Positioning Accuracy Evaluation for the Collaborative Automation of Mining Fleet With the Support of Memory Cutting Technology

Abstract

Taking mining fleet constituted by a shearer, hydraulic supports and a scraper conveyor as the object, the mining fleet needs to move to the intended position in accordance with the functional requirements, such as machinery tracking of hydraulic supports and memory cutting of the shearer. This paper proposes a shearer wireless positioning method under the conditions of inaccurate anchor nodes. First, action rules for hydraulic supports and an adaptive height adjustment strategy for the shearer are arranged based on analyzing the cooperative movement of mining fleet. Second, the duality mapping between local strong signal sets and positioning spatial domain is revealed, and inaccurate anchor nodes can be refined using the memory cutting and motion constraints of mining fleet. Third, an extended Cramer-Rao lower bound is derived to seek the inherent relationships among shearer positioning accuracy, multi-source errors, and coordinate errors of anchor nodes. Finally, comprehensive experiments for the analytical accuracy assessment and node configuration of shearer positioning are achieved with the support of memory cutting technology. Research results indicate that the proposed shearer positioning can satisfy the requirements of mining fleet, which can provide the theoretical basis for the collaborative automation of mining fleet on fully mechanized mining face.

Keywords

• Mechanized mining face
• mining fleet
• collaborative automation
• shearer positioning
• memory cutting technology