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Journal of Applied Sciences
  Year: 2012 | Volume: 12 | Issue: 18 | Page No.: 1960-1965
DOI: 10.3923/jas.2012.1960.1965
 
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Intelligent Fault Diagnosis via EMD Method
Ali Dorostghol and Masoud Dorfeshan

Abstract:
In the first stage of failure, the vibrations of gearboxes have a low range, which are often covered with stronger vibrations of the system. Thus, diagnosing the faults of the gears of the gearbox is difficult among the vibrations of other parts of the machine. In this regard, varied mathematical methods have been used, each having its own potentials and shortcomings. Fast Fourier Transforms (FFT) and Short-Time Fourier Transform (STFT) are two of these methods. However, due to the wide range of gearbox faults, distinguishing these faults is not possible via the aforementioned methods. So, with regard to the capability of empirical model decomposition EMD method in distinguishing faults, this study investigates the gearboxes vibration signals practically and in laboratory. First some intentional faults are applied on the experimental gearboxes. Then, the group of vibration signals of varied faults is collected and the data collected from the practical test are analyzed. Finally, a neural network was offered for an intelligent fault diagnosis of the gearbox. The findings verified the suggested methods (computing standard deviation and root-mean-square) not only are accurate enough but also have reduced the size of computations to a great extent.
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How to cite this article:

Ali Dorostghol and Masoud Dorfeshan, 2012. Intelligent Fault Diagnosis via EMD Method. Journal of Applied Sciences, 12: 1960-1965.

DOI: 10.3923/jas.2012.1960.1965

URL: https://scialert.net/abstract/?doi=jas.2012.1960.1965

 
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