A heterodyne interference elliptic-deviation measurement nonlinear error compensation method

A nonlinear error and heterodyne interference technology, applied in measurement devices, phase influence characteristic measurement, instruments, etc., can solve the problems of error, influence work stability, increase the complexity of measurement system, etc., to improve accuracy and suppress drift. Effect

Inactive Publication Date: 2009-09-02
SHENZHEN UNIV
View PDF2 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] Some methods need to use an additional photoelectric error compensation system, which will increase the complexity of the measurement system, affect the stability of the work, and introduce other errors

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A heterodyne interference elliptic-deviation measurement nonlinear error compensation method
  • A heterodyne interference elliptic-deviation measurement nonlinear error compensation method
  • A heterodyne interference elliptic-deviation measurement nonlinear error compensation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] see figure 2 as well as image 3 , the present invention provides a method for compensating nonlinear errors of heterodyne interference ellipsometry based on neural network, which includes the following steps: A provides a series of film samples with different thicknesses and measures the film samples by using a heterodyne interference ellipsometry system; B The experimental data of the ellipsometric parameters obtained above, the ambient temperature during measurement, the polarization state distortion of the incident beam, and the theoretical data of the ellipsometric parameters are used as learning samples to train the neural network; Linearity error online compensation.

[0029] The neural network-based heterodyne interference ellipsometry nonlinear error compensation method of the present invention uses the same material to make (or select) a series of film samples with different thicknesses according to the structure of the film system to be measured, covering t...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a heterodyne interference elliptic-deviation measurement nonlinear error compensation method based on a neuronic network, which comprises the following steps: A. providing a series of thin film samples with different thicknesses and adopting a heterodyne interference elliptic-deviation measurement system to measure the thin film samples; B. taking elliptic-deviation parameter experimental data obtained from the A, environment temperature and the polarization state aberration of incident light beams during measurement and elliptic-deviation parameter theoretical data as learning samples to train the neuronic network; and C. controlling nonlinear error on-line compensation in a weight way by the neuronic network after being successfully trained. The invention has the advantages that the heterodyne interference elliptic-deviation measurement nonlinear error compensation method adopts a neuronic network compensation system to synthetize nonlinear errors and takes environment temperature as an input of the neuronic network, thereby effectively suppressing the shifting of the nonlinear errors; and the polarization state aberration of the incident light beams is observed and taken as an input of the neuronic network, thereby the precision of nonlinear error models is enhanced.

Description

technical field [0001] The invention relates to the field of optical precision measurement, in particular to a neural network-based nonlinear error compensation method for heterodyne interference ellipsometry. Background technique [0002] Ellipsometry is an advanced optical technology that uses polarized light to measure and study the properties of material surfaces and thin films, and is especially suitable for the measurement of nanoscale thin films. Due to the advantages of non-contact non-destructive testing, high measurement accuracy, and simultaneous measurement of film thickness and refractive index, it is widely used in many fields such as microelectronics, materials, optics, chemistry and chemical engineering. [0003] Heterodyne interference ellipsometry technology combines the advantages of laser heterodyne interferometry and the basic principles of ellipsometry. It has fast measurement speed and strong anti-interference ability, and can be used for online measur...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/45G01B11/06
Inventor 邓元龙李学金
Owner SHENZHEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap