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A Survey on Iris Recognition
-- Lenina Birgale and Manesh Kokare
As the demand for security systems is increasing exponentially day by day, there has been a rigorous
search for different verification and identification techniques. Facial features, voice patterns, hand geometry,
retinal patterns, vein patterns, signature dynamics, voice verification, facial thermography, DNA matching,
nailbed identification, gait recognition, ear shape recognition and finger prints have all been explored as
biometric identifiers with varying levels of success. However, they have their own shortcomings. But iris has
unique patterns; no two iris patterns are alike. After a rigorous review of hundreds of papers on iris
recognition systems we present this review paper.
© 2009 IUP. All Rights Reserved.
H-Shaped Slotted Microstrip Fractal Antenna for
Wideband Applications
-- Jagadeesha S, Vani R M and P V Hunagund
H-shaped slotted microstrip fractal antenna is designed as an efficient scheme for wideband applications.
The designed antenna is based on the fractal geometry with the unique property of self-similarity, having
dimensions of 20 mm × 40 mm × 1.6 mm, used to achieve wider bandwidth of 44.72%. This covers full band of
Digital Cellular System (DCS) (1.710-1880 MHz), Personal Communication System (PCS) (1850-1990 MHz), a
few frequencies of Light Weight Moving Target System (LMTS) (1698-2350 MHz) and International
Mobile Telecommunication (IMT)-2000(1900-2200 MHz). The measured return loss, bandwidth and radiation
patterns of the proposed antenna are presented and compared with simulated results.
© 2009 IUP. All Rights Reserved.
Robust Indirect Vector Control of Induction Motor Using Neuro-Fuzzy Controller
--
B Mahesh Kumar, G Ravi and R Chakrabarti
This paper presents a novel speed control scheme of an Induction Motor (IM) using adaptive
neuro-fuzzy controller. Adaptive Neuro-Fuzzy Inference System (ANFIS) which tunes the fuzzy inference system with
a backpropagation algorithm based on collection of input-output data is implemented. The speed control
scheme is based on the indirect vector control. The complete vector control scheme of the IM drive incorporating
the neuro-fuzzy controller is simulated using MATLAB for 5 hp three-phase squirrel cage IM. The
performances of the proposed neuro-fuzzy-based IM drive are investigated and compared to those obtained from
the conventional Proportional-Integral (PI) controller-based drive at different dynamic operating conditions
such as sudden change in command speed, step change in load, etc. The comparative results reveal that the
neuro-fuzzy controller is more robust and hence, found to be a suitable replacement of the conventional PI
controller for high-performance industrial drive applications.
© 2009 IUP. All Rights Reserved.
Determination of Critical Clearing Time in a Power
System Using Support Vector Machine
-- Hari Om Bansal
A Support Vector Machine (SVM) is a new supervised machine learning method based on the
statistical learning theory. It is a very useful method for classification and regression in small-sample cases such
as critical clearing time (TCC ) calculations, fault diagnosis, etc. In this paper, an effort has been made to
determine the TCC using SVM for a system having exposed to a fault and the results obtained are compared with
the results of `Step-by-Step' method— a classical method for
determining TCC—to prove its superiority
over classical methods.
© 2009 IUP. All Rights Reserved.
Incipient Detection of Faults in Three-Phase
Induction Motors Using Stator Current Spatial Angular Vector Analysis
-- R A Gupta, A K Wadhwani and S R Kapoor
The detection of motor faults at their incipient stage is gaining importance as it leads to increased reliability
and reduced machine downtime. The stator current analysis has caught the attention of researchers as a
mature and simple technique for induction motor fault detection and identification. In this paper, angular space
vector analysis of the induction motor stator current for fault identification has been investigated. The tracking
of spatial angular vector profile of stator current (Parke's vector) is used to identify the degrading health
condition of induction motors. Any significant deviation in the shape of spatial angular vector is an indicator of the
inset of irregularities —mechanical or electrical—in the induction motor. Three major types of induction
motor faults—bearing fault, broken rotor bar fault, and unbalanced supply faults—have been experimentally
investigated. The experimentation has been performed on a
3f, 1.5 kW, 4 poles, 1440 RPM, ABB squirrel cage motor.
The motor setup was mechanically loaded to operate at various loads. The TMS 320F420 DSP-based dSPACE
DS 1104 control card has been used to carry out the experimentation. The softwares used include
Matlab® ver. 2006 and dSPACE controldesk.
© 2009 IUP. All Rights Reserved.
Effect of TCSC on Ill-Conditioned
Power Systems
-- S Suresh Reddy, Sarat Kumar Sahu and S V Jayaram Kumar
This paper presents the variation of condition number `K' on ill-conditioned power system with series
flexible ac transmission system device, TCSC (Thyristor Controlled Series Compensator) with varying degree
of compensation. Case studies are carried out on IEEE 14-bus test system by gradually increasing the
resistance part of the line data of IEEE 14-bus system is to create an ill-condition in the system.
© 2009 IUP. All Rights Reserved.
Statistical Analysis of Vibration Signals:
A Predictive Maintenance Strategy
for Locomotive Auxiliary Drives
-- Jaideep Gupta, A K Wadhwani and S Wadhwani
The motivation for this paper is the need for improved reliability/availability of different electrical drives in
a locomotive for improving the reliability and quality of service to the passengers as well as the requirement
for cost-effective and more efficient condition-based maintenance management. A failure of a locomotive
online not only affects the profits of the railways but also adversely affects the image of the system. To avoid
failure of locomotives online, various strategies are devised but a zero failure scenario has not been achieved so
far. To achieve the reliability of the highest order, various maintenance practices are being used for
different components. This paper deals with the maintenance practice based on the online condition monitoring
of different components so that the timely and cost-effective attention is paid to the equipment whenever it
is needed. This predictive maintenance strategy can be further incorporated with some intelligent
monitoring system like Artificial Neural Networks (ANN) or fuzzy logic. The embedded software would implement
the ANN-based learning algorithms which model the behavior of the equipment during healthy operation
and provide `pre-failure warning' when there is a significant deviation from the expected performance.
© 2009 IUP. All Rights Reserved.
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