Fast Position and Accurate Segmentation Algorithms for Detecting Surface Defects of the Thermal-State Heavy Rail Based on Machine Vision

2013 ◽  
Vol 5 (4) ◽  
pp. 40-60
Author(s):  
Xue Wang ◽  
Yiran Chen ◽  
Tao Cheng ◽  
Zhijiang Xie
Keyword(s):  
Nearest Neighbor ◽  
Surface Defects ◽  
Thermal State ◽  
Mean Shift ◽  
Sampling Point ◽  
Positioning Method ◽  
Rolled Condition ◽  
Novel Algorithms ◽  
Hot Rolled ◽  
Heavy Rail

Color imaging in the hot rolled condition provides the better reaction of heavy rail on surface defects. In this paper, it proposes a series of novel algorithms of accurate position and segmentation of surface defects of heavy rail. An image acquisition device is designed on the adjustable camera bracket with the linear array CCD, and based on the correlation among pixels at the image level, a fast positioning method is developed for searching the Region Of Interesting (ROI) of the surface defects. Using the Mean-Shift image filtering algorithm which features multi-parameter kernel function, amendments to the sampling point weights and regional search with the nearest neighbor sampling points, accurate segmentation of the identification character is easily achieved by K-means clustering. Experiments show that this algorithm for the identification of the heavy rail surface defects is proven to be more rapid in testing the inclusions, cracks and oxide skin defects with a good promotional value.

REPUBLIC X-80-W

Alloy Digest ◽  
1980 ◽  
Vol 29 (5) ◽  
Keyword(s):  
Corrosion Resistance ◽  
Yield Strength ◽  
Physical Properties ◽  
Surface Treatment ◽  
High Strength ◽  
Heat Treating ◽  
Low Alloy Steel ◽  
Rolled Condition ◽  
Hot Rolled ◽  
Minimum Yield

Abstract REPUBLIC X-80-W is a high-strength, low-alloy steel developed to achieve a minimum yield strength of 80,000 psi in the as-hot-rolled condition. It also exhibits good fatigue performance, good bendability, and good weldability. It is available as bars and can be used in various automotive and machinery applications. This datasheet provides information on composition, physical properties, elasticity, and tensile properties. It also includes information on corrosion resistance as well as forming, heat treating, machining, joining, and surface treatment. Filing Code: SA-372. Producer or source: Republic Steel Corporation.

scholarly journals X-SDD: A New Benchmark for Hot Rolled Steel Strip Surface Defects Detection

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 706
Author(s):  
Xinglong Feng ◽  
Xianwen Gao ◽  
Ling Luo
Keyword(s):  
Surface Defect ◽  
Surface Defects ◽  
Steel Strip ◽  
Rolled Strip ◽  
Rolled Steel ◽  
Strip Surface ◽  
Hot Rolled Strip ◽  
Hot Rolled ◽  
Hot Rolled Steel ◽  
Detection Of Defects

It is important to accurately classify the defects in hot rolled steel strip since the detection of defects in hot rolled steel strip is closely related to the quality of the final product. The lack of actual hot-rolled strip defect data sets currently limits further research on the classification of hot-rolled strip defects to some extent. In real production, the convolutional neural network (CNN)-based algorithm has some difficulties, for example, the algorithm is not particularly accurate in classifying some uncommon defects. Therefore, further research is needed on how to apply deep learning to the actual detection of defects on the surface of hot rolled steel strip. In this paper, we proposed a hot rolled steel strip defect dataset called Xsteel surface defect dataset (X-SDD) which contains seven typical types of hot rolled strip defects with a total of 1360 defect images. Compared with the six defect types of the commonly used NEU surface defect database (NEU-CLS), our proposed X-SDD contains more types. Then, we adopt the newly proposed RepVGG algorithm and combine it with the spatial attention (SA) mechanism to verify the effect on the X-SDD. Finally, we apply multiple algorithms to test on our proposed X-SDD to provide the corresponding benchmarks. The test results show that our algorithm achieves an accuracy of 95.10% on the testset, which exceeds other comparable algorithms by a large margin. Meanwhile, our algorithm achieves the best results in Macro-Precision, Macro-Recall and Macro-F1-score metrics.

scholarly journals An improved Vision Transformer-based method for classifying surface defects in hot-rolled strip steel

2021 ◽  
Vol 2082 (1) ◽  
pp. 012016
Author(s):  
Xinglong Feng ◽  
Xianwen Gao ◽  
Ling Luo
Keyword(s):  
Surface Defect ◽  
Surface Defects ◽  
Steel Strip ◽  
Learning Ability ◽  
Rolled Strip ◽  
Strip Surface ◽  
Strip Steel ◽  
Hot Rolled Strip ◽  
Hot Rolled ◽  
Improved Algorithm

Abstract A new Vision Transformer(ViT) model is proposed for the classification of surface defects in hot rolled strip, optimizing the poor learning ability of the original Vision Transformer model on smaller datasets. Firstly, each module of ViT and its characteristics are analyzed; Secondly, inspired by the deep learning model VGGNet, the multilayer fully connected layer in VGGNet is introduced into the ViT model to increase its learning capability; Finally, by performing on the X-SDD hot-rolled steel strip surface defect dataset. The effect of the improved algorithm is verified by comparison experiments on the X-SDD hot-rolled strip steel surface defect dataset. The test results show that the improved algorithm achieves better results than the original model in terms of accuracy, recall, F1 score, etc. Among them, the accuracy of the improved algorithm on the test set is 5.64% higher than ViT-Base and 2.64% higher than ViT-Huge; the accuracy is 4.68% and 1.36% higher than both of them, respectively.

scholarly journals Application of a WiFi/Geomagnetic Combined Positioning Method in a Single Access Point Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hongbin Pan ◽  
Yang Xiang ◽  
Jian Xiong ◽  
Yifan Zhao ◽  
Ziwei Huang ◽  
...  
Keyword(s):  
Nearest Neighbor ◽  
Detection Method ◽  
Access Point ◽  
Combination Method ◽  
Data Set ◽  
Positioning Accuracy ◽  
Multipath Effects ◽  
Positioning Method ◽  
Fingerprint Database ◽  
Mismatch Rate

Because of the particularity of urban underground pipe corridor environment, the distribution of wireless access points is sparse. It causes great interference to a single WiFi positioning method or geomagnetic method. In order to meet the positioning needs of daily inspection staff, this paper proposes a WiFi/geomagnetic combined positioning method. In this combination method, firstly, the collected WiFi strength data was filtered by outlier detection method. Then, the filtered data set was used to construct the offline fingerprint database. In the following positioning operation, the classical k -nearest neighbor algorithm was firstly used for preliminary positioning. Then, a standard circle was constructed based on the points obtained by the algorithm and the actual coordinate points. The diameter of the standard circle was the error, and the geomagnetic data were used for more accurate positioning in this circle. The method reduced the WiFi mismatch rate caused by multipath effects and improved positioning accuracy. Finally, a positioning accuracy experiment was performed in a single AP distribution environment that simulates a pipe corridor environment. The results proves that the WiFi/geomagnetic combined positioning method proposed in this paper is superior to the traditional WiFi and geomagnetic positioning methods in terms of positioning accuracy.

Investigation into Surface Defects Arising in Hot-Rolled SUP 11A Grade Spring Billets

2008 ◽  
Vol 8 (6) ◽  
pp. 492-497 ◽  
Author(s):  
Santosh Kumar ◽  
Vinod Kumar ◽  
R. K. Nandi ◽  
T. S. Suresh ◽  
Ramen Datta
Keyword(s):  
Surface Defects ◽  
Hot Rolled

Hot Deformation Behavior of Al-Cu-Li-Mg-Zn-Zr-Sc Alloy in As-Cast and Hot-Rolled Condition

2018 ◽  
Vol 920 ◽  
pp. 244-249 ◽  
Author(s):  
Yaroslav Erisov ◽  
Sergey Surudin ◽  
Fedor Grechnikov
Keyword(s):  
Strain Rate ◽  
Hot Deformation ◽  
Rheological Model ◽  
Physical Simulation ◽  
Constant Strain Rate ◽  
Rolled Plate ◽  
Hollomon Parameter ◽  
Aluminum Lithium ◽  
Rolled Condition ◽  
Hot Rolled

The results of physical simulation of hot compression of semi-finished products, selected from a cast ingot and hot-rolled plate from aluminum-lithium alloy V-1461, in the temperature range of 400-460°C and strain rates of 1-60 s-1are presented. It is established that at a constant strain rate the flow stresses decrease with increasing test temperature, an increase in the strain rate leads to an increase in flow stresses at a constant temperature. The parameters of the hot deformation rheological model, including the Zener-Hollomon parameter and the hyperbolic sine law, are determined. It is established that the parameters of the rheological model for the cast and hot-rolled state differ insignificantly.

Texture Descriptors for Automatic Classification of Surface Defects of the Hot-Rolled Steel Strip

2021 ◽  
pp. 251-260
Author(s):  
Virginia Riego del Castillo ◽  
Lidia Sánchez-González ◽  
Alexis Gutiérrez-Fernández
Keyword(s):  
Surface Defects ◽  
Steel Strip ◽  
Automatic Classification ◽  
Rolled Steel ◽  
Hot Rolled ◽  
Hot Rolled Steel
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