ПРИМЕНЕНИЕ НЕЙРОСЕТЕВОГО ПОДХОДА ДЛЯ ДИАГНОСТИКА ДВИГАТЕЛЯ ВНУТРЕННЕГО СГОРАНИЯ ТРАНСПОРТНЫХ СРЕДСТВ

Abstract

The work is devoted to the problem of diagnosing the internal combustion engine of vehiclesthis problem is now the most relevant due to the constant growth of the car fleet and the tighteningof requirements for safe operation. Timely and accurate control of the internal combustion engineis able to prevent the failure of entire vehicle assemblies, as well as to avoid such serious consequencesas a traffic accident. With the advent of modern technologies the long-known method ofengine condition estimation by sound can become the most advanced, since the human factor isexcluded, for signal processing the computer technique is applied, the analysis of a sound spectrumin which is carried out by means of artificial neural networks. The application of artificialneural networks for analyzing the sound spectrum has found application in speech recognition andfor diagnosing diseases of the respiratory system. The article deals with the failure of one of themain parts of internal combustion engine - the bearing. All possible types of bearing faults and thereasons why they occur are presented. The nodes and mechanisms of the internal combustion enginein which bearings are used are listed. The algorithm of the experimental part is described.The experiment which includes transformation of the received sound signals into spectrogramsand extraction of features with the help of which the classification is carried out, is executed. Theexecuted experimental part has proved the possibility of diagnosing of the internal combustionengine by means of artificial neural networks. Scientific novelty lies in the fact that the diagnosticprocess becomes automated, all the sounds taken by sensors are processed in a computer or in thefuture in a special scanner, the display shows information about the state of certain nodes, unliketraditional methods where the diagnosis is carried out visually or by ear. Thus, the diagnosticaccuracy increases and the overall labor intensity decreases due to the exclusion of partial orcomplete engine disassembly.