01904nam a22001577a 4500999001700000100007600017245006900093260003000162300000900192500126800201700004201469856003301511942001101544952008901555952010201644  c55746d55743  aWaqar, Ahmed Aadila11MPE06aSupervisor Prof. Dr. Muhammad Usman Keerio  aApplication Of Time Frequency Wavelet Transformation (ME Theses)  aNawabshah:bQUEST,c2014.  a68p.  aABSTRACT

Power system transient disturbances (PSTD) arc sub-category of power quality, arising as a result of variation in sinusoidal nature of power system suppl y volt.1gc which is said to be non-repetitive. Random and causes equipment failure. Looking a\ their wave shape, transients arc classified as oscillatory and 1mpuls1ve.
This work proposes wavelet transform based detection and classification of transient signal. Real time collecllon of transient data 1s expensive and time consuming. Therefore transient signals are generated with the help of mathematical equations and the generated signal comply IEEE-1 159 standards. The next step in
the analysis   is   to   choose effective  signal   processing   technique.  A   time-frequency mapping known as wavelet transform is preferred over other techniques in such cases. A sui table mother wavelet is chosen from some of the mostly used mother wavelet functions. Mulliresolution algorithm (MRA) of DWT is used to detect and further extract features for possible classification of transients defined by IEEE-1 159. The simulated results of proposed methodology prove its successfulness, simplicity,
Accuracy and usefulness for detection, analysis and classification the power system transient problems.
  aDepartment of Electrical Engineering   uhttps://tinyurl.com/3bnd9wby  cTHESIS  00104070aRESEARCHbRESEARCHd2016-11-21l0pMP/06-53r2016-11-21 00:00:00yTHESIS  00104070aRESEARCHbRESEARCHd2018-09-25l0pMP/22-231r2018-09-25 00:00:00w2018-09-25yTHESIS