期刊
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 147, 期 -, 页码 -出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2020.107104
关键词
Bolt loosening; Fault indicator; Local tuning; Fault location; Nonlinearity
资金
- General Research Fund (GRF) project of Hong Kong Research Grants Council (RGC) [15206717]
- Hong Kong Polytechnic University [1-ZE1N]
This paper presents a novel method based on second-order output spectrum for the precise localization of multiple bolt-loosening faults in complex structures. By considering a more general multi-degree-of-freedom model and a special local tuning mechanism, a novel damage indicator is derived successfully.
This paper presents a novel second-order output spectrum (SOOS) based method with a local tuning approach (LTA) for the precise localization of multiple bolt-loosening faults in complex structures with a simple sensor chain. The development of this new method is based on a recently developed virtual beam-like structure (VBLS) concept and the nth-order output spectrum estimation (nth-OSE) algorithm using only properly measured data. In this new method, a more general multi-degree-of-freedom (MDOF) model with general nonlinear restoring forces, caused by not only faults but also inherently existing material or boundary nonlinearities in structures, is considered, and a special local tuning mechanism is intentionally proposed to derive the novel SOOS based damage indicator. Results of numerical and experimental studies demonstrate that this novel SOOS based local tuning method can give more accurate, sensitive and reliable information about fault positions, and then can be used effectively and reliably for the precise localization of multiple bolt-loosening faults in complex structures even with inherent material or boundary nonlinearities. The results of this study would present a totally new insight into initial structural fault detection by employing sensitive nonlinear features from a systematic frequency domain approach. (C) 2020 Elsevier Ltd. All rights reserved.
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