Assessment of concrete pavement support conditions using distributed optical vibration sensing fiber and a neural network. (20th August 2019)

• Record Type: Journal Article
• Authors: Zhao, Hongduo; Wu, Difei; Zeng, Mengyuan; Tian, Yu; Ling, Jianming
• Is Part Of: Construction & building materials. Volume 216(2019)
• Page Start: 214
• Page End: 226
• Publication Date: 2019-08-20
• Subjects: Concrete pavement -- Support condition -- Distributed optical vibration sensing -- Vibration testing -- Wavelet packet transform -- Probabilistic neural network; Building materials -- Periodicals; 624.18
• DOI: 10.1016/j.conbuildmat.2019.04.195
• Languages: English
• ISSNs: 0950-0618

Abstract

Highlights: Distributed optical vibration sensing technology was used for vibration monitoring. Wavelet packet transform was used to process the captured vibration signals. A probabilistic neural network was developed to assess the support condition. Results of N-fold cross-validations demonstrated the effectiveness of this method. Abstract: This paper presents a new method that uses distributed optical vibration sensing (DOVS) technology and a neural network, which can access the concrete pavement support condition with lower cost and higher efficiency. This method relies on the vibration properties of the concrete pavement slabs, which was captured by an embedded DOVS system and extracted using the wavelet packet transform. Based on the extracted properties, a grading method that using probabilistic neural network (PNN) to assess the support condition was proposed. Through field tests, the accuracy of this method can reach 92.8% for 2-grade assessment and 81.4% for 3-grade assessment, respectively.