Looseness Monitoring of Bolted Spherical Joint Connection Using Electro-Mechanical Impedance Technique and BP Neural Networks

Jing Xu; Jinhui Dong; Hongnan Li; Chunwei Zhang; Siu Chun Ho

doi:10.3390/s19081906

Looseness Monitoring of Bolted Spherical Joint Connection Using Electro-Mechanical Impedance Technique and BP Neural Networks

Sensors (Basel). 2019 Apr 22;19(8):1906. doi: 10.3390/s19081906.

Authors

Jing Xu^{1

2}, Jinhui Dong³, Hongnan Li⁴, Chunwei Zhang⁵, Siu Chun Ho⁶

Affiliations

¹ School of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China. jingxu180@qut.edu.cn.
² State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China. jingxu180@qut.edu.cn.
³ School of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China. dongjinjs@hotmail.com.
⁴ State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China. hnli@dlut.edu.cn.
⁵ School of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China. zhangchunwei@qut.edu.cn.
⁶ Department of Mechanical Engineering, University of Houston, Houston, TX 77004, USA. smho@uh.edu.

Abstract

The bolted spherical joint (BSJ) has wide applications in various space grid structures. The bar and the bolted sphere are connected by the high-strength bolt inside the joint. High-strength bolt is invisible outside the joint, which causes the difficulty in monitoring the bolt looseness. Moreover, the bolt looseness leads to the reduction of the local stiffness and bearing capacity for the structure. In this regard, this study used the electro-mechanical impedance (EMI) technique and back propagation neural networks (BPNNs) to monitor the bolt looseness inside the BSJ. Therefore, a space grid specimen having bolted spherical joints and tubular bars was considered for experimental evaluation. Different torques levels were applied on the sleeve to represent different looseness degrees of joint connection. As the torque levels increased, the looseness degrees of joint connection increased correspondingly. The lead zirconate titanate (PZT) patch was used and integrated with the tubular bar due to its strong piezoelectric effect. The root-mean-square deviation (RMSD) of the conductance signatures for the PZT patch were used as the looseness-monitoring indexes. Taking RMSD values of sub-frequency bands and the looseness degrees as inputs and outputs respectively, the BPNNs were trained and tested in twenty repeated experiments. The experimental results show that the formation of the bolt looseness can be detected according to the changes of looseness-monitoring indexes, and the degree of bolt looseness by the trained BPNNs. Overall, this research demonstrates that the proposed structural health monitoring (SHM) technique is feasible for monitoring the looseness of bolted spherical connection in space grid structures.

Keywords: Bolt looseness damage; back propagation neural networks (BPNNs); bolted spherical joint (BSJ); electro-mechanical impedance (EMI); space grid structures; structural health monitoring (SHM).