Analysis Of Sound Signal Of Shearer Experimental Device Based On LabVIEW

The double-drum shearer is an important equipment for the coal mining face under the coal mine.Accurately identifying the coal rock cutting status and automatically adjusting the height of the drum is the key to the automatic control of the drum shearer.The shearing sound signal of the shearer contains not only the useful signal reflecting the cutting status,but also the environmental background noise of the transmission such as mechanical electrical.How to analyze and process the shearer’s cutting sound signal,identify useful signals reflecting different cutting conditions,and extract feature vectors have important theoretical and engineering guidance for coal-rock interface identification and automatic shearer height adjustment significance In this paper,using the shearer height adjustment experimental device developed by the research group in the early stage as a platform,an in-depth study of the shearer height adjustment and control system and the analysis and processing of the cutting sound signal were conducted.Chapter 2 of the thesis briefly introduces the principle,composition and function of the shearer height adjustment experimental device,and makes related calculations for the reducer.Chapter 3 firstly designed and configured the hardware of the measurement and control system based on the measurement and control tasks of the device.Using the LabVIEW software,the experimental system of the height measurement and control of the shearer was developed.The system can realize the multi-channel acquisition,data processing,real-time display,storage and other signals of the shearer’s cutting sound,heightening cylinder pressure,rocker arm inclination and vibration.Chapter 4 of the thesis first uses MATLAB and LabVIEW software to develop a self-made A-weighted sound level meter.Comparative experiments show that the self-made A-weighted sound level meter can be used to test the shearer’s cutting sound signal.Based on the environmental background noise of the height-adjusting experimental device,a cut sound simulation signal is constructed,and the noise reduction study of the cut sound simulation signal is carried out using the wavelet threshold noise reduction theory.Finally,it is determined to apply the coif4 wavelet base.After 6-layer wavelet decomposition,a soft threshold function is used,and the sqtwolog threshold rule is selected to have the best noise reduction effect on the cut sound signal.Environmental background noise can be eliminated to the greatest extent.Chapter 5 of the thesis firstly carried out FFT analysis,power spectrum estimation and octave analysis on the sound signals of two typical cutting conditions.The results show that the three traditional analysis methods have little difference in the recognition of cutting conditions.The distinction is not high.To this end,the analysis and processing of the cut sound signal based on the EEMD decomposition method,and an experimental study.The experimental results show that for the cut sound signal,the IMF component is obtained by EEMD decomposition after wavelet threshold noise reduction.Select the IMF components with greater cross-correlation with the original signal,and extract the average,standard deviation and energy of the typical time-domain characteristic parameters of these components.These characteristic parameters have great differences under different cutting conditions,and can be used to identify different cutting conditions.Therefore,these three time-domain feature parameters can be used to construct feature vectors to identify different cutting conditions.This article provides a reference for the development of similar measurement and control systems for the hardware and software design of the measurement and control system of the shearer height adjustment experimental device.The noise reduction of the cutting sound signal and the extraction of characteristic parameters provide a theoretical basis for the recognition of the cutting sound signal and different cutting conditions under the environmental background noise of the coal mining machine.Figure[57]table[17]reference[85]...