A management method, equipment and medium based on full performance test equipment

Abstract

A management method, equipment and medium based on full performance test and detection equipment, the method comprising: presetting a number of full performance test and detection equipment roles; identifying a QR code of a tested equipment, obtaining the properties of the tested equipment, and registering an identification code of the tested equipment; calculating a matching score using a device role matching scoring algorithm based on the properties of the tested equipment and the full performance test and detection equipment roles, and performing authorization verification according to the matching score; for a tested equipment that allows authorization, collecting the tested equipment operation data, and using a device operation status evaluation algorithm to calculate an evaluated value of the tested equipment operation status; determining the tested equipment operation status according to the evaluation value; for an abnormal operation status of the tested equipment, using an abnormal equipment intelligent diagnosis algorithm to calculate the deviation of the tested equipment operation data; calculating the full performance test and detection equipment working status score using a device status evaluation algorithm based on the deviation, and switching the full performance test and detection equipment working mode according to the working status.

Description

Technical Field

[0001] The invention relates to a management method, equipment and medium based on full performance test detection equipment, belonging to the field of intelligent management. Background Art

[0002] With the rapid development of science and technology and the continuous progress of the industrial field, the application of full-performance test and inspection equipment is becoming more and more extensive, becoming an important tool to ensure product quality and improve scientific research level. However, the traditional test and inspection equipment management methods have many shortcomings, such as low management efficiency, opaque equipment use, serious data island phenomenon, etc., which can no longer meet the high requirements of modern industry for test and inspection accuracy, efficiency and intelligence level. In this context, the intelligent management method of full-performance test and inspection equipment came into being, aiming to achieve comprehensive, efficient and refined management of test and inspection equipment by introducing advanced information technology and intelligent means.

[0003] Existing technologies such as the Chinese patent with the patent number "CN117376108A" disclose a method and system for intelligent operation and maintenance of IoT devices, which involves the field of intelligent operation and maintenance technology. The method includes: collecting device data to generate pre-processed data; using machine learning algorithms to build an intelligent operation and maintenance model; performing abnormal diagnosis on IoT devices to generate diagnostic results; using the intelligent operation and maintenance model to generate abnormal decisions including automated processing strategies and alarm strategies; performing automated processing on IoT devices according to the automated processing strategies and generating processing logs; generating abnormal alarms according to the alarm strategies to issue alarm notifications and generate alarm records; generating updated data sets according to the processing logs and alarm records and updating the intelligent operation and maintenance model based on them.

[0004] The problems with the above-mentioned existing technologies are that, in the Internet of Things and industrial control systems, device access management is complex and has security issues, and there is a lack of effective device identification and attribute matching mechanisms, which makes the device access process cumbersome and error-prone; the existing equipment operation status assessment methods do not monitor the equipment operation status comprehensively enough and cannot accurately reflect the actual operation status of the equipment; when diagnosing abnormal equipment operation data, the abnormal data identification is not accurate and timely enough, and it is easy to miss or misdetect abnormalities. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention proposes a management method, equipment and medium based on full performance test detection equipment.

[0006] The technical solution of the present invention is as follows:

[0007] On the one hand, the present invention proposes a management method based on full performance test detection equipment, comprising the following specific steps:

[0008] Preset a number of full performance test detection equipment roles, wherein the full performance test detection equipment roles are equipment roles that are allowed to access;

[0009] Identify the QR code of the device under test, obtain the properties of the device under test, and register the identification code of the device under test according to the properties of the device under test;

[0010] Based on the attributes of the device under test and the role of the full performance test device, the device role matching scoring algorithm is used to calculate the matching score, and authorization verification is performed based on the matching score;

[0011] For the authorized devices under test, collect the operating data of the devices under test, use the device operating status evaluation algorithm to calculate the evaluation value of the operating status of the devices under test; determine the operating status of the devices under test according to the evaluation value;

[0012] For abnormal operation status of the equipment under test, the abnormal equipment intelligent diagnosis algorithm is used to calculate the deviation of the operating data of the equipment under test;

[0013] Based on the deviation, the working status score of the full performance test and detection equipment is calculated using the equipment status evaluation algorithm, and the working mode of the full performance test and detection equipment is switched according to the current working status score.

[0014] As a preferred implementation, the specific steps of calculating the matching score by the device role matching scoring algorithm are as follows:

[0015] Full performance test equipment role ;

[0016] Where m represents the number of full performance test equipment roles, represents the jth full performance test equipment role, ;

[0017] Use integer encoding techniques to convert the device under test properties into numeric format:

[0018] Set the device under test properties ;

[0019] Where n is the number of attributes of the device under test, represents the i-th attribute of the device under test, ;

[0020] The calculation formula of the device role matching scoring algorithm is:

[0021] ;

[0022] in, It represents the matching score between the device under test and the jth full performance test device role. ; Represents the summation symbol, which is the weighted sum of all attributes of the device under test; represents the i-th attribute of the device under test; represents the square of the attribute of the i-th device under test; represents the weight of the jth full performance test equipment role on the ith device under test attribute; represents the natural logarithm function; represents a negative exponential function;

[0023] The method to obtain is:

[0024] ;

[0025] in, Indicates Full performance test equipment role During the test, The sensitivity of each DUT attribute, Indicates Full performance test equipment role During the test, The accuracy of each DUT attribute, Indicates Full performance test equipment role During the test, The response time of each property of the device under test, Indicates normalization processing.

[0026] As a preferred implementation, the specific method of the authorization verification is:

[0027] Preset matching score threshold Q;

[0028] Score the matching degree between the device under test and the jth full performance test equipment role Compare with the matching score threshold Q;

[0029] If the matching score between the device under test and the jth full performance test device role is If it is higher than or equal to the matching score threshold Q, the device under test is authorized to access;

[0030] If the matching score between the device under test and the jth full performance test device role is If the match score is lower than the threshold Q, no processing will be performed.

[0031] As a preferred implementation, the specific steps for calculating the evaluation value are:

[0032] Operation data of the equipment under test ;

[0033] Where N represents the number of running data of the device under test, It represents the kth operating data of the device under test collected at time t. The operating data of the device under test includes current, voltage and temperature. ;

[0034] The operating data of the equipment under test is standardized by:

[0035] ;

[0036] in, represents the kth tested equipment operation data collected at time t after standardization; represents the mean value of the operating data of the kth device under test; Represents the standard deviation of the operating data of the kth device under test;

[0037] Obtain standardized operating data of the equipment under test :

[0038] ;

[0039] Based on the standardized operating data of the tested equipment , use the equipment operation status evaluation algorithm to calculate the evaluation value of the operation status of the equipment under test.

[0040] As a preferred implementation, the specific calculation method of the equipment operation status evaluation algorithm is:

[0041] ;

[0042] in, It represents the evaluation value of the operating status of the equipment under test at time t; Represents the weight coefficient of the current time t; represents the summation symbol; Indicates the weight of the kth tested device’s operating data; represents trigonometric functions; Indicates the frequency of periodic changes; Indicates the initial phase of the periodic change; Indicates the historical time arrive Sum the operating data of the equipment under test at all historical time points; Indicates a point in history; Indicates that after standardization The kth measured device operation data collected at the moment; represents the time decay factor; Represents the time decay coefficient.

[0043] As a preferred implementation, the specific calculation method of the abnormal equipment intelligent diagnosis algorithm is:

[0044] ;

[0045] in, It represents the deviation of the kth measured equipment operation data collected at time t; Represents the square root symbol; Represents the square of the time derivative of the operating data of the kth device under test; represents the kth tested equipment operation data collected at time t after standardization; represents the time derivative of the operating data of the kth device under test; Represents the deviation term based on the sine function; sin represents the sine function, capturing the periodic change characteristics; Indicates scale conversion; It represents the difference between the kth tested equipment operation data collected at time t and the historical mean after standardization; Fractional terms representing logarithmic characteristics; A fraction representing a logarithmic characteristic; ln() represents the natural logarithm function.

[0046] As a preferred implementation, the specific calculation method of the device status evaluation algorithm is:

[0047] ;

[0048] in, It represents the working status score of the full performance test equipment at time t; It represents the deviation of the kth measured equipment operation data collected at time t; represents the summation symbol; It represents the natural logarithmic function of the deviation of the kth device under test operating data collected at time t plus one; Represents a negative exponential function, exponential Indicates the load condition of the current working state of the full performance test equipment; Represents the load response sensitivity coefficient.

[0049] As a preferred implementation, the specific method for switching the working mode of the full performance test detection equipment according to the current working status score is:

[0050] Let the threshold range of the normal mode of the full performance test equipment be ;

[0051] like , then the full performance test equipment switches to normal mode;

[0052] like , the full performance test detection equipment switches to enhanced mode to increase detection sensitivity and frequency;

[0053] like , the full performance test equipment switches to protection mode, reduces the sensitivity and frequency of detection, reduces the load of the full performance test equipment, and protects the full performance test equipment from overload damage.

[0054] On the other hand, the present invention further provides an electronic device having a computer program stored thereon, wherein when the computer program is executed by a processor, the management method based on the full performance test detection equipment as described in any embodiment of the present invention is implemented.

[0055] On the other hand, the present invention also provides a computer-readable storage medium for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the management method based on the full performance test detection equipment as described in any embodiment of the present invention.

[0056] The present invention has the following beneficial effects:

[0057] The present invention realizes more refined authority management by presetting the full performance test detection equipment role. The introduction of the equipment role matching scoring algorithm makes the authorization verification process more scientific and objective, improves the accuracy of authorization decisions, and avoids the misallocation of authority caused by human factors. The real-time collection of equipment operation data and the use of the equipment operation status evaluation algorithm to continuously monitor and evaluate the equipment status can timely discover potential abnormal problems of the equipment and improve the predictability and initiative of equipment maintenance. The equipment operation status is accurately judged by the evaluation value, which provides reliable data support for subsequent maintenance and management, and reduces the risk of production interruption caused by equipment failure. For the abnormal operation status of the equipment found, the deviation of the equipment operation data is calculated using the abnormal equipment intelligent diagnosis algorithm, which can quickly locate the cause of the abnormality and improve the efficiency and accuracy of fault diagnosis. Based on the deviation, the equipment status evaluation algorithm is further used to calculate the current working status score, and the equipment working mode is automatically switched accordingly, effectively preventing the abnormal state from further affecting production and ensuring the safety and continuity of production. The entire solution realizes closed-loop management from equipment registration, authorization verification, status monitoring to abnormal handling, greatly improving the automation level and intelligence level of equipment management. By reducing manual intervention, management costs are reduced and management efficiency is improved, allowing enterprises to focus more on the development of core businesses. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1The figure is a flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] It should be understood that the step numbers used in this article are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0061] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0062] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0063] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0064] Embodiment 1:

[0065] See also Figure 1 The present invention proposes a management method based on full performance test detection equipment, including the following specific steps:

[0066] Preset a number of full performance test detection equipment roles, wherein the full performance test detection equipment roles are equipment roles that are allowed to access;

[0067] Identify the QR code of the device under test, obtain the properties of the device under test, and register the identification code of the device under test according to the properties of the device under test;

[0068] Based on the attributes of the device under test and the role of the full performance test device, the device role matching scoring algorithm is used to calculate the matching score, and authorization verification is performed based on the matching score;

[0069] For the authorized devices under test, collect the operating data of the devices under test, use the device operating status evaluation algorithm to calculate the evaluation value of the operating status of the devices under test; determine the operating status of the devices under test according to the evaluation value;

[0070] For abnormal operation status of the equipment under test, the abnormal equipment intelligent diagnosis algorithm is used to calculate the deviation of the operating data of the equipment under test;

[0071] Based on the deviation, the working status score of the full performance test and detection equipment is calculated using the equipment status evaluation algorithm, and the working mode of the full performance test and detection equipment is switched according to the current working status score.

[0072] As a preferred implementation, the specific steps of calculating the matching score by the device role matching scoring algorithm are as follows:

[0073] Full performance test equipment role ;

[0074] Where m represents the number of full performance test equipment roles, represents the jth full performance test equipment role, ;

[0075] Use integer encoding techniques to convert the device under test properties into numeric format:

[0076] Set the device under test properties ;

[0077] Where n is the number of attributes of the device under test, represents the i-th attribute of the device under test, ;

[0078] The calculation formula of the device role matching scoring algorithm is:

[0079] ;

[0080] in, It represents the matching score between the device under test and the jth full performance test device role. ; Represents the summation symbol, which is the weighted sum of all attributes of the device under test; represents the i-th attribute of the device under test; represents the square of the attribute of the i-th device under test; represents the weight of the jth full performance test equipment role on the ith device under test attribute; represents the natural logarithm function; represents a negative exponential function;

[0081] The method to obtain is:

[0082] ;

[0083] in, Indicates Full performance test equipment role During the test, The sensitivity of the property of the device under test is obtained based on the sensor characteristics provided in the full performance test equipment manual and the fluctuation range of the property of the device under test. Indicates Full performance test equipment role During the test, The accuracy of the property of the device under test is Full performance test equipment role Test The error range of the property of the tested device is obtained through the manual of the full performance test equipment. The contribution of the full performance test equipment to the accuracy is measured by the inverse of the error range. Indicates Full performance test equipment role During the test, The response time of the property of the device under test reflects the time required for the full performance test detection equipment role to complete a test and provide results. It is obtained through the full performance test equipment manual. The shorter the response time, the stronger the response capability of the full performance test detection equipment role. Indicates normalization processing.

[0084] The device role matching scoring algorithm enhances the ability to capture the differences between device attributes and attribute weights by combining square and logarithmic operations with exponential operations. The square of the device attribute amplifies the impact of the device attribute on the matching score, the logarithmic function of the attribute weight ensures the moderate change of the attribute weight, and the exponential function adjusts the smoothness of the matching score.

[0085] As a preferred implementation, the specific method of the authorization verification is:

[0086] Preset matching score threshold Q;

[0087] Score the matching degree between the device under test and the jth full performance test equipment role Compare with the matching score threshold Q;

[0088] If the matching score between the device under test and the jth full performance test device role is If it is higher than or equal to the matching score threshold Q, the device under test is authorized to access;

[0089] If the matching score between the device under test and the jth full performance test device role is If the match score is lower than the threshold Q, no processing will be performed.

[0090] By setting the full performance test equipment role, the access process of the tested equipment is simplified, the tedious steps of manual configuration are reduced, and the management efficiency is improved. It ensures that the tested equipment can be authorized to access only when it meets the permission requirements of a specific role, which can effectively prevent unauthorized or non-compliant equipment from accessing and enhance security. In addition, the setting of the full performance test equipment role can effectively allocate the resource requirements of different types of equipment, thereby optimizing resource allocation and improving resource utilization efficiency.

[0091] As a preferred implementation, the specific steps for calculating the evaluation value are:

[0092] Operation data of the equipment under test ;

[0093] Where N represents the number of running data of the device under test, It represents the kth operating data of the device under test collected at time t. The operating data of the device under test includes current, voltage and temperature. ;

[0094] The operating data of the equipment under test is standardized by:

[0095] ;

[0096] in, represents the kth tested equipment operation data collected at time t after standardization; represents the mean value of the operating data of the kth device under test; Represents the standard deviation of the operating data of the kth device under test;

[0097] Obtain standardized operating data of the equipment under test :

[0098] ;

[0099] Based on the standardized operating data of the tested equipment , use the equipment operation status evaluation algorithm to calculate the evaluation value of the operation status of the equipment under test.

[0100] As a preferred implementation, the specific calculation method of the equipment operation status evaluation algorithm is:

[0101] ;

[0102] in, It represents the evaluation value of the operating status of the equipment under test at time t; Represents the weight coefficient of the current time t; represents the summation symbol; Indicates the weight of the kth tested device’s operating data; represents trigonometric functions; Indicates the frequency of periodic changes; Indicates the initial phase of the periodic change; Indicates the historical time arrive Sum the operating data of the equipment under test at all historical time points; Indicates a point in history; Indicates that after standardization The kth measured device operation data collected at the moment; represents the time decay factor; Represents the time decay coefficient.

[0103] The equipment operation status evaluation algorithm standardizes the preprocessed equipment operation data to eliminate the dimensional differences between different parameters, performs weighted processing on the standardized equipment operation data at the current time point, adjusts the importance of different equipment operation data in the equipment operation status evaluation, introduces periodic change factors, and simulates the periodic fluctuations of equipment operation data through trigonometric functions. In addition to the data at the current time point, the influence of historical equipment operation data is also comprehensively considered, and a time attenuation factor is introduced to reasonably weaken the influence of historical equipment operation data far away from the current time point.

[0104] As a preferred implementation, the specific calculation method of the abnormal equipment intelligent diagnosis algorithm is:

[0105] ;

[0106] in, It represents the deviation of the kth measured equipment operation data collected at time t; Represents the square root symbol; Represents the square of the time derivative of the operating data of the kth device under test; represents the kth tested equipment operation data collected at time t after standardization; represents the time derivative of the operating data of the kth device under test; Represents the deviation term based on the sine function; sin represents the sine function, capturing the periodic change characteristics; Indicates scale conversion; It represents the difference between the kth tested equipment operation data collected at time t and the historical mean after standardization; Fractional terms representing logarithmic characteristics; A fraction representing a logarithmic characteristic; ln() represents the natural logarithm function.

[0107] The abnormal equipment intelligent diagnosis algorithm obtains the change speed of the equipment operation data at each time point by differentiating the time series of the equipment operation data, enhances the sensitivity to the change of the equipment operation data, reflects the periodic fluctuation characteristics by calculating the sine transform of the equipment operation data relative to the historical mean, identifies the abnormality of the equipment in the periodic operation, and amplifies the subtle changes of the equipment operation data by calculating the logarithm of the absolute difference between the equipment operation data and the historical mean and performing fractional processing on the logarithm, while weakening the influence of extreme values, thereby improving the robustness of the abnormal equipment intelligent diagnosis.

[0108] As a preferred implementation, the specific calculation method of the device status evaluation algorithm is:

[0109] ;

[0110] in, It represents the working status score of the full performance test equipment at time t; It represents the deviation of the kth measured equipment operation data collected at time t; represents the summation symbol; It represents the natural logarithmic function of the deviation of the kth device under test operating data collected at time t plus one; Represents a negative exponential function, exponential Indicates the load condition of the current working state of the full performance test equipment; Represents the load response sensitivity coefficient.

[0111] With the continuous development of industrial automation and equipment intelligence, the environment faced by full performance test equipment during operation is becoming more and more complex, which is prone to overload or misjudgment, resulting in detection failure. In order to ensure that the full performance test equipment can maintain stable operation in different working environments, the full performance test equipment status evaluation algorithm is used to calculate the current working status score of the test equipment;

[0112] The full-performance test equipment status evaluation algorithm is based on the deviation of the equipment operation data, quantifies the severity of each abnormal equipment operation data, reflects the abnormal degree of the equipment operation data, and directly reflects the working status and load conditions of the full-performance test equipment through logarithmic functions and exponential smoothing processing.

[0113] As a preferred implementation, the specific method for switching the working mode of the full performance test detection equipment according to the current working status score is:

[0114] Let the threshold range of the normal mode of the full performance test equipment be ;

[0115] like , then the full performance test equipment switches to normal mode;

[0116] like , the full performance test detection equipment switches to enhanced mode to increase detection sensitivity and frequency;

[0117] like , the full performance test equipment switches to protection mode, reduces the sensitivity and frequency of detection, reduces the load of the full performance test equipment, and protects the full performance test equipment from overload damage.

[0118] The full-performance test and detection equipment can respond quickly to abnormal situations and automatically adjust the operating mode. The load state sensitive response and adaptive adjustment reduce the risk of overload operation of the full-performance test and detection equipment, extend the service life of the full-performance test and detection equipment, realize intelligent and automated equipment management, and reduce the complexity of manual configuration.

[0119] Embodiment 2:

[0120] This embodiment provides an electronic device having a computer program stored thereon. When the computer program is executed by a processor, the management method based on the full performance test detection device as described in any embodiment of the present invention is implemented.

[0121] Embodiment three:

[0122] This embodiment provides a computer-readable storage medium for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the management method based on the full performance test detection equipment as described in any embodiment of the present invention.

[0123] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0124] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0125] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0126] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), disk or optical disk, and other media that can store program codes.

[0127] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A management method based on full performance test equipment, characterized in that: The specific steps include: Preset a number of full performance test detection equipment roles, wherein the full performance test detection equipment roles are equipment roles that are allowed to access; Identify the QR code of the device under test, obtain the properties of the device under test, and register the identification code of the device under test according to the properties of the device under test; Based on the attributes of the device under test and the role of the full performance test device, the device role matching scoring algorithm is used to calculate the matching score, and authorization verification is performed based on the matching score; For the authorized devices under test, collect the operating data of the devices under test, use the device operating status evaluation algorithm to calculate the evaluation value of the operating status of the devices under test; determine the operating status of the devices under test according to the evaluation value; For abnormal operation status of the equipment under test, the abnormal equipment intelligent diagnosis algorithm is used to calculate the deviation of the operating data of the equipment under test; Calculate the working status score of the full performance test and detection equipment using the equipment status evaluation algorithm based on the deviation, and switch the working mode of the full performance test and detection equipment according to the current working status score; The specific steps of calculating the matching score by the device role matching scoring algorithm are as follows: Full performance test equipment role ; Where m represents the number of full performance test equipment roles, represents the jth full performance test equipment role, ; Use integer encoding techniques to convert the device under test properties into numeric format: Set the device under test properties ; Where n represents the number of attributes of the device under test, represents the i-th attribute of the device under test, ; The calculation formula of the device role matching scoring algorithm is: ； in, It represents the matching score between the device under test and the jth full performance test device role. ; Represents the summation symbol, which is the weighted sum of all attributes of the device under test; represents the i-th attribute of the device under test; represents the square of the attribute of the i-th device under test; Indicates the jth full performance test equipment role The weight of the attribute of the i-th device under test; represents the natural logarithm function; represents a negative exponential function; The method to obtain is: ； in, Indicates Full performance test equipment role During the test, The sensitivity of the DUT attribute, Indicates Full performance test equipment role During the test, The accuracy of each DUT attribute, Indicates Full performance test equipment role During the test, The response time of each property of the device under test, Indicates normalization processing; The specific calculation steps of the evaluation value are: Operation data of the equipment under test ; Where N represents the number of running data of the device under test, It represents the kth operating data of the device under test collected at time t. The operating data of the device under test includes current, voltage and temperature. ; The operating data of the equipment under test is standardized by: ； in, represents the kth tested equipment operation data collected at time t after standardization; represents the mean value of the operating data of the kth device under test; Represents the standard deviation of the operating data of the kth device under test; Obtain standardized operating data of the equipment under test : ； Based on the standardized operating data of the tested equipment , using the equipment operation status evaluation algorithm to calculate the evaluation value of the operation status of the equipment under test; The specific calculation method of the equipment operation status evaluation algorithm is: ； in, It represents the evaluation value of the operating status of the equipment under test at time t; Represents the weight coefficient of the current time t; represents the summation symbol; Indicates the weight of the kth tested device’s operating data; represents trigonometric functions; Indicates the frequency of periodic changes; Indicates the initial phase of the periodic change; Indicates the historical time arrive Sum the operating data of the equipment under test at all historical time points; Indicates a point in history; Indicates that after standardization The kth measured device operation data collected at the moment; represents the time decay factor; represents the time attenuation coefficient; The specific calculation method of the abnormal equipment intelligent diagnosis algorithm is: ； in, It represents the deviation of the kth measured equipment operation data collected at time t; Represents the square root symbol; Represents the square of the time derivative of the operating data of the kth device under test; represents the kth tested equipment operation data collected at time t after standardization; represents the time derivative of the operating data of the kth device under test; Represents the deviation term based on the sine function; sin represents the sine function, capturing the periodic change characteristics; Indicates scale conversion; It represents the difference between the kth tested equipment operation data collected at time t and the historical mean after standardization; Fractional terms representing logarithmic characteristics; A fraction representing a logarithmic characteristic; ln() represents the natural logarithm function; The specific calculation method of the equipment status evaluation algorithm is: ； in, It represents the working status score of the full performance test equipment at time t; It represents the deviation of the kth measured equipment operation data collected at time t; represents the summation symbol; It represents the natural logarithmic function of the deviation of the kth device under test operating data collected at time t plus one; Represents a negative exponential function, exponential Indicates the load condition of the current working state of the full performance test equipment; Represents the load response sensitivity coefficient.

2. The management method based on full performance test equipment according to claim 1 is characterized in that: The specific method of the authorization verification is: Preset matching score threshold Q; Score the matching degree between the device under test and the jth full performance test equipment role Compare with the matching score threshold Q; If the matching score between the device under test and the jth full performance test device role is If it is higher than or equal to the matching score threshold Q, the device under test is authorized to access; If the matching score between the device under test and the jth full performance test device role is If the match score is lower than the threshold Q, no processing will be performed.

3. The management method based on full performance test equipment according to claim 1 is characterized in that: The specific method of switching the working mode of the full performance test equipment according to the current working status score is: Let the threshold range of the normal mode of the full performance test equipment be ; like , then the full performance test equipment switches to normal mode; like , the full performance test detection equipment switches to enhanced mode to increase detection sensitivity and frequency; like , the full performance test equipment switches to protection mode, reduces the sensitivity and frequency of detection, reduces the load of the full performance test equipment, and protects the full performance test equipment from overload damage.

4. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the management method based on the full performance test detection equipment as described in any one of claims 1 to 3 is implemented.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the management method based on the full performance test detection equipment as described in any one of claims 1 to 3 is implemented.

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