Algorithm for Diagnosing an Autonomous Low-Power Diesel-Generator Unit

A method for diagnosing autonomous diesel-generator units has been proposed, based on the use of artificial neural network technology. This method allows for a reduction in the time required for diagnosis without the need for a complete examination of the diagnostic object. The method enables a reduction in the number of checks needed to identify a faulty condition of an element by an average of 30%.

Authors

Institutions

Publication Details

Journal
Russian Electrical Engineering
Published
2024-10-01
DOI
https://doi.org/10.3103/s1068371224700998
Primary Topic
Engineering Diagnostics and Reliability
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Algorithm for Diagnosing an Autonomous Low-Power Diesel-Generator Unit

Дамир Михайлович Кочеганов, Alexey Steklov, A. V. Serebryakov
Russian Electrical Engineering
Engineering Diagnostics and Reliability
article

Algorithm for Diagnosing an Autonomous Low-Power Diesel-Generator Unit

Дамир Михайлович Кочеганов, Alexey Steklov, A. V. Serebryakov
article en

Abstract

A method for diagnosing autonomous diesel-generator units has been proposed, based on the use of artificial neural network technology. This method allows for a reduction in the time required for diagnosis without the need for a complete examination of the diagnostic object. The method enables a reduction in the number of checks needed to identify a faulty condition of an element by an average of 30%.

Russian Electrical EngineeringVol. 95(10)
Linguistics University of Nizhny Novgorod (RU), Nizhny Novgorod State Technical University (RU), Nizhny Novgorod State Pedagogical University (RU)
Affordable and clean energy
Openalex Percentile: Top 70%
Engineering Diagnostics and Reliability
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.