Propagation-Based Fault Detection for Optimal Sensor Deployment
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Solution Overview
Problem
Existing sensor deployment strategies for fault detection and isolation in monitoring systems are inefficient due to the lack of operating data, leading to the need for extensive simulations and high costs, and there is a challenge in determining the optimal number and placement of sensors.
Innovation Solution
A model-based approach is used to simulate system operating states, inject faults, and develop propagation-based fault detection and discrimination strategies to identify optimal sensor sets for fault detection, utilizing models like ISFA and PFDD engines to select sensors based on fault feature matrices and optimization algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large number of simulations based on numerical models are performed to cover a wide range of faults and obtain system behaviors, then fault detection coverage is improved, but data processing complexity and computational cost increase overwhelmingly
Solution Approach 1:
The patent extracts and focuses only on the critical propagation paths of faults through the system rather than analyzing all possible fault scenarios. By identifying and isolating the key signal propagation routes that carry fault information from source to detection points, the method reduces the overwhelming simulation data to essential pathways, thereby maintaining comprehensive fault coverage while significantly reducing processing complexity.
Solution Approach 2:
The patent segments the system into distinct propagation paths and analyzes fault behavior along each path separately. By dividing the complex system into manageable segments (individual propagation paths), the method enables targeted analysis of fault signals without requiring comprehensive simulation of the entire system under all possible fault conditions, thus reducing overall computational burden while maintaining detection effectiveness.
2Reliability
If sensors are deployed to cover all possible fault scenarios, then fault detection capability is improved, but sensor deployment cost and system complexity increase
Solution Approach 1:
The patent performs preliminary analysis of propagation paths and fault signal characteristics during the design phase. By pre-identifying which sensors are needed to monitor critical propagation paths and which fault scenarios are most likely to occur, the method enables optimized sensor deployment that achieves comprehensive fault detection capability with fewer sensors, reducing both deployment cost and system complexity while maintaining high reliability.
3Measurement precision
If extensive simulations are conducted to optimize sensor deployment, then sensor placement accuracy is improved, but time consumption and computational resources increase
Solution Approach 1:
The patent applies partial action by focusing simulations only on the most critical propagation paths and fault scenarios rather than exhaustively simulating all possible conditions. By concentrating computational resources on the most influential factors that determine optimal sensor placement, the method achieves high placement accuracy with significantly reduced simulation time and computational resource requirements compared to comprehensive exhaustive simulations.
Data Source
AI summary
A model (137) is created of a system (110) to be monitored (805). Operating states of the monitored system, including steady and transient states, are identified. Faults are injected into the model and the model is used to simulate each of the identified operating states (810). Results of each simulation are analyzed and used to develop one or more propagation-based fault detection and discrimination strategies (147) that can be used to identify faults in each of the identified operating states (815). The strategies may further be used to select an optimal set of sensors (155) to assist with fault detection.