The efficiency of a fault monitoring system critically depends on the structure of the plant instrumentation system. For processes monitored using principal component analysis, the multivariate statistical technique most used for fault diagnosis in industry, an existing strategy aims at selecting the set of instruments that satisfies the detection of a given set of faults at minimum cost. It is based on the minimum fault magnitude concept. Because that procedure discards lower-cost feasible solutions, in this work, a new optimal selection methodology is proposed whose constraints are straightaway defined in terms of the principal component analysis's statistics. To solve the optimization problem, a level traversal search with cutting criteria is enhanced taking into account that the fault observability is a necessary condition for fault detection when statistical monitoring techniques are applied. Furthermore, observability and detection degree concepts are defined and considered as constraints of the optimization problems to devise robust sensor structures, which are able to detect a set of key faults under the presence of failed sensors or outliers. Application results of the new strategy to a case study taken from the literature are provided.
Key faults significantly affect the normal operation of the process originating risk conditions. These failures should be identified even in the presence of missing measurements or outliers. In this work a new strategy to design sensor networks, which are able to resolve a set of key faults when sensors fail, is presented. The procedure deals with failure isolation using the Fault Resolution Degree concept. This is incorporated as a constraint of the minimum-cost design formulation, and the resulting optimization problem is solved using MILP codes. The strategy only uses low uncertainty data that are readily available at the process design stage. Application results of the methodology to case studies extracted from the literature are presented and compared with those provided by other existing techniques.
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