Abstract: In this paper proposed the effective fault detection of industrial drives by using Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system. This system was focused to reducing the current flow and to identify faults with lesser execution time with harmonic values obtained through fifth derivative. Initially, the construction of Biorthogonal vibration signal-data based wavelet transform in BPPVS-WNN system localizes the time and frequency domain. The Biorthogonal wavelet approximates the broken bearing using double scaling and factor, identifies the transient disturbance due to fault on induction motor through approximate coefficients and detailed coefficient. Posterior Probabilistic Neural Network detects the final level of faults using the detailed coefficient till fifth derivative and the results obtained through it at a faster rate at constant frequency signal on the industrial drive. Experiment through the Simulink tool detects the healthy and unhealthy motor on measuring parametric factors such as fault detection rate based on time, current flow rate, and execution time.
Abstract: In this paper, we analyze NEtwork MObility (NEMO) supporting problems in Content-Centric Networking (CCN), and propose the CCN-NEMO which can well support the deployment of the content-centric paradigm in large-scale mobile Internet. The CCN-NEMO extends the signaling message of the basic CCN protocol, to support the mobility discovery and fast trigger of Interest re-issuing during the network mobility. Besides, the Mobile Router (MR) is extended to optimize the content searching and relaying in the local subnet. These features can be employed by the nested NEMO to maximize the advantages of content retrieving with CCN. Based on the analysis, we compare the performance on handover latency between the basic CCN and our proposed CCN-NEMO. The results show that our scheme can facilitate the content-retrieving in the NEMO scenario with improved performance.
Abstract: To focus on the vibration mode of a cone loudspeaker,
which acts as an electroacoustic transducer, excitation experiments
were performed using two types of loudspeaker units: one employing
an impulse hammer and the other a sweep signal. The on-axis sound
pressure frequency properties of the loudspeaker were evaluated, and
the characteristic properties of the loudspeakers were successfully
determined in both excitation experiments. Moreover, under
conditions identical to the experiment conditions, a coupled analysis of
the vibration-acoustics of the cone loudspeaker was performed using
an acoustic analysis software program that considers the impact of
damping caused by air viscosity. The result of sound pressure
frequency properties with the numerical analysis are the most closely
match that measured in the excitation experiments over a wide range
of frequency bands.
Abstract: An experiment to verify the relationships between
physiological indexes of an e-learner and the presence or absence of an
operation during e-learning is described. Electroencephalogram
(EEG), hemoencephalography (HEG), skin conductance (SC), and
blood volume pulse (BVP) values were measured while participants
performed experimental learning tasks. The results show that there are
significant differences between the SC values when reading with
clicking on learning materials and the SC values when reading without
clicking, and between the HEG ratio when reading (with and without
clicking) and the HEG ratio when resting for four of five participants.
We conclude that the SC signals can be used to estimate whether or not
a learner is performing an active task and that the HEG ratios can be
used to estimate whether a learner is learning.
Abstract: Smart metering and demand response are gaining
ground in industrial and residential applications. Smart Appliances
have been given concern towards achieving Smart home. The success
of Smart grid development relies on the successful implementation of
Information and Communication Technology (ICT) in power sector.
Smart Appliances have been the technology under development and
many new contributions to its realization have been reported in the
last few years. The role of ICT here is to capture data in real time,
thereby allowing bi-directional flow of information/data between
producing and utilization point; that lead a way for the attainment of
Smart appliances where home appliances can communicate between
themselves and provide a self-control (switch on and off) using the
signal (information) obtained from the grid. This paper depicts the
background on ICT for smart appliances paying a particular attention
to the current technology and identifying the future ICT trends for
load monitoring through which smart appliances can be achieved to
facilitate an efficient smart home system which promote demand
response program. This paper grouped and reviewed the recent
contributions, in order to establish the current state of the art and
trends of the technology, so that the reader can be provided with a
comprehensive and insightful review of where ICT for smart
appliances stands and is heading to. The paper also presents a brief
overview of communication types, and then narrowed the discussion
to the load monitoring (Non-intrusive Appliances Load Monitoring
‘NALM’). Finally, some future trends and challenges in the further
development of the ICT framework are discussed to motivate future
contributions that address open problems and explore new
possibilities.
Abstract: Magnetic Resonance Imaging Contrast Agents
(MRI-CM) are significant in the clinical and biological imaging as
they have the ability to alter the normal tissue contrast, thereby
affecting the signal intensity to enhance the visibility and detectability
of images. Superparamagnetic Iron Oxide (SPIO) nanoparticles,
coated with dextran or carboxydextran are currently available for
clinical MR imaging of the liver. Most SPIO contrast agents are
T2 shortening agents and Resovist (Ferucarbotran) is one of a
clinically tested, organ-specific, SPIO agent which has a low
molecular carboxydextran coating. The enhancement effect of
Resovist depends on its relaxivity which in turn depends on factors
like magnetic field strength, concentrations, nanoparticle properties,
pH and temperature. Therefore, this study was conducted to
investigate the impact of field strength and different contrast
concentrations on enhancement effects of Resovist. The study
explored the MRI signal intensity of Resovist in the physiological
range of plasma from T2-weighted spin echo sequence at three
magnetic field strengths: 0.47 T (r1=15, r2=101), 1.5 T (r1=7.4,
r2=95), and 3 T (r1=3.3, r2=160) and the range of contrast
concentrations by a mathematical simulation. Relaxivities of r1 and r2
(L mmol-1 Sec-1) were obtained from a previous study and the selected
concentrations were 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5,
0.6, 0.7, 0.8, 0.9, 1.0, 2.0, and 3.0 mmol/L. T2-weighted images were
simulated using TR/TE ratio as 2000 ms /100 ms. According to the
reference literature, with increasing magnetic field strengths, the
r1 relaxivity tends to decrease while the r2 did not show any
systematic relationship with the selected field strengths. In parallel,
this study results revealed that the signal intensity of Resovist at lower
concentrations tends to increase than the higher concentrations. The
highest reported signal intensity was observed in the low field strength
of 0.47 T. The maximum signal intensities for 0.47 T, 1.5 T and 3 T
were found at the concentration levels of 0.05, 0.06 and 0.05 mmol/L,
respectively. Furthermore, it was revealed that, the concentrations
higher than the above, the signal intensity was decreased
exponentially. An inverse relationship can be found between the field
strength and T2 relaxation time, whereas, the field strength was
increased, T2 relaxation time was decreased accordingly. However,
resulted T2 relaxation time was not significantly different between
0.47 T and 1.5 T in this study. Moreover, a linear correlation of
transverse relaxation rates (1/T2, s–1) with the concentrations of
Resovist can be observed. According to these results, it can conclude
that the concentration of SPIO nanoparticle contrast agents and the
field strengths of MRI are two important parameters which can affect the signal intensity of T2-weighted SE sequence. Therefore, when MR
imaging those two parameters should be considered prudently.
Abstract: Many cluster based routing protocols have been
proposed in the field of wireless sensor networks, in which a group of
nodes are formed as clusters. A cluster head is selected from one
among those nodes based on residual energy, coverage area, number
of hops and that cluster-head will perform data gathering from
various sensor nodes and forwards aggregated data to the base station
or to a relay node (another cluster-head), which will forward the
packet along with its own data packet to the base station. Here a
Game Theory based Diligent Energy Utilization Algorithm (GTDEA)
for routing is proposed. In GTDEA, the cluster head selection is done
with the help of game theory, a decision making process, that selects
a cluster-head based on three parameters such as residual energy
(RE), Received Signal Strength Index (RSSI) and Packet Reception
Rate (PRR). Finding a feasible path to the destination with minimum
utilization of available energy improves the network lifetime and is
achieved by the proposed approach. In GTDEA, the packets are
forwarded to the base station using inter-cluster routing technique,
which will further forward it to the base station. Simulation results
reveal that GTDEA improves the network performance in terms of
throughput, lifetime, and power consumption.
Abstract: Myoelectric control system is the fundamental
component of modern prostheses, which uses the myoelectric signals
from an individual’s muscles to control the prosthesis movements.
The surface electromyogram signal (sEMG) being noninvasive has
been used as an input to prostheses controllers for many years.
Recent technological advances has led to the development of
implantable myoelectric sensors which enable the internal
myoelectric signal (MES) to be used as input to these prostheses
controllers. The intramuscular measurement can provide focal
recordings from deep muscles of the forearm and independent signals
relatively free of crosstalk thus allowing for more independent
control sites. However, little work has been done to compare the two
inputs. In this paper we have compared the classification accuracy of
six pattern recognition based myoelectric controllers which use
surface myoelectric signals recorded using untargeted (symmetric)
surface electrode arrays to the same controllers with multichannel
intramuscular myolectric signals from targeted intramuscular
electrodes as inputs. There was no significant enhancement in the
classification accuracy as a result of using the intramuscular EMG
measurement technique when compared to the results acquired using
the surface EMG measurement technique. Impressive classification
accuracy (99%) could be achieved by optimally selecting only five
channels of surface EMG.
Abstract: Orthogonal Frequency Division Multiplexing
(OFDM) has been used in many advanced wireless communication
systems due to its high spectral efficiency and robustness to
frequency selective fading channels. However, the major concern
with OFDM system is the high peak-to-average power ratio (PAPR)
of the transmitted signal. Some of the popular techniques used for
PAPR reduction in OFDM system are conventional partial transmit
sequences (CPTS) and clipping. In this paper, a parallel
combination/hybrid scheme of PAPR reduction using clipping and
CPTS algorithms is proposed. The proposed method intelligently
applies both the algorithms in order to reduce both PAPR as well as
computational complexity. The proposed scheme slightly degrades
bit error rate (BER) performance due to clipping operation and it can
be reduced by selecting an appropriate value of the clipping ratio
(CR). The simulation results show that the proposed algorithm
achieves significant PAPR reduction with much reduced
computational complexity.
Abstract: Multiple Sclerosis (MS) is a disease which affects the
central nervous system and causes balance problem. In clinical, this
disorder is usually evaluated using static posturography. Some linear
or nonlinear measures, extracted from the posturographic data (i.e.
center of pressure, COP) recorded during a balance test, has been
used to analyze postural control of MS patients. In this study, the
trend (TREND) and the sample entropy (SampEn), two nonlinear
parameters were chosen to investigate their relationships with the
expanded disability status scale (EDSS) score. 40 volunteers with
different EDSS scores participated in our experiments with eyes open
(EO) and closed (EC). TREND and 2 types of SampEn (SampEn1
and SampEn2) were calculated for each combined COP’s position
signal. The results have shown that TREND had a weak negative
correlation to EDSS while SampEn2 had a strong positive correlation
to EDSS. Compared to TREND and SampEn1, SampEn2 showed a
better significant correlation to EDSS and an ability to discriminate
the MS patients in the EC case. In addition, the outcome of the study
suggests that the multi-dimensional nonlinear analysis could provide
some information about the impact of disability progression in MS on
dynamics of the COP data.
Abstract: In this paper, an Infinite Impulse Response (IIR) filter
has been designed and simulated on an Field Programmable Gate
Arrays (FPGA). The implementation is based on Multiply Add and
Accumulate (MAC) algorithm which uses multiply operations for
design implementation. Parallel Pipelined structure is used to
implement the proposed IIR Filter taking optimal advantage of the
look up table of target device. The designed filter has been
synthesized on Digital Signal Processor (DSP) slice based FPGA to
perform multiplier function of MAC unit. The DSP slices are useful
to enhance the speed performance. The proposed design is simulated
with Matlab, synthesized with Xilinx Synthesis Tool, and
implemented on FPGA devices. The Virtex 5 FPGA based design can
operate at an estimated frequency of 81.5 MHz as compared to 40.5
MHz in case of Spartan 3 ADSP based design. The Virtex 5 based
implementation also consumes less slices and slice flip flops of target
FPGA in comparison to Spartan 3 ADSP based implementation to
provide cost effective solution for signal processing applications.
Abstract: Weak damping of low frequency oscillations is a frequent phenomenon in electrical power systems. These frequencies can be damped by power system stabilizers. Unified power flow controller (UPFC), as one of the most important FACTS devices, can be applied to increase the damping of power system oscillations and the more effect of this controller on increasing the damping of oscillations depends on its proper placement in power systems. In this paper, a technique based on controllability is proposed to select proper location of UPFC and the best input control signal in order to enhance damping of power oscillations. The effectiveness of the proposed technique is demonstrated in IEEE 9 bus power system.
Abstract: Digital images are widely used in computer
applications. To store or transmit the uncompressed images
requires considerable storage capacity and transmission bandwidth.
Image compression is a means to perform transmission or storage of
visual data in the most economical way. This paper explains about
how images can be encoded to be transmitted in a multiplexing
time-frequency domain channel. Multiplexing involves packing
signals together whose representations are compact in the working
domain. In order to optimize transmission resources each 4 × 4
pixel block of the image is transformed by a suitable polynomial
approximation, into a minimal number of coefficients. Less than
4 × 4 coefficients in one block spares a significant amount of
transmitted information, but some information is lost. Different
approximations for image transformation have been evaluated as
polynomial representation (Vandermonde matrix), least squares +
gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev
polynomials or singular value decomposition (SVD). Results have
been compared in terms of nominal compression rate (NCR),
compression ratio (CR) and peak signal-to-noise ratio (PSNR)
in order to minimize the error function defined as the difference
between the original pixel gray levels and the approximated
polynomial output. Polynomial coefficients have been later encoded
and handled for generating chirps in a target rate of about two
chirps per 4 × 4 pixel block and then submitted to a transmission
multiplexing operation in the time-frequency domain.
Abstract: Journal bearings used in IC engines are prone to premature
failures and are likely to fail earlier than the rated life due to
highly impulsive and unstable operating conditions and frequent
starts/stops. Vibration signature extraction and wear debris analysis
techniques are prevalent in industry for condition monitoring of
rotary machinery. However, both techniques involve a great deal of
technical expertise, time, and cost. Limited literature is available on
the application of these techniques for fault detection in reciprocating
machinery, due to the complex nature of impact forces that
confounds the extraction of fault signals for vibration-based analysis
and wear prediction. In present study, a simulation model was developed to investigate
the bearing wear behaviour, resulting because of different operating
conditions, to complement the vibration analysis. In current
simulation, the dynamics of the engine was established first, based on
which the hydrodynamic journal bearing forces were evaluated by
numerical solution of the Reynold’s equation. In addition, the
essential outputs of interest in this study, critical to determine wear
rates are the tangential velocity and oil film thickness between the
journals and bearing sleeve, which if not maintained appropriately,
have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to
calculate the wear rate of bearings with specific location information
as all determinative parameters were obtained with reference to crank
rotation. Oil film thickness obtained from the model was used as a
criterion to determine if the lubrication is sufficient to prevent contact
between the journal and bearing thus causing accelerated wear. A
limiting value of 1 μm was used as the minimum oil film thickness
needed to prevent contact. The increased wear rate with growing
severity of operating conditions is analogous and comparable to the
rise in amplitude of the squared envelope of the referenced vibration
signals. Thus on one hand, the developed model demonstrated its
capability to explain wear behaviour and on the other hand it also
helps to establish a co-relation between wear based and vibration
based analysis. Therefore, the model provides a cost effective and
quick approach to predict the impending wear in IC engine bearings
under various operating conditions.
Abstract: The occurrences of precipitation, also commonly
referred as rain, in the form of "convective" and "stratiform" have
been identified to exist worldwide. In this study, the radar return
echoes or known as reflectivity values acquired from radar scans
have been exploited in the process of classifying the type of rain
endured. The investigation use radar data from Malaysian
Meteorology Department (MMD). It is possible to discriminate the
types of rain experienced in tropical region by observing the vertical
characteristics of the rain structure. .Heavy rain in tropical region
profoundly affects radiowave signals, causing transmission
interference and signal fading. Required wireless system fade margin
depends on the type of rain. Information relating to the two
mentioned types of rain is critical for the system engineers and
researchers in their endeavour to improve the reliability of
communication links. This paper highlights the quantification of
percentage occurrences over one year period in 2009.
Abstract: In this study, Brillouin Gain Spectrum (BGS) is
experimentally analyzed in the Brillouin Optical Time Domain
Reflectometry (BOTDR) and Brillouin Optical Time Domain
Analyzer (BOTDA). For this purpose, the signal level of the
microwave generator is varied and the effects of BGS are
investigated. In the setups, 20 km conventional single mode fiber is
used to both setups and laser wavelengths are selected around 1550
nm. To achieve best results, it can be used between 5 dBm to 15 dBm
signal level of microwave generator for BOTDA and BOTDR setups.
Abstract: Fluctuations of Schottky diode parameters in a
structure of the mixer are investigated. These fluctuations are
manifested in two ways. At the first, they lead to fluctuations in the
transfer factor that is lead to the amplitude fluctuations in the signal
of intermediate frequency. On the basis of the measurement data of
1/f noise of the diode at forward current, the estimation of a spectrum
of relative fluctuations in transfer factor of the mixer is executed.
Current dependence of the spectrum of relative fluctuations in
transfer factor of the mixer and dependence of the spectrum of
relative fluctuations in transfer factor of the mixer on the amplitude
of the heterodyne signal are investigated. At the second, fluctuations
in parameters of the diode lead to occurrence of 1/f noise in the
output signal of the mixer. This noise limits the sensitivity of the
mixer to the value of received signal.
Abstract: Small-size and low-power sensors with sensing, signal
processing and wireless communication capabilities is suitable for the
wireless sensor networks. Due to the limited resources and battery
constraints, complex routing algorithms used for the ad-hoc networks
cannot be employed in sensor networks. In this paper, we propose
node-disjoint multi-path hexagon-based routing algorithms in wireless
sensor networks. We suggest the details of the algorithm and compare
it with other works. Simulation results show that the proposed scheme
achieves better performance in terms of efficiency and message
delivery ratio.
Abstract: Online measurement of the product quality is a
challenging task in cement production, especially in the production of
Celitement, a novel environmentally friendly hydraulic binder. The
mineralogy and chemical composition of clinker in ordinary Portland
cement production is measured by X-ray diffraction (XRD) and
X-ray fluorescence (XRF), where only crystalline constituents can be
detected. But only a small part of the Celitement components can be
measured via XRD, because most constituents have an amorphous
structure. This paper describes the development of algorithms
suitable for an on-line monitoring of the final processing step of
Celitement based on NIR-data. For calibration intermediate products
were dried at different temperatures and ground for variable
durations. The products were analyzed using XRD and
thermogravimetric analyses together with NIR-spectroscopy to
investigate the dependency between the drying and the milling
processes on one and the NIR-signal on the other side. As a result,
different characteristic parameters have been defined. A short
overview of the Celitement process and the challenging tasks of the
online measurement and evaluation of the product quality will be
presented. Subsequently, methods for systematic development of
near-infrared calibration models and the determination of the final
calibration model will be introduced. The application of the model on
experimental data illustrates that NIR-spectroscopy allows for a quick
and sufficiently exact determination of crucial process parameters.
Abstract: The increase in electric power demand in face of
environmental issues has intensified the participation of renewable
energy sources such as photovoltaics, in the energy matrix of various
countries. Due to their operational characteristics, they can generate
time-varying harmonic and inter-harmonic distortions. For this
reason, the application of methods of measurement based on
traditional Fourier analysis, as proposed by IEC 61000-4-7, can
provide inaccurate results. Considering the aspects mentioned herein,
came the idea of the development of this work which aims to present
the results of a comparative evaluation between a methodology
arising from the combination of the Prony method with the Kalman
filter and another method based on the IEC 61000-4-30 and IEC
61000-4-7 standards. Employed in this study were synthetic signals
and data acquired through measurements in a 50kWp photovoltaic
installation.