APPLICATION OF ARTIFICIAL INTELLIGENCE METHODS IN DIAGNOSTICS OF MINING MACHINERY

The paper describes the modern diagnostic system destined for mine haulage and hoisting equipment, equipped with intelligent sensors and transducers, and controlled by means of an industrial computer. Expert System (ES) has been chosen to diagnose the above mentioned equipment. The paper presents the basic architecture of “Diagnoprzem” and “HELMOS” computer knowledge based expert system (KBES) implemented for the fault diagnostics and the detailed monitoring of generators and distribution substations in power systems. The operation of every circuit breaker and switch is recorded in the Digital Fault Recorder (DFR) of the mine. All electrical, mechanical and kinetics parameters are measured by the installed sensors and transformers respectively. These signals are acquired by the presented computational system and subsequently used to evaluate the condition of the generator and the substation. The estimated conditions are compared to the measured ones in order to detect any conflict that could induce an abnormal situation. An intelligent algorithm is executed during a program scan cycle incorporating the stored knowledge of the expert operator. Some results of computer simulations are given. This paper presents also the results of industrial testing.