Abstract

Purpose This paper aims to study the affecting factors on bird nesting on electronic railway catenary lines and the impact of bird nesting events on railway operation. Design/methodology/approach First, with one year’s bird nest events in the form of unstructured natural language collected from Shanghai Railway Bureau, the records were structured with the help of python software tool. Second, the method of root cause analysis (RCA) was used to identify all the possible influencing factors which are inclined to affect the probability of bird nesting. Third, the possible factors then were classified into two categories to meet subsequent analysis separately, category one was outside factors (i.e. geographic conditions related factors), the other was inside factors (i.e. railway related factors). Findings It was observed that factors of city population, geographic position affect nesting observably. Then it was demonstrated that both location and nesting on equipment part have no correlation with delay, while railway type had a significant but low correlation with delay. Originality/value This paper discloses the principle of impacts of nest events on railway operation.

Highlights

  • With the development of high-speed railway, it plays an increasingly important role in national transportation system

  • The corresponding probability density and cumulative probability distributions are depicted in Figure 9, which are used for evaluating the delay probability when a bird nesting event happens on normal-speed railway or high-speed railway. t0.9 means 90% of delays occur

  • This paper analyzed all the possible factors influencing on bird nesting on railway catenary lines, with obtained one year’s Shanghai region railway operation events data from Shanghai Railway Bureau and geographic data from the internet, to find out which factors had a statistically significant impact on probability of bird nesting and the characteristics of nesting events

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Summary

Introduction

With the development of high-speed railway, it plays an increasingly important role in national transportation system. According to the difference in data sources and analysis methods, two categories are decided, i.e. railway related factors and geographic characters; use the brainstorm method to find the reasons under each category, including nesting time, nesting on the equipment part, railway type, the delay of the nest events on train operation, nesting location (station or section), geographic position and environmental factors; Consider the factors that may contribute to each cause and put them on a line from the cause. For the sake of the convenience of expression, the factors extracted from the nest event records are given as the general term “inside factors”, including nesting location (station, section), event time (discovery time, responding time, end time), nesting on equipment parts of catenary lines (supporting column, hard horizontal beam, compensation device, pedestal, protecting mesh, disconnector switch, return line shoulder, insulator, etc.), railway type.

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