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-1.0.24.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-1.0.24-py3-none-any.whl (6.7 kB view details)

Uploaded Python 3

File details

Details for the file sspqdd-1.0.24.tar.gz.

File metadata

  • Download URL: sspqdd-1.0.24.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-1.0.24.tar.gz
Algorithm Hash digest
SHA256 99d2190e834e18562fd4c5ce520c2385a472b18b2def24c8d9d12a26e10f935c
MD5 59b2ca973f31f966311a86038750f381
BLAKE2b-256 790d0158e778d1138d818ef1bea881c30e5a876416f6af991ebb0eb27f45b630

See more details on using hashes here.

File details

Details for the file sspqdd-1.0.24-py3-none-any.whl.

File metadata

  • Download URL: sspqdd-1.0.24-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-1.0.24-py3-none-any.whl
Algorithm Hash digest
SHA256 22e819fd99d258e28bf8c134914ba4ea8daa1db0b5eb4852c24ab97700ee95dc
MD5 cb4c1266cdf36039b6115dbb54907364
BLAKE2b-256 4339313cc2107773353ca0eefb5090ba39fddcfb9e6844d3523983e8faa3fe08

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