Abstract: In this paper, a dual inverter configuration has been implemented for induction motor drive. This isolated dual inverter is capable to produce high quality of output voltage and minimize common mode voltage (CMV). To this isolated dual inverter a decoupled space vector based pulse width modulation (PWM) technique is proposed. Conventional space vector based PWM (SVPWM) techniques require reference voltage vector calculation and sector identification. The proposed decoupled SVPWM technique generates gating pulses from instantaneous phase voltages and gives a CMV of ±vdc/6. To evaluate proposed algorithm MATLAB based simulation studies are carried on indirect vector controlled open end winding induction motor drive.
Abstract: This paper presents a study of Lamb wave damage
diagnosis of composite delamination using instantaneous phase
data. Numerical experiments are performed using the finite element
method. Different sizes of delamination damages are modeled
using finite element package ABAQUS. Lamb wave excitation
and responses data are obtained using a pitch-catch configuration.
Empirical mode decomposition is employed to extract the intrinsic
mode functions (IMF). Hilbert–Huang Transform is applied to each
of the resulting IMFs to obtain the instantaneous phase information.
The baseline data for healthy plates are also generated using the
same procedure. The size of delamination is correlated with the
instantaneous phase change for damage diagnosis. It is observed that
the unwrapped instantaneous phase of shows a consistent behavior
with the increasing delamination size.
Abstract: The inherent skin patterns created at the joints in the
finger exterior are referred as finger knuckle-print. It is exploited to
identify a person in a unique manner because the finger knuckle print
is greatly affluent in textures. In biometric system, the region of
interest is utilized for the feature extraction algorithm. In this paper,
local and global features are extracted separately. Fast Discrete
Orthonormal Stockwell Transform is exploited to extract the local
features. Global feature is attained by escalating the size of Fast
Discrete Orthonormal Stockwell Transform to infinity. Two features
are fused to increase the recognition accuracy. A matching distance is
calculated for both the features individually. Then two distances are
merged mutually to acquire the final matching distance. The
proposed scheme gives the better performance in terms of equal error
rate and correct recognition rate.