Operation monitoring of the locomotive diesel turbocharger performance

Almost all known solutions in diagnostics of the locomotive diesel gas-air tract units are related to the stationary testing diagnostics performed during the rheostat tests of a locomotive diesel or the turbocharger running-in on a stand, and they involve monitoring a significant number of parameters. At the same time, if parametric failures of the supercharging units are not detected in a timely manner, this could lead to a decrease in the locomotive plant power and efficiency, and deterioration of its environmental performance indicators. Therefore, the task of promptly assessing technical condition of the locomotive diesel gas-air tract main units both during operation and during rheostat tests in order to timely detect and predict its deterioration appears relevant. The paper theoretically substantiates and experimentally verifies the method for operation monitoring the turbocharger and the diesel exhaust device performance based on the results of measuring the total temperature difference on the nozzle apparatus and the turbine wheel. It proposes a method for implementing this technique using the intelligent neural network classifier. A method for accounting the influence of heat removal from gas into the cooling water was developed using mathematical simulation of the diesel engine and supercharging units working processes. Advantage of the proposed method in monitoring the turbocharger technical condition lies in simplicity of its implementation and a possibility of using data from different diesel engines to learn the unified classifier of technical condition.
EDN: FNMMPG, https://elibrary/fnmmpg

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