Abstract: Recently, the issue of machine condition monitoring
and fault diagnosis as a part of maintenance system became global
due to the potential advantages to be gained from reduced
maintenance costs, improved productivity and increased machine
availability. The aim of this work is to investigate the effectiveness
of a new fault diagnosis method based on power spectral density
(PSD) of vibration signals in combination with decision trees and
fuzzy inference system (FIS). To this end, a series of studies was
conducted on an external gear hydraulic pump. After a test under
normal condition, a number of different machine defect conditions
were introduced for three working levels of pump speed (1000, 1500,
and 2000 rpm), corresponding to (i) Journal-bearing with inner face
wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii)
Journal-bearing with inner face wear plus Gear with tooth face wear
(B&GW). The features of PSD values of vibration signal were
extracted using descriptive statistical parameters. J48 algorithm is
used as a feature selection procedure to select pertinent features from
data set. The output of J48 algorithm was employed to produce the
crisp if-then rule and membership function sets. The structure of FIS
classifier was then defined based on the crisp sets. In order to
evaluate the proposed PSD-J48-FIS model, the data sets obtained
from vibration signals of the pump were used. Results showed that
the total classification accuracy for 1000, 1500, and 2000 rpm
conditions were 96.42%, 100%, and 96.42% respectively. The results
indicate that the combined PSD-J48-FIS model has the potential for
fault diagnosis of hydraulic pumps.
Abstract: This paper has as its main aim to analyse how
corporate web pages can become an essential tool in order to detect
strategic trends by firms or sectors, and even a primary source for
benchmarking. This technique has made it possible to identify the key
issues in the strategic management of the most excellent large Spanish
firms and also to describe trends in their long-range planning, a way of
working that can be generalised to any country or firm group. More
precisely, two objectives were sought. The first one consisted in showing
the way in which corporate websites make it possible to obtain direct
information about the strategic variables which can define firms. This
tool is dynamic (since web pages are constantly updated) as well as
direct and reliable, since the information comes from the firm itself, not
from comments of third parties (such as journalists, academicians,
consultants...). When this information is analysed for a group of firms,
one can observe their characteristics in terms of both managerial tasks
and business management. As for the second objective, the methodology
proposed served to describe the corporate profile of the large Spanish
enterprises included in the Ibex35 (the Ibex35 or Iberia Index is the
reference index in the Spanish Stock Exchange and gathers periodically
the 35 most outstanding Spanish firms). An attempt is therefore made to
define the long-range planning that would be characteristic of the largest
Spanish firms.
Abstract: The objectives of this research were 1) to study the
opinions of newspaper journalists about their trustworthiness in the
National Press Council of Thailand (NPCT) and the NPCT-s success
in regulating the professional ethics; and 2) to study the differences
among mean vectors of the variables of trustworthiness in the NPCT
and opinions on the NPCT-s success in regulating professional ethics
among samples working at different work positions and from
different affiliation of newspaper organizations. The results showed
that 1) Interaction effects between the variables of work positions and
affiliation were not statistically significant at the confidence level of
0.05. 2) There was a statistically significant difference (p
Abstract: The use of artificial neural network (ANN) modeling
for prediction and forecasting variables in water resources
engineering are being increasing rapidly. Infrastructural applications
of ANN in terms of selection of inputs, architecture of networks,
training algorithms, and selection of training parameters in different
types of neural networks used in water resources engineering have
been reported. ANN modeling conducted for water resources
engineering variables (river sediment and discharge) published in
high impact journals since 2002 to 2011 have been examined and
presented in this review. ANN is a vigorous technique to develop
immense relationship between the input and output variables, and
able to extract complex behavior between the water resources
variables such as river sediment and discharge. It can produce robust
prediction results for many of the water resources engineering
problems by appropriate learning from a set of examples. It is
important to have a good understanding of the input and output
variables from a statistical analysis of the data before network
modeling, which can facilitate to design an efficient network. An
appropriate training based ANN model is able to adopt the physical
understanding between the variables and may generate more effective
results than conventional prediction techniques.
Abstract: Dynamic characteristics of a four-lobe journal bearing
of micropolar fluids are presented. Lubricating oil containing
additives and contaminants is modelled as micropolar fluid. The
modified Reynolds equation is obtained using the micropolar
lubrication theory and solving it by using finite difference technique.
The dynamic characteristics in terms of stiffness, damping
coefficients, the critical mass and whirl ratio are determined for
various values of size of material characteristic length and the
coupling number. The results show compared with Newtonian fluids,
that micropolar fluid exhibits better stability.