In Situ Switch Blade Displacement Measurements in A Railway Turnout for Short-Term Monitoring Application

سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 51

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شناسه ملی سند علمی:

JR_IJRRS-6-1_003

تاریخ نمایه سازی: 5 آذر 1402

چکیده مقاله:

Due to the importance of the fundamental role of turnouts in network operations and their higher vulnerability than other assets, turnout condition monitoring is necessary for reliability-centered maintenance. Along with periodic visual inspections, real-time infrastructure condition detection can help introduce the structure's performance so that infrastructure maintenance is more reliable. A new approach for railway turnout pass-by condition detection is provided based on statistical process control (SPC) of damage-sensitive features (DSF) using switchblade lateral displacement (BLD) measurements.  BLD time series data is modeled using a neural network model to extract DSF. This approach is applied to ۳۳ passenger trains. The results of the proposed approach are validated by analysis of BLD and switch rod force sensor outputs. This method can be applied in turnout short-term condition monitoring for condition detection, leading to preventive maintenance, proper track operation management, and increased reliability.

نویسندگان

Kaveh Mehrzad

Avand Barzin Knowledge Enterprise, Tehran, Iran

Shervan Ataei

School of Railway Engineering, Iran University of science and technology, Tehran, Iran

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  • Ma, A. A. Mashal, and V. L. Markine, "Modelling and ...
  • T. Torstensson, G. Squicciarini, M. Krüger, B. A. Pålsson, J. ...
  • A. Boogaard, Z. Li, and R. P. B. J. Dollevoet, ...
  • Liu, V. L. Markine, H. Wang, and I. Y. Shevtsov, ...
  • Jing, M. Siahkouhi, K. Qian, and S. Wang, "Development of ...
  • Grossoni, P. Hughes, Y. Bezin, A. Bevan, and J. Jaiswal, ...
  • Ma, P. Wang, J. Xu, and R. Chen, "Effect of ...
  • Ma, P. Wang, J. Xu, and R. Chen, "Comparison of ...
  • UFC ۴-۸۶۰-۰۳ Railroad Track Maintenance And Safety Standard, U. S. ...
  • Bornn, C. R. Farrar, G. Park, and K. Farinholt, "Structural ...
  • Mei, A. Mita, and J. Zhou, "An improved substructural damage ...
  • Mehrzad, "Presenting a prediction model for the safe passage speed ...
  • Mehrzad and S. Ataei, "Railway crossing vertical vibration response prediction ...
  • Ataei and K. Mehrzad, "Permanent condition Monitoring of Yatri P۲ ...
  • Hudson, B. Hagan, Deep Learning Toolbox, Getting Started Guide Mark, ...
  • R. Joseph, "Optimal ratio for data splitting," Statistical Analysis and ...
  • C. Navidi, Statistics for engineers and scientists, ۳th ed. New ...
  • W. Hines, D. C. Montgomery, D. M. Goldsman, and C. ...
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