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The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
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Related Experiment Video

Updated: Sep 11, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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Multitask allocation model of the coal foreign object sorting robot based on optimal capacity and benefit.

Wu Xudong1, Cao Xiangang2, Ding Wentao1

  • 1School of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an, Shaanxi Province, China.

Scientific Reports
|August 11, 2025
PubMed
Summary

This study introduces a novel robot sorting system for coal foreign objects, improving coal quality and safety. The proposed genetic algorithm strategy significantly enhances sorting efficiency compared to existing methods.

Keywords:
Benefit functionCoal foreign object sorting robotLocally constrained multi-capacityMulti-task allocationOptimal capacity function

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Area of Science:

  • Robotics and Automation
  • Materials Science
  • Environmental Engineering

Background:

  • Existing coal gangue sorting methods struggle with complex, random foreign objects.
  • Current approaches fail to optimize coal quality, human-machine safety, and environmental impact simultaneously.

Purpose of the Study:

  • To develop an intelligent multi-task allocation model for coal foreign object sorting robots (CFoSR).
  • To enhance coal quality, human-machine safety, and reduce environmental pollution through optimized sorting.

Main Methods:

  • A multi-task allocation model for CFoSR based on optimal capacity and benefit was constructed.
  • A multi-evaluation index fitness function considering gangue mass and sundry count was designed.
  • A combined rule strategy based on a genetic algorithm (GACRS) was proposed, incorporating FIFO, BF, and SPT rules.

Main Results:

  • The GACRS achieved a 24.73% higher optimal fitness value than the greedy algorithm in simulations.
  • Experimental results on the CFoSR platform showed GACRS outperformed the greedy algorithm by 14.02% in optimal fitness.
  • Analysis revealed the impact of scheduling rules, manipulators, belt speed, and coal flow on sorting performance.

Conclusions:

  • The proposed GACRS provides an effective solution for intelligent coal foreign object sorting.
  • The developed model and method offer significant improvements in sorting efficiency and overall system performance.
  • This research contributes to advancing automation in the mining industry for better resource management and safety.