Stereo vision measurement technique using artifical neural network

2000 ◽  
Author(s):  
Wenyi Deng ◽  
Naiguang Lu ◽  
Di Feng
2019 ◽  
Vol 30 (4) ◽  
pp. 556-575 ◽  
Author(s):  
Zhi-cheng Qiu ◽  
Tao-xian Wang

Vibration control on a two-connected piezoelectric flexible hinged plate is investigated, using a fuzzy neural network algorithm based on binocular vision measurement. As for vision sensing, a method to acquire vibration signals of the low frequency bending and torsional mode is investigated. To damp out the residual vibration quickly, the fuzzy neural network is applied to ensure the stability and control effect adaptively. To verify the stereo vision measurement method and the applied controller, an experimental setup of the piezoelectric flexible hinged plate with a binocular stereo vision is constructed. Experiments are conducted by using the binocular stereo vision measurement system and the adopted controller. The experimental results demonstrate the feasibility of the visual measurement method. Furthermore, the designed fuzzy neural network can attenuate the bending and torsional vibrations quickly, in comparison with proportional and derivative control, particularly for the small-level residual vibration.


2009 ◽  
Vol 29 (6) ◽  
pp. 1546-1551
Author(s):  
徐巧玉 Xu Qiaoyu ◽  
姚怀 Yao Huai ◽  
车仁生 Che Rensheng

2014 ◽  
Vol 580-583 ◽  
pp. 2805-2809
Author(s):  
Qiang Wang ◽  
Xi Min Cui ◽  
Cong Li ◽  
Jia Jie Cui ◽  
Liang Jian Li

In precision machining, we often detect the location of some round holes or other geometric parameters. Given the disadvantages of traditional method is contacted, artificial and time-consuming, this paper has proposed a image measurement method based on stereo vision. We use the method of digital image processing to perform the denoising, binarization, edge detection, and centralized location of the orifice image, and analyze the accuracy of the hole machining and arrangement. Experimental results show that the error of image measurement proposed is less than 0.14mm, which meets the general requirements of the hole measurement precision and is applicable to the online measurement that the accuracy requirement is not high and the task with large amount of object to detect.


2019 ◽  
Vol 68 (10) ◽  
pp. 3563-3575 ◽  
Author(s):  
Zhen Liu ◽  
Suining Wu ◽  
Qun Wu ◽  
Chenggen Quan ◽  
Yiming Ren

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