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Fault diagnosis using a probability least squares support vector classification machine

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Mining Science and Technology 2010年第6期20卷 917-921页

作者： GAO Yang, WANG Xuesong, CHENG Yuhu, PAN Jie School of Information and electrical engineering, China University of Mining & Technology, Xuzhou 221116, China School of Information and electrical engineering China University of Mining & Technology Xuzhou 221116 China

Coal mines require various kinds of machinery. The fault diagnosis of this equipment has a great impact on mine production. The problem of incorrect classification of noisy data by traditional support vector machines is addressed by a proposed Probability Least Squares Support Vector Classification Machine (PLSSVCM). Samples that cannot be definitely determined as belonging to one class will be assigned to a class by the PLSSVCM based on a probability value. This gives the classification results both a qualitative explanation and a quantitative evaluation. Simulation results of a fault diagnosis show that the correct rate of the PLSSVCM is 100%. Even though samples are noisy, the PLSSVCM still can effectively realize multi-class fault diagnosis of a roller bearing. The generalization property of the PLSSVCM is better than that of a neural network and a LSSVCM.

关键词： fault diagnosis probability least squares support vector classification machine roller bearing

Concurrent collision probability of RFID tags in underground mine personnel position systems

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Mining Science and Technology 2010年第5期20卷 734-737页

作者： JI Yuchu,XU Zhao,FENG Qinzhu,SANG Yuan School of Information & electrical engineering,China University of Mining & Technology,Xuzhou 221008,China School of Information&electrical engineering China University of Mining&Technology Xuzhou 221008 China

According to the basic requirements of underground mine personnel position systems and the working characteristics of active RFID tags,we studied the cause of concurrent collision of RFID tags and leak reading probability,by means of theoretical analysis and *** result shows that the probability of wireless collision increases linearly with an increase in the number of *** probability of collision and leak reading can be reduced by extending the working period of the duty cycle and using a backoff *** a practical application,a working schedule for available labels has been designed according to the requirement of the project.

关键词： personnel position system RFID collision probability of RFID tag

Practical Issues Concerning Moment Invariants

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Journal of Systems engineering and Electronics 1996年第1期7卷 43-57页

作者： Xiaojian Xu & A.G. Constantinides (Beijing Institute of Environment Features)(Depatment of electrical and Electronic engineering Imperial College of Science,Technology and Medicine) Beijing Institute of Environment Features Department of electrical and Electronic engineering Imperial College of Science Technology and Medicine

In this report several practical issues about moment invariants with application to image classification are concerned. A modified formulation for the approximation of the moments of digital images is suggested. Four ... 详细信息

关键词： Pattern recognition Image processing,Momeent invariant,Fuzzy logic.

Gear Fault Diagnosis Based on Rough Set and Support Vector Machine

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武汉理工大学学报 2006年第S3期28卷 1046-1051页

作者： TIAN Huifang SUN Shanxia School of mech.nical and electrical engineering,Wuhan University of Technology,Wuhan 430070,China, School of mech.nical and electrical engineering Wuhan University of TechnologyWuhan 430070China

By introducing Rough Set Theory and the principle of Support vector machine,a gear fault diagnosis method based on them is ***,diagnostic decision-making is reduced based on rough set theory,and the noise and redundancy in the sample are removed,then,according to the chosen reduction,a support vector machine multi-classifier is designed for gear fault ***,SVM’training data can be reduced and running speed can *** shows its accuracy and effi- ciency of gear fault diagnosis.

关键词： rough set support vector machine fault diagnosis multi-classifier

Gene association study with SVM,MLP and cross-validation for the diagnosis of diseases

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Progress in Natural Science:Materials International 2008年第6期18卷 741-750页

作者： Junying Zhanga,*,Shenling Liu a,Yue Wang b aSchool of Computer Science and engineering,Xidian University,161 Postbox,Xi’an 710071,China bDepartment of electrical and Computer engineering,Virginia Polytechnic Institute and State University,Alexandria,VA 22314,USA School of Computer Science and engineering Xidian University 161 Postbox Xi’an 710071 China Department of electrical and Computer engineering Virginia Polytechnic Institute and State University Alexandria VA 22314 USA

Gene association study is one of the major challenges of biochip technology both for gene diagnosis where only a gene subset is responsible for some diseases,and for the treatment of the curse of dimensionality which occurs especially in DNA microarray datasets where there are more than thousands of genes and only a few number of experiments(samples).This paper presents a gene selection method by training linear support vector machine(SVM)/nonlinear MLP(multilayer perceptron)classifiers and testing them with cross-validation for finding a gene subset which is optimal/suboptimal for the diagnosis of binary/multiple disease *** are selected with linear SVM classifier for the diagnosis of each binary disease types pair and tested by leave-one-out cross-validation;then,genes in the gene subset initialized by the union of them are deleted one by one by removing the gene which brings the greatest decrease of the generalization power,for samples,on the gene subset after removal,where generalization is measured by training MLPs with leave-one-out and leave-four-out *** proposed method was tested with experiments on real DNA microarray MIT data and NCI *** result shows that it outperforms conventional SNR method in the separability of the data with expression levels on selected *** real DNA microarray MIT/NCI data,which is composed of 7129/2308 eective genes with only 72/64 labeled sam-ples belonging to 2/4 disease classes,only 11/6 genes are selected to be diagnostic *** selected genes are tested by the classification of samples on these genes with SVM/MLP with leave-one-out/both leave-one-out and leave-four-out *** result of no misclassification indicates that the selected genes can be really considered as diagnostic genes for the diagnosis of the corresponding diseases.

关键词： DNA microarray data Curse of dimensionality Gene selection Diagnostic genes SVM MLP Cross-validation

Aging assessment of large generator insulation based on PD measurements

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Progress in Natural Science:Materials International 2005年第11期15卷 1035-1043页

作者： YUE Bo, CHEN Xiaolin, CHENG Yonghong and XIE Hengkun (State Key Laboratory of electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710049, China Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China Department of electrical engineering, Tsinghua University, Beijing 100084, China) State Key Laboratory of electrical Insulation and Power Equipment Xi'an Jiaotong University Xi'an 710049 China Graduate School at Shenzhen Tsinghua University Shenzhen 518055 China Department of electrical engineering Tsinghua University Beijing 100084 China

The statistical parameters of phase resolved partial discharge (PD) distribution and ultra-wideband (UWB) characteristics of PD pulse are proposed for aging assessment of large generator insulation. Multi-stress aging tests of the model generator stator bar specimens were performed and PD measurements were conducted using both digital PD detector with frequency ranging from 40 kHz to 400 kHz and UWB PD detector with bandwidth from 10 MHz to 3 GHz at different aging stages. The test results show that the skewness and UWB frequency characteristics of PD can be taken as the characterization parameters for aging assessment of generator insulation. Furthermore, the measurement results of real generator stator bars show that these methods based on statistical parameters and UWB characteristics of PD are prospective for aging assessment and residual lifetime estimation of large generator stator insulation.

关键词： partial discharge stator insulation multi-stress accelerated aging statistical parameters ultra-wideband aging assessment.

A Cumulative Damage Reliability Model on the Basis of Contact Fatigue of the Rolling Bearing

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武汉理工大学学报 2006年第S1期28卷 367-370页

作者： HUANG Li (School of mech.nical&electrical engineering,Wuhan University of Technology,Wuhan 430070,China) School of mech.nical&electrical engineering Wuhan University of TechnologyWuhan 430070China

A cumulative damage reliability model of contact fatigue of the rolling bearing is more identical with the actual conditions. It is put forward on the basis of contact fatigue life probability distribution of the rolling bearing that obey Weibull distribution and rest on the Miner cumulative damage theory. Finally a case is given to predict the reliability of bearing roller by using these models.

关键词： rolling bearing reliability model cumulative damage contact fatigue

Dye Laser-pumped Cr: LiSrAIF6 Laser

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Chinese Journal of Lasers 1995年第2期 97-100页

作者： WU Xing(Dept. of Precision Instrument engineering,Tianjin 300072, China)T. Okada, K. Kaeda(Dept. of electrical engineering, Kgushu, Japan)

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关键词： Cr: LiSrAIF6 laser dye laser pumping

A Modified T-test Feature Selection Method and Its Application on the HapMap Genotype Data

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Genomics,Proteomics & Bioinformatics 2007年第Z1期 242-249页

作者： Nina Zhou and Lipo Wang School of electrical and Electronic engineering,Nanyang Technological University,Singapore.

Single nucleotide polymorphisms (SNPs) are genetic variations that determine the differences between any two unrelated individuals. Various population groups can be distinguished from each other using SNPs. For instance,the HapMap dataset has four population groups with about ten million SNPs. For more insights on human evolution,ethnic variation,and population assignment,we propose to find out which SNPs are significant in determining the population groups and then to classify different populations using these relevant SNPs as input features. In this study,we developed a modified t-test ranking measure and applied it to the HapMap genotype data. Firstly,we rank all SNPs in comparison with other feature importance measures including F-statistics and the informativeness for assignment. Secondly,we select different numbers of the most highly ranked SNPs as the input to a classifier,such as the support vector machine,so as to find the best feature subset corresponding to the best classification accuracy. Experimental results showed that the proposed method is very effective in finding SNPs that are significant in determining the population groups,with reduced computational burden and better classification accuracy.

关键词： SNP modified t-test F-statistics SVM