Time-frequency analysis of single-point engine-block vibration measurements for multiple excitation-event identification

Vulli, S; Dunne, John F.; Potenza, R; Richardson, Dave; King, Paul D.

doi:10.1016/j.jsv.2008.10.011

Cited by 83 publications

(47 citation statements)

References 19 publications

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“…The vibration signal of diesel engine cylinder head contains much information about working state and fault characteristics. Extracting proper characteristic parameters from the vibration signal can effectively identify the working state and related faults of a diesel engine [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Diesel Engine Valve Clearance Fault Diagnosis Based on Improved Variational Mode Decomposition and Bispectrum

Cao

Zhang

2019

Energies

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The evaluation and fault diagnosis of a diesel engine’s health conditions without disassembly are very important for diesel engine safe operation. Currently, the research on fault diagnosis has focused on the time domain or frequency domain processing of vibration signals. However, early fault signals are mostly weak energy signals, and the fault information cannot be completely extracted by time domain and frequency domain analysis. Thus, in this article, a novel fault diagnosis method of diesel engine valve clearance using the improved variational mode decomposition (VMD) and bispectrum algorithm is proposed. First, the experimental study was designed to obtain fault vibration signals. The improved VMD method by choosing the optimal decomposition layers is applied to denoise vibration signals. Then the bispectrum analysis of the reconstructed signal after VMD decomposition is carried out. The results show that bispectrum image under different working conditions exhibits obviously different characteristics respectively. At last, the diagonal projection method proposed in this paper was used to process the bispectrum image, and the fourth order cumulant is calculated. The calculation results show that three states of the valve clearance are successfully distinguished.

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Section: Introductionmentioning

confidence: 99%

Diesel Engine Valve Clearance Fault Diagnosis Based on Improved Variational Mode Decomposition and Bispectrum

Cao

Zhang

2019

Energies

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“…The mother wavelet used by the transformation is the Morlet, and the critical contents are clearly highlighted by the CWT analysis. For the subsequent analysis, valve-close timing information is also indicated because, compared with exhaust valve opening (EVO) and inlet valve opening (IVO), the dominant response is still caused by the combined IVC and EVC [32]. At 360 °CA, the prominent response energy areas are in frequencies of 5, 6.48, 13.2, and 16 kHz.…”

Section: Engine Head Vibration Signal Analysismentioning

confidence: 99%

Vibration Characteristics of Compression Ignition Engines Fueled with Blended Petro-Diesel and Fischer-Tropsch Diesel Fuel from Coal Fuels

Yang

Wang

et al. 2018

Energies

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Fischer-Tropsch diesel fuel synthesized from coal (CFT) is an alternative fuel that gives excellent emission performance in compression ignition (CI) engines. In order to study the vibration characteristics, which are important for determining the applicability of the fuel, CFT-diesel blends were tested on a CI engine to acquire vibration signals from the engine head and block. Based on the FFT and continuous wavelet transformation (CWT) analysis, the influence of CFT on the vibration was studied. The results showed that the root mean square (RMS) values of the vibration signal decrease as the proportion of CFT in the blends increases. The CWT results indicated that the vibration energy areas motivated by the pressure shock of transient combustion were weak with increasing CFT proportion for the different frequency bands. The blend of 90% pure petro-diesel and 10% CFT registered the largest RMS value for piston side thrust response, and the RMS of high-frequency pressure oscillation response is greater than that of the main response of combustion, for FT30. Therefore, CFT has the potential to reduce the combustion vibration of the engine at all frequency bands, and there is a possibility that the proportion of blended fuel can be modified to satisfy the vibration characteristics requirements in different frequency bands.

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“…The use of an OBD scan tool may reveal which cylinder or cylinders are misfiring, but this information is of uncertain provenance and dubious value due to the use of proprietary classification schemes [13] [23]. Some direct-sensing alternatives to crankshaft position-based detection include sampling of the instantaneous exhaust gas pressure, measuring ionization current in the combustion chamber, or installing other sensors within [25] [4] or outside the combustion chamber [14] [24].…”

Section: Prior Artmentioning

confidence: 99%

Engine Misfire Detection with Pervasive Mobile Audio

Siegel

Kumar

Ehrenberg

2016

Machine Learning and Knowledge Discovery in Databases

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Abstract. We address the problem of detecting whether an engine is misfiring by using machine learning techniques on transformed audio data collected from a smartphone. We recorded audio samples in an uncontrolled environment and extracted Fourier, Wavelet and Mel-frequency Cepstrum features from normal and abnormal engines. We then implemented Fisher score and Relief score based variable ranking to obtain an informative reduced feature set for training/testing classification algorithms. Using this feature set, we were able to obtain a model accuracy of over 99% using a linear SVM on outsample data. This application of machine learning to vehicle subsystem monitoring simplifies traditional engine diagnostics, aiding vehicle owners in the maintenance process and opening up new avenues for pervasive mobile sensing and automotive diagnostics.

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Time-frequency analysis of single-point engine-block vibration measurements for multiple excitation-event identification

Cited by 83 publications

References 19 publications

Diesel Engine Valve Clearance Fault Diagnosis Based on Improved Variational Mode Decomposition and Bispectrum

Diesel Engine Valve Clearance Fault Diagnosis Based on Improved Variational Mode Decomposition and Bispectrum

Vibration Characteristics of Compression Ignition Engines Fueled with Blended Petro-Diesel and Fischer-Tropsch Diesel Fuel from Coal Fuels

Engine Misfire Detection with Pervasive Mobile Audio

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