Influence of vision measurement system spatial configuration on measurement uncertainty, based on the example of electric traction application

Abstract Technical diagnostics plays a significant role in ensuring operational reliability of electrified rail transport. The most critical point in the transmission of electric energy to vehicles is the sliding contact of the current collector with the traction network. For this reason, work is currently being carried on new measuring methods, whose appliance allows for more complete diagnostics of the contact line and current collectors, as well as for monitoring the co-operation of these elements. Each measurement method must be analysed for level of uncertainty, so that the obtained measurement results are reliable. This paper presents a theoretical analysis of the influence of the visual measuring method spatial configuration on the obtained level of measurement uncertainty. This method is designed for measurement contact wire displacements. The results of theoretical analysis were verified by a measurement experiment performed with the use of the Last Square Fitting Algorithm. Finally, the results of sample measurement results obtained at the laboratory tests stand, which proved the practical usefulness of the discussed measurement method, were presented.

[1]  Jacek Skibicki.  The new version of contact-less method for localisation of catenary contact wire - theoretical assumption , 2013 .

[2]  Young Park,et al.  New Monitoring Technologies for Overhead Contact Line at 400 km·h −1 , 2016 .

[3]  M. Mizan,et al.  Monitoring of current collectors on the railway line , 2016 .

[4]  T. Dong,et al.  Measuring principle of vertical target density based on single linear array CCD camera , 2014 .

[5]  Elzbieta Pastucha,et al.  Catenary System Detection, Localization and Classification Using Mobile Scanning Data , 2016, Remote Sensing.

[6]  Hanseok Ko,et al.  Video-Based Dynamic Stagger Measurement of Railway Overhead Power Lines Using Rotation-Invariant Feature Matching , 2015, IEEE Transactions on Intelligent Transportation Systems.

[7]  Leszek Jarzebowicz,et al.  Analysis of Measurement Errors in Rail Vehicles’ Pantograph Inspection System , 2016 .

[8]  Luca Sani,et al.  Hough transform and thermo-vision for monitoring pantograph-catenary system , 2006 .

[9]  Emanuele Zappa,et al.  Modeling Uncertainty for a Vision System Applied to Vibration Measurements , 2016, IEEE Transactions on Instrumentation and Measurement.

[10]  Jacek Skibicki,et al.  Analysis of measurement uncertainty for contact-less method used to measure the position of catenary contact wire, performed with the use of Monte Carlo method , 2017 .

[11]  Mehmet Karaköse,et al.  A New Experimental Approach Using Image Processing-Based Tracking for an Efficient Fault Diagnosis in Pantograph–Catenary Systems , 2017, IEEE Transactions on Industrial Informatics.

[12]  Luca Sani,et al.  Wavelet multiresolution analysis for monitoring the occurrence of arcing on overhead electrified railways , 2003 .

[13]  Mostafa Arastounia,et al.  Automated Recognition of Railroad Infrastructure in Rural Areas from LIDAR Data , 2015, Remote. Sens..

[14]  Zhigang Liu,et al.  A High-Precision Detection Approach for Catenary Geometry Parameters of Electrical Railway , 2017, IEEE Transactions on Instrumentation and Measurement.

[15]  Peng Wang,et al.  Distortion correction for the orthogonally-splitting-imaging pose sensor , 2015 .

[16]  Ilhan Aydin,et al.  A new approach based on firefly algorithm for vision-based railway overhead inspection system , 2015 .