Ultrasonic Signal Estimation Based on Manta Ray Foraging Optimization Algorithm

In order to solve the problem of echo transit time estimation of weak ultrasonic detection signal in ultrasonic nondestructive testing, this paper proposes a novel method that estimates the transit time parameters of ultrasonic detection signal based on Manta Ray Foraging Optimization (MRFO) algorithm. The method transforms the problem of estimating transit time parameters into a function optimization problem by establishing a Gaussian convolution model of ultrasonic signal. Then, by using MRFO algorithm to solve the objective function, the estimation of transit time parameters is achieved. The simulation and experimental results show that when using the method proposed in this paper to estimate the parameters of weak ultrasonic detection signal with a signal-to-noise ratio of -10dB, the Mean Square Error (MSE) and Estimated Signal-to-Noise Ratio (ESNR) are 0.0003 and 8.8500, respectively. The results of the proposed method are significantly superior to the wavelet transform and empirical mode decomposition.