Specifications

feedforward process neural network, establishes a mapping of dynamic feature vectors into fault
type, and finally realizes intelligent fault diagnosis. Application to a practical example shows that
the method converges faster and its forecast accuracy is higher than that of traditional RBF or BP
neural network. The method produces a small average classification error and hence it is suitable
for vortex fusion fault diagnosis of draft tube. © copyright.
Number of references: 11
Main heading: Hydraulic turbines
Controlled terms: Neural networks - Signal processing - Tubes (components) -
Vortex flow
Uncontrolled terms: Draft tubes - Fusion diagnosis - Hydroturbines - Index
energy - Process neural network - Vertex strip
Classification code: 616.1 Heat Exchange Equipment and Components - 617.1 Hydraulic
Turbines - 631.1 Fluid Flow, General - 716.1 Information Theory and Signal Processing -
723.4 Artificial Intelligence
Database: Compendex
Compilation and indexing terms, © 2013 Elsevier Inc.
10.
Accession number: 20130415923574
Title: Calibration-free and model-independent method for high-DOF image-based visual
servoing
Authors: Zhang, Jie1 ; Liu, Ding1/;刘丁
Author affiliation:
1 School of Automation and Information Engineering, Xi'an University of Technology, Xi'an
Shaanxi, 710048, China
Corresponding author: Zhang, J. ([e-mail])
Source title: Journal of Control Theory and Applications
Abbreviated source title: J. Control Theory Appl.
Volume: 11
Issue: 1
Issue date: 2013
Publication year: 2013
Pages: 132-140
Language: English
ISSN: 16726340
E-ISSN: 10008152
Document type: Journal article (JA)
Publisher: South China University of Technology, Guangzhou, 510640, China
Abstract: This paper presents a novel method to improve the performance of high-DOF
image base visual servoing (IBVS) with an uncalibrated camera. Firstly, analysis and comparison
between point-based and moment-based features are carried out with respect to a 4-DOF
positioning task. Then, an extended interaction matrix (IM) related to the digital image, and a
Kalman filter (KF)-based estimation algorithm of the extended IM without calibration and IM
model are proposed. Finally, the KF-based algorithm is extended to realize an approximation to
decoupled control scheme. Experimental results conducted on an industrial robot show that our