ARDIS: Knowledge-Based Dynamic Architecture for Real-Time Surface Visual Inspection

2009 ◽  
pp. 395-404 ◽  
Author(s):  
D. Martín ◽  
M. Rincón ◽  
M. C. García-Alegre ◽  
D. Guinea
Keyword(s):  
Real Time ◽  
Visual Inspection ◽  
Dynamic Architecture ◽  
Knowledge Based

Augmented reality for enhanced visual inspection through knowledge-based deep learning

2020 ◽  
pp. 147592172097698
Author(s):  
Shaohan Wang ◽  
Sakib Ashraf Zargar ◽  
Fuh-Gwo Yuan
Keyword(s):  
Deep Learning ◽  
Pilot Study ◽  
Augmented Reality ◽  
Damage Detection ◽  
Real Time ◽  
Visual Inspection ◽  
Probability Of Detection ◽  
Two Stage ◽  
Knowledge Based ◽  
Smart Glasses

A two-stage knowledge-based deep learning algorithm is presented for enabling automated damage detection in real-time using the augmented reality smart glasses. The first stage of the algorithm entails the identification of damage prone zones within the region of interest. This requires domain knowledge about the damage as well as the structure being inspected. In the second stage, automated damage detection is performed independently within each of the identified zones starting with the one that is the most damage prone. For real-time visual inspection enhancement using the augmented reality smart glasses, this two-stage approach not only ensures computational feasibility and efficiency but also significantly improves the probability of detection when dealing with structures with complex geometric features. A pilot study is conducted using hands-free Epson BT-300 smart glasses during which two distinct tasks are performed: First, using a single deep learning model deployed on the augmented reality smart glasses, automatic detection and classification of corrosion/fatigue, which is the most common cause of failure in high-strength materials, is performed. Then, in order to highlight the efficacy of the proposed two-stage approach, the more challenging task of defect detection in a multi-joint bolted region is addressed. The pilot study is conducted without any artificial control of external conditions like acquisition angles, lighting, and so on. While automating the visual inspection process is not a new concept for large-scale structures, in most cases, assessment of the collected data is performed offline. The algorithms/techniques used therein cannot be implemented directly on computationally limited devices such as the hands-free augmented reality glasses which could then be used by inspectors in the field for real-time assistance. The proposed approach serves to overcome this bottleneck.

scholarly journals Real-Time Train Wheel Condition Monitoring by Fiber Bragg Grating Sensors

2011 ◽  
Vol 8 (1) ◽  
pp. 409048 ◽  
Author(s):  
Chuliang Wei ◽  
Qin Xin ◽  
W. H. Chung ◽  
Shun-yee Liu ◽  
Hwa-yaw Tam ◽  
...  
Keyword(s):  
Fiber Bragg Grating ◽  
Real Time ◽  
Visual Inspection ◽  
Condition Index ◽  
Bragg Grating ◽  
Time System ◽  
Real Time System ◽  
Fiber Bragg Grating Sensors ◽  
Extensive Field ◽  
The Cost

Wheel defects on trains, such as flat wheels and out-of-roundness, inevitably jeopardize the safety of railway operations. Regular visual inspection and checking by experienced workers are the commonly adopted practice to identify wheel defects. However, the defects may not be spotted in time. Therefore, an automatic, remote-sensing, reliable, and accurate monitoring system for wheel condition is always desirable. The paper describes a real-time system to monitor wheel defects based on fiber Bragg grating sensors. Track strain response upon wheel-rail interaction is measured and processed to generate a condition index which directly reflects the wheel condition. This approach is verified by extensive field test, and the preliminary results show that this electromagnetic-immune system provides an effective alternative for wheel defects detection. The system significantly increases the efficiency of maintenance management and reduces the cost for defects detection, and more importantly, avoids derailment timely.

scholarly journals HaemoKBS: A knowledge-based system for real-time, continuous categorisation of adverse reactions in blood recipients

2021 ◽  
Vol 423 ◽  
pp. 756-767
Author(s):  
Augusto Ramoa ◽  
Jorge Condeço ◽  
Florentino Fdez-Riverola ◽  
Anália Lourenço
Keyword(s):  
Real Time ◽  
Adverse Reactions ◽  
Knowledge Based System ◽  
Knowledge Based

Real-time fuzzy-knowledge-based control of Baker's yeast production

1995 ◽  
Vol 45 (2) ◽  
pp. 135-143 ◽  
Author(s):  
Terhi Siimes ◽  
Pekka Linko ◽  
Camilla von Numers ◽  
Mikio Nakajima ◽  
Isao Endo
Keyword(s):  
Real Time ◽  
Baker’S Yeast ◽  
Baker's Yeast ◽  
Knowledge Based ◽  
Yeast Production ◽  
Fuzzy Knowledge

Knowledge-based systems for real-time process control: The MIP project

1992 ◽  
Vol 17 ◽  
pp. 391-396
Author(s):  
X. Alamán ◽  
S. Romero ◽  
C. Aguirre ◽  
P. Serrahima ◽  
R. Muñoz ◽  
...  
Keyword(s):  
Process Control ◽  
Real Time ◽  
Knowledge Based Systems ◽  
Time Process ◽  
Knowledge Based
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