MARC details
| 000 -LEADER |
|---|
| fixed length control field |
04157ntm a2200373 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
MY-KuUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251125110124.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
|---|
| fixed length control field |
t||||fr|||| 00| 0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
ta |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
221011s2022 my a|||frm||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0009364(Local) |
| Qualifying information |
hardback |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
UMP |
| Language of cataloging |
eng |
| Transcribing agency |
UMP |
| Description conventions |
rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
FTKEE .L53 2022 r Thesis |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Norliana Khamisan, |
| Relator term |
author. |
| 245 13 - TITLE STATEMENT |
|---|
| Title |
An improved feature extraction technique for diagnosing thermal condition of bearing induction motor based on thermal image analysis / |
| Statement of responsibility, etc. |
Norliana Khamisan |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Kuantan, Pahang : |
| Name of producer, publisher, distributor, manufacturer |
UMP, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2022 |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
© 2022 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxi, 254 pages : |
| Other physical details |
illustrations (some color) ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD ROM |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rdacontent |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| Source |
rdamedia |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| Source |
rdacarrier |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
computer disc |
| Source |
rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
|---|
| File type |
text file |
| Encoding format |
PDF |
| Source |
rda |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Faculty of Electrical & Electronics Engineering |
| 502 ## - DISSERTATION NOTE |
|---|
| Dissertation note |
Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2022 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
This study demonstrates the importance of condition monitoring to detect early failures in bearing machinery automatically, faster and accurately. Bearings is one of the main components which has been used extensively in most machining systems including in electrical and mechanical systems. If it is damaged, it has the potential to produce adverse effects such as thermal stress which can cause damage to motor parts and affect the motor performance until it freezes and burn out. Thus, to prevent this problem occur, early monitoring detection is required as a precautionary measure for bearing components. In this research, a detector device that is infrared thermography (IRT) has been utilized since it is one of the non -destructive and most effective testing techniques to monitor and identify failures on motor bearings. Furthermore, infrared thermal imaging systems and image processing approaches are combined using computing systems to build efficient algorithms to detect motor bearing conditions more effectively. Hence, image processing to solve the problem of feature extraction techniques to detect the thermal state of motor bearing images is the main focus of this study. The Color-based, the original GWT-based feature extraction method has been enhanced and resulted in a new feature extraction method as well as become a novelty in this study. A total of three new feature extraction methods have been developed namely Enhanced Gabor Features (EGF), Enhanced Gabor Wavelet Sharpness Median Histogram (GWSMH) and Enhanced Gabor Wavelet Contrast Limited Adaptive Histogram Equalization (GWCLAHE) that aim to modify the thermal features of the motor bearing image in enhancing the visual of the original image. The ANOVA was also used to measure the strength of features for each developed method. Next, Linear Thresholding (LT) and MultiLayer Artificial Neural Networks (MLANNs) classification methods were also used to classify normal, warning, and abnormal conditions on the thermal image of the bearing. Finally, the experimental results on the thermal image of motor bearings have proven that the newly developed Enhanced Gabor Features (EGF) obtained the highest classification performance compared to other new feature extraction methods. This Enhanced Gabor Features method was found to have produced significant features for detecting normal, warning and abnormal conditions on the thermal image of motor bearings. The accuracy value acquired is 99.47%. This has also proved that the image enhancement techniques have given accurate results to improve the image quality in this study. Findings from this research showed that the Enhanced Gabor Features-based method is capable in detecting the abnormalities features from the thermal group of motor bearing images in this research. |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
Faculty of Electrical & Electronics Engineering |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Universities and colleges |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Theses |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Restricted Collection |