2014 International Conference and Exposition on Electrical and Power Engineering (EPE) 2014
DOI: 10.1109/icepe.2014.6970004
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Algorithm for automatic wear estimation of railway contact strips based on 3D scanning results

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Cited by 22 publications
(10 citation statements)
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“…This paper is related to previous works [4], [5], which concern CCS diagnostics. In [4] authors proposed a new Laser Scanning Inspection System (LSIS) for CCS diagnostics.…”
Section: Introductionmentioning
confidence: 81%
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“…This paper is related to previous works [4], [5], which concern CCS diagnostics. In [4] authors proposed a new Laser Scanning Inspection System (LSIS) for CCS diagnostics.…”
Section: Introductionmentioning
confidence: 81%
“…The proposed test profiles are based on a desire trapezoidal shape corresponding to a factory new CCS [5]. The desire trapezoidal profile is combined with defect pattern, located in the middle.…”
Section: A a Damaged Ccs Test Profilementioning
confidence: 99%
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“…The system uses a specialized camera and a laser line generator to acquire 3D scan of CCS surface. A specialized data processing algorithm has been applied for automatic CCS Manuscript received 18 September, 2015; accepted 10 March, 2016. wear estimation [9]. During the research a question has arisen on the accuracy of the estimated wear value.…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, diagnostics of current collectors is usually performed with the use of stationary diagnostic stands, where static characteristics of the collector and suspension of the slipper are tested [9]. Evaluation of the technical condition of strips is carried out using 3D visualization devices [10][11][12][13]. On the other hand, correctness of cooperation between the collector and the contact line can be monitored with the use of stationary measurement points which help to determine the correctness of the collector's adjustments based on displacements of the contact line caused by its impact when a vehicle passes through the diagnostic stand.…”
Section: Introductionmentioning
confidence: 99%