Condition Monitoring of Overhead Line Equipment (OHLE) Structures Using Ground-Bourne Vibrations from Train Passages
The most modern railway systems have fully adopted clean energy for train and track operations. Trains or rolling stocks are powered by electricity through the overhead wire or the third rail on ground. Commonly, the overhead line equipment (OHLE), which supplies electric power to the trains, is widely adopted in new railway networks around the world since its system enables trains to operate smoothly while track inspectors can safely work on tracks. The OHLE is supported by mast structure, which is located at the lineside along the track. The mast structure is often made of steel structure built on mat or pile foundation. Due to the train passages, ground-bourne periodic forces may cause damage to the OHLE structure especially mast structure, connections and its foundation, which can lead to operational failure of train electrification. On this ground, the structural integrity of mast structures must be inspected regularly. In this study, the modal analysis is used in order to identify the mode shapes and natural frequencies of the mast structure. A mast structure with varying rotational soil stiffness is used to construct dynamic influential lines for soil-structure integrity prediction. Finite element model updating technique has been used to perform modal analysis and modal parameter identification. This paper presents the integrated numerical of three-dimensional mast structure considering soil-structure interaction to evaluate the condition of OHLE structures for maintenance planning. The outcome of this study will help civil and track engineers to effectively and efficiently inspect OHLE structures using ground borne vibrations from train passages.
The authors are sincerely grateful to the European Commission for the financial sponsorship of the H2020-RISE Project No. 691135 “RISEN: Rail Infrastructure Systems Engineering Network”, which enables a global research network that tackles the grand challenge of railway infrastructure resilience and advanced sensing in extreme environments (www.risen2rail.eu) (Kaewunruen et al. 2016).
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