A new efficient method for system structural analysis and generating Analytical Redundancy Relations

In this paper we present a new efficient algorithmic method for generating the analytical redundancy relations (ARRs). ARRs are one of the crucial tools for model-based diagnosis as well as for optimizing, analyzing, and validating the system of sensors. However, despite the importance of the ARRs for both system diagnosis and sensor optimization, it seems that less attention has been paid to the development of systematic and efficient approaches for their generation. In this paper we discuss the complexity in derivation of ARRs and present a new efficient algorithm for their derivation. Given a system with a set of L ARRs, our algorithm achieves a complexity of O(L⁴) for generating the ARRs. To our knowledge, this is the first algorithm with a polynomial complexity for derivation of ARRs. We also present the results of application of our algorithms, for generating the complete set of ARRs, to both synthetic and industrial examples.