Wind Generator State Recognition Based on Information Fusion Technology

2014 ◽  
Vol 953-954 ◽  
pp. 467-471
Author(s):  
Wen Zhi Yang ◽  
Hua Li ◽  
Ju Feng Cao ◽  
Zhi Bin Feng
Keyword(s):  
Information Fusion ◽  
Vibration Signal ◽  
Recognition System ◽  
Identification System ◽  
Fusion Technology ◽  
State Recognition ◽  
Vibration Data ◽  
Wind Generator ◽  
Data Extract ◽  
Set Up

This paper mainly researches on information fusion technology in the application of wind generator state recognition. Set up the model of information fusion based on bayesian theory, and develop status identification system by the platform of Labview. Conduct the test on Drivetrain Diagnosis Simulator (DDS), Simulate the normal and fault condition of wind generator main drive system by using normal and fault gear. Collect the vibration data, extract time domain feature parameters of the vibration signal, and train the identification system with these features. Verify the accuracy of the recognition system through the experiment.

FFT Analysis Using LabView as a Part of Vibration and Preventive Maintenance Class for Senior Level MET students

2005 ◽  
Author(s):  
Aniruddha Mitra ◽  
Sahana Sen
Keyword(s):  
Preventive Maintenance ◽  
Laboratory Experiments ◽  
Vibration Signal ◽  
Engineering Technology ◽  
Technology Program ◽  
Student Activities ◽  
Labview Software ◽  
Vibration Data ◽  
Set Up ◽  
Fft Analysis

An existing senior level elective course on vibration in Mechanical Engineering Technology program at Georgia Southern University has been modified significantly. Two major components have been added to this course. Those are theoretical topics on preventive maintenance and laboratory experiments. As a part of laboratory experiments, Fast Fourier Transform (FFT) was introduced as a possible tool for vibration analysis for the purposes of machine diagnosis. Utilizing the current laboratory set up for the data acquisition systems, LabView software has been used for FFT analysis of signals from various sources. Four different modules were developed and implemented. The modules are as follows: random variation in acceleration of a toy cart due to roughness of the track and pulley, regular uniform wave signal which is generated by the lateral vibration of a cantilever beam at its natural frequency, signal generated by the imported raw data from other sources (e.g. MATLAB) and vibration signal of a shaft mounted on ball bearings in order to detect the defects in the bearing. Each of these modules is illustrated in this paper with suitable examples and suggested student activities and involvements. The results from FFT analysis have been cross checked using other methods and observations. As a follow up, students have been taken to a local industry where significant amount of emphasis is given to preventive maintenance of machineries by vibration data analysis using FFT. Future possible projects include the analysis of vibration data gathered from actual machine shop. This project opens the scope for greater collaborative effort between local industries and classroom activities.

Research on Evaluation of Vehicle Dangerous Traveling State Based on Information Fusion Method

2013 ◽  
Vol 791-793 ◽  
pp. 1018-1022
Author(s):  
Peng Wang ◽  
Zhi Qiang Liu
Keyword(s):  
Information Fusion ◽  
Evaluation System ◽  
Evidence Theory ◽  
Recognition System ◽  
Fusion Method ◽  
Source Information ◽  
State Recognition ◽  
Research On Evaluation ◽  
Lane Departure ◽  
Level Information

An evaluation system of vehicle traveling state was proposed,and an unsafe vehicle traveling state recognition system was established using multi-level information fusion method. In view of the effects of the complexity of the driving environment, a variety of working conditions and the diversity of vehicle traveling characteristics, combing BP neural network with Dempster-Shafer evidence theory technique, the multi-information decision-level fusion was proposed to estimate the different kind model of the vehicle status. To verify the proposed strategies,the vehicle traveling posture evaluation system was established. The lane departure parameters and the relative distance parameters were studied in order to get the characterization of the vehicle traveling status information. The simulation results indicate that the adaptability and accuracy and the intelligence level of driving characterization estimation are significantly improved by using the pattern classification and decision technology of multi-source information fusion.

Application of Integrated Neural Network Information Fusion in Fault Diagnosis of one Missile Launching Control Unit

2013 ◽  
Vol 427-429 ◽  
pp. 2808-2812
Author(s):  
Xu De Cheng ◽  
Hong Li Wang ◽  
Bing Xu ◽  
Xue Dong Xue
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Information Fusion ◽  
Preliminary Analysis ◽  
Control Unit ◽  
Fusion Technology ◽  
Network Information ◽  
Diagnosis Rate ◽  
Fault Diagnosis System ◽  
Made In

Research and development of fault diagnosis system in application of integrated neural network information fusion is based on information fusion technology, with which preliminary analysis of equipment fault is made in different perspectives in terms of neural network, so as to identify the fault on the basis of fusion outcome. This technique is applied in fault diagnosis of one type of missile launching control unit, leading to sufficient use of various information and substantially increased fault diagnosis rate.

scholarly journals Vibration analysis based on the spectrum kurtosis for adjustment and monitoring of ball bearing radial clearance

2018 ◽  
Vol 211 ◽  
pp. 06006 ◽  
Author(s):  
Anthimos Georgiadis ◽  
Xiaoyun Gong ◽  
Nicolas Meier
Keyword(s):  
Signal Analysis ◽  
Vibration Signal ◽  
Radial Clearance ◽  
Spectral Kurtosis ◽  
Vibration Data ◽  
Bearing Clearance ◽  
Bearing Condition Monitoring ◽  
Bearing Vibration ◽  
Vibration Signal Analysis

Vibration signal analysis is a common tool to detect bearing condition. Effective methods of vibration signal analysis should extract useful information for bearing condition monitoring and fault diagnosis. Spectral kurtosis (SK) represents one valuable tool for these purposes. The aim of this paper is to study the relationship between bearing clearance and bearing vibration frequencies based on SK method. It also reveals the effect of the bearing clearance on the bearing vibration characteristic frequencies This enables adjustment of bearing clearance in situ, which could significantly affect the performance of the bearings. Furthermore, the application of the proposed method using SK on the measured data offers useful information for predicting bearing clearance change. Bearing vibration data recorded at various clearance settings on a floating and a fixed bearing mounted on a shaft are the basis of this study

Research of the Vertical Vibrations of Tandem Mill Based on Wavelet Analysis

2015 ◽  
Vol 724 ◽  
pp. 279-282
Author(s):  
Chun Hua Ren ◽  
Xu Ma ◽  
Ze Ming Li ◽  
Yan Hong Ding
Keyword(s):  
Wavelet Analysis ◽  
Wavelet Decomposition ◽  
Vibration Signal ◽  
Vertical Vibration ◽  
Rolling Speed ◽  
Vibration Data ◽  
Signal Features ◽  
Operating Side ◽  
Vertical Vibrations ◽  
Vibration Parameters

In this paper, the defect sheet was captured coincidentally. According to the defective product’s characteristics, we suspected to be caused by the vertical vibration of the roll. When the rolling speed reached a certain value, the vibration of the fourth stand can be feel. The experiment of the vibration data collection was taken to compare the vibration parameters of rolling operating side with those of drive side by wavelet analysis. The result states that the abnormal vibration signal features can be extracted in a special frequency segment of wavelet decomposition, and the vibration frequency to the roll is confirmed which appeared product defects.

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