Xiufeng Wang
4 Papers
12 Citations
Xiufeng Wang is an academic researcher. The author has contributed to research in topics: Bending & Artificial neural network. The author has an hindex of 3, co-authored 4 publications.
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Papers
Patent
Non-contact real-time displacement measuring method and device in bending deformation process of work piece
Brandner E,Juergen Silvanus,Yougui Cai,Tianyi Gui,Xiaoli Guo,Linlin Huang,Jian Lu,Xiufeng Wang,Qingfeng Yang +8 more
- 23 Jun 2010
TL;DR: In this paper, a non-contact real-time method for measuring the bending displacement of a work piece (5) which is deformed by a bending method is proposed. But the method is not suitable for real time applications.
5
Patent
Bending displacement by utilizing artificial neural network
Brandner E,Juergen Silvanus,Yougui Cai,Xiaoli Guo,Jian Lu,Xiufeng Wang,Qingfeng Yang +6 more
- 23 Jun 2010
TL;DR: In this article, a bending displacement by utilizing artificial neural network and relates to a method for estimating the functional dependence of manufacturing parameters and the bending displacement in the bending process by an artificial neural networks method.
3
Patent
Method for measuring the bending displacement of workpiece and system for measuring the bending displacement
Xiufeng Wang,Qingfeng Yang,Linlin Huang,Tianyi Gui,Xiaoli Guo,Yougui Cai,Juergen Silvanus,Erhard Brandl,Jian Lu +8 more
- 17 Nov 2009
TL;DR: In this article, a method for measuring the bending displacement of a workpiece to be deformed by bending means comprises the steps of: bending the workpiece (5), capturing images of at least a part of the work piece (5) by a camera (7), processing the images by a processor (8), which is electronically connected with the camera(7), and determining the bending displacements by the processor(8).
3
Patent
Bending displacement with utilization of an artificial neural network
Xiufeng Wang,Qingfeng Yang,Xiaoli Guo,Yougui Cai,Juergen Silvanus,Erhard Brandl,Jian Lu +6 more
- 17 Nov 2009
TL;DR: In this article, a method for estimating a functional dependency between manufacturing parameters and a bending displacement by means of an Artificial Neural Network in a bending process was proposed, the method comprising the steps of pre-calculating weights and threshold values of the artificial neural network by means a genetic algorithm, assigning the weights and thresholds to the Artificial Neural Networks, and training the artificial Neural Networks.
1