A two-step localization method using wavelet packet energy characteristics for low-velocity impacts on composite plate structures. (1st April 2023)

• Record Type: Journal Article
• Authors: Liu, Qi; Wang, Fengde; Liu, Mengxue; Xiao, Wensheng
• Is Part Of: Mechanical systems and signal processing. Volume 188(2023)
• Publication Date: 2023-04-01
• Subjects: Structural health monitoring -- Wavelet packet decomposition -- Stochastic fractal search algorithm -- Fiber Bragg grating sensor -- Impact localization; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.110061
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A two-step localization method using wavelet packet energy characteristics is proposed. The wavelet packet decomposition method is used to define the impact feature. The impact feature can eliminate the influence of the impact height. The first step is to identify the impact area and the second step is to predict the location. Prove the effectiveness and superiority of the proposed impact localization method. Abstract: Composite plate structures are prone to damages caused by low-velocity impacts. To locate these impacts, many impact localization methods using fiber Bragg grating (FBG) sensors have been developed. However, it is difficult to achieve the high localization accuracy when impact response signals are acquired by a FBG sensing system with a low sampling frequency in previous studies. In this paper, a two-step localization method using wavelet packet energy characteristics is proposed to address this problem. The proposed impact localization method consists of the collection of impact samples, feature extraction, and two-step localization. To collect impact samples, a FBG sensing system with a sampling frequency of 5 kHz and four FBG sensors is utilized to acquire the response signals induced by the low-velocity impacts on a carbon fiber reinforced plastic (CFRP) plate. Then, a new impact feature, which is sensitive to the low-velocity impacts and can eliminate the influence of the impact height, is defined according to the wavelet packet energy characteristics. Finally, a two-step localization method is designed to achieve the accurate localization for the impacts, in which the first step is the impact area identification based on a feature database and the second step is the impact localization based on the stochastic fractal search (SFS) algorithm. The results of four sets of experiments prove the effectiveness and satisfactory performance of the proposed impact localization method for the low-velocity impact localization on the CFRP plate.