Koopman Operator Based Fault Diagnostic Methods for Mechanical Systems

Alexandru Nichifor, Yongzhi Qu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traditionally, dynamical systems can be simulated with physics-based model when the design parameters and material property are pre-known. However, when a system is deployed in field and has suffered potential degradation, a physics-based model might be infeasible to obtain. Moreover, the non-linearity and unknown coupling between the system and contacting constraints are often hard to determine accurately. The analysis of those systems becomes practically problematic. In this paper, the Koopman operator is used to learn and represent a dynamic system in a data driven manner. This paper proposes two methods of using the Koopman operator to extract and classify critical parameters of a non-linear dynamic mechanical system for fault diagnosis. The first method proposes a model to extract key features from a dynamic system and feed the features to a neural network to classify the existence of a fault. The second method uses parameters derived from the Koopman operator to create a prediction model with healthy data. This prediction model is then used to predict future system dynamics for a measured time evolution and compare that with direct measurements when future dynamics become available. Both methods are then tested via an experimental case study and the results are discussed.

Original languageEnglish (US)
Title of host publicationStructural Health Monitoring 2021
Subtitle of host publicationEnabling Next-Generation SHM for Cyber-Physical Systems - Proceedings of the 13th International Workshop on Structural Health Monitoring, IWSHM 2021
EditorsSaman Farhangdoust, Alfredo Guemes, Fu-Kuo Chang
PublisherDEStech Publications Inc.
Pages542-549
Number of pages8
ISBN (Electronic)9781605956879
StatePublished - 2021
Event13th International Workshop on Structural Health Monitoring: Enabling Next-Generation SHM for Cyber-Physical Systems, IWSHM 2021 - Stanford, United States
Duration: Mar 15 2022Mar 17 2022

Publication series

NameStructural Health Monitoring 2021: Enabling Next-Generation SHM for Cyber-Physical Systems - Proceedings of the 13th International Workshop on Structural Health Monitoring, IWSHM 2021

Conference

Conference13th International Workshop on Structural Health Monitoring: Enabling Next-Generation SHM for Cyber-Physical Systems, IWSHM 2021
Country/TerritoryUnited States
CityStanford
Period3/15/223/17/22

Bibliographical note

Publisher Copyright:
© 2021 Structural Health Monitoring 2021: Enabling Next-Generation SHM for Cyber-Physical Systems - Proceedings of the 13th International Workshop on Structural Health Monitoring, IWSHM 2021. All rights reserved.

Fingerprint

Dive into the research topics of 'Koopman Operator Based Fault Diagnostic Methods for Mechanical Systems'. Together they form a unique fingerprint.

Cite this