Ultrasonic imaging recognition of coal-rock interface based on the improved variational mode decomposition

Abstract

Extracting effective ultrasonic echo signals in multilayered media is the key technology for detection of coal-rock interface, which is the basis of automatic height adjustment of the shearer drums during automatic coal mining. However, it is tough to recognize echo signals of coal-rock interface efficiently and accurately through common signal processing methods such as Fourier Transform (FT), Wavelet Transform (WT) and Empirical Mode Decomposition (EMD). Therefore, an improved Empirical Variational Mode Decomposition (EVMD) method for ultrasonic echo signal processing is proposed in this paper. Firstly, EVMD is used to preprocess the received echoes of coal-rock interface. Secondly, the optimization iterative method of weight coefficient is introduced to fit part of distorted echo envelope with asymmetric Gaussian model, which can effectively reduce the calculation error. Finally, peak focusing imaging technique is used to image the processed envelopes. The experimental results show that the proposed method can recognize the coal-rock interface efficiently.