Multi-objective niching quantum genetic algorithm-based optimization method for pneumatic hammer structure

Jine Cao

doi:10.1016/j.eswa.2023.122047

Multi-objective niching quantum genetic algorithm-based optimization method for pneumatic hammer structure

2024-03-01

2

PRE

AI

DOI：10.1016/j.eswa.2023.122047

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Pneumatic down-the-hole (DTH) hammer drilling technology has been used extensively in various drilling ap-plications owing to its high drilling efficiency, low gas consumption, non-polluting nature, and safety. Opti-mizing the hammer structure using empirical approaches is challenging due to the highly complex nonlinear problem caused by the piston movement. To address it, the intelligent algorithm is introduced for the first time and a multi-objective niching quantum genetic algorithm-based (MNQGA) optimization method for pneumatic hammer structure design is proposed in this study, to simultaneously maximize impact energy and minimize air consumption or optimize these objectives individually. Additionally, a novel niching strategy, corresponding adaptive quantum rotation gate, and mutation strategy are designed for the proposed method. The radial structures of a GQ127-type pneumatic hammer are optimized to maximize impact energy, followed by the optimization of the axial structures to satisfy four working conditions. The results show that different optimi-zation objectives and constraints lead to different axial structural parameter values. After optimization, the hammer air consumption is reduced by at least 50.80 % at a constant impact energy of 350 J. The hammer impact energy is improved by more than 15.93 % if the volumetric flow rate of the supplied air is maintained at 10 m3/min. In addition, the effects of the hammer's axial structure on its impact energy are investigated in detail based on an analytical model to validate the results of the proposed method. Five axial structure parameters are analyzed that have different effects on the impact energy. Within the given constraints, these parameters have their own optimal values that can be easily obtained using the proposed method. That is, the optimizations using the proposed method are consistent with those of the analytical models published in the literature. Therefore, the proposed method is efficient and accurate and can be used confidently when designing pneumatic hammers.

Keyword:

Quantum genetic algorithm

Optimization design

Pneumatic down -the -hole hammer

Percussive drilling

Multi-objective niching quantum genetic algorithm-based optimization method for pneumatic hammer structure

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