Skip to main content

Single-Shot-Power-Quality-Disturbance-Detector

Project description

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sspqdd-1.0.23.tar.gz (23.5 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sspqdd-1.0.23-py3-none-any.whl (6.7 kB view details)

Uploaded Python 3

File details

Details for the file sspqdd-1.0.23.tar.gz.

File metadata

  • Download URL: sspqdd-1.0.23.tar.gz
  • Upload date:
  • Size: 23.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for sspqdd-1.0.23.tar.gz
Algorithm Hash digest
SHA256 e5e67e49967b9e27a6be5d776eaf825a65a798c162ceb61cc5d17d4bd2242628
MD5 926de6f0b0f8e819fc3a4cc943f2a6a4
BLAKE2b-256 f0fe763aa38e28b69f26a88082b4fcfd92ad6f8049fdb18fdd74a196088e6edc

See more details on using hashes here.

File details

Details for the file sspqdd-1.0.23-py3-none-any.whl.

File metadata

  • Download URL: sspqdd-1.0.23-py3-none-any.whl
  • Upload date:
  • Size: 6.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for sspqdd-1.0.23-py3-none-any.whl
Algorithm Hash digest
SHA256 1eea0026ae1616f2acfae29e484a65d5c39665a642334d44b135b631a46a9dd1
MD5 60de5b04547052f7c2d5a31a22a100a4
BLAKE2b-256 d76d884ee1a6ec76aa40221615bf272a4a96118cecf37d2396d93885a492732d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page