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-1.0.8.tar.gz (5.8 kB view details)

Uploaded Source

Built Distribution

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

sspqdd-1.0.8-py3-none-any.whl (3.0 kB view details)

Uploaded Python 3

File details

Details for the file sspqdd-1.0.8.tar.gz.

File metadata

  • Download URL: sspqdd-1.0.8.tar.gz
  • Upload date:
  • Size: 5.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for sspqdd-1.0.8.tar.gz
Algorithm Hash digest
SHA256 84f8f51c352b9489ae7a22e3d819527e296cf0ec257d630b86c94d04eabbd606
MD5 f643e6575e45faa66c0fa3880a8a9024
BLAKE2b-256 7484dee7a352a0f6e5428c36d6e5f30f857096ad4ed6e606753f5691e46fbbbf

See more details on using hashes here.

File details

Details for the file sspqdd-1.0.8-py3-none-any.whl.

File metadata

  • Download URL: sspqdd-1.0.8-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/3.9.16

File hashes

Hashes for sspqdd-1.0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 e60b91d32b146ffda0d03e394f385330c7ed724612bc6c766a9ffa55dd1c0dca
MD5 ee1d75e89db45a453962c4f96d15327f
BLAKE2b-256 3d3fea229865071985641d4d85514fb8d959ac0f970799f7c10ea2976c97288b

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