Influence Matrix Approach for an Optimal Sensor Placement
Abid Sabrina, Haffaf Hafid
Progress in Signals and Telecommunication Engineering, Vol. 8, No. 1, 2019.
DOI: 
Link: http://www.dline.info/pste/fulltext/v8n1/pstev8n1_3.pdf
Abstract:
Fault Detection and Isolation (FDI) procedure increase assurance on quality, reliability and safety in industrial systems. A suitable installed sensors in an industrial process is a necessary condition for fault diagnosis. Sensor placement for diagnosis purposes consists to study which process variables have to be measured to satisfy diagnosis specifications. Analytical redundancy relations (ARRs) are used frequently in the area of diagnosis as well as optimizing, analyzing, and validating
of sensors of the system. This paper presents the optimal sensor placement approach based on structural analysis methods using tripartite graph approach. The proposed approach allows to study which sensors are required to be installed in a process in order to improve certain fault diagnosis specifications; and it includes 2 phases: (i) development of systematic and efficient approaches for the generation of ARRs set allowing to generate â€œinfluence matrixâ€, (ii) then the multi-criteria optimization is applied by selecting robust sensor placements (Pareto Optimal Solutions) leading to a sensor placement
algorithm. The proposed method has been validated on a robot dynamic model taken as a benchmark where the benefits of the
method are clearly shown.