Management System Data Processing for Startup Troubleshooting
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Solution Overview
Problem
During system startup, long startup times due to abnormalities in certain modules hinder operation efficiency, requiring manual troubleshooting that is time-consuming and inefficient.
Innovation Solution
A data processing method and apparatus that enable target modules, collect operation data of sub-modules via a USB over LAN, sort the data by startup time, and output the dataset, automating the troubleshooting process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual troubleshooting is performed to determine internal causes of long startup time, then the startup time can be diagnosed, but the processing efficiency is reduced due to time-consuming manual operations
Solution Approach 1:
The system performs self-diagnosis by automatically collecting operation data from sub-modules and analyzing startup time issues without requiring technician intervention. The management system enables target modules, collects data automatically, and identifies abnormal sub-modules, allowing the system to troubleshoot itself.
Solution Approach 2:
Manual troubleshooting operations are replaced by an automated data collection and analysis system. The management system uses software-based data collection through USB over LAN and automated analysis algorithms to substitute the mechanical manual troubleshooting process, thereby improving processing efficiency while maintaining diagnostic accuracy.
2Loss of information
If operation data is collected manually during troubleshooting, then startup time can be analyzed, but the time required for data collection increases due to large data volume and sequential collection process
Solution Approach 1:
The management system pre-configures data collection paths and enables target modules before startup. Operation data is collected automatically during the startup process itself, rather than requiring separate post-startup analysis. This preliminary automation of data collection significantly reduces the time required while ensuring complete data capture.
Solution Approach 2:
Data collection occurs continuously during the normal startup process rather than requiring separate manual collection steps. The system collects operation data from sub-modules in real-time as they execute programs, ensuring no data is lost while eliminating idle collection time. The useful action of system startup simultaneously performs the useful action of data collection.
Data Source
AI summary
A data processing method, applied to a management system, includes enabling target modules of a target system, collecting operation data of at least one sub-module in the target system according to a first target path in response to the target system being in a successful startup status, sorting the collected operation data according to the startup time to obtain a target dataset, and outputting the target dataset. Each target module of the target modules is an operation module for starting the target system. Each sub-module of the at least one sub-module is configured to run a part or all of a program of a target module to which the sub-module belongs. The first target path at least includes a USB over LAN. The operation data is at least used to represent startup time of the sub-module.