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| 1 | Fault Diagnosis Model Based on Feature Compression with Orthogonal Locality Preserving Projection显示文摘Based on feature compression with orthogonal locality preserving projection(OLPP),a novel fault diagnosis model is proposed in this paper to achieve automation and high-precision of fault diagnosis of rotating machinery.With this model,the original vibration signals of training and test samples are first decomposed through the empirical mode decomposition(EMD),and Shannon entropy is constructed to achieve high-dimensional eigenvectors.In order to replace the traditional feature extraction way which does the selection manually,OLPP is introduced to automatically compress the high-dimensional eigenvectors of training and test samples into the low-dimensional eigenvectors which have better discrimination.After that,the low-dimensional eigenvectors of training samples are input into Morlet wavelet support vector machine(MWSVM) and a trained MWSVM is obtained.Finally,the low-dimensional eigenvectors of test samples are input into the trained MWSVM to carry out fault diagnosis.To evaluate our proposed model,the experiment of fault diagnosis of deep groove ball bearings is made,and the experiment results indicate that the recognition accuracy rate of the proposed diagnosis model for outer race crack、inner race crack and ball crack is more than 90%.Compared to the existing approaches,the proposed diagnosis model combines the strengths of EMD in fault feature extraction,OLPP in feature compression and MWSVM in pattern recognition,and realizes the automation and high-precision of fault diagnosis. | TANG Baoping LI Feng QIN Yi | 2011 | Chinese Journal of Mechanical Engineering2011，24，5： | 14 |
| 2 | RESEARCH OF WAVELET TRANSFORM INSTRUMENT SYSTEM FOR SIGNAL ANALYSIS显示文摘After brief describing the Principle of wavelet transform (WT) of signals, a new signals analysis system based on wavelet transform is introduced. The design and development of the instryment of wavelet transform are described. A number of practical uses of this system demonstrate that wavelet transform system is specially functional in identifying and processing impulse, singular and non-smooth signals, so that it should be evaluated the most advanced signal analyzing system. | Qin Shuren Chen Zhikui Tang Baoping Yang Changqi Xu Mingtao He Hui (Test Center, Chongqing University) | 2000 | Chinese Journal of Mechanical Engineering2000，13，2： | 11 |
| 3 | SAMPLING PRINCIPLE AND TECHNOLOGY IN WAVELET ANALYSIS FOR SIGNALS显示文摘0INTRODUCTIONInrecenttenyears,waveletanalysiswithgoodlocalizationcharacteristicsindomain-timeanddomain-frequencyhasbeendevelo... | Qin, Shuren Chen, Zhikui Xu, Mingtao Tang, Baoping | 1998 | Chinese Journal of Mechanical Engineering1998，11，4： | 4 |
| 4 | Design of Onboard Instrument Based on Virtual Instrument Technology显示文摘After analyzing and comparing the traditional automobile instrument,the onboard instrument based on virtual instrument technology is designed in this paper.The PC/104 computer was employed as the core processing unit of the onbaard in- strument,and the several intelligent data acquisition nodes are set and connected by the CAN bus,through which the nodes can com- municate with the core processing unit.The information of the vehicle’s working condition can be displayed synthetically by adopt- ing virtual instrument technology.When the working condition goes beyond its limit,the system can emit an alarm,record and storage the abnormal condition automatically,and suggest how to deal with the abnormity urgently.The development background and design idea of onboard information system were elaborated in the paper.The software,the hardware architecture and the principle of onboard information system were introduced in detail. | TANG Baoping ZHONG Yuanchang QIU Jianwei (Department of Mechatronics,College of Mechanical Engineering,Chongqing University,Chongqing 400030,China | 2006 | 武汉理工大学学报2006，28，S2： | 2 |
| 5 | Spatial, seasonal and species variations of harmful algal blooms in the South Yellow Sea and East China Sea显示文摘 | Tang Dangling Di Baoping Wei Guifeng | 2006 | Hydrobiologia2006，568，： | 1 |
| 6 | Wind Tur- bine Fault Diagnosis Based on Morlet Wavelet Transformation and Wigner-ville Distribution显示文摘 | Tang Baoping Liu Wenyi Tao Song | 2010 | Renewable Energy2010，35，12： | 1 |
| 7 | Fault Di- agnosis Method Using Supervised Extended Local Tangent Space Alignment for Dimension Reduction 显示文摘 | Su Zuqiang Tang Baoping Deng Lei | 2015 | Measurement2015，62，： | 1 |
| 8 | Fault Diag- nosis for a Wind Turbine Transmission System Based on Manifold Learning and Shannon Wavelet Support Vector Machine显示文摘 | Tang Baoping Song Tao Li Feng | 2014 | Renewable Energy2014，62，3： | 1 |
| 9 | lntelligent Virtual controls--The Measuring Instrument from Whole to Part 显示文摘 | Shuren Qin Baoping Tang | 2002 | The Chinese journal of mechanical engineering2002，15，2： | 1 |
| 10 | Implementation of Intelligent Virtual Controls Based on Qin's Model 显示文摘 | Baoping Tang | 2002 | Proceedings of ISIST''2002 Jinan China:144-1502002，，： | 1 |
| 11 | Multi-fault diagnosis study on roller bearing based on multi-kernel support vector machine with chaotic particle swarm optimization显示文摘 | CHEN Fafa TANG Baoping SONG Tao | 2014 | Measurement2014，47，1： | 1 |
| 12 | Life grade recognition method based on supervised uneorrelated orthogonal locality preserving Projection and K-nearest neighbor classifier显示文摘 | Feng Li Jiaxu Wang Baoping Tang | 2014 | Neurocomputing2014，138，： | 1 |
| 13 | Fault diagnosis for a wind turbine transmission system based on manifold learning and Shannon wavelet support vector machine显示文摘 | Baoping Tang Tao Song Feng Li Lei Deng | 2014 | Renewable Energy2014，，： | 1 |
| 14 | An accurate 3- D fire location method based on sub-pixel edge detection and non-parametric stereo matching 显示文摘 | Song Tao Tang Baoping Zhao Minghang | 2014 | Measurement2014，50，： | 1 |
| 15 | Multi-fault diagnosis study on roller bearing based on multi-kernel support vector machine with chaotic particle swarm optimization显示文摘 | Chen Fafa Tang Baoping Song Tao | 2014 | Measurement2014，47，1： | 1 |
| 16 | Wind turbine fault diagnosis based on Morlet wavelet transformation and Wigner-Ville distribution 显示文摘 | TANG BAOPING LIU WENYI SONG TAO | 2010 | Renewable Energy2010，35，12： | 1 |
| 17 | Wind turbine fault diagnosis based on Morlet wavelet transformation and Wigner-Ville distribution显示文摘 | TANG BAOPING LIU WENYI TAO SONG | | 0，，12： | 1 |
| 18 | Bearing Running State recongnition Based on Non-extensive Wave- let Feature Scale Entropy and Support Vetor machine 显示文摘 | DONG Shaojiang TANG Baoping CHEN Renxing | 2013 | Measurement2013，46，10： | 1 |
| 19 | Fault di- agnosis for a wind turbine transmission system based on manifold learning and Shannon wavelet support vector machine显示文摘 | TANG Baoping SONG Tao LI Feng | 2014 | Renewable Energy2014，62，： | 1 |
| 20 | Spatial, seasonal and species variations of harmful algal blooms in the South Yellow Sea and East China Sea显示文摘 | TANG Danling DI Baoping WEI Guifeng | 2006 | Hydrobiologia2006，568，： | 1 |
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