scholarly journals Magnetic Ring Multi-Defect Stereo Detection System Based on Multi-Camera Vision Technology

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 392
Author(s):  
Xinman Zhang ◽  
Weiyong Gong ◽  
Xuebin Xu
Keyword(s):  
Surface Defects ◽  
Detection System ◽  
Recognition Rate ◽  
Large Area ◽  
Edge Removal ◽  
Ring Location ◽  
Image Edge ◽  
Low Efficiency ◽  
Magnetic Ring ◽  
Magnetic Rings

Magnetic rings are the most widely used magnetic material product in industry. The existing manual defect detection method for magnetic rings has high cost, low efficiency and low precision. To address this issue, a magnetic ring multi-defect stereo detection system based on multi-camera vision technology is developed to complete the automatic inspection of magnetic rings. The system can detect surface defects and measure ring height simultaneously. Two image processing algorithms are proposed, namely, the image edge removal algorithm (IERA) and magnetic ring location algorithm (MRLA), separately. On the basis of these two algorithms, connected domain filtering methods for crack, fiber and large-area defects are established to complete defect inspection. This system achieves a recognition rate of 100% for defects such as crack, adhesion, hanger adhesion and pitting. Furthermore, the recognition rate for fiber and foreign matter defects attains 92.5% and 91.5%, respectively. The detection speed exceeds 120 magnetic rings per minutes, and the precision is within 0.05 mm. Both precision and speed meet the requirements of real-time quality inspection in actual production.

scholarly journals Strip Steel Surface Defects Recognition Based on SOCP Optimized Multiple Kernel RVM

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Hou Jingzhong ◽  
Xia Kewen ◽  
Yang Fan ◽  
Zu Baokai
Keyword(s):  
Steel Surface ◽  
Surface Defect ◽  
Surface Defects ◽  
Recognition Rate ◽  
Strip Surface ◽  
Strip Steel ◽  
Practical Applications ◽  
Multiple Kernel ◽  
Low Efficiency ◽  
Defect Recognition

Strip steel surface defect recognition is a pattern recognition problem with wide applications. Previous works on strip surface defect recognition mainly focus on feature selection and dimension reduction. There are also approaches on real-time systems that mainly exploit the autocorrection within some given picture. However, the instances cannot be used in practical applications because of a bad recognition rate and low efficiency. In this paper, we study the intelligent algorithm of strip steel surface defect recognition, where the goal is to improve the accuracy and save running time. This problem is very important in various applications, especially the process testing of steel manufacturing. We propose an approach called the second-order cone programming (SOCP) optimized multiple kernel relevance vector machine (MKRVM), which can recognize strip surface defects much better than other methods. The method includes the model parameter estimation, training, and optimization of the model based on SOCP and the classification test. We compare our approach with existing methods on strip surface defect recognition. The results demonstrate that our proposed approach can improve the recognition accuracy and reduce the time costs of the strip surface defect.

scholarly journals Study on defects detection technique of precise optical element

2018 ◽  
Vol 53 ◽  
pp. 01037
Author(s):  
Mi Zz ◽  
C Cong ◽  
Y Cheng ◽  
Zhang Hm
Keyword(s):  
Surface Defects ◽  
Recognition Performance ◽  
Recognition Rate ◽  
Optical Element ◽  
Detection Methods ◽  
Optical Elements ◽  
Average Recognition Rate ◽  
The Difference ◽  
Low Efficiency ◽  
Defect Recognition

Aiming at the problems of low efficiency of traditional detection methods for surface defects of precision optical element and inconvenient detection for optical elements of different calibers, a adjustable optical element defects detecting device for large laser devices is designed. The key technical points of system composition, detection environment, illumination design and image stitching are expounded. According to the characteristics of surface defects of optical element, such as the difference of contour, gray scale, contrast and ambiguity, a classification method based on FCM is proposed. The experimental results show that the system can realize the automatic detection of surface defects, also it can effectively distinguishes micron-scale defects and has good defect recognition performance. The overall average recognition rate reached to 93.3%.

Design of Bamboo Strip Detection System Based on Labview and Matlab Mixed Programming

2013 ◽  
Vol 302 ◽  
pp. 772-775 ◽  
Author(s):  
Li Ping He ◽  
Shu Xiang Song ◽  
Lei Liu ◽  
Xian Ming Jiang
Keyword(s):  
Real Time ◽  
Detection Rate ◽  
Surface Defects ◽  
Detection System ◽  
Detection Accuracy ◽  
The Novel ◽  
Large Area ◽  
Accuracy Requirement ◽  
Detection Technology ◽  
Mixed Programming

According to the domestic situation that bamboo strip detection technology is artificial intervention and low automation, the novel automatic bamboo strip detection system is designed based on Labview and Matlab mixed programming. The real-time detection on bamboo surface defects is realized in the system such as serious damage, stripe, scratch, large area dim. Moreover, the system provides more than 92% detection accuracy and eight strips per second detection rate, both of which can meet the accuracy requirement of practical production. In general, this paper provides a new kind of method for detection system.

Design and Implementation of the Cold-Rolled Aluminum Plate Surface On-Line Defect Detection System

2013 ◽  
Vol 712-715 ◽  
pp. 2323-2326
Author(s):  
Xing Guang Qi ◽  
Hai Lun Zhang ◽  
Xiao Ting Li
Keyword(s):  
High Speed ◽  
Surface Defects ◽  
Detection System ◽  
Aluminum Plate ◽  
Gigabit Ethernet ◽  
Accurate Detection ◽  
High Processing Speed ◽  
Rolled Aluminum ◽  
On Line ◽  
Cold Rolled

This paper presents an on-line surface defects detection system based on machine vision, which has high speed architecture and can perform high accurate detection for cold-rolled aluminum plate. The system consists of high speed camera and industrial personal computer (IPC) array which connected through Gigabit Ethernet, achieved seamless detection by redundant control. In order to acquire high processing speed, single IPC as processor receives from and deals with only one or two cameras' image. Experimental results show that the system with high accurate detection capability can satisfy the requirement of real time detection and find out the defects on the production line effectively.

scholarly journals A Low Cost Vision-Based Road-Following System for Mobile Robots

2018 ◽  
Vol 8 (9) ◽  
pp. 1635 ◽  
Author(s):  
Haojie Zhang ◽  
David Hernandez ◽  
Zhibao Su ◽  
Bo Su
Keyword(s):  
Mobile Robots ◽  
Unscented Kalman Filter ◽  
Detection System ◽  
Tracking System ◽  
Low Cost ◽  
Recognition Rate ◽  
Road Detection ◽  
The Road ◽  
Road Following ◽  
Following Error

Navigation is necessary for autonomous mobile robots that need to track the roads in outdoor environments. These functions could be achieved by fusing data from costly sensors, such as GPS/IMU, lasers and cameras. In this paper, we propose a novel method for road detection and road following without prior knowledge, which is more suitable with small single lane roads. The proposed system consists of a road detection system and road tracking system. A color-based road detector and a texture line detector are designed separately and fused to track the target in the road detection system. The top middle area of the road detection result is regarded as the road-following target and is delivered to the road tracking system for the robot. The road tracking system maps the tracking position in camera coordinates to position in world coordinates, which is used to calculate the control commands by the traditional tracking controllers. The robustness of the system is enhanced with the development of an Unscented Kalman Filter (UKF). The UKF estimates the best road borders from the measurement and presents a smooth road transition between frame to frame, especially in situations such as occlusion or discontinuous roads. The system is tested to achieve a recognition rate of about 98.7% under regular illumination conditions and with minimal road-following error within a variety of environments under various lighting conditions.

scholarly journals A Modeling Method for Automatic Extraction of Offshore Aquaculture Zones Based on Semantic Segmentation

2020 ◽  
Vol 9 (3) ◽  
pp. 145 ◽  
Author(s):  
Baikai Sui ◽  
Tao Jiang ◽  
Zhen Zhang ◽  
Xinliang Pan ◽  
Chenxi Liu
Keyword(s):  
Recognition Rate ◽  
Semantic Segmentation ◽  
Recognition Algorithm ◽  
Identification Accuracy ◽  
Generative Adversarial Networks ◽  
Automatic Extraction ◽  
Large Area ◽  
Marine Aquaculture ◽  
Floating Raft ◽  
Offshore Aquaculture

Monitoring of offshore aquaculture zones is important to marine ecological environment protection and maritime safety and security. Remote sensing technology has the advantages of large-area simultaneous observation and strong timeliness, which provide normalized monitoring of marine aquaculture zones. Aiming at the problems of weak generalization ability and low recognition rate in weak signal environments of traditional target recognition algorithm, this paper proposes a method for automatic extraction of offshore fish cage and floating raft aquaculture zones based on semantic segmentation. This method uses Generative Adversarial Networks to expand the data to compensate for the lack of training samples, and uses ratio of green band to red band (G/R) instead of red band to enhance the characteristics of aquaculture spectral information, combined with atrous convolution and atrous space pyramid pooling to enhance the context semantic information, to extract and identify two types of offshore fish cage zones and floating raft aquaculture zones. The experiment is carried out in the eastern coastal waters of Shandong Province, China, and the overall identification accuracy of the two types of aquaculture zones can reach 94.8%. The results show that the method proposed in this paper can realize high-precision extraction both of offshore fish cage and floating raft aquaculture zones.

An Automatic Spike Detection System Based on Elimination of False Positives Using the Large-Area Context in the Scalp EEG

2011 ◽  
Vol 58 (9) ◽  
pp. 2478-2488 ◽  
Author(s):  
Zhanfeng Ji ◽  
T. Sugi ◽  
S. Goto ◽  
Xingyu Wang ◽  
A. Ikeda ◽  
...  
Keyword(s):  
Detection System ◽  
False Positives ◽  
Spike Detection ◽  
Large Area ◽  
Scalp Eeg

REGULATION OF FACTOR V (FV) EXPRESSION IN HUMAN MEGAKARYOCYTES

1987 ◽  
Author(s):  
A Gewirtz ◽  
C L shepiro ◽  
R Bovd ◽  
R W Colman
Keyword(s):  
Cell Size ◽  
Detection System ◽  
Correlation Coefficients ◽  
Coefficient Of Determination ◽  
Maturation Stage ◽  
Factor V ◽  
Large Area ◽  
Dna Quantitation ◽  
Tetradecanoyl Phorbol Acetate

We have suggested that synthesis of FY by human megakaryocytes (MEGS), is a maturation relrted event. This is based on our finding that when MEGS are cloned from progenitor cells in vitro in FY depleted medium, FY is immunochemically detectable only in morphologically recognizable (mature) cells (Blood 67:1639, '86). The stimuli which induce FY synthesis in MEGS are unknown, but if they are related or linked to factors which regulate terminal maturation processes cellular FY levels might increase as the maturation routine proceeds. To test this hypothesis, mature human MEGS were isolated from normal bone marrow by counterflow centrifugel elutrietion, deposited onto gloss slides by cytocentri-fugation, and then fixed in methanol:acetone. Individual cells were then staged, geometric meon cell diometer (size) determined with on opticol fylor, end FY end DNA levels measured. FV expression in a large area of the MEG (38 urn in diameter) was semi-quantitated by microspectrophotometry (MSPEC) using a sensitive Texas Red labeled streptavidin-biotin detection system and a monoclonal antibody probe (B10) directed against the non-binding FY activation peptide (150,000 kd). Cells were then reacted with Chromomycin A3 to allow for simultaneous DNA quantitation by MSPEC in the same cell. Correlation coefficients (r) and coefficient of determination [r2] were computer generated to discern potential relationships between FY expression, and MEG maturation stage, size or ploidy level in a total of 532 MEGS. Characteristics of the population, and r/r2 vs. MEG FV content ere shown below:r/r2 values did not significantly change when total MEG FY content was measured in 100 additional MEGS. Therefore, MEG FY levels varied independently with cell size and ploidy, and did not appear to correlate with degree of mature MEG maturation as determined by standard critera. In two of four preliminary experiments, low dose (8nM ql2h × 4 doses) tetradecanoyl phorbol acetate augmented both the number of MEGS expressing FV, and the level of FY expressed per individual cell. We conclude from these data that once FV synthesis is initiated, FY synthesis and events relating to final cell size and ploidy development are regulated independently. Our data also suggest that MEG FV synthesis may be regulated in part by the phosphoinositide-protein kinase C system.

scholarly journals An Enhanced Detection System of Drill Rod Bending Degree Based on Two-Dimensional Laser

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 370
Author(s):  
Lingling Wu ◽  
Guojun Wen ◽  
Yudan Wang ◽  
Xinjian Xu
Keyword(s):  
Detection Method ◽  
Detection System ◽  
Least Square Method ◽  
Least Square ◽  
Two Dimensional ◽  
Optical Inspection ◽  
Section Shape ◽  
Mechanical Bending ◽  
Low Efficiency ◽  
Displacement Based

Drill rod straightness has to be strictly controlled and the maximum bending degree detection needs to be used in the straightening process. The mechanical bending degree measurement depends on machinery instruments and workers’ experience, often with low efficiency and precision. While the optical inspection, as a non-contact detection method, with higher precision and lower installation accuracy requirements, is frequently applied in the online detection system. Based on this, an enhanced bending degree detection system for a drill rod is proposed in this paper. Compared to the existing detection system, the main progress is to use a two-dimensional laser to quickly obtain arc profile data and fit with ellipse. Segment inspection idea is also utilized is this system as the camera that could obtain the whole drill rod in one shot needs extremely high resolution and price. A specialized algorithm is designed to fit the cross-section shape and whole centerline displacement based on the least square method. Some laboratory tests are conducted to verify this detection system, findings of which are compared to manual measured results. The maximum bending degree error is 2.14 mm and the maximum position error is 8.21 mm, which are both within the tolerance of error. Those results show the feasibility and precision of this enhanced detection system.

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