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



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


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

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