Influence of Drum Cutting Height on Shearer Cutting Unit Vibration by Co-Simulation Method

Sun, Lin; Jiang, Kaiwen; Zeng, Qingliang; Gao, K. D.; Zhang, X. D.

doi:10.2507/ijsimm20-1-548

Cited by 6 publications

(6 citation statements)

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“…At this time, the cutting wheel of the shearer does not move, the cutting work is reduced, and the coal seam mining is affected. Therefore, it is very important to improve the shear wheel model, which has been studied by many researchers before [1]. Shears are one of the main equipment of fully mechanised coal mining face production, which together with scraper conveyor and hydraulic support are collectively called 'three machines' of the working face.…”

mentioning

confidence: 99%

Retracted: Research on intelligent elevation control method of shearer drum based on deep learning

Zhang

2023

IET Software

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Research on deep learning and shearer drum elevation control is a hot topic in recent years. The shearer drum elevation control based on deep learning has been paid attention to by the majority of researchers and a series of studies have been carried out. In order to solve the problem that the traditional memory cutting method of shearer is not accurate, the research on intelligent elevation control method of shearer drum based on deep learning is proposed. In this essay, the intelligent control system of drum elevation of shearer is modelled mathematically, and the improved deep-learning firefly algorithm is used to optimise the PID parameters of the drum control system, and the Simulink simulation model of the intelligent control system of drum elevation is built. The response of the system using the improved and basic firefly algorithm is analysed. The experimental results show that the overshoot of the optimised system decreases by 21.6% under the step signal. Under the ramp signal, the overshoot of the optimised system decreased by 38.4%. Under the pulse interference signal, the overshoot of the optimised system is reduced by 21.9%. Under the step interference signal, the overshoot of the optimised system is reduced by 33.2%. Under the random interference signal, the wave range of the optimised response curve is reduced by 40.1%. Conclusion: After adding the PID controller optimised by the improved deep learning firefly algorithm to the drum elevation control system, the response performance and anti-interference performance of the system are greatly improved and enhanced. The research of this article provides important guidance for deep learning and shearer drum elevation control. K E Y W O R D S biomedical electronics, combinatorial mathematics | INTRODUCTIONThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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confidence: 99%

Retracted: Research on intelligent elevation control method of shearer drum based on deep learning

Zhang

2023

IET Software

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“…The shearer has been confirmed as the critical equipment for the fully mechanized mining face in the coal mine. The shearer comprises the cutting department for coal cutting, the transmission system for power transmission, as well as the hydraulic height adjustment system [23]. To be specific, the hydraulic height adjustment system is a vital part of the shearer, which is mainly responsible for adjusting the height of the cutting drum [28].…”

Section: Case Analysismentioning

confidence: 99%

Multi-dimensional T-S dynamic fault tree analysis method involving failure correlation

Chen,

Liu,

Yao

et al. 2023

IFS

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The lack of effective failure correlation analysis is one main reason for the gap between the reliability models and the actual complex systems with mixed static and dynamic characteristics. Takagi and Sugeno (T-S) dynamic fault tree is one powerful tool to analyze the static and dynamic failure logic relationship but it assumes the failure probability of the event is independent. Therefore, this paper proposes a multi-dimensional T-S dynamic fault tree analysis method involving failure correlation. The method integrates the failure probability distribution function of basic events with multi-factors and the multi-dimensional copula function, and the important measure of this method is also deduced. The reliability model expression for systems with failure correlations, both in series and in parallel, is discussed and verified. Compare the proposed method with the assumption that the probability of a failure event is independent. This method solves the problem of a large error when ignoring the failure correlation between parts and the degree of the correlation between variables can be characterized. The reliability analysis can be conducted on complex systems affected both by multi-factors and failure correlations. The proposed method is applied to the reliability analysis of a hydraulic height adjustment system and the correctness and superiority of the method are verified.

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“…Based on the wavelet denoising and independent component analysis, Ding et al [ 15 ] proposed a nonlinear signal blind source separation and fault feature identification method, which was experimentally verified to be able to separate the vibration source of the shearer faults from nonlinear mixed signals and to be able to identify the vibration features of the shearer's fault at the early stage. Sun et al [ 16 ] established the electromechanical coupling model of the shearer cutting unit, and they analyzed the influence of rocker height and hydraulic system on the vibration of the shearer. The results show that the drum height does not directly affect the shearer vibration but the pressure change of the hydraulic cylinder aggravates the shearer vibration.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on shearer traction vibration considering attitude disturbances

Ma,

Wan,

Zeng

et al. 2024

Heliyon

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Influence of Drum Cutting Height on Shearer Cutting Unit Vibration by Co-Simulation Method

Cited by 6 publications

References 0 publications

Retracted: Research on intelligent elevation control method of shearer drum based on deep learning

Retracted: Research on intelligent elevation control method of shearer drum based on deep learning

Multi-dimensional T-S dynamic fault tree analysis method involving failure correlation

Experimental study on shearer traction vibration considering attitude disturbances

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