Dr. Xiaoyan Shen Profile

Dr. Xiaoyan Shen

Lecturer at China Jiliang Univ

SPIE Involvement:

Author

Publications (4)

Proceedings Article | 18 March 2024 Paper

Image processing method in bump height measurement in chip packaging

Xinxin Zhang, Zili Zhang, Xiaoyan Shen, Fanchang Meng, Dezhao Wang

Proceedings Volume 13104, 1310454 (2024) https://doi.org/10.1117/12.3023654

KEYWORDS: Image processing, Feature extraction, Laser processing, Packaging, Computer simulations, Matrices, Inspection, Semiconducting wafers, Reflection, Objectives

Read Abstract +

Proceedings Article | 19 November 2021 Paper

The error analysis and experimental research of micro-angle measurement system based on F-P etalon

Shinan Zhou, Xiaoyan Shen, Chenguang Wu, Dongsheng Li

Proceedings Volume 12059, 120590O (2021) https://doi.org/10.1117/12.2611746

KEYWORDS: Fabry–Perot interferometers, Error analysis, Temperature metrology, Data processing, Staring arrays, Refractive index, Light sources, Image quality

Read Abstract +

Proceedings Article | 10 August 2015 Paper

A new population initialization method of genetic algorithm applied in FBG inhomogeneous strain demodulation

Liangyue Zhang, Xiaoyan Shen, Ya Han, Jie Sun, Dongsheng Li

Proceedings Volume 9620, 96200Z (2015) https://doi.org/10.1117/12.2193093

KEYWORDS: Fiber Bragg gratings, Genetic algorithms, Demodulation, Reconstruction algorithms, Algorithms, Modulation, Sensors, Computer simulations, Genetics, Refractive index

Read Abstract +

FBG is a kind of promising high precision strain sensor, and it can not only detect the homogeneous strain, but also identify non-uniform strain distribution. In the application of FBG in inhomogeneous strain sensing, genetic algorithm is an important method to reconstruct the non-uniform strain from reflection spectra of FBG. However, the practical reconstruction of genetic algorithm demonstrates its shortcomings such as low computational efficiency, easily falling into local optimal solution, etc , and it is well known that there is a great relationship between computational efficiency and population initialization of genetic algorithm. In general genetic algorithm employed in FBG strain reconstruction, the initialized population is randomly distributed strain along FBG axial direction, which ignores the continuity between neighbor strains. To reduce the number of population parameters and make the original population more close to the real strain distribution, a new method of population initialization is proposed here, that is using polynomial function parameters to be the initialized population instead of the randomly distributed strain, supposed that the FBG axial strains can be described as a polynomial function with independent variable of axial position. In simulation experiments, the reflection spectrums of a 10mm-long FBG are obtained from T-Matrix method in four cases of strain-free, linear-distributed strain, parabola-distributed strain and exponential –distributed strain, and then the general genetic algorithm and the new genetic algorithm with simplified population initialization were applied to reconstruct the strain distribution from the reflection spectrums respectively. The experiment results verify the supposition of the polynomial function of the FBG, and show clearly that the new method can improve the computational efficiency of genetic algorithm in FBG inhomogeneous strain demodulation greatly. From the results, it is found that with the same calculation accuracy, the computing time of the new population initialization method is reduced to about 1/5 of the general on average.

Proceedings Article | 8 September 2011 Paper

A large-scale strain sensor based on fiber Bragg grating

Xiaoyan Shen, Yuchi Lin

Proceedings Volume 8191, 81911Z (2011) https://doi.org/10.1117/12.900934

KEYWORDS: Fiber Bragg gratings, Sensors, Finite element methods, Resistance, Corrosion, Electromagnetic interference, Distortion, Metals, Numerical simulations, Optical fibers

Read Abstract +

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years