A Multi-Fault Modeling Approach for Fault Diagnosis and Failure Prognosis of Engineering Systems

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Published Mar 26, 2021
Bin Zhang Chris Sconyers Romano Patrick George Vachtsevanos

Abstract

Accurate and reliable fault diagnosis and prognosis of safety or mission critical components/ subsystems in complex engineering systems present major challenges to the Condition-Based Maintenance (CBM) or Prognostic and Health Management (PHM) designer. A crucial step in the development of CBM/PHM strategies relates to the designer’s ability to understand and model the incipient failure or fault modes and mechanisms. A single fault growth model might not be often capable to capture a sequence of fault behaviors. Consider, for example, a rolling element bearing as a critical component of rotating machinery. The bearing may begin to corrode under certain operating conditions and, in parallel or sequentially, may be spalling and eventually, cracking. For accurate model-based fault diagnosis and failure prognosis, therefore, it is essential that fault progression models be developed to represent these evolving behaviors. This paper introduces an approach to multi-fault modeling with an application to a rolling element bearing of a helicopter’s oil cooler. A simple and cost-effective on-line parameter adaptation solution is introduced to improve the performance of modeling. Finally, a series of experiments for different fault modes are presented to verify the proposed solution.

How to Cite

Zhang, B., Sconyers, C., Patrick, R., & Vachtsevanos, G. (2021). A Multi-Fault Modeling Approach for Fault Diagnosis and Failure Prognosis of Engineering Systems. Annual Conference of the PHM Society, 1(1). Retrieved from https://papers.phmsociety.org/index.php/phmconf/article/view/1465
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Keywords

diagnosis, fault diagnosis, model based diagnostics, model based prognostics, prediction, prognostics

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Section
Technical Papers

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