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In the mechanical fault diagnosis and signal processing domain, there has been growing interest in sparse coding which is advocated as an effective mathematical description for the underlying principle of sensory systems in signal processing. In this paper, a natural extension of sparse coding, locality-constrained sparse coding, is introduced as a feature extraction technique for machinery fault...
Rolling bearing is a kind of very common mechanical components, of which the fault diagnosis is of great significance. In former fault diagnosis of bearings power spectrum is widely used. In this paper, a method consists of power spectrum analysis and support vector machine is proposed. Experimental results show that this method can be effectively applied in rolling bearing fault diagnosis.
Rotor-to-stator impact-rub of rotor is a kind of common fault of steam turbine. Traditional method of fault modeling, such as statistical theory and artificial neural network, usually gets a non-linear model because of the complexity of turbine system. Based on the need of analysis for impact-rub degree and fault trend, Support Vector Regression (SVR) arithmetic is imported and used for time series...
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