ANALYSIS OF TIMING BELT VIBRATIONAL BEHAVIOR DURING A DURABILITY TEST USING ARTIFICIAL NEURAL NETWORK (ANN)

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KHAZAEE MEGHDAD; BANAKAR AHMAD; GHOBADIAN BARAT; MIRSALIM MOSTAFA; MINAEI SAEID; JAFARI SEYED MOHAMAD; SHARGHI PEYMAN

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Journal: Modares Mechanical Engineering Year:2016 | Volume:16 | Issue:3 Page(s): 311-318

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Title

ANALYSIS OF TIMING BELT VIBRATIONAL BEHAVIOR DURING A DURABILITY TEST USING ARTIFICIAL NEURAL NETWORK (ANN)

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Keywords

TIMING BELTQ2

REMAINING USEFUL LIFE (RUL)Q1

ACCELERATED DURABILITY TESTQ1

VIBRATION SIGNALQ1

ARTIFICIAL NEURAL NETWORKS (ANN)Q1

Abstract

In this research, an intelligent method is introduced for prediction of remaining useful life of an internal combustion engine TIMING BELT based on its vibrational signals. For this goal, an ACCELERATED DURABILITY TEST for TIMING BELT was designed and performed based on high temperature and high pre tension. Then, the durability test was began and VIBRATION SIGNALs of TIMING BELT were captures using a vibrational displacement meter laser device. Three feature functions, namely, Energy, Standard deviation and kurtosis were extracted from VIBRATION SIGNALs of TIMING BELT in healthy and faulty conditions and TIMING BELT failure threshold was determined. The Artificial Neural Network (ANN) was used for predicting and monitoring vibrational behavior of TIMING BELT. Finally, the ANN based on Energy, Standard deviation and kurtosis features of VIBRATION SIGNALs could predict TIMING BELT remaining useful life with accuracy of 98%, 98% and 97%, respectively. The correlation factor (R2) of vibration time series prediction by ANN and based on Energy, Standard deviation and kurtosis features of VIBRATION SIGNALs were determined as 0.87, 0.91 and 87, respectively. Also, Root Mean Square Error (RMSE) of ANN based on Energy, Standard deviation and kurtosis features of VIBRATION SIGNALs was calculated as 3.6%, 5.4% and 5.6%, respectively.

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APA: Copy

KHAZAEE, MEGHDAD, BANAKAR, AHMAD, GHOBADIAN, BARAT, MIRSALIM, MOSTAFA, MINAEI, SAEID, JAFARI, SEYED MOHAMAD, & SHARGHI, PEYMAN. (2016). ANALYSIS OF TIMING BELT VIBRATIONAL BEHAVIOR DURING A DURABILITY TEST USING ARTIFICIAL NEURAL NETWORK (ANN). MODARES MECHANICAL ENGINEERING, 16(3), 311-318. SID. https://sid.ir/paper/178499/en

Vancouver: Copy

KHAZAEE MEGHDAD, BANAKAR AHMAD, GHOBADIAN BARAT, MIRSALIM MOSTAFA, MINAEI SAEID, JAFARI SEYED MOHAMAD, SHARGHI PEYMAN. ANALYSIS OF TIMING BELT VIBRATIONAL BEHAVIOR DURING A DURABILITY TEST USING ARTIFICIAL NEURAL NETWORK (ANN). MODARES MECHANICAL ENGINEERING[Internet]. 2016;16(3):311-318. Available from: https://sid.ir/paper/178499/en

IEEE: Copy

MEGHDAD KHAZAEE, AHMAD BANAKAR, BARAT GHOBADIAN, MOSTAFA MIRSALIM, SAEID MINAEI, SEYED MOHAMAD JAFARI, and PEYMAN SHARGHI, “ANALYSIS OF TIMING BELT VIBRATIONAL BEHAVIOR DURING A DURABILITY TEST USING ARTIFICIAL NEURAL NETWORK (ANN),” MODARES MECHANICAL ENGINEERING, vol. 16, no. 3, pp. 311–318, 2016, [Online]. Available: https://sid.ir/paper/178499/en

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