An Automatic Detection Algorithm for Surface Defects in TFT-LCD

2013 ◽  
Author(s):  
Ling Ma ◽  
Wei Liu ◽  
Yumin Liu ◽  
Huiqin Jiang
Keyword(s):  
Surface Defects ◽  
Automatic Detection ◽  
Detection Algorithm ◽  
Automatic Detection Algorithm

Automatic Detection of Corrugation: Preliminary Results in the Dutch Network Using Axle Box Acceleration Measurements

2015 ◽  
Author(s):  
Shaoguang Li ◽  
Alfredo Núñez ◽  
Zili Li ◽  
Rolf Dollevoet
Keyword(s):  
Automatic Detection ◽  
Detection Algorithm ◽  
System Response ◽  
Growth Mechanisms ◽  
Preliminary Results ◽  
Rail Network ◽  
Track System ◽  
Good Potential ◽  
Automatic Detection Algorithm ◽  
Wheel Track

Short pitch corrugation is commonly seen in all kinds of tracks. There is not yet a conclusive explanation in the literature for its initiation and growth mechanisms. In this paper, we use an axle box acceleration (ABA) measurement system to detect corrugation. ABA can be easily implemented in operational trains, providing direct and reliable health monitoring of the track. We have extended a detection algorithm for rail surface local short wavelength defects to also detect short pitch corrugation, which is a continuous defect over the track. A 3D transient FE wheel-track model is employed to find theoretical signature tunes of the wheel-track system response when passing over a short pitch corrugation. Numerical simulations agree with ABA measurement obtained in the Dutch rail network. Based on the signature tune identified, an automatic detection algorithm is developed. Preliminary results with the algorithm are discussed. Field observations show a good potential of the detection algorithm to be used by inframanagers, to detect and monitor corrugation.

scholarly journals EP-1592: Automatic detection algorithm for MLC position using a single EPID image in a daily QA program

2016 ◽  
Vol 119 ◽  
pp. S740
Author(s):  
P. Colleoni ◽  
A. Gambirasio ◽  
C. Bianchi ◽  
M. Fortunato ◽  
S. Andreoli
Keyword(s):  
Automatic Detection ◽  
Detection Algorithm ◽  
Automatic Detection Algorithm

scholarly journals A practical approach to tramway track condition monitoring: vertical track defects detection and identification using time-frequency processing technique

2018 ◽  
Vol 13 (s1) ◽  
pp. 135-146
Author(s):  
Péter Bocz ◽  
Ákos Vinkó ◽  
Zoltán Posgay
Keyword(s):  
Surface Defects ◽  
Detection Algorithm ◽  
Processing Technique ◽  
False Alarms ◽  
Distribution Analysis ◽  
Time Frequency ◽  
Detection And Identification ◽  
Track Condition ◽  
Automatic Detection Algorithm ◽  
Track Irregularities

Abstract This paper presents an automatic method for detecting vertical track irregularities on tramway operation using acceleration measurements on trams. For monitoring of tramway tracks, an unconventional measurement setup is developed, which records the data of 3-axes wireless accelerometers mounted on wheel discs. Accelerations are processed to obtain the vertical track irregularities to determine whether the track needs to be repaired. The automatic detection algorithm is based on time–frequency distribution analysis and determines the defect locations. Admissible limits (thresholds) are given for detecting moderate and severe defects using statistical analysis. The method was validated on frequented tram lines in Budapest and accurately detected severe defects with a hit rate of 100%, with no false alarms. The methodology is also sensitive to moderate and small rail surface defects at the low operational speed.

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