Optimization of blasting parameters in opencast mines

Drilling and blasting are the major unit operations in opencast mining. Inspite of the best efforts to introduce mechanization in the opencast mines, blasting continue to dominate the production. Therefore to cut down the cost of production optimal fragmentation from properly designed blasting pattern has to be achieved. Proper adoption of drilling and blasting can contribute significantly towards profitability and therefore optimization of these parameters is essential. Introduction Rock breaking by drilling and blasting is the first phase of the production cycle in most of the mining operations. Optimization of this operation is very important as the fragmentation obtained thereby affects the cost of the entire gamut of interrelated mining activities, such as drilling, blasting, loading, hauling, crushing and to some extent grinding. Optimization of rock breaking by drilling and blasting is sometimes understood to mean minimum cost in the implementation of these two individual operations. However, a minimum cost for breaking rock may not be in the best interest of the overall mining system. A little more money spent in the rock-breaking operation can be recovered later from the system and the aim of the coordinator of the mining work should be to achieve a minimum combined cost of drilling, blasting, loading, hauling, crushing and grinding. Only a “balance sheet” of total cost of the full gamut of mining operations vis-à-vis production achieved can establish whether the very first phase- rock breaking- was “optimum” financially; leaving aside factors of human safety. An optimum blast is also associated with the most efficient utilization of blasting energy in the rock- breaking process, reducing blasting cost through less explosive consumption and less wastage of explosive energy in blasting, less throw of materials, and reduction of blast vibration resulting in greater degrees of safety and stability to the nearby structures. Development of a Blast Optimization Model Selection of proper explosive in any blasting round is an important aspect of optimum blast design. Basic parameters include VOD of explosive (m/s), Density (g/cc), Characteristic impedance, Energy output (cal/gm), and Explosive type (ANFO, Slurry, Emulsion etc.). However, all these parameters can not be taken for optimizing the blasting method successfully. Some of the parameters are taken for minimizing the blasting cost. These cost reduction and optimum blast design parameter will give an economical result. The parameters are i. Drill hole diameter, ii. Powder factor (desired), iii. Cost of explosive, iv. Numbers of holes required to blast. Methodology The study of the various parameters of blasting suggests that the powder factor should be constant as per the requirement. The number of holes desired as per the explosive, the drill ihole diameter as available and the cost of explosive are kept as input. The spacing, bench height, burden, charge per hole as depending on the previous parameters can be calculated. From the different input and calculated parameters the total cost of the method is calculated and the least expensive method is selected as the optimized model. Blasting related information were collected from three different mines of Mahanadi Coalfields Ltd.(MCL) for implementation of the optimization model. A program was designed using visual basic on .net platform taking the above parameters into consideration to select the optimized model. It was observed that the program gives satisfactory results. A sample output of the program is as presented below: Conclusion The blast optimization model has been developed with simple methodologies which can be adopted by the mining industry to compare the explosive costs and achieve better blasting results and. The model developed is a user friendly one, since by keeping the powder factor and number of choices of explosives available as constant and by varying the parameters like drill hole diameter, number of holes and cost of explosives one can compare the explosive performance and accordingly take a decision to select the proper type of explosives for blasting. It may be noted, that the model has been developed based on case studies of three different mines of MCL, and it can be modified with collection of information from a large number of mines. References Nanda, N.K. (2003), “Optimization of mine production system through operation research techniques”, 19 th World Mining Congress, New Delhi, November, pp.583-595. Pal Roy, P. (2005), “Terms and parameters influencing mine and ground excavations”, Rock blasting effects and operations, pp. 17-22

Predictive model for the degradation state of a hydraulic system with dimensionality reduction

In recent years, the optimization in the use of resources has a key role in achieving a bigger marginality, reducing the operative costs. Due to the advances in the data science field, even the maintenance context is living important changes. The predictive maintenance and the condition-based maintenance can overcome the classic traditional maintenance methods, like the time-based maintenance or the corrective maintenance, with respect to the first intervention, reducing the costs for unscheduled maintenance, manpower, or loss of production and extending the useful life of the components. Based on these presuppositions, the paper proposes the development of a predictive model for the degradation state of the components of a complex hydraulic system, with some tests and some suggestions about the dimensionality reduction. The system has four known types of breakdown, with different degrees of severity; moreover, a fifth parameter represents whether the cycle has reached stable conditions or not

Volume 1 – Symposium

We are pleased to present the conference proceedings for the 12th edition of the International Fluid Power Conference (IFK). The IFK is one of the world’s most significant scientific conferences on fluid power control technology and systems. It offers a common platform for the presentation and discussion of trends and innovations to manufacturers, users and scientists. The Chair of Fluid-Mechatronic Systems at the TU Dresden is organizing and hosting the IFK for the sixth time. Supporting hosts are the Fluid Power Association of the German Engineering Federation (VDMA), Dresdner Verein zur Förderung der Fluidtechnik e. V. (DVF) and GWT-TUD GmbH. The organization and the conference location alternates every two years between the Chair of Fluid-Mechatronic Systems in Dresden and the Institute for Fluid Power Drives and Systems in Aachen. The symposium on the first day is dedicated to presentations focused on methodology and fundamental research. The two following conference days offer a wide variety of application and technology orientated papers about the latest state of the art in fluid power. It is this combination that makes the IFK a unique and excellent forum for the exchange of academic research and industrial application experience. A simultaneously ongoing exhibition offers the possibility to get product information and to have individual talks with manufacturers. The theme of the 12th IFK is “Fluid Power – Future Technology”, covering topics that enable the development of 5G-ready, cost-efficient and demand-driven structures, as well as individual decentralized drives. Another topic is the real-time data exchange that allows the application of numerous predictive maintenance strategies, which will significantly increase the availability of fluid power systems and their elements and ensure their improved lifetime performance. We create an atmosphere for casual exchange by offering a vast frame and cultural program. This includes a get-together, a conference banquet, laboratory festivities and some physical activities such as jogging in Dresden’s old town.:Group A: Materials Group B: System design & integration Group C: Novel system solutions Group D: Additive manufacturing Group E: Components Group F: Intelligent control Group G: Fluids Group H | K: Pumps Group I | L: Mobile applications Group J: Fundamental

Shared Control Policies and Task Learning for Hydraulic Earth-Moving Machinery

This thesis develops a shared control design framework for improving operator efficiency and performance on hydraulic excavation tasks. The framework is based on blended shared control (BSC), a technique whereby the operator’s command input is continually augmented by an assistive controller. Designing a BSC control scheme is subdivided here into four key components. Task learning utilizes nonparametric inverse reinforcement learning to identify the underlying goal structure of a task as a sequence of subgoals directly from the demonstration data of an experienced operator. These subgoals may be distinct points in the actuator space or distributions overthe space, from which the operator draws a subgoal location during the task. The remaining three steps are executed on-line during each update of the BSC controller. In real-time, the subgoal prediction step involves utilizing the subgoal decomposition from the learning process in order to predict the current subgoal of the operator. Novel deterministic and probabilistic prediction methods are developed and evaluated for their ease of implementation and performance against manually labeled trial data. The control generation component involves computing polynomial trajectories to the predicted subgoal location or mean of the subgoal distribution, and computing a control input which tracks those trajectories. Finally, the blending law synthesizes both inputs through a weighted averaging of the human and control input, using a blending parameter which can be static or dynamic. In the latter case, mapping probabilistic quantities such as the maximum a posteriori probability or statistical entropy to the value of the dynamic blending parameter may yield a more intelligent control assistance, scaling the intervention according to the confidence of the prediction. A reduced-scale (1/12) fully hydraulic excavator model was instrumented for BSC experimentation, equipped with absolute position feedback of each hydraulic actuator. Experiments were conducted using a standard operator control interface and a common earthmoving task: loading a truck from a pile. Under BSC, operators experienced an 18% improvement in mean digging efficiency, defined as mass of material moved per cycle time. Effects of BSC vary with regard to pure cycle time, although most operators experienced a reduced mean cycle time

The 747 primary flight control systems reliability and maintenance study

The major operational characteristics of the 747 Primary Flight Control Systems (PFCS) are described. Results of reliability analysis for separate control functions are presented. The analysis makes use of a NASA computer program which calculates reliability of redundant systems. Costs for maintaining the 747 PFCS in airline service are assessed. The reliabilities and cost will provide a baseline for use in trade studies of future flight control system design

Analytical techniques and instrumentation: A compilation

Technical information is presented covering the areas of: (1) analytical instrumentation useful in the analysis of physical phenomena; (2) analytical techniques used to determine the performance of materials; and (3) systems and component analyses for design and quality control

Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems

The transition to 100% renewable energy in the future is one of the most important ways of achieving "carbon peaking and carbon neutrality" and of reducing the adverse effects of climate change. In this process, the safe, stable and economical operation of renewable energy generation systems, represented by hydro-, wind and solar power, is particularly important, and has naturally become a key concern for researchers and engineers. Therefore, this book focuses on the fundamental and applied research on the modeling, control, monitoring and diagnosis of renewable energy generation systems, especially hydropower energy systems, and aims to provide some theoretical reference for researchers, power generation departments or government agencies

Failure Diagnosis and Prognosis of Safety Critical Systems: Applications in Aerospace Industries

Many safety-critical systems such as aircraft, space crafts, and large power plants are required to operate in a reliable and efficient working condition without any performance degradation. As a result, fault diagnosis and prognosis (FDP) is a research topic of great interest in these systems. FDP systems attempt to use historical and current data of a system, which are collected from various measurements to detect faults, diagnose the types of possible failures, predict and manage failures in advance. This thesis deals with FDP of safety-critical systems. For this purpose, two critical systems including a multifunctional spoiler (MFS) and hydro-control value system are considered, and some challenging issues from the FDP are investigated. This research work consists of three general directions, i.e., monitoring, failure diagnosis, and prognosis. The proposed FDP methods are based on data-driven and model-based approaches. The main aim of the data-driven methods is to utilize measurement data from the system and forecast the remaining useful life (RUL) of the faulty components accurately and efficiently. In this regard, two dierent methods are developed. A modular FDP method based on a divide and conquer strategy is presented for the MFS system. The modular structure contains three components:1) fault diagnosis unit, 2) failure parameter estimation unit and 3) RUL unit. The fault diagnosis unit identifies types of faults based on an integration of neural network (NN) method and discrete wavelet transform (DWT) technique. Failure parameter estimation unit observes the failure parameter via a distributed neural network. Afterward, the RUL of the system is predicted by an adaptive Bayesian method. In another work, an innovative data-driven FDP method is developed for hydro-control valve systems. The idea is to use redundancy in multi-sensor data information and enhance the performance of the FDP system. Therefore, a combination of a feature selection method and support vector machine (SVM) method is applied to select proper sensors for monitoring of the hydro-valve system and isolate types of fault. Then, adaptive neuro-fuzzy inference systems (ANFIS) method is used to estimate the failure path. Similarly, an online Bayesian algorithm is implemented for forecasting RUL. Model-based methods employ high-delity physics-based model of a system for prognosis task. In this thesis, a novel model-based approach based on an integrated extended Kalman lter (EKF) and Bayesian method is introduced for the MFS system. To monitor the MFS system, a residual estimation method using EKF is performed to capture the progress of the failure. Later, a transformation is utilized to obtain a new measure to estimate the degradation path (DP). Moreover, the recursive Bayesian algorithm is invoked to predict the RUL. Finally, relative accuracy (RA) measure is utilized to assess the performance of the proposed methods

Modelling of Crankcase Gas Behaviour in a Heavy-Duty Diesel Engine

The origin of many environmental and health hazardous emissions from diesel engines are the crankcase gases. Since no regulations of the emission levels from the crankcase have existed in the past, no attention has been paid to cleaning crankcase gases. New regulations are coming up and they will all demand lower emissions from the engine. This has lead to the introduction of the Alfdex separator. The Alfdex separator is built to separate oil droplets and soot from the crankcase gases. In the research work made in this master thesis, we have investigated the possibilities to model the crankcase gases with respect to flow rate and oil content with some parameters of the engine. The model could then be used as an input to a controller that controls the separator speed. Since the test engine used here is old and is not in production anymore, the idea of the modelling is to find more general characteristics rather than specifics for the tested engine. The work made in this master thesis shows that the crankcase gas flow rate can be modelled in a good way. The identifying process done here is accomplished by field tests on a Volvo bus equipped with a TD123E motor, which is a 6 cylinder, 12 litres, turbocharged diesel engine. Since no prior testing had been made, the project involved much practical work such as test rig building, mounting on the bus etc. The measurements on crankcase gases have been made both at stationary modes and dynamically. The project also involves measurements of the oil content in crankcase gases. These measurements have been made at steady state, with no possibility to investigate the dynamic behaviour of the oil aerosol. The tests made on the size distribution of oil in the crankcase gases gives a hint to the future development of a controller

Integrated Application of Active Controls (IAAC) technology to an advanced subsonic transport project: Current and advanced act control system definition study. Volume 2: Appendices

The current status of the Active Controls Technology (ACT) for the advanced subsonic transport project is investigated through analysis of the systems technical data. Control systems technologies under examination include computerized reliability analysis, pitch axis fly by wire actuator, flaperon actuation system design trade study, control law synthesis and analysis, flutter mode control and gust load alleviation analysis, and implementation of alternative ACT systems. Extensive analysis of the computer techniques involved in each system is included