Automatic tracking of natural frequency in the time–frequency domain for blade tip timing. (6th January 2022)

• Record Type: Journal Article
• Authors: Wang, Zeng-Kun; Yang, Zhi-Bo; Li, Hao-Qi; Cao, Jia-Hui; Tian, Shao-Hua; Chen, Xue-Feng
• Is Part Of: Journal of sound and vibration. Volume 516(2022)
• Publication Date: 2022-01-06
• Subjects: Blade tip timing (BTT) -- Natural frequency -- MUSIC -- Morphological filtering -- Curve fitting; Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2021.116522
• Languages: English
• ISSNs: 0022-460X

Abstract

Abstract: Natural frequency is an essential parameter for rotating blade condition monitoring. Various previous simulations and experiments have shown that multiple signal classification (MUSIC) has the advantage of filtering out the synchronous frequency component to make the natural frequency more prominent in the frequency domain. However, the negative effect of this characteristic is the poor performance in the resonance area because of the overlap between the synchronous frequency component and the natural frequency. This effect results in the disconnection of the natural frequency line in the resonance area. Thus, morphological filtering and mean absolute error (MAE)-based curve fitting are applied to robustly extract and restore the natural frequency line. Based on this method, automatic tracking of the natural frequency in the time–frequency domain is proposed in this study. Additionally, the mathematical principle of the inherent characteristic of MUSIC to filter out synchronous frequency components is first mentioned and explored herein. Furthermore, simulations and experiments under variable rotating frequencies are conducted to show that the proposed method can track the natural frequency under variable operating conditions.