Abstract
Fault detection of the rolling element bearing (REB) has been the subject of extensive research because of its detrimental influence on the reliability of machines. Vibration-based condition monitoring is one of the commonly used methods. In most cases, vibration signals are attenuated and contaminated resulting from background noise and complex structure. Independent component analysis (ICA) has been proved to be an effective method to separate bearing defect related feature from background noise. However, it is a prerequisite that the number of observations has to be larger than that of sources. The requirement cannot be satisfied in helicopter main gearbox (MGB) bearing condition monitoring because it is not possible to install more sensors than vibration sources considering the complexity of the MGB. Hence, this paper investigates the feasibility of using envelope extraction to reduce signal dimension. The experiment was conducted on a MGB operating under different load level and input speed. The results show that bearing defect related feature was observed by combing envelope extraction and the ICA method.
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Duan, F., Corsar, M., Zhou, L., Mba, D. (2019). Bearing Defect Detection Using Envelope Extraction for Dimension Reduction. In: Mathew, J., Lim, C., Ma, L., Sands, D., Cholette, M., Borghesani, P. (eds) Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-95711-1_14
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DOI: https://doi.org/10.1007/978-3-319-95711-1_14
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