Application of small self-propelled drill rigs

The benefits of sensor based computer control in the international mining industry are many. Consequently, the industry expends considerable effort researching and developing automated systems. These efforts span the total industry including exploration, extraction, processing, and refining. All of the major segments of the mining industry: underground and surface, industrial minerals, metal, non-metal, and coal have participated in these developments. The result is a large body of information that is impossible to cover completely in a conference paper. To provide interesting information to the conference audience, this paper focuses on efforts to automate mobile production equipment. Most of the efforts apply to international underground metal and coal mines. Mobile mining and construction equipment presently utilize mechanization and remote control. For example, remote controlled equipment, where an operator is stationed some distance from the machine, but within line-of-sight, is found on many continuous mining machines in underground coal mines and LHD'S in underground metal mines. Teleoperated equipment where operators can be stationed further away, beyond-line-of-sight, is currently being tried at mines in the USA, Canada, Australia, and Sweden. Research projects currently focus on intelligent analysis of data from sensors to produce control algorithms which will be termed "mining robotics" to distinguish it from simpler closed ioop control termed "automation." The reason current research focuses on intelligent analysis of sensor data to produce control algorithms is that mining takes place in the geological environment where conditions are highly variable and unpredictable. As a result, mining systems must have substantial cognitive abilities to recognize and deal with these unpredictable variations. Robotics has been described as the intelligent connection between perception and action. It may provide the greatest benefits in productivity and safety since it incorporate artificial-intelligence-based algorithms that show promise for adapting to the dynamic mining environment. Many mines have purchased the latest available technology from equipment manufacturers. These large, expensive, advanced machines have high production capabilities and are very reliable. For these machines to provide the highest cost effectiveness, they should be fully utilized; however this is not always the case. For example, underground coal continuous miners are only utilized 17% of the shift (Suboleski and King, 1990, and King and Suboleski, 1991). These problems occur in surface and underground mines, but underground mining has the most opportunity for improvement. In addition, maintaining an artificial environment 348 / SPIE Vol. 1613 Mobile Robots VI (1991) 0-8 194-0750-X/92/$4.00 in an underground mine that is conducive to optimal work performance is expensive. By its nature, underground mining can be hot or humid, in addition, the equipment produces dust, noise, fumes, and other hazards. Explosive or toxic gases and the constant danger of rock falls add to the increasing list of health and safety concerns that have initiated volumes of federal and state regulations for maintaining safe work places for humans in underground mines. These regulations cause tremendous capital and operating expenditures that prevent many mineral deposits from being mined profitably. For example, in both underground coal and metal mines, miners excavate many more entries or drifts than necessary to produce and remove the ore or coal in order to provide a safe environment for humans. These difficulties will increase as mines deplete nearsurface reserves that have the best working conditions. As a result, some areas are not mined because of the expense of providing an adequate environment for human operators. A good example is narrow ore veins in metal mines that would normally require cut and fill stoping methods to provide adequate ground support. With teleoperated or robotic equipment, less expensive open stoping practices can be used. Another example is automated longwall systems that can be operated more freely in a bi-directional cutting mode because they eliminate respirable dust exposure on the face.

Tool condition monitoring (TCM) measures the condition of a cutting tool used in machining, and provides the operator with information relating to the state of the process. A TCM system gathers data about a process using a number of different sensor types, including force, motor power, strain, vibration and acoustic emission. With pressure on the manufacturing industry to reduce material waste and increase productivity, the dependence on TCM systems is ever increasing. Unreliable TCM can allow a process to continue with a broken or worn tool which may damage the workpiece. This is problematic as workpieces can have a high embedded value, or the machine can be making scrap for significant periods which can be costly. On the other hand, time is wasted changing a tool too often or resetting after false alarms which is also costly. Therefore increasing the reliability of TCM systems is of critical importance to a manufacturing system. A further challenge to TCM is presented in micro machining processes, in particular with small diameter drilling. In small diameter drilling it can be very difficult to detect variations in the measurable phenomena due to the low levels recorded by sensors. One sensor that has been shown to detect valuable information during micro machining and micro drilling is an Acoustic Emission (AE) sensor. This paper outlines the an approach to processing an AE signal from micro drilling in order to provide information on the process parameters. The challenges and limitations of the analysis are discussed. (8 pages)

How to demonstrate the deformation and failure mode of the slope under combine surface and underground mining and evaluate its stability scientifically is one of the problems that need urgent solutions in mining engineering. First, the deformation and failure mode of the slope under simple surface mining, the deformation and failure mechanism of the overlying strata affected by underground mining and deformation mechanism of the slope under combined surface and underground mining were analyzed, then the failure mode and the stability calculation method of the slope under combined surface and underground mining was studied. The results show that the failure modes of the slope under combined surface and underground mining involve three patterns: slipping failure, subsiding failure and slipping-subsiding combined failure, that the failure modes and the stability of the slope under combined surface and underground mining be significantly affected by the underground mining positions and the influence be mainly controlled by the length of the latent slide plane of the slope and the weakening degree of the rock masses in the subsidence range. Finally, a limit equilibrium method to calculate the slope stability under combined surface and underground mining was put forward.

Mining-induced seismicity in the area of development works and proper mining operations is one of the major determinants of the rockburst hazard level in underground mines. Rockburst hazard assessment in Polish collieries is performed by a variety of mining and geophysical methods, including seismic and seismoacoustic techniques, borehole surveys, small diameter drilling, rock strata profiling and analyses of geomechanical properties of rocks, geological structure and geological mining conditions. In the case of zones particularly exposed to potential hazards, it is recommended that analytical or numerical forecasts of the state of stress in the vicinity of workings should be used already at the stage of planning of mining operations. This study summarises the comparative analysis of seismic test data and analytical forecasts of the state of stress in five selected headings in one of the burst-prone collieries within the Upper Silesia Coal Basin in Poland (USCB). As regards the seismic data, duly defined quantitative indicators and energy criteria of the registered seismic activity are recalled in the assessment of rockburst hazard level during the roadheading operations. Analytical simulations utilise a developed geomechanical model and stress–strain relationships stemming from the principles of elastic media mechanics. From the standpoint of mining engineering practice, interpretation of results obtained by the two methods reveals how effective analytical models will be in prognosticating or verification of rockburst hazard conditions.

Recently, as workpieces have become increasingly fine, there has been growing demand for small-diameter hole drilling of 1 mm or less. Compared to general drills, small-diameter drills have lower tool rigidity and poor chip evacuation, making them prone to breakage. In actual machining operations, the workpiece may be wasted owing to unexpected tool breakage. Therefore, there is a growing expectation for "the development of prediction technology to avoid breakage" of small-diameter drills. In this study, we analyzed the mechanism of breakage for small diameter drill, which will help future research on the prediction and detection of tool breakage.

Underground coal seam mining significantly reduces the stability of slopes, especially soil slopes, and an accurate evaluation of the stability of soil slopes under underground mining conditions is crucial for mining safety. In this study, the impact of coal seam mining is considered as the additional horizontal and vertical stresses acting on the slope, and an equation for calculating the safety factor of soil slopes under underground mining conditions is derived based on the rigorous Janbu method. Then, the Improved Radial Movement Optimization (IRMO) algorithm is introduced and combined with Lévy flight optimization to conduct global optimization searches, obtaining the critical sliding surface and corresponding safety factor of the soil slope under underground coal seam mining. Through comparisons with the numerical simulation results in three different case studies, the feasibility of applying the IRMO algorithm with Lévy flight to analyze the stability of soil slopes under underground mining is demonstrated. This ensures the accuracy and stability of the calculation results while maintaining a high convergence efficiency. Furthermore, the effects of the mining thickness and mining direction on slope stability are analyzed, and the results indicate that a smaller mining thickness and mining along the slope are advantageous for slope stability. The method proposed in this study provides valuable insights for preventing the slope instability hazards caused by underground coal seam mining.

Dahongshan iron ore mine, in China, is a mine that operates both open pit and underground mining at the same time. The ultimate slope will be 435 m high with an overall slope angle of 47°. Underground mining is using the sublevel caving method. Secondary stress by underground mining may seriously deteriorate the stability of the slope. In order to monitor and evaluate the stability of the slope, based on the microseismic monitoring system with 18 sensors installed in the slope, using the calculation method of the amplitude’s attenuation and frequency domain of seismic wave, this paper deduced calculation formula of quality factor based on the dynamic blasting location and uniaxial sensors. This paper obtained continuous dynamic three dimensional quality factor value of the slope rock mass for evaluating the stability and damage degree of the high and steep slope. The results revealed that the quality factor of the rock slope was generally stable in 2015, indicating that there were minimal secondary stress impacts from underground mining. The slope is, so far, still stable.

This paper presents a real-time tool breakage detection method for small diameter drills using acoustic emission (AE) and current signals. Using the transmitted properties of the AE signal, apparatus for detecting the AE signal for tool breakage monitoring was developed for a machine centre. The features of tool breakage were obtained from the AE signal using typical signal processing methods. The continuous wavelet transform (CWT) and the discrete wavelet transform (DWT) were used to decompose the spindle current signal and the feed current signal, respectively. The tool breakage features were extracted from the decomposed signals. Experimental results show that the proposed monitoring system possessed an excellent real-time capability and a high success rate for the detection of the breakage of small diameter drills using combined AE and current signals.

A number of problems related to land use and foundations of new structures are encountered in underground mining areas. Potential suitability and/or unsuitability of lands for new structures must be considered in areas affected by underground mining. It is well-known that subsidence, slope instability, and surface flooding are frequently observed in underground mining areas. Thus, a map that takes into account such geo-hazards and classifies suitable and unsuitable areas for new structures is needed. Areas affected by underground mining of coal in Stonava near to the border of the Czech Republic and Poland represent specific areas where subsidence, slope instability, and surface flooding problems need a strategy for future utilization of the landscape by means of land use plans. In light of the above reasons, the methodology and preparation of a map model incorporating the effect of landslides and surface flooding has been introduced in this study. This map depicts three levels of influence (important influence, moderate influence, and negligible influence). Chronological variations in the building site categories in the study area have been analyzed as another part of the study. It was further crucial to consider the current built-up area in the underground mining area, and therefore, its relation to building site categories has also been evaluated. Consequently, the building site categories were evaluated in relation to the planned built-up area, which is the most important landscape element in a land-use plan as a tool in the decision-making process.

Study on small diameter drilling in GFRP

Investigation on cutting mechanism in small diameter drilling for GFRP (thrust force and surface roughness at drilled hole wall)

This thesis focuses on the numerical simulation of non-linear free surface flow problems. Different simulation kernels based on the Lattice Boltzmann method (LBM) have been developed or extended, implemented, and, after validation, applied to a number of applications in civil and environmental engineering. The LB model solves viscous and turbulent flows, essentially representing similar physics as Navier-Stokes or reduced shallow water models, but with specific solver advantages concerning data locality and parallel computing.
\nThe first part of this thesis deals with numerical simulations on high-performance GPU (graphics processing unit) hardware. Validations and applications of a reduced LB model for solving the shallow water equations are presented. The resulting GPU kernel has shown to be applicable to state-of-the-art benchmark problems, dealing with wave propagation and wave run-up. Subsequently, the GPU implementation of a 3D numerical wave tank for the simulation of various applications in civil engineering is presented.
\nThe second main target of this thesis is to develop and apply a novel model based on an enhanced representation and advection of the phase interface for the simulation of more complex and demanding free surface flow problems. A volume-of-fluid (VOF) approach in combination with a piecewise linear interface reconstruction (PLIC) has been coupled with the LBM. The resulting hybrid model has been successfully validated against various benchmark experiments. Even a breaking wave during shoaling on a slope, which is a demanding test case for VOF solvers, was successfully simulated.
\nApart from the model development and validation itself, a coupling to a rigid body engine for the simulation of FSI problems has been established. Finally, several techniques for the coupling to a potential flow solver are discussed and validated, in order to generate realistic wave profiles and for the efficient simulation of wave run-up and wave breaking.

Optimization problems aim to minimize or maximize an objective function while fulfilling related constraints. This objective function may be a single or multi-objective optimization. Many studies have been conducted on using these optimization problems in civil and construction engineering, especially for the various machine learning techniques and algorithms that have been developed for fiber reinforced polymer (FRP) applications in the rehabilitation and design of RC structures. FRP is considered the most effective and superior technique for strengthening and retrofitting due to its significant benefits over traditional methods, which have numerous drawbacks, as well as the importance of structural strengthening as a cost-effective and practical option. In this research, an insight into how to apply algorithms and machine learning approaches to optimize FRP applications in civil and construction engineering is presented, as well as a detailed analysis of the various optimization strategies used and their findings. A total of 18 case studies from previous research were discussed and critically evaluated, and they were categorized into six groups according to the algorithm or machine learning technique utilized. Based on the case studies investigated in this study, the genetic algorithm was found to be the optimal algorithm utilized for optimizing FRP applications. The result of this research provides a useful guideline for future researchers and specialists.

Mining is one of the oldest professions in history. Along with the development of human life, mines also give direction to civilization and the economy. Mining activities carry various risks in terms of occupational health and safety (OHS). These risks can be examined under the main headings of work accidents and occupational diseases. As a result,thousands of workers face illness and death every year. Additionally, economic losses occur as a result of production interruption and stopping. Despite all the efforts to reduce mining accidents, statistics show that underground mining is one of the riskiest among all working industries. It is seen that the physical risk factors encountered in the mining sectorline are remarkable in terms of risk factors. Physical risk factors that may be encountered in mines are dust, noise, vibration, lighting problems, and thermal conditions. It is essential to take measures to assess these risks and ensure the comfort of employees where each physical risk factor needs to be examined separately. In this study, physical risks beingfrequently encountered in underground coal mines are taken into account with recommendations for the risks.

Mining is one of the oldest professions in history. Along with the development of human life, mines also give direction to civilization and the economy. Mining activities carry various risks in terms of occupational health and safety (OHS). These risks can be examined under the main headings of work accidents and occupational diseases. As a result, thousands of workers face illness and death every year. Additionally, economic losses occur as a result of production interruption and stopping. Despite all the efforts to reduce mining accidents, statistics show that underground mining is one of the riskiest among all working industries. It is seen that the physical risk factors encountered in the mining sector line are remarkable in terms of risk factors. Physical risk factors that may be encountered in mines are dust, noise, vibration, lighting problems, and thermal conditions. It is essential to take measures to assess these risks and ensure the comfort of employees where each physical risk factor needs to be examined separately. In this study, physical risks being frequently encountered in underground coal mines are taken into account with recommendations for the risks.