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A podcast: Predictive turbine maintenance from SCADA data

By Paul Dvorak | May 16, 2014

Spain based, predictive-maintenance company NEM Solutions, says its technology can glean a lot of good maintenance information from the mountains of SCADA data produced by each wind turbine. The company began by monitoring similar information from railroad equipment and recognized the application to wind turbines.

In this WindTalk podcast, we interview Gorka Parada and Nagore Guarretxena. Gorka is the Sales Director and Nagore is Energy Division Manager with NEM Solutions.

 

Nagore Guarretxena

Nagore Guarretxena

 

Gorka Parada
Gorka Parada


Filed Under: News, O&M, Podcasts
Tagged With: nemsolutions
 

About The Author

Paul Dvorak

Comments

  1. Oren Shapira says

    February 4, 2015 at 2:09 am

    DiagSense has developed a system for prognostics and diagnostics of evolving failures in mechanical parts. The diagnostic system is based on a statistical algorithm that processes the data from the sensors installed on the diagnosed mechanical part. Each time that the algorithm receives the data from sensors, it calculates the “system health grade”, makes a decision on normality of the system and outputs the alerts if needed. These alerts can be delivered to the equipment operators in any form upon according the clients requirements.

    These days DiagSense concentrates on leakage detection problem, we have a several installations in Israel and Europe.
    Based on our experience, we would like to extend to “Predictive maintenance of wind turbines”. We have all the technology required in order to start such a project, we are looking for partner that will provide us a SCADA data.
    Can you please give me your mail and I will send you a presentation of our approach.

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