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Bearing is a mechanical element of machine to reduce friction between two rotating objects. Bearings have an optimal lifetime but in real application, not all of them are able to reach their lifetime and most of them are damaged in a relatively short time. Any flaw on bearing that is not addressed earlier can lead to operation failure on mechanical equipment or machines. Usually type of bearing damage...
Condition monitoring and fault diagnosis of rolling element bearings (REBs) are at present very important to ensure the reliability of rotating machinery. This paper presents a new pattern classification approach for bearings diagnostics, which combines Mathematical Morphology (MM) and Multi-output Adaptive Neuro Fuzzy Inference System (M-ANFIS) classifier. MM is used for filtering Vibration signals,...
Vibration signals of rolling bearing contain deterministic components and random components, both of them reflect the failure information of bearing. For qualitative diagnosis of bearing faults using random components we need less vibration signal data that increases the computational efficiency for cyclostational analysis. In this paper we propose to use logarithmic contour maps of spectral correlation...
Bearing is an important part of electric machines. In order to avoid unscheduled outputs, it is important to detect an upcoming fault as soon as possible. Since fault in a great number of bearings commences from a single point defect, research on this category of faults has shared a great deal in predictive diagnosis literature. Single point defects will cause certain characteristic frequencies to...
This paper presents the study of permanent magnet synchronous machines (PMSM) running with eccentricity and bearings damage. The objective is to detect and identify the fault through the current signature analysis. The stator current has been analyzed by means of both Fourier (FFT) and Discrete Wavelet (DWT) transforms. Simulations have been carried out with a two-dimensional (2-D) finite element...
This paper presents a study of permanent magnet synchronous machines (PMSM) with bearing fault using a two-dimensional (2-D) finite element analysis (FEA). Fourier fast and wavelet transform were used to fault detection of bearing damage under stationary and non stationary working conditions. Simulation were carried out and compared with experimental results.
Since fault in a great number of bearings commences from a single point defect, research on this category of faults has shared a great deal in predictive diagnosis literature. Single point defects will cause certain characteristic fault frequencies to appear in machine vibration spectrum. In traditional methods, data extracted from frequency spectrum has been used to identify damaged bearing part...
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