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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...
In order to effectively solve the uncertainty small-samples fault diagnosis problem, a practical data-driven grey-based fault detection and diagnosis (FDD) method for complex equipments is investigated. Firstly, an improved fuzzy-grey relational analysis (FGRA) technique is proposed by introducing dynamic identification coefficient and fuzzy relational weight. Compared with the traditional Deng's...
The inconsistent diagnostic information often occurs in fault diagnosis of complex equipments. In order to improve the diagnosis precision, an integrated fault diagnosis method is proposed based on variable precision rough set (VPRS) and Naive Bayesian network classifier (NBNC). Firstly, according to the relative discernibility of the original fault diagnosis decision table, the β in VPRS is self-determined...
Rapid and accurate fault detection and diagnosis (FDD) is gaining importance for complex equipments because of the need to increase reliability and to decrease possible loss. In this paper, an intelligent fault diagnosis method is presented by using case-based reasoning (CBR) methodology to infer and classify various failures. Firstly, the case representation and the case base are established according...
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.
In view of the non-stationary features of vibration signals of gear and the difficulty to obtain a large number of fault samples in practice, a fault diagnosis scheme based on empirical mode decomposition (EMD) entropy of singular values and support vector machine is put forward in this paper. Firstly, original acceleration vibration signals are decomposed into a finite number of stationary intrinsic...
Trunking communication system is a sort of specialized command and control system. It is widely used in rescue work and public safety emergency. The peculiar occasion of its application requires more efficient fault diagnostic system. The rapid development of virtual instrument provides a new approach to the fault diagnosis of communication equipment. In this paper, the construction and the realization...
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...
Rough Bayesian network classifier (RBNC) not only has the ability of rough set (RS) for analyzing and reducing data, but also holds the advantage of Bayesian network (BN) for parallel reasoning, and it has been successfully used in fault diagnosis field. However, single RBNC sometimes will produce misdiagnosis because of many uncertainty factors in practical diagnostic process. In order to improve...
A new particle filter based fault diagnosis method for nonlinear stochastic system with non-Gaussian noise and disturbances is proposed by combining particle filter algorithm and fault diagnosis theory. One of the appealing advantages of the new approach is that the complete probability distribution information of the state estimates from particle filter is utilized for fault detection, another is...
Nowadays, the Built-in test (BIT) technique is adopted widely in aircraft fault diagnosis and maintenance. However, because of the complicated structure, mass data transmission, and especially propagations of coherent faults in aircraft, it is difficult to localize faults and to guarantee the accuracy and efficiency of BIT fault diagnosis. To reduce the high BIT false alarm rate (FAR), the coherent...
The fault detection of rotary rectifier based on harmonic analysis has some deficiencies. A new fault diagnosis method is presented using fractal theory and dynamics. Firstly, the quantitative description of exciter field currentpsilas complexity and irregularity is performed by box dimension calculation. Then the exciter field current fluctuation range under noisy environments is obtained by dynamics...
The fault diagnosis on large complex system is a difficult problem due to the complex structure of the system and the presence of high dimensional fault datasets. To solve this problem, integrating minimize entropy principle approach (META), rough sets theory and C4.5 algorithm, an entropy-based rough decision tree method is proposed to extract fault diagnosis rules. The diagnosis example of a 4153...
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