Neural network based bridge balance system
Dissertant
University
University of Technology
Faculty
-
Department
Department of Building and Construction Engineering
University Country
Iraq
Degree
Master
Degree Date
2002
English Abstract
Bridge balance system (BBS) suffer from different types of difficulties, 7 such as : balance reading sensitivity error, balance loading linearity error, corner loading error, balance reading deviation due to mechanical effect (with time),and very complex installation procedures.
These problems should be solved by an expert at the balance installation.
In addition, such systems have to be recalibrated periodically, in some applications they have to be calibrated daily.
This calibration process is to overcome the problem of the system drift (mechanical or electrical) or deterioration, it is a difficult, and time consuming operation.
The modern bridge balances already have microcomputers to control and organize the system operation.
In this work, neural networks have been used to solve the above problems.
These neural networks may be designed to operate on the same above microcomputer.
A Bridge Balance System prototype (laboratory scale model) with load cells as a weighing sensor is designed to enable us to simulate the operation of the practical BBS, -A personal computer is used as a data acquisition system to collect the data from 3l.BBS load cells > and also to implement the required neural network weight measuring system software.
Then any drift or deterioration in the system can be overcome by rerunning the learning software.
Also the above mentioned problems at the installation can be solved simply by this new technique in a short time respectively without the need for an expert person.
An extra neural network has been designed to operate as a fault diagnosing machine.
This network is trained with single fault and tested to detect single and double fault successfully.
Main Subjects
Topics
American Psychological Association (APA)
Tawfiq, Raghad Zuhayr. (2002). Neural network based bridge balance system. (Master's theses Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305674
Modern Language Association (MLA)
Tawfiq, Raghad Zuhayr. Neural network based bridge balance system. (Master's theses Theses and Dissertations Master). University of Technology. (2002).
https://search.emarefa.net/detail/BIM-305674
American Medical Association (AMA)
Tawfiq, Raghad Zuhayr. (2002). Neural network based bridge balance system. (Master's theses Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-305674
Language
English
Data Type
Arab Theses
Record ID
BIM-305674
