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-1.0.16.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-1.0.16-py3-none-any.whl (3.1 kB view details)

Uploaded Python 3

File details

Details for the file sspqdd-1.0.16.tar.gz.

File metadata

  • Download URL: sspqdd-1.0.16.tar.gz
  • Upload date:
  • Size: 23.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.8

File hashes

Hashes for sspqdd-1.0.16.tar.gz
Algorithm Hash digest
SHA256 34fe1c0b9e12d30cfce533a4622c1e14545ea0b675d67177941625e418b0fe4b
MD5 45d3eb87c2704fe779ccb02663eb1477
BLAKE2b-256 0c777a52d5a2839de132c047b32f0b971de00cb54577493bcc641e433398fc67

See more details on using hashes here.

File details

Details for the file sspqdd-1.0.16-py3-none-any.whl.

File metadata

  • Download URL: sspqdd-1.0.16-py3-none-any.whl
  • Upload date:
  • Size: 3.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.8

File hashes

Hashes for sspqdd-1.0.16-py3-none-any.whl
Algorithm Hash digest
SHA256 d883ec342cb3258853f3ebaa4146183edce036406e9143b4118ef0df76b4a862
MD5 232c896f42fada943fcf726455c4eb52
BLAKE2b-256 fa37825a51c3d594e577ede6060ed4914b6eb28da33df346eadea364c7667a7e

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