Continuous Flow Engine Threshold Adaptation for False Alarm Control
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Solution Overview
Problem
Continuous flow engines face challenges in monitoring and control due to the vast amount of data requiring manual processing, with existing automatic systems often resulting in either ignoring critical issues or generating false alarms, and the need for adaptive monitoring systems that can identify problems early while minimizing false alarms.
Innovation Solution
A method and system that acquire measurement values from sensors, evaluate them against threshold ranges, trigger alarms, and allow operators to evaluate the alarms with options to adjust the threshold ranges based on feedback, using a counter system to adapt the ranges dynamically and reduce false alarms, with the ability to automatically adjust the threshold values using relative and absolute factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If narrow threshold ranges and limits are used for monitoring, then early problem identification is improved, but false alarm rate increases significantly
Solution Approach 1:
The patent implements dynamic threshold adjustment where threshold ranges are automatically adapted based on historical data and operational conditions. The system transitions from static to dynamic monitoring parameters, allowing thresholds to evolve with the engine's operational patterns while maintaining sensitivity to actual problems and reducing false alarms.
Solution Approach 2:
The system incorporates feedback mechanisms where alarm history and operational data are continuously analyzed to refine threshold settings. The monitoring system learns from past alarms and adjustments, automatically optimizing threshold ranges to balance early detection with false alarm reduction over time.
2Reliability
If broad threshold ranges and limits are used for monitoring, then false alarm rate is reduced, but early problem identification capability deteriorates
Solution Approach 1:
The system employs dynamic threshold adaptation that adjusts monitoring sensitivity based on operational context. During normal operation, thresholds may be broader to reduce false alarms, while automatically tightening when anomaly patterns are detected, thus maintaining both reliability and precision across different operational states.
Solution Approach 2:
The monitoring system applies different threshold strategies to different parameters and operational conditions. Critical parameters maintain tighter thresholds while less critical ones use broader ranges, and thresholds are locally optimized for each operational mode rather than applying uniform limits across all conditions.
3Measurement precision
If manual monitoring of vast data is performed, then monitoring accuracy is maintained, but operator workload and time consumption increase significantly
Solution Approach 1:
The system performs self-monitoring and self-adjustment of threshold parameters based on historical data and operational patterns. The automated monitoring reduces the need for continuous manual oversight while maintaining high detection accuracy, allowing the system to serve itself in identifying anomalies and optimizing parameters.
Solution Approach 2:
The patent replaces manual mechanical monitoring with automated electronic systems that continuously analyze sensor data. The system uses computer-based algorithms to process vast amounts of data that would be impossible to analyze manually, substituting human operators with automated intelligence for data processing while maintaining monitoring accuracy.
4Device complexity
If existing automatic monitoring systems with fixed parameters are used, then system complexity is minimized, but adaptability to changing engine conditions deteriorates
Solution Approach 1:
The system transitions from fixed static parameters to dynamic adaptive parameters that automatically adjust to changing engine conditions. The monitoring system evolves its threshold ranges and monitoring strategies based on accumulated operational data, maintaining simplicity in implementation while achieving high adaptability through continuous parameter optimization.
Solution Approach 2:
The patent implements automatic changes to monitoring parameters including threshold ranges, alarm limits, and evaluation criteria based on operational conditions and historical performance. The system dynamically modifies these parameters to adapt to engine wear, maintenance patterns, and operational variations without requiring complex reconfiguration.
Data Source
AI summary
The present invention refers to a continuous flow engine monitoring and controlling method including an improved process to adapt the existing system to deviation detected to provide an improved management and control system increasing the overall benefit provided by such continuous flow engine. Furthermore, the present invention refers to a system being adapted to perform such method. Additionally, the present invention refers to a computer program product being utilized to realize such method. Furthermore, the present invention refers to a use of such means to improve the utilization of such continuous flow engine.