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Advanced signal processing and fault diagnosis in condition monitoring

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Advanced signal processing methods combined with automatic fault detection enable reliable condition monitoring even when long periods of continuous operation are required. The parameters x(3) and x(4) are very suitable for the condition monitoring of slowly rotating bearings, as although the acceleration pulses are weak and occur at long intervals, the changes in acceleration are rapid and become emphasised upon differentiation of the signal x(2). Grounds for the need of x(-n) signals, ie integration of displacement n times with respect to time, have been indicated. In addition, derivatives where the order is a real number or a complex number + i have been developed. These signals can be utilised in process or machine operation by combining the features obtained from the derivatives. The importance of each derivative is defined by weight factors.

Dimensionless indices are obtained by comparing each feature value with the corresponding value in normal operation. These indices provide useful information on different faults, and even more sensitive solutions can be obtained by selecting suitable features. Widely used root-mean-square values are important in many applications, but the importance of the peak values increases in slowly rotating machines. Further details can be introduced by analysing the distributions of the signals. The features are generated directly from the higher order derivatives of the acceleration signals, and the model can be based on data or expertise. The intelligent models extend the idea of dimensionless indices to nonlinear systems. Variation with time can be handled as uncertainty by presenting the indices as time-varying fuzzy numbers. The classification limits can also be considered fuzzy. The reasoning system will produce degrees of membership for different cases. Practical long-term tests have been performed e.g. for fault diagnosis in bearings, cogwheels, gear boxes, electric motors and supporting rolls, and for cavitation in turbines and pumps.
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Keywords: Higher; fuzzy logic and condition monitoring; linguistic equations; real and complex order derivatives; vibration analysis

Document Type: Research Article

Affiliations: 1 Mechatronics and Machine Diagnostics Laboratory, Department of Mechanical Engineering, PO Box 4200, University of Oulu, FI-90014 Finland.

Publication date: December 1, 2007

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