An Improved Fruit Fly Optimization Algorithm Based Orthogonal Matching Pursuit for Ultrasonic Noise Reduction

Noise reduction is the key technology of ultrasonic testing whose performance affects the evaluation of ultrasonic testing results directly. Orthogonal matching pursuits(OMP) is one of the most popular methods for the purpose of noise reduction; however, OMP suffers from a number of disadvantages of high complexity and time-consuming of the atom searching, and it is unable to extract the ultrasonic signal under background of powerful noise. An improved fruit fly optimization algorithm based orthogonal matching pursuit(IFOA-OMP) for ultrasonic noise reduction method is proposed, the parameters of Gabor function are estimated by IFOA, and the global ergodicity is improved by the adaptive step function, at the same time, the high-dimensional extensive CAT map is introduced to jump out of the local optimum. Finally, the ultrasonic signal is reconstructed from the best matching atoms. In order to validate the effectiveness of the proposed method, the simulated multi frequency ultrasonic signal and the real ultrasonic signal of forging block are used. The processing results show the proposed method can accurately extract the ultrasonic signal under background of powerful noise.