The boom-type roadheader plays a crucial role in coal mining. However, conducting the real-time monitoring of the mechanical performance and comprehensive adaptive cutting in the dynamic cutting process are challenging. To address these issues, a digital twin system that integrates the elements of "shape, performance, and control" for roadheaders is presented in this paper. The system comprises three components: physical space, service space, and twin space. The service space forms the core of the entire system. Within this space, twin models and control models are created using numerical simulation, artificial intelligence and multi-source data fusion technology. These models serve the purpose of predicting the roadheader's mechanical performance and controlling the swing speed of the cutting arm. The physical space is built using technologies such as robot kinematics, electrical systems, hydraulic transmission, and other relevant techniques. This approach facilitates the transmission of multi-sensor data to twin models. The control model then manages the roadheader's function based on the output signals from the control model. The twin space is constructed utilizing physical rendering engines, databases, and 3D modelling tools. This space visualizes and stores the movement, performance, and control parameters of the roadheader. The results demonstrate that the average absolute error between the measured data from the test's three position strain gauges and the predicted data from the twin system is 10.38 MPa. Furthermore, the twin system achieves an average update interval of 0.34 s, allowing real-time stress monitoring of the structural components of the roadheader and preventing damage caused by overload. The proposed control model enables adaptive adjustment of the swing speed of the cutting arm in approximately 0.3 s. This improvement significantly enhances the adaptive cutting capabilities of roadheaders when dealing with complex coal and rock formations.
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http://dx.doi.org/10.1038/s41598-024-56539-8 | DOI Listing |
Zhonghua Xue Ye Xue Za Zhi
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Institute of Hematology, Tongji Medical College Affiliated Union Hospital, Huazhong University of Science and Technology, Wuhan 430022, China.
Venous thromboembolism (VTE) is clinically manifested as deep vein thrombosis (DVT) and pulmonary embolism (PE). VTE is the third most prevalent vascular disease after coronary artery and cerebrovascular diseases. VTE is a multifactorial disease caused by the interaction of genetic and acquired risk factors.
View Article and Find Full Text PDFClin Transl Med
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Department of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria.
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Department of Perinatal Maternal and Child Medical Center, Shizuoka Children's Hospital, 860 Urushiyama, Aoi-Ku, Shizuoka-Shi, Shizuoka, 420-8660, Japan.
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Phys Med Biol
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Department of Radiology Oncology, Emory University, Clifton Rd, Atlanta, Georgia, 30322-1007, UNITED STATES.
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December 2024
Departments of Orthopaedic Surgery and Neurological Surgery, Duke University Health System, Durham, NC, USA.
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Research Question: The purpose of this study was to investigate the relationship between lumbar DSH and NFD using computed tomography (CT), accounting for influences of patient demographic and anthropometric characteristics.
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