Condition Monitoring Analysis Timing for Real-Time Anomaly Detection
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Solution Overview
Problem
Existing condition monitoring systems lack real-time processing capabilities, leading to delays in anomaly detection and response due to non-real-time analysis and diagnosis processes.
Innovation Solution
A condition monitoring system that sets measurement and analysis conditions based on the time required for analysis and diagnosis processes, ensuring they do not exceed the measurement interval, using a data analyzer to calculate and adjust these conditions to maintain real-time processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If real-time analysis and diagnosis processes are performed on measurement data, then responsiveness of anomaly detection is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary setup of measurement conditions (sampling frequency, measurement interval) and analysis conditions (analysis method, calculation interval) before real-time monitoring begins. These pre-configured conditions ensure that the analysis process can operate in real-time without requiring complex dynamic adjustments during operation, thus reducing system complexity while maintaining responsiveness.
Solution Approach 2:
The system dynamically adjusts parameters such as measurement interval and analysis calculation interval based on the relationship between data acquisition speed and processing speed. By changing these parameters adaptively, the system maintains real-time processing capability without requiring overly complex hardware or algorithms, thereby resolving the contradiction between response time and system complexity.
2Loss of time
If measurement interval is reduced to improve real-time monitoring, then anomaly detection responsiveness is improved, but data processing load increases
Solution Approach 1:
The system dynamically adjusts the measurement interval and analysis calculation interval based on real-time conditions. When the facility operates normally, longer intervals reduce processing load. When anomalies are detected or suspected, the system automatically shortens intervals to improve detection responsiveness. This dynamic adjustment resolves the contradiction between monitoring responsiveness and processing load.
Solution Approach 2:
Instead of continuously performing full analysis at maximum frequency, the system applies analysis at selective intervals based on operational needs. The analysis calculation interval is set to be longer than the measurement interval, performing analysis only on selected measurement data points. This partial action approach maintains adequate monitoring responsiveness while significantly reducing overall data processing load.
Data Source
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AI summary
A condition monitoring system (100) includes a data measurement device (20), a data analyzer (30), and a diagnosis device (40). The data measurement device (20) obtains, according to a measurement condition provided, measurement data from a detection signal of a sensor. The data analyzer (30) performs an analysis process on the measurement data obtained by the data measurement device (20). The diagnosis device (40) performs a diagnosis process of diagnosing a condition of a facility based on an analysis result obtained through the analysis process. The data analyzer (30) sets the measurement condition and an analysis condition for the analysis process based on a time required for the analysis process and the diagnosis process.