Wavelet neural network aided on-line detection and diagnosis of rotating machine fault

2008 ◽  
Author(s):  
Liao Wei ◽  
Han Pu
Keyword(s):  
Neural Network ◽  
Wavelet Neural Network ◽  
Line Detection ◽  
Rotating Machine ◽  
On Line ◽  
Machine Fault ◽  
Detection And Diagnosis

A Method of Fault Detection and Diagnosis for Electromagnetic Direction Valve Based on Artificial Neural Network

2012 ◽  
Vol 476-478 ◽  
pp. 2384-2388
Author(s):  
Min Qiang Dai ◽  
Wei Cai ◽  
Sheng Dun Zhao
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fault Detection ◽  
Wavelet Packet ◽  
Vibration Signal ◽  
Fault Detection And Diagnosis ◽  
Line Detection ◽  
On Line ◽  
Artificial Neural ◽  
Detection And Diagnosis

The magnetic field and vibration signal of electromagnetic direction valve can be detected real-timely by a non-intrusive on line detection device, which can use to monitor working state of the valve. A method of fault detection and diagnosis for electromagnetic direction valve from the signal detected by the non-intrusive on line detection device is presented in this paper. The wave frequency bands energy analysis method is adopted to distinguish the electromagnetic direction valve’s state, and the vibration signal are decomposed by three-layer wavelet packet which wavelet basis is db10. The fault identification method is based on BP artificial neural network (ANN), which is the most well-known three-layers BP ANN whose input and output layers have 8 and 3 neurons respectively.

A Self-Constructing Wavelet Neural Network Controller to Mitigate the Subsynchronous Oscillations

2012 ◽  
Vol 135 (2) ◽  
Author(s):  
Mohsen Farahani ◽  
Soheil Ganjefar
Keyword(s):  
Neural Network ◽  
Power Systems ◽  
Adaptive Learning ◽  
Control Process ◽  
Wavelet Neural Network ◽  
Intelligent Control System ◽  
Intelligent Technique ◽  
Neural Network Controller ◽  
Learning Rates ◽  
On Line

This study proposes a new intelligent controller based on self-constructing wavelet neural network (SCWNN) to suppress the subsynchronous resonance (SSR) in power systems compensated by series capacitors. In power systems, the use of intelligent technique is inevitable, because of the uncertainties such as operating condition variations, different kinds of disturbances, etc. Accordingly, an intelligent control system that is an on-line trained SCWNN controller with adaptive learning rates is used to mitigate the SSR. The Lyapunov stability method is used to extract the adaptive learning rates. Hence, the convergence of the proposed controller can be guaranteed. At first, there is no wavelet in the structure of controller. They are automatically generated and begin to grow during the control process. In the whole design process, the identification of the controlled plant dynamic is not necessary according to the ability of the proposed controller. The effectiveness and robustness of the proposed controller are demonstrated by using the simulation results.

On-Line Handy Handwriting Chinese Characters Input for Non-Chinese Speakers Based on Wavelet Neural Network

2016 ◽  
Vol 30 (06) ◽  
pp. 1659017 ◽  
Author(s):  
Tongcheng Huang ◽  
Siyang Zhang ◽  
Xu Duan ◽  
Ronglong Liang
Keyword(s):  
Neural Network ◽  
Genetic Code ◽  
Wavelet Neural Network ◽  
Chinese Characters ◽  
Input Information ◽  
Chinese Speakers ◽  
On Line ◽  
Hidden Layer ◽  
Online Handwriting

Non-Chinese speakers hold increasing opportunities and need to process Chinese information and communicate in Chinese. This paper, with the purpose of facilitating the handwriting input of Chinese characters for non-Chinese speakers, is directed towards the development of the handwriting rules and vocabulary for Latin-style anti-cursive characters and the ways of their selection and classification. This aims to build a practical platform by utilizing three characteristics of wavelet neural network — automatically ascertaining the number of hidden layer unit, converging rapidly and never running into the partial minimum of networks — for a simple Latin-style online handwriting input and processing, meanwhile, taking the customary handwriting habits of non-Chinese speakers. The paper, based on profound information of cursive characters, deciphered the genetic code of ancient cursive symbols and made clear the rules for characters changing into its cursive style. As a result, it breaks the bottleneck, which enables non-Chinese speakers to easily input information through handwriting Chinese characters.

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