Implementation of MODWT on Real Time Power Quality Disturbance Signal
S. Upadhyaya1, A. Panda2
1Swarnabala Upadhyaya*, Department of Electrical and electronics Engineering, Sambalpur University Institute of Information Technology, Sambalpur, India.
2Ambarish Panda, Department of Electrical and electronics Engineering, Sambalpur University Institute of Information Technology, Sambalpur, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 24, 2020. | Manuscript published on March 10, 2020. | PP: 796-800 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2484039520/2020©BEIESP | DOI: 10.35940/ijitee.E2484.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Maximal overlap discrete wavelet transform (MODWT) is the upgradation of traditional wavelet transform (WT), has been employed for localization of different power quality disturbance signal (PQDS). Every signal has been break down up to fourth level to localize the disturbances. The co-efficient of MODWT have been again employed for classification. The selected indices have been obtained utilizing the detail coefficient of this variant of WT. These features are the inputs to the data mining classifier. Decision Tree (DT) have been implemented for discrimination of PQ disturbance signals. Various PQDS have been generated in noisy and noise free climate. Besides this, the aforementioned techniques is examined with three phase signals bring out from transmission line panels.
Keywords: Artificial Neural Network (ANN), Decision Tree Classifier (DT), Maximum overlap discrete Wavelet Transform (MODWT), Power quality disturbance signals (PQDS).
Scope of the Article: Artificial Intelligence