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Self-adaptive control of shearer based on cutting resistance recognition

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Abstract

With the rapid development of automation technology, self-adaptive control methods have been widely used for drum shearers for the rapid development of automation technology. The main objective of this paper is to propose a control system wherein the motion parameters can be adjusted adaptively with the variation in the cutting resistance. The cutting resistance recognition is achieved by using the theory of wavelet packet decomposition and back propagation neural network. The motion parameters comprising hauling and drum rotation speeds are optimized by using particle swarm optimization algorithm. Different speed-control strategies are proposed to meet the variations of the cutting resistance. A self-adaptive control system model is developed to realize the self-adaptive control of the drum shearer. Finally, a simulation test is conducted to validate the effectiveness of the cutting resistance recognition method. The speed-control strategies are validated through an experimental bench test.

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Funding

The work presented in this paper is funded by the National Key Basic Research Program of China (973 Program, Grant No. 2014CB046304).

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Authors and Affiliations

  1. State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing, 400044, China

    Yonggang Liu, Liliang Hou & Datong Qin

  2. Department of Mechanical Engineering, University of Michigan-Dearborn, Dearborn, MI, 48128, USA

    Yi Zhang

Authors
  1. Yonggang Liu
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  2. Liliang Hou
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  3. Datong Qin
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  4. Yi Zhang
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Correspondence to Yonggang Liu.

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Liu, Y., Hou, L., Qin, D. et al. Self-adaptive control of shearer based on cutting resistance recognition. Int J Adv Manuf Technol 94, 3553–3561 (2018). https://doi.org/10.1007/s00170-017-1199-8

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  • DOI: https://doi.org/10.1007/s00170-017-1199-8

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