if not, performing environment compensation on the test environment condition, and if so, triggering a test link;
acquiring a time stamp of testing environment change in the environment change of a testing link of the passive component to be tested, acquiring a time difference according to the environment change starting time stamp and the environment change finishing time stamp, and reading a corresponding testing data time sequence through the time difference;
labeling the test data time sequence according to the test type, acquiring an environmental error source of the performance test of the passive component to be tested through the test type label, and extracting a compensation optimization relation between environmental factors and errors in the environmental error source;
and correcting the test data time sequence corresponding to the acquired time difference through the compensation optimization relation.
9. The performance evaluation system of the passive component according to claim 7, wherein a performance evaluation model of the passive component is constructed, and a performance evaluation result of the passive component to be tested is obtained by comparing test data with standards of various performance test indexes, specifically:
generating a performance test vector of the passive component to be tested according to the test data after error correction, and reading standard test data of different performance test indexes from performance test standards corresponding to the test environment conditions of the current timestamp under the performance test indexes of the passive component to be tested to construct a standard performance matrix;
learning based on a standard performance matrix to construct a performance evaluation model of the passive component, and inputting a performance test vector of the passive component to be tested into the performance evaluation model;
performing comparison and weighting calculation on the performance test vector and a standard performance matrix to obtain a performance evaluation vector of the passive component to be tested, calculating residual values of the evaluation vector and the performance test vector, and judging whether the performance of the passive component to be tested reaches the performance standard of the current test environment condition or not according to the residual values;
acquiring a performance evaluation result of the passive component to be tested according to the judgment result of each timestamp in the testing link;
the expression of the performance evaluation model specifically includes:
wherein,
a performance evaluation vector representing the passive component under test,
a standard performance matrix is represented that represents,
the transpose of the matrix is represented,
the expression of the euclidean distance operation,
representing performance test vectors.
10. A computer-readable storage medium characterized by: the computer-readable storage medium includes a program for a method of evaluating performance of a passive component, which when executed by a processor implements the steps of a method of evaluating performance of a passive component as claimed in any one of claims 1 to 6.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116542503A (en) * | 2023-07-07 | 2023-08-04 | 深圳市鑫典金光电科技有限公司 | Performance test distribution method, system and medium based on artificial intelligence |
| CN116609255A (en) * | 2023-07-17 | 2023-08-18 | 张家港市卓华金属科技有限公司 | Weather resistance testing method and system for building paint |
| CN116626574A (en) * | 2023-07-19 | 2023-08-22 | 深圳市华测半导体设备有限公司 | Reliability test method, system and storage medium of signal tester |
| CN117251706A (en) * | 2023-10-07 | 2023-12-19 | 东莞市粤广创照明有限公司 | Performance test method for household lighting equipment |
| CN117473266A (en) * | 2023-11-10 | 2024-01-30 | 广州市德珑电子器件有限公司 | EMI power supply filter safety performance monitoring method, device, medium and equipment |
| CN117651289A (en) * | 2024-01-26 | 2024-03-05 | 中国人民解放军军事科学院系统工程研究院 | Data processing method and device for radio communication equipment test |
| CN118467987A (en) * | 2024-07-10 | 2024-08-09 | 威鹏晟(山东)机械有限公司 | Vacuum pump overall performance evaluation and lifting system and method based on big data |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108363660A (en) * | 2017-01-26 | 2018-08-03 | 华为技术有限公司 | A kind of method of generating test program and device |
| CN110377004A (en) * | 2019-07-12 | 2019-10-25 | 北京祥远通达科技有限公司 | Automobile-used half virtual ECU test macro and its test method |
| US20200158697A1 (en) * | 2018-11-21 | 2020-05-21 | Waters Technologies Ireland Limited | Techniques for evaluating analytical instrument performance |
| CN114461534A (en) * | 2022-03-14 | 2022-05-10 | 广域铭岛数字科技有限公司 | Software performance testing method and system, electronic equipment and readable storage medium |
| CN114595124A (en) * | 2022-05-09 | 2022-06-07 | 北京瑞莱智慧科技有限公司 | Time sequence abnormity detection model evaluation method, related device and storage medium |
-
2022
- 2022-11-09 CN CN202211401546.9A patent/CN115455089B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108363660A (en) * | 2017-01-26 | 2018-08-03 | 华为技术有限公司 | A kind of method of generating test program and device |
| US20200158697A1 (en) * | 2018-11-21 | 2020-05-21 | Waters Technologies Ireland Limited | Techniques for evaluating analytical instrument performance |
| CN110377004A (en) * | 2019-07-12 | 2019-10-25 | 北京祥远通达科技有限公司 | Automobile-used half virtual ECU test macro and its test method |
| CN114461534A (en) * | 2022-03-14 | 2022-05-10 | 广域铭岛数字科技有限公司 | Software performance testing method and system, electronic equipment and readable storage medium |
| CN114595124A (en) * | 2022-05-09 | 2022-06-07 | 北京瑞莱智慧科技有限公司 | Time sequence abnormity detection model evaluation method, related device and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| BAEK, MS ET AL.: "Field Trials and Evaluations of In-Band Digital Radio Technologies: HD Radio and DRM", 《IEEE TRANSACTIONS ON BROADCASTING》 * |
| 谢红卫等: "装备试验评估中的变动统计问题与方法", 《宇航学报》 * |
| 韩治国: "灰色关联分析指标的大学科研评估系统", 《现代电子技术》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116542503A (en) * | 2023-07-07 | 2023-08-04 | 深圳市鑫典金光电科技有限公司 | Performance test distribution method, system and medium based on artificial intelligence |
| CN116542503B (en) * | 2023-07-07 | 2024-02-02 | 深圳市鑫典金光电科技有限公司 | Performance test distribution method, system and medium based on artificial intelligence |
| CN116609255A (en) * | 2023-07-17 | 2023-08-18 | 张家港市卓华金属科技有限公司 | Weather resistance testing method and system for building paint |
| CN116609255B (en) * | 2023-07-17 | 2023-09-22 | 张家港市卓华金属科技有限公司 | Weather resistance testing method and system for building paint |
| CN116626574A (en) * | 2023-07-19 | 2023-08-22 | 深圳市华测半导体设备有限公司 | Reliability test method, system and storage medium of signal tester |
| CN116626574B (en) * | 2023-07-19 | 2023-09-19 | 深圳市华测半导体设备有限公司 | Reliability test method, system and storage medium of signal tester |
| CN117251706A (en) * | 2023-10-07 | 2023-12-19 | 东莞市粤广创照明有限公司 | Performance test method for household lighting equipment |
| CN117473266A (en) * | 2023-11-10 | 2024-01-30 | 广州市德珑电子器件有限公司 | EMI power supply filter safety performance monitoring method, device, medium and equipment |
| CN117473266B (en) * | 2023-11-10 | 2024-05-17 | 广州市德珑电子器件有限公司 | EMI power supply filter safety performance monitoring method, device, medium and equipment |
| CN117651289A (en) * | 2024-01-26 | 2024-03-05 | 中国人民解放军军事科学院系统工程研究院 | Data processing method and device for radio communication equipment test |
| CN117651289B (en) * | 2024-01-26 | 2024-04-05 | 中国人民解放军军事科学院系统工程研究院 | Data processing method and device for radio communication equipment test |
| CN118467987A (en) * | 2024-07-10 | 2024-08-09 | 威鹏晟(山东)机械有限公司 | Vacuum pump overall performance evaluation and lifting system and method based on big data |
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