Abstract: This project aims at building an efficient and
automatic power monitoring SCADA system, which is capable of
monitoring the electrical parameters of high voltage powered devices
in real time for example RMS voltage and current, frequency, energy
consumed, power factor etc. The system uses RS-485 serial
communication interface to transfer data over longer distances.
Embedded C programming is the platform used to develop two
hardware modules namely: RTU and Master Station modules, which
both use the CC2540 BLE 4.0 microcontroller configured in slave /
master mode. The Si8900 galvanic ally isolated microchip is used to
perform ADC externally. The hardware communicates via UART
port and sends data to the user PC using the USB port. Labview
software is used to design a user interface to display current state of
the power loads being monitored as well as logs data to excel
spreadsheet file. An understanding of the Si8900’s auto baud rate
process is key to successful implementation of this project.
Abstract: Microstructure and fabric of soils play an important
role on structural properties e.g. stiffness and strength of compacted
earthwork. Traditional quality control monitoring based on moisturedensity
tests neither reflects the variability of soil microstructure nor
provides a direct assessment of structural property, which is the
ultimate objective of the earthwork quality control. Since stiffness
and strength are sensitive to soil microstructure and fabric, any
independent test methods that provide simple, rapid, and direct
measurement of stiffness and strength are anticipated to provide an
effective assessment of compacted earthen materials’ uniformity. In
this study, the soil stiffness gauge (SSG) and the dynamic cone
penetrometer (DCP) were respectively utilized to measure and
monitor the stiffness and strength in companion with traditional
moisture-density measurements of various earthen materials used in
Thailand road construction projects. The practical earthwork quality
control criteria are presented herein in order to assure proper
earthwork quality control and uniform structural property of
compacted earthworks.
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: The increasing availability of information about earth
surface elevation (Digital Elevation Models DEM) generated from
different sources (remote sensing, Aerial Images, Lidar) poses the
question about how to integrate and make available to the most than
possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the
quality of data management plays a fundamental role. Due to the high
acquisition costs and the huge amount of generated data, highresolution
terrain surveys tend to be small or medium sized and
available on limited portion of earth. Here comes the need to merge
large-scale height maps that typically are made available for free at
worldwide level, with very specific high resolute datasets. One the
other hand, the third dimension increases the user experience and the
data representation quality, unlocking new possibilities in data
analysis for civil protection, real estate, urban planning, environment
monitoring, etc. The open-source 3D virtual globes, which are
trending topics in Geovisual Analytics, aim at improving the
visualization of geographical data provided by standard web services
or with proprietary formats. Typically, 3D Virtual globes like do not
offer an open-source tool that allows the generation of a terrain
elevation data structure starting from heterogeneous-resolution terrain
datasets. This paper describes a technological solution aimed to set
up a so-called “Terrain Builder”. This tool is able to merge
heterogeneous-resolution datasets, and to provide a multi-resolution
worldwide terrain services fully compatible with CesiumJS and
therefore accessible via web using traditional browser without any
additional plug-in.
Abstract: The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.
Abstract: Recently, traffic monitoring has attracted the attention
of computer vision researchers. Many algorithms have been
developed to detect and track moving vehicles. In fact, vehicle
tracking in daytime and in nighttime cannot be approached with the
same techniques, due to the extreme different illumination conditions.
Consequently, traffic-monitoring systems are in need of having a
component to differentiate between daytime and nighttime scenes. In
this paper, a HSV-based day/night detector is proposed for traffic
monitoring scenes. The detector employs the hue-histogram and the
value-histogram on the top half of the image frame. Experimental
results show that the extraction of the brightness features along with
the color features within the top region of the image is effective for
classifying traffic scenes. In addition, the detector achieves high
precision and recall rates along with it is feasible for real time
applications.
Abstract: The aim of irrigation is to recharge the available water
in the soil. Quality of irrigation water is essential for the yield and
quality of crops produced, maintenance of soil productivity and
protection of the environment. The analysis of irrigation water arises
as a need to know the impact of irrigation water on the yield of crops,
the effect, and the necessary control measures to rectify the effect of
this for optimum production and yield of crops. This study was conducted to assess the quality of irrigation water
with its performance on crop planted, in Josepdam irrigation scheme
Bacita, Nigeria. Field visits were undertaken to identify and locate
water supply sources and collect water samples from these sources;
X1 Drain, Oshin, River Niger loop and Ndafa. Laboratory
experiments were then undertaken to determine the quality of raw
water from these sources. The analysis was carried for various parameters namely; physical
and chemical analyses after water samples have been taken from four
sources. The samples were tested in laboratory. Results showed that
the raw water sources shows no salinity tendencies with SAR values
less than 1me/l and Ecvaules at Zero while the pH were within the
recommended range by FAO, there are increase in potassium and
sulphate content contamination in three of the location. From this, it
is recommended that there should be proper monitoring of the
scheme by conducting analysis of water and soil in the environment,
preferable test should be carried out at least one year to cover the
impact of seasonal variations and to determine the physical and
chemical analysis of the water used for irrigation at the scheme.
Abstract: Landfill waste is a common problem as it has an
economic and environmental impact even if it is closed. Landfill
waste contains a high density of various persistent compounds such
as heavy metals, organic and inorganic materials. As persistent
compounds are slowly-degradable or even non-degradable in the
environment, they often produce sublethal or even lethal effects on
aquatic organisms. The aims of the present study were to estimate
sublethal effects of the Kairiai landfill (WGS: 55°55‘46.74“,
23°23‘28.4“) leachate on the locomotor activity of rainbow trout
Oncorhynchus mykiss juveniles using the original system package
developed in our laboratory for automated monitoring, recording and
analysis of aquatic organisms’ activity, and to determine patterns of
fish behavioral response to sublethal effects of leachate. Four
different concentrations of leachate were chosen: 0.125; 0.25; 0.5 and
1.0 mL/L (0.0025; 0.005; 0.01 and 0.002 as part of 96-hour LC50,
respectively). Locomotor activity was measured after 5, 10 and 30
minutes of exposure during 1-minute test-periods of each fish (7 fish
per treatment). The threshold-effect-concentration amounted to 0.18
mL/L (0.0036 parts of 96-hour LC50). This concentration was found
to be even 2.8-fold lower than the concentration generally assumed to
be “safe” for fish. At higher concentrations, the landfill leachate
solution elicited behavioral response of test fish to sublethal levels of
pollutants. The ability of the rainbow trout to detect and avoid
contaminants occurred after 5 minutes of exposure. The intensity of
locomotor activity reached a peak within 10 minutes, evidently
decreasing after 30 minutes. This could be explained by the
physiological and biochemical adaptation of fish to altered
environmental conditions. It has been established that the locomotor
activity of juvenile trout depends on leachate concentration and
exposure duration. Modeling of these parameters showed that the
activity of juveniles increased at higher leachate concentrations, but
slightly decreased with the increasing exposure duration. Experiment
results confirm that the behavior of rainbow trout juveniles is a
sensitive and rapid biomarker that can be used in combination with
the system for fish behavior monitoring, registration and analysis to
determine sublethal concentrations of pollutants in ambient water.
Further research should be focused on software improvement aimed
to include more parameters of aquatic organisms’ behavior and to
investigate the most rapid and appropriate behavioral responses in
different species. In practice, this study could be the basis for the
development and creation of biological early-warning systems
(BEWS).
Abstract: The beginning of 21st century has witnessed new
advancements in the design and use of new materials for biosensing
applications, from nano to macro, protein to tissue. Traditional
analytical methods lack a complete toolset to describe the
complexities introduced by living systems, pathological relations,
discrete hierarchical materials, cross-phase interactions, and
structure-property dependencies. Materiomics – via systematic
molecular dynamics (MD) simulation – can provide structureprocess-
property relations by using a materials science approach
linking mechanisms across scales and enables oriented biosensor
design. With this approach, DNA biosensors can be utilized to detect
disease biomarkers present in individuals’ breath such as acetone for
diabetes. Our wireless sensor array based on single-stranded DNA
(ssDNA)-decorated single-walled carbon nanotubes (SWNT) has
successfully detected trace amount of various chemicals in vapor
differentiated by pattern recognition. Here, we present how MD
simulation can revolutionize the way of design and screening of DNA
aptamers for targeting biomarkers related to oral diseases and oral
health monitoring. It demonstrates great potential to be utilized to
build a library of DNDA sequences for reliable detection of several
biomarkers of one specific disease, and as well provides a new
methodology of creating, designing, and applying of biosensors.
Abstract: The construction of most coastal infrastructure developments around the world are usually made considering wave height, current velocities and river discharges; however, little effort has been paid to surveying sediment transport during dredging or the modification to currents outside the ports or marinas during and after the construction. This study shows a complete survey during the construction of one of the largest ports of the Gulf of Mexico. An anchored Acoustic Doppler Current Velocity profiler (ADCP), a towed ADCP and a combination of model outputs were used at the Veracruz port construction in order to describe the hourly sediment transport and current modifications in and out of the new port. Owing to the stability of the system the new port was construction inside Vergara Bay, a low wave energy system with a tidal range of up to 0.40 m. The results show a two-current system pattern within the bay. The north side of the bay has an anticyclonic gyre, while the southern part of the bay shows a cyclonic gyre. Sediment transport trajectories were made every hour using the anchored ADCP, a numerical model and the weekly data obtained from the towed ADCP within the entire bay. The sediment transport trajectories were carefully tracked since the bay is surrounded by coral reef structures which are sensitive to sedimentation rate and water turbidity. The survey shows that during dredging and rock input used to build the wave breaker sediments were locally added (< 2500 m2) and local currents disperse it in less than 4 h. While the river input located in the middle of the bay and the sewer system plant may add more than 10 times this amount during a rainy day or during the tourist season. Finally, the coastal line obtained seasonally with a drone suggests that the southern part of the bay has not been modified by the construction of the new port located in the northern part of the bay, owing to the two subsystem division of the bay.
Abstract: The early-stage damage detection in offshore
structures requires continuous structural health monitoring and for the
large area the position of sensors will also plays an important role in
the efficient damage detection. Determining the dynamic behavior of
offshore structures requires dense deployment of sensors. The wired
Structural Health Monitoring (SHM) systems are highly expensive
and always needs larger installation space to deploy. Wireless sensor
networks can enhance the SHM system by deployment of scalable
sensor network, which consumes lesser space. This paper presents the
results of wireless sensor network based Structural Health Monitoring
method applied to a scaled experimental model of offshore structure
that underwent wave loading. This method determines the
serviceability of the offshore structure which is subjected to various
environment loads. Wired and wireless sensors were installed in the
model and the response of the scaled BLSRP model under wave
loading was recorded. The wireless system discussed in this study is
the Raspberry pi board with Arm V6 processor which is programmed
to transmit the data acquired by the sensor to the server using Wi-Fi
adapter, the data is then hosted in the webpage. The data acquired
from the wireless and wired SHM systems were compared and the
design of the wireless system is verified.
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: Maintenance and design engineers have great concern
for the functioning of rotating machineries due to the vibration
phenomenon. Improper functioning in rotating machinery originates
from the damage to rolling element bearings. The status of rolling
element bearings require advanced technologies to monitor their
health status efficiently and effectively. Avoiding vibration during
machine running conditions is a complicated process. Vibration
simulation should be carried out using suitable sensors/ transducers to
recognize the level of damage on bearing during machine operating
conditions. Various issues arising in rotating systems are interlinked
with bearing faults. This paper presents an approach for fault
diagnosis of bearings using neural networks and time/frequencydomain
vibration analysis.
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: A myriad of environmental issues face the Nigerian
industrial region, resulting from; oil and gas production, mining,
manufacturing and domestic wastes. Amidst these, much effort has
been directed by stakeholders in the Nigerian oil producing regions,
because of the impacts of the region on the wider Nigerian economy.
Although collaborative environmental management has been noted as
an effective approach in managing environmental issues, little
attention has been given to the roles and practices of stakeholders in
effecting a collaborative environmental management framework for
the Nigerian oil-producing region. This paper produces a framework
to expand and deepen knowledge relating to stakeholders aspects of
collaborative roles in managing environmental issues in the Nigeria
oil-producing region. The knowledge is derived from analysis of
stakeholders’ practices – studied through multiple case studies using
document analysis. Selected documents of key stakeholders –
Nigerian government agencies, multi-national oil companies and host
communities, were analyzed. Open and selective coding was
employed manually during document analysis of data collected from
the offices and websites of the stakeholders. The findings showed
that the stakeholders have a range of roles, practices, interests, drivers
and barriers regarding their collaborative roles in managing
environmental issues. While they have interests for efficient resource
use, compliance to standards, sharing of responsibilities, generating
of new solutions, and shared objectives; there is evidence of major
barriers and these include resource allocation, disjointed policy,
ineffective monitoring, diverse socio- economic interests, lack of
stakeholders’ commitment and limited knowledge sharing. However,
host communities hold deep concerns over the collaborative roles of
stakeholders for economic interests, particularly, where government
agencies and multi-national oil companies are involved. With these
barriers and concerns, a genuine stakeholders’ collaboration is found
to be limited, and as a result, optimal environmental management
practices and policies have not been successfully implemented in the
Nigeria oil-producing region. A framework is produced that describes
practices that characterize collaborative environmental management
might be employed to satisfy the stakeholders’ interests. The
framework recommends critical factors, based on the findings, which
may guide a collaborative environmental management in the oil
producing regions. The recommendations are designed to re-define
the practices of stakeholders in managing environmental issues in the
oil producing regions, not as something wholly new, but as an
approach essential for implementing a sustainable environmental
policy. This research outcome may clarify areas for future research as
well as to contribute to industry guidance in the area of collaborative
environmental management.
Abstract: In this paper, the experimental study for the instability
of a separator rotor is presented, under dynamic loading response in
the harmonic analysis condition. The global measurement and
analysis of vibration on the cement separator RC500 is carried, the
points of measurement used are radial dots, vertical, horizontal and
oblique. The measures of trends and spectral analysis for
reconnaissance of the main anomalies, the main defects in the
separator and manifestation, the results prove that the defects effect
has a negative effect on the stability of the rotor. Experimentally the
study of the rotor in transient system allowed to determine the
vibratory responses due to the unbalances and various excitations.
Abstract: In this paper, de Laval rotor system has been
characterized by a hinge model and its transient response numerically
treated for a dynamic solution. The effect of the ensuing non-linear
disturbances namely rub and breathing crack is numerically
simulated. Subsequently, three analysis methods: Orbit Analysis, Fast
Fourier Transform (FFT), and Wavelet Transform (WT) are
employed to extract features of the vibration signal of the faulty
system. An analysis of the system response orbits clearly indicates
the perturbations due to the rotor-to-stator contact. The sensitivities
of WT to the variation in system speed have been investigated by
Continuous Wavelet Transform (CWT). The analysis reveals that
features of crack, rubs and unbalance in vibration response can be
useful for condition monitoring. WT reveals its ability to detect nonlinear
signal, and obtained results provide a useful tool method for
detecting machinery faults.
Abstract: This paper introduces a signal monitoring program
developed with a view to helping electrical engineering students get
familiar with sensors with digital output. Because the output of digital
sensors cannot be simply monitored by a measuring instrument such as
an oscilloscope, students tend to have a hard time dealing with digital
sensors. The monitoring program runs on a PC and communicates with
an MCU that reads the output of digital sensors via an asynchronous
communication interface. Receiving the sensor data from the MCU,
the monitoring program shows time and/or frequency domain plots of
the data in real time. In addition, the monitoring program provides a
serial terminal that enables the user to exchange text information with
the MCU while the received data is plotted. The user can easily
observe the output of digital sensors and configure the digital sensors
in real time, which helps students who do not have enough experiences
with digital sensors. Though the monitoring program was programmed
in the Matlab programming language, it runs without the Matlab since
it was compiled as a standalone executable.
Abstract: Gastric Cancer (GC) has high morbidity and fatality
rate in various countries. It is still one of the most frequent and
deadly diseases. Gastrokine1 (GKN1) and gastrokine2 (GKN2) genes
are highly expressed in the normal stomach epithelium and play
important roles in maintaining the integrity and homeostasis of
stomach mucosal epithelial cells. In this study, 47 paired samples that
were grouped according to the types of gastric cancer and the clinical
characteristics of the patients, including gender and average of age.
They were investigated with gene expression analysis and mutation
screening by monitoring RT-PCR, SSCP and nucleotide sequencing
techniques. Both GKN1 and GKN2 genes were observed significantly
reduced found by (Wilcoxon signed rank test; p
Abstract: Monitoring the conditions of rotating machinery, such
as bearings, is important in order to improve the stability of work.
Acoustic Emission (AE) and vibration analysis are some of the most
accomplished techniques used for this purpose. Acoustic emission
has the ability to detect the initial phase of component degradation.
Moreover, it has been observed that vibration analysis is not as
successful at low rotational speeds (below 100 rpm). This because the
energy generated within this speed region is not detectable using
conventional vibration. From this perspective, this paper has
presented a brief review of using acoustic emission techniques for
monitoring bearing conditions.