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Instantaneous frequency extraction in time-varying structures using a maximum gradient method
Liu, Jing-liang,Wei, Xiaojun,Qiu, Ren-Hui,Zheng, Jin-Yang,Zhu, Yan-Jie,Laory, Irwanda Techno-Press 2018 Smart Structures and Systems, An International Jou Vol.22 No.3
A method is proposed for the identification of instantaneous frequencies (IFs) in time-varying structures. The proposed method combines a maximum gradient algorithm and a smoothing operation. The maximum gradient algorithm is designed to extract the wavelet ridges of response signals. The smoothing operation, based on a polynomial curve fitting algorithm and a threshold method, is employed to reduce the effects of random noises. To verify the effectiveness and accuracy of the proposed method, a numerical example of a signal with two frequency modulated components is investigated and an experimental test on a steel cable with time-varying tensions is also conducted. The results demonstrate that the proposed method can extract IFs from the noisy multi-component signals and practical response signals successfully. In addition, the proposed method can provide a better IF identification results than the standard synchrosqueezing wavelet transform.
Instantaneous frequency extraction in time-varying structures using a maximum gradient method
Jing-liang Liu,Xiaojun Wei,Ren-Hui Qiu,Jin-Yang Zheng,Yan-Jie Zhu,Irwanda Laory 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.22 No.3
A method is proposed for the identification of instantaneous frequencies (IFs) in time-varying structures. The proposed method combines a maximum gradient algorithm and a smoothing operation. The maximum gradient algorithm is designed to extract the wavelet ridges of response signals. The smoothing operation, based on a polynomial curve fitting algorithm and a threshold method, is employed to reduce the effects of random noises. To verify the effectiveness and accuracy of the proposed method, a numerical example of a signal with two frequency modulated components is investigated and an experimental test on a steel cable with time-varying tensions is also conducted. The results demonstrate that the proposed method can extract IFs from the noisy multi-component signals and practical response signals successfully. In addition, the proposed method can provide a better IF identification results than the standard synchrosqueezing wavelet transform.