Interface circuit remote test system based on virtual instrument technology

Abstract

The invention discloses an interface circuit remote test system based on a virtual instrument technology, relates to the technical field of interface circuit test, and improves the detection accuracy of hardware interface circuit abnormity. According to the method, the normal fluctuation amplitude coefficient range of the interface transmission signal between the same pair of hardware under the same equipment test event is obtained, the abnormal signal segment is extracted from the interface transmission signal according to the normal fluctuation amplitude coefficient range, and the abnormal label element is set for the operation parameter data according to the standard range interval; establishing a characteristic relation matrix between the parameter abnormity matrix and the abnormal signal segment, obtaining test operation parameter data executed by the to-be-detected equipment and a test interface transmission signal, comparing the test operation parameter data and the test interface transmission signal with a corresponding standard range interval and a normal fluctuation amplitude coefficient range, and matching the characteristic relation matrix according to a comparison result; and judging whether the to-be-detected equipment has component abnormity or data transmission protocol abnormity or not.

Description

Technical Field

[0001] The invention relates to the technical field of interface circuit testing, in particular to an interface circuit remote testing system based on virtual instrument technology. Background Art

[0002] Traditional hardware fault detection methods often focus only on monitoring the operating parameters of a single hardware component, lacking a comprehensive consideration of the data interaction between hardware. For example, only paying attention to whether the voltage, current and other parameters of a component are within the normal range, while ignoring the abnormal fluctuations of the interface transmission signal between hardware, it is easy to make it difficult to detect faults caused by abnormal data transmission protocols in a timely manner.

[0003] At the same time, traditional methods do not adequately monitor the coordinated operation of different hardware during the execution of various equipment test events, and cannot accurately capture potential problems that may arise when hardware interacts with each other. In addition, when faced with a large amount of operating parameter data and interface transmission signals, traditional methods lack effective data analysis and integration methods, making it difficult to quickly and accurately locate the root cause of the fault, resulting in long troubleshooting time and high costs, which seriously affects the normal use and maintenance efficiency of hardware equipment. For this reason, an interface circuit remote test system based on virtual instrument technology is provided. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide an interface circuit remote testing system based on virtual instrument technology.

[0005] In order to achieve the above object, the present invention provides the following technical solutions: The interface circuit remote test system based on virtual instrument technology includes a hardware operation data acquisition module, an interface circuit state analysis module and a fault analysis and positioning module; The hardware operation data acquisition module is used to set multiple device test events to execute various device test events several times, set transmission detection data between various hardware during the execution of each device test event, and collect interface transmission signals and operation parameter data of each component in the hardware after each device test event is executed; The interface circuit state analysis module is used to establish an event hardware topology diagram according to the data interaction direction between the hardware, and obtain the normal fluctuation amplitude coefficient range of the interface transmission signal between the same pair of hardware under the same device test event, and extract abnormal signal fragments from the interface transmission signal according to the normal fluctuation amplitude coefficient range; At the same time, the standard range intervals of various operating parameters of various components are obtained through the Internet, and then abnormal label elements are set for the operating parameter data according to the standard range intervals, and the abnormal label elements are integrated to establish a parameter abnormality matrix, and then a feature relationship matrix between the parameter abnormality matrix and the abnormal signal fragments is established; The fault analysis and positioning module is used to obtain the test operation parameter data and test interface transmission signal executed by the device to be tested, and compare them with the corresponding standard range interval and the normal fluctuation amplitude coefficient range, match the characteristic relationship matrix according to the comparison result, and then determine whether there is any abnormal component or data transmission protocol abnormality in the device to be tested.

[0006] Furthermore, the data acquisition card has a built-in operation data acquisition unit and a transmission data acquisition unit; The operation data acquisition unit is used to collect the operation parameter data of the components of the hardware in which it is located. The transmission data acquisition unit is used to set a transmission detection data synchronization to perform data interaction when data interaction is performed between various hardwares, and obtain the interface transmission signal when the data interaction between the hardware is completed.

[0007] Furthermore, the interface transmission signal and the collection process of the operating parameter data include: During the execution of each device detection event, the data acquisition unit in each data acquisition card synchronously collects several operating parameter data of each component in the hardware, and before each hardware performs data exchange, the transmission data acquisition unit generates a transmission detection data with the same length and format as the data exchanged between the hardware; Furthermore, when data is interacted between hardware, the transmission detection data is sent to the previous hardware, so that when data is interacted between corresponding hardware, the transmission detection data is transmitted synchronously, and after the data interaction is completed, the transmission data acquisition unit collects the interface transmission signal corresponding to the transmission detection data after the data interaction is completed.

[0008] Furthermore, the process of establishing the normal fluctuation range coefficient includes: Establishing an event hardware topology diagram according to the data interaction direction between various hardware in each device test event, wherein the event hardware topology diagram is provided with a plurality of hardware nodes, and data flow lines are provided between various hardware nodes; A two-dimensional coordinate space is established, and interface transmission signals corresponding to the same device test event and the same data flow line are placed in the same two-dimensional coordinate space; Performing Hilbert transform on each interface transmission signal, and establishing a correlation signal equation between the interface transmission signal and its corresponding Hilbert transform result signal; The execution time length of the device operation event is divided into multiple time segments, and the mean μ and standard deviation of the correlation signal equation corresponding to each interface transmission signal in each time segment are obtained, and then the fluctuation amplitude coefficient of each interface transmission signal in the corresponding time segment is obtained according to the ratio between the standard deviation and the mean; The fluctuation amplitude coefficient of each interface transmission signal in each time segment is normally distributed, and the fluctuation amplitude coefficient value corresponding to the center position of the normal distribution result is selected and recorded as the normal fluctuation amplitude coefficient range of the corresponding time segment.

[0009] Furthermore, the process of setting an abnormal label element for the operating parameter data includes: Each operating parameter data is divided into several parameter data segments. Through the standard range interval of each operating parameter, each equipment test event is judged whether each operating parameter data is within the corresponding standard range interval in each time segment. If so, a normal label is set for the parameter data segment of the corresponding time segment, otherwise it is recorded as an abnormal label element.

[0010] Furthermore, the process of establishing the parameter anomaly matrix includes: According to the number of components contained in each hardware, multiple component nodes are set for each hardware node on the event hardware topology map, and at the same time, a dynamic state matrix is ​​set for each component node according to the parameter data fragments of the component in each time segment; According to the time segment sequence and the direction of the data flow lines between the hardware nodes on the event hardware topology diagram, the abnormal label elements are extracted from the dynamic state matrices associated with the hardware nodes with the data flow lines, and merged to generate a parameter abnormality matrix; Retrieving each operating parameter data and correlating the generated interface transmission signal with the normal fluctuation amplitude coefficient range, and then determining whether the interface transmission signal has a portion exceeding the normal fluctuation amplitude coefficient range in each time segment; If it does not exist, the corresponding time segment is skipped; if it does exist, the interface transmission signal segment that exceeds the normal fluctuation amplitude coefficient range is intercepted and recorded as an abnormal signal segment.

[0011] Furthermore, the process of obtaining the feature relationship matrix includes: The absolute value of each abnormal label element in the parameter abnormality matrix is ​​decremented from the closest value in the corresponding standard range, and then each abnormal label element in the parameter abnormality matrix is ​​updated, and then the abnormal label element of each column in the parameter abnormality matrix is ​​converted to a standard normal distribution form with a mean of 0 and a variance of 1, and the parameter covariance matrix corresponding to the parameter abnormality matrix after the standard normal distribution form is obtained; Divide a number of time nodes in the time segment, obtain the abnormal peak value of the abnormal signal fragment at each time node, and then use the abnormal peak value as the impact result value at each time node, and each element in the parameter covariance matrix at each time node as the impact guide value, and establish the corresponding impact relationship equation; Then, according to the parameter operation data and interface transmission signals of different device test events, several rounds of iterations are performed on the influence relationship equations of different component elements and types of operation parameters, and the characteristic relationship matrix is ​​obtained according to the iteration results.

[0012] Furthermore, the process of determining whether the device to be detected has an abnormal component or an abnormal data transmission protocol includes: The process of using the hardware operation data acquisition module to obtain the operation parameter data and the interface transmission signal, so that the device to be tested performs various device test events in sequence, and after each device test event is completed, all the test operation parameter data and the test interface transmission signal are uploaded to the fault analysis and positioning module; According to the normal fluctuation range coefficient ranges corresponding to the test events of each device, determine whether the transmission signals of each test interface exceed the normal fluctuation range coefficient range in each time segment. If so, intercept the exceeding part and record it as an abnormal test signal segment. Otherwise, ignore the test interface transmission signal of the corresponding time segment. If it is determined that there is no abnormal test signal segment in each time segment, proceed to the next pair of hardware node detection; At the same time, according to the standard range of each operating parameter, it is judged whether each test operating parameter data has abnormalities, and the abnormal data interval is marked in the test operating parameter data according to the judgment result; Map each abnormal test signal segment and abnormal data interval in the event hardware topology map in sequence according to the hardware correspondence, and then retrieve the corresponding feature relationship matrix according to the device test event type and hardware type; Matching the characteristic relationship matrix according to the type of operating parameters corresponding to the abnormal data interval, and then obtaining the expected abnormal test signal segment according to the elements in the matched characteristic relationship matrix and the time segment where the abnormal data interval occurs; According to the time sequence, the expected abnormal test signal segments and the abnormal test segments in each time segment are sequentially mapped into the same two-dimensional coordinate system, and firstly, it is determined whether each expected abnormal test signal segment and the abnormal test segment in each time segment correspond to each other one by one; If it is determined that there is no one-to-one correspondence, it is determined again whether the abnormal test fragment appears alone in a time segment. If so, it is determined that there is an abnormality in the data transmission protocol in the interface circuit between the corresponding hardware; If it is determined that there is a one-to-one correspondence, or it is determined that there is no abnormal test segment that appears alone in a time period, it is determined that there is an abnormality in the component of the corresponding hardware.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention obtains the normal fluctuation amplitude coefficient range of the interface transmission signal between the same pair of hardware under the same equipment test event, extracts abnormal signal fragments therefrom, and sets abnormal label elements for the operating parameter data through the standard range interval of each operating parameter, establishes a parameter abnormality matrix and a characteristic relationship matrix between the parameter abnormality matrix and the abnormal signal fragments, thereby realizing in-depth analysis and integration of hardware operation data, and accurately identifying abnormal situations during hardware operation, providing a strong data basis for fault location.

[0014] 2. By comparing the test operation parameter data of the device to be tested and the test interface transmission signal with the corresponding standard range and the normal fluctuation amplitude coefficient range, and matching the characteristic relationship matrix according to the comparison results, it is possible to quickly and accurately determine whether there are component abnormalities or data transmission protocol abnormalities in the device to be tested. At the same time, it shortens the troubleshooting time, reduces maintenance costs, and improves the utilization efficiency and reliability of hardware equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0016] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0017] Example

[0018] like Figure 1 As shown, the interface circuit remote test system based on virtual instrument technology includes a hardware operation data acquisition module, an interface circuit state analysis module and a fault analysis and positioning module; The hardware operation data acquisition module is used to set a data acquisition card for each hardware, and set a variety of equipment test events, so as to make each hardware jointly execute various equipment test events for several times, and set transmission detection data between each hardware during the execution of each equipment test event. After each equipment test event is executed, the data acquisition card acquisition interface transmits signals and operation parameter data of each component in the hardware; The interface circuit state analysis module is used to establish an event hardware topology diagram according to the data interaction direction between the hardware, and obtain the normal fluctuation amplitude coefficient range of the interface transmission signal between the same pair of hardware under the same device test event, and extract abnormal signal fragments from the interface transmission signal according to the normal fluctuation amplitude coefficient range; At the same time, the standard range intervals of various operating parameters of various components are obtained through the Internet, and then abnormal label elements are set for the operating parameter data according to the standard range intervals, and the abnormal label elements are integrated to establish a parameter abnormality matrix, and then a feature relationship matrix between the parameter abnormality matrix and the abnormal signal fragments is established; The fault analysis and positioning module is used to obtain the test operation parameter data and test interface transmission signal executed by the device to be tested, and compare them with the corresponding standard range interval and the normal fluctuation amplitude coefficient range, match the characteristic relationship matrix according to the comparison result, and then determine whether there is any abnormal component or data transmission protocol abnormality in the device to be tested.

[0019] In this embodiment, the hardware operation data acquisition module includes: Install a data acquisition card on each of the hardware in the various devices, and set a number a1, a2, a3, ..., a for each data acquisition card. n , where n is an integer greater than 0, and n represents the total number of hardware in the various devices, each of which is composed of multiple components, such as a level converter, an optocoupler, a diode, etc.; The data acquisition card is built with an operation data acquisition unit and a transmission data acquisition unit; The operation data acquisition unit is used to collect operation parameter data of the components of the hardware in which it is located, such as temperature, voltage, current, etc.; The transmission data acquisition unit is used to set a transmission detection data synchronization to perform data interaction when data interaction is performed between various hardwares, and obtain an interface transmission signal when the data interaction between the hardwares ends; Then the hardware operation data acquisition module sets device test events for various devices, wherein the device test events include startup initialization events, peak load events, low power consumption events, abnormal recovery events, mode switching events, and limit test events; During the execution of each device detection event, the data acquisition unit running in each data acquisition card synchronously collects several items of operation parameter data of each component in the hardware, and before each hardware performs data interaction, the transmission data acquisition unit generates a transmission detection data with the same length and format as the data exchanged between the hardware, and then when the data is exchanged between the hardware, the transmission detection data is sent to the previous hardware, so that when the corresponding hardware interacts with each other, the transmission detection data is synchronously transmitted, and after the data interaction is completed, the transmission data acquisition unit collects the interface transmission signal corresponding to the transmission detection data after the data interaction is completed; The test event of each device is repeatedly executed several times. At the same time, the hardware data acquisition module collects the operating parameter data of each hardware component and the interface transmission signal after the detection data passes through each hardware interface.

[0020] In this embodiment, the interface circuit state analysis module includes: Establishing an event hardware topology diagram according to the data interaction direction between various hardware in each device test event, wherein the event hardware topology diagram is provided with a plurality of hardware nodes, and data flow lines are provided between various hardware nodes; It should be noted that the position distribution of each hardware node in the event hardware topology diagram is the same as the position distribution in various devices. At the same time, according to the data interaction sequence between hardware in the device test event, each data flow line is marked with the data interaction sequence and data interaction direction; A two-dimensional coordinate space is established, and interface transmission signals corresponding to the same device test event and the same data flow line are placed in the same two-dimensional coordinate space; The transmission signal of each interface is recorded as x i (t), transmit signal x to each interface i (t) Perform Hilbert transform and record the interface transmission signal after Hilbert transform as x i ~ (t), where x i (t) and x i ~ (t) respectively represent the interface transmission signal and the Hilbert transform result signal corresponding to any data flow line when the i-th device test event is executed, t represents time, and i is an integer greater than 0; Establish the correlation signal equation θ(t) between the interface transmission signal and its corresponding Hilbert transform result signal, where the correlation signal equation is expressed as ,in A correlation signal equation representing the correlation signal between the corresponding interface transmission signal and its corresponding Hilbert transform result signal when the i-th device test event is executed; The execution time length of the device operation event is divided into multiple time segments, and the mean μ and standard deviation α of the correlation signal equation corresponding to each interface transmission signal in each time segment are obtained, and then the fluctuation amplitude coefficient of each interface transmission signal in the corresponding time segment is obtained according to the ratio between the standard deviation α and the mean μ; The fluctuation amplitude coefficient of each interface transmission signal in each time segment is normally distributed, and the fluctuation amplitude coefficient value corresponding to the center position of the normal distribution result is selected and recorded as the normal fluctuation amplitude coefficient range of the corresponding time segment.

[0021] Furthermore, the standard range intervals of various operating parameters of various components in the hardware are obtained through the Internet, and at the same time, the time segment with the same range of normal fluctuation coefficient is used to divide each operating parameter data into several parameter data segments; Then, through the standard range interval of each operating parameter, it is judged whether each equipment test event and each operating parameter data in each time segment are within the corresponding standard range interval. If so, a normal label is set for the parameter data segment of the corresponding time segment, otherwise it is recorded as an abnormal label element; According to the number of components contained in each hardware, multiple component nodes are set for each hardware node on the event hardware topology diagram. At the same time, according to the parameter data fragments of the component in each time segment, a dynamic state matrix is ​​set for each component node. The dynamic state matrix is ​​expressed as [x1, ..., x j ], where x j represents the j-th parameter data fragment, where j is an integer greater than 1; It should be noted that each parameter data segment in the dynamic state matrix changes synchronously with the time segment; According to the time segment sequence and the direction of the data flow lines between the hardware nodes on the event hardware topology diagram, the abnormal label elements are extracted from the dynamic state matrices associated with the hardware nodes with the data flow lines, and merged to generate a parameter abnormality matrix; It should be noted that in the parameter anomaly matrix, the anomaly label elements from the same dynamic state matrix are located in the same column, and the anomaly label elements from different dynamic state matrices are located in different columns; Retrieving each operating parameter data and correlating the generated interface transmission signal with the normal fluctuation amplitude coefficient range, and then determining whether the interface transmission signal has a portion exceeding the normal fluctuation amplitude coefficient range in each time segment; If it does not exist, the corresponding time segment is skipped; if it does exist, the interface transmission signal segment that exceeds the normal fluctuation amplitude coefficient range is intercepted and recorded as an abnormal signal segment; Repeat the above operation of obtaining contribution rate scores to obtain the feature relationship matrix between various hardware under different device test events; The process of obtaining the feature relationship matrix includes: The absolute value of each abnormal label element in the parameter abnormality matrix is ​​decremented from the closest value in the corresponding standard range, and then each abnormal label element in the parameter abnormality matrix is ​​updated, and then the abnormal label element of each column in the parameter abnormality matrix is ​​converted to a standard normal distribution form with a mean of 0 and a variance of 1, and the parameter covariance matrix corresponding to the parameter abnormality matrix after the standard normal distribution form is obtained; Divide a number of time nodes in the time segment, obtain the abnormal peak value of the abnormal signal fragment at each time node, and then use the abnormal peak value as the impact result value at each time node, and each element in the parameter covariance matrix at each time node as the impact guide value, and establish the corresponding impact relationship equation; Then, according to the parameter operation data and interface transmission signals of different device test events, several rounds of iterations are performed on the influence relationship equations of different types of components and operation parameters, and a characteristic relationship matrix is ​​obtained according to the iteration results, wherein the same column in the characteristic relationship matrix represents the relationship parameters of multiple parameters of the same component, and different columns correspond to the relationship parameters of different components; Repeat the above-mentioned operation of generating a characteristic relationship matrix to obtain multiple characteristic relationship matrices of different components between various hardware in each device test event, and send all characteristic relationship matrices to the fault analysis and positioning module.

[0022] In this embodiment, the fault analysis and location module includes: The process of using the hardware operation data acquisition module to obtain the operation parameter data and the interface transmission signal, so that the device to be tested performs various device test events in sequence, and after each device test event is completed, all the test operation parameter data and the test interface transmission signal are uploaded to the fault analysis and positioning module; According to the normal fluctuation range coefficient ranges corresponding to the test events of each device, determine whether the transmission signals of each test interface exceed the normal fluctuation range coefficient range in each time segment. If so, intercept the exceeding part and record it as an abnormal test signal segment. Otherwise, ignore the test interface transmission signal of the corresponding time segment. If it is determined that there is no abnormal test signal segment in each time segment, proceed to the next pair of hardware node detection; At the same time, according to the standard range of each operating parameter, it is judged whether each test operating parameter data has abnormalities, and the abnormal data interval is marked in the test operating parameter data according to the judgment result; Map each abnormal test signal segment and abnormal data interval in the event hardware topology map in sequence according to the hardware correspondence, and then retrieve the corresponding feature relationship matrix according to the device test event type and hardware type; Matching the characteristic relationship matrix according to the type of operating parameters corresponding to the abnormal data interval, and then obtaining the expected abnormal test signal segment according to the elements in the matched characteristic relationship matrix and the time segment where the abnormal data interval occurs; According to the time sequence, the expected abnormal test signal segments and the abnormal test segments in each time segment are sequentially mapped into the same two-dimensional coordinate system, and firstly, it is determined whether each expected abnormal test signal segment and the abnormal test segment in each time segment correspond to each other one by one; If it is determined that there is no one-to-one correspondence, it is determined again whether the abnormal test fragment appears alone in a time segment. If so, it is determined that there is an abnormality in the data transmission protocol in the interface circuit between the corresponding hardware; If it is determined that there is a one-to-one correspondence, or it is determined that there is no abnormal test segment that appears alone in a time period, it is determined that there is an abnormality in the component of the corresponding hardware.

[0023] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any indirect modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. The interface circuit remote testing system based on virtual instrument technology is characterized by: It includes hardware operation data acquisition module, interface circuit status analysis module and fault analysis and positioning module; The hardware operation data acquisition module is used to set multiple device test events to execute various device test events several times, set transmission detection data between various hardware during the execution of each device test event, and collect interface transmission signals and operation parameter data of each component in the hardware after each device test event is executed; The interface circuit state analysis module is used to establish an event hardware topology diagram according to the data interaction direction between the hardware, and obtain the normal fluctuation amplitude coefficient range of the interface transmission signal between the same pair of hardware under the same device test event, and extract abnormal signal fragments from the interface transmission signal according to the normal fluctuation amplitude coefficient range; At the same time, the standard range intervals of various operating parameters of various components are obtained through the Internet, and then abnormal label elements are set for the operating parameter data according to the standard range intervals, and the abnormal label elements are integrated to establish a parameter abnormality matrix, and then a feature relationship matrix between the parameter abnormality matrix and the abnormal signal fragments is established; The fault analysis and positioning module is used to obtain the test operation parameter data and test interface transmission signal executed by the device to be tested, and compare them with the corresponding standard range interval and the normal fluctuation amplitude coefficient range, match the characteristic relationship matrix according to the comparison result, and then determine whether there is any abnormal component or data transmission protocol abnormality in the device to be tested.

2. The interface circuit remote testing system based on virtual instrument technology according to claim 1 is characterized in that: The hardware operation data acquisition module is provided with a data acquisition card, and the data acquisition card has an operation data acquisition unit and a transmission data acquisition unit built in; The operation data acquisition unit is used to collect the operation parameter data of the components of the hardware in which it is located. The transmission data acquisition unit is used to set a transmission detection data synchronization to perform data interaction when data interaction is performed between various hardwares, and obtain the interface transmission signal when the data interaction between the hardware is completed.

3. The interface circuit remote testing system based on virtual instrument technology according to claim 2 is characterized in that: The interface transmission signal and the collection process of the operating parameter data include: During the execution of each device detection event, the operation data acquisition unit synchronously collects several operation parameter data of each component in the hardware, and before each hardware performs data exchange, generates a transmission detection data with the same length and format as the data exchanged between the hardware; When data is exchanged between hardware, the transmission detection data is sent to the previous hardware, and after the data interaction is completed, the interface transmission signal corresponding to the transmission detection data is collected after the data interaction is completed.

4. The interface circuit remote testing system based on virtual instrument technology according to claim 3 is characterized in that: The process of establishing the normal fluctuation range coefficient includes: Establishing an event hardware topology map according to the data interaction direction between various hardware in each device test event, wherein the event hardware topology map is provided with a plurality of hardware nodes; Performing Hilbert transform on each interface transmission signal, and establishing a correlation signal equation between the interface transmission signal and its corresponding Hilbert transform result signal; The execution time length of the device operation event is divided into multiple time segments, and the mean and standard deviation of the correlation signal equation corresponding to each interface transmission signal in each time segment are obtained, and then the fluctuation amplitude coefficient of each interface transmission signal is obtained according to the ratio between the standard deviation and the mean; The fluctuation amplitude coefficient of each interface transmission signal in each time segment is normally distributed, and the fluctuation amplitude coefficient value corresponding to the center position of the normal distribution result is selected and recorded as the normal fluctuation amplitude coefficient range of the corresponding time segment.

5. The interface circuit remote testing system based on virtual instrument technology according to claim 3 is characterized in that: The process of setting abnormal label elements for operating parameter data includes: Each operating parameter data is divided into several parameter data segments. Through the standard range interval of each operating parameter, each equipment test event is judged whether each operating parameter data is within the corresponding standard range interval in each time segment. If so, a normal label is set for the parameter data segment of the corresponding time segment, otherwise it is recorded as an abnormal label element.

6. The interface circuit remote testing system based on virtual instrument technology according to claim 5, characterized in that: The process of establishing the parameter anomaly matrix includes: Set a dynamic state matrix, extract abnormal label elements from each dynamic state matrix in turn according to the time segment sequence and the data flow line direction between each hardware node on the event hardware topology diagram, and merge them to generate a parameter abnormality matrix; Retrieve the data of various operating parameters and simultaneously associate the generated interface transmission signal with the normal fluctuation amplitude coefficient range, and then determine whether the interface transmission signal has a part exceeding the normal fluctuation amplitude coefficient range in each time segment, and obtain the abnormal signal segment based on the judgment result.

7. The interface circuit remote testing system based on virtual instrument technology according to claim 6 is characterized in that: The process of obtaining the feature relationship matrix includes: Subtract the absolute value of each abnormal label element in the parameter abnormality matrix from the closest value in the corresponding standard range, update each abnormal label element in the parameter abnormality matrix, and then convert the abnormal label element in each column into a standard normal distribution form, and obtain the parameter covariance matrix corresponding to the parameter abnormality matrix after the standard normal distribution form; Divide a number of time nodes in the time segment, obtain the abnormal peak value of the abnormal signal fragment at each time node, and then use the abnormal peak value as the impact result value at each time node, and each element in the parameter covariance matrix at each time node as the impact guide value, and establish the corresponding impact relationship equation; Then, according to the parameter operation data and interface transmission signals of different device test events, several rounds of iterations are performed on the influence relationship equations of different component elements and types of operation parameters, and the characteristic relationship matrix is ​​obtained according to the iteration results.

8. The interface circuit remote testing system based on virtual instrument technology according to claim 7 is characterized in that: The process of determining whether the device to be tested has abnormal components or abnormal data transmission protocol includes: Instruct the device to be tested to execute various device test events in sequence, and transmit all test operation parameter data and test interface transmission signals after each device test event is completed; According to the normal fluctuation range coefficient ranges corresponding to the test events of each device, it is determined whether the transmission signal of each test interface exceeds the normal fluctuation range coefficient range in each time segment, and the abnormal test signal segment is intercepted according to the determination result; At the same time, according to the standard range of each operating parameter, it is judged whether each test operating parameter data has abnormalities, and the abnormal data interval is marked in the test operating parameter data according to the judgment result; Retrieve the corresponding feature relationship matrix according to the type of device test event and the type of hardware, and obtain the expected abnormal test signal segment according to the elements in the matched feature relationship matrix and the time period in which the abnormal data interval occurs; According to the time sequence, the expected abnormal test signal segments and abnormal test segments in each time segment are mapped in turn in the same two-dimensional coordinate system, so as to determine whether there is an abnormality in the data transmission protocol of the interface circuit between the hardware, or whether there is an abnormality in the component.

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