An algorithm of lens surface error compensation based on Zernike polynomial

2020 ◽  
Author(s):  
chunqi Chen ◽  
jianzhong Shang ◽  
wei Wu
Keyword(s):  
Error Compensation ◽  
Surface Error ◽  
Zernike Polynomial ◽  
Lens Surface

The Research of Error Compensation for the 3D Surface Measurement

2012 ◽  
Vol 482-484 ◽  
pp. 2192-2196
Author(s):  
Yuan Tian ◽  
Zi Ma ◽  
Peng Li
Keyword(s):  
Measurement Error ◽  
Fuzzy Inference System ◽  
Error Compensation ◽  
Point Cloud ◽  
Fuzzy Inference ◽  
Surface Measurement ◽  
Anfis Model ◽  
Inference System ◽  
Surface Error ◽  
3D Surface

For improving precision of 3D surface measurement equipments, which are playing important role in reverse engineering, the Adaptive Network based Fuzzy Inference System (ANFIS) is developed to reconstruct 3D surface error, and the measurement error of point cloud is compensated by the presented 3D error ANFIS model. The precision of 3D surface measurement equipments has been improved noticeably

Surface Error Compensation of Off-axis Parabolic Mirrors by Alignment

2010 ◽  
Vol 39 (9) ◽  
pp. 1578-1581
Author(s):  
陈钦芳 CHEN Qin-fang ◽  
李英才 LI Ying-cai ◽  
马臻 MA Zhen ◽  
李旭阳 LI Xu-yang ◽  
郭永祥 GUO Yong-xiang
Keyword(s):  
Error Compensation ◽  
Surface Error

Tracking Error Compensation of XY Table Ball Screw Driven System Using Cascade Fuzzy P+PI

2016 ◽  
Vol 9 (5) ◽  
pp. 324 ◽  
Author(s):  
Zain Retas ◽  
Lokman Abdullah ◽  
Syed Najib Syed Salim ◽  
Zamberi Jamaludin ◽  
Nur Amira Anang
Keyword(s):  
Error Compensation ◽  
Tracking Error ◽  
Ball Screw ◽  
Driven System

Study of the route correction system for the on-board navigation system of an unmanned aerial vehicle on the grounds of radar images of the terrain

2020 ◽  
pp. 129-134
Keyword(s):  
Predictive Model ◽  
Unmanned Aerial Vehicle ◽  
Predictive Models ◽  
Navigation System ◽  
Error Compensation ◽  
Compensation Scheme ◽  
Radar Images ◽  
Aerial Vehicle ◽  
System Errors ◽  
Correction System

The system of route correction of an unmanned aerial vehicle (UAV) is considered. For the route correction the on-board radar complex is used. In conditions of active interference, it is impossible to use radar images for the route correction so it is proposed to use the on-board navigation system with algorithmic correction. An error compensation scheme of the navigation system in the output signal using the algorithm for constructing a predictive model of the system errors is applied. The predictive model is building using the genetic algorithm and the method of group accounting of arguments. The quality comparison of the algorithms for constructing predictive models is carried out using mathematical modeling.

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