scholarly journals A Micro-Damage Detection Method of Litchi Fruit Using Hyperspectral Imaging Technology

Sensors ◽  
2018 ◽  
Vol 18 (3) ◽  
pp. 700 ◽  
Author(s):  
Juntao Xiong ◽  
Rui Lin ◽  
Rongbin Bu ◽  
Zhen Liu ◽  
Zhengang Yang ◽  
...  
Keyword(s):  
Damage Detection ◽  
Hyperspectral Imaging ◽  
Detection Method ◽  
Imaging Technology ◽  
Litchi Fruit

scholarly journals Research on Detection Method of Pea Seed Vigor based on Hyperspectral Imaging Technology

2021 ◽  
Vol 15 ◽  
pp. 1072-1083
Author(s):  
Luo Qinjuan ◽  
Wang Lianming ◽  
Zhao Xiaoqing ◽  
Qian Hua ◽  
Yan Lei
Keyword(s):  
Hyperspectral Imaging ◽  
Seed Quality ◽  
Detection Method ◽  
Seed Vigor ◽  
Detection Methods ◽  
Band Spectrum ◽  
Imaging Technology ◽  
Full Band ◽  
Pea Seeds ◽  
Pea Seed

Rapid and noninvasive detection methods of seed vigor, an important index to evaluate seed quality, have been the research focus in recent years. In this paper, the detection method of pea seed vigor based on hyperspectral imaging technology was researched. First, the spectral images of different vigor grade samples with artificial aging were captured, and the original spectrum was pretreated with multiple scattering correction. Secondly, SPA and PCA were used to select respective bands. Finally, PLS-DA and LS-SVM model were established to identify the seed vigor of the pea seed, based on the whole band spectrum, the characteristic bands extracted by SPA and PCA respectively. The results showed that PLS-DA and LS-SVM models are effective, but LS-SVM had better performance. Through comparison, the method using full band spectrum was more accurate, the efficiency of method using 5 characteristic bands extracted by PCA was the highest while the way of extracting the representative band by SPA was the most meaningful to this study which achieved similar accuracy to the full band with only 20 bands. The SPA-LS-SVM method afforded the recognition accuracy (100%) for modeling set and validation set used to determine the vigor of pea seeds. The overall results suggest that hyperspectral imaging technology is useful for classification of different vitality pea seeds with non-destructive manner, which can provide a basis for further development of online scoring devices

scholarly journals Study on Detection Method of Foxing on Paper Artifacts Based on Hyperspectral Imaging Technology

2021 ◽  
Vol 2010 (1) ◽  
pp. 012177
Author(s):  
Ruochen Dai ◽  
Bin Tang ◽  
Mingfu Zhao ◽  
Huan Tang ◽  
Hang Liu
Keyword(s):  
Hyperspectral Imaging ◽  
Detection Method ◽  
Imaging Technology

scholarly journals Mode Shape-Based Damage Detection Method (MSDI): Experimental Validation

2021 ◽  
Vol 11 (10) ◽  
pp. 4589
Author(s):  
Ivan Duvnjak ◽  
Domagoj Damjanović ◽  
Marko Bartolac ◽  
Ana Skender
Keyword(s):  
Boundary Conditions ◽  
Damage Detection ◽  
Mode Shape ◽  
Experimental Validation ◽  
Detection Method ◽  
Dynamic Properties ◽  
Damage Index ◽  
Main Principle ◽  
The Difference ◽  
Different Levels

The main principle of vibration-based damage detection in structures is to interpret the changes in dynamic properties of the structure as indicators of damage. In this study, the mode shape damage index (MSDI) method was used to identify discrete damages in plate-like structures. This damage index is based on the difference between modified modal displacements in the undamaged and damaged state of the structure. In order to assess the advantages and limitations of the proposed algorithm, we performed experimental modal analysis on a reinforced concrete (RC) plate under 10 different damage cases. The MSDI values were calculated through considering single and/or multiple damage locations, different levels of damage, and boundary conditions. The experimental results confirmed that the MSDI method can be used to detect the existence of damage, identify single and/or multiple damage locations, and estimate damage severity in the case of single discrete damage.

Elimination of outlier measurements for damage detection of structures under changing environmental conditions

2021 ◽  
pp. 147592172199847
Author(s):  
William Soo Lon Wah ◽  
Yining Xia
Keyword(s):  
Damage Detection ◽  
Multiple Regression ◽  
Natural Frequencies ◽  
Detection Method ◽  
Detection Methods ◽  
Structure Model ◽  
Bridge Structure ◽  
Beam Structure ◽  
Dependent Variables ◽  
The Difference

Damage detection methods developed in the literature are affected by the presence of outlier measurements. These measurements can prevent small levels of damage to be detected. Therefore, a method to eliminate the effects of outlier measurements is proposed in this article. The method uses the difference in fits to examine how deleting an observation affects the predicted value of a model. This allows the observations that have a large influence on the model created, to be identified. These observations are the outlier measurements and they are eliminated from the database before the application of damage detection methods. Eliminating the outliers before the application of damage detection methods allows the normal procedures to detect damage, to be implemented. A multiple-regression-based damage detection method, which uses the natural frequencies as both the independent and dependent variables, is also developed in this article. A beam structure model and an experimental wooden bridge structure are analysed using the multiple-regression-based damage detection method with and without the application of the method proposed to eliminate the effects of outliers. The results obtained demonstrate that smaller levels of damage can be detected when the effects of outlier measurements are eliminated using the method proposed in this article.

scholarly journals Quality inspection of nectarine based on hyperspectral imaging technology

2021 ◽  
Vol 9 (1) ◽  
pp. 350-357
Author(s):  
Feng-Hua Huang ◽  
Yan-Hong Liu ◽  
XinYi Sun ◽  
Hua Yang
Keyword(s):  
Hyperspectral Imaging ◽  
Quality Inspection ◽  
Imaging Technology

Adaptive and automatic red blood cell counting method based on microscopic hyperspectral imaging technology

2017 ◽  
Vol 19 (12) ◽  
pp. 124014 ◽  
Author(s):  
Xi Liu ◽  
Mei Zhou ◽  
Song Qiu ◽  
Li Sun ◽  
Hongying Liu ◽  
...  
Keyword(s):  
Blood Cell ◽  
Hyperspectral Imaging ◽  
Red Blood Cell ◽  
Cell Counting ◽  
Counting Method ◽  
Imaging Technology ◽  
Blood Cell Counting

Study on Damage Detection of Bridge Based on Wavelet Multi-Scale Analysis

2013 ◽  
Vol 639-640 ◽  
pp. 1010-1014 ◽  
Author(s):  
Ke Ding ◽  
Ting Peng Chen
Keyword(s):  
Wavelet Transform ◽  
Damage Detection ◽  
Detection Method ◽  
Mode Shapes ◽  
Scale Analysis ◽  
Multi Scale ◽  
Damage Location ◽  
Transform Coefficients ◽  
Beam Bridge ◽  
Multi Scale Analysis

The damage detection method based on wavelet multi-scale analysis is presented in the paper. The damage location can be identified by analyzing the multi-scale wavelet transform coefficients of curvatures of mode shapes. The extreme value of wavelet transform coefficients indicates the damage location. But it is difficult to detect the location of defect if the defect is near to the equilibrium position of vibration. In order to solve this problem, we put forward a method which is to add the wavelet transform coefficients of multi modals together. The method can effectively overcome the above problem. Three damage situations of simply supported beam bridge are discussed in the paper. The results show that the peaks of wavelet transform coefficients indicate the damage location of structural. It is possible to pinpoint the damage location based on wavelet multi-scale analysis on curvatures of mode shapes.

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