Open AccessMethodology for diagnosing diesel engines of automotive vehicles by the parameters of the acoustic signal
Author(s) -
Victor A. KRUCHEK,
AUTHOR_ID,
Andrey A. GORBACHEV,
Roman Ivanov,
AUTHOR_ID,
AUTHOR_ID
Publication year - 2021
Publication title -
izvestiâ peterburgskogo universiteta putej soobŝeniâ
Language(s) - English
Resource type - Journals
eISSN - 2658-6851
pISSN - 1815-588X
DOI - 10.20295/1815-588x-2021-4-571-577
Subject(s) - automotive engineering , chassis , automotive industry , troubleshooting , automotive engine , reliability (semiconductor) , signal (programming language) , engineering , signal processing , computer science , reliability engineering , power (physics) , mechanical engineering , electronic engineering , digital signal processing , physics , quantum mechanics , programming language , aerospace engineering
Objective: Development of a methodology for diagnosing engines of automotive vehicles by the parameters of an acoustic signal. Methods: A mathematical apparatus has been developed for processing acoustic signals of engines, which allows creating an acoustic portrait of the engine under test with high reliability and comparing it with high effi ciency with a reference acoustic portrait of a serviceable engine of the same type. The acoustic signal is removed from the power plant of the car base chassis using a newly created technical diagnostic tool. Results: The developed methodology for diagnosing automotive engines by the parameters of an acoustic signal allows us to signifi cantly increase the level of effi ciency and reliability of troubleshooting in automotive engines without resorting to collapsible diagnostic methods. Practical importance: The developed methodology and new diagnostic equipment make it possible to conclude on the serviceability of the power plant and to give an opinion on further operation or to obtain information on the types of malfunctions in the engine, which will reduce the time for diagnosing automotive equipment in general and speed up the process of identifying malfunctions by a CIP method with the issuance of recommendations for their elimination.