| Autor: |
Vijayalakshmi, G., Gayathri, J., Senthilkumar, K. K., Kalanandhini, G., Aravind, A. R. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 5/19/2022, Vol. 2393 Issue 1, p1-8, 8p |
| Abstrakt: |
During the past years, there is an increased derailment scenario due to track faults. To resolve this issue, an intelligent visualization-built rail inspection system, which is automatic and real time has been developed. The system strongly notices important rail components like draws, tie plates and nuts and bars which helps in rail fastener with more accurateness and effectiveness. In current years, the railway transportation system developed as one of the chief resources of transport. Hence, the safety in the railway line is of more important. However, due to the expected multiple breaks of elastic rail clips in a fixed rail, accidents may rise when a train is permitted through the track. To attain this goal, a group of image analytics have been developed first and then planned an original universal optimized outline to associate evidence from numerous television camera, sensors and remoteness gauging device to further progress the detection routine. Complete track analyses have been ensured and provide clearance to the train motion only when the track health is perfect. This paper aims at completely reducing the human interference. Quantitative analysis has been completed on a big image set of data taken with diverse track and light circumstances and on a real–time field test. The fist system used to handle and resolve both module and omission finding and exception handling problems. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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