RAILWAY SECURITY SYSTEM
BASED ON WIRELESS SENSOR NETWORKS: STATE OF THE ART
ABSTRACT
Railways are
large infrastructures and are the prime mode of transportation in many
countries. The railways have become a prime means of transportation owing to
their capacity, speed, and reliability. Even a small improvement in performance
of railways has significant economic benefits to rail industry. Thus, a proper
maintenance strategy is required to govern optimization of inspection frequency
and/or improvement in skill and efficiency. Accidents happening due to track
breaking have been a big problem for railways for life security and timely
management of services. This breakage needs to be identified in real time
before a train actually comes near to the broken track and get subjected to an
accident. In this paper, different kinds of rail defects inspection and
maintenance methods are described and a basic algorithm is readdressed that
makes use of wireless acoustic sensors for detecting cracks and breakages in
the railway tracks.
Keywords: Cracks detection, railway security, acoustic sensor
INTRODUCTION
Railways
comprise a large infrastructure and are an important mode of transportation in
many countries. The railways have become a new means of transportation owing to
their capacity, speed, and reliability, being closely associated with passenger
and goods transportation; they have high risk associated with them in terms of
human lives and cost of assets. The poor maintenance of the railways can lead
to accidents. New technologies for railways and better safety measures are
introduced time to time but still accidents do occur. Thus, a proper strategy
is required for maintenance and inspection of tracks.
Detection and
maintenance of rail defects are major issues for the rail community all around
the world. The defects mainly include weld problems, internal defects worn out
rails, head checks, squats, spalling and shelling, corrugations and rolling
contact fatigue (RCF) initiated problems such as surface cracks. If these
defects are not handled and corrected they can lead to rail breaks and
accidents. There are numerous challenges to rail community and the
infrastructure maintenance people such as to perform effective inspection and
cost effective maintenance decisions. If these issues are taken care of
properly, inspection and maintenance decisions can reduce potential risk of
rail breaks and derailment.
TECHNIQUES
FOR INSPECTING CRACKS IN RAILWAY TRACKS
Long Range
Ultrasonic Testing (LRUT)
Authors in paper
[4] focus on the limitations of methods in their ability to detect defects in
the rail foot, especially in the side edges away from the region directly below
the web and how the LRUT method provides a significant improvement for the
same.
Long Range
Ultrasonic Testing (LRUT) technique is proposed as a complimentary inspection
technique to examine the foot of rails, especially in track regions where
corrosion and associated fatigue cracking is likely, such as at level
crossings. LRUT technique is found to be suitable for examining inaccessible
areas of railway tracks such as areas where corrosion occurs and susceptible
areas of fatigue cracking. In different parts of the rail section (such as
head, web and foot) properties of guided waves are used and are examined for
their capability to detect defects in each part.
A suitable array
of transducers is developed that is able to generate selected guided wave modes
in rails which allow a reliable long range inspection of the rail. The
characteristics of ultrasonic guided waves in the rail complex geometrical
profile have been identified.
Vision Based System
A rail track
inspection technique using automated video analysis is proposed. The aim of the
system is to replace manual visual checks performed by the railway engineers
for track inspection. A combination of image processing and analysis methods is
used in the paper to achieve high performance automated rail track inspection.
This paper focuses on the issues of finding missing clips and finding blue
clips which have been recently replaced in place of damaged clips.
The objective of
the algorithm is to automatically find clips in video sequences and thereafter
recognize whether they are broken and if they are new or old as indicated by
their color. Metal clips hold the rail track to the sleepers on the ground.
Clips are searched to locate their position. Some clips on the track may be
broken or missing due to excessive strain on them as the train moves on the
track which may lead to the track failure these missing clips are identified.
The clips used may be of different color depending on whether it is new (blue
color) or old (grey color). So a video color analysis is done on the clips and
the results are given to track maintenance engineers.
The
main image pre-processing steps in the recognition of clips include smoothing,
edge detection, and short line removal.
The
irregularities in the Railway track gauge reduces the service life of rail and
vehicle, and even result in vehicle falling off rail or wheel trapping, which
causes driving accidents. A dynamic inspection method of track gauge based on
computer vision is developed in. The inspection system is constructed by using
four CCD (Charge-coupled Device) cameras and two red laser sector lights. The
inspection principle and corresponding calibration method of inspection system
are analyzed. Several image processing technologies such as image component
extraction, differential, adaptive iteration threshold, dilation and thinning
are used to extract gauge points.
Experiment
results have proved that the proposed inspection method is capable of fast obtaining
track gauge value with high accuracy and repeatability, and meets the
requirement of dynamic inspection for track gauge.
The method
proposed in the paper confirms the calibration method for track gauge
inspection by. The method strictly controls the change of railway gauge and
provides an effective inspection method with high precision to railway
engineers.
Train-Mounted
GPR
A
technique based on Ground-penetrating radar (GPR) is used for obtaining
quantitative information about the depth and degree of deterioration of the
track. This paper aims at automating the processing and interpretation of data
to the extent whereby on-site interpretations may be achieved with minimal intervention
of the expert. This is done through the development of new image and signal
processing tools specifically for GPR data and the range of anomalies found on
the track bed.
For
monitoring track conditions and other infrastructure assets the most efficient
way is by means of a train, which can collect data for many parameters
simultaneously, where possible at normal line speed. A multichannel ground-
penetrating radar system is presented in the paper which is capable of
operating at speeds of up to 200 kmph. A road-rail variant of the system is
also presented which can collect up to 6 simultaneous continuous channels
across the track, and can deliver on-site interpretation of ballast thickness
and quality, irregularities, weak spots and utilities.
Novel
multivariate signal and image processing techniques are used that can
automatically detect, quantify and map variations in ballast depth and
condition. To enable automatic characterization and classification of regions
of interest within the radar grams, multi-resolution texture analysis
techniques are applied. The proposed system can probe the ballast both
underneath and between the sleepers, thus potential problems can be identified
with individual sleepers.
LED-LDR
Assembly
An
algorithm for crack detection in rail tracks is uses Light Emitting Diode and
Light Emitting Resistor (LED-LDR) assembly which track the exact location of
faulty track. The design proposed by the authors includes LED which are
attached to one side of the rails and the LDR to the opposite side. When there
are no cracks i.e. during normal operation, the LED light does not fall on the
LDR and hence the LDR resistance is high. Subsequently, when the LED light
falls on the LDR, the resistance of the LDR gets reduced and the amount of
reduction will be approximately proportional to the intensity of the incident
light. Consequently the light from the LED deviates from its path due to the
presence of a crack or a break and there is a sudden decrease in the resistance
value of the LDR. This change in resistance indicates the presence of a crack
or some other similar structural defect in the rails. In order to detect the
current location of the device in case of detection of a crack, a GPS receiver
whose function is to receive the current latitude and longitude data is used.
To communicate the received information, a GSM modem has been utilized. The
function of the GSM module being used is to send the current latitude and
longitude data to the relevant authority as an SMS. The robot is driven by four
DC motors. If this system is employed only latitudes and longitudes of the
broken track will only be received so that the exact location cannot be known.
GPRS
module is used to get exact location of the broken rail track. ARM7 controller
is also used owning to is low cost and less power consumption it also decreases
the time used in detecting cracks.
RAIL
TRACK INSPECTION USING SENSORS
Automatic
Railroad Track Inspection
An
automatic inspection system is proposed in the paper but it is limited to the
track bed and the rails. Deployment of the rail track to cover maximum optimum
segment is also discussed. Instead of six transducers employed in bi-static
mode, a single mono-static mode T-R, transducers is used which offers a
significant saving in material, installation, electronics, and space, as well
as cost. The proposed system helps in monitoring high risks in track beds by
deploying sensors at particular areas and by the use of probabilistic selection
method to identify high risk areas.
Wireless
Sensor Networks Based on Fuzzy Logic
The
concept of fuzzy logic is used by author’s deployed sensors. A model for
placing sensors on the railway track is described in the system. There are many
base stations or control centers which collect the data from the numerous
sensor nodes distributed on the railway tracks. Multi-layer routing is used to
transmit the sensed data to control station. The sensor nodes transmit the data
to their nearby cluster heads. Multi-layer routing is used; the nodes in lower
layer transmit their data to higher layer instead of transmitting it directly
to base station.
For
detecting cracks on rail tracks ultrasonic method is used. Ultrasonic waves are
injected into the rails by special transducers. High-energy signal is sent in
two directions at predetermined intervals. The transmitted signal is propagated
in the rail and is received by receivers. The nearby transmitters send
ultrasonic waves with the same frequency but with different period’s .In this
way, the receivers will be able to recognize the direction (left or right) from
which they receive the signal. If there is a break or chafe in the rail, the
amplitude of the waves received by receivers will be reduced and an alarm
signal will be sounded.
To track cross (horizontal) defects that happen in the crown of
the rail, the ultrasonic method is used: power is concentrated in the crown of
the rail so that it becomes possible to track these defects as the ultrasonic
waves are maximized. Ultrasonic sensors are alternately installed 1.75km apart
from each other in the inside wall of the rail and they must be in complete
contact with the crown of the rail, in this way by increasing the number of the
rail which needs to be investigated.
Collision
in the tracks can be avoided using sensors and a technique based on IR Rays
& Sensors. Collisions are avoided by fixing the sensors in the train wheels
and transmitting the rays in the track. The trains coming from opposite
direction also have the same option. If two trains are on same track, the rays
will get collided and get reflected back to the respective engines and the LED
or Alarm will blink that will help in stopping the train.
The detection of
Cracks is done using IR rays with the IR transmitter & receiver.IR receiver
connected to the Signal Lamp or Electrified lamp with the IR sensor. CAN
controller is connected to the main node and it sends the information via GSM
and transmit the message to engine and to the nearest station. The detection of
Cracks can be identified using IR rays and IR sensor.IR receiver is connected
to the signal lamp and to the CAN controller. The electrified lamp is nothing
but it sides of the tracks the electric lamp which is current flowing for the
engines transportation.
A failure
tolerant (FT) algorithm is proposed for monitoring the rail lines. The algorithm
is based on the simultaneous use of movable and fixed sensor network design and
has the ability to send information as online-offline.
The proposed
algorithm reduces fault tolerance and energy consumption in the network thereby
increasing network lifetime. The algorithm has two parts fixed and movable. The
fixed algorithm works for sensor networks that are in places such as bridges,
tunnels and special points. This algorithm collects information about seismic
data and the bridge balance and Cracking in the foundations of bridges and
Pressure on the bridge and investigates this information. Movable algorithm,
displays how to collect information of fixed sensor network by installed
networks on the locomotive or monitoring cars , it also check the balance point
line and register in a data position. In this system, GPS will detect
coordinates of points that their data is registered.
Track Surveying
with Sensors
For Track
surveying with sensors the authors have proposed an architecture which has
sensor nodes deployed along a railway track as shown in Fig 1. The network
consists of numerous control centers (sink nodes) that are connected through a
wire lined connection, and the sensor nodes are deployed along the railway
lines.The sensor nodes collect the necessary data and forward the data back to
the sink.
An innovative
railway track surveying procedure is described that uses sensors and simple
components like a GPS module, GSM Modem and MEMS based track detector assembly
[14]. The surveying system proposed in this paper can be used for both ballast
and slab tracks. The railway geometrical parameters which are Track axis
coordinates are obtained with integrated Global Positioning System (GPS) and
Global System for Mobile communication (GSM) receivers.
The authors have
proposed a cheap and simple scheme with sufficient ruggedness which is suitable
in the Indian scenario that uses an LVDT arrangement to survey track geometry
by using multi sensor, which has proved to be cost effective as compared to the
existing methods. This sensor very accurate detection and it will send
information immediately by using GSM. The system can be operated in tunnels
without interruption
Fig 1. Architecture of Track Surveying with Sensors
Bridge damage
status is monitored by the sensor and wireless modules, when the sensor not
getting signal, immediately nearby wireless system notifies and alert or
informs to the current train on the track. The above task can achieve through
microcontrollers, GSM, LVDT.
RAIL
DEFECT DETECTION PROCEDURE
Rail defect
detection is a process for which many different detection techniques have been
studied and implemented. In general, for a defect detection system, the
following need to be made available: a system of sensors which traverses the
rail tracks, a data acquisition system, an algorithm to process the data and
classify the signals as those arising from a break or no break and finally a
means for notifying the GPS position of the break to authorities so that
necessary action may be taken. Figure discusses the flow of the process of
fault detection and remediation in case of rail break instances. A schema of
the discussed method is given in figure 2.
Fig 2 Break
Detection procedure
CONCLUSION
Accidents
occurring in railway transportation systems cost a large number of lives. Many
people die and several others get physical and mentally injured. Accidents are
the major causes for traumatic injuries. There is certain need of advanced and
robust techniques that can not only prevent these accidents but also eradicate
all possibilities of their occurrence. Wireless sensor network which
continuously monitors the railway track through the sensors and detect any
abnormality in the track. The sensor nodes are equipped with sensors that can
sense the vibration in the railway track due a coming train. The geographical
positioning sensors are placed on the trains. These sensors send the train’s
geographic location. The complete process is needed to be real time in nature
and should meet the deadlines. Optimization of the communication protocol and
real time working network with minimum delay in multi-hop routing from the
nodes to the train using a static base station is needed, so that the decision
making can be done and the decision is forwarded to the train without any
delay.
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