Remote Test System for Interface Circuit Based on Virtual Instrument Technology

Abstract

The present invention discloses a remote test system for interface circuits based on virtual instrument technology, which relates to the technical field of interface circuit testing and improves the detection accuracy of hardware interface circuit anomalies. The present invention obtains the normal fluctuation amplitude coefficient range of the interface transmission signal between the same pair of hardware under the test events of the same device, extracts abnormal signal segments from the interface transmission signal according to the normal fluctuation amplitude coefficient range, and at the same time sets abnormal label elements for the operation parameter data according to the standard range interval, thereby establishing a characteristic relationship matrix between the parameter anomaly matrix and the abnormal signal segments, obtaining the test operation parameter data and the test interface transmission signal executed by the device to be detected, comparing them with the corresponding standard range interval and the normal fluctuation amplitude coefficient range, and matching the characteristic relationship matrix according to the comparison result, thereby determining whether there are anomalies in the component elements or data transmission protocols of the device to be detected.

Description

Technical Field

[0001] The present invention relates to the technical field of interface circuit testing, and specifically to a remote testing system for interface circuits based on virtual instrument technology. Background Art

[0002] Traditional hardware fault detection methods often only focus on monitoring the operating parameters of individual components of the hardware, lacking a comprehensive consideration of the data interaction between hardware components. For example, only paying attention to whether parameters such as voltage and current of a certain component are within the normal range, while ignoring abnormal fluctuations in the signals transmitted through the interfaces between hardware components, it is easy to cause faults caused by abnormal data transmission protocols to be difficult to be detected in a timely manner.

[0003] At the same time, traditional methods have insufficient monitoring of the coordinated operation of different hardware during the execution of various device test events, and cannot accurately capture potential problems that may occur when hardware components interact with each other. In addition, in the face of a large amount of operating parameter data and interface transmission signals, traditional methods lack effective data analysis and integration means, making it difficult to quickly and accurately locate the root cause of faults, resulting in long fault troubleshooting time and high costs, seriously affecting the normal use and maintenance efficiency of hardware devices. Therefore, a remote testing system for interface circuits 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 a remote testing system for interface circuits based on virtual instrument technology.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] A remote testing system for interface circuits based on virtual instrument technology, including a hardware operation data acquisition module, an interface circuit status analysis module, and a fault analysis and location module;

[0007] The hardware operation data acquisition module is used to set a variety of device test events to execute various device test events several times, set transmission detection data between each hardware during the execution of each device test event, and collect interface transmission signals and the operation parameter data of each component within the hardware whenever a device test event ends;

[0008] The interface circuit status analysis module is used to establish an event-hardware topology diagram according to the data interaction direction between hardware components, obtain the normal fluctuation amplitude coefficient range of the interface transmission signals between the same pair of hardware components under the same device test event, and extract abnormal signal segments from the interface transmission signals according to the normal fluctuation amplitude coefficient range;

[0009] Meanwhile, obtain the standard range intervals of the operating parameters of each component through the Internet, then set abnormal label elements for the operating parameter data according to the standard range intervals, integrate the abnormal label elements to establish a parameter abnormal matrix, and further establish a characteristic relationship matrix between the parameter abnormal matrix and the abnormal signal segments;

[0010] The fault analysis and location module is used to obtain the test operation parameter data executed by the device to be detected and the test interface transmission signal, compare them with the corresponding standard range intervals and the normal fluctuation amplitude coefficient range, match the characteristic relationship matrix according to the comparison results, and then judge whether there are abnormal component elements or abnormal data transmission protocols in the device to be detected.

[0011] Furthermore, the data acquisition card is built-in with an operating data acquisition unit and a transmission data acquisition unit;

[0012] The operating data acquisition unit is used to collect the operating parameter data of the component elements of the hardware where it is located. The transmission data acquisition unit is used to set a transmission detection data to synchronize data interaction when data is exchanged between each hardware, and obtain the interface transmission signal when the data interaction between the hardware ends.

[0013] Furthermore, the acquisition process of the interface transmission signal and the operating parameter data includes:

[0014] During the execution of each device detection event, the operating data acquisition units in each data acquisition card synchronously collect several items of operating parameter data of each component element in the hardware where they are located. Before data interaction between each hardware, the transmission data acquisition unit generates a transmission detection data with the same length and format as the data exchanged between the hardware.

[0015] Furthermore, when data is exchanged between the hardware, the transmission detection data is sent to the previous hardware, so that when data is exchanged between the corresponding hardware, the transmission detection data is synchronously transmitted, and after the data interaction ends, the transmission data acquisition unit collects the interface transmission signal corresponding to the transmission detection data after the data interaction ends.

[0016] Furthermore, the establishment process of the normal fluctuation amplitude coefficient range includes:

[0017] Establish an event hardware topology diagram according to the data interaction directions between each hardware in each device test event. There are several hardware nodes set in the event hardware topology diagram, and data flow lines are set between each hardware node;

[0018] Establish a two-dimensional coordinate space, and place the interface transmission signals corresponding to the same device test event and the same data flow line in the same two-dimensional coordinate space;

[0019] Perform Hilbert transform on the signals transmitted through each interface, and establish a correlation signal equation between the interface transmission signal and its corresponding Hilbert transform result signal;

[0020] Divide the execution time length of the device operation event into multiple time segments, obtain the mean μ and standard deviation of the correlation signal equations corresponding to each interface transmission signal in each time segment, and then obtain the fluctuation amplitude coefficient of each interface transmission signal in the corresponding time segment according to the ratio between the standard deviation and the mean;

[0021] Perform normal distribution on the fluctuation amplitude coefficients of each interface transmission signal in each time segment, and select the numerical value of the fluctuation amplitude coefficient corresponding to the central position of the normal distribution result, which is denoted as the normal fluctuation amplitude coefficient range of the corresponding time segment.

[0022] Further, the process of setting abnormal label elements for the operation parameter data includes:

[0023] Divide each operation parameter data into several parameter data segments, and judge whether each operation parameter data is within the corresponding standard range interval in each time segment for each device test event through the standard range interval of each operation parameter. If it is, set a normal label for the parameter data segment in the corresponding time segment, otherwise record it as an abnormal label element.

[0024] Further, the process of establishing the parameter abnormal matrix includes:

[0025] According to the number of component elements included in each hardware, set multiple component nodes for each hardware node on the event hardware topology diagram. At the same time, according to the parameter data segments of the component elements in each time segment, set a dynamic state matrix for each component node;

[0026] According to the time segment sequence and the data flow line direction between each hardware node on the event hardware topology diagram, sequentially extract the abnormal label elements from the dynamic state matrices associated with the hardware nodes with data flow lines and merge them to generate a parameter abnormal matrix;

[0027] Retrieve the interface transmission signals and the normal fluctuation amplitude coefficient range generated by associating each operation parameter data at the same time, and then judge whether there is a part exceeding the normal fluctuation amplitude coefficient range in each time segment of the interface transmission signal;

[0028] If not, skip the corresponding time segment. If so, intercept the interface transmission signal segment exceeding the normal fluctuation amplitude coefficient range and record it as an abnormal signal segment.

[0029] Further, the process of obtaining the characteristic relationship matrix includes:

[0030] Take the absolute value of each abnormal label element in the parameter abnormal matrix in a decreasing order with respect to the closest value in the corresponding standard range interval, and then update each abnormal label element in the parameter abnormal matrix. Then, convert the abnormal label elements in each column of the parameter abnormal matrix into the form of a standard normal distribution with a mean of 0 and a variance of 1, and obtain the parameter covariance matrix corresponding to the parameter abnormal matrix in the form of a standard normal distribution;

[0031] Divide a time period into several time nodes, obtain the abnormal peaks of the abnormal signal segments at each time node, and then establish a corresponding influence relationship equation with the abnormal peaks as the influence result values at each time node and the elements in the parameter covariance matrix at each time node as the influence guiding values;

[0032] Furthermore, perform several rounds of iteration on the influence relationship equations of different component types and operation parameter types according to the parameter operation data and interface transmission signals of different device test events, and obtain the characteristic relationship matrix according to the iteration results.

[0033] Further, the process of determining whether there are abnormal component or data transmission protocol in the device to be detected includes:

[0034] In the process of using the hardware operation data acquisition module to obtain the operation parameter data and interface transmission signals, let the device to be detected execute various device test events in turn, and upload all the test operation parameter data and test interface transmission signals to the fault analysis and location module after each device test event ends;

[0035] According to the normal fluctuation amplitude coefficient ranges corresponding to each device test event, determine whether there is a part exceeding the normal fluctuation amplitude coefficient range in each test interface transmission signal in each time period. If so, intercept the exceeding part and record it as an abnormal test signal segment. Otherwise, ignore the test interface transmission signal in the corresponding time period. If it is determined that there is no abnormal test signal segment in each time period, proceed to the next pair of hardware node detections;

[0036] At the same time, according to the standard range intervals of each operation parameter, determine whether there are abnormalities in each test operation parameter data, and mark the abnormal data intervals in the test operation parameter data according to the judgment results;

[0037] Map each abnormal test signal segment and abnormal data interval to the event hardware topology diagram in sequence according to the hardware corresponding relationship, and then retrieve the corresponding characteristic relationship matrix according to the device test event types and hardware types;

[0038] Match the characteristic relationship matrix according to the operation parameter types corresponding to the abnormal data intervals, and then obtain the predicted abnormal test signal segments according to the elements in the matched characteristic relationship matrix and the time periods when the abnormal data intervals appear.

[0039] According to the chronological order, the predicted abnormal test signal segments and abnormal test segments in each time period are sequentially mapped onto the same two-dimensional coordinate system. First, it is determined whether each predicted abnormal test signal segment and abnormal test segment correspond one by one in each time period;

[0040] If it is determined that they do not correspond one by one, then it is determined again whether the abnormal test segment appears alone in a time period. If so, it is determined that there is an abnormal data transmission protocol in the interface circuit between the corresponding hardware;

[0041] If it is determined that they correspond one by one, or it is determined that there is no abnormal test segment appearing alone in a time period, then it is determined that there is an abnormality in the constituent elements of the corresponding hardware.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] 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 device test event, extracts abnormal signal segments therefrom, and sets abnormal label elements for the operation parameter data through the standard range intervals of various operation parameters, establishes a parameter abnormal matrix and a characteristic relationship matrix between the parameter abnormal matrix and the abnormal signal segments, realizes the in-depth analysis and integration of the hardware operation data, and realizes the accurate identification of abnormal situations in the hardware operation process, providing a strong data basis for fault location.

[0044] 2. By comparing the test operation parameter data and test interface transmission signal of the device to be detected with the corresponding standard range intervals and normal fluctuation amplitude coefficient ranges, and matching the characteristic relationship matrix according to the comparison results, it can quickly and accurately determine whether there is an abnormality in the constituent elements or data transmission protocol of the device to be detected, while shortening the fault troubleshooting time, reducing the maintenance cost, and improving the use efficiency and reliability of the hardware device. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0046] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following combines the drawings and preferred embodiments to detail the specific implementation manner, structure, characteristics and effects of the present invention as follows.

[0047] Embodiment

[0048] As Figure 1As shown in the figure, an interface circuit remote test system based on virtual instrument technology includes a hardware operation data acquisition module, an interface circuit status analysis module, and a fault analysis and location module;

[0049] The hardware operation data acquisition module is used to set data acquisition cards for each hardware, set multiple device test events, and then make each hardware execute various device test events several times. During the execution of each device test event, transmission detection data is set between each hardware. Whenever a device test event is executed, the interface transmission signal and the operation parameter data of each component in the hardware are collected through the data acquisition card;

[0050] The interface circuit status analysis module is used to establish an event hardware topology diagram according to the data interaction direction between the hardware, 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 segments from the interface transmission signal according to the normal fluctuation amplitude coefficient range;

[0051] At the same time, the standard range interval of the operation parameters of each component is obtained through the Internet. Then, abnormal label elements are set for the operation parameter data according to the standard range interval, and the abnormal label elements are integrated to establish a parameter abnormal matrix. Furthermore, a characteristic relationship matrix is established between the parameter abnormal matrix and the abnormal signal segment;

[0052] The fault analysis and location module is used to obtain the test operation parameter data and test interface transmission signal executed by the device to be detected, compare them with the corresponding standard range interval and normal fluctuation amplitude coefficient range, match the characteristic relationship matrix according to the comparison result, and then judge whether there are component abnormalities or data transmission protocol abnormalities in the device to be detected.

[0053] In this embodiment, the hardware operation data acquisition module includes:

[0054] A data acquisition card is installed for each hardware in multiple devices, and numbers a1, a2, a3,..., a n , where n is an integer greater than 0, and n represents the total number of hardware in multiple devices. Each hardware is composed of multiple components, such as a level converter, an optocoupler, a diode, etc.;

[0055] The data acquisition card is built-in with an operation data acquisition unit and a transmission data acquisition unit;

[0056] The operation data acquisition unit is used to collect the operation parameter data of the components of the hardware where it is located, such as temperature, voltage, current, etc.;

[0057] The transmission data acquisition unit is used to set a transmission detection data to synchronously perform data interaction when data is interacted between various hardware components, and obtain an interface transmission signal when the data interaction between the hardware components ends;

[0058] Furthermore, the hardware operation data acquisition module sets device test events for multiple devices, and the device test events include start initialization event, peak load event, low power consumption event, exception recovery event, mode switching event, and extreme test event;

[0059] During the execution of each device detection event, the operation data acquisition unit in each data acquisition card synchronously acquires several items of operation parameter data of each component within the corresponding hardware. Before data interaction between the hardware components, the transmission data acquisition unit generates a transmission detection data with the same length and format as the data interacted between the hardware components. Then, when data is interacted between the hardware components, the transmission detection data is sent to the previous hardware, so that when data is interacted between the corresponding hardware components, the transmission detection data is synchronously transmitted. After the data interaction ends, the transmission data acquisition unit acquires the interface transmission signal corresponding to the transmission detection data after the data interaction ends;

[0060] Each device test event is repeatedly executed several times. At the same time, the hardware data acquisition module acquires the operation parameter data of the components of each hardware, and the interface transmission signal after the detection data passes through each hardware interface.

[0061] In this embodiment, the interface circuit state analysis module includes:

[0062] An event hardware topology graph is established according to the data interaction directions between the hardware components in each device test event. Several hardware nodes are set in the event hardware topology graph, and data flow lines are set between the hardware nodes;

[0063] It should be noted that the position distribution of each hardware node in the event hardware topology graph is the same as its position distribution in multiple devices. At the same time, according to the data interaction sequence between the hardware components in the device test event, each data flow line is marked with the data interaction sequence and the data interaction direction;

[0064] A two-dimensional coordinate space is established, and the 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;

[0065] Denote each interface transmission signal as x i (t), perform Hilbert transform on each interface transmission signal x i (t), and denote 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 during the execution of the i-th device test event, t represents time, and i is an integer greater than 0;

[0066] Establish an associated signal equation θ(t) between the interface transmission signal and its corresponding Hilbert transform result signal, where the associated signal equation is expressed as , where represents the associated signal equation between the interface transmission signal and its corresponding Hilbert transform result signal during the execution of the i-th device test event;

[0067] Divide the execution time length of the device operation event into multiple time segments, and obtain the mean μ and standard deviation α of the associated signal equations corresponding to each interface transmission signal in each time segment. Then, obtain the fluctuation amplitude coefficient of each interface transmission signal in the corresponding time segment according to the ratio between the standard deviation α and the mean μ;

[0068] Perform a normal distribution on the fluctuation amplitude coefficients of each interface transmission signal in each time segment, and select the value of the fluctuation amplitude coefficient corresponding to the center position of the normal distribution result, which is recorded as the normal fluctuation amplitude coefficient range of the corresponding time segment.

[0069] Furthermore, obtain the standard range interval of each operating parameter of each component within the hardware through the Internet. At the same time, use the same time segments as the normal fluctuation amplitude coefficient range to divide each operating parameter data into several parameter data segments;

[0070] Then, through the standard range interval of each operating parameter, determine whether each operating parameter data of each device test event is within the corresponding standard range interval in each time segment. If it is, set a normal label for the parameter data segment in the corresponding time segment, otherwise, record it as an abnormal label element;

[0071] According to the number of components included in each hardware, set multiple component nodes for each hardware node on the event hardware topology diagram. At the same time, according to the parameter data segments of the components in each time segment, set a dynamic state matrix for each component node. The dynamic state matrix is expressed as [x1, ……, x j , where x j represents the j-th type of parameter data segment, and j is an integer greater than 1;

[0072] It should be noted that each parameter data segment in the dynamic state matrix changes synchronously with the change of the time segment;

[0073] According to the time segment sequence and the data flow line directions between each hardware node on the event hardware topology diagram, extract the abnormal label elements from each dynamic state matrix associated with the hardware nodes with data flow lines in sequence, and merge them to generate a parameter abnormal matrix;

[0074] It should be noted that in the parameter abnormal matrix, the abnormal label elements from the same dynamic state matrix are located in the same column, and the abnormal label elements from different dynamic state matrices are located in different columns;

[0075] Retrieve the interface transmission signals and the normal fluctuation amplitude coefficient ranges generated simultaneously in association with each operating parameter data, and then determine whether there is a part that exceeds the normal fluctuation amplitude coefficient range in each time segment for the interface transmission signals;

[0076] If not, skip the corresponding time segment. If so, intercept the interface transmission signal segment that exceeds the normal fluctuation amplitude coefficient range and record it as an abnormal signal segment;

[0077] Repeat the above operation of obtaining the contribution rate scores, and then obtain the characteristic relationship matrix between each hardware under different device test events;

[0078] The process of obtaining the characteristic relationship matrix includes:

[0079] Subtract the absolute value of each abnormal label element in the parameter abnormal matrix from the closest value in the corresponding standard range interval in a decreasing manner, and then update each abnormal label element in the parameter abnormal matrix. Then, convert the abnormal label elements in each column of the parameter abnormal matrix into a standard normal distribution form with a mean of 0 and a variance of 1, and obtain the parameter covariance matrix corresponding to the parameter abnormal matrix in the standard normal distribution form;

[0080] Divide a number of time nodes within the time segment, obtain the abnormal peaks of the abnormal signal segments at each time node, and then use the abnormal peaks as the influence result values at each time node, and each element in the parameter covariance matrix at each time node as the influence guiding value to establish the corresponding influence relationship equation;

[0081] Furthermore, according to the parameter operation data and interface transmission signals of different device test events, perform several rounds of iteration on the influence relationship equations for different types of component elements and operating parameter types, and obtain the characteristic relationship matrix based on the iteration results. In the characteristic relationship matrix, the same column represents the relationship parameters of multiple parameters of the same component element, and different columns correspond to the relationship parameters of different component elements;

[0082] Repeat the above operation of generating the characteristic relationship matrix, and then obtain multiple characteristic relationship matrices of different component elements between each hardware in each device test event, and send all the characteristic relationship matrices to the fault analysis and location module.

[0083] In this embodiment, the fault analysis and location module includes:

[0084] In the process of using the hardware operation data acquisition module to obtain operation parameter data and interface transmission signals, the device to be detected is made to execute various device test events in sequence, and after each device test event ends, all the test operation parameter data and test interface transmission signals are uploaded to the fault analysis and location module;

[0085] According to the normal fluctuation amplitude coefficient ranges corresponding to each device test event, it is judged whether there is a part exceeding the normal fluctuation amplitude coefficient range in each test interface transmission signal in each time period. If so, the exceeding part is intercepted and recorded as an abnormal test signal segment; otherwise, the test interface transmission signal in the corresponding time period is ignored. If it is judged that there is no abnormal test signal segment in each time period, the next pair of hardware nodes is detected;

[0086] At the same time, according to the standard range intervals of each operation parameter, it is judged whether there is any abnormality in each test operation parameter data, and the abnormal data intervals are marked in the test operation parameter data according to the judgment results;

[0087] Map each abnormal test signal segment and abnormal data interval to the event hardware topology diagram in sequence according to the hardware corresponding relationship, and then call the corresponding characteristic relationship matrix according to the types of device test events and hardware types;

[0088] Match the characteristic relationship matrix according to the types of operation parameters corresponding to the abnormal data intervals, and then obtain the expected abnormal test signal segments according to the elements in the matched characteristic relationship matrix and the time periods when the abnormal data intervals appear;

[0089] According to the time sequence, map the expected abnormal test signal segments and abnormal test segments in each time period to the same two-dimensional coordinate system. First, judge whether each expected abnormal test signal segment and abnormal test segment correspond one by one in each time period;

[0090] If it is judged that they do not correspond one by one, then judge again whether the abnormal test segments appear alone in a time period. If so, it is judged that there is an abnormality in the data transmission protocol of the interface circuit between the corresponding hardware;

[0091] If it is judged that they correspond one by one, or it is judged that there are no abnormal test segments appearing alone in a time period, then it is judged that there is an abnormality in the constituent elements of the corresponding hardware.

[0092] The above are only the preferred embodiments of the present invention, and do not impose any form of limitation on the present invention. Although the present invention has been disclosed above with the preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments with equivalent changes within the scope of the technical solution of the present invention. However, as long as it does not depart from the content of the technical solution of the present invention, any indirect modification, equivalent change and modification made to the above embodiments based on the technical essence 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 the test interface transmission signal executed by the device to be detected, 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 the device to be detected has abnormal components or abnormal data transmission protocol; 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, and 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 hardwares ends; 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; 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; Normally distribute the fluctuation amplitude coefficient of each interface transmission signal in each time segment, select the fluctuation amplitude coefficient value corresponding to the center position of the normal distribution result, and record it as the normal fluctuation amplitude coefficient range of the corresponding time segment; 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 in each time segment is 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; 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 correlate the generated interface transmission signal and 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 according to the determination result; 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.

2. The interface circuit remote testing system based on virtual instrument technology according to claim 1 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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