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采煤机数字孪生切割实验系统设计

Design of Digital Twin Cutting Experiment System for Shearer.

作者信息

Miao Bing, Li Yunwang, Guo Yinan

机构信息

School of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.

Key Laboratory of Intelligent Mining Robotics, Ministry of Emergency Management, Beijing 100083, China.

出版信息

Sensors (Basel). 2024 May 17;24(10):3194. doi: 10.3390/s24103194.

Abstract

This study presents an advanced simulated shearer machine cutting experiment system enhanced with digital twin technology. Central to this system is a simulated shearer drum, designed based on similarity theory to accurately mirror the operational dynamics of actual mining cutters. The setup incorporates a modified machining center equipped with sophisticated sensors that monitor various parameters such as cutting states, forces, torque, vibration, temperature, and sound. These sensors are crucial for precisely simulating the shearer cutting actions. The integration of digital twin technology is pivotal, featuring a real-time data management layer, a dynamic simulation mechanism model layer, and an application service layer that facilitates virtual experiments and algorithm refinement. This multifaceted approach allows for in-depth analysis of simulated coal cutting, utilizing sensor data to comprehensively evaluate the shearer's performance. The study also includes tests on simulated coal samples. The system effectively conducts experiments and captures cutting condition signals via the sensors. Through time domain analysis of these signals, gathered while cutting materials of varying strengths, it is determined that the cutting force signal characteristics are particularly distinct. By isolating the cutting force signal as a key feature, the system can effectively distinguish between different cutting modes. This capability provides a robust experimental basis for coal rock identification research, offering significant insights into the nuances of shearer operation.

摘要

本研究提出了一种采用数字孪生技术增强的先进模拟采煤机切割实验系统。该系统的核心是一个模拟采煤机滚筒,它基于相似理论设计,能够精确反映实际采煤机截割部的运行动态。该装置包括一个经过改装的加工中心,配备了先进的传感器,可监测各种参数,如切割状态、力、扭矩、振动、温度和声。这些传感器对于精确模拟采煤机切割动作至关重要。数字孪生技术的集成至关重要,它具有实时数据管理层、动态仿真机理模型层和应用服务层,便于进行虚拟实验和算法优化。这种多方面的方法允许对模拟煤炭切割进行深入分析,利用传感器数据全面评估采煤机的性能。该研究还包括对模拟煤样的测试。该系统通过传感器有效地进行实验并采集切割状态信号。通过对切割不同强度材料时采集的这些信号进行时域分析,确定切割力信号特征尤为明显。通过将切割力信号作为关键特征分离出来,该系统能够有效区分不同的切割模式。这一能力为煤岩识别研究提供了坚实的实验基础,为深入了解采煤机运行的细微差别提供了重要见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e7/11124836/5d99d3be3882/sensors-24-03194-g001.jpg

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