2022
DOI: 10.1016/j.measurement.2022.111722
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Intelligent decision method for the position and attitude self-adjustment of hydraulic support groups driven by a digital twin system

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Cited by 21 publications
(5 citation statements)
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“…Meanwhile the mining height of the working face is also getting higher. These all cause the support to bear a large number of dynamic loads and reducing its reliability [8,12,22,27].…”
Section: Eksploatacja I Niezawodnosc -Maintenance and Reliabilitymentioning
confidence: 99%
“…Meanwhile the mining height of the working face is also getting higher. These all cause the support to bear a large number of dynamic loads and reducing its reliability [8,12,22,27].…”
Section: Eksploatacja I Niezawodnosc -Maintenance and Reliabilitymentioning
confidence: 99%
“…The results show that with the increase in the caving interval, the amount of single caving increases [26]. Jiao et al reconstructed the position and attitude of the hydraulic support, completed the virtual decision making, virtual execution, and strategy optimization of the virtual space adjustment behavior, and finally realized the self-adjustment of the position and attitude of the support [27]. Li et al realized different parameter configurations in the process of following machine automation according to the principle of three-machine cooperation, an established support behavior process decision model, and a supporting equipment linearity collaborative control model of coal mining technology, and previewed the decision model in a virtual scene.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, repeated recalculations and continuous changes are required. As a result, the expected outcome is often not achieved (Jiao et al 2022). Thus, in the teaching phase of the mining equipment, it is highly important to fully consider the actual operating conditions, quickly identify the problems in equipment operation and maintenance, and validate the actual working conditions at the early stage of testing.…”
Section: Introductionmentioning
confidence: 99%