Nikola Lilic

Risk assessment model of mining equipment failure based on fuzzy logic

Abstract The systematic maintenance of mining machinery and equipment is the crucial factor for the proper functioning of a mine without production process interruption. For high-quality maintenance of the technical systems in mining, it is necessary to conduct a thorough analysis of machinery and accompanying elements in order to determine the critical elements in the system which are prone to failures. The risk assessment of the failures of system parts leads to obtaining precise indicators of failures which are also excellent guidelines for maintenance services. This paper presents a model of the risk assessment of technical systems failure based on the fuzzy sets theory, fuzzy logic and min–max composition. The risk indicators, severity, occurrence and detectability are analyzed. The risk indicators are given as linguistic variables. The model presented was applied for assessing the risk level of belt conveyor elements failure which works in severe conditions in a coal mine. Moreover, this paper shows the advantages of this model when compared to a standard procedure of RPN calculating – in the FMEA method of risk assessment.

An intelligent hybrid system for surface coal mine safety analysis

Analysis of safety in surface coal mines represents a very complex process. Published studies on mine safety analysis are usually based on research related to accidents statistics and hazard identification with risk assessment within the mining industry. Discussion in this paper is focused on the application of AI methods in the analysis of safety in mining environment. Complexity of the subject matter requires a high level of expert knowledge and great experience. The solution was found in the creation of a hybrid system PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. The main goal of the system is the estimation of mining environment as one of the significant components of general safety state in a mine. This global goal is subdivided into a hierarchical structure of subgoals where each subgoal can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination, geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. Both the hybrid nature of the system and the possibilities it offers are illustrated through a case study using field data related to an existing Serbian surface coal mine.

Prediction of flyrock launch velocity using artificial neural networks

Due to a potential to cause damage to machinery and structures and cause injuries to personnel, flyrock is the most dangerous adverse effect of blasting operations. Because of that, it is of primary importance to predict flyrock events and maximum range of flyrock fragments in order to define safety limits and secure the perimeter. There are various models for flyrock range prediction, and most of them rely on proper calculations of flyrock launch velocity. However, a unique and universally applicable model of launch velocity prediction still does not exist. Work presented in this article is a concept of adaptive system application for the prediction of flyrock launch velocities. It shows the principles of input data selection, acquisition and processing and presents the principles of design, training, validation and verification of applied artificial neural network.

A KNOWLEDGE-BASED APPROACH TO MINE VENTILATION PLANNING IN YUGOSLAV MINING PRACTICE

Ventilation system analysis is a complex process based on the calculation and analysis of numerous parameters. These problems can be successfully solved by the SimVent numerical package, but a full understanding and use of the obtained results require the involvement of an experienced specialist in the ventilation field. The solution was found in the creation of a hybrid system INVENTS, whose knowledge base represents a formalization of the expert knowledge in the mine ventilation field. In this paper, we present the design methodology of the hybrid system INVENTS, as well as system structure and user interface.