Quantitative Analysis of Aluminum Alloy Based on Laser-Induced Breakdown Spectroscopy and Radial Basis Function Neural Network

2020 ◽  
Vol 57 (19) ◽  
pp. 193002
Author(s):  
潘立剑 Pan Lijian ◽  
陈蔚芳 Chen Weifang ◽  
崔榕芳 Cui Rongfang ◽  
李苗苗 Li Miaomiao
Keyword(s):  
Neural Network ◽  
Aluminum Alloy ◽  
Quantitative Analysis ◽  
Radial Basis Function ◽  
Basis Function ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Radial Basis ◽  
Laser Induced Breakdown

Quantitative analysis of the major components of coal ash using laser induced breakdown spectroscopy coupled with a wavelet neural network (WNN)

2016 ◽  
Vol 8 (7) ◽  
pp. 1674-1680 ◽  
Author(s):  
Jiao Wei ◽  
Juan Dong ◽  
Tianlong Zhang ◽  
Zhanmei Wang ◽  
Hua Li
Keyword(s):  
Neural Network ◽  
Quantitative Analysis ◽  
Coal Ash ◽  
Wavelet Neural Network ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

A laser induced breakdown spectroscopy (LIBS) technique combined with a wavelet neural network (WNN) was proposed for the quantitative analysis of the major components of coal ash.

The Radial Basis Function Neural Network Quantitative Analysis Model for Determination of Anti-tuberculosis Tablets Using Near Infrared Spectroscopy

2009 ◽  
Vol 29 (2) ◽  
pp. 459-463
Author(s):  
逯家辉 Lu Jiahui ◽  
王迪 Wang Di ◽  
沈畏 Shen Wei ◽  
郭伟良 Guo Weiliang ◽  
张益波 Zhang Yibo ◽  
...  
Keyword(s):  
Neural Network ◽  
Infrared Spectroscopy ◽  
Quantitative Analysis ◽  
Radial Basis Function ◽  
Near Infrared Spectroscopy ◽  
Basis Function ◽  
Near Infrared ◽  
Analysis Model ◽  
Radial Basis

Quantitative analysis of pit defects in an automobile engine cylinder cavity using the radial basis function neural network–genetic algorithm model

2016 ◽  
Vol 16 (6) ◽  
pp. 696-710 ◽  
Author(s):  
Xiaoxia Yang ◽  
Bin Xue ◽  
Lecheng Jia ◽  
Hao Zhang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Quantitative Analysis ◽  
Radial Basis Function ◽  
Basis Function ◽  
Phased Array ◽  
Engine Cylinder ◽  
Radial Basis ◽  
Ultrasonic Phased Array ◽  
Genetic Algorithm Model

In the automotive remanufacturing movement, the inspection of the corrosion defects on the engine cylinder cavity is a key and difficult problem. In this article, based on the ultrasonic phased array technology and the radial basis function neural network–genetic algorithm model, a new quantitative analysis method is proposed to estimate the size of the pit defects on the automobile engine cylinder cavity. Echo signals from the small pit defects with different sizes are acquired by an ultrasonic phased array transducer. According to the ultrasonic signal characteristics, the feature vectors are extracted using wavelet packet, fractal technology, peak amplitude method, and some routine extract methods. The radial basis function neural network–genetic algorithm model is investigated for the quantitative analysis of the pit defects, which can obtain an optimal quantitative model. The results show that the proposed model is effective in the corrosion estimation work.

Quantitative Analysis of Magnesium and Titanium Elements in Aluminum Alloy by Handheld Laser-Induced Breakdown Spectroscopy

2019 ◽  
Vol 56 (2) ◽  
pp. 023002 ◽  
Author(s):  
李婧御 Li Jingyu ◽  
陈宽 Chen Kuan ◽  
陈国飞 Chen Guofei ◽  
李扬彦 Li Yangyan ◽  
曾爱军 Zeng Aijun ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Quantitative Analysis ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown
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