Improving ultrasonic multi-level measurements with wavelets - results from separators and smelters

Abstract

Usage of ultrasonic level measurements is encountered in different industrial applications such as gas, oil, water and sand in separators, liquid-solid in sedimentation processes, molten metals, etc. When the reflected signal level from multi-layers is low and swamped in noise with very poor signal to noise ratio (SNR), getting good enough signals for level estimation and interface detection will be difficult. This will be even more difficult in flowing mediums with multi-levels or in ultrasonic interrogations of molten metals. To enhance the signal detection algorithms, wavelets have been applied with some success. The objective of this paper is to present wavelet based algorithms for the detection of reflected signals from multi-layers when the SNR is very low. Ultrasonic time domain reflectometry (UTDR) is performed using buffer rods for signal transmission and wavelets for signal analysis. Suitable mother wavelet selection, threshold and thresholding algorithms are proposed and successfully implemented. Discrete wavelet Transform (DWT) based algorithms for signal denoising gives better signal trains in the UTDR studies performed in multilayered systems including molten metals. A system consisting of three layers is studied using ultrasonic transmission via a buffer rod. Useful denoising properties are achieved using Sym7 mother wavelet, Rigrsure threshold, and soft thresholding for analyzing the reflected signals in multi-layered systems. A significant improvement is observed in the case of UTDR based studies involving molten metals too.