Methodology in early detection of conveyor belt fire in coal transportation

Ray, S. K.; Khan, Asfar Mobin; Mohalik, N.K.; Mishra, Debashish; Varma, N. K.; Pandey, Jai Krishna; Singh, Pradeep K.

doi:10.1080/15567036.2020.1823527

Cited by 8 publications

(4 citation statements)

References 15 publications

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“…By inputting the extracted flame characteristics into a neural network, real-time fire detection can be accomplished. During transportation, the friction between the belt conveyor tape and coal or gangue generates heat, which also poses a hidden risk of fire [190] . Nevertheless, the accuracy of fire identification and positioning may be affected by some factors, such as high-concentrate smoke, long measurement distance, uneven illumination, and even red clothes, which need to be further improved by intelligent algorithms.…”

Section: ) Fire Monitoring and Preventionmentioning

confidence: 99%

Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review

Du,

Zhang,

Liang

et al. 2023

IEEE Access

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The realization of intelligent mining is the only method for realizing high-quality development in the coal industry. As the forefront working link in mine production, achieving automatic roadway tunneling control is key to improving production efficiency, enhancing intelligence, and reducing accident rates at fully mechanized tunneling working faces. Among various detection techniques, machine vision technology stands out with advantages of non-contact measurement, rich information acquisition, and high detection accuracy. The detection and control of tunneling equipment groups based on machine vision has become a research hotspot in the intelligence process of coal mines. This study first introduces the key technologies of a visual detection system, including camera calibration, image preprocessing, feature extraction, visual matching, target segmentation and recognition, visual measurement, and 3D reconstruction. It then elaborates on detection principles, workflows, limitations, precautions, and development status of various vision detection systems in practical application scenarios at tunneling faces, such as tunneling equipments, anchoring systems, transportation systems, and safety auxiliary systems, which significantly improve production safety and efficiency. Finally, considering challenging work conditions and strong interference in mines, the successful adaptation of machine vision to excavation sites relies on addressing technical challenges related to poor environment adaptability, limited imaging field of view, and low intelligence level. Furthermore, according to existing research results and the current technical status, this paper forecasts key technologies that need to be developed in the future for coal mine intelligent equipment systems based on machine vision, including multi-sensor information fusion, equipment group collaborative control, and digital twin-driven remote monitoring.INDEX TERMS Machine vision, coal machinery equipment, detection and measurement, roadway fully mechanized tunneling faces, unmanned coal mine.

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Section: ) Fire Monitoring and Preventionmentioning

confidence: 99%

Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review

Du,

Zhang,

Liang

et al. 2023

IEEE Access

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“…Fire poses one of the primary hazards to conveyor belts, encompassing not only the drives but also the entire structures [10,11]. The probability of conveyor fires is heightened by the expansive nature of conveyor systems [12], complex routing, and demanding working conditions arising from substantial mechanical loads and aggressive work environments [13].…”

Section: Introductionmentioning

confidence: 99%

Determining and Verifying the Operating Parameters of Suppression Nozzles for Belt Conveyor Drives

Bałaga,

Kalita,

Siegmund

et al. 2023

Energies

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Drives in belt conveyors are critical components of the conveyor system, susceptible to various factors that can cause disruptions and energy losses. In underground mining conditions, the risk of drive fires is particularly hazardous. Therefore, it is necessary to develop highly effective fire suppression systems. However, there are no guidelines for designing such systems. This study presents a methodology for selecting and verifying the fire suppression systems for belt conveyor drives. The proposed AMIGA system for extinguishing fires on underground coal mine conveyor belts, incorporating spraying and water mist installations, is supported by a theoretical calculation methodology. This enables determining the number of required nozzles and flow rate for complete fire suppression. The development of a methodology for the selection and verification of the sprinkler system components utilized guidelines provided in the standard VdS 2109:2002-03 and the PN-EN 12845+A2 standard from 2010, while a novel approach is proposed for water mist parameters that has not been previously applied anywhere else, and is based on assessing the fire’s intensity and the persistent disruption of the energy balance of the combusted coal. The theoretical calculations for potential fire power facilitate the determination of the appropriate water flow rate for the spraying system to protect the upper belt drive. For the proposed AMIGA system, the potential fire power was calculated to be 10.33MJ/min. Based on this, the water flow rate for the spraying installation to protect the upper drive belt of the conveyor was established to be a minimum 37.5dm3/min, and 21.4dm3/min for the mist installation used to protect the space below the conveyor drive. In order to verify the developed methodology for parameter selection, on-site tests were conducted to verify the results. Tests were conducted on an AMIGA prototype suppression system integrated into a conveyor drive. The results demonstrate that the developed system is effective in extinguishing fires on the belt using the spraying installation, as well as under the conveyor belt drive using the water mist installation, within the entire supply pressure range ( 0.4MPa to 1.6MPa ).

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“…Conveyor lines can be tens kilometers long, and the length of one conveyor can exceed one kilometer. The prompt detection of faults is difficult without special facilities [7,8] as it is necessary to inspect each roller in the conveyor line, and the number of the rollers may exceed six thousand [9,10]. The automated fire extinguishment systems are only provided at the power-drive and tension stations of conveyors and are absent along the conveyor flight.…”

Section: Introductionmentioning

confidence: 99%

Modeling heating of faulty roller of belt conveyor in the presence of coal dust

Malashkina¹,

Shaportov²

2023

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Belt conveyor is a common means of transport in underground mines. At the same time, longwalls equipped with belt conveyors face high fire risk. One of the fire causes on belt conveyors is the seizure of rollers and their friction on the loaded belt in the long flight regions. The modern detectors of fire on belt conveyors fail to ensure ultra early sensing of inflammation. This article describes modeling of heating of a faulty roller in friction with a moving conveyor belt with a layer of coal dust. The modeling has found the rate of heating of the belt conveyor roller up to the temperature of the ultra early fire development with inflammation of coal dust particles, and the degree of effect of the coal dust layer on the fire onset speed. The graphic chart is plotted for the heat balance of a belt conveyor roller in friction-induced heating.

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Methodology in early detection of conveyor belt fire in coal transportation

Cited by 8 publications

References 15 publications

Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review

Applications of Machine Vision in Coal Mine Fully Mechanized Tunneling Faces: A Review

Determining and Verifying the Operating Parameters of Suppression Nozzles for Belt Conveyor Drives

Modeling heating of faulty roller of belt conveyor in the presence of coal dust

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