Owing to continuous production lines with large amount of consecutive controls, various control signals and huge logistic relations, this paper introduced the methods and principles of the development of knowledge bas...Owing to continuous production lines with large amount of consecutive controls, various control signals and huge logistic relations, this paper introduced the methods and principles of the development of knowledge base in a fault diagnosis expert system that was based on machine learning by the four-layer perceptron neural network. An example was presented. By combining differential function with not differential function and back propagation of error with back propagation of expectation, the four-layer perceptron neural network was established. And it was good for solving such a bottleneck problem in knowledge acquisition in expert system and enhancing real-time on-line diagnosis. A method of synthetic back propagation was designed, which broke the limit to non-differentiable function in BP neural network.展开更多
In neutral point indirectly grounded systems, phase-to-ground fault is putting new demands on fault diagnosis technology. Information fusion is applied to detect the phase-to-ground fault, which integrates several sou...In neutral point indirectly grounded systems, phase-to-ground fault is putting new demands on fault diagnosis technology. Information fusion is applied to detect the phase-to-ground fault, which integrates several sources of information, including line current, line voltage, zero sequence current and voltage, and quintic harmonic wave component. This method is testified through the simulation of Matlab. Simulation results show that the precision and reliability of the detection has been greatly increased.展开更多
文摘Owing to continuous production lines with large amount of consecutive controls, various control signals and huge logistic relations, this paper introduced the methods and principles of the development of knowledge base in a fault diagnosis expert system that was based on machine learning by the four-layer perceptron neural network. An example was presented. By combining differential function with not differential function and back propagation of error with back propagation of expectation, the four-layer perceptron neural network was established. And it was good for solving such a bottleneck problem in knowledge acquisition in expert system and enhancing real-time on-line diagnosis. A method of synthetic back propagation was designed, which broke the limit to non-differentiable function in BP neural network.
文摘In neutral point indirectly grounded systems, phase-to-ground fault is putting new demands on fault diagnosis technology. Information fusion is applied to detect the phase-to-ground fault, which integrates several sources of information, including line current, line voltage, zero sequence current and voltage, and quintic harmonic wave component. This method is testified through the simulation of Matlab. Simulation results show that the precision and reliability of the detection has been greatly increased.
