Initial Study into the Possible Use of Digital Sound Processing for the Development of Automatic Longwall Shearer Operation

Author:

Kiljan Piotr,Moczulski Wojciech,Kalinowski KrzysztofORCID

Abstract

Competition on the local and global market forces enterprises to implement modern solutions and adapt to technological changes. Applying modern solutions allows an increase in the quality of the product and reduces production costs. The acoustic sensor, as a relatively cheap solution, allows signals to be obtained which, after appropriate processing, can be used to develop an automatic control of the longwall shearer, together with the recognition of the type of shale. This paper presents an introductory research, the goal of which has been to check whether acoustic signals carry useful information on what kind of material–shale or coal–is being cut by the cutting head of a longwall shearer. For this purpose, the fast Fourier transform and short-time Fourier transform functions implemented in MatLab were used. The results of the analysis are presented in the form of three-dimensional graphs and spectrograms. To sum up, the research carried out so far justifies the need for continuation in the form of systematic experiments, the results of which could be incorporated into the control system of an unmanned combine.

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)

Reference26 articles.

1. The Risk of Disrupting Production in Longwall Conditions with High Concentration of Production;Przybyła,2009

2. Factors Lowering the Effective Working Time of Employees in a Hard Coal Mine;Gumiński,2011

3. Analysis of Changes in Technical, Economic and Financial Indicators in the Polish Hard Coal Mining Industry in the Years 1900–2006;Gumiński;Min. News,2008

4. Balluffhttps://innovatingautomation.pl/przemysl-4-0/?gclid=EAIaIQobChMIk7Gxv8Dz7gIVpgV7Ch2LFwbiEAAYASAAEgIJNPD_BwE

5. Smart Factory Industry 4.0;Grabowska;Manag. Qual.,2009

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