Advancing respirable coal mine dust source apportionment:a preliminary laboratory exploration of optical microscopy as a novel monitoring tool

Exposure to respirable coal mine dust(RCMD)can cause chronic and debilitating lung diseases.Real-time monitoring capabilities are sought which can enable a better understanding of dust components and sources.In many underground mines,RCMD includes three primary components which can be loosely associated with three major dust sources:coal dust from the coal seam itself,silicates from the surrounding rock strata,and carbonates from the inert‘rock dust’products that are applied to mitigate explosion hazards.A monitor which can reliably partition RCMD between these three components could thus allow source apportionment.And tracking silicates,specifically,could be valuable since the most serious health risks are typically associated with this component-particularly if abundant in crystalline silica.Envisioning a monitoring concept based on field microscopy,and following up on prior research using polarized light,the aim of the current study was to build and test a model to classify respirable-sized particles as either coal,silicates,or carbonates.For model development,composite dust samples were generated in the laboratory by successively depositing dust from high-purity materials onto a sticky transparent substrate,and imaging after each deposition event such that the identity of each particle was known a priori.Model testing followed a similar approach,except that real geologic materials were used as the source for each dust component.Results showed that the model had an overall accuracy of 86.5%,indicating that a field-microscopy based moni-tor could support RCMD source apportionment and silicates tracking in some coal mines.

Smart industrial IoT empowered crowd sensing for safety monitoring in coal mine

The crowd sensing technology can realize the sensing and computing of people,machines,and environment in smart industrial IoT-based coal mine,which provides a solution for safety monitoring through distributed intelligence optimization.However,due to the difficulty of neural network training to achieve global optimality and the fact that traditional LSTM methods do not consider the relationship between adjacent machines,the accuracy of human body position prediction and pressure value prediction is not high.To solve these problems,this paper proposes a smart industrial IoT empowered crowd sensing for safety monitoring in coal mine.First,we propose a Particle Swarm Optimization-Elman Neural Network(PE)algorithm for the mobile human position prediction.Second,we propose an ADI-LSTM neural network prediction algorithm for pressure values of machines supports in underground mines.Among them,our proposed PE algorithm has the lowest average cumulative prediction error,and the trajectory fit rate is improved by 24.1%,13.9%and 8.7%compared with Kalman filtering,Elman and Kalman plus Elman algorithms,respectively.Meanwhile,compared with single-input ARIMA,RNN,LSTM,and GRU,the RMSE values of our proposed ADI-LSTM are reduced by 36.6%,52%,32%,and 13.7%,respectively;and the MAPE values are reduced by 0.0003%,0.9482%,1.1844%,and 0.3620%,respectively.

The safety parameters monitoring system for the coal mine based on CAN bus communication and intelligent data acquisition

In this paper,a monitoring and controlling system for the safety in production and environmental parameters of a small and medium-sized coal mine has been developed after analyzing the current domestic coal production and security conditions. The client computer can convert the analog signal about the safety in production and environmental parameters detected from the monitoring terminal into digital signal,and then,send the signal to the coal mine safety monitoring centre. This information can be analyzed,judged,and diagnosed by the monitoring-management-controlling software for helping the manager and technical workers to control the actual underground production and security situations. The system has many advantages including high reliability,better performance of real-time monitoring,faster data communicating and good practicability,and it can effectively prevent the occurrence of safety incidents in coal mines.

Gas concentration monitoring system for small and medium-sized coal mines based on gas-sensing detection and single-chip control

This paper is aimed at the actual conditions of disaster caused by gas in small and medium-sized coal mines. A new gas concentration monitoring system for coal mines is developed on the basis of gas-sensing detection and single-chip control. The monitoring system uses the tin oxide as the main material of N-type semiconductor gas sensors, be- cause it has good sensitive characteristics for the flammable and explosive gas （ such as methane, carbon monoxide）. The QM-N5-semiconductor gas sensor is adopted to detect the output values of the resistance under the different gas con- centrations. The system, designedly, takes the AT89C51 digital chip as the core of the circuit processing hardware structure to analyze and judge the input values of the resistance, and then achieve the control and alarm for going beyond the limit of gas concentration. The gas concentration monitoring system has man）, advantages including simple in struc- ture, fast response time, stable performance and low cost. Thus, it can be widely used to monitor gas concentration and provide early wamings in small and medium-sized coal mines.

Short-term warning and integrity monitoring algorithm for coal mine shaft safety

A new short-term warning and integrity monitoring algorithm was proposed for coal mine shaft safety. The Kalman filter (KF) model was used to extract real global positioning system (GPS) kinematic deformation information. The short-term warning model was built by using the two-side cumulative sum (CUSUM) test, which further improves the warning system reliability. Availability (the minimum warning deformation, MWD), false alarm rate (the average run length, ARL), missed rate (the warning delay, WD) and the relationships among them were analyzed and the method choosing warning parameters is given. A test of a deformation simulation platform shows that the warning algorithm can be effectively used for steep deformation warning. A field experiment of the Malan mine shaft in Shanxi coal area illustrates that the proposed algorithm can detect small dynamic changes and the corresponding occurring time. At given warning thresholds (MWD is 15 mm and ARL is 1000),the detected deformations of two consecutive days’ deformation sequences with the algorithm occur at the 705th epoch (705 s) and the 517th epoch (517 s), respectively.

Mechanism and monitoring and early warning technology for rockburst in coal mines

On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst,the research progress and shortcomings in understanding the rockburst phenomenon have been comprehensively in-vestigated.This study focuses on the occurrence mechanism and monitoring and early warning technology for rockburst in coal mines.Results showed that the prevention and control of rockburst had made significant progress.However,with the increasing mining depth,several unre-solved concerns remain challenging.From the in-depth research and analysis,it can be inferred that rockburst disasters involve three main problems,i.e.,the induction factors are complicated,the mechanism is still unclear,and the accuracy of the monitoring equipment and multi-source stereo monitoring technology is insufficient.The monitoring and warning standards of rockburst need to be further clarified and im-proved.Combined with the Internet of Things,cloud computing,and big data,a study of the trend of rockburst needs to be conducted.Further-more,the mechanism of multiphase and multi-field coupling induced by rockburst on a large scale needs to be explored.A multisystem and multiparameter integrated monitoring and early warning system and remote monitoring cloud platform for rockburst should be explored and developed.High-reliability sensing technology and equipment and perfect monitoring and early warning standards are considered to be the de-velopment direction of rockburst in the future.This research will help experts and technicians adopt effective measures for controlling rock-burst disasters.

Improved complex filter applied in enhancing EFT/B immunity at a coal mine monitoring substation

A monitoring system is an important guarantee of safety in a production mine. However, not all monitoring substations pass the electrical fast transient/burst （EFT/B） immunity test and the explosion-proof test simultaneously. To enhance the immunity, the values of capacitance and inductance should be increased, which are actually limited by coal mine explosion-proof standards. Hence, for the first time, an active filter was applied in an electromagnetic interference （EMI） output filter. As a result, the interference within 30 MHz clearly weakened, but the frequency spectrum had a wide range. An EMI input filter and ferrite beads were adopted to restrain higher frequency interference. An output interference spectrogram of the substation was obtained with an analyzer. The results indicate that the improved complex filtering markedly help to control interference. With the support of improved complex filtering and other enhancing immunity means about I/O ports, the substation managed to pass both the EFT/B immunity test and the explosion-proof test synchronously. We conclude that improved complex filtering is of vital importance in enhancing the electromagnetic compatibilitv （EMC） of the coal mine monitoring system.

Fire monitoring in coal mines using wireless underground sensor network and interval type-2 fuzzy logic controller

From the view of underground coal mining safety system, it is extremely important to continuous monitoring of coal mines for the prompt detection of fires or related problems inspite of its uncertainty and imprecise characteristics. Therefore, evaluation and inferring the data perfectly to prevent fire related accidental risk in underground coal mining (UMC) system are very necessary. In the present article, we have proposed a novel type-2 fuzzy logic system (T2FLS) for the prediction of fire intensity and its risk assessment for risk reduction in an underground coal mine. Recently, for the observation of underground coal mines, wireless underground sensor network (WUSN) are being concerned frequently. To implement this technique IT2FLS, main functional components are sensor nodes which are installed in coal mines to accumulate different imprecise environmental data like, temperature, relative humidity, different gas concentrations etc. and these are sent to a base station which is connected to the ground observation system through network. In the present context, a WUSN based fire monitoring system is developed using fuzzy logic approach to enhance the consistency in decision making system to improve the risk chances of fire during coal mining. We have taken Mamdani IT2FLS as fuzzy model on coal mine monitoring data to consider real-time decision making (DM). It is predicted from the simulated results that the recommended system is highly acceptable and amenable in the case of fire hazard safety with compared to the wired and off-line monitoring system for UMC. Legitimacy of the suggested model is prepared using statistical analysis and multiple linear regression analysis.

EFT/B interference transmission model and method of anti-interference in a coal mine monitoring substation

Coal mining monitoring system has been enforcing tests for the immunity of Electromagnetic Compatibility(EMC) since 2006.However,not all monitoring substations can pass the Electrical Fast Transient/Burst(EFT/B) immunity test and the explosion-proof test simultaneously.In order to enhance EMC,the EFT/B interfere transmission model was presented at the substation power port,after the EFT/B test method was used to analyze the monitoring substation power ports.Hence,a low-pass filter was designed by using the simulation software PIPICE and an anti-jamming method was proposed by way of a parallel connection of the discharge interfere circuit and the low-pass filter.The improved complex EMI filter was made up of an interference discharge device and a filter.The dynamic equivalent circuit was proposed for the EFT/B immunity test.As a result,the monitoring substation has passed the EFT/B immunity and explosion-proof tests with the complex filter.It is concluded that the complex EMI filter has significantly enhanced the immunity of the coal mining monitoring system.

Pore-pressure and stress-coupled creep behavior in deep coal:Insights from real-time NMR analysis

Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxial creep test on deep coal at various pore pressures using a test system that combines in-situ mechanical loading with real-time nuclear magnetic resonance(NMR) detection was conducted.Full-scale quantitative characterization, online real-time detection, and visualization of MPFS during coal creep influenced by pore pressure and stress coupling were performed using NMR and NMR imaging(NMRI) techniques. The results revealed that seepage pores and microfractures(SPM) undergo the most significant changes during coal creep, with creep failure gradually expanding from dense primary pore fractures. Pore pressure presence promotes MPFS development primarily by inhibiting SPM compression and encouraging adsorption pores(AP) to evolve into SPM. Coal enters the accelerated creep stage earlier at lower stress levels, resulting in more pronounced creep deformation. The connection between the micro and macro values was established, demonstrating that increased porosity at different pore pressures leads to a negative exponential decay of the viscosity coefficient. The Newton dashpot in the ideal viscoplastic body and the Burgers model was improved using NMR experimental results, and a creep model that considers pore pressure and stress coupling using variable-order fractional operators was developed. The model’s reasonableness was confirmed using creep experimental data. The damagestate adjustment factors ω and β were identified through a parameter sensitivity analysis to characterize the effect of pore pressure and stress coupling on the creep damage characteristics(size and degree of difficulty) of coal.

Mechanics of rib deformation—Observations and monitoring in Australian coal mines

The risk of fatalities from rib failure is still prevalent in the coal mining industry. This risk has prompted further research to be conducted on rib deformation in order to understand the mechanisms of rib failure,with the long-term objective being to improve rib support design. This paper presents the results of ACARP research project C25057, which investigated the mechanics and drivers of rib failure. The results of rib deformation monitoring at three different mines in Australia provide rib deformation characteristics for overburden depths ranging from 160 to 530 m. Monitoring includes deformation during development drivage conditions and during the longwall retreat abutment stress environment. The rib deformation monitoring covered three different seams: the Goonyella Middle Seam, Ulan Seam, and Bulli Seam in the Bowen Basin, Western Coalfield, and Southern Coalfield, respectively. The observed mechanisms driving the rib deformation ranged from bedding shear failure along weak claystone bands to vertical shear fractures to kinematic failures driven by shear failure dilation. The variation in mechanisms of rib failure, together with the seemingly consistent method of rib support design, prompts the question: what exactly is the role of rib support?

A coal rib monitoring study in a room-and-pillar retreat mine

The National Institute for Occupational Safety and Health(NIOSH)conducted a comprehensive monitoring program in a room-and-pillar mine located in Southern Virginia.The deformation and the stress change in an instrumented pillar were monitored during the progress of pillar retreat mining at two sites of different geological conditions and depths of cover.The main objectives of the monitoring program were to better understand the stress transfer and load shedding on coal pillars and to quantify the rib deformation due to pillar retreat mining;and to examine the effect of rib geology and overburden depth on coal rib performance.The instrumentation at both sites included pull-out tests to measure the anchorage capacity of rib bolts,load cells mounted on rib bolts to monitor the induced loads in the bolts,borehole pressure cells(BPCs)installed at various depths in the study pillar to measure the change in vertical pressure within the pillar,and roof and rib extensometers installed to quantify the vertical displacement of the roof and the horizontal displacement of the rib that would occur during the retreat mining process.The outcome from the monitoring program provides insight into coal pillar rib support optimization at various depths and geological conditions.Also,this study contributes to the NIOSH rib support database in U.S coal mines and provides essential data for rib support design.

Risk monitoring and early-warning technology of coal mine production

This article was written according to the secudty information theory and the secudty cybernetics basic principle, for reducing the accident risk effectively and safeguarding the production safety in coal mine. First, each kind of risk characteristic has carried on the earnest analysis to the coal-mining production process. Then it proposed entire wrap technology system of the risk management and the risk monitoring early warning in the coal-mining production process, and developed the application software-coal mine risk monitoring and the early warning system which runs on the local area network. The coal-mining production risk monitoring and early warning technology system includes risk information gathering, risk identification and management, risk information transmission; saving and analysis, early warning prompt of accident risk, safety dynamic monitoring, and safety control countermeasure and so on. The article specifies implementation method and step of this technology system, and introduces application situations in cooperating mine enterprise, e.g. Xiezhuang coal mine. It may supply the risk management and the accident prevention work of each kind of mine reference.

Analysis of the Risk of Water Breakout in the Bottom Plate of High-Intensity Mining of Extra-Thick Coal Seams

In order to clarify the danger of water breakout in the bottom plate of extra-thick coal seam mining, 2202 working face of a mine in the west is taken as the research object, and it is proposed to use the on-site monitoring means combining borehole peeping and microseismic monitoring, combined with the theoretical analysis to analyze the danger of water breakout in the bottom plate. The results show that: 1) the theoretically calculated maximum damage depth of the bottom plate is 27.5 m, and its layer is located above the Austrian ash aquifer, which has the danger of water breakout;2) the drill hole peeping at the bottom plate of the working face shows that the depth of the bottom plate fissure development reaches 26 m, and the integrity of the water barrier layer has been damaged, so there is the risk of water breakout;3) for the microseismic monitoring of the anomalous area, the bottom plate of the return air downstream channel occurs in the field with a one-week lag, which shows that microseismic monitoring events may reflect the water breakout of the underground. This shows that the microseismic monitoring events can reflect the changes of the underground flow field, which can provide a reference basis for the early warning of water breakout. The research results can provide reference for the prediction of sudden water hazard.

Monitoring mine collapse by D-InSAR

For harmful ground collapse and its special deformation characteristics,which causes SAR images to lose coherence,InSAR technology cannot be applied in monitoring surface collapse in mining areas.We took the Shenmu mining area in northern Shaanxi province as an example to study subsidence in mining areas and proposed an interpolated multi-view processing method.The results show that this method can improve the detectable deformation gradient to a certain extent and can become a good reference value for monitoring large scale gradient deformation.We also analyzed the rules for temporal decorrelation in mining.

Determining areas in an inclined coal seam floor prone to water-inrush by micro-seismic monitoring

The failure depth of the coal seam floor is one important consideration that must be kept in mind when mining is carried out above a confined aquifer.Determining the floor failure depth is the essential precondition for predicting the water-resisting ability of the floor.We have used a high-precision microseismic monitoring technique to overcome the limited amount of data available from field measurements. The failure depth of a coal seam floor,especially an inclined coal seam floor,may be more accurately estimated by monitoring the continuous,dynamic failure of the floor.The monitoring results indicate the failure depth of the coal seam floor near the workface conveyance roadway（the lower crossheading） is deeper and that the failure range is wider here compared to the coal seam floor near the return airway（the upper crossheading）.The results of micro-seismic monitoring show that the dangerous area for water-inrush from the coal seam floor may be identified.This provides an important field measurement that helps ensure safe and highly efficient mining of the inclined coal seam above the confined aquifer at the Taoyuan Coal Mine.

Activation characteristics analysis on concealed fault in the excavating coal roadway based on microseismic monitoring technique

In order to effectively monitor the concealed fault activation process in excavation activities, based on the actual condition of a working face containing faults with high outburst danger in Xin Zhuangzi mine in Huainan, China, we carried out all-side tracking and monitoring on the fault activation process and development trend in excavation activities by establishing a microseismic monitoring system. The results show that excavation activities have a rather great influence on the fault activation. With the working face approaching the fault, the fault activation builds up and the outburst danger increases; when the excavation activities finishes, the fault activation tends to be stable. The number of microseismic events are corresponding to the intensity of fault activation, and the distribution rules of microseismic events can effectively determine the fault occurrence in the mine. Microseismic monitoring technique is accurate in terms of detecting geologic tectonic activities, such as fault activations lying ahead during excavation activities. By utilizing this technique, we can determine outburst danger in excavation activities in time and accordingly take effective countermeasures to prevent and reduce the occurrence of outburst accidents.

A multipath routing protocol for wireless sensor network for mine security monitoring

Underground mining is a hazardous industrial activity. In order to provide a safe working environment for miners, a Wireless Sensor Network (WSN) technology has been used for security monitoring. It can provide a wide range of surveillance with a relatively low cost. In this study, an Energy-Based Multipath Routing (EBMR) protocol is proposed, which considers residual energy capacity and link quality in choosing hops and routing paths. Hops and paths with a high residual energy capacity and link quality will have the best chance to be selected to transmit data packages. Since the EBMR stores several routes in the routing table, when the current path fails, another path will be chosen to fulfill the task immediately. In this way, EBMR improves reliability and decrease time latency. Compared to AOMDV and REAR, EBMR decreases time latency by 51% and 12%.

A model of unsafe behavior in coal mines based on game theory

Behavior choice, coal mine monitoring, and control intensity are combined in a general mathematical model established from the perspective of a behavioral game. A case study is provided with effective conditions of monitoring provided. This paper defines the expected value difference of control return and behavior cost difference and discusses the measurement and optimization of variable indexes, including the monitoring intensity and costs of control. The results imply that the control of unsafe behavior can be more effective when monitoring and control of coal mines are both improved. Monitoring will be useful when the rewards for displaying safe behavior, and the monitoring of unsafe behavior, are improved to a high level.

Using self-determination theory to identify organizational interventions to support coal mineworkers’ dust-reducing practices

Advancing the application of safety and health(S&H)technologies is likely to remain a value in the mining industry.However,any information that technologies generate must be translated from the organization to the workforce in a targeted way to result in sustainable change.Using a case study approach with continuous personal dust monitors(CPDMs),this paper argues for an organizational focus on technology integration.Although CPDMs provide mineworkers with near real-time feedback about their respirable coal dust exposure,they do not ensure that workers or the organization will continuously use the information to learn about and reduce exposure sources.This study used self-determination theory(SDT)to help three mines manage and communicate about information learned from the CPDM technology.Specifically,35 mineworkers participated in two mixed-method data collection efforts to discuss why they do or do not use CPDMs to engage in dust-reducing practices.Subsequently,the data was analyzed to better understand how organizations can improve the integration of technology through their management systems.Results indicate that using the CPDM to reduce sources of dust exposure is consistent with mineworkers’self-values to protect their health and not necessarily because of compliance to a manager or mine.