This study considered the role of coal as China’s basic energy source and examines the development of the coal industry. We focused on the intelligent development of coal mines, and introduced the “Chinese mode” of intelligent mining in underground coal mines, which uses complete sets of technical equipment to propose classification and grading standards. In view of the basic characteristics and technical requirements of intelligent coal mine systems, we established a digital logic model and propose an information entity and knowledge map construction method. This involves an active information push strategy based on a knowledge demand model and an intelligent portfolio modeling and distribution method for collaborative control of coal mines. The top-level architecture of 5G+ intelligent coal mine systems combines intelligent applications such as autonomous intelligent mining, human–machine collaborative rapid tunneling, unmanned auxiliary transportation, closed-loop safety control, lean collaborative operation, and intelligent ecology. Progress in intelligent mining technology was described in terms of a dynamic modified geological model, underground 5G network and positioning technology, intelligent control of the mining height and straightness of the longwall working face, and intelligent mining equipment. The development of intelligent coal mines was analyzed in terms of its imbalances, bottlenecks, and the compatibility of large-scale systems. Implementation ideas for promoting the development of intelligent coal mines were proposed, such as establishing construction standards and technical specifications, implementing classification and grading standards according to mining policy, accelerating key technology research, and building a new management and control model.

The battery management system (BMS) is the main safeguard of a battery system for electric propulsion and machine electrification. It is tasked to ensure reliable and safe operation of battery cells connected to provide high currents at high voltage levels. In addition to effectively monitoring all the electrical parameters of a battery pack system, such as the voltage, current, and temperature, the BMS is also used to improve the battery performance with proper safety measures within the system. With growing acceptance of lithium-ion batteries, major industry sectors such as the automotive, renewable energy, manufacturing, construction, and even some in the mining industry have brought forward the mass transition from fossil fuel dependency to electric powered machinery and redefined the world of energy storage. Hence, the functional safety considerations, which are those relating to automatic protection, in battery management for battery pack technologies are particularly important to ensure that the overall electrical system, regardless of whether it is for electric transportation or stationary energy storage, is in accordance with high standards of safety, reliability, and quality. If the system or product fails to meet functional and other safety requirements on account of faulty design or a sequence of failure events, then the environment, people, and property could be endangered. This paper analyzed the details of BMS for electric transportation and large-scale energy storage systems, particularly in areas concerned with hazardous environment. The analysis covers the aspect of functional safety that applies to BMS and is in accordance with the relevant industrial standards. A comprehensive evaluation of the components, architecture, risk reduction techniques, and failure mode analysis applicable to BMS operation was also presented. The article further provided recommendations on safety design and performance optimization in relation to the overall BMS integration.

This paper studies the precise position control of the hydraulic cylinder in the hydraulic support. The aim of this paper is to develop a method of hydraulic cylinder position control based on pressure and flow coupling, which takes the coupling feedback of load and flow into account, especially in the scene of cooperative control under the condition of multiple actuators and variable load. This method solves the problems of slow movement and sliding effect of hydraulic support in the traditional time-dependent hydraulic position control, as well as better realizes the intelligent and unmanned development of the fully mechanized mining face. First, based on the flow continuity equation and Newton Euler dynamic equation, the flow and stroke control model with the input and output pressure of hydraulic cylinder is established. Then, the effectiveness and correctness of the control model are verified by the comparison between the hydraulic system simulation software, AMESim, and the experiment. Finally, a test system is built. When the system pressure is large than 10 MPa, the error between the data determined by the fitting algorithm and the actual detection data is within 5%, which verifies the effectiveness of the theory and simulation model.

We present Bento Box, a virtual reality data visualization technique and bimanual 3D user interface for exploratory analysis of 4D data ensembles. Bento Box helps scientists and engineers make detailed comparative judgments about multiple time-varying data instances that make up a data ensemble (e.g., a group of 10 parameterized simulation runs). The approach is to present an organized set of complementary volume visualizations juxtaposed in a grid arrangement, where each column visualizes a single data instance and each row provides a new view of the volume from a different perspective and/or scale. A novel bimanual interface enables users to select a sub-volume of interest to create a new row on-the-fly, scrub through time, and quickly navigate through the resulting virtual “bento box.” The technique is evaluated through a real-world case study, supporting a team of medical device engineers and computational scientists using in-silico testing (supercomputer simulations) to redesign cardiac leads. The engineers confirmed hypotheses and developed new insights using a Bento Box visualization. An evaluation of the technical performance demonstrates that the proposed combination of data sampling strategies and clipped volume rendering is successful in displaying a juxtaposed visualization of fluid-structure-interaction simulation data (39 GB of raw data) at interactive VR frame rates.