Published September 1, 2019 | Version v1
Journal article

Study of Weight in Motion Sensor for Railroad Crossing Warning System Using Artificial Neural Network

  • 1. Diploma 3 Teknik Informatika Sebelas Maret University, Jl. Ir. Sutami 36A Kentingan Jebres Surakarta 57126 (Indonesia)
  • 2. Physics Department of Post Graduate Program Sebelas Maret University, Jl. Ir. Sutami 36A Kentingan Jebres Surakarta 57126 (Indonesia)

Description

IThe risk of accidents in the railway, especially on unmanned railroad crossing, are still high. A train arrival on railroad crossing warning system is indispensable. The warning system will detect train arrival on the railroad crossing and issue a warning to the crossers. A sensor based on optical fiber Weight in Motion (WIM) is proposed. This paper presents a design of a railroad crossing warning system based on WIM sensor. The sensor placed under the railroad tracks and detects vibrations footprints transmitted along those rails. Artificial Neural Network (ANN) is used to process the signal pattern of the WIM system output. By using ANN, the vibration footprint pattern was classified and used as on-sensor train detection. As the train detected, the arrival time of the train on the raiload crossing was estimated. The result is a warning system which can detect train arrival on the railroad crossing and issue a warning signal. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1757-899X/578/1/012086

Additional details

Publishing Information

Journal Title
IOP Conference Series. Materials Science and Engineering (Online)
Journal Volume
578
Journal Issue
1
Journal Page Range
[4 p.]
ISSN
1757-899X

Conference

Title
International Conference on Advanced Materials for Better Future 2018
Dates
15-16 Oct 2018
Place
Surakarta (Indonesia)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52113045
Subject category
S42: ENGINEERING;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ALARM SYSTEMS; DESIGN; NEURAL NETWORKS; OPTICAL FIBERS; SENSORS; SIGNALS
Descriptors DEC
FIBERS