Fault Diagnosis and Analysis of Diesel Engine Valve Mechanism Based on ITD

In order to better diagnose and analyze faults in diesel engine valve train, this paper first simulates four working conditions: normal valve clearance, small clearance, large clearance, and coupling of strut bending by adjusting valve clearance and replacing the tappet.Cylinder head vibration signals are collected at idle speed of 700 rpm; Then, the ITD algorithm is used to decompose the signal, extract marginal spectral features, and select 12 frequency domain features to construct a fault feature vector; finally Using ITD marginal spectrum and Mahalanobis distance for fault identification, the results showed that there were significant differences in ITD marginal spectrum under different operating conditions.Among the 12 test samples, there were 0 false positives, and the diagnostic accuracy reached 100%.Research has shown that the ITD marginal spectrum can effectively characterize the fault characteristics of diesel engine valve mechanisms, providing a new approach for fault diagnosis of non-stationary vibration signals.

Publication Details

Journal
International Journal of Science and Engineering Applications
Published
2025-04-25
DOI
https://doi.org/10.7753/ijsea1405.1003
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Fault Diagnosis and Analysis of Diesel Engine Valve Mechanism Based on ITD

International Journal of Science and Engineering Applications
Advanced Sensor and Control Systems
article

Fault Diagnosis and Analysis of Diesel Engine Valve Mechanism Based on ITD

article en

Abstract

In order to better diagnose and analyze faults in diesel engine valve train, this paper first simulates four working conditions: normal valve clearance, small clearance, large clearance, and coupling of strut bending by adjusting valve clearance and replacing the tappet.Cylinder head vibration signals are collected at idle speed of 700 rpm; Then, the ITD algorithm is used to decompose the signal, extract marginal spectral features, and select 12 frequency domain features to construct a fault feature vector; finally Using ITD marginal spectrum and Mahalanobis distance for fault identification, the results showed that there were significant differences in ITD marginal spectrum under different operating conditions.Among the 12 test samples, there were 0 false positives, and the diagnostic accuracy reached 100%.Research has shown that the ITD marginal spectrum can effectively characterize the fault characteristics of diesel engine valve mechanisms, providing a new approach for fault diagnosis of non-stationary vibration signals.

International Journal of Science and Engineering Applications
Affordable and clean energy
Openalex Percentile: Top 91%
Advanced Sensor and Control Systems
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Fault Diagnosis and Analysis of Diesel Engine Valve Mechanism Based on ITD · International Journal of Science and Engineering Applications (2025) | TGRS Research Map | TGRS