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Algorithm Design for Improving Feature Extraction Efficiency Based on KPCA

Xu Yong,Yangjingyu,Lu Jianfeng

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 38-42

Abstract: It can extract nonlinear feature components of samples.However, feature extraction for one sample requires that kernel functions between training samples andSo, the size of training sample set affects the efficiency of feature extraction.It is supposed that in feature space the eigenvectors may be linearly expressed by a part of trainingIKPCA extracts feature components of one sample efficiently, only based on kernel functions between nodes

Keywords： KPCA(Kernel PCA)     IKPCA(Improved KPCA)     feature extraction     feature space    

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Feature extraction from slice data for reverse engineering

ZHANG Yingjie, LU Shangning

Frontiers of Mechanical Engineering 2007, Volume 2, Issue 1,   Pages 25-31 doi: 10.1007/s11465-007-0004-z

Abstract: A new approach to feature extraction for slice data points is presented.

Keywords： feasibility     corresponding     B-spline     pre-determined tolerance     extraction    

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Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet

Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3,   Pages 406-419 doi: 10.1007/s11465-017-0419-0

Abstract: several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault featureAiming to extract the fault feature of planet gear effectively, we propose a novel feature extractioncollected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the featureextraction and fault diagnosis for the planet gear with a localized defect.

Keywords： wind turbine     planet gear fault     feature extraction     spectral kurtosis     time wavelet energy spectrum    

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Application of wavelet scalogram in feature extraction of acoustic emission signal

Xiao Siwen,Liao Chuanjun,Li Xuejun

Strategic Study of CAE 2008, Volume 10, Issue 11,   Pages 69-75

Abstract: By analyzing the characteristics and feature extraction of typical AE signals, the paper applies wavelet

Keywords： wavelets scalogram     acoustic emission     feature extraction     fault diagnosis     rolling bearing    

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A Face Recognition Based on Fusion Features Extraction From Two Kinds of Projection

Zhang Shengliang,Xu Yong,Yang Jian,Yang Jingyu

Strategic Study of CAE 2006, Volume 8, Issue 8,   Pages 50-55

Abstract: Then the fusion features in the complex feature space is extracted by using complex PCA (CPCA).

Keywords： feature fusion     linear discriminant analysis (LDA)     feature extraction     face recognition    

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signal analysis based on general parameterized time--frequency transform and its application in the featureextraction of a rotary machine

Peng ZHOU, Zhike PENG, Shiqian CHEN, Yang YANG, Wenming ZHANG

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2,   Pages 292-300 doi: 10.1007/s11465-017-0443-0

Abstract: pattern of the vibration signal from the rotary machine often contains condition information and fault featureA multi-component instantaneous frequency (IF) extraction method is proposed based on it.

Keywords： rotary machines     condition monitoring     fault diagnosis     GPTFT     SCI    

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Image quality assessmentmethod based on nonlinear feature extraction in kernel space Article

Yong DING,Nan LI,Yang ZHAO,Kai HUANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 10,   Pages 1008-1017 doi: 10.1631/FITEE.1500439

Abstract: one, a full-reference image quality assessment method is proposed based on high-dimensional nonlinear featureextraction.

Keywords： Image quality assessment     Full-reference method     Feature extraction     Kernel space     Support vector regression    

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Feature extraction of hyperspectral images for detecting immature green citrus fruit

Yongjun DING, Won Suk LEE, Minzan LI

Frontiers of Agricultural Science and Engineering 2018, Volume 5, Issue 4,   Pages 475-484 doi: 10.15302/J-FASE-2018241

Abstract:

At an early immature growth stage of citrus, a hyperspectral camera of 369–1042 nm was employed to acquire 30 hyperspectral images in order to detect immature green fruit within citrus trees under natural illumination conditions. First, successive projections algorithm (SPA) were implemented to select 677, 804, 563, 962, and 405 nm wavebands and to construct multispectral images from the original hyperspectral images for further processing. Then, histogram threshold segmentation using NDVI of 804 and 677 nm was implemented to remove image backgrounds. Three slope parameters, calculated from the pairs 405 and 563 nm, 563 and 677 nm, and 804 and 962 nm were used to construct a classifier to identify the potential citrus fruit. Then, a marker-controlled watershed segmentation based on wavelet transform was applied to obtain potential fruit areas. Finally, a green fruit detection model was constructed according to Grey Level Co-occurrence Matrix (GLCM) texture features of the independent areas. Three supervised classifiers, logistic regression, random forest and support vector machine (SVM) were developed using texture features. The detection accuracies were 79%, 75%, and 86% for the logistic regression, random forest, and SVM models, respectively. The developed algorithm showed a great potential for identifying immature green citrus for an early yield estimation.

Keywords： hyperspectral     green citrus     image processing     fruit detection     precision agriculture     yield mapping    

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Local uncorrelated local discriminant embedding for face recognition

Xiao-hu MA,Meng YANG,Zhao ZHANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 3,   Pages 212-223 doi: 10.1631/FITEE.1500255

Abstract: The feature extraction algorithm plays an important role in face recognition.In this paper, we introduce a novel feature extraction method called local uncorrelated local discriminantB, and FERET databases demonstrate that LULDE outperforms LDE and other representative uncorrelated featureextraction methods.

Keywords： Feature extraction     Local discriminant embedding     Local uncorrelated criterion     Face recognition    

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Intrinsic feature extraction using discriminant diffusion mapping analysis for automated tool wear evaluation None

Yi-xiang HUANG, Xiao LIU, Cheng-liang LIU, Yan-ming LI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 11,   Pages 1352-1361 doi: 10.1631/FITEE.1601512

Abstract: from both the time and frequency domains, by preserving the diffusion distances within the intrinsic featurecoupling the features to a discriminant kernel to refine the information from the high-dimensional featureThe proposed DDMA method consists of three main steps: (1) signal processing and feature extraction;(2) intrinsic dimensionality estimation; (3) feature fusion implementation through feature space mapping

Keywords： condition monitoring     Manifold learning     Dimensionality reduction     Diffusion mapping analysis     Intrinsic featureextraction    

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Basic research on machinery fault diagnostics: Past, present, and future trends

Xuefeng CHEN, Shibin WANG, Baijie QIAO, Qiang CHEN

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 2,   Pages 264-291 doi: 10.1007/s11465-018-0472-3

Abstract:

Machinery fault diagnosis has progressed over the past decades with the evolution of machineries in terms of complexity and scale. High-value machineries require condition monitoring and fault diagnosis to guarantee their designed functions and performance throughout their lifetime. Research on machinery Fault diagnostics has grown rapidly in recent years. This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics. The review discusses the special contributions of Chinese scholars to machinery fault diagnostics. On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in machinery fault diagnosis.

Keywords： fault diagnosis     fault mechanism     feature extraction     signal processing     intelligent diagnostics    

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Informatization of Mechanical Product —Some Information Techniques for Mechanical Equipment

Qu Liangsheng,Hu Zhaoyong

Strategic Study of CAE 2004, Volume 6, Issue 11,   Pages 20-28

Abstract: some achievements in authors' research practice, the paper mainly analyzes information fusion and featureextraction during the process of mechanical product informatization.

Keywords： informatization     mechanical engineering     information fusion     feature extraction    

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Entity and relation extraction with rule-guided dictionary as domain knowledge

Frontiers of Engineering Management   Pages 610-622 doi: 10.1007/s42524-022-0226-0

Abstract: Entity and relation extraction is an indispensable part of domain knowledge graph construction, whichThe existing entity and relation extraction methods that depend on pretrained models have shown promisingEntity extraction models treat characters as basic semantic units while ignoring known character dependencyRelation extraction is based on the hypothesis that the relations hidden in sentences are unified, therebyIn addition, the extraction accuracy of entity relation triplet reaches 83% and 76% on laser industry

Keywords： entity extraction     relation extraction     prior knowledge     domain rule    

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A Study on the Essence of Optimal Statistical Uncorrelated Discriminant Vectors

Wu Xiaojun,Yang Jingyu,Wang Shitong,Liu Tongming,Josef Kittler

Strategic Study of CAE 2004, Volume 6, Issue 2,   Pages 44-47

Abstract: The proposed method suits for all the problems of algebraic feature extraction.

Keywords： pattern recognition     feature extraction     disciminant analysis     generalized optimal set of discriminant    

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Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 829-839 doi: 10.1007/s11465-021-0652-4

Abstract: this problem, an imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph featureeffectively achieve rotating machinery fault diagnosis towards imbalanced training dataset through graph feature

Keywords： imbalanced fault diagnosis     graph feature learning     rotating machinery     autoencoder    

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Title Author Date Type Operation

Algorithm Design for Improving Feature Extraction Efficiency Based on KPCA

Xu Yong,Yangjingyu,Lu Jianfeng

Journal Article

Feature extraction from slice data for reverse engineering

ZHANG Yingjie, LU Shangning

Journal Article

Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet

Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU

Journal Article

Application of wavelet scalogram in feature extraction of acoustic emission signal

Xiao Siwen,Liao Chuanjun,Li Xuejun

Journal Article

A Face Recognition Based on Fusion Features Extraction From Two Kinds of Projection

Zhang Shengliang,Xu Yong,Yang Jian,Yang Jingyu

Journal Article

signal analysis based on general parameterized time--frequency transform and its application in the featureextraction of a rotary machine

Peng ZHOU, Zhike PENG, Shiqian CHEN, Yang YANG, Wenming ZHANG

Journal Article

Image quality assessmentmethod based on nonlinear feature extraction in kernel space

Yong DING,Nan LI,Yang ZHAO,Kai HUANG

Journal Article

Feature extraction of hyperspectral images for detecting immature green citrus fruit

Yongjun DING, Won Suk LEE, Minzan LI

Journal Article

Local uncorrelated local discriminant embedding for face recognition

Xiao-hu MA,Meng YANG,Zhao ZHANG

Journal Article

Intrinsic feature extraction using discriminant diffusion mapping analysis for automated tool wear evaluation

Yi-xiang HUANG, Xiao LIU, Cheng-liang LIU, Yan-ming LI

Journal Article

Basic research on machinery fault diagnostics: Past, present, and future trends

Xuefeng CHEN, Shibin WANG, Baijie QIAO, Qiang CHEN

Journal Article

Informatization of Mechanical Product —Some Information Techniques for Mechanical Equipment

Qu Liangsheng,Hu Zhaoyong

Journal Article

Entity and relation extraction with rule-guided dictionary as domain knowledge

Journal Article

A Study on the Essence of Optimal Statistical Uncorrelated Discriminant Vectors

Wu Xiaojun,Yang Jingyu,Wang Shitong,Liu Tongming,Josef Kittler

Journal Article

Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning

Journal Article