Replacement condition detection of railway point machines using an electric current sensor

18Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.

Abstract

Detecting replacement conditions of railway point machines is important to simultaneously satisfy the budget-limit and train-safety requirements. In this study, we consider classification of the subtle differences in the aging effect—using electric current shape analysis—for the purpose of replacement condition detection of railway point machines. After analyzing the shapes of after-replacement data and then labeling the shapes of each before-replacement data, we can derive the criteria that can handle the subtle differences between “does-not-need-to-be-replaced” and “needs-to-be-replaced” shapes. On the basis of the experimental results with in-field replacement data, we confirmed that the proposed method could detect the replacement conditions with acceptable accuracy, as well as provide visual interpretability of the criteria used for the time-series classification.

Cite

CITATION STYLE

APA

Sa, J., Choi, Y., Chung, Y., Kim, H. Y., Park, D., & Yoon, S. (2017). Replacement condition detection of railway point machines using an electric current sensor. Sensors (Switzerland), 17(2). https://doi.org/10.3390/s17020263

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free