Yaozhang Sai

Acoustic emission source localization technique based on least squares support vector machine by using FBG sensors

An intelligent acoustic emission (AE) source localization technique by using fiber Bragg grating (FBG) sensors was investigated. Four FBGs sensing network was established for detecting the AE signal. And power intensity demodulation method was initialized employing narrow-band tunable laser. The intelligent AE source localization method was proposed based on wavelet transform, cross-correlation analysis, and least squares support vector machines (LS-SVM). LS-SVM modal’s input is signal time difference and output is AE source position. The location experiments were carried out on a 500 mm × 500 mm × 2 mm aluminum alloy plate. The results showed that the AE source position abscissa and ordinate localization errors are all less than 10 mm. The maximum and average localization errors are 8.65 and 6.78 mm, respectively. The research results provided a novel method for AE source localization by using FBG sensors.

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.

Acoustic emission location on aluminum alloy structure by using FBG sensors and PSO method

Acoustic emission location is important for finding the structural crack and ensuring the structural safety. In this paper, an acoustic emission location method by using fiber Bragg grating (FBG) sensors and particle swarm optimization (PSO) algorithm were investigated. Four FBG sensors were used to form a sensing network to detect the acoustic emission signals. According to the signals, the quadrilateral array location equations were established. By analyzing the acoustic emission signal propagation characteristics, the solution of location equations was converted to an optimization problem. Thus, acoustic emission location can be achieved by using an improved PSO algorithm, which was realized by using the information fusion of multiple standards PSO, to solve the optimization problem. Finally, acoustic emission location system was established and verified on an aluminum alloy plate. The experimental results showed that the average location error was 0.010 m. This paper provided a reliable method for aluminum alloy structural acoustic emission location.

Low Velocity Impact Localization on CFRP Based on FBG Sensors and ELM Algorithm

Carbon fiber reinforced plastics (CFRPs) structures are very susceptible to invisible damage induced by the low velocity impact. The impact area localization can be useful information for detecting this damage. In this paper, the low velocity impact area localization system using fiber Bragg grating (FBG) sensors and area localization algorithm based on extreme learning machine (ELM) were investigated. The FBG sensors were used to detect the impact signal. Fourier transform, Relief F algorithm, and principal component analysis technology were used to extract the impact signal characteristic. The ELM technology was used to realize the impact area localization. Finally, the impact area localization system was established and verified on a CFRP plate with 240-mm × 240-mm experiment area. The experimental results showed that the proposed system made accurate identification 35 times for 36 times experiments. The area localization accuracy was 96.9%. In addition, the precision of the area localization system was 40-mm × 40-mm area. This paper provided a reliable method for CFRP low velocity impact area localization.

FBG sensor array-based-low speed impact localization system on composite plate

A fiber Bragg grating (FBG) sensors-based impact localization system on composite structure and a novel localization algorithm independent of wave velocity were proposed. Six FBG sensors constitute two isosceles right triangle FBG arrays. Impact signals were detected by a high-speed FBG interrogation system. Morlet wavelet transform was employed to extract time differences of impact signals. The straight lines equations, which are through impact source and FBG sensors of right-angled vertices of FBG arrays, can be obtained by the time differences. The coordinate of impact source is the intersection of straight lines. Testing experiments were carried out on composite plate within 400 mm × 400 mm monitor area. The experimental results showed that the maximum and average errors were 20.92 and 8.67 mm, respectively. This article provides a simple and stable impact source localization system independent of wave velocity.

Multi-Damage Identification System of CFRP by Using FBG Sensors and Multi-Classification RVM Method

Multi-damage identification of carbon fiber reinforced plastics (CFRP) structure is very important to ensure the structural safety. In this paper, the multi-damage identification system of CFRP using fiber Bragg grating (FBG) sensors and multi-classification relevance vector machine (RVM) method was proposed. First, the multi-damage identification method was researched by an active actuation method. In addition, the structural dynamic response signals were detected by the FBG sensors. Then, the multi-damage characteristics extraction was completed by Fourier transform, reliefF, and principal component analysis algorithms. With the multi-damage characteristics as the input and their corresponding multi-damage state as the output, the multi-classification RVM model was trained to identify the multi-damage state. Finally, the multi-damage identification system was established and verified on a CFRP plate with dimensions of 500 mm

Low velocity impact localization system of CFRP using fiber Bragg grating sensors

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Damage identification system of CFRP using fiber Bragg grating sensors

mm

Composite plate low energy impact localization system based on FBG sensing network and hybrid algorithm

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Multi-source acoustic emission localization technology research based on FBG sensing network and time reversal focusing imaging

mm. The results showed that the proposed multi-damage identification method can accurately identify the CFRP structural multi-damage state. This paper provided a reliable method for the CFRP structural multi-damage identification.