Weld Pool Image Processing and Feature Extraction Based on the Vision of the CO2 Welding

2015 ◽  
pp. 625-633
Author(s):  
Xiaogang Liu ◽  
Xiaowei Ji
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Weld Pool ◽  
Co2 Welding ◽  
Pool Image

Molten Pool Image Processing and Feature Extraction Based on Multiple Visions

2013 ◽  
Vol 753-755 ◽  
pp. 2131-2134
Author(s):  
Da Wei Wu ◽  
Zhen Yu Xiong ◽  
Wang Ping Gu ◽  
Jun Shan
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Molten Pool ◽  
Median Filtering ◽  
Threshold Method ◽  
Welding Arc ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Composite Filter ◽  
Pool Image

A molten pool image gathering system is designed based on multiple visions. By using a composite filter, it can effectively overcome the interference of the welding arc and obtain a clear molten pool image. A series of image processing algorithms has been proposed based on the features of the molten pool image. A median filtering has been used to remove the noise of the molten pool image. A canny multi-threshold method has been used to extract the edge characteristics of the molten pool. Then the edge feature of the molten pool can be gotten after false edge removing and iterative fitting.

Dynamic estimation of joint penetration by deep learning from weld pool image

2021 ◽  
pp. 1-7
Author(s):  
Yongchao Cheng ◽  
Shujun Chen ◽  
Jun Xiao ◽  
YuMing Zhang
Keyword(s):  
Deep Learning ◽  
Weld Pool ◽  
Dynamic Estimation ◽  
Pool Image

Image processing and control of weld pool in switch-back welding without backing plate

2005 ◽  
Vol 19 (11) ◽  
pp. 856-861
Author(s):  
S Yamane ◽  
K Oshima ◽  
H Yuzawa ◽  
Y Kaneko ◽  
H Yamamoto ◽  
...  
Keyword(s):  
Image Processing ◽  
Weld Pool ◽  
Backing Plate ◽  
And Control

scholarly journals Research on Rolling Bearing Fault Feature Extraction and Diagnosis Method Based on Image Processing

2021 ◽  
Vol 5 (2) ◽  
pp. 1-7
Author(s):  
Sun Y
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Working Conditions ◽  
Rolling Bearing ◽  
Extraction Methods ◽  
Working Environment ◽  
Ring Rolling ◽  
Rolling Bearings ◽  
Binary Matrix ◽  
The Time Domain

In economic construction, there are many large and important machinery and equipment. Some equipment will continue to work in a harsh working environment, so many and various failures will occur. Rolling bearings are one of the widely used parts in rotating machinery. They are generally composed of inner ring, outer ring, rolling element and holding. The frame is composed of four parts, the failure of the bearing is particularly important, and its safe operation has a vital impact on the entire equipment, Feature extraction is the key link in the subsequent identification of fault types, Although feature extraction in the time domain and frequency domain is effective, it is also necessary to find new feature extraction methods in new areas. On the basis of the snowflake image obtained by using the principle of SDP(Symmetrized Dot Pattern), a method for extracting fault features of rolling bearings based on image processing is proposed, and the snowflake standard map for different working conditions is constructed. The number of snowflake images under different working conditions is different. The binary matrix of the test image is compared with it, and then classified and identified. Finally, the algorithm is validated, and the ideal result is obtained to verify its rationality and effectiveness.

scholarly journals AN OPTIMIZED SURF-BASED FIRE AND SMOKE DETECTION SYSTEM USING IMAGE PROCESSING FROM SURVEILLANCE VIDEO.

2020 ◽  
Vol 9 (10) ◽  
pp. 86-96
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Feature Selection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Optimization Approach ◽  
Surveillance Video ◽  
Smoke Detection ◽  
Video Frames ◽  
Optimal Feature

Over the last decades, digital image processing based fire and smoke detection have been improving steadily to provide a more accurate detection results in the area of surveillance security system. Detection of the fire and smoke from the surveillance videos is very challenging task due to the complex structural properties of the video frames or images and need improvisation in the existing work by utilization of feature selection or optimization approach to select on optimal feature according to the fire and smoke. A research based on the combination of various feature extraction techniques with feature selection approach for fire and smoke detection has been presented in this paper. In this research, we develop Fire and Smoke Detection (FSD) system using digital image processing with the concept of Speed up Robust Feature (SURF) along with the Intelligent Water Drops (IWD) as a feature selection and optimization algorithm. Here, Artificial Neural Network (ANN) is used as an Artificial Intelligence (AI) technique with that helps to select a set of optimal feature from the extracted by SURF descriptor from the video frames. By utilizing the concept of optimized ANN, the accuracy of proposed FSD system is increases in terms of detection accuracy and with minimum percentage of error. At last, the performance of the FSD system is calculated to validate the model and this shows that it is possible to use IWD with SURF as a feature extraction technique in order to detect the fire or smoke form the surveillance video with minimum error rate and the simulation results clearly show the effectiveness of proposed FSD system

scholarly journals Automatic penetration bead welding technology in horizontal position using weld pool image recognition

2021 ◽  
Vol 39 (4) ◽  
pp. 309-321
Author(s):  
Keita OZAKI ◽  
Naohide FURUKAWA ◽  
Akira OKAMOTO ◽  
Keito ISHIZAKI ◽  
Yuji KIMURA ◽  
...  
Keyword(s):  
Weld Pool ◽  
Image Recognition ◽  
Horizontal Position ◽  
Welding Technology ◽  
Pool Image

Wavelet image processing for optical pattern recognition and feature extraction

1997 ◽  
Author(s):  
Casimer M. DeCusatis ◽  
A. Abbatte ◽  
Daniel M. Litynski ◽  
Pankaj K. Das
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Feature Extraction ◽  
Optical Pattern Recognition ◽  
Optical Pattern ◽  
Wavelet Image
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