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.

Early faults prediction of running state of electromechanical systems and reconfigurable integration of series safety monitoring systems

Fault prediction technology of running state of electromechanical systems is one of the key technologies that ensure safe and reliable operation of electromechanical equipment in health state. For multiple types of modern, high-end and key electromechanical equipment, this paper will describe the early faults prediction method for multi-type electromechanical systems, which is favorable for predicting early faults of complex electromechanical systems in non-stationary, nonlinear, variable working conditions and long-time running state; the paper shall introduce the reconfigurable integration technology of series safety monitoring systems based on which the integrated development platform of series safety monitoring systems is built. This platform can adapt to integrated R&D of series safety monitoring systems characterized by high technology, multiple species and low volume. With the help of this platform, series safety monitoring systems were developed, and the Remote Network Security Monitoring Center for Facility Groups was built. Experimental research and engineering applications show that: this new fault prediction method has realized the development trend features extraction of typical electromechanical systems, multi-information fusion, intelligent information decision-making and so on, improving the processing accuracy, relevance and applicability of information; new reconfigurable integration technologies have improved the integration level and R&D efficiency of series safety monitoring systems as well as expanded the scope of application; the series safety monitoring systems developed based on reconfigurable integration platform has already played an important role in many aspects including ensuring safety operation of equipment, stabilizing product quality, optimizing running state, saving energy consumption, reducing environmental pollution, improving working conditions, carrying out scientific maintenance, advancing equipment utilization, saving maintenance charge and enhancing the level of information management.

A comparative study of dust control practices in Chinese and Australian longwall coal mines

Mine dust is one of the main hazards in underground longwall mines worldwide.In order to solve the mine dust problem,a significant number of studies have been carried out regarding longwall mine dust control,both in China and Australia.This paper presents a comparative study of dust control practices in Chinese and Australian longwall mines,with particular references to statutory limits,dust monitoring methods and dust management practices,followed by a brief discussion on the research status of longwall mine dust control in both countries.The study shows that water infusion,face ventilation controls,water sprays,and deep and wet cutting in longwall shearer operations are commonly practiced in almost all underground longwall mines and that both Chinese and Australian longwall mine dust control practices have their own advantages and disadvantages.It is concluded that there is a need for further development and innovative design of more effective dust mitigation products or systems despite the development of various dust control technologies.Based on the examinations and discussions,the authors have made some recommendations for further research and development in dust control in longwall mines.It is hoped that this comparative study will provide beneficial guidance for scholars and engineers who are engaging in longwall mine dust control research and practice.

Key techniques for evaluation of safety monitoring sensors in water conservancy and hydropower engineering

For the evaluation of construction quality and the verification of the design of water conservancy and hydropower engineering projects, and especially for the control of dam safety operation behavior, safety monitoring sensors are employed in a majority of engineering projects. These sensors are used to monitor the project during the dam construction and operation periods, and play an important role in reservoir safety operation and producing benefits. With the changing of operating environments and run-time of projects, there are some factors affecting the operation and management of projects, such as a certain amount of damaged sensors and instability of the measured data. Therefore, it is urgent to evaluate existing safety monitoring sensors in water conservancy and hydropower engineering projects. However, there are neither standards nor evaluation guidelines at present. Based on engineering practice, this study examined some key techniques for the evaluation of safety monitoring sensors, including the evaluation process of the safety monitoring system, on-site detection methods of two typical pieces of equipment, the differential resistor sensor and vibrating wire sensor, the on-site detection methods of communication cable faults, and a validity test of the sensor measured data. These key techniques were applied in the Xiaolangdi Water Control Project and Xiaoxi Hydropower Project. The results show that the measured data of a majority of sensors are reliable and reasonable, and can reasonably reflect the structural change behavior in the project operating process, indicating that the availabilities of the safety monitoring sensors of the two projects are high

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.

On the mechanism of coal mine safety monitor based on game analysis

Analyzed the monitor results under current systems concerning game and then pointed out that a way-out to improve chinese coal mine production safety control is to implement system innovation and punish the monitor＇s lazy behaviors strictly.

Analysis of factors of top coal caving in fully mechanized sublevel caving face in soft coal and control

According to the analysis of the mechanism of top coal caving, the caving condition was pointed out, and many factors of caving were also determined. Then the relationship between factors and caving was studied. Based on the above research, one effective method by using field monitoring was brought forward to determine the controlling factor. Then some related key technologies were provided, such as keeping the integrality of the top-coal, raising the horizontal resistance of supports and decreasing the real end-face distance etc.. At last one application of this method was presented, and it was proved to be an effective method.

CONTROL OF GAS EMISSION AT COAL FACE IN CHINA

All the underground coal mines in China are gassy mines. The gas emission at coal face increasingly grows with the increase of working depth and coal output, for example, the gas emission at a full mechanized coal face of mine No. 2 at Yongquan with a daily output of 2. 000t/d is up to 66-72m2/min. Special gas emission phenomena such as gas blowout, gas and coal outburst etc. have occurred at some faces, which threatens the safe production of face. obstructs the growth of productivity and limits the full play of mechanized equipment.In this paper, gas at face is divided, according to its origin, into three constituents, namely , coming from the coal wall, mined coal and goaf;and a formula for calculation is given. Also , the characteristics of the variation of gas emission at coal face, and the influence of mining sequence of a group of seams and supplied air quantity on the gas emission are discussed. Furthermore . based on the regularity of gas emission at coal face from the above three sources, and on the experiences of years, three principles on controlling gas emission at coal face are presented, that are managing the gas on classification basis, harnessing each source separately and comprehensive prevention and control. Finally, technical measures for prevention and treatment of the accumulation of gas in the upper corner of face, at the working place of coal-winning machine and in the bottom trough of conveyor are introduced.

Effect of the computer fuzzy control on coal seam injection

To enhance the technology and efficiency of strata injection is a problem to be solved urgently. Because of effected by the rough and poor production conditions of mining and the changeable bearing condition of strata, the technological process of injection can not be controlled automatically.The fuzzy controlling technology of the coal strata injection is applied. This is the good way to ensure the effectiveness and efficiency of coal strata injection and to solve the current problems of production and safety in mining industry.

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.

Migration law of heavy metal cadmium in soil-root interface systems

The distribution characteristics of heavy metals in soil-root systems have great significance for the research into soil pollution risk assessment and the phytoremediation effect. This paper takes ligustrum lucidum as an example, based on the characteristics of adsorption of heavy metals in soil by woody plants, lays out sampling points, and using software Surer for the Kiging interpolation analysis, and the horizontal migration law of heavy metal cadmium in the soil-root interface system is simulated. Through multi-model statistical regression trend analysis, the horizontal migration mechanism of cadmium in different sections is discussed. The results show that： （1） under horizontal migration law： the migration ability of Cd is weaker near the Ligustrum lucidum root （0 30 cm）; with the root extension, the migration ability of Cd gradually is strengthened, and the main range of the migration ability is 60-90 cm. In addition, its migration law follows the cubic curve mode. （2） under longitudinal migration law： based on the Kriging method, migration models Z（hi） of heavy metal Cd in any depth of hi are constructed and fit the correlation coefficient R^2〉0.95.

Profibus-DP总线单主站系统报文传输延时分析

采用确定与随机Petri网建立了Profibus-DP总线单主站系统报文传输延时的模型,并在TimeNet软件环境下对其进行了仿真分析,得出了报文传输延时与目标令牌循环时间的关系;并以STEP7软件为例,说明了在实际工程中如何根据Profibus-DP总线参数合理设定目标令牌循环时间、从而使监控系统获得最好的实时性的方法。仿真结果验证了该模型的正确性。

燃煤发电机组灵活调峰下机炉安全状态监测与调控研究综述

“双碳”背景下新能源大量接入电网,燃煤发电机组承担调峰任务,长期处于瞬态运行过程,其灵活运行水平需进一步提升,但深度调峰与快速变负荷使机组运行可靠性下降,机组灵活调峰能力面临设备安全性制约。该文对燃煤发电机组在灵活调峰下安全稳定运行的研究现状进行评述。首先,综述调峰工况下锅炉换热面、汽轮机转子等部件存在的安全技术问题,明确灵活运行对机组设备安全性的影响。其次,对比分析监测温度、应力等关键运行状态参数的不同方法优缺点与适用性;针对存在的安全技术问题介绍现有的机组运行参数优化与设备结构优化方法。未来将可靠性评估与诊断、停机保温预热及智能先进控制等技术应用于燃煤发电机组的调峰运行将对其安全性提升具有重要意义。最后,对目前燃煤发电机组灵活安全运行的研究现状及面临问题进行总结。

基于SEM的煤矿工人易发不安全行为控制研究

为了准确识别煤矿工人易发不安全行为,预防由此导致的煤矿事故,文章首先构建了由作业过程、工艺设备、环境限制和作业决策4个一级指标和操作错误等18个二级指标构成的煤矿工人不安全行为评价指标体系。其次,将结构方程模型(SEM)运用到了煤矿工人易发不安全行为控制研究中。研究结果表明:作业过程等4个一级指标(潜在变量)均对煤矿工人不安全行为的发生具有显著影响;18个二级指标(观测变量)中,有无视警示进入危险区域等14种煤矿工人易发不安全行为,且根据路径系数得到了其易发程度。最后,提出了控制煤矿工人易发不安全行为的对策。文章为煤矿工人不安全行为研究提供了一种方法。

煤岩瓦斯复合动力灾害监测预警与防控技术研究进展

煤岩瓦斯复合动力灾害是深部煤炭开采的重大安全隐患,探明其致灾机理、发展监测预警及防控技术是防治关键。提出了煤岩瓦斯复合动力灾害防治“四面体”理论,即分别从灾害分类、灾害机理、灾害预警、灾害防控4个层面概述煤岩瓦斯复合动力灾害研究进展。总结了以能量释放主体、初始瓦斯压力、载荷条件为主的复合动力灾害类型划分依据;梳理了理论分析尺度和实验室尺度下的复合动力灾害机理研究进展,发现应力路径、微裂纹动态演化和煤岩赋存地质因素临界指标是致灾机理研究的关键;概述了以前期灾害前兆信息判识、中期灾害前兆信息采集、后期灾害一体化监测预警为主线的复合动力灾害监测预警技术研究进展;揭示了复合动力灾害消能减灾一体化防控技术和多尺度分源防控关键技术科学内涵。在此基础上针对两淮矿区灾害特点,提出了深部强动载条件下复合动力灾害智能判识与预警方法和分区协同防控方法。基于当前研究进展,提出了煤岩瓦斯复合动力灾害研究亟待解决的问题,助力实现深部煤炭安全、精准、高效开采。

面向煤矿安全监测边缘计算的YOLOv5s剪枝方法

目前,边缘计算与机器视觉相结合具有较好的煤矿安全监测应用前景,但边缘端存储空间和计算资源有限,高精度的复杂视觉模型难以部署。针对上述问题,提出了一种面向煤矿安全监测边缘端的基于间接和直接重要性评价空间融合(IDESF)的YOLOv5s剪枝方法,实现对YOLOv5s网络的轻量化。首先对YOLOv5s网络中各模块的卷积层进行结构分析,确定自由剪枝层和条件剪枝层,为后续分配剪枝率及计算卷积核剪枝数奠定基础。其次,根据基于卷积核权重幅值和层相对计算复杂度的卷积核权重重要性得分为可剪枝层分配剪枝率,有效降低剪枝后网络的计算复杂度。然后,基于卷积核直接重要性评价准则,将卷积层的间接输出重要性以缩放因子的形式引入直接重要性空间中,更新卷积核位置分布,构建包含卷积核输出信息和幅值信息的融合重要性评价空间,提高卷积核重要性评价的全面性。最后,借鉴topk投票的思想对中值滤波筛选冗余卷积核的流程进行优化,并用有向图的邻接矩阵中节点的入度来量化卷积核的冗余程度,提高了冗余卷积核筛选过程的可解释性和通用性。实验结果表明:①从平衡模型精度和轻量化程度的角度出发,剪枝率为50%的YOLOV5s_IDESF是最优的轻量级YOLOv5s。在VOC数据集上,YOLOv5s_IDESF的mAP@.5和mAP@0.5∶0.95均达到最高,分别为0.72和0.44,参数量降至最低2.65×10^(6),计算量降低至1.16×10^(9),综合复杂度也降至最低,图像处理帧率达到31.15帧/s。②在煤矿数据集上,YOLOv5s_IDESF的mAP@.5和mAP@0.5∶0.95均达到最高,分别为0.94和0.52,参数量降至最低3.12×10^(6),计算量降低至1.24×10^(9),综合复杂度也降至最低,图像处理帧率达到31.55帧/s。

定向长钻孔瓦斯抽采负压变化规律及监测控制技术研究进展

【意义】近水平定向长钻孔是煤矿瓦斯灾害防治的重要技术途径和有效手段,负压是影响定向长钻孔瓦斯抽采效果的重要因素。【进展】从孔内负压衰减机制与分布规律、瓦斯抽采参数监测技术、瓦斯抽采智能调控系统等3个方面系统总结了近水平定向长钻孔瓦斯抽采技术研究进展,其中在孔内负压衰减机制与分布规律方面,总结了负压对瓦斯抽采影响机制、负压衰减机制、负压分布规律等基础理论研究成果;在瓦斯抽采参数监测技术方面,基于不同原理,阐述了超声波式、激光式、孔板式、循环自激式等不同类型的孔口瓦斯监测仪器现状,以及以束管法为主的孔内瓦斯监测手段;在瓦斯抽采智能调控系统方面,介绍了瓦斯抽采智能调控理念与技术装备研究上取得的成果,以负压、流量、浓度等抽采参数为分析调控对象,基于智能算法与PLC控制技术,初步实现井下管网智能调控,提高了瓦斯抽采效率。【展望】指出当前研究存在定向长钻孔内负压变化规律不清、正负压耦合作用机制不明,缺乏孔内长距离的瓦斯抽采参数监测手段和瓦斯多参数监测方法,瓦斯抽采调控系统智能化程度低等不足。同时提出瓦斯抽采定向长钻孔研究的未来发展趋势,包括基于定向长钻孔特殊结构分析的负压抽采与正压扩散耦合机制、基于光纤传感的孔内瓦斯多参数监测系统、基于机器学习的瓦斯抽采参数精细调控方法等研究方向,为近水平定向长钻孔瓦斯治理工程设计、施工、抽采与效果评价提供支撑。

川西高原某隧道幔源气逸出机理及防控研究

川西高原地区特殊的构造和岩性为幔源气提供了赋存环境。本文针对幔源气成因、出气段落超前地质预报探测原则、检测与监测进行了阐述,总结了幔源气出气段工作思路:(1)辨识幔源气类型及其不同浓度下的危害;(2)树立“物钻结合,长短结合”的超前地质预报理念;(3)加强气体的检测与监测,加强幔源气的通风管理。通过以上探测及防控手段,实现了对岩浆岩幔源气的可防可治,保证了施工安全。研究成果可为类似地质背景环境的隧道施工提供针对性探测及防控思路。

基于6LoWPAN的智慧校园公共安全异常监控系统设计

在智慧校园网络中,监控系统无法准确捕获异常人员信息,是造成公共安全事件的主要原因;为提高智慧校园公共安全性,设计基于6LoWPAN的智慧校园公共安全异常监控系统;建立6LoWPAN网络,并在其中规范协议栈堆叠形式,完成基于6LoWPAN的智慧校园监控协议栈开发;利用6LoWPAN协议栈,划分功能性模块,以此为基础,建立人员信息采集模块、环境监测模块、门禁控制模块之间的连接关系,实现异常监控系统的应用部件设计;采用监控系统上位机节点,设置各级部件结构的模块运行条件,并联合相关应用部件,实现基于6LoWPAN的智慧校园公共安全异常监控系统设计;实验结果表明,在同一帧图像中,设计系统可以全部提取异常人员信息,且不会出现错误提取的情况,监控准确率高达100%,能够有效提高智慧校园公共安全性和异常监控准确性。