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In this article, the main methods of technical diagnostics of diesel fuel equipment are considered. The faults they detect are listed. The principles of the methods work are examined in detail, the shortcomings and advantages of the chosen methods are revealed.

The article presents statistical studies of acoustic control signals when diagnosing power transformers of the railway power supply system. Statistical processing of acoustic monitoring data was carried out on the example of transformers with different levels of insulation condition. Comparisons of histograms of the experimental distribution of amplitudes and dominant frequencies of signals with the nearest theoretical distribution laws, performed in the STATISTICA program according to control data obtained from the automated system. The conducted studies have shown a close correlation of defects registered by the acoustic method with the distribution of signals in the form of laws of distribution of random variables. It is shown that for power transformers with mechanical oscillations, both during the passage of the train and at idle, the distribution of amplitudes and dominant frequencies of the recorded signals corresponds to a uniform law. The distribution of amplitudes and dominant frequencies is not centered around a certain average value. For power transformers containing partial discharges, the cause of which is the deterioration of the insulating properties of the windings under the influence of high voltage, the best approximation, both amplitudes and dominant frequencies, showed the Lognormal distribution. The signals are centered around a characteristic mean value. When the train passes, the acoustic system registers both high-frequency signals from the PD and low-frequency signals from body vibrations. There are two components in the distribution law - uniform and lognormal distribution densities. Thus, by the type of distribution of the recorded signals, their amplitude and dominant frequency, it is possible to determine the presence of a defective state of the insulation of power transformers. The study was carried out with the financial support of the Russian Foundation for Basic Research within the framework of the scientific project No. 20-38-90231.