Fuzzy-FMSA: Evaluating Fault Monitoring and Detection Strategies Based on Failure Mode and Symptom Analysis and Fuzzy Logic

Author:

Murad Carlos Alberto1,Melani Arthur Henrique de Andrade1,Michalski Miguel Angelo de Carvalho1,Caminada Netto Adherbal1,de Souza Gilberto Francisco Martha1,Nabeta Silvio Ikuyo2

Affiliation:

1. Mechatronics and Mechanical System Engineering Department, Polytechnic School of the University of São Paulo, Avenida Professor Mello Moraes 2231, Cidade Universitária, São Paulo, SP 05508-030, Brazil

2. Department of Energy Engineering and Electrical Automation, Polytechnic School of the University of São Paulo, Avenida Professor Luciano Gualberto, Travessa 3, 158, Cidade Universitária, São Paulo, SP 05508-010, Brazil

Abstract

Abstract Failure mode and symptoms analysis (FMSA) is a relatively new and still not very much employed variation of failure modes, effects and criticality analysis (FMECA), a technique broadly used in reliability, safety, and quality engineering. While FMECA is an extension of the well-known failure mode and effects analysis (FMEA) method, primarily used when a criticality analysis is required, FMSA focuses on the symptoms produced by each considered failure mode and the selection of the most appropriate detection and monitoring techniques and strategies, maximizing the confidence level in the diagnosis and prognosis. However, in the same way as FMECA and FMEA, FMSA inherits some deficiencies, presenting somewhat biased results and uncertainties intrinsic to its development, due to its own algorithm and the dependence on knowledge-based inputs from experts. Accordingly, this article presents a fuzzy logic application as a complement to FMSA in order to mitigate such uncertainties' effects. As a practical example, the method is applied to a Kaplan turbine shaft system. The monitoring priority number (MPN) obtained through FMSA is compared to the fuzzy monitoring priority number (FMPN) resulting from fuzzy logic application, demonstrating how the proposed method improves the evaluation of detection and monitoring techniques and strategies.

Publisher

ASME International

Subject

Mechanical Engineering,Safety Research,Safety, Risk, Reliability and Quality

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