Advanced Condition Assessment and Pipe Failure Prediction ProjectAdvanced Condition Assessment and Pipe Failure Prediction Project
  • Home
  • About
    • Partners
    • Governance
    • Structure
    • People
      • Committee of Management
      • Activity Leaders
      • Activity 1 team (Monash University)
      • Activity 2 Team (UTS)
      • Activity 3 Team (University of Newcastle)
      • Activity 4 Teams (refer to Activities 1-3)
      • Consultant to the project
  • Activities
    • Overview
    • Activity 1
      • Activity 1 team (Monash University)
    • Activity 2
      • Activity 2 Team (UTS)
    • Activity 3
      • Activity 3 Team (University of Newcastle)
    • Activity 4
      • Activity 4 Teams (refer to Activities 1-3)
    • Activity 5
  • Vision & Future
  • Publications
    • Conference Papers
    • Fact Sheets
    • Journal Papers
    • Bulletins
    • Videos
  • Intranet
  • News
  • Events
  • Contact

Fact Sheet No.11 – Automatic Detection of Pipeline Construction Features with RFEC technology

Automatic Detection of Pipeline Construction Features with RFEC technology

Overview

In-line inspection with Remote Field Eddy Current (RFEC) tools requires detection of construction features such as joints, elbows and off-takes. We propose to automate this process using supervised learning. Firstly, signal processing techniques are used to detect features in the RFEC recorded data, where features in general refer to both defects and construction characteristics. Secondly, a machine learning algorithm is employed to classify all the detected features into construction features or defects. Over 800 meters of RFEC data recorded from the Strathfield research test-bed, established as part of this collaborative project, have been used to evaluate the proposed approach.

Click here to download the Fact Sheet

Information about Pipes

In August 2011 international water research organisations, Australian water utilities and three Australian universities came together through a collaborative research agreement, and committed overall funding of $16 million (including $4 million cash) over five years to undertake this research through the Advanced Condition Assessment and Pipe Failure Prediction Project.

more info

Recent posts

  • The final meeting of the Committee of Management

    December 6, 2016

  • Final Technical Assessment Committee meeting

    November 24, 2016

  • Critical Pipes Project wins B/HERT award

    November 16, 2016

Quick Links

  • About
  • Activities
  • Vision and Future
  • Resources
  • News
  • Events
  • Contact

Critical Pipes 2021 © - by Inspire Design

  • Home
  • About
  • Activities
  • Resources
  • Events
  • News
  • Contact