Pre-ignition detection and early fire detection in mining vehicles

Hansen, Rickard

doi:10.1080/25726668.2021.1871820

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…The Department of Mineral Resources in South Africa [56] defines regular inspections of working areas to monitor compliance with fire controls, including preventive procedures, a 250 h inspection of mobile equipment, as well as equipment pre-and postmaintenance inspections, as fire prevention tools. Detection of fires on mining machines is highly dependent on the operator or miners in the vicinity [57]. Utilizing their remarkably sensitive olfactory senses, early detection of smoke becomes feasible, enabling the identification of warning signals encompassing aberrant behavior, heightened vibrations, or unexpected shocks.…”

Section: Acknowledgmentsmentioning

confidence: 99%

Holistic Approach Promotes Failure Prevention of Smart Mining Machines Based on Bayesian Networks

Martinsen,

Fentaye,

Dahlquist

et al. 2023

Machines

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In the forthcoming era of fully autonomous mining, spanning from drilling operations to port logistics, novel approaches will be essential to pre-empt hazardous situations in the absence of human intervention. The progression towards complete autonomy in mining operations must have meticulous approaches and uncompromised security. By ensuring a secure transition, the mining industry can navigate the transformative shift towards autonomy while upholding the highest standards of safety and operational reliability. Experiments involving autonomous pathways for mining machinery that utilize AI for route optimization demonstrate a higher speed capacity than manually operated approaches; this translates to enhanced productivity, subsequently fostering increased production capacity to meet the rising demand for metals. Nonetheless, accelerated wear on crucial elements like tires, brakes, and bearings on mining machines has been observed. Autonomous mining processes will require smarter machines without humans that guide and support actions prior to a hazardous situation occurring. This paper will delve into a comprehensive perspective on the safety of autonomous mining machines by using Bayesian networks (BN) to detect possible hazard fires. The BN is tuned with a combination of empirical field data and laboratory data. Various faults have been recognized, and their correlation with the measurements has been established.

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Section: Acknowledgmentsmentioning

confidence: 99%

Holistic Approach Promotes Failure Prevention of Smart Mining Machines Based on Bayesian Networks

Martinsen,

Fentaye,

Dahlquist

et al. 2023

Machines

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“…However, works [19,20] consider maximal HDs with a constant minimal static response temperature. Paper [21] reports a study into the use of various types of detectors in the engine compartments of mining vehicles. Based on the experiments, it was determined that smoke FDs effectively detect ignition in the engine compartment.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Operational algorithm for a heat detector used in motor vehicles

Kushnir¹,

Kopchak²,

Gavryliuk³

2021

EEJET

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In most cases, fixed temperature heat detectors are used to detect fire in vehicles. The response parameter of such detectors is constant. The time of fire detection by a fire detector, as well as the probability of its false operation, are affected by heat flux from an internal combustion engine. This paper reports the development and investigation of an operational algorithm of the fixed-dynamic heat detectors with variable response parameters. Depending on the temperature influence exerted by engine operation modes, a given algorithm automatically changes a value of the minimal static response temperature of a detector, as well as value of the rate of rise in the temperature of its response. The experimental results showed that in the initial period of engine operation, the temperature change rate in the engine compartment fluctuates and is the largest. It can exceed 290 °С/min. However, regardless of the type of vehicle and the type of engine, when the temperature reaches technological, the temperature change rate would vary within small limits, approximately 30÷50 °С/min. The study results from the Simulink software package (USA) in the MATLAB programming environment (USA) confirm the effectiveness of the programmed operational algorithm of a thermal fire detector. The developed algorithm of a fire detector's operation makes it possible to detect the fire at an early stage and reduce the cases of the device's false response. The fire detector responded to both the maximal and dynamic components. As regards the maximal component, the proposed detector is triggered about 2.3 times faster than the classic maximal thermal fire detector. Detection of fire at an early stage makes it possible to quickly use the fire extinguishing system

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