A Fast Signal-Processing Method for Electromagnetic Ultrasonic Thickness Measurement of Pipelines Based on UKF and SMO

Abstract

Electromagnetic ultrasonic testing technology has advantages in measuring the thickness of pipelines in service. However, the ultrasonic signal is susceptible to corrosions on the internal and external surfaces of the pipeline. Since the electromagnetic ultrasonic signal is nonlinear, and a dynamic model is difficult to establish accurately, in this paper, a new unscented Kalman filter (UKF) method based on a sliding mode observer (SMO) is proposed. The experiments, conducted on five different testing samples, validate that the proposed method can effectively process the signals drowned in noise and accurately measure the wall thickness. Compared with FFT and UKF, the signal-to-noise ratio of the signals processed by SMO–UKF shows a maximum increase of 155% and 171%. Meanwhile, a random assignment method is proposed for the self-regulation of hyper parameters in the process of Kalman filtering. Experimental results show that the automatic adjustment of hyper parameters can be accomplished in finite cycle numbers and greatly shortens the overall filtering time.