Fault diagnosis of internal combustion engines using visual dot patterns of acoustic and vibration signals

In this article authors show the possibillities of using the parameters of vibration signals to estimate valve clearance in internal combustion engines. The main methodological assumptions of signal analysis and their results have been presented herein. The concept of research so as to solve the valve clearance diagnostic problem, based on the vibration signal, has been shown as well.

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Fault diagnosis in internal combustion engines using non-linear multivariate statistics

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1243/095965105x9614 ◽

2005 ◽

Vol 219 (4) ◽

pp. 243-258 ◽

Cited By ~ 17

Author(s):

D Antory ◽

U Kruger ◽

G Irwin ◽

G McCullough

Keyword(s):

Fault Diagnosis ◽

Internal Combustion Engines ◽

Principal Component ◽

Reconstruction Algorithm ◽

Internal Combustion ◽

Fault Isolation ◽

Operating Conditions ◽

Combustion Engines ◽

Sensor Fault ◽

Non Linear

This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce non-linear relationships between the recorded engine variables, the paper proposes the use of non-linear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new non-linear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady state operating conditions. More precisely, non-linear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (a) an enhanced identification of potential root causes of abnormal events and (b) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA-based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, while the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 litre diesel engine mounted on an experimental engine test bench facility.

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Modelling and diagnosis of big-end bearing knock fault in internal combustion engines

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406214524743 ◽

2014 ◽

Vol 228 (16) ◽

pp. 2973-2984 ◽

Cited By ~ 5

Author(s):

Jian Chen ◽

Robert Randall ◽

Ningsheng Feng ◽

Bart Peeters ◽

Herman Van der Auweraer

Keyword(s):

Internal Combustion Engines ◽

Internal Combustion ◽

Combustion Engines ◽

Vibration Signals ◽

Impact Forces ◽

Mechanical Faults ◽

Measured Frequency Response ◽

Lubrication Characteristics ◽

The Time Domain ◽

The Impact

Big-end bearing knock is considered to be one of the common mechanical faults in internal combustion engines (IC engines). In this paper, a model has been built to simulate the effects of oversized clearance in the big-end bearing of an engine. In order to find a relationship between the acceleration response signal and the oversized clearance, the kinematic/kinetic and lubrication characteristics of the big ending bearing were studied. By adjusting the clearance, the impact forces with different levels of bearing knock fault can be simulated. The acceleration on the surface of the engine block was calculated by multiplying the simulated force spectrum by an experimentally measured frequency response function (FRF) in the frequency domain (and then inverse transforming to the time domain). As for experimentally measured vibration signals from bearing knock faults, the signal processing approach used involved calculating the squared envelopes of the simulated acceleration signals. The comparison to the experimental results demonstrated that the simulation model can correctly simulate vibration signals with different stages of bearing knock faults.

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