Acoustic emission localization based on FBG sensing network and SVR algorithm

Abstract In practical application, carbon fiber reinforced plastics (CFRP) structures are easy to appear all sorts of invisible damages. So the damages should be timely located and detected for the safety of CFPR structures. In this paper, an acoustic emission (AE) localization system based on fiber Bragg grating (FBG) sensing network and support vector regression (SVR) is proposed for damage localization. AE signals, which are caused by damage, are acquired by high speed FBG interrogation. According to the Shannon wavelet transform, time differences between AE signals are extracted for localization algorithm based on SVR. According to the SVR model, the coordinate of AE source can be accurately predicted without wave velocity. The FBG system and localization algorithm are verified on a 500 mm×500 mm×2 mm CFRP plate. The experimental results show that the average error of localization system is 2.8 mm and the training time is 0.07 s

Development of high temperature acoustic emission sensing system using fiber Bragg grating

Abstract In some applications in structural health monitoring (SHM), the acoustic emission (AE) detection technology is used in the high temperature environment. In this paper, a high-temperature-resistant AE sensing system is developed based on the fiber Bragg grating (FBG) sensor. A novel high temperature FBG AE sensor is designed with a high signal-to-noise ratio (SNR) compared with the traditional FBG AE sensor. The output responses of the designed sensors with different sensing fiber lengths also are investigated both theoretically and experimentally. Excellent AE detection results are obtained using the proposed FBG AE sensing system over a temperature range from 25 ℃ to 200 ℃. The experimental results indicate that this FBG AE sensing system can well meet the application requirement in AE detecting areas at high temperature

Development of an FBG Sensor Array for Multi-Impact Source Localization on CFRP Structures

We proposed and studied an impact detection system based on a fiber Bragg grating (FBG) sensor array and multiple signal classification (MUSIC) algorithm to determine the location and the number of low velocity impacts on a carbon fiber-reinforced polymer (CFRP) plate. A FBG linear array, consisting of seven FBG sensors, was used for detecting the ultrasonic signals from impacts. The edge-filter method was employed for signal demodulation. Shannon wavelet transform was used to extract narrow band signals from the impacts. The Gerschgorin disc theorem was used for estimating the number of impacts. We used the MUSIC algorithm to obtain the coordinates of multi-impacts. The impact detection system was tested on a 500 mm × 500 mm × 1.5 mm CFRP plate. The results show that the maximum error and average error of the multi-impacts’ localization are 9.2 mm and 7.4 mm, respectively