A Review of Intelligent Unmanned Mining Current Situation and Development Trend

Zhang, Kexue; Kang, Lei; Chen, Xuexi; He, Manchao; Zhu, Chun; Li, Dong

doi:10.3390/en15020513

Cited by 50 publications

(14 citation statements)

References 27 publications

(22 reference statements)

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“…China has achieved rapid economic growth over 30 years, especially in the mining industry (both coal and metal mines) [16,17].…”

Section: Mining Groundwater Pollutionmentioning

confidence: 99%

The Recent Progress China Has Made in Green Mine Construction, Part I: Mining Groundwater Pollution and Sustainable Mining

Jiang³

et al. 2022

IJERPH

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With the development of technology, the concepts of “green” and “sustainable” have gradually been popularized in all walks of life. With the continuous development of the world mining industry, the efficiency of resource development in various countries has been improved, but mining activities and production will undoubtedly bring many environmental pollution problems. As a mining power, China is one of the first countries to put forward the concept of “green mining”. Over the years, as people emphasize safety and environmental protection, green mining technology has become the hot topic. At the same time, groundwater pollution caused by mining has become the focus of China’s “green mine construction”: with the continuous development of mining, mining activities and production will also undoubtedly bring significant environmental pollution. The environmental pollution of the mined area has a vital influence on the surrounding environment. The pollutants mainly come from mining operations and production of the mineral processing industry, including process wastewater, gas waste, smelting slag, etc., which are all acidic. Acid mine drainage (AMD) occurs in the process of mining production, due to the structure of minerals and the complex reactions between oxygen and minerals, and results in heavy metal ions leaching into groundwater. Once the groundwater is polluted, it will slowly flow to the surrounding area, resulting in the migration and diffusion of pollutants in the groundwater, affecting the surrounding rivers, farmland, and drinking water for residents. In recent years, environmental damage caused by groundwater pollution from underground mines in Shijiazhuang, China, and Selangor, Malaysia, has had a negative impact on rivers, farmland, and human health. At the same time, the paper introduces many key technologies of green mine construction, such as the backfill mining method. In cooperation with China Road & Bridge Corporation, this paper also introduces the progress in the reuse of mining waste, especially the use of mining waste as aggregate to prepare concrete materials for road and bridge construction. This information article introduces the development status of green mine construction in China and briefly reviews the key technologies of green mine construction in China.

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“…China has achieved rapid economic growth over 30 years, especially in the mining industry (both coal and metal mines) [16,17].…”

Section: Mining Groundwater Pollutionmentioning

confidence: 99%

The Recent Progress China Has Made in Green Mine Construction, Part I: Mining Groundwater Pollution and Sustainable Mining

Jiang³

et al. 2022

IJERPH

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“…The intelligentization of tunneling work surfaces has become a hot research topic and has made certain achievements in areas such as advanced detection, position detection, autonomous cutting, collaborative operations, fault diagnosis, digital twins, and remote monitoring and control. However, there are still many key problems to be solved, such as precise guidance and control of tunneling machines, coordinated control of equipment, perception of the coal-rock interface, multi-dimensional perception of tunneling environment parameters, and lowlatency data transmission [4][5][6]. The fundamental requirement for tunneling is precise directional excavation, and the precise guidance and control of the tunneling machine is the premise to ensure accurate directional excavation of tunnels without human intervention.…”

Section: Introductionmentioning

confidence: 99%

Position measurement technology of boom-type roadheader based on binocular vision

Cheng,

Wang,

Zheng

et al. 2023

Meas. Sci. Technol.

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Positioning of underground mining equipment in coal mines is a primary challenge in the intelligent development of tunnel excavation. Accurate and reliable position measurement plays a crucial role in improving excavation efficiency. However, the stability and accuracy of traditional measurement methods are difficult to guarantee due to factors such as vibration, magnetic interference, and the absence of GPS signals in coal mine environments. To address the problem of unstable measurement of the boom-type roadheader‘s position, this paper proposes a binocular vision-based measurement technique that utilizes four light spots as characteristic points. By processing the target images captured by the binocular camera and combining the minimum bounding rectangle and ellipse fitting of the spot regions, the method successfully obtains the four light spot characteristics. Subsequently, precise matching and stereo distance measurement of the target in the left and right images enable the determination of the boom-type roadheader’s posi-tion information. A positioning platform based on binocular vision is built and experimentally evaluated. The results demonstrate that this method can achieve accurate spot extraction and stable measurement of the machine’s position, even in complex backgrounds such as mixed lighting and low illumination. The planar measurement errors within a distance range of 50 m are all within ±25 mm, which basically meets the required construction precision for tunnel excavation.

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“…With the increase in global demand for energy, coal mining equipment is developing in the direction of being large-scale and intelligent [ 1 , 2 ]. Scraper conveyors are mainly responsible for conveying coal in coal mining.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Fault Diagnosis Method Based on VMD-Hilbert Spectrum and ShuffleNet-V2: Application to the Gears in a Mine Scraper Conveyor Gearbox

Wang,

Guo,

Zhao

et al. 2023

Sensors

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This paper introduces a fault diagnosis method for mine scraper conveyor gearbox gears using motor current signature analysis (MCSA). This approach solves problems related to gear fault characteristics that are affected by coal flow load and power frequency, which are difficult to extract efficiently. A fault diagnosis method is proposed based on variational mode decomposition (VMD)–Hilbert spectrum and ShuffleNet-V2. Firstly, the gear current signal is decomposed into a series of intrinsic mode functions (IMF) by using VMD, and the sensitive parameters of VMD are optimized by using a genetic algorithm (GA). The Sensitive IMF algorithm judges the modal function sensitive to fault information after VMD processing. By analyzing the local Hilbert instantaneous energy spectrum for fault-sensitive IMF, an accurate expression of signal energy changing with time is obtained to generate the local Hilbert immediate energy spectrum dataset of different fault gears. Finally, ShuffleNet-V2 is used to identify the gear fault state. The experimental results show that the accuracy of the ShuffleNet-V2 neural network is 91.66% after 778 s.

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A Review of Intelligent Unmanned Mining Current Situation and Development Trend

Cited by 50 publications

References 27 publications

The Recent Progress China Has Made in Green Mine Construction, Part I: Mining Groundwater Pollution and Sustainable Mining

The Recent Progress China Has Made in Green Mine Construction, Part I: Mining Groundwater Pollution and Sustainable Mining

Position measurement technology of boom-type roadheader based on binocular vision

Intelligent Fault Diagnosis Method Based on VMD-Hilbert Spectrum and ShuffleNet-V2: Application to the Gears in a Mine Scraper Conveyor Gearbox

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