Research Status and Development Trend of Unmanned Driving Technology in Coal Mine Transportation

Wang, Maosen; Bao, Jiusheng; Yuan, Xiaoming; Yin, Yan; Khalid, Shah

doi:10.3390/en15239133

Cited by 11 publications

(7 citation statements)

References 30 publications

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“…(1) Each factor in the criterion layer is compared separately in each element (scheme) in the scheme layer. Their importance is scored using the numbers in the interval (1,9) to form a judgment matrix. After the consistency ratio test C × R = λ max −n (n−1)R×I < 0.1 is met, the weight direction w i = (w 1 , w 2 , .…”

Section: Determination Of Assessment Index Weightsmentioning

confidence: 99%

“…The majority of these accidents are caused by fire-induced gas explosions, with the severity of death reaching more than nine people per fire accident, and the severity of death in all other accidents is less than that of fire accidents, so coal mines need to pay sufficient attention to fire [4][5][6]. In recent years, China's coal enterprises also generally pay attention to the prevention of coal mine fire accidents, and the construction of a major disaster prevention and protection system for China's coal enterprises has gone through five stages: passive prevention, traditional empirical prevention pre-prevention post-prevention, systematic prevention and protection, and systematic scientific management [7][8][9]. At present, most of China's coal enterprises are still in the fourth stage, and the emergency rescue construction of China's coal enterprises still has problems in all aspects.…”

Section: Introductionmentioning

confidence: 99%

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Coal Mine Fire Emergency Rescue Capability Assessment and Emergency Disposal Research

et al. 2023

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Nowadays, underground coal mine accidents occur frequently, causing huge casualties and economic losses, most of which are gas explosion accidents caused by fires. In order to improve the emergency rescue capability of coal mine fires and reduce the losses caused by coal mine fires, this article is dedicated to the assessment of coal mine fire rescue capability. Taking the fire emergency rescue system of Lugou mine as an example, based on the introduction of gray system theory and gray evaluation method, an evaluation model was established to assess the risk of the fire emergency rescue index system of Lugou mine. Four primary and 19 secondary indicators were delineated, and a hierarchical structure model of the fire emergency rescue capability of the Lugou mine was established by combining expert opinions, and the weights of indicators at all levels were calculated by using hierarchical analysis. We then used the gray system evaluation method and expert scoring to judge the safety level of various indicator factors in the index system. The evaluation results show that the risk level of the emergency rescue system of the Lugou mine fire is higher than the fourth level. The main risk indicator factors are firefighting equipment, decision-making command, emergency education and training, and fire accident alarm. In response to this evaluation result, corresponding control measures were formulated in four aspects: rescue organization guarantee, personnel guarantee, material guarantee, and information guarantee, which optimally improved the emergency rescue capability of the Lugou mine fire and reduced the loss caused by fire.

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Section: Determination Of Assessment Index Weightsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Coal Mine Fire Emergency Rescue Capability Assessment and Emergency Disposal Research

et al. 2023

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“…In June 2021, the National Energy Administration and the National Mine Safety Supervision Bureau collaborated to release the "Guidelines for the Intelligent Construction of Coal Mines". These guidelines aim to facilitate the systematic and organized implementation of intelligent construction practices across the coal mining industry [3]. The auxiliary transportation vehicles usually employed in underground coal mines are regarded as one of the most frequently utilized means of transportation [4].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy PID Control Design of Mining Electric Locomotive Based on Permanent Magnet Synchronous Motor

Ma,

Huang,

Basher

et al. 2024

Electronics

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Achieving precise stopping of electric locomotives is crucial for the realization of intelligent and unmanned auxiliary transportation systems. Presently, human drivers play a central role in ensuring accurate stopping, presenting obstacles to automation and cargo location precision, especially within the coal mining sector. This article centers on achieving the precise stopping of electric locomotives under various conditions through the utilization of permanent magnet synchronous motor-driven locomotives. This approach introduces a novel stopping control method that integrates a fuzzy proportional–integral–derivative (F-PID) controller with a vector control model for permanent magnet synchronous motors (PMSM). Subsequently, we develop the F-PID controller using the PMSM technique, incorporating new fuzzy rules for each subsystem to enhance control accuracy and efficiency. Finally, extensive simulations and real-world experiments are conducted on an electric locomotive stopping test bed to validate the effectiveness of the proposed control method. The results show that the method consistently achieves precise stopping under diverse working conditions, with an error of less than 0.3 m, confirming its robustness and reliability.

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“…Transportation issues are also examined in the context of ensuring the safety of mining crews, including in the studies by Tu et al 2023 [13], Li et al (2022) [14], Fabiano et al (2014) [15], and Thakur (2019) [16]. This trend also includes advanced studies on unmanned transportation carried out in the spirit of smart technologies, as demonstrated by Wang et al (2022) [17]. Transportation also appears as a subject of consideration for individual links of mining production, such as in Yuan et al 2022 [18], Krauze et al (2020) [19], and Szewerda et al (2021) [20].…”

Section: Introductionmentioning

confidence: 99%

The Optimal Transportation Option in an Underground Hard Coal Mine: A Multi-Criteria Cost Analysis

Bąk,

Turek,

Bednarczyk

et al. 2024

Resources

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The issue of transport in underground hard coal mines is very rarely described in the literature. The financial aspects of this issue are even less often analyzed. Publications in this area focus on technical issues and the safety of mining crews. More attention is paid to transport in open-pit mines. The above premises and practical needs imply the need to conduct economic analyses of transport systems in underground hard coal mines. This paper is a scientific communication, which presents the concept of a multi-criteria cost analysis as a tool to support the selection of the optimal transportation option in an underground hard coal mine. Considerations in this area have not been carried out in the relevant literature, and the problem of selecting a transportation option is a complex and necessary issue in the practice of underground mines with extensive mine workings. The methodology presented includes five cost criteria (costs of carrying out the transportation task; route expansion costs; rolling stock maintenance costs; depreciation costs; and additional personnel costs). The simultaneous application of criteria relating to utility properties in addition to cost criteria makes it possible to adopt a specific technical and organizational model of the transportation system based on the indication of the optimal solution, resulting from the mathematical construction of functions of objectives relating to utility and cost. The optimal variant of the designed system and configuration of the material transportation system in underground workings takes into consideration the following: (1) seven utility criteria (KU1—transportation task completion time; KU2—compatibility of transportation systems; KU3—continuous connectivity; KU4—co-use with other transportation tasks; KU5—safety; KU6—inconvenience; KU7—operation under overplanning conditions) and (2) five cost criteria (KK1—costs of implementing the transportation task; KK2—costs of route expansion; KK3—rolling stock maintenance costs; KK4—depreciation costs; KK5—additional personnel costs). Based on the aforementioned criteria, two objective functions are built for each option: utility and cost. They present divergent goals; therefore, they are non-cooperative functions. Both utility and costs strive for the maximum. In the developed methodology, an ideal point is usually a fictitious solution representing a set of maximum values among all the achievable values in a set of solutions, but it is impossible to achieve this simultaneously based on all the criteria. This point illustrates the maximum utility and lowest cost among the alternatives considered, which is obviously impossible for any of the variants to meet at the same time, although it indicates the possibilities of the technique and the range of costs. For the developed method, a so-called “PND” nadir point is also determined, representing the least-preferred level of achievement of all goals simultaneously, determined from the set of optimal points in the Pareto sense. The originality of the conceptual considerations undertaken stems from: filling the gap in the economic methodology of complex transportation systems evaluation; embedding considerations in the trend concerning complex transportation systems of underground mines; and focusing considerations on the pre-investment phase, making it possible to optimize costs before expenditures are incurred.

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Research Status and Development Trend of Unmanned Driving Technology in Coal Mine Transportation

Cited by 11 publications

References 30 publications

Coal Mine Fire Emergency Rescue Capability Assessment and Emergency Disposal Research

Coal Mine Fire Emergency Rescue Capability Assessment and Emergency Disposal Research

Fuzzy PID Control Design of Mining Electric Locomotive Based on Permanent Magnet Synchronous Motor

The Optimal Transportation Option in an Underground Hard Coal Mine: A Multi-Criteria Cost Analysis

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