Calgary, AB, Canada, August 2021 – ROSEN Canada introduces the RoCorr MFL-A+ Service in response to the ever-growing need for improved integrity management of corrosion in pipelines. This upgrade to the existing service for in-line high-resolution metal loss detection and sizing incorporates the latest improvements in data evaluation and anomaly sizing algorithms as well as substantially improved specification parameters for assessing pinhole corrosion and axial slotting, enabling effective management of corrosion threats across the full Pipeline Operator Forum (POF) dimension classifications.

The specific upgrades include a machine-learning-based data evaluation system used to classify and size corrosion defects. Known as AutoData™, this artificial intelligence (AI) approach to data evaluation applies artificial neural networks to process large amounts of data, visual recognition algorithms to identify cluster anomalies and installations, all while reducing false call. The system is based on thousands of laser-mapped real pipe defects to identify even the smallest defects. The machine-learning component allows for long-term continuous improvement as each evaluation is performed and reduces human error in defect sizing.

About the ROSEN Group

The ROSEN Group is a globally leading provider of cutting-edge solutions in all areas of the integrity process chain. Since its origins as a one-man business in 1981, ROSEN has rapidly grown and continues to do so.
Today, the business is still privately owned and consists of a team of more than 3,800 employees operating in more than 120 countries.

ROSEN’s products and services include:

  • Inspection of critical industrial assets to ensure reliable operations of the highest standards and effectiveness  
  • Customized engineering consultancy providing efficient asset integrity management
  • Production and supply of customized novel systems and products
  • Market-driven, topical state-of-the-art research and development providing “added-value” products and services

 

For more information about the ROSEN Group, go to: www.rosen-group.com.

Press Photo Material

Image1: Improved specification parameters allows for better assessment of pinhole corrosion and axial slotting.

Image: ROSEN Group

Caption: Improved specification parameters allows for better assessment of pinhole corrosion and axial slotting.

Image2: Includes machine-learning-based data evaluation system for classification and sizing of corrosion defects.

Image: ROSEN Group

Caption: Includes machine-learning-based data evaluation system for classification and sizing of corrosion defects.

 

Press Contact:
ROSEN Canada
E-Mail     public_cal@rosen-group.com