Intelligent slurry level measurement system of coal mine based on SVM

Abstract

The filling mining technology is a new trend in coal mining. This paper designs an intelligent sensor system for slurry level measurement of pulping station. Multi-sensor data fusion and the SVM algorithm are adopted for training of collected liquid level values, and compared with the BP neural network, the MSE of the liquid level prediction results obtained using our method is 73.7% lower. This system cannot only address the current state requiring manual monitoring of mixing tank slurry level in coal mine filling system, but can also be used to accurately measure the liquid levels in other complicated industrial applications.