Computer System for Electric Drives Fault Diagnosis of Mining Shovels

Abstract

It is proposed to conduct fault diagnostic test on electric drives of mining shovels based on the results of monitoring the current values of electromagnetic and mechanical parameters and variables of electric drives obtained in the course of their operation using the modern computer technology. The structure of the developed system of functional diagnostics, allowing to monitor the status of the drive and identify emerging fault is shown in the paper. To determine in real time the current parameters and variables of DC motor which can't be measured during their operation, the dynamic identification was used based on the measured current and voltage of the motor windings, and mathematical estimation methods. Parameters of the mechanical subsystem of electric drive are identified by a mobile measuring system. The authors also give the structure and characteristics of the one-step neural network predictor of current, used to predict the current values in the armature and field windings of motor. The analysis of the technical state of the electric drive by a set of attributes is performed in a special analyzer, built on the basis of pre-trained artificial neural network. The results of these studies support the possibility of creating a diagnostic system for the main electric drives of mining shovels using the estimation methods and apparatus of artificial neural networks.

The observer of a direct-current moto condition on the basis of the particles swarm method

“…Target function allows to define a degree of surge characteristics approximation of the motor and its computer model. There are many estimation methods of dynamical systems, the most frequently used from them are least-square and recursive least-square methods, Kalman Filter, Search Methods, Genetic algorithms, Artificial Neural Networks [1][2][3][4][5][6][7][8][9][10]. Unlike the known algorithms of estimation developed for dynamic identification of electric motors, the PSO method allows to carry out high performance and targeted searching of a target function minimum at change of model parameters, on the basis of adaptation and algorithm parameters correction.…”

The intelligent mechatronic system for open pit mining to increase the operation life of equipment

“…This operation can lead to increasing of high frequency noises from the measuring system. To avoid potential estimation errors and provide high quality of controlling to relay on estimated values, the authors suggest using the numerical filter-differentiator with finite pulse response [14] according to the methodology [15]. …”

“…The service life of the mining machines for open pit mining can be increased without any changes in the design of mechanisms by using intelligent tools [15]. Such tools may be the introduction of additional measurements or using the controlled induction motor drives, which, for example, control the spring forces in the transmission.…”