Optimization of Shearer Drum Based on Multi-Objective Bat Algorithm with Grid (MOBA/G)
Open Access
Abstract
The shearer drum undertakes the main function of coal falling and loading, and picks distributed on it have a great impact on the performance of the drum. However, few studies have optimized the pick and drum at the same time. In this paper, parameters of pick and drum are considered as design variables, and the response functions of design variables are established based on the central composite experiment method. The optimal structural and working parameters of the pick and the drum of MG500/1130-WD shearer are obtained by using the multi-objective bat algorithm and multi-objective bat algorithm with grid, respectively. Comparing results of the two algorithms, the multi-objective bat algorithm with grid is more effective in improving the comprehensive performance of the drum. According to the optimized design variables, a coal mining test is carried out to verify the optimization effect of the algorithm. The result provides some theoretical references for the design and production of the drum and has some engineering application value.Keywords
Funding Information
- National Natural Science Foundation of China (No. 51575201, No. 51905229)
- atural Science Foundation of Jiangsu Province (No. BK20190968)
This publication has 40 references indexed in Scilit:
- Application of Bat Algorithm to Optimize Scaling Factors of Fuzzy Logic-Based Power System Stabilizer for Multimachine Power SystemInternational Journal of Nonlinear Sciences and Numerical Simulation, 2016
- An Improved Particle Swarm Optimization AlgorithmApplied Mechanics and Materials, 2013
- Parameters analysis of shearer drum loading performanceMining Science and Technology (China), 2011
- Firefly algorithm, stochastic test functions and design optimisationInternational Journal of Bio-Inspired Computation, 2010
- Study on pick arrangement of shearer drum based on load fluctuationJournal of China University of Mining and Technology, 2008
- A fast and elitist multiobjective genetic algorithm: NSGA-IIIEEE Transactions on Evolutionary Computation, 2002
- Approximating the Nondominated Front Using the Pareto Archived Evolution StrategyEvolutionary Computation, 2000
- Ant colony system: a cooperative learning approach to the traveling salesman problemIEEE Transactions on Evolutionary Computation, 1997
- Ant system: optimization by a colony of cooperating agentsIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1996
- The concept of specific energy in rock drillingInternational Journal of Rock Mechanics and Mining Sciences, 1965