English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The paper introduces a new method for analyzing and classifying various Power Quality (PQ) disturbances using Kalman Filter (KF) and Adaptive Neural Fuzzy Inference System (ANFIS). The variety of distortion waveforms are simulated on the test system using MATLAB software and various input features like amplitude and slope have been used in ANFIS classifier technique inorder to clasify the PQ disturbances. This is mainly achieved by implementing and training ANFIS classifier through the obtained features by KF method for disturbance classification. The results indicates that the KF based ANFIS method is clearly detected and classify the several PQ disturbance signals. The performance of the KF based ANFIS has been evaluated by comparing the results against KF based neural network and KF based fuzzy system.

Power Quality Disturbance Classification based on Kalman filter and Adaptive Neural Fuzzy Inference System (ANFIS)