Fault Detection of an Internal Combustion Engine through Vibration Analysis by Wavelets Transform

Gina P. Novillo, Nestor Diego Rivera Campoverde, Hector Adrian Auquilla Veintimilla, Cesar Daniel Beltrán Orellana


This paper presents a vibration analysis of an internal alternative combustion engine through frequency analysis and wavelet transform, where a form study of the temporary signal and the energy of that signal is carried out to extract certain  characteristic values that allow to differentiate and identify to which pre-established operating conditions, a specific vibration signal belongs. Software is used to make the data decomposition, analysis and value extraction. Different analysis results are presented on this investigation like frequency analysis, spectrogram analysis, wavelet analysis, cross wavelet analysis, and results validation by extracting values of the signals of two tests generating a variation chart showing runs variability if it is big o tiny variability. This analysis is performed to characterize the engine vibration signals so that it is possible to identify an incipient failure in a non-intrusive manner and optimize its maintenance. Also, it can be determined the repetitive form that describes a temporary signal of mechanical vibrations of a motor, if its work cycle it is considered to separate the temporary signal into sections, as long as there are no lower frequency components than the result of dividing the sampling frequency for the number of points that are in a work cycle (the limit frequency).


Faul detection; FFT; internal combustion engine; Spectrogram; Wavelets transform

Full Text:



Néstor Rivera, Juan Chica, Ivan Zambrano, and Cristian Garcıa. Estudio del comportamiento de un motor ciclo otto de inyeccion electronica respecto de la estequiometr´ıa de la mezcla y del adelanto al encendido para la ciudad de cuenca. Revista Polit´ecnica, 40(1):59–67, 2017.

L Hinke, L Pichler, HJ Pradlwarter, BR Mace, and TP Waters. Modelling of spa- tial variations in vibration analysis with application to an automotive windshield. Finite Elements in Analysis and Design, 47(1):55–62, 2011.

Yoshio Kurosawa, Hideki Enomoto, Shuji Matsumura, and Takao Yamaguchi. High frequency vibration analysis of automotive bodies with panels that have attached viscoelastic layers. In ASME 2003 International Mechanical Engineering Congress and Exposition, pages 23–29. American Society of Mechanical Engineers Digital Collection, 2003.

Seyed Hamed Mirafzal, Amir Mahyar Khorasani, and Amir Hossein Ghasemi. Op- timizing time delay feedback for active vibration control of a cantilever beam using a genetic algorithm. Journal of Vibration and Control, 22(19):4047–4061, 2016.

T Yamaguchi, Y Kurosawa, and H Enomoto. Damped vibration analysis using finite element method with approximated modal damping for automotive double walls with a porous material. Journal of Sound and Vibration, 325(1-2):436–450, 2009.

Sze-jung Wu, Nagi Gebraeel, Mark A Lawley, and Yuehwern Yih. A neural net- work integrated decision support system for condition-based optimal predictive maintenance policy. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 37(2):226–236, 2007.

Zhiqiang Huo, Yu Zhang, Pierre Francq, Lei Shu, and Jianfeng Huang. Incipient fault diagnosis of roller bearing using optimized wavelet transform based multi- speed vibration signatures. IEEE Access, 5:19442–19456, 2017.

Xinsheng Lou and Kenneth A Loparo. Bearing fault diagnosis based on wavelet transform and fuzzy inference. Mechanical systems and signal processing, 18(5):1077–1095, 2004.

Stefan Ericsson, Niklas Grip, Elin Johansson, Lars-Erik Persson, Ronny Sjoberg, and Jan-Olov Stromberg. Towards automatic detection of local bearing defects in rotating machines. Mechanical systems and signal processing, 19(3):509–535, 2005.

ZK Peng and FL Chu. Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography. Mechanical systems and signal processing, 18(2):199–221, 2004.

Daljeet Kaur Khanduja and MY Gokhale. Time domain signal analysis using modified haar and modified daubechies wavelet transform. Signal Processing-An International Journal (SPIJ), 4(3):161, 2010.

Dipalee Gupta and Siddhartha Choubey. Discrete wavelet transform for image processing. International Journal of Emerging Technology and Advanced Engineering, 4(3):598–602, 2015.

Shuilong He, Yikun Liu, Jinglong Chen, and Yanyang Zi. Wavelet transform basedon inner product for fault diagnosis of rotating machinery. In Structural Health Monitoring, pages 65–91. Springer, 2017.

Jinglong Chen, Zipeng Li, Jun Pan, Gaige Chen, Yanyang Zi, Jing Yuan, Binqiang Chen, and Zhengjia He. Wavelet transform based on inner product in fault diag- nosis of rotating machinery: A review. Mechanical systems and signal processing, 70:1–35, 2016.

Tomasz Figlus. 1592. the application of a continuous wavelet transform for diagnosing damage to the timing chain tensioner in a motorcycle engine. Journal of Vibroengineering, 17(3), 2015.

D Siano and D Dagostino. Knock detection in si engines by using the discrete wavelet transform of the engine block vibrational signals. Energy Procedia, 81:673–688, 2015.

Daniela Siano, Maria Antonietta Panza, and Danilo D’Agostino. Knock detection based on mapo analysis, ar model and discrete wavelet transform applied to the in-cylinder pressure data: results and comparison. SAE International Journal of Engines, 8(1):1–13, 2015.

Fengrong Bi, Lin Li, Jian Zhang, and Teng Ma. Source identification of gasoline engine noise based on continuous wavelet transform and eemd–robustica. Applied Acoustics, 100:34–42, 2015.

Jian-Da Wu and Jun-Ming Kuo. An automotive generator fault diagnosis system using discrete wavelet transform and artificial neural network. Expert Systems with Applications, 36(6):9776–9783, 2009.

Jian-Da Wu and Chiu-Hong Liu. An expert system for fault diagnosis in internal combustion engines using wavelet packet transform and neural network. Expert systems with applications, 36(3):4278–4286, 2009.

Jian-Da Wu and Jien-Chen Chen. Continuous wavelet transform technique for fault signal diagnosis of internal combustion engines. NDT & e International, 39(4):304–311, 2006.

Humberto Guti´errez Pulido, Roman De la Vara Salazar, Porfirio Guti´errez Gonzalez, Carlos T´ellez Mart´ınez, and Mar´ıa del Carmen Temblador P´erez. Analisis y diseno de experimentos. McGraw-Hill New York, NY, USA:, 2012.

Silvia Rocio Esparza Becerra. Analisis eficiente de camaras semianecoicas en alta frecuencia. 2012.

Mechanical Vibration. Evaluation of machine vibration by measurements on non- rotating parts–part 6, 1995.

DOI: http://dx.doi.org/10.18517/ijaseit.10.3.10810


  • There are currently no refbacks.

Published by INSIGHT - Indonesian Society for Knowledge and Human Development