A New Approach to Quantitative and Reliable Diagnosis for Multiple Failures of Components and Sensors

Abstract

Many practical applications of diagnosis require the reliable identification of multiple faults of components and sensors in quantitative measures. However, the state of the art of diagnosis technique is considered to be still insufficient to meet these severe requirements especially for nonlinear and dynamic components and sensors. This research proposes a method to achieve these practical requirements by using the frameworks of optimized constraints, minimal conflicts based diagnosis, and causal ordering of physical systems. First, the detection of faulty behaviors of an objective system is performed based on the quantitative consistency checking between observations and the optimized constraints called as "minimal over-constraints". Second, once if some inconsistencies are detected, a mathematical operation of minimal conflicts based diagnosis derives the candidates of faulty mechanisms and functions even under multiple failure conditions. Third, the anomalous quantities directly disturbed by the faulty mechanisms are identified systematically based on causal ordering. Furthermore, the quantitative deviations of these quantities are evaluated by using the minimal over-constraints. The performance of the proposed method is demonstrated through an example to diagnose an electric water heater. The practicality of this diagnosis has been confirmed for the multiple failures in nonlinear and dynamic systems.