Computer repair control method and system

Abstract

The invention discloses a computer repair control method and system, and relates to the technical field of computer repair control, and the method comprises the steps: obtaining repair control cases under different computer systems and software environments, and constructing a repair control case database; matching the characteristics of the current computer system and the software environment with the repair control case database, and further determining a monitoring mode; obtaining computer monitoring state parameters, and setting a monitoring threshold value based on the current real-time state of the computer and user requirements; comparing the computer monitoring state parameters with a monitoring threshold value, and judging whether a current computer system and a current software environment have faults or not; classifying faults identified by the current computer system and the software environment, and automatically matching or generating fault repair control measures of the current computer system and the software environment from the repair control case database according to a classification result. Rapid fault identification and automatic repair are realized, and the efficiency and accuracy of computer maintenance are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of computer repair control, and specifically provides a computer repair control method and system. Background Art

[0002] Modern computer system architectures have become increasingly complex, covering a variety of hardware components (such as CPUs, GPUs, memory, hard drives, etc.) and different levels of software (operating systems, drivers, applications, etc.). The interaction relationships between these components and software are intricate, which greatly increases the likelihood of failures and makes it extremely difficult to locate the causes of failures.

[0003] In the prior art, when encountering computer failures, technicians often need to analyze the causes of failures from scratch and try different repair methods. There is a lack of a unified case library for reference, resulting in a long repair process. Moreover, due to the lack of systematic classification and matching of failures, the repair methods may not be precise enough, and effective repair measures cannot be taken for specific failure types, increasing the difficulty and time cost of repair. Traditional monitoring methods usually adopt fixed monitoring strategies and thresholds, without considering the differences in computer systems and software environments as well as the personalized needs of users. For computers with different configurations and usage scenarios, fixed monitoring strategies may not be able to detect failures in a timely manner or may frequently issue unnecessary alarms, affecting the monitoring effect and user experience. At the same time, computer systems and software environments are dynamically changing, and the monitoring methods of the prior art are difficult to adapt to these changes in real time, resulting in inaccurate monitoring results and the inability to detect potential failure hazards in a timely manner.

[0004] Therefore, in view of the above problems, there is an urgent need for a computer repair control method and system. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a computer repair control method and system, which solves the problem of traditional computer failure repair relying on manual labor and low efficiency.

[0006] To achieve the above object, the present invention is realized through the following technical solutions: A computer repair control method and system, comprising the following steps: obtaining repair control cases under different computer systems and software environments, and constructing a repair control case database; detecting the characteristics of the current computer system and software environment, and matching the characteristics of the current computer system and software environment with the repair control case database, so as to determine the monitoring method; monitoring the current computer system and software environment based on the determined monitoring method to obtain computer monitoring status parameters, and setting a monitoring threshold based on the real-time status of the current computer and user requirements; comparing the computer monitoring status parameters with the monitoring threshold to determine whether there is a fault in the current computer system and software environment; classifying the faults identified in the current computer system and software environment, and automatically matching or generating fault repair control measures for the current computer system and software environment from the repair control case database according to the classification results.

[0007] Further, the specific analysis of obtaining repair control cases under different computer systems and software environments and constructing a repair control case database is as follows: collecting repair control case data under different computer systems and software environments based on multiple data sources, and the multiple data sources include but are not limited to computer system logs, software error reports, technical support records, online technical forums and communities; for each case, collecting computer system and software environment related parameters, including operating system type, version, installation time, CPU model, memory capacity, storage device, graphics card type and size, network connection type, IP address, subnet mask, gateway, network bandwidth, network latency, installed software list, software version, installation time, update time, software startup time, response time, system resource occupation situation and error prompt information during operation; for each case, collecting repair control related parameters, including the time and frequency of the fault occurrence, the specific manifestation of the fault, the operation steps when the fault occurs, the repair methods taken, the tools and software used during the repair process, and the repair effect evaluation; cleaning the collected computer system and software environment related parameters and repair control related parameters to remove duplicate, incorrect or incomplete data records; classifying the cleaned data according to the computer system type, software type and fault type, and labeling key information for each case data, and the key information includes a fault type label and a repair measure label; establishing a repair control case database, storing the classified and labeled data into the repair control case database, and designing the structure of the repair control case database, and the structure of the repair control case database includes the definition of data tables, the setting of fields and the creation of indexes; monitoring the generation of new repair control case data, and adding the new repair control case data to the repair control case database.

[0008] Further, detect the characteristics of the current computer system and software environment, and match the characteristics of the current computer system and software environment with the repair control case database. Then, the specific analysis of the monitoring method is as follows: collect the basic information, hardware configuration information, and network configuration information of the current computer system. The basic information includes the operating system type, version, and installation time. The hardware configuration information includes the CPU model, memory capacity, storage device, and graphics card type and size. The network configuration information includes the network connection type, IP address, subnet mask, gateway, network bandwidth, network latency, installed software list, software version, installation time, update time, software startup time, response time, system resource occupancy, and error prompt information during operation. Combine the collected basic information, hardware configuration information, and network configuration information of the current computer system to form the characteristics of the current computer system and software environment. Then, perform standardization processing on the characteristics of the current computer system and software environment to make the format of the characteristics of the current computer system and software environment consistent with the data format in the repair control case database. Based on string matching, compare the standardized characteristics of the current computer system and software environment with the cases in the repair control case database to identify whether there are cases with a similarity greater than the similarity threshold. For the cases with a similarity greater than the similarity threshold, call the monitoring method corresponding to the case, and monitor the current computer system and software environment according to the monitoring method of the called case. The monitoring methods include, but are not limited to, regularly collecting system performance indicators, real-time monitoring of software running status, and setting trigger alarms for specific events. For the situation where no cases with a similarity greater than the similarity threshold are identified in the repair control case database, match the personalized monitoring method.

[0009] Further, the specific analysis of matching the personalized monitoring method is as follows: for the situation where no cases with a similarity greater than the similarity threshold are identified in the repair control case database, obtain the importance parameters of different systems and software environments of the current computer. The importance parameters include data sensitivity, business impact, and performance stability. Take the mean values of the data sensitivity, business impact, and performance stability of different systems and software environments of the current computer as the importance evaluation index of different systems and software environments. According to the size of the importance evaluation index of different systems and software environments, automatically match the monitoring periods of different systems and software environments.

[0010] Further, the specific analysis of monitoring the current computer system and software environment based on the determined monitoring method, obtaining computer monitoring status parameters, and setting monitoring thresholds based on the real-time status of the current computer and user requirements is as follows: Obtain computer monitoring status parameters, which include but are not limited to CPU usage rate, memory occupancy rate, disk I / O rate, network bandwidth occupancy rate, and response speed; obtain the user requirement values of each computer monitoring status parameter, and the user requirement values of each computer monitoring status parameter include but are not limited to the expected value of CPU usage rate, the expected value of memory occupancy rate, the expected value of disk I / O rate, the expected value of network bandwidth occupancy rate, and the expected value of response speed; obtain the historical data of each computer monitoring status parameter, and then obtain the historical average value of each computer monitoring status parameter. The historical average values of each computer monitoring status parameter include but are not limited to the historical average value of CPU usage rate, the historical average value of memory occupancy rate, the historical average value of disk I / O rate, the historical average value of network bandwidth occupancy rate, and the historical average value of response speed; take the mean of the user requirement value and the historical average value of each computer monitoring status parameter as the monitoring threshold of each computer monitoring status parameter. The monitoring thresholds of each computer monitoring status parameter include but are not limited to the monitoring threshold of CPU usage rate, the monitoring threshold of memory occupancy rate, the monitoring threshold of disk I / O rate, the monitoring threshold of network bandwidth occupancy rate, and the monitoring threshold of response speed.

[0011] Further, the specific analysis of comparing the computer monitoring status parameters with the monitoring thresholds to determine whether there is a fault in the current computer system and software environment is as follows: Set a diagnostic cycle, and then compare the computer monitoring status parameters at each time node within the diagnostic cycle with the monitoring thresholds of each computer monitoring status parameter respectively. When any computer monitoring status parameter at each time node within the diagnostic cycle is lower than the monitoring threshold, trigger a fault alarm and determine that there is a fault in the current computer system and software environment.

[0012] Further, the specific analysis of classifying the faults identified in the current computer system and software environment and automatically matching or generating the fault repair control measures for the current computer system and software environment based on the classification results is as follows: When a fault alarm is detected, obtain the fault-related parameters identified in the current computer system and software environment, where the fault-related parameters include the fault nature, the fault impact range, and the fault severity; Combine the fault nature, the fault impact range, and the fault severity to assign a unique identifier to the fault, and the unique identifier assigned to the fault is specifically a fault label composed of the fault nature and the mean value of the fault impact range and the fault severity; Based on the fault label as the classification basis, then compare the fault label with the case faults in the repair control case database based on keyword matching and feature vectors, and select the cases with a similarity greater than the preset threshold as the matching repair cases; Extract the operation steps, the repair methods adopted, and the tools used during the repair corresponding to the occurrence of the fault in the matching repair cases, and then generate the fault repair control measures for the current computer system and software environment based on the extracted operation steps, the repair methods adopted, and the tools used during the repair; In the case where no similarity greater than the preset threshold is screened out, trigger an artificial repair prompt alarm and visually display the fault label.

[0013] A computer repair control method system, applying the above-mentioned computer repair control method, includes: a case database construction module, configured to obtain repair control cases under different computer systems and software environments and construct a repair control case database; an environment feature matching and monitoring method determination module, configured to detect the features of the current computer system and software environment and match the features of the current computer system and software environment with the repair control case database, and then determine the monitoring method; a monitoring and threshold setting module, configured to monitor the current computer system and software environment based on the determined monitoring method, obtain computer monitoring status parameters, and set a monitoring threshold based on the real-time status of the current computer and user requirements; a fault judgment module, configured to compare the computer monitoring status parameters with the monitoring threshold to determine whether there is a fault in the current computer system and software environment; a fault classification and repair measure matching module, configured to classify the faults identified in the current computer system and software environment and automatically match or generate the fault repair control measures for the current computer system and software environment according to the classification results.

[0014] The present invention has the following beneficial effects:

[0015] The computer repair control method and system can, when encountering computer system or software failures, quickly match similar cases from the database, directly obtain verified repair measures, avoid the time consumption of re-exploring and trying different repair methods, and greatly shorten the time for fault repair. By classifying faults and matching repair measures according to the classification results, the repair plan is more targeted. Different types of faults have different causes and solutions, and accurate matching can improve the success rate of repair and reduce secondary faults caused by incorrect repair. By determining the monitoring method according to the characteristics of the current computer system and software environment, customized monitoring can be carried out for different computer configurations and usage scenarios. For example, for critical business systems, more frequent and comprehensive monitoring can be adopted, while for ordinary office computers, a relatively loose monitoring strategy can be adopted to improve the effectiveness and efficiency of monitoring. By setting monitoring thresholds based on the real-time state of the current computer and user requirements, the thresholds are more in line with the actual situation. Different users have different requirements for computer performance, and the real-time state is also constantly changing. Intelligent threshold setting can avoid misjudgment or missed judgment caused by fixed thresholds not adapting to the actual situation. By regularly monitoring the computer system and software environment and comparing the monitored state parameters with the thresholds, potential fault hazards can be detected in a timely manner, and measures can be taken to repair them before the faults occur, which can avoid the further deterioration of the faults, reduce system downtime, and improve the stability and reliability of the system. By recording the repair process and results in the case database and continuously enriching and updating the database content, as cases accumulate, the repair strategy will be continuously optimized, which can better handle various complex fault situations, further improve the stability and reliability of the system, reduce the impact of computer system and software failures on the normal use of users, and improve user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of a computer repair control method of the present invention.

[0017] Figure 2 It is a structural diagram of a computer repair control system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In the embodiments of the present application, a computer repair control method and system are adopted to achieve rapid fault identification and automated repair, improving the efficiency and accuracy of computer maintenance.

[0019] The general idea of the embodiments of this application is as follows: First, establish a repair control case database to accumulate fault repair experience in different computer systems and software environments; then use feature matching technology to determine an appropriate monitoring method according to the characteristics of the current computer system and software environment; next, monitor in real time and set reasonable monitoring thresholds to detect potential faults in a timely manner; finally, classify the identified faults and automatically match or intelligently generate corresponding repair control measures from the repair control case database to achieve fast response and efficient repair of faults.

[0020] Please refer to Figure 1 , an embodiment of the present invention provides a technical solution: A computer repair control method, comprising the following steps: obtaining repair control cases in different computer systems and software environments, and constructing a repair control case database; detecting the characteristics of the current computer system and software environment, and matching the characteristics of the current computer system and software environment with the repair control case database to determine a monitoring method; monitoring the current computer system and software environment based on the determined monitoring method to obtain computer monitoring status parameters, and setting a monitoring threshold based on the real-time status of the current computer and user requirements; comparing the computer monitoring status parameters with the monitoring threshold to determine whether there are faults in the current computer system and software environment; classifying the faults identified in the current computer system and software environment, and automatically matching or generating fault repair control measures for the current computer system and software environment according to the classification results.

[0021] Specifically, the specific analysis of obtaining repair control cases under different computer systems and software environments and constructing a repair control case database is as follows: Collect repair control case data under different computer systems and software environments based on multiple data sources. The multiple data sources include, but are not limited to, computer system logs, software error reports, technical support records, online technical forums, and communities. For each case, collect parameters related to the computer system and software environment, including the type of operating system, version, installation time, CPU model, memory capacity, storage device, graphics card type and size, network connection type, IP address, subnet mask, gateway, network bandwidth, network latency, list of installed software, software version, installation time, update time, software startup time, response time, system resource occupancy, and error prompt information during operation. For each case, collect parameters related to repair control, including the time and frequency of the fault occurrence, the specific manifestation of the fault, the operation steps when the fault occurs, the repair methods adopted, the tools and software used during the repair process, and the repair effect evaluation. Clean the collected parameters related to the computer system and software environment and the parameters related to repair control to remove duplicate, incorrect, or incomplete data records. Classify the cleaned data according to the computer system type, software type, and fault type, and label key information for each case data. The key information includes a fault type label and a repair measure label. Establish a repair control case database, store the classified and labeled data in the repair control case database, and design the structure of the repair control case database. The structure of the repair control case database includes the definition of data tables, the setting of fields, and the creation of indexes. Monitor the generation of new repair control case data and add the new repair control case data to the repair control case database.

[0022] In this implementation, the operating system type refers to the types of operating systems installed on a computer, such as Windows, Linux, macOS, etc. The architectures and operating mechanisms of different operating systems are different, and the fault manifestations and repair methods also vary; the operating system version is the specific operating system version number, such as Windows 10 21H2, Ubuntu 22.For 04 LTS and others, different versions may have different vulnerabilities and compatibility issues; the operating system installation time is the date when the operating system was installed, which can be used to judge the usage duration of the system and the problems that may have accumulated; the CPU model is the specific model that identifies the computer's central processing unit. CPUs of different models have different performance and characteristics, which may affect the operation and fault conditions of the system; the memory capacity is the size of the computer's memory. Insufficient memory may cause the system to run slowly or programs to crash; the storage device includes information such as the type (mechanical hard drive or solid-state drive) and capacity of the hard drive. The performance and health status of the storage device will affect the data read / write speed and the stability of the system; the type and size of the graphics card. For applications with high graphics processing requirements, poor graphics card performance may cause display anomalies; the network connection type includes Ethernet, Wi-Fi, cellular network, etc. Different network connection methods may face different network failures; the IP address, subnet mask, and gateway are the basic parameters of network configuration. Incorrect configuration may cause network connection problems; the network bandwidth represents the transmission rate of the network. Insufficient bandwidth may affect the usage experience of network applications; the network latency is the round-trip time of data packets from the sender to the receiver. Excessive latency may cause network applications to respond slowly; the list of installed software represents the names of all software installed on the computer. There may be compatibility issues between different software; the software version is the specific version number of the software. Software updates may fix known problems or introduce new ones; the software installation time and update time are specifically the dates when the software was installed and updated, which can be used to analyze the relationship between software failures and installation / update operations; the software startup time and response time reflect the performance of the software. Excessively long startup time or response time may indicate problems with the software; the system resources occupied by the software include resources such as CPU and memory occupied during software operation. Excessive resource occupancy may cause a decline in system performance; the error prompt information during software operation is an important clue for locating software failures. By analyzing the error information, the specific cause of the failure can be understood; the time and frequency of the failure occurrence are to record the time when the failure first occurred and the number of occurrences within a certain period, which helps to judge the urgency and stability of the failure; the specific manifestations of the failure are used to describe in detail the phenomena when the failure occurs, such as system blue screen, software crash, network connection interruption, etc., which are important bases for failure diagnosis; the operation steps when the failure occurs are used to understand the specific operations performed by the user before the failure occurred, which may be the cause of triggering the failure; the repair methods taken are to record the specific repair measures taken for this failure, such as reinstalling the software, updating the driver, etc.; the tools and software used during the repair process, such as antivirus software, system optimization tools, etc. The usage of these tools can provide reference for subsequent repairs; the repair effect evaluation is used to evaluate whether the repair measures have successfully solved the failure and whether the performance and stability of the system have returned to normal after the repair.

[0023] The type and version of the operating system are obtained through the system information tool provided by the system; the installation time of the operating system is obtained by viewing the system log or using a third-party tool; the CPU model is viewed through the task manager or the system information tool; the memory capacity is viewed in the system properties; the storage device is obtained through the disk management tool provided by the system or a third-party disk detection software; the type and size of the graphics card are viewed through the device manager; the network connection type is viewed through the Network and Sharing Center; the IP address, subnet mask, and gateway are viewed through the `ipconfig` command in the Command Prompt; the network bandwidth and network latency are identified using a network speed test tool; the list of installed software is viewed through "Programs and Features" in the Control Panel; the software version is viewed through the "About" interface or the help menu of the software itself; the installation time and update time of the software are obtained through the registry or the system log; the startup time and response time of the software are measured using a performance monitoring tool; the system resources occupied by the software are identified using the performance monitoring tool provided by the system or a third-party software; the error prompt information during the software operation is obtained by viewing the log file of the software; the time and frequency of the occurrence of the fault are obtained from the system log, software log, or user records; the specific manifestations of the fault are obtained by the user's description or by organizing the information in the system log and software error report; the operation steps when the fault occurs are obtained through user feedback or operation records; the repair methods adopted are specifically obtained from the specific operation steps taken by the technical personnel or the user who records; the tools and software used during the repair process are recorded according to the actual usage; the evaluation of the repair effect is carried out by checking the running status of the system, whether the functions of the software are normal, and whether the performance indicators are restored, etc.

[0024] By integrating the data from multiple data sources such as computer system logs, software error reports, technical support records, online technical forums, and communities, a rich variety of repair control cases can be obtained. Different data sources reflect the fault situations of the computer system and software environment from different perspectives, making the information covered by the case database more comprehensive and helping to analyze and solve various complex problems more accurately; cleaning the collected data to remove duplicate, incorrect, or incomplete data records ensures the quality and accuracy of the data in the case database. High-quality data is the basis for effective analysis and decision-making and can improve the reliability of subsequent fault diagnosis and repair; classifying the data according to the computer system type, software type, and fault type and annotating each case data with key information such as fault type labels and repair measure labels. This makes the structure of the case database clearer, facilitating the management and retrieval of data. When encountering a new fault, relevant cases can be quickly located, improving the efficiency of fault resolution.

[0025] Specifically, the characteristics of the current computer system and software environment are detected, and the characteristics of the current computer system and software environment are matched with the repair control case database. Furthermore, the specific analysis of the monitoring method is as follows: collect the basic information, hardware configuration information, and network configuration information of the current computer system. The basic information includes the type, version, and installation time of the operating system. The hardware configuration information includes the CPU model, memory capacity, storage device, and graphics card type and size. The network configuration information includes the network connection type, IP address, subnet mask, gateway, network bandwidth, network latency, list of installed software, software version, installation time, update time, software startup time, response time, system resource occupancy, and error prompt information during operation. Combine the collected basic information, hardware configuration information, and network configuration information of the current computer system to form the characteristics of the current computer system and software environment. Then, perform standardization processing on the characteristics of the current computer system and software environment to make the format of the characteristics of the current computer system and software environment consistent with the data format in the repair control case database. Based on string matching, compare the standardized characteristics of the current computer system and software environment with the cases in the repair control case database to identify whether there are cases with a similarity greater than the similarity threshold. For the cases with a similarity greater than the similarity threshold, call the monitoring method corresponding to the case, and monitor the current computer system and software environment according to the monitoring method of the called case. The monitoring methods include, but are not limited to, regularly collecting system performance indicators, real-time monitoring of software operation status, and setting trigger alarms for specific events. For the situation where no case with a similarity greater than the similarity threshold is identified in the repair control case database, match the personalized monitoring method.

[0026] In this implementation plan, the specific analysis of matching the personalized monitoring method is as follows: for the situation where no case with a similarity greater than the similarity threshold is identified in the repair control case database, obtain the importance parameters of different systems and software environments of the current computer. The importance parameters include data sensitivity, business impact, and performance stability. Take the average values of the data sensitivity, business impact, and performance stability of different systems and software environments of the current computer as the importance evaluation index of different systems and software environments. According to the size of the importance evaluation index of different systems and software environments, automatically match the monitoring periods of different systems and software environments.

[0027] The specific method of setting the similarity threshold is as follows: according to previous practical experience and expert knowledge, combined with a large amount of test data and actual cases, an initial similarity threshold is set. For example, after many experiments and verifications, it is found that when the feature similarity reaches 80%, the reference value of the case is high, and the similarity threshold can be set to 80%; a large number of cases in the repair control case database can also be analyzed, and the relationship between feature similarity and actual fault handling effect can be statistically analyzed. Through machine learning algorithms such as clustering analysis and regression analysis, a similarity threshold that can balance matching accuracy and recall rate can be found. For example, clustering algorithms are used to group cases according to feature similarity, and the fault handling success rates under different groups are analyzed. The similarity corresponding to the group with a higher success rate is selected as the similarity threshold; with the continuous updating and expansion of the case database and the emergence of new fault cases, the similarity threshold can also be regularly evaluated and adjusted. For example, when the feature difference between the new case and the existing case is large, the similarity threshold is appropriately lowered to increase the possibility of matching. When the case similarity in the case database is generally high, the similarity threshold is appropriately increased to improve the accuracy of matching.

[0028] Regular collection of system performance indicators specifically includes: collecting various performance indicators of the computer system, such as CPU usage, memory occupancy, disk I / O, etc., at preset time intervals, such as every minute, every hour or every day. By analyzing the changing trends of these performance indicators, the performance bottlenecks and potential problems of the system can be discovered in a timely manner. For example, if the CPU usage rate exceeds 80% for a long time, it may mean that the system load is too high and further investigation is needed, such as whether there is an abnormal process or software failure.

[0029] Real-time monitoring of software operation status means: continuously tracking the software operation status, including whether the software starts normally, whether it responds to operations, whether error information is generated, etc. Real-time monitoring can promptly detect software crashes, unresponsiveness and other problems, and take corresponding measures, such as restarting the software or notifying the administrator. For example, when a key business software is detected to be unresponsive, the system can automatically try to restart the software and record relevant information for subsequent analysis.

[0030] To set a trigger alarm for a specific event, you can define some specific events or conditions. When these events occur or the conditions are met, the system automatically triggers an alarm. These events may include system performance indicators exceeding a threshold, specific error codes in the software, network connection interruption, etc. For example, you can set an alarm to be triggered when the remaining disk space is less than 10%, reminding the administrator to clean up the disk or add storage devices in time.

[0031] Data sensitivity refers to the sensitivity level of the data processed by computer systems and software, that is, the degree of risk and impact that may be brought about by data leakage or damage. For example, data containing user personal privacy information, business secrets, financial data, etc. has a relatively high data sensitivity, while data such as public promotional materials and ordinary documents has a relatively low data sensitivity. Through data classification and tagging, the system administrator or data owner classifies the data, clarifies the sensitivity levels of different data, and records them in the system. Business impact refers to the importance of computer systems and software to business operations, that is, the degree of impact on business processes, business goals, and business outcomes when the system or software fails. For example, core business systems (such as financial transaction systems and e-commerce order processing systems) have a relatively high business impact, while some auxiliary office software (such as ordinary document editors) has a relatively low business impact. Specifically, by sorting out and analyzing the enterprise's business processes, the position and role of each system and software in the business process are determined, and their impact on the business is evaluated; Performance stability refers to the ability of computer systems and software to maintain stable operation within a certain period of time, that is, the frequency and degree of system and software failures or performance fluctuations. For example, a system or software that often crashes, freezes, or responds slowly has poor performance stability, while a system or software that runs stably for a long time and rarely fails has good performance stability. Through the analysis of historical failure records, the historical failure records of the system and software are viewed, the number of failures, frequency, and severity are counted, and its performance stability is evaluated.

[0032] By collecting multi-dimensional computer system and software environment characteristics and matching them with the case database, similar cases and corresponding monitoring methods can be quickly found, enabling precise monitoring of the current system and software. Once a failure occurs, the handling experience in the cases can be used for reference to improve the efficiency of failure handling; standardizing the processed feature data ensures compatibility with the case database, improves the accuracy and efficiency of matching, and avoids matching errors caused by data format differences; for situations where no similar cases can be found in the case database, by evaluating the importance parameters of the system and software environment and matching personalized monitoring methods, targeted monitoring can be carried out according to the characteristics and requirements of different systems and software, improving the effectiveness of monitoring and resource utilization efficiency; automatically matching the monitoring cycle based on the importance evaluation index enables systems and software with high importance to be monitored more frequently to detect potential problems in a timely manner, while systems and software with low importance can appropriately reduce the monitoring frequency to reduce unnecessary resource consumption.

[0033] Specifically, the specific analysis of monitoring the current computer system and software environment based on the determined monitoring method, obtaining computer monitoring status parameters, and setting monitoring thresholds based on the real-time status of the current computer and user requirements is as follows: Obtain computer monitoring status parameters, which include but are not limited to CPU usage rate, memory occupancy rate, disk I / O rate, network bandwidth occupancy rate, and response speed; obtain the user requirement values for each computer monitoring status parameter, and the user requirement values for each computer monitoring status parameter include but are not limited to the expected value of CPU usage rate, the expected value of memory occupancy rate, the expected value of disk I / O rate, the expected value of network bandwidth occupancy rate, and the expected value of response speed; obtain the historical data of each computer monitoring status parameter, and then obtain the historical average value of each computer monitoring status parameter. The historical average values of each computer monitoring status parameter include but are not limited to the historical average value of CPU usage rate, the historical average value of memory occupancy rate, the historical average value of disk I / O rate, the historical average value of network bandwidth occupancy rate, and the historical average value of response speed; take the average of the user requirement value and the historical average value of each computer monitoring status parameter as the monitoring threshold for each computer monitoring status parameter. The monitoring thresholds for each computer monitoring status parameter include but are not limited to the monitoring threshold of CPU usage rate, the monitoring threshold of memory occupancy rate, the monitoring threshold of disk I / O rate, the monitoring threshold of network bandwidth occupancy rate, and the monitoring threshold of response speed.

[0034] In this implementation plan, the specific analysis of comparing the computer monitoring status parameters with the monitoring thresholds to determine whether there are faults in the current computer system and software environment is as follows: Set a diagnostic cycle, and then compare each computer monitoring status parameter at each time node within the diagnostic cycle with the monitoring threshold of each computer monitoring status parameter respectively. When any computer monitoring status parameter at each time node within the diagnostic cycle is lower than the monitoring threshold, trigger a fault alarm and determine that there are faults in the current computer system and software environment.

[0035] CPU usage rate refers to the percentage of the amount of tasks being processed by the CPU at a certain moment in its total processing capacity, reflecting the busyness of the CPU, which can be viewed through the task manager; memory occupancy rate represents the proportion of the used memory space in the total memory space in the current system, reflecting the usage of memory resources, which can be viewed in the task manager; disk I / O rate refers to the amount of data read and written by the disk per unit time, reflecting the data transfer ability and busyness of the disk, which is monitored using the performance monitor; network bandwidth occupancy rate refers to the proportion of the bandwidth used by the current network in the total available bandwidth, used to measure the usage of the network, and the network usage situation can be viewed using the resource monitor; response speed usually refers to the time for the system or application to respond to user operations, reflecting the timeliness and interactivity of the system, which is measured using the performance analysis function in the browser developer tools.

[0036] The user demand values for each computer monitoring status parameter are the values that the user expects the computer's monitoring status parameters to reach according to their own usage scenarios and requirements. For example, the user hopes that the CPU usage rate does not exceed 50% during normal operation, and the memory occupancy rate does not exceed 70%. Through the configuration interface provided by the system, the user can directly input the expected values for each monitoring status parameter.

[0037] By combining the user demand values and historical averages to set the monitoring thresholds, it not only takes into account the user's personalized expectations for the computer system performance but also refers to the historical operating conditions of the system, making the monitoring thresholds more reasonable and accurate, better reflecting the user's actual needs for the system, and avoiding the problem of unreasonable thresholds caused by relying solely on historical data or user subjective expectations. Based on the set diagnosis cycle, comparing the computer monitoring status parameters with the monitoring thresholds can promptly detect abnormal situations in the computer system and software environment. When the monitoring status parameter is lower than the monitoring threshold, a fault alarm is triggered, which helps to detect potential faults in advance, so as to take timely measures for repair, reduce the impact of faults on the normal operation of the system, and improve the reliability and stability of the system. Since the monitoring thresholds are dynamically generated based on user needs and historical data, as the computer system is used and user needs change, the monitoring thresholds can be adjusted accordingly, enabling the system to have better dynamic adaptability and maintaining an efficient and accurate monitoring effect for a long time.

[0038] Specifically, the classification of the faults identified in the current computer system and software environment, and the specific analysis of automatically matching or generating the fault repair control measures for the current computer system and software environment based on the classification results are as follows: When the trigger of the fault alarm is detected, obtain the fault-related parameters identified in the current computer system and software environment. The fault-related parameters include the nature of the fault, the scope of the fault impact, and the severity of the fault. Combine the nature of the fault, the scope of the fault impact, and the severity of the fault to assign a unique identifier to the fault. The unique identifier for the fault assignment is specifically a fault label composed of the nature of the fault and the average value of the scope of the fault impact and the severity of the fault. Based on the fault label as the classification basis, then compare the fault label with the case faults in the repair control case database through keyword matching and feature vectors, and screen out the cases with a similarity greater than the preset threshold as the matching repair cases. Extract the operation steps, repair methods, and tools used during the repair process corresponding to the occurrence of the fault in the matching repair cases, and then generate the fault repair control measures for the current computer system and software environment based on the extracted operation steps, repair methods, and tools used during the repair process. In the case where no cases with a similarity greater than the preset threshold are screened out, trigger an artificial repair prompt alarm and visually display the fault label.

[0039] In this implementation plan, the nature of a fault refers to the essential attribute of the fault. For example, it could be a hardware fault (such as a hard drive failure or a memory fault), a software fault (such as a program crash or a software conflict), a network fault (such as a network connection interruption or insufficient bandwidth), or a system configuration fault (such as incorrect parameter settings), etc. It is determined through system log analysis, observation of fault symptoms, and relevant diagnostic tools. For example, the appearance of a hardware driver error message in the system log may indicate a hardware fault; frequent software error reports related to specific software operations may be a software fault.

[0040] The scope of fault impact represents the degree and scope of the impact of a fault on the computer system and software environment. It can be divided into local faults (only affecting a certain software or a certain functional module), partial system faults (affecting multiple related software or partial functions of the system), and global faults (causing the entire computer system to be unable to operate normally). It is determined by checking the affected software, system functions, and user feedback. For example, if only a specific office software cannot be used properly, it may be a local fault; if multiple software that rely on the same service have problems, it may be a partial system fault; if the entire system cannot start or frequently freezes, it may be a global fault. The quantification of the specific scope of fault impact is as follows: it can be divided into several clear levels. For example, the local impact is level 1, where the fault only affects a specific component, software module, or function in the computer system and does not affect the normal operation of other parts. The partial system impact is level 2, where the fault affects multiple interrelated components or software in the computer system, resulting in limited partial system functions. The global impact is level 3, where the fault causes the entire computer system or critical business to be unable to operate normally. For example, when the operating system crashes and the computer cannot start, and all software and functions cannot be used. It can also be quantified according to the proportion of system components, software functions, or business processes affected by the fault. For example, if there are a total of 10 main functional modules in the computer system, and the fault causes 2 of them to be unable to work properly, then the scope of fault impact can be quantified as 20% (2÷10×100%). For a business process, if a business process consists of 5 steps and the fault causes 2 of them to be unable to be executed, then the scope of fault impact is 40% (2÷5×100%).

[0041] The severity of a fault specifically measures the harm caused by the fault to the business or users, and is divided into minor faults (with little impact on the business and no disruption to the normal work process), medium faults (resulting in partial restriction of business functions or a decrease in work efficiency), and severe faults (causing business interruption and significant losses). It is evaluated by considering business requirements, the scope of the fault's impact, and the duration of the fault. For example, if a small function of a software is unavailable but does not affect the main business operations, it may be a minor fault; if some core functions of the business system are not working properly and affect some business processes, it may be a medium fault; if the key business system is completely paralyzed and the business cannot be carried out, it may be a severe fault. The specific quantification of the severity of a fault can also be divided into several levels. For example, minor is level 1, medium is level 2, and severe is level 3. The severity can also be determined based on economic losses, time losses, or other quantifiable loss indicators caused by the fault. For example, calculate the amount of reduced business revenue due to the fault, the time cost required to repair the fault, the potential losses caused by data loss, etc. These loss values are classified according to certain rules. For example, economic losses below 1000 yuan are minor, those between 1000 yuan and 10,000 yuan are medium, and those above 10,000 yuan are severe.

[0042] The specific logical steps for comparing the fault label with the case faults in the fault repair control case database based on correlation word matching and feature vectors are as follows:

[0043] Clean the fault labels and the case fault descriptions in the case database, remove useless characters, unify the format, perform word segmentation on the text, split the fault labels and case fault descriptions into words or phrases, and treat the quantified numerical parts as special "words" to participate in subsequent operations together with other text information. The specific correlation word matching is as follows: construct a correlation word dictionary that includes fault-related words, quantified index-related words, and synonyms. For example, for the fault impact scope, the correlation words include "local", "partial system", "global", "percentage", etc.; for the fault severity, the correlation words can be "slight", "moderate", "severe", "loss", etc. Traverse each word in the fault labels and case fault descriptions to check if there is a correlation word match. When a correlation word related to a quantified index is matched, further compare whether the quantified values are similar. For example, if the fault impact scope in the fault label is "20%", and the case fault description mentions that "about 25% of the functions are affected", it can be regarded as having a certain match in the quantified index of the fault impact scope. Record the number and position of the matched words, and calculate the correlation word matching score based on the number and position of the matched words and the matching degree of the quantified index. The more matched words, the more critical the position, and the closer the quantified index, the higher the score. The specific feature vector analysis is as follows: use the bag-of-words model or TF-IDF algorithm to convert the fault labels and case fault descriptions into feature vectors. For the quantified index, represent its value as a feature dimension. For example, the percentage or level value of the fault impact scope, and the level value of the fault severity can all be used as separate feature dimensions. In the bag-of-words model, the value of the vector is the occurrence frequency of the word; in the TF-IDF algorithm, the value of the vector is determined by comprehensively considering the frequency of the word in the current text and its rarity in the entire corpus. The value of the quantified index is appropriately weighted according to its importance in the text, and then methods such as cosine similarity and Euclidean distance are used to calculate the similarity between the fault label feature vector and the case fault feature vector. When calculating, fully consider the influence of the quantified index feature dimension. For example, if the two feature vectors are highly similar in the text feature dimension and are also similar in the quantified index feature dimensions of the fault impact scope and severity, the overall similarity will be high. Perform a weighted sum of the correlation word matching score and the feature vector similarity score to obtain a comprehensive score. When determining the weights, the degree of emphasis on the correlation word matching and the feature vector similarity, as well as the influence weight of the quantified index in them, can be adjusted according to the actual situation. Sort the cases in the case database according to the comprehensive score, and select the cases with a comprehensive score greater than the preset threshold as the matching repair cases.

[0044] The specific method for obtaining the preset threshold is as follows: Based on past fault handling experience and a large amount of test data, an initial preset threshold is manually set by experts or technicians. For example, after multiple experiments and verifications, it is found that when the comprehensive score reaches 0.7, the matching cases have high reference value, and the preset threshold can be set to 0.7. It is also possible to analyze a large number of cases in the repair control case database, and statistically calculate the accuracy and recall rate of the matching cases under different thresholds. Accuracy refers to the proportion of truly effective cases among the matched cases, and recall rate refers to the proportion of cases that should actually be matched and are correctly matched. By adjusting the threshold, an optimal value that can balance accuracy and recall rate is found as the preset threshold. The cross-validation method in machine learning can be used to optimize the selection of the threshold; as the case database is continuously updated and expanded, and new fault cases appear, the preset threshold is regularly evaluated and adjusted. For example, when the difference between new cases and existing cases is large, the preset threshold is appropriately lowered to increase the possibility of matching. When the similarity of cases in the case database is generally high, the preset threshold is appropriately increased to improve the accuracy of matching.

[0045] By classifying faults and matching them with the repair control case database, similar fault cases and their corresponding repair measures can be quickly found, improving the efficiency of fault repair and avoiding the process of re-conducting complex fault troubleshooting and solution exploration every time a fault occurs; the entire fault matching and repair measure generation process is automated, reducing manual intervention, lowering labor costs and the possibility of human errors. After a fault is detected, the system can automatically search for solutions from the case database and quickly respond to the fault problem; when there are no cases in the database with a similarity greater than the preset threshold, an artificial repair prompt alarm is triggered and the fault label is visually displayed, providing clear fault information for manual intervention and facilitating the intervention of technicians to ensure that the fault can ultimately be resolved; as fault cases are continuously processed and the database is continuously updated, the repair control case database will be continuously enriched and improved, and new fault cases and corresponding repair measures will be added to the database, providing more references for future fault handling and forming a virtuous cycle of knowledge accumulation and optimization.

[0046] Please refer to Figure 2, a computer repair control method system, applying the above-mentioned computer repair control method, includes: a case database construction module, which is used to obtain repair control cases under different computer systems and software environments and construct a repair control case database; an environment feature matching and monitoring method determination module, which is used to detect the features of the current computer system and software environment, match the features of the current computer system and software environment with the repair control case database, and then determine the monitoring method; a monitoring and threshold setting module, which is used to monitor the current computer system and software environment based on the determined monitoring method, obtain computer monitoring status parameters, and set monitoring thresholds based on the real-time status of the current computer and user requirements; a fault judgment module, which is used to compare the computer monitoring status parameters with the monitoring thresholds to judge whether there are faults in the current computer system and software environment; a fault classification and repair measure matching module, which is used to classify the faults identified in the current computer system and software environment, and automatically match or generate fault repair control measures for the current computer system and software environment according to the classification results.

[0047] In summary, the present application has at least the following effects:

[0048] By constructing a repair control case database and performing intelligent matching based on the characteristics of the current computer system and software environment, the applicable fault repair control measures can be quickly located, significantly shortening the time for fault troubleshooting and repair; by using real-time monitoring and setting reasonable monitoring thresholds, the abnormal states of the computer system and software environment can be accurately captured, potential faults can be identified in a timely manner, and further losses caused by the development of faults can be avoided; by automatically matching or generating repair control measures according to the fault classification results, manual intervention is reduced, the intelligent level of fault repair is improved, and at the same time, the demand for professional technical personnel is reduced; through timely and effective fault repair, the stability and reliability of the computer system and software environment can be significantly improved, and the continuity of business and the integrity of data can be guaranteed.

[0049] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods and systems. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0050] The present invention is described with reference to the flowcharts and block diagrams of methods and systems according to embodiments of the present invention. It should be understood that each flow and combination of blocks in the flowcharts and block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and block diagrams Figure 1 or multiple blocks.

[0051] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and block diagrams Figure 1 or multiple blocks.

[0052] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and block diagrams Figure 1 or multiple blocks.

[0053] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0054] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A computer repair control method, characterized in that: The following steps are involved: Obtain repair control cases in different computer systems and software environments, and build a repair control case database; Detecting the characteristics of the current computer system and software environment, and matching the characteristics of the current computer system and software environment with the repair control case database, thereby determining a monitoring method; Monitor the current computer system and software environment based on the determined monitoring method, obtain computer monitoring status parameters, and set monitoring thresholds based on the current real-time status of the computer and user needs; Compare the computer monitoring status parameters with the monitoring thresholds to determine whether there are faults in the current computer system and software environment; Classify the faults identified in the current computer system and software environment, and automatically match or generate fault repair control measures for the current computer system and software environment from the repair control case database based on the classification results.

2. A computer repair control method according to claim 1, characterized in that: The specific analysis of obtaining repair control cases in different computer systems and software environments and building a repair control case database is as follows: Collecting repair control case data in different computer systems and software environments based on multiple data sources, including but not limited to computer system logs, software error reports, technical support records, online technical forums and communities; For each case, collect computer system and software environment parameters, including operating system type, version, installation time, CPU model, memory capacity, storage device, graphics card type and size, network connection type, IP address, subnet mask, gateway, network bandwidth, network latency, installed software list, software version, installation time, update time, software startup time, response time, system resource usage, and error information during operation; For each case, collect the parameters related to repair control, including the time and frequency of the fault, the specific manifestation of the fault, the operation steps when the fault occurs, the repair method adopted, the tools and software used in the repair process, and the evaluation of the repair effect; Clean the collected computer system and software environment related parameters and repair control related parameters to remove duplicate, erroneous or incomplete data records; Classify the cleaned data according to computer system type, software type and fault type, and annotate key information for each case data, wherein the key information includes a fault type label and a repair measure label; Establish a repair control case database, store the classified and annotated data in the repair control case database, and design the structure of the repair control case database, which includes the definition of data tables, the setting of fields, and the creation of indexes; Monitor the generation of new repair control case data and add the new repair control case data to the repair control case database.

3. A computer repair control method according to claim 1, characterized in that: Detect the characteristics of the current computer system and software environment, and match the characteristics of the current computer system and software environment with the repair control case database, and then determine the specific analysis of the monitoring method as follows: Collect basic information, hardware configuration information and network configuration information of the current computer system. Basic information includes operating system type, version and installation time. Hardware configuration information includes CPU model, memory capacity, storage device, graphics card type and size. Network configuration information includes network connection type, IP address, subnet mask, gateway, network bandwidth, network latency, installed software list, software version, installation time, update time, software startup time, response time, system resource usage and error information during operation. The basic information, hardware configuration information and network configuration information of the current computer system collected are combined to form the characteristics of the current computer system and software environment, and then the characteristics of the current computer system and software environment are standardized so that the characteristic format of the current computer system and software environment is consistent with the data format in the repair control case database; Based on string matching, the standardized features of the current computer system and software environment are compared with the cases in the repair control case database to identify whether there are cases with a similarity greater than a similarity threshold; For case situations where the similarity is greater than the similarity threshold, the monitoring method corresponding to the case is called, and the current computer system and software environment are monitored according to the monitoring method of the called case. The monitoring method includes but is not limited to regularly collecting system performance indicators, real-time monitoring of software running status, and setting trigger alarms for specific events; For situations where a case with a similarity greater than a similarity threshold has not been identified in the repair control case database, a personalized monitoring method is matched.

4. A computer repair control method according to claim 3, characterized in that: The specific analysis of the matching personalized monitoring method is as follows: For a situation where no case with a similarity greater than a similarity threshold has been identified in the repair control case database, importance parameters of different systems and software environments of the current computer are obtained, wherein the importance parameters include data sensitivity, business impact, and performance stability; The average values ​​of data sensitivity, business impact, and performance stability of different current computer systems and software environments are taken as the importance assessment index of different systems and software environments; Automatically match the monitoring cycles of different systems and software environments based on their importance assessment indexes.

5. A computer repair control method according to claim 1, characterized in that: Based on the determined monitoring method, the current computer system and software environment are monitored to obtain computer monitoring status parameters, and the specific analysis of setting monitoring thresholds based on the current computer's real-time status and user needs is as follows: Acquire computer monitoring status parameters, which include but are not limited to CPU usage, memory occupancy, disk I / O rate, network bandwidth occupancy, and response speed; Obtaining user demand values ​​of various computer monitoring status parameters, wherein the user demand values ​​of various computer monitoring status parameters include but are not limited to expected values ​​of CPU usage, expected values ​​of memory occupancy, expected values ​​of disk I / O rate, expected values ​​of network bandwidth occupancy, and expected values ​​of response speed; Obtaining historical data of each computer monitoring status parameter, and then obtaining a historical average value of each computer monitoring status parameter, wherein the historical average value of each computer monitoring status parameter includes but is not limited to a historical average value of CPU usage, a historical average value of memory occupancy, a historical average value of disk I / O rate, a historical average value of network bandwidth occupancy, and a historical average value of response speed; The average of the user demand value and the historical average value of each computer monitoring status parameter is marked as the monitoring threshold of each computer monitoring status parameter. The monitoring threshold of each computer monitoring status parameter includes but is not limited to the monitoring threshold of CPU usage, the monitoring threshold of memory occupancy, the monitoring threshold of disk I / O rate, the monitoring threshold of network bandwidth occupancy and the monitoring threshold of response speed.

6. A computer repair control method according to claim 5, characterized in that: Compare the computer monitoring status parameters with the monitoring thresholds to determine whether there are faults in the current computer system and software environment. The specific analysis is as follows: A diagnostic cycle is set, and then each computer monitoring status parameter at each time node within the diagnostic cycle is compared with the monitoring threshold of each computer monitoring status parameter. When any computer monitoring status parameter at each time node within the diagnostic cycle is lower than the monitoring threshold, a fault alarm is triggered, and it is determined that there is a fault in the current computer system and software environment.

7. A computer repair control method according to claim 5, characterized in that: The specific analysis of classifying the faults identified in the current computer system and software environment and automatically matching or generating fault repair control measures for the current computer system and software environment from the repair control case database based on the classification results is as follows: When the triggering of the fault alarm is detected, the fault-related parameters identified by the current computer system and software environment are obtained, wherein the fault-related parameters include the nature of the fault, the scope of the fault impact, and the severity of the fault; A unique identifier is assigned to the fault in combination with the fault nature, the fault impact range and the fault severity. The unique identifier assigned to the fault is specifically a fault label composed of the fault nature, the fault impact range and the average value of the fault severity. Based on the fault label as the classification basis, the fault label is compared with the case faults in the repair control case database based on the associated word matching and feature vector, and the cases with similarity greater than the preset threshold are selected as matching repair cases; Extract the operation steps, repair methods and tools used in the repair process when the corresponding fault occurs in the matching repair case, and then generate the fault repair control measures for the current computer system and software environment based on the extracted operation steps, repair methods and tools used in the repair process when the fault occurs; For situations where the screening does not exist and the similarity is greater than the preset threshold, a manual repair prompt alarm is triggered and the fault label is visualized.

8. A computer repair control system, applying a computer repair control method according to any one of claims 1 to 7, characterized in that: include: A case database construction module is used to obtain repair control cases in different computer systems and software environments and to construct a repair control case database; An environment feature matching and monitoring method determination module, used to detect the features of the current computer system and software environment, and match the features of the current computer system and software environment with the repair control case database, and then determine the monitoring method; A monitoring and threshold setting module, which is used to monitor the current computer system and software environment based on a determined monitoring method, obtain computer monitoring status parameters, and set monitoring thresholds based on the current real-time status of the computer and user needs; A fault judgment module is used to compare the computer monitoring status parameters with the monitoring threshold to determine whether there is a fault in the current computer system and software environment; The fault classification and repair measure matching module is used to classify the faults identified by the current computer system and software environment, and automatically match or generate fault repair control measures for the current computer system and software environment from the repair control case database based on the classification results.

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