Research on Structural Health Monitoring Method Based on Multi- source Sensing Information Fusion L.Sun 1 , Y. S. Wang 1 *, B.R. Miao 3 , D. Wu 2 , H. Sun 1 , X.L. Qing 1 1 School of Aerospace Engineering, Xiamen University, Xiamen 361102, China Email: 494942801@qq.com; {wangys, sunhu, xinlinqing}@xmu.edu.cn 2 State-key Laboratory of Tranction Power, Southwest Jiaotong University, Chengdu 610031 Email: brmiao@home.swjtu.edu.cn 3 Research & Develop Center at Headquarters of China Academy of Launching Vehicle Technology, Beijing 100076, China Email: wd_buaa@163.com KEY WORDS: Structural Health Monitoring; PZT; Optical Fibre; Information Fusion; Kalman filtering ABSTRACT With the development of sensor and information technology, more and more sensors are applied in the structural health monitoring system, and the size and sensor signals are gradually increasing. The fusion of different sensor signals can improve the stability and reliability of structural health monitoring technology. In this paper, eight piezoelectric transducers (PZT) and the distributed optical fibre sensors were layouted on the surface of an aluminum alloy plate to collect signals under the load-changing environment. The ultrasonic guided waves generated and received by PZTs were used to diagnose the damage in a way of imaging, while the strains obtained by optical fibre sensor were used to identify the damage. These two signal information is fused in feature level using Kalman filtering method. The results show that the fusion damage diagnosis results are more stable and the accuracy of damage location is improved than the single signal’s diagnosis results. 1. Introduction In recent years, the accidents have frequently occurred due to failures on mechanical structures, aircraft, and large civil engineering, etc. The needs to acquire structural state information real time is becoming more and more urgent. The structural health monitoring (SHM) as an innovative technology for online monitoring the structural state (strain, damage, etc.) has become a research focus [1] . Many advanced SHM methods have emerged, mainly including [1- * Corresponding author. Associate professor, wangys@xmu.edu.cn. Creative Commons CC-BY-NC licence https://creativecommons.org/licenses/by/4.0/ 7th Asia-Pacific Workshop on Structural Health Monitoring November 12-15, 2018 Hong Kong SAR, P.R. China More info about this article: http://www.ndt.net/?id=24091