This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Fault Diagnosis of an Engine through Analyzing Vibration Signals at the Block
ISSN: 0148-7191, e-ISSN: 2688-3627
Published September 30, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Event: 11th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference
Unpredictable faults oriented from ambiguous reasons could occur in an engine of a vehicle. However, there are some symptoms from which an engine is working abnormally before the engine is stalled by faults. In this paper, methods for diagnosis of engine faults by using vibrations are proposed. Through bench tests, to extract features for fault diagnosis, various samples with normal and abnormal conditions are prepared and vibration signals from the block of an engine are measured and analyzed. To consider cost and performance of a sensor, vibrations from a knock sensor signal as well as accelerometers are analyzed. Measured vibration signals are synchronized with signal of the crank position sensor and analyzed to detect which event is involved. Modulation analysis and Hilbert transform are applied to extract features representing the symptoms of engine faults and to indicate when the abnormal event happens, respectively. As a result, the mean value of modulation indexes at modulated frequencies called as the half order modulation index (HOMI) is a factor determining if an engine is abnormal and envelope of the vibration signal is an indicator of the abnormal timing.
CitationJin, J., Jung, I., and Shin, S., "Fault Diagnosis of an Engine through Analyzing Vibration Signals at the Block," SAE Technical Paper 2020-01-1568, 2020, https://doi.org/10.4271/2020-01-1568.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
- Steffens, Ch., Eisele, G., Kauth, M., and Glusk, P. , “Impact of Automotive Megatrends on NVH,” in Aachen Acoustics Colloquium 2017.
- Chiavola, O., Chiatti, G., Arnone, L., and Manelli, S. , “Combustion Characterization in Diesel Engine via Block Vibration Analysis,” SAE Technical Paper 2010-01-0168, 2010, https://doi.org/10.4271/2010-01-0168.
- Jung, I., Jin, J., Lee, D., Lee, S. et al. , “Closed-Loop Control Method for Monitoring and Improving the Diesel Combustion Noise,” SAE Technical Paper 2016-01-1770, 2016, https://doi.org/10.4271/2016-01-1770.
- Lee, Y., Lee, S., Lee, S., Jin, J. et al. , “New Index for Diagnosis of Abnormal Combustion Using a Crankshaft Position Sensor in a Diesel Engine,” SAE Technical Paper 2019-01-0720, 2019, https://doi.org/10.4271/2019-01-0720.
- Saad, A., Ahmed, I., Watany, M., and Metwally, S. , “Diagnostic of Localized Engine Faults Using Vibration Monitoring,” SAE Technical Paper 2009-01-1610, 2009, https://doi.org/10.4271/2009-01-1610.
- Kirillov, S., Kirillov, A. Sr., and Kirillova, O. , “System of the Automatic Preventive On-line Monitoring and Diagnostics of Car Engines on the Basis of the New Methods of Preventive Diagnostics,” SAE Technical Paper 2011-01-0747, 2011, https://doi.org/10.4271/2019-01-0747.
- Bendat, J.S. and Piersol, A.G. , Random Data, Analysis and Measurement Procedure, Second Edition (Revised and Expanded) (John Wiley & Sons, 2007).
- Randall, R.B., Antoni, J. and Gryllias, K. , “Alternatives to Kurtosis as an Indicator of Rolling Element Bearing Faults,” in Monitoring and Diagnostics of Rotating Machinery, Proceedings of ISMA2016, Including USD, 2016.
- Pachaud, C., Salvetat, R., and Fray, C. , “Crest Factor and Kurtosis Contributions to Identify Defects Inducing Periodical Impulsive Force,” ASME Journal of Vibration and Acoustics 125:282-289, 2003.