EI检索:Stress Analysis of Sheet Metal Vibration Incremental Fo

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EI检索:Stress Analysis of Sheet Metal Vibration Incremental Forming
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云小枫 共回答了24个问题 | 采纳率87.5%
Accession number:x05x0520110213566162
x05Title:x05x05Stress analysis of sheet metal vibration incremental forming
x05Authors:x05x05Cai,Gaipin1 ; Zhu,Ningyuan1 ; Wen,Na1
x05Author affiliation:x05x05
1 x05Jiangxi University of Science and Technology,Ganzhou,Jiangxi 341000,China
x05Corresponding author:x05x05Cai,G.(cgp4821@yahoo.com.cn)
x05Source title:x05x05Advanced Materials Research
x05Abbreviated source title:x05x05Adv.Mater.Res.
x05Volume:x05x05154-155
x05Monograph title:x05x05Materials Processing Technologies
x05Issue date:x05x052011
x05Publication year:x05x052011
x05Pages:x05x05166-170
x05Language:x05x05English
x05ISSN:x05x0510226680
x05ISBN-13:x05x059780878492046
x05Document type:x05x05Conference article (CA)
1年前

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Detecting and extracting vibration disturb in IMU testing in field
Liu Gang; Yang Jie; Wang Lixin; Gao Jiang; Wang Xiaomei;
还有一篇:Modulation recognition of communication signal based on wavelet RBF neural network
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  第一篇:
  Accession number: 20104313316802
  Title: Detecting and extracting vibration disturb in IMU testing in field
  Authors: Gang, Liu1 ; Jie, Yang1 ; Lixin, Wang1 ; Jiang, Gao2 ; Xiaomei, Wang2
  Author affiliation: 1 Xi'an Hongqing Research Institute of Hi-Tech, Xi'an, Shaanxi Province, China
  2 PLA Sergeant College of the Second Artillery, Qinzhou, China
  Corresponding author: Gang, L. (yangjieflying@126.com)
  Source title: ICCET 2010 - 2010 International Conference on Computer Engineering and Technology, Proceedings
  Abbreviated source title: ICCET - Int. Conf. Comput. Eng. Technol., Proc.
  Volume: 2
  Monograph title: ICCET 2010 - 2010 International Conference on Computer Engineering and Technology, Proceedings
  Issue date: 2010
  Publication year: 2010
  Pages: V2516-V2518
  Article number: 5485585
  Language: English
  ISBN-13: 9781424463503
  Document type: Conference article (CA)
  Conference name: 2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010
  Conference date: April 16, 2010 - April 18, 2010
  Conference location: Chengdu, China
  Conference code: 81865
  Publisher: IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
  Abstract: IMU was often interrupted by the vibration of ground when it was calibrated in the field, the vibration disturb would cause great influence to the calibrated precision of IMU. This paper first established the mathematic model of vibration signal, then analyzed the output signal of IMU by using wavelet modulus maximum method, finally deduced a arithmetic to restrain the noise disturb and distill the vibration. Simulation shows that this arithmetic had very good detection ability. © 2010 IEEE.
  Number of references: 6
  Main heading: Vibration analysis
  Controlled terms: Calibration - Signal detection
  Uncontrolled terms: Detection ability - IMU calibration - In-field - Mathematic model - Modulus maxima - Output signal - Vibration disturb - Vibration signal - Wavelet - Wavelet modulus maxima
  Classification code: 716.1 Information Theory and Signal Processing - 941 Acoustical and Optical Measuring Instruments - 942 Electric and Electronic Measuring Instruments - 943 Mechanical and Miscellaneous Measuring Instruments - 943.2 Mechanical Variables Measurements - 944 Moisture, Pressure and Temperature, and Radiation Measuring Instruments
  DOI: 10.1109/ICCET.2010.5485585
  Database: Compendex
  Compilation and indexing terms, © 2010 Elsevier Inc.
  第二篇:
  Accession number: 20104313316796
  Title: Modulation recognition of communication signal based on wavelet RBF neural network
  Authors: He, Bing1 ; Liu, Gang1 ; Cun, Ge2 ; Jiang, Gao2
  Author affiliation: 1 Xi'an Hongqing Research Institute of Hi-Tech, Xi'an, Shaanxi Province, China
  2 Second Artillery Petty Officer School, QingZhou, Shandong Province, China
  Corresponding author: He, B. (hb830513@126.com)
  Source title: ICCET 2010 - 2010 International Conference on Computer Engineering and Technology, Proceedings
  Abbreviated source title: ICCET - Int. Conf. Comput. Eng. Technol., Proc.
  Volume: 2
  Monograph title: ICCET 2010 - 2010 International Conference on Computer Engineering and Technology, Proceedings
  Issue date: 2010
  Publication year: 2010
  Pages: V2490-V2492
  Article number: 5485567
  Language: English
  ISBN-13: 9781424463503
  Document type: Conference article (CA)
  Conference name: 2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010
  Conference date: April 16, 2010 - April 18, 2010
  Conference location: Chengdu, China
  Conference code: 81865
  Publisher: IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
  Abstract: Modulation recognition of communication signal is to confirm the modulation style of communication signal in the condition with much noise. Wavelet transformation has a good localization characteristic in time-frequency domain, while the neural network has characteristics of self-studying, self-adaptation, and high stabilization and can improve the autoimmunization and intelligence of recognition. We adopted the ideal of combination of wavelet and neural network in the paper, firstly, we used the wavelet to decompose the signal, and then abstracted the characteristic through the wavelet coefficient, lastly we adopted the RBF(Radial Basis Funtion) nerual network to recognize 4 kinds of common digital communication signal. The simulation results indicate that the presented method performs well. © 2010 IEEE.
  Number of references: 8
  Main heading: Neural networks
  Controlled terms: Amplitude modulation - Communication - Digital communication systems - Radial basis function networks - Signal processing - Wavelet transforms
  Uncontrolled terms: Communication signals - Digital communication signals - Modulation recognition - Radial basis - RBF Neural Network - Self adaptation - Simulation result - Time frequency domain - Wavelet coefficients - Wavelet transformations
  Classification code: 716 Telecommunication; Radar, Radio and Television - 716.1 Information Theory and Signal Processing - 723.4 Artificial Intelligence - 921.3 Mathematical Transformations
  DOI: 10.1109/ICCET.2010.5485567
  Database: Compendex
  Compilation and indexing terms, © 2010 Elsevier Inc.
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Contribution of river width derived from satellite images to retrieve river discharge through rainfall-runoff modeling
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Record 1 from Compendex for: ((Contribution of river width derived from satellite images to retrieve river discharge through rainfall-runoff modeling) WN TI), 1969-2011

Check record to add to Selected Records

1. Accession number: 20094612450084

Title: Contribution of river width derived from satellite images to retrieve river discharge through rainfall-runoff modeling

Authors: Sun, Wen-Chao1 ; Ishidaira, Hiroshi1 ; Bastola, Satish2

Author affiliation: 1 Dept. of Civil and Environmental Eng., Univ. of Yamanashi, 4-3-11, Takeda, Kofu, Yamanashi 400-8511, Japan

2 UMR-Hydrosciences, Univ. of Montpellier-II, 34095 Montpellier Cedex 5, France


Corresponding author: Sun, W.-C. (wsun.uy@gmail.com)

Source title: Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition)

Abbreviated source title: Sichuan Daxue Xuebao (Gongcheng Kexue Ban)

Volume: 41

Issue: SUPPL. 2

Issue date: September 2009

Publication year: 2009

Pages: 205-214

Language: English

ISSN: 10093087

CODEN: SXGKFI

Document type: Journal article (JA)

Publisher: Editorial Department of Journal of Sichuan University, 24 South Section, 1, Yihuan Rd., Chengdu, 610065, China

Abstract: Many satellites have been launched into space to collect information about the Earth's surface for decades. Water surface width of large rivers is one kind of hydraulic information that can be extracted from satellite images. In this study, an approach that contributes river width data derived from satellite images to retrieve river discharge in remote reaches of large river basins through rainfall-runoff modeling is proposed. By connecting rainfall-runoff model with hydraulic geometry, instead of in situ gauged discharge data, rainfall-runoff model is calibrated against remotely sensed river width. A case study is carried out by applying effective width of river water surface derived from Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) images to calibrate HYMOD rainfall-runoff model at Pakse gauging station in the Mekong River Basin. The results show an acceptable accuracy for discharge estimation. And uncertainties of the proposed method were also discussed through the case study.

Number of references: 19

Main heading: Hydraulic models

Controlled terms: Calibration - Computational geometry - Earth (planet) - Estimation - Image processing - Imaging systems - Rain - Remote sensing - Research - Rivers - Runoff - Satellites - Synthetic aperture radar - Synthetic apertures - Watersheds

Uncontrolled terms: Discharge estimation - Earth's surface - Effective width - Gauging stations - Hydraulic geometry - In-situ - Japanese earth resources satellites - Large rivers - Mekong River - Rainfall-runoff modeling - Rainfall-runoff models - River discharge - River discharge estimation - River water - Satellite images - Synthetic aperture radar images - Water surface

Classification code: 746 Imaging Techniques - 901.3 Engineering Research - 902.2 Codes and Standards - 921 Mathematics - 741 Light, Optics and Optical Devices - 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory - 942 Electric and Electronic Measuring Instruments - 943 Mechanical and Miscellaneous Measuring Instruments - 944 Moisture, Pressure and Temperature, and Radiation Measuring Instruments - 941 Acoustical and Optical Measuring Instruments - 731.1 Control Systems - 442.1 Flood Control - 443.3 Precipitation - 444.1 Surface Water - 632.1 Hydraulics - 407.2 Waterways - 655.2 Satellites - 716.2 Radar Systems and Equipment - 723.2 Data Processing and Image Processing - 723.5 Computer Applications - 657 Space Physics

Database: Compendex

Compilation and indexing terms, © 2011 Elsevier Inc.
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Author affiliation: 1 Information Technology Institute, Northwest University for Nationalities, Lanzhou, China

2 School of Computer Science and Information Engineering, Northwest University for Nationalities, Lanzhou, China


Corresponding author: Li, X. (hakuna__matata@126.com)

Source title: IASP 10 - 2010 International Conference on Image Analysis and Signal Processing

Abbreviated source title: IASP - Int. Conf. Image Analys. Signal Process.

Monograph title: IASP 10 - 2010 International Conference on Image Analysis and Signal Processing

Issue date: 2010

Publication year: 2010

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Article number: 5476104

Language: English

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Conference location: Xiamen, China

Conference code: 80893

Publisher: IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States

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Number of references: 8

Main heading: Color

Controlled terms: Image analysis - Image enhancement - Image retrieval - Mapping - Signal processing

Uncontrolled terms: Color space - Euclidean distance - Histogram method - Local accumulate histogram - Natural scenery

Classification code: 405.3 Surveying - 716.1 Information Theory and Signal Processing - 723.2 Data Processing and Image Processing - 741 Light, Optics and Optical Devices - 741.1 Light/Optics - 902.1 Engineering Graphics

DOI: 10.1109/IASP.2010.5476104

Database: Compendex

Compilation and indexing terms, © 2009 Elsevier Inc.
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Accession number: 20133516668765


Title: The application and research of fault detection based on PC-KNN in semiconductor batch process

Authors: Zhang, Cheng1; Li, Yuan1

Author affiliation: 1 Shen Yang University of Chemical Technology, Shen Yang 110142, China

Source title: 2013 25th Chinese Control and Decision Conference, CCDC 2013

Abbreviated source title: Chin. Control Decis. Conf., CCDC

Monograph title: 2013 25th Chinese Control and Decision Conference, CCDC 2013

Issue date: 2013

Publication year: 2013

Pages: 4209-4214

Article number: 6561690

Language: Chinese

ISBN-13: 9781467355322

Document type: Conference article (CA)

Conference name: 2013 25th Chinese Control and Decision Conference, CCDC 2013

Conference date: May 25, 2013 - May 27, 2013

Conference location: Guiyang, China

Conference code: 98686

Publisher: IEEE Computer Society, 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States

Abstract: In this paper, PC-KNN is studied on the condition that the data dimension is reduced by PCA. FD-KNN (Fault Detection based on K - Nearest - Neighbor) has been applied in semiconductor manufacturing Fault Detection, it can handle nonlinear and multi modal testing problems that influence the performance of PCA. The computational complexity and higher requirement of time and storage space have become the major factors which influence performance of FD-KNN. First, PCA is used to reduce the dimension of original data, then FD-KNN method is applied in principal space, it can effectively reduce the complexity of the calculation and the requirements of system resources process. Through the application in semiconductor batch production process, the results show the performance of PC-KNN dealing with nonlinear and multimodal, it demonstrate the effectiveness of the method proposed in this paper. © 2013 IEEE.

Number of references: 22

Main heading: Fault detection

Controlled terms: Batch data processing - Digital storage - Finite difference method - Modal analysis - Principal component analysis - Semiconductor device manufacture

Uncontrolled terms: Batch process - Batch production process - Data dimensions - K-nearest neighbors - Major factors - Semiconductor manufacturing - Storage spaces - System resources

Classification code: 922.2 Mathematical Statistics - 921.6 Numerical Methods - 921 Mathematics - 723.2 Data Processing and Image Processing - 722.1 Data Storage, Equipment and Techniques - 714.2 Semiconductor Devices and Integrated Circuits - 422 Strength of Building Materials; Test Equipment and Methods

DOI: 10.1109/CCDC.2013.6561690

Database: Compendex
Compilation and indexing terms, © 2013 Elsevier Inc
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