| dc.contributor.author |
Yousuf, Md. Adib Ibne |
|
| dc.contributor.author |
Shamim, S.M. |
|
| dc.contributor.author |
Akanda, Md. Touhidur Rahman |
|
| dc.date.accessioned |
2015-06-29T08:07:35Z |
|
| dc.date.available |
2015-06-29T08:07:35Z |
|
| dc.date.issued |
2013-12 |
|
| dc.identifier.uri |
http://hdl.handle.net/123456789/122 |
|
| dc.description |
The authors would specially like to express their most sincere gratitude to their respected
Supervisor, Hafiz Imtiaz, Assistant Professor, Department of Electrical and Electronic
Engineering, Bangladesh University of Engineering and Technology for his continuous
guidance, encouragement, valuable suggestion and inspiration. His sincere and wise advice
helped the authors greatly to make the work successful. Without his initiatives this work would
not have been possible.
The authors would like to express their thanks to their department for all types of help they
offers.They are also grateful to their library & laboratories for lots of help.The authors
acknowledge the help of the individuals who contributed to the successful completion of the whole work. |
en_US |
| dc.description.abstract |
Discrete Cosine Transform feature has become an effective feature extraction method in modern
power system. In this paper, we used algorithm of a unique feature for power quality (PQ)
disturbance signal classification. Here, we proposed the extraction of spectral features from
Discrete Cosine Transform (DCT) domain. This feature extraction offers the ability to detect and
localize harmonic events and it also classifies different power quality disturbance signals. A
useful technique of selecting significant DCT coefficients is proposed for optimal feature
selection. This process offers dimensional feature reduction. In this paper we consider seven
types of power quality disturbance signals and simulate for each of the given categories. Using
this extracted feature we can get not only very high classification accuracy but also a low
computational burden. This feature extraction using Discrete Cosine Transform is one of the best
feature extraction formula, we have ever seen |
en_US |
| dc.description.sponsorship |
DEPARTMENT OF ELECTRICAL, ELECTRONIC AND COMMUNICATION
ENGINEERING (EECE),
MILITARY INSTITUTE OF SCIENCE AND TECHNOLOGY, DHAKA, BANGLADESH |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
Department of Electrical Electronic and Communication Engineering Military Institute of Science and Technology |
en_US |
| dc.subject |
Power, Quality, Disturbance Classification, Frequency, Domain Features . |
en_US |
| dc.title |
Power Quality Disturbance Classification Using Frequency Domain Features A |
en_US |
| dc.type |
Thesis |
en_US |
