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An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 292-298 doi: 10.1007/s11465-006-0022-2

Abstract: To deal with pattern classification of complicated mechanical faults, an approach to multi-faults classificationKPCA is good at detection of machine abnormality while GDA performs well in multi-faults classificationbased on the collection of historical faults symptoms.When the proposed method is applied to air compressor condition classification and gear fault classification, an excellent performance in complicated multi-faults classification is presented.

Keywords： generalized discriminant     non-separable     abnormality     classification     multi-faults classification    

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A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0736-9

Abstract: Given the advantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studiedSecond, the localization for multi-source faults is seldom investigated, although locating the anomalyvariable over multivariate sensing data for certain types of faults is desirable.weaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensor

Keywords： fault recognition     fault localization     multi-sensor relations     network analysis     graph neural network    

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Urban landscape classification using Chinese advanced high-resolution satellite imagery and an object-orientedmulti-variable model

Li-gang MA,Jin-song DENG,Huai YANG,Yang HONG,Ke WANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 3,   Pages 238-248 doi: 10.1631/FITEE.1400083

Abstract: Its capability for comprehensive landscape classification, especially in urban areas, has been underand heterogeneity across urban environments, we attempt to test its performance of urban landscape classificationselected using forward stepwise linear discriminant analysis and applied in the following object-oriented classificationResults indicated an overall classification accuracy of 92.63% and a kappa statistic of 0.9124.presented method and the Chinese ZY-1 02C satellite imagery are robust and effective for urban landscape classification

Keywords： ZY-1 02C satellite     Classification     Urban     Multi-variable model    

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A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumerelectrical appliances classification

Chuan Choong YANG, Chit Siang SOH, Vooi Voon YAP

Frontiers in Energy 2019, Volume 13, Issue 2,   Pages 386-398 doi: 10.1007/s11708-017-0497-z

Abstract: The classification algorithm performs cropping and image pyramid reduction of the - trajectory plotsystematic approach of load disaggregation through - trajectory-based load signature images by utilizing a multi-stageclassification algorithm methodology.the number of closest data points to the nearest neighbor, in the -NN algorithm to be effective in classificationThe results of the multi-stage classification algorithm implementation have been discussed and the idea

Keywords： load disaggregation     voltage-current (V-I) trajectory     multi-stage classification algorithm    

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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning andunary classification

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 527-544 doi: 10.1007/s11708-023-0880-x

Abstract: Moreover, sensor data faults in power systems are dynamically changing and pose another challenge.exhaust gas temperatures (EGTs) of a real-world 9F gas turbine with sudden, progressive, and hybrid faultsresults show that the proposed method can achieve a relatively high recall for all kinds of typical faultsThe model can detect progressive faults very quickly and achieve improved results for comparison without

Keywords： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear    

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Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 2,   Pages 214-223 doi: 10.1007/s11709-021-0800-2

Abstract: The paper proposes a multi-level strategy, designed and implemented on the basis of periodic structural

Keywords： concrete structure     GPR     damage classification     convolutional neural network     transfer learning    

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Condition monitoring of a wind turbine generator using a standalone wind turbine emulator

Himani,Ratna DAHIYA

Frontiers in Energy 2016, Volume 10, Issue 3,   Pages 286-297 doi: 10.1007/s11708-016-0419-5

Abstract: open source technology from graze required for the condition monitoring to diagnose rotor and stator faultselectric subassemblies direct drive WTs are most susceptible to damage in practice, generator winding faults

Keywords： (WTE)     wind turbine generator (WTG)     maximum power point tracking (MPPT)     tip speed ratio (TSR)     rotor faults     stator faults    

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Development of a new method for RMR and Q classification method to optimize support system in tunneling

Asghar RAHMATI,Lohrasb FARAMARZI,Manouchehr SANEI

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 4,   Pages 448-455 doi: 10.1007/s11709-014-0262-x

Abstract: Rock mass classification system is very suitable for various engineering design and stability analysisclassification method is confirmed by Japan Highway Public Corporation that this method can figure outThese equations as a new method were able to optimize the support system for and classification systemsFrom classification and its application in these case studies, it is pointed out that the methodfor the design of support systems in underground working is more reliable than the and classification

Keywords： JH classification     Q and RMR classification     new method    

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A knowledge matching approach based on multi-classification radial basis function neural network for Research Articles

Shu-you Zhang, Ye Gu, Guo-dong Yi, Zi-li Wang,zsy@zju.edu.cn,me_guye@zju.edu.cn,ygd@zju.edu.cn,ziliwang@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900057

Abstract: In addition, we propose a multi-classification radial basis function neural network that can match the

Keywords： Product design     Knowledge push system     Augmented training set     Multi-classification neural network     Knowledge    

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Molecular classification and precision therapy of cancer: immune checkpoint inhibitors

Yingyan Yu

Frontiers of Medicine 2018, Volume 12, Issue 2,   Pages 229-235 doi: 10.1007/s11684-017-0581-0

Abstract: Taking gastric cancer as an example, its molecular classification is built on genome abnormalities, butSubsequently, by using their findings, oncologists will carry out targeted therapy based on molecular classification

Keywords： molecular classification     precision medicine     pembrolizumab     PD-1/PD-L1     MSI-H    

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A new and best approach for early detection of rotor and stator faults in induction motors coupled to

Abderrahim ALLAL,Boukhemis CHETATE

Frontiers in Energy 2016, Volume 10, Issue 2,   Pages 176-191 doi: 10.1007/s11708-015-0386-2

Abstract: proposed which was endowed with a dominant sensitivity in the case in which there would be rotor or stator faults

Keywords： induction motor     incipient broken bar     extended Park’s vector approach     spectral analysis     inter-turn short-circuit     Hilbert transform    

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Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration

Deepak PALIWAL,Achintya CHOUDHURY,T. GOVANDHAN

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 2,   Pages 130-141 doi: 10.1007/s11465-014-0298-6

Abstract:

Fault diagnosis of rolling element bearings requires efficient signal processing techniques. For this purpose, the performances of envelope detection with fast Fourier transform (FFT) and continuous wavelet transform (CWT) of vibration signals produced from a bearing with defects on inner race and rolling element, have been examined at low signal to noise ratio. Both simulated and experimental signals from identical bearings have been considered for the purpose of analysis. The bearings have been modeled as spring-mass-dashpot systems and the simulated signals have been obtained considering transfer functions for the bearing systems subjected to impulsive loads due to the defects. Frequency B spline wavelets have been applied for CWT and a discussion on wavelet selection has been presented for better effectiveness. Results show that use of CWT with the proposed wavelets overcomes the short coming of FFT while processing a noisy vibration signals for defect detection of bearings.

Keywords： Fault detection     spline wavelet     continuous wavelet transform     fast Fourier transform    

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EAI-oriented information classification code system in manufacturing enterprises

WANG Junbiao, DENG Hu, JIANG Jianjun, YANG Binghong, WANG Bailing

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 1,   Pages 81-85 doi: 10.1007/s11465-008-0011-8

Abstract: Although the traditional information classification coding system in manufacturing enterprises (MEs)integration (EAI) in manufacturing enterprises, an enterprise application integration oriented information classificationEAIO-ICCS expands the connotation of the information classification code system and assures the identity

Keywords： EAI     EAIO-ICCS     management     classification     connotation    

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A graph-based two-stage classification network for mobile screen defect inspection Research Article

Chaofan ZHOU, Meiqin LIU, Senlin ZHANG, Ping WEI, Badong CHEN

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 2,   Pages 203-216 doi: 10.1631/FITEE.2200524

Abstract: low contrast, tiny-sized, or incomplete defects, and (3) the modeling of category dependencies for multi-labelTo solve these problems, a graph reasoning module, stacked on a classification module, is proposed toTo further improve the classification performance, the classifier of the classification module is redesignedWith the help of contrastive learning, the classification module can better initialize the category-wise

Keywords： Graph-based methods     Multi-label classification     Mobile screen defects     Neural networks    

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Fault classification and reconfiguration of distribution systems using equivalent capacity margin method

K. Sathish KUMAR, T. JAYABARATHI

Frontiers in Energy 2012, Volume 6, Issue 4,   Pages 394-402 doi: 10.1007/s11708-012-0211-0

Abstract: This paper investigates the capability of support vector machines (SVM) for prediction of fault classificationHere, the SVM has been used as a classification.

Keywords： machines (SVM)     structural risk minimization (SRM)     equivalent capacity margin (ECM)     restoration     fault classification    

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Title Author Date Type Operation

An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

Journal Article

A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Journal Article

Urban landscape classification using Chinese advanced high-resolution satellite imagery and an object-orientedmulti-variable model

Li-gang MA,Jin-song DENG,Huai YANG,Yang HONG,Ke WANG

Journal Article

A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumerelectrical appliances classification

Chuan Choong YANG, Chit Siang SOH, Vooi Voon YAP

Journal Article

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning andunary classification

Journal Article

Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Journal Article

Condition monitoring of a wind turbine generator using a standalone wind turbine emulator

Himani,Ratna DAHIYA

Journal Article

Development of a new method for RMR and Q classification method to optimize support system in tunneling

Asghar RAHMATI,Lohrasb FARAMARZI,Manouchehr SANEI

Journal Article

A knowledge matching approach based on multi-classification radial basis function neural network for

Shu-you Zhang, Ye Gu, Guo-dong Yi, Zi-li Wang,zsy@zju.edu.cn,me_guye@zju.edu.cn,ygd@zju.edu.cn,ziliwang@zju.edu.cn

Journal Article

Molecular classification and precision therapy of cancer: immune checkpoint inhibitors

Yingyan Yu

Journal Article

A new and best approach for early detection of rotor and stator faults in induction motors coupled to

Abderrahim ALLAL,Boukhemis CHETATE

Journal Article

Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration

Deepak PALIWAL,Achintya CHOUDHURY,T. GOVANDHAN

Journal Article

EAI-oriented information classification code system in manufacturing enterprises

WANG Junbiao, DENG Hu, JIANG Jianjun, YANG Binghong, WANG Bailing

Journal Article

A graph-based two-stage classification network for mobile screen defect inspection

Chaofan ZHOU, Meiqin LIU, Senlin ZHANG, Ping WEI, Badong CHEN

Journal Article

Fault classification and reconfiguration of distribution systems using equivalent capacity margin method

K. Sathish KUMAR, T. JAYABARATHI

Journal Article