Ultrasonic Signal Detection Via Improved Sparse Representations

Interference noising originating from the ultrasonic testing defect signal seriously influences the accuracy of the signal extraction and defect location. Sparse signal representations are the most recent technique in the signal processing. This technique is utilized to extract casting ultrasonic flaw signals in this paper. But its calculation is huge. A new improved matching pursuit algorithm is proposed. Artificial fish swarm algorithm is a stochastic global optimization technique proposed lately. A hybrid artificial fish swarm optimization algorithm based on mutation operator and simulated annealing are employed to search the best atomic, it can greatly reduce complexity of sparse representations. Experimental results to detect ultrasonic flaw echoes contaminated by white Gaussian additive noise or correlated noise are presented in the paper. Compared with the wavelet transform, the results show that the signal quality and performance parameters are improved obviously.