85 research outputs found
ANALYSIS OF BOILER TUBE LEAKAGE BY USING ARTIFICIAL NEURAL NETWORK
Artificial neural network (ANN) models, developed by training the network with
data from an existing plant, are very useful especially for large systems such as Thermal
Power Plant. The project is focusing on the ANN modeling development and to examine
the relative importance of modeling and processing variables in investigating the unit
trip due to steam boiler tube leakage.
The modeling and results obtained will be used to overcome the effect of the boiler tube
leakage which influenced the boiler to shutdown if the tube leakage continuously
producing the mixture of steam and water to escape from the risers into the furnace. The
Artificial Intelligent-ANN has been chosen as the system to evaluate the behavior of the
boiler because it has the ability to forecast the trips.
Hence, the objective of this study has been developed to design an ANN to detect and
diagnosis the boiler tube leakage and to simulate the ANN using real data obtained from
Thermal Power Plant. The feed-forward with back-propagation, (BP) ANN model will
be trained with the real data obtained from the plant.
Training and validation of ANN models, using real data from an existing plant, are very
useful to minimize or avoid the trip occurrence in the plants. The study will focus on
investigating the unit trip due to tube leakage of risers in the boiler furnace and
developing the ANN model to forecast the trip
ANALYSIS OF BOILER TUBE LEAKAGE BY USING ARTIFICIAL NEURAL NETWORK
Artificial neural network (ANN) models, developed by training the network with
data from an existing plant, are very useful especially for large systems such as Thermal
Power Plant. The project is focusing on the ANN modeling development and to examine
the relative importance of modeling and processing variables in investigating the unit
trip due to steam boiler tube leakage.
The modeling and results obtained will be used to overcome the effect of the boiler tube
leakage which influenced the boiler to shutdown if the tube leakage continuously
producing the mixture of steam and water to escape from the risers into the furnace. The
Artificial Intelligent-ANN has been chosen as the system to evaluate the behavior of the
boiler because it has the ability to forecast the trips.
Hence, the objective of this study has been developed to design an ANN to detect and
diagnosis the boiler tube leakage and to simulate the ANN using real data obtained from
Thermal Power Plant. The feed-forward with back-propagation, (BP) ANN model will
be trained with the real data obtained from the plant.
Training and validation of ANN models, using real data from an existing plant, are very
useful to minimize or avoid the trip occurrence in the plants. The study will focus on
investigating the unit trip due to tube leakage of risers in the boiler furnace and
developing the ANN model to forecast the trip
A Knowledge-Based System for Reliability-Centered Maintenance in the Chemical Industry.
An innovative new framework for the implementation of reliability centered maintenance (RCM) in industrial settings was developed and implemented during this study. Fuzzy reasoning algorithms were designed to evaluate and assess the likelihood of equipment failure mode precipitation and aggravation. Furthermore, an alternative to the traditional RCM decision tree for prioritizing equipment failure modes was defined through the development of an approximate reasoning scheme. This priority scheme not only takes into account the relevancy of failure modes on local and product effects, but also their possibility of occurrence, as well as associated negative consequences on adjacent machinery. The new RCM approach was implemented through an objected-oriented expert system built to perform reliability centered maintenance analysis on industrial chemical processes. The developed expert system reads the process flowsheet generated by ASPEN Plus, a chemical process simulation package, and, based on relevant machine operating data, it provides the user with the final process RCM availability structure diagram. This availability diagram consists of a listing of all critical machine failure modes likely to occur, prioritized according to their overall negative impact on the process, as well as important information on their corresponding local and system effects, and suggested controls for their detection. Although the chemical process industry was selected as the application domain for this research, the developed RCM framework was designed to be extensible across the entire maintenance activity spectrum, regardless of the type of industry associated. The prototype knowledge based system was constructed and delivered on an IBM compatible Personal Computer through an object oriented computer shell, LEVEL 5 Object
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ECOS 2012
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SPATIAL TRANSFORMATION PATTERN DUE TO COMMERCIAL ACTIVITY IN KAMPONG HOUSE
ABSTRACT Kampung houses are houses in kampung area of the city. Kampung House oftenly transformed into others use as urban dynamics. One of the transfomation is related to the commercial activities addition by the house owner. It make house with full private space become into mixused house with more public spaces or completely changed into full public commercial building. This study investigate the spatial transformation pattern of the kampung houses due to their commercial activities addition. Site observations, interviews and questionnaires were performed to study the spatial transformation. This study found that in kampung houses, the spatial transformation pattern was depend on type of commercial activities and owner perceptions, and there are several steps of the spatial transformation related the commercial activity addition.
Keywords: spatial transformation pattern; commercial activity; owner perception, kampung house; adaptabilit
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