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Smart Structures and Systems Volume 30, Number 1, July 2022 , pages 75-88 DOI: https://doi.org/10.12989/sss.2022.30.1.075 |
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A generalized adaptive variational mode decomposition method for nonstationary signals with mode overlapped components |
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Jing-Liang Liu, Fu-Lian Qiu, Zhi-Ping Lin, Yu-Zu Li and Fei-Yu Liao
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| Abstract | ||
| Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate nonstationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component. | ||
| Key Words | ||
| adaptive; closely-spaced; instantaneous frequency; mode overlapped; variational modal decomposition | ||
| Address | ||
| (1) Jing-Liang Liu, Fu-Lian Qiu, Yu-Zu Li, Fei-Yu Liao: College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China; (2) Jing-Liang Liu, Fei-Yu Liao: "Digital Fujian" Laboratory of Internet Things for Intelligent Transportation Technology, Fuzhou 350002, China; (3) Zhi-Ping Lin: Fujian Expressway Group Co., LTD, Fuzhou 350001, China. | ||