Analytical Life Prediction Modelling of an Automotive Timing Belt

Hamilton, Andy; Fattah, Muhammad; Campean, Felician; Day, Andrew J.

doi:10.4271/2008-01-1207

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…The studied defects were selected according to the common and valid theories about timing belt defects. 45 Figure 4 shows different timing belts with the aforementioned defects.…”

Section: Timing Belt Faultsmentioning

confidence: 99%

Fault detection of engine timing belt based on vibration signals using data-mining techniques and a novel data fusion procedure

Khazaee

Banakar

Ghobadian

et al. 2016

Structural Health Monitoring

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In this research, an intelligent procedure was designed and implemented based on vibration signals for detecting and classifying prevalent faults of an internal combustion engine timing belt. The vibration signals of the timing belt were captured during operation in six different states: healthy, tooth crack, back crack, wear, separated tooth, and oil pollution. These signals were processed at three domains, namely, time, frequency, and time-frequency domains. Time-domain signals were transformed into the frequency and time-frequency domains using fast Fourier transform and wavelet transform, respectively. Then, six statistical features were extracted from vibration signals at all three domains. The extracted features were used as inputs to an artificial neural network for the primary classification of timing belt defects. Classification accuracy of artificial neural network in detecting and classifying timing belt faults in the time, frequency, and time-frequency domains have obtained 71%, 78%, and 84%, respectively. Combining separate classification accuracies from time, frequency, and time-frequency domains has been implemented using Dempster-Shafer theory of evidence. Classification accuracy based on the fusion of time-and frequency-domain classifiers was 97%, from time and timefrequency results was 98%, and from frequency and time-frequency results was also 98%, whereas the combination of results for all domains led to a .99% accuracy. Results show that the proposed methodology can detect and classify timing belt defects with high precision and reliability before failure occurrence.

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“…The studied defects were selected according to the common and valid theories about timing belt defects. 45 Figure 4 shows different timing belts with the aforementioned defects.…”

Section: Timing Belt Faultsmentioning

confidence: 99%

Fault detection of engine timing belt based on vibration signals using data-mining techniques and a novel data fusion procedure

Khazaee

Banakar

Ghobadian

et al. 2016

Structural Health Monitoring

View full text Add to dashboard Cite

show abstract

“…Long et al [11] analyzed the dynamic performance of the timing belt and presented the influence of the tensioner design and belt pre-tension on the dynamic belt tension. Domek et al [12] modeled the wear of the timing belt pulley, while Hamilton et al [13] presented the combination of the computer-based analytical simulation methods coupled with statistical tools to predict Energies 2021, 14, 317 2 of 15 the timing belt life. Merghache and Ghernaout [14] focused on studying the heat transfer through the belt transmissions concerning different rotational speeds, engine torque, and setting tension.…”

Section: Introductionmentioning

confidence: 99%

Determining the Power Consumption of the Automatic Device for Belt Perforation Based on the Dynamic Model

et al. 2021

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The subject of the dynamic analysis presented in the article is the linear drive system with a timing belt utilized in the automatic device for polymer composite belt perforation. The analysis was carried out in two stages. In the first stage, the timing belt was modeled with all the relevant dynamic phenomena; subsequently, the tension force of the belt required for the correct operation of the belt transmission was determined. The necessary parameters for belt elasticity, vibration damping, and inertia are based exclusively on the catalog data provided by the manufacturer. During the second stage, equations of motion were derived for the designed drive system with a timing belt, and characteristics were identified to facilitate the optimal selection of electromechanical drives for the construction solution under analysis. The presented methodology allows for designing an effective solution that may be adapted for other constructions. The obtained results showed the influence of the kinematic parameters on the motor torque and proved the importance of reducing the mass of the components in machines that perform high-speed processes.

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Application of TRIZ to Develop an In-service Diagnostic System for a Synchronous Belt Transmission for Automotive Application

2013

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Analytical Life Prediction Modelling of an Automotive Timing Belt

Cited by 4 publications

References 18 publications

Fault detection of engine timing belt based on vibration signals using data-mining techniques and a novel data fusion procedure

Fault detection of engine timing belt based on vibration signals using data-mining techniques and a novel data fusion procedure

Determining the Power Consumption of the Automatic Device for Belt Perforation Based on the Dynamic Model

Application of TRIZ to Develop an In-service Diagnostic System for a Synchronous Belt Transmission for Automotive Application

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