System-State Monitoring via Operating Mode Deviation Detection
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Solution Overview
Problem
Existing system-state monitoring mechanisms fail to detect changes in a system's running rules, such as performance degradation due to equipment aging or process reformation, even when parameter values remain within normal ranges, necessitating a method to timely adjust supporting services.
Innovation Solution
A system-state monitoring method and device that determine a reference running mode by analyzing historical data, comparing it with the current running mode using similarity measurements between graph groups, and adjusting based on weight considerations to identify deviations and improve system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional parameter-based monitoring is used, then the system can identify when parameters exceed normal ranges, but it cannot detect changes in running rules when parameters remain within normal ranges
Solution Approach 1:
The patent transforms the monitoring approach from checking individual parameter values to analyzing the distribution characteristics of parameters. By extracting distribution parameters (mean, variance, skewness, kurtosis) from running data and comparing their changes, the system can detect running rule changes even when parameters stay within normal ranges. This resolves the contradiction by changing what is being monitored from raw parameters to distribution characteristics of parameters.
2Device complexity
If the system monitors only whether parameters are within normal ranges, then the monitoring mechanism is simple, but it fails to detect performance degradation due to equipment aging or process reformation
Solution Approach 1:
The patent segments the monitoring process into distinct stages: data collection, distribution parameter extraction, change detection, and cause analysis. By dividing the monitoring mechanism into modular components, the system achieves higher detection accuracy without creating an overly complex monolithic structure. Each segment handles a specific aspect of the monitoring task, making the overall system manageable and effective.
Solution Approach 2:
The patent introduces distribution parameters as intermediary variables between raw running parameters and detection results. Instead of directly comparing raw parameters, the system extracts distribution parameters (mean, variance, etc.) as intermediaries that capture the underlying running rules. These intermediaries enable detection of subtle changes that would be invisible in raw parameter comparisons.
3Measurement precision
If the system uses detailed distribution parameter analysis, then it can accurately detect running rule changes, but the computational complexity increases
Solution Approach 1:
The patent extracts only the essential distribution parameters (mean, variance, skewness, kurtosis) needed to characterize running rules, rather than analyzing all possible statistical properties. By selecting and extracting only the most relevant features, the system achieves accurate change detection while keeping computational complexity manageable. This selective extraction avoids the need for comprehensive but computationally expensive analysis.
Data Source
AI summary
At least some example embodiments provide a system-state monitoring method and device and a storage medium. The method includes determining a standard operation mode of a system, the standard operation mode including a plurality of operation states of the system in a unit time period. The method further includes determining, according to current operation data of the system, a current operation mode of the system and determining, by comparing the current operation mode with the standard operation mode, whether or not the system is in the standard operation mode. The plurality of operation states of the system are determined to be the standard operation mode, such that changes in system operation patterns can be readily detected, thereby facilitating a timely adjustment of the monitored system or peripheral mechanisms in cooperation therewith and improving system performance.