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-1.0.6.tar.gz (5.7 kB view details)

Uploaded Source

Built Distribution

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

sspqdd-1.0.6-py3-none-any.whl (3.0 kB view details)

Uploaded Python 3

File details

Details for the file sspqdd-1.0.6.tar.gz.

File metadata

  • Download URL: sspqdd-1.0.6.tar.gz
  • Upload date:
  • Size: 5.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.8

File hashes

Hashes for sspqdd-1.0.6.tar.gz
Algorithm Hash digest
SHA256 327f4a843da3ee1a2684402d0c9df31aae8390610e7b02916dc3d080192ae152
MD5 6a34a5b318f15ea804df05da6dcd45c2
BLAKE2b-256 a4c6c30a4c930560ecd643455536a2c306bc028e08fcffd5aa7ff2089019cb3e

See more details on using hashes here.

File details

Details for the file sspqdd-1.0.6-py3-none-any.whl.

File metadata

  • Download URL: sspqdd-1.0.6-py3-none-any.whl
  • Upload date:
  • Size: 3.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.8

File hashes

Hashes for sspqdd-1.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 0b124e73ac92bd4cdcbd74e492cceade4825327e39c6eaf2d0c86695fcb89152
MD5 350d5859e9a298cac63b145c243dd940
BLAKE2b-256 51bcb501571e1e83df9d23217be442f859ab7a80f1236e1a62db3e88a33f710b

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