sspqdd 1.0.5

Single-Shot-Power-Quality-Disturbance-Detector

Single-Shot-Power-Quality-Disturbance-Detector (SSPQDD) is a Python package that provides a comprehensive solution for detection and classification of power quality disturbances. It utilizes state-of-the-art deep learning algorithms to analyze power signals and identify various types of disturbances, such as voltagesags, swells, harmonics, transients, notch and interruptions. The SSPQDD is designed to empower engineers and researchers working in the field of power quality analysis. By leveraging deep learning techniques, it offers an efficient and accurate approach to automatically detect and classify power disturbances, saving time and effort compared to manual inspection. With the SSPQDD, users can gain valuable insights into power quality issues and make informed decisions for optimal system performance and reliability.

Features: - Detection and classification of power quality disturbances: SSPQDD provides an extensive library of pre-trained deep learning models capable of identifying various power disturbances with high precision. - Real-time monitoring: It enables real-time analysis of power signals,allowing for immediate detection and notification of disturbances as they occur. - Customizability: Users have the flexibility to fine-tune or retrain the models with their own datasets to cater to specific power quality analysis requirements. -Visualization and reporting: PowerQDetect offers interactive visualization tools and comprehensive reporting capabilities to help users interpret the detected disturbances and generate detailed reports.