scholarly journals Study on the Extraction Method of Deformation Influence Factors of Flexible Material Processing Based on Information Entropy

2014 ◽  
Vol 6 ◽  
pp. 547947 ◽  
Author(s):  
Yaohua Deng ◽  
Qiwen Lu ◽  
Jiayuan Chen ◽  
Sicheng Chen ◽  
Liming Wu ◽  
...  
Keyword(s):  
Material Processing ◽  
Information Entropy ◽  
Extraction Method ◽  
Knowledge Extraction ◽  
Attribute Importance ◽  
Compensation Control ◽  
Flexible Material ◽  
Extraction Algorithm ◽  
Control Knowledge ◽  
Deformation Compensation

Through analyzing the flexible material processing (FMP) deformation factors, it is pointed out that without a choice of deformation influence quantity would increase the compensation control predict model system input. In order to reduce the count of spatial dimensions of knowledge, we proposed the method by taking the use of FMP deformation compensation control knowledge extraction, which is based on decision table (DT) attribute reduction, deriving the algorithm that is based on information entropy attribute importance, to find the dependencies between attributes through attribute significance (AS) and to extract the intrinsic attributes which is the most close to deformation compensation control decision making. Finally, through an example presented in this paper to verify the efficiency of RS control knowledge extraction method. Compared with the Pawlak method and genetic extraction algorithm, the prediction accuracy of after reduction data is 0.55% less than Pawlak method and 3.64% higher than the genetic extraction algorithm; however, the time consumption of forecast calculation is 30.3% and 11.53% less than Pawlak method and genetic extraction algorithm, respectively. Knowledge extraction entropy methods presented in this paper have the advantages of fast calculating speed and high accuracy and are suitable for FMP deformation compensation of online control.

Research of Processing Deformation Compensation of Flexible Leather Material Based on Knowledge Management

2014 ◽  
Vol 912-914 ◽  
pp. 1681-1684 ◽  
Author(s):  
Li Ming Wu ◽  
Si Cheng Chen ◽  
Yao Hua Deng ◽  
Fu Jian Li ◽  
Bing Jing Li
Keyword(s):  
Knowledge Management ◽  
Impact Factors ◽  
Real Time Processing ◽  
Compensation Control ◽  
Leather Processing ◽  
Flexible Material ◽  
Shoe Manufacturing ◽  
Tool Trajectory ◽  
Processing Material ◽  
Deformation Compensation

Leather is a common processing material with poor rigidity in shoe manufacturing, there is easy to generate tensile or compress deformation, so reducing the processing quality. Considering the reasons of leather processing deformation, there are flexible material variety, different material thickness and complicated processing path. The article discussing the various impact factors of leather cutting deformation, combined with the theory and method of processing decision knowledge acquisition, processing knowledge management, and closed-loop compensation control, to propose a deformation compensation method of leather cutting based on knowledge management. Thought the real-time processing path compensation control, to correcting the tool trajectory in process, improving the accuracy and reliability of leather cutting.

A Novel Blind Watermark Extraction Algorithm Based on Nonsubsampled Contourlet Transform

2014 ◽  
Vol 989-994 ◽  
pp. 1901-1904
Author(s):  
Lei Feng ◽  
Xiao Fei Shi ◽  
Hong Yu Chen ◽  
Yan Hua Li ◽  
Yue Long Zhang
Keyword(s):  
Prior Knowledge ◽  
Blind Source Separation ◽  
Extraction Method ◽  
Low Frequency ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Independent Components ◽  
Extraction Algorithm ◽  
Blind Extraction ◽  
Ica Algorithm

Most existing watermark extraction algorithms were dependent on prior knowledge. This paper proposed a blind extraction method without relying on prior knowledge. According to constructing new observation based on nonsubsampled contourlet transform, which utilizes low frequency and directional components of watermarked image, more independent components are generated. We involve these components into watermarked image and resort this solution to multichannel blind source separation. Estimated watermark is recovered by ICA algorithm. Experiment results indicate that the proposed method can achieve better results in contrast with two existing algorithms.

scholarly journals A Feature Points Extraction Algorithm Based on Adaptive Information Entropy

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 127134-127141
Author(s):  
Dan Yin ◽  
Siwei Zhou ◽  
Pengcheng Wang ◽  
Manling Lin ◽  
Hui Song ◽  
...  
Keyword(s):  
Information Entropy ◽  
Feature Points ◽  
Extraction Algorithm

Research on Flow Object Knowledge Extraction Method

2008 ◽  
Author(s):  
Shouning Qu ◽  
Guangqiang Cui ◽  
Zhaolian Liu ◽  
Jinbin Wu
Keyword(s):  
Extraction Method ◽  
Knowledge Extraction ◽  
Object Knowledge

A modified welding image feature extraction algorithm for rotating arc narrow gap MAG welding

2015 ◽  
Vol 42 (3) ◽  
pp. 222-227 ◽  
Author(s):  
Wenhang Li ◽  
Yunhong Ji ◽  
Jing Wu ◽  
Jiayou Wang
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Image Feature ◽  
Mag Welding ◽  
Narrow Gap ◽  
Image Feature Extraction ◽  
Content Type ◽  
Feature Extraction Method ◽  
Extraction Algorithm ◽  
Welding Image

Purpose The purpose of this paper is to provide a modified welding image feature extraction algorithm for rotating arc narrow gap metal active-gas welding (MAG) welding, which is significant for improving the accuracy and reliability of the welding process. Design/methodology/approach An infrared charge-coupled device (CCD) camera was utilized to obtain the welding image by passive vision. The left/right arc position was used as a triggering signal to capture the image when the arc is approaching left/right sidewall. Comparing with the conventional method, the authors’ sidewall detection method reduces the interference from arc; the median filter removes the welding spatter; and the size of the arc area was verified to reduce the reflection from welding pool. In addition, the frame loss was also considered in the authors’ method. Findings The modified welding image feature extraction method improves the accuracy and reliability of sidewall edge and arc position detection. Practical implications The algorithm can be applied to welding seam tracking and penetration control in rotating or swing arc narrow gap welding. Originality/value The modified welding image feature extraction method is robust to typical interference and, thus, can improve the accuracy and reliability of the detection of sidewall edge and arc position.

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