Abstract: The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.
Abstract: In this work, functionally graded materials (FGMs), subjected to loading, which varies with time has been studied. The material properties of FGM are changing through the thickness of material as power law distribution. The conical shells have been chosen for this study so in the first step capability equations for FGM have been obtained. With Galerkin method, these equations have been replaced with time dependant differential equations with variable coefficient. These equations have solved for different initial conditions with variation methods. Important parameters in loading conditions are semi-vertex angle, external pressure and material properties. Results validation has been done by comparison between with those in previous studies of other researchers.
Abstract: Quality Function Deployment (QFD) was developed in 1960 in Japan and introduced in 1983 in America and Europe. The paper presents a real application of this technique in a way that the method of applying QFD in design and production aero fuel pumps has been considered. While designing a product and in order to apply system engineering process, the first step is identification customer needs then its transition to engineering parameters. Since each change in deign after production process leads to extra human costs and also increase in products quality risk, QFD can make benefits in sale by meeting customer expectations. Since the needs identified as well, the use of QFD tool can lead to increase in communications and less deviation in design and production phases, finally it leads to produce the products with defined technical attributes.
Abstract: In the present study, the properties of Al-Al2O3
nanocomposite hollow sphere structures were investigated. For this
reason, the Al-based nanocomposite hollow spheres with different
amounts of nano-alumina reinforcement (0-10wt %) and different
ratio of thickness to diameter (t/D: 0.06-0.3) were prepared via a
powder metallurgy method. Then, the effect of mentioned parameters
was studied on physical and quasi static mechanical properties of
their related prepared structures (open/closed cell) such as density,
hardness, strength, and energy absorption. It was found that, as the
t/D ratio increases the relative density, compressive strength and
energy absorption increase. The highest values of strength and energy
absorption were obtained from the specimen with 5 wt. % of
nanoparticle reinforcement, t/D of 0.3 (t=1 mm, D=400μm) as 22.88
MPa and 13.24 MJ/m3, respectively. The moderate specific strength
of prepared composites in the present study showed the good
consistency with the properties of others low carbon steel composite
with similar structure.
Abstract: This paper presents the investigation results of UV
measurement at different level of altitudes and the development of a
new portable instrument for measuring UV. The rapid growth of
industrial sectors in developing countries including Malaysia, brings
not only income to the nation, but also causes pollution in various
forms. Air pollution is one of the significant contributors to global
warming by depleting the Ozone layer, which would reduce the
filtration of UV rays. Long duration of exposure to high to UV rays
has many devastating health effects to mankind directly or indirectly
through destruction of the natural resources. This study aimed to
show correlation between UV and altitudes which indirectly can help
predict Ozone depletion. An instrument had been designed to
measure and monitors the level of UV. The instrument comprises of
two main blocks namely data logger and Graphic User Interface
(GUI). Three sensors were used in the data logger to detect changes
in the temperature, humidity and ultraviolet. The system has
undergone experimental measurement to capture data at two different
conditions; industrial area and high attitude area. The performance of
the instrument showed consistency in the data captured and the
results of the experiment drew a significantly high reading of UV at
high altitudes.
Abstract: In this paper a data miner based on the learning
automata is proposed and is called LA-miner. The LA-miner extracts
classification rules from data sets automatically. The proposed
algorithm is established based on the function optimization using
learning automata. The experimental results on three benchmarks
indicate that the performance of the proposed LA-miner is
comparable with (sometimes better than) the Ant-miner (a data miner
algorithm based on the Ant Colony optimization algorithm) and CNZ
(a well-known data mining algorithm for classification).
Abstract: This paper presents the development of analysis tools
for Home Agriculture project. The tools are required for monitoring
the condition of greenhouse which involves two components:
measurement hardware and data analysis engine. Measurement
hardware is functioned to measure environment parameters such as
temperature, humidity, air quality, dust and etc while analysis tool is
used to analyse and interpret the integrated data against the condition
of weather, quality of health, irradiance, quality of soil and etc. The
current development of the tools is completed for off-line data
recorded technique. The data is saved in MMC and transferred via
ZigBee to Environment Data Manager (EDM) for data analysis.
EDM converts the raw data and plot three combination graphs. It has
been applied in monitoring three months data measurement for
irradiance, temperature and humidity of the greenhouse..
Abstract: The necessity of solving multi dimensional
complicated scientific problems beside the necessity of several
objective functions optimization are the most motive reason of born
of artificial intelligence and heuristic methods.
In this paper, we introduce a new method for multiobjective
optimization based on learning automata. In the proposed method,
search space divides into separate hyper-cubes and each cube is
considered as an action. After gathering of all objective functions
with separate weights, the cumulative function is considered as the
fitness function. By the application of all the cubes to the cumulative
function, we calculate the amount of amplification of each action and
the algorithm continues its way to find the best solutions. In this
Method, a lateral memory is used to gather the significant points of
each iteration of the algorithm. Finally, by considering the
domination factor, pareto front is estimated. Results of several
experiments show the effectiveness of this method in comparison
with genetic algorithm based method.