Material Thickness Detection Based On Laser Ultrasonic

With the development of science and technology,the demand for effective and reliable non-destructive testing(NDT)techniques has been rising enormously due to the ever-increasing need for safety and reliability of engineering structures.Among various NDT techniques,laser ultrasonic technique provides a new paradigm to detect the damage with non-contact ultrasonic generation,which is more suitable for the damage evaluation in the complex structures with curved surfaces.Hence,laser ultrasound technology has become a hotspot in the field of NDT.This thesis is focus on material thickness detection based on laser ultrasonic.Firstly,the basic principle of laser ultrasonic testing is studied.The excitation principle and sensing method of laser ultrasound are analyzed in this thesis and the signal processing methods are introduced in detail.On this basis,the improvement of laser ultrasonic testing system is completed,which can be applied to the detection of bulk wave and Lamb wave.Secondly,as the signal-to-noise ratio of bulk-wave signals is low,wavelet denoising method is used to denoise the signal.Meanwhile,to obtain the transit time of the transverse and longitudinal waves,Hilbert transform method is used to extract the envelope of the signal.On this basis,B-scan is carried out on the aluminum block with pits,and the thickness of the aluminum block is measured using the transit time.Finally,laser ultrasonic testing is made to realize the wavefield visualization of Lamb wave,and the time-space diagram of Lamb wave in the scanned area is obtained.The phase velocity of Lamb wave is extracted by two-dimensional Fourier transform,and the thickness of thin aluminum plate is detected by genetic algorithm.In order to further realize the detection of local thickness,the local time-space diagram is transformed into the local frequency-wavenumber domain using short-space Fourier transform,and the local phase velocity is measured.On this basis,the thickness of the damaged aluminum plate is reconstructed with genetic algorithm.