Frequency estimator using artificial neural network for electrical power system dynamic
Also available in printed version
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| Format: | Master's thesis |
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Universiti Teknologi Malaysia
2025
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| Online Access: | https://utmik.utm.my/handle/123456789/102129 |
| Abstract | Abstract here |
| _version_ | 1854975108250075136 |
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| author | Azliza Mohd. Jelani |
| author2 | Abdullah Asuhaimi Mohd., supervisor |
| author_facet | Abdullah Asuhaimi Mohd., supervisor Azliza Mohd. Jelani |
| author_sort | Azliza Mohd. Jelani |
| description | Also available in printed version |
| format | Master's thesis |
| id | utm-123456789-102129 |
| institution | Universiti Teknologi Malaysia |
| publishDate | 2025 |
| publisher | Universiti Teknologi Malaysia |
| record_format | dspace |
| record_pdf | Abstract |
| spelling | utm-123456789-1021292025-08-21T11:37:09Z Frequency estimator using artificial neural network for electrical power system dynamic Azliza Mohd. Jelani Abdullah Asuhaimi Mohd., supervisor Electrical engineering Also available in printed version Development of measurement technology has a significant impact on the survey industry, especially in terms of equipment such as EDM, Total Station, Digital Leveling and GPS. The used of conventional method in distance measurement such as using chain is no longer practical in the actual job application because it is already outdated. However, there are some things that need to be taken into consideration and attention before or during measure a distance by using the EDM or Total Station. This is due to the distance given by the device is not the actual distance. This is due by errors that affected the accuracy of every distance measurements. There are several errors that can affect the accuracy of distance measurements such as zero error, scale error and cyclic error. However, this study only focuses on zero error that affected the accuracy of distance measurements. Zero error, also known as index error which happens while measuring. Zero error due caused by many factors such as electrical delays, geometrical detours and eccentricities in the instruments, differences between the electronic centre and the mechanical centre of the instrument and differences between the optical and mechanical centers of the reflector. These errors may vary due to changes of reflector, jolts, different instrument mounting and after service. Traditionally, the evaluation of the zero and the scale errors is the purpose of the calibration process. EDM calibration test was conducted to test the accuracy of an EDM distance observations. It also seeks to obtain an average difference of a constant for the EDM instrument by comparing the reading distance is given by means of the standard range of test sites. Besides that, the main objective of this study is to develop new software that can be used to determine the zero error that affected EDM/ Total Station while calibration or while measure a distance. This new software is developing by the combination of MOREFIX program and Visual Basic 6.0. MOREFIX program has been used to process raw data from observation while Visual Basic 6.0 software has been used to make the new stand alone software and friendly user practical01 UTM 121 p. Thesis (Sarjana Kejuruteraan (Elektrik)) - Universiti Teknologi Malaysia, 2015 2025-04-10T05:08:48Z 2025-04-10T05:08:48Z 2015 Master's thesis https://utmik.utm.my/handle/123456789/102129 valet-20160413-123154 vital:86617 Closed Access UTM Complete Unpublished application/pdf Universiti Teknologi Malaysia |
| spellingShingle | Electrical engineering Azliza Mohd. Jelani Frequency estimator using artificial neural network for electrical power system dynamic |
| thesis_level | Master |
| title | Frequency estimator using artificial neural network for electrical power system dynamic |
| title_full | Frequency estimator using artificial neural network for electrical power system dynamic |
| title_fullStr | Frequency estimator using artificial neural network for electrical power system dynamic |
| title_full_unstemmed | Frequency estimator using artificial neural network for electrical power system dynamic |
| title_short | Frequency estimator using artificial neural network for electrical power system dynamic |
| title_sort | frequency estimator using artificial neural network for electrical power system dynamic |
| topic | Electrical engineering |
| url | https://utmik.utm.my/handle/123456789/102129 |
| work_keys_str_mv | AT azlizamohdjelani frequencyestimatorusingartificialneuralnetworkforelectricalpowersystemdynamic |