Ford Zetec-E, I4 Engine Timing Belt Drive

Thomanek, Ralf; Steinberg, Rainer; Krauser, Beate; Morawitz, Urban; Querengaesser, J.; Weiss, Johannes M.; Graf, Herbert

doi:10.4271/1999-01-0641

Cited by 7 publications

(5 citation statements)

References 1 publication

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“…Belt faults (C i ) (3,1) f (3,2) f (3,4) f (3,5) f ( signals from the timing belt, employed data-mining techniques, feature extraction, ANN, and the data fusion of DST of evidence. ANN inputs have been selected from signals in the time, frequency, and timefrequency domains and detected timing belt defects with accuracies of 71%, 78%, and 84%, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…1 Using the timing belt in IC engines brings about undeniable benefits including lower costs, lower noise levels, better performance at higher speeds, lower wear, and no need for lubricants. 2 In contrast, compared to chain counterparts, belt system has a much larger problem, which is lower reliability. In other words, the timing belts, in some cases, encounter failure or slipping in the middle of their service life leading to severe damages to engine and its components.…”

Section: Backward Knowledge and Necessity Of The Researchmentioning

confidence: 99%

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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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Section: Resultsmentioning

confidence: 99%

Section: Backward Knowledge and Necessity Of The Researchmentioning

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

“…where j is a counter. Comparing equations (2) and 3shows that, in WT, the scale parameter s and the translation parameter t are replaced by 2 j and 2 j k respectively. Equation 3acts as high-pass and low-pass filters on signals.…”

Section: Time-frequency-domain Signals: Discrete Wavelet Transformmentioning

confidence: 99%

“…The advantages of timing belts in comparison with other power transmission systems include a lower price, weight and noise, workability at higher speeds, no need for lubrication and a lower maintenance cost. 2 Because of the undeniable advantages of belts in comparison with chain wheel systems, timing belts are being commonly used to drive camshafts in cars. Today, timing belts are considered a sensitive and important piece of equipment in cars.…”

Section: Introductionmentioning

confidence: 99%

Detection of inappropriate working conditions for the timing belt in internal-combustion engines using vibration signals and data mining

Khazaee

Banakar

Ghobadian

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part D:

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Abnormal operating conditions for the timing belt can lead to cracks, fatigue, sudden rupture and damage to engines. In this study, an intelligent system was developed to detect and classify high-load operating conditions and high-temperature operating conditions for timing belts. To achieve this, vibration signals in normal operating conditions, high-load operating conditions and high-temperature operating conditions were collected. Time-domain signals were transformed to the frequency domain and the time–frequency domain using the fast Fourier transform method and the wavelet transform method respectively. In the data-mining stage, 25 statistical features were extracted from different signal domains. The improved distance evaluation method was adopted to select the best features and to reduce the input space for the classifier. Then, the signal features from the time domain, the frequency domain and the time-frequency domain were fed into an artificial neural network to evaluate the accuracy of this designed procedure for detecting inappropriate operating conditions for the timing belt. Based on all these features extracted from the signals in the time, frequency and time–frequency domains, the artificial neural network classifier detected and classified normal operating conditions, high-load operating conditions and high-temperature operating conditions with accuracies of 73.3%, 85% and 89.2% respectively. The classification accuracies using features selected by improved distance evaluation in the signals from the time, frequency and time–frequency domains were found to be 85%, 95.8% and 95% respectively. The results showed that the developed system was capable of detecting and classifying both the normal operating conditions and abnormal operating conditions for the timing belt. The results also suggested that a combination of signal processing and feature selection can significantly enhance the classification accuracy.

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“…Production VVT systems typically vary the relative camshaft position (cam phasing angle) [5][6][7][8][9] or using more than cam profile and select one among them [10,11] depending on engine operating conditions. These systems seek to reduce the impact of the traditional fixed valve timing compromise, which penalizes low volumetric efficiency versus high speed and low speed combustion stability.…”

Section: Introductionmentioning

confidence: 99%

Theoretical and Experimental Analysis of Electromagnetic Variable Valve Timing Control Systems for Improvement of Spark Ignition Engine Performance

A¹

2014

Adv Automob Eng

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The objective of this paper is to meet the requirements of higher torque values at all engine speeds. This can be achieved by varying the valve timing automatically using a new variable valve timing system (VVT), which gives continuously variable valve actuation at all engine speeds. A model engine is designed using dimensional analysis methods and then implemented to verify the proposed control system. Moreover, microcontroller and computeraided control systems are constructed and used to modify the variable valve timing control in the laboratory. In this paper, a mathematical model of variable valve timing is developed to obtain the best volumetric efficiency with optimum valve timing at different engine speeds. From this model, the look-up table is created at all ranges of the engine speed. A single cylinder engine is used to estimate engine performance characteristics for conventional camshaft. In addition, a model engine is designed and constructed to apply the Variable Valve Timing control system. The investigations show that the system is flexible throughout the entire range of operation speeds and is able to alter valve timing concerning both valve opening and closing. The ability of valve opening and closing can be realized with rates higher than these of the conventional timing mechanisms.

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Ford Zetec-E, I4 Engine Timing Belt Drive

Cited by 7 publications

References 1 publication

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

Detection of inappropriate working conditions for the timing belt in internal-combustion engines using vibration signals and data mining

Theoretical and Experimental Analysis of Electromagnetic Variable Valve Timing Control Systems for Improvement of Spark Ignition Engine Performance

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