Towards Long-Term Monitoring of the Structural Health of Deep Rock Tunnels with Remote Sensing Techniques

Due to the substantial need to continuously ensure safe excavations and sustainable operation of deep engineering structures, structural health monitoring based on remote sensing techniques has become a prominent research topic in this field. Indeed, throughout their lifetime, deep tunnels are usually exposed to many complex situations which inevitably affect their structural health. Therefore, appropriate and effective monitoring systems are required to provide real-time information that can be used as a true basis for efficient and timely decision-making. Since sensors are at the heart of any monitoring system, their selection and conception for deep rock tunnels necessitates special attention. This work identifies and describes relevant structural health problems of deep rock tunnels and the applicability of sensors employed in monitoring systems, based on in-depth searches performed on pertinent research. The outcomes and challenges of monitoring are discussed as well. Results show that over time, deep rock tunnels suffer several typical structural diseases namely degradation of the excavation damaged areas, corrosion of rock bolts and cable bolts, cracks, fractures and strains in secondary lining, groundwater leaks in secondary lining, convergence deformation and damage provoked by the triggering of fires. Various types of remote sensors are deployed to monitor such diseases. For deep rock tunnels, it is suggested to adopt comprehensive monitoring systems with adaptive and robust sensors for their reliable and long-lasting performance

Towards Long-Term Monitoring of the Structural Health of Deep Rock Tunnels with Remote Sensing Techniques

Due to the substantial need to continuously ensure safe excavations and sustainable operation of deep engineering structures, structural health monitoring based on remote sensing techniques has become a prominent research topic in this field. Indeed, throughout their lifetime, deep tunnels are usually exposed to many complex situations which inevitably affect their structural health. Therefore, appropriate and effective monitoring systems are required to provide real-time information that can be used as a true basis for efficient and timely decision-making. Since sensors are at the heart of any monitoring system, their selection and conception for deep rock tunnels necessitates special attention. This work identifies and describes relevant structural health problems of deep rock tunnels and the applicability of sensors employed in monitoring systems, based on in-depth searches performed on pertinent research. The outcomes and challenges of monitoring are discussed as well. Results show that over time, deep rock tunnels suffer several typical structural diseases namely degradation of the excavation damaged areas, corrosion of rock bolts and cable bolts, cracks, fractures and strains in secondary lining, groundwater leaks in secondary lining, convergence deformation and damage provoked by the triggering of fires. Various types of remote sensors are deployed to monitor such diseases. For deep rock tunnels, it is suggested to adopt comprehensive monitoring systems with adaptive and robust sensors for their reliable and long-lasting performance

Monitoring Technology of Surrounding Rock Deformation Based on IWFBG Sensing Principle and Its Application

To address the challenge of achieving precise real-time monitoring of significant deformation in deep roadway surrounding rock, a quasi-distributed strain-sensing cable (SSC), which has a spatial resolution of 1 m, was developed based on the principle of Identical Weak Fiber Bragg Gratings. The performance of SSC has been evaluated through a series of calibration tests, revealing a range of 0%–3%, an accuracy level of 0.5%, a strain sensitivity measuring at 1.23 pm/με, and a temperature sensitivity recorded as 10.78 pm/℃. Furthermore, a real-time deformation monitoring system has been established to monitor rock deformation, consisting of SSC, supporting installation equipment, demodulation equipment, and monitoring software. Moreover, the proposed methodology was applied in the deep roadway of Guqiao coal mine. The results showed that the maximum surface displacement of the roadway is 103.47 mm, while the lateral contrast error stands at 5%. The maximum strain value of the surrounding rock measures 27,095 με. The depth of rock rupture zone is about 3 m, while the boundary of rock damage zone extends up to 6 m. This information serves as the foundation for determining the parameters of the roadway reinforcement support design

Monitoring of strain and temperature in an open pit using brillouin distributed optical fiber sensors

Marble quarries are quite dangerous environments in which rock falls may occur. As many workers operate in these sites, it is necessary to deal with the matter of safety at work, checking and monitoring the stability conditions of the rock mass. In this paper, some results of an innovative analysis method are shown. It is based on the combination of Distributed Optical Fiber Sensors (DOFS), digital photogrammetry through Unmanned Aerial Vehicle (UAV), topographic, and geotechnical monitoring systems. Although DOFS are currently widely used for studying infrastructures, buildings and landslides, their use in rock marble quarries represents an element of peculiarity. The complex morphologies and the intense temperature range that characterize this environment make this application original. The selected test site is the Lorano open pit which is located in the Apuan Alps (Italy); here, a monitoring system consisting of extensometers, crackmeters, clinometers and a Robotic Total Station has been operating since 2012. From DOFS measurements, strain and temperature values were obtained and validated with displacement data from topographic and geotechnical instruments. These results may provide useful fundamental indications about the rock mass stability for the safety at work and the long-term planning of mining activities

Comparative analysis of coal fatalities in Australia, South Africa, India, China and USA, 2006-2010

Coal mining (especially underground) is considered one of the most hazardous industries, and as a result considerable focus is applied to eliminating or mitigating hazards through careful mine planning, equipment selection and certification, and development of management systems and procedures. Regulatory agencies have developed in-house methods for reporting, classification and tracking of fatalities and other incidents according to the type of event, often including consideration of different hazard types. Unfortunately, direct comparison of mining safety statistics between countries is confounded by considerable differences in the way that individual countries classify specific fatalities or incidents. This paper presents a comparative analysis of coal mining fatality data in Australia, South Africa, India, China and the United States from 2006 to 2010. Individual classification definitions are compared between the five countries, and methods presented to normalise each country’s hazard definitions and reporting regimes around the RISKGATE framework of seventeen different priority unwanted events (or topics). Fatality data from individual countries is then re-classified according to the different RISKGATE topics, thereby enabling a comparative analysis between all five countries. This paper demonstrates the utility and value of a standard classification approach, and submits the RISKGATE framework as a model for classification that could be applied globally in coal mining. RISKGATE is the largest health and safety project ever funded by the Australian coal industry (http://www.riskgate.org) to build an industry body of knowledge to assist in managing common industry hazards. A comprehensive knowledge base has been captured for risk management of tyres, collisions, fires, isolation, strata underground, ground control open cut, explosions, explosives, manual tasks and slips/trips/falls. This has been extended to outburst, coal burst and bumps, interface displays and controls, tailings dams and inrush

Commissioning adiabatic oven testing - an inter-laboratory comparison

Adiabatic oven testing for spontaneous combustion assessment has been a primary method used by the Australian and New Zealand coal industries for input to the development of Principal Hazard Management Plans for mining operations. Consistency of results is important to ensure that the ratings obtained are accurate and reliable for maintaining the integrity of the database used to compare between mines and for obtaining site specific relationships. This paper presents the results from commissioning tests of four new adiabatic ovens at two different laboratories, which show the high level of reproducibility and repeatability needed for confidence in planning of future mining operations. The results cover a range of coal self-heating rates to show the validity of the testing and the reliability of the adiabatic ovens

Is carbon monoxide sensing an effective early fire detection option for underground coal mines?

The ability of carbon monoxide (CO) sensing to detect early stage smouldering of fixed plant fires in underground coal mines was recently assessed as part of an ongoing fire detection research project. Experiments were carried out to record the level of CO concurrent at the time of alarm activation of a Video Based Fire Detection (VBFD) system. The tests were carried out under simulated mine conditions within the SIMTARS facility at Redbank, Queensland. The experimental setup initially located the CO sensors in the positions at where they would typically be installed underground. On testing the experimental setup, it was found that the amount of CO produced from simulated overheating conveyor belt bearing housings did not display a reading on the CO sensors. The VBFD system however detected smoke and alarmed on each of the trial tests. To enable the experiments to proceed and a comparison to be made, the CO sensors were moved considerably closer to the weak pyrolysis fire source. The question of CO sensor capability in typical operational mine positions was highlighted as a result of this experiment. Computational Fluid Dynamics (CFD) modelling was used to estimate the fire size required to activate CO sensors under typical mining conditions. This modelling reinforced the limitations in using CO detectors on fixed plant. As such, the study presented here indicates that CO sensing may not be the most effective early fire detection option available, and that further research and development work with VBFD should be undertaken

RISKGATE and Australian coal operations

The major Australian Coal Association Research Program (ACARP) project, RISKGATE has now completed three years of knowledge capture and system development. The body of knowledge for risk management of tyres, collisions, fires, isolation, strata underground, ground control open cut, explosions, explosives underground, explosives open cut, manual tasks and slips/trips/falls was launched in December 2012. Recently, the project added knowledge about outbursts, coal bumps and bursts, human-machine interface, tailings dams, occupational hygiene and inrush to the original 11 topics. In 2014, the project plans (pending ACARP funding approval) to focus on issues around Fitness for Work. RISKGATE provides an environment for knowledge capture and knowledge exchange to drive innovation and cross industry sharing of current practice in the identification, assessment and management of risk. By capturing operational knowledge from industry experts, RISKGATE provides a cumulative corporate memory at a time of high personnel turnover in the coal industry. RISKGATE is the largest single ACARP Occupational Health and Safety (OHS) initiative to date. This paper presents an overview of the first seventeen topics, topic structures, and contrasts and inter-relationships between topics. The second part of the paper discusses some early steps that companies are taking to integrate RISKGATE into their operations; and conclude with some thoughts on where RISKGATE can go in the future

Optimisation of waste-dump lift heights for pre-strip operations

The optimisation of waste dump design parameters is a vital aspect that has the potential to significantly influence operational costs within mining operations. This research study investigates the effects waste dump lift height has on a truck-shovel coal mining operation. The analysis focusses upon simulating various dump lift heights in a truck-shovel operation in order to determine the optimal overall dump lift height. The dump lift height is the height to which each dump level or lift is constructed. The optimal height will therefore be determined by plotting the simulated cost results for each height and undergoing a comparative study. Additional factors incorporated within the simulation results include the cost of haulage, and ancillary equipment works (dozers, graders and water cartsto maintain the dump and construct haul roads to each new dump lift. Generating results from the research analysis to closely resemble real world applications, current mine data is incorporated within each simulation, including dig, dump and equipment data obtained from King 2 North pit of the Meandu mine located in Queensland

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors