Search Results (8)

In the field of handling, storage and transportation, chutes are used to transfer bulk solids between conveyors and warehouses. In these systems, traditional analytical methods based on the principles of continuum mechanics approximate an accelerated flow that contains the physical body solid properties obtained from standardized tests. Because it is difficult to physically observe the flow inside the transfer structure, there have been few studies to validate the method at full scale. In contrast, discrete element modeling (DEM) allows flow visualization through a transfer chute and qualitative and quantitative analysis if accurate simulation parameters are selected. In order to adapt to the needs of modern intelligent warehousing, we reduced the grain crushing and damage in the process of grain storage. To design and investigate the motion performance of grain particles in a sliding dustpan, this paper utilizes rocky simulation technology, combined with the corresponding bench experiments, to study the impact of the angle arrangement of the dustpan, and to verify the results of the simulation analysis based on the stress–strain analysis of the particle impact. It was found that when the angle of the dustpan arrangement was 40 degrees, the flow of all particles had a better performance in terms of pass ability and energy loss. In the continuous cycle obtained from the simulation, the particle group state at each moment is almost the same as the particle characteristics in the experiment, indicating that the angle of the bucket has an effect on the particle permeability. In this paper, the results of the study on the state of the grain group on the silo device will provide a useful reference for the design of a grain silo device. Full article

This paper presents a model for determining the availability of continuous systems at open pits using the neuro-fuzzy system. The concept of availability is divided into partial indicators (synthetic indicators and sub-indicators). The presented model in relation to already existing models for determining availability uses a combination of the advantages of artificial neural networks and fuzzy logic. The case study addressed the I ECC (bucket wheel excavator–conveyors–crushing plant) system of the open pit Drmno, Kostolac. In this paper, in addition to the ANFIS model for determining the availability of continuous systems, a simulation model was developed. The obtained results of the ANFIS model were verified with the help of a simulation model that uses certain assumptions about the distribution of failures. This paper was created as a result of several years of field and theoretical research into the availability of continuous systems in open pits, and completes a cycle that consists of several published articles on the subject of modeling the behavior of these systems in real time using a time picture of the state, expert assessment, simulation and AI models, while respecting the multidisciplinarity of the problem (mining technological, mechanical, and information technological aspects). The developed ANFIS model is a key instrument for improving operational efficiency and resource management in the mining sector. Its ability to accurately predict the availability of the ECC system brings not only operational benefits through reduced downtime and optimized maintenance, but also a potential reduction in overall costs at coal open pits. Such an innovative model marks a significant step forward in the mining industry, especially when it comes to continuous systems in coal open pits. Full article

This study presents the structure and principles of operation of the control system for a bucket conveyor operating in a jig preparation plant. The idea of controlling the conveyor speed is to maintain constant, nominal filling of the buckets, and thus achieve a constant mass of material on the conveyor. As part of the completed task, a new control algorithm was developed and implemented to increase transport efficiency. Simulation and industrial test results were analyzed, in which the traditional PID controller was replaced with a fuzzy controller, which enabled control error reduction, thus achieving better control quality. Full article

This paper presents a model for determining fuzzy evaluations of partial indicators of the availability of continuous systems at coal open pits using a neuro-fuzzy inference system. The system itself is a combination of fuzzy logic and artificial neural networks. The system availability is divided into partial indicators. By combining the fuzzy logic and artificial neural networks, a model is obtained that has the ability to learn and uses expert judgment for that learning. This paper deals with the ECC system (bucket wheel excavator-conveyor-crushing plant) of the open pit Drmno-Kostolac, which operates within the Electric Power Company of Serbia. The advantage of a model of this type is that it does not rely on the historical experiences of experts and usual predicted values for the fuzzy evaluation of partial indicators, which are based on the assumption that similar systems affect availability in a similar way. The fuzzy evaluation of partial indicators is based on historical data for the specific system for which the model was created. As such, it can more accurately predict continuous systems availability on the basis of expert evaluations in the appropriate time period. Another advantage of this model is that the availability is estimated on a quarterly basis, which gives a more accurate view because it uses a smaller time period with more similar characteristics and, thus, includes certain external influences which are related to the quarterly meteorological conditions. Full article

The subject of the discussion is oriented toward limiting the energy consumption of the bucket conveyor used in jig concentrator plants by controlling its speed. A method of predictive control of the bucket conveyor speed is presented. It allows for reducing the energy consumption due to appropriate selection of bucket movement speed to ensure the nominal filling of buckets along the entire length of the conveyor. This approach enables limiting the idling speed of the conveyor, extend its life, and also reduce the electricity consumption of the entire system. Experimental studies, carried out at the “Sośnica” Coal Mine working facility, confirmed that the use of a predictive algorithm for controlling the bucket conveyor speed and adapting the bucket speed to the current load decreased in energy consumption n by 9.6%, with 80% of the filling conveyor. Full article

Urbanization is a big concern for both developed and developing countries in recent years. People shift themselves and their families to urban areas for the sake of better education and a modern lifestyle. Due to rapid urbanization, cities are facing huge challenges, one of which is waste management, as the volume of waste is directly proportional to the people living in the city. The municipalities and the city administrations use the traditional wastage classification techniques which are manual, very slow, inefficient and costly. Therefore, automatic waste classification and management is essential for the cities that are being urbanized for the better recycling of waste. Better recycling of waste gives the opportunity to reduce the amount of waste sent to landfills by reducing the need to collect new raw material. In this paper, the idea of a real-time smart waste classification model is presented that uses a hybrid approach to classify waste into various classes. Two machine learning models, a multilayer perceptron and multilayer convolutional neural network (ML-CNN), are implemented. The multilayer perceptron is used to provide binary classification, i.e., metal or non-metal waste, and the CNN identifies the class of non-metal waste. A camera is placed in front of the waste conveyor belt, which takes a picture of the waste and classifies it. Upon successful classification, an automatic hand hammer is used to push the waste into the assigned labeled bucket. Experiments were carried out in a real-time environment with image segmentation. The training, testing, and validation accuracy of the purposed model was 0.99% under different training batches with different input features. Full article

The sustainability of lignite production requires, among other factors, cost reduction, high efficiency, as well as the increase of the production capacity. In order to rationalize and increase the efficiency of lignite mines, the optimization of the production process is necessary. In this respect, equipment revitalization and modernization is a key issue. This paper deals with the analysis of the time response of the boom structure of a bucket wheel excavator (BWE) during operation. For this, we propose a virtual model of the boom, on which a variable-in-time force generated by the bucket wheel acts. The kinematic drive chain of the bucket wheel and the conveyor belt, which are also vibration generators, were simulated only by the static load produced on the excavator’s boom. Thus, it is possible to highlight the time response of the load-bearing structure (the boom) of the bucket wheel to the action of forces resulting from the cutting of the face under pretensioning conditions. The forces generated by the excavation process have high values and a slow variation over time, depending on the bucket wheel’s rotation speed and the number of buckets installed on the wheel. The dynamic time response simulation was performed considering the global damping variation as dependent on frequency. The simulation was done for both the excavation of a homogeneous material and for the case of the sudden appearance of a hard material inclusion (boulder) during homogenous material cutting. Full article

In a continuous system of production in open-cast coal mining, in addition to the basic machinery which consists of highly productive machines (bucket-wheel excavators, bucket-chain excavators, spreaders, conveyor-belt transporters, etc.) that provide an uninterrupted exploitation of mineral ores, the usage of auxiliary machinery is also necessary. The auxiliary machinery provides the possibility of using the capacities of basic machinery adequately and timely. Further, it must be mentioned that the auxiliary machinery generates up to 20% of the total mining expenses. Dozers are the most commonly used machines. Choosing the adequate dozer of the right type and manufacturer is of great importance and can be made easier by carrying out an analysis of the existent operational-exploitative parameters. In this paper, the method of grading the operational-exploitative parameters of dozer is defined. The choice of the optimal type of dozer was conducted by using the analytical hierarchy process (AHP). Full article