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The basic principle of Artificial Neural Networks and BP algorithm was introduced in this paper. The application of BP algorithm Artificial Neural Networks in fault diagnosis of 40TM liquid-gas hammer was studied. The superiority of BP algorithm Artificial Neural Networks in fault diagnosis was proved by the MATLAB simulation and the training. The causes of faults were determined by BP algorithm Artificial...
This paper introduces a method for the fault diagnosis of a rotor system. For a vibration signal of a rotor system fault, an AR model is established first, and then the related parameter and amplitude spectrum of this mode can be obtained, etc. The experiments show the above-mentioned method can effectively diagnose the fault of a rotor system.
The application of neural networks to power systems has been extensively reported. Neural networks based protection techniques have been proposed by a number of authors. However, almost all the studies have so far employed the back-propagation neural network structure with supervised learning. This paper presents an on line method for fault identification in Electrical High Voltage (EHV) transmission...
Research on thruster fault diagnosis of Underwater Robots (URs) is undertaken to improve its whole system reliability. Based on the BP neural network, a recurrent neural network (RNN) is presented and the network training algorithm is deduced. The RNN is trained by voyage head and yaw turning experiments, and the well trained network is applied to model for the URs. Compared the outputs between model...
A fault diagnosis method of rolling bearing based on BP neural network and time domain parameters of vibration signal was proposed to realize fast fault diagnosis. The input vectors of the BP neural network were skewness, kurtosis, peak and margin of vibration signal. The structure of the neural network was determined with simulation research. Gradient descending method was used to train the parameters...
This paper presents applications of A.I. in turbine engines fault diagnosis and health management. Self-organizing map and back-propagation neural networks supported with fuzzy-logic decision-making tool were developed and integrated together as diagnostics software for turbine engines. Two different neural network architectures were trained and used. An unsupervised network (SOM) was used to cluster...
Taking FOG SINS (fiber-optic gyroscope strapdown inertial system) as an object, a new fault diagnostic scheme based on BP (back-propagation) neural network is proposed. Being capable of training and simulating data off-line, neural networks provide a solution to overcome some drawbacks of the quantitative fault diagnosis. The fault tree of FOG SINS is analyzed, which is the basis of the study of neural...
In the paper, the mapping relation between static characteristics of electro-hydraulic servo valve and fault pattern is analyzed. The method of multi-parameter fault pattern recognition of electro-hydraulic servo valve based on BP neural networks is introduced, which is researched based on tests. The result shows that the accuracy rate of fault pattern recognition is higher by adopting this method...
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