Image Stitching and Quality Evaluation Algorithm for Large Size Parts

2017 ◽  
Author(s):  
Xin Li ◽  
Liming Wu ◽  
Guitang Wang ◽  
Yujun Chen ◽  
Kuai Rong ◽  
...  
Keyword(s):  
Quality Evaluation ◽  
Image Stitching ◽  
Large Size ◽  
Evaluation Algorithm

Метод и аппаратура инфракрасного и ультразвукового термографического контроля крупногабаритных композиционных изделий сложной формы

2021 ◽  
Vol 7 ◽  
pp. 67-74
Author(s):  
А.О. Чулков ◽  
Д.А. Нестерук ◽  
Б.И. Шагдыров ◽  
В.П. Вавилов
Keyword(s):  
Neural Network ◽  
Nondestructive Testing ◽  
Data Fusion ◽  
Defect Detection ◽  
Complex Shape ◽  
Reference Sample ◽  
Robotic System ◽  
Image Stitching ◽  
Large Size ◽  
Thermal Nondestructive Testing

A robotic system for combined thermal nondestructive testing of large-size parts, including data fusion, is described. The efficiency of combining results of infrared (IR) and ultrasonic IR thermographic inspection has been demonstrated on a complex-shape reference sample containing 18 surrogates of manufacture and in-service defects. The data fusion algorithms including IR image stitching in space and automated defect detection and characterization by using a neural network have demonstrated efficiency of the proposed approach in practical testing.

Fuzzy Evaluation of Synthetic Quality for Fabric Materials

2010 ◽  
Vol 108-111 ◽  
pp. 878-883
Author(s):  
Xiu Chen Wang
Keyword(s):  
Data Model ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Fuzzy Theory ◽  
Quality Standard ◽  
Fuzzy Evaluation ◽  
Evaluation Algorithm ◽  
Index Value ◽  
Fabric Materials ◽  
Quality Evaluation System

Aaccording to the cases that the synthetic quality evaluation system for fabric is not reasonable at present, a new synthetic quality evaluation system for fabric on fuzzy theory is proposed. This new evaluation system is made of foundation layer, evaluating layer and result layer. In foundation layer, the quality standard model and evaluating data model based on multi-indexes are proposed, and the calculation method of each index value in these models is given. In evaluating layer, according to the problem that the result of existing closeness algorithm has greatly repeated, a new evaluation algorithm is proposed. In result layer, two formulas which are continuous result and discrete result are given. Also the accuracy and rationality of this evaluation system is validated by some examples in this paper, and the effect of evaluation result by the primary-secondary indexes, the significance of closeness, the expansibility of model, the accuracy of system and the application method are made analysis. At last, the conclusion shows that this system can make the synthetic evaluation for fabric quality rationally and accurately.

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