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AI Monitoring for Wind Turbine Operations

Reduce risks of failures by detecting them months in advance. Cut repair costs and minimize downtime with effective damage control, proactive planning, and improved efficiency.

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Wind turbine O&M risks are on the rise:


Higher workload in operations due more complex WTGs


Inconsistent service report interpretations when taking actions


Frequently no detailed history for specific components, recurring faults often go unnoticed


Not identifying root causes for underperformance results in inefficient troubleshooting


The rising risks lead to:

  • Underperformance

  • Unplanned downtimes

  • High spare part costs

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Reduce Risks with Turbit AI Monitoring

AI Performance Monitoring

Performance optimization with control values and thresholds is a time-consuming challenge. Also, this threshold analysis leads to a trade-off between "reliability" and "false alarms". Turbit ML Power resolves this trade-off. Get precise analytics when it's time to act.


AI Component Monitoring 

Turbit uncovers patterns hidden in raw data that precede technical issues of main components months before they occur. With in-depth analytics from Turbit AI, you get all the information you need to prevent sudden breakdowns.

Turbit AI Infrastructure


The 4 steps of Turbit’s fully automated and self improving preventive maintenance infrastructure.

1. Data Engineering

Raw Data Collection

Data Lake and Warehouse

Selection of Training Sets

2. Anomaly Detection

Classic Deep NN* predict normal behaviour

Outlier Detection

Transfer Learning

3. Classification

Anomaly Classification

Failure Mode Prediction

Relevance Prediction

4. Feedback

Customer Feedback Functionalities

Communication Process

with O&M

Reporting & Analytics Tools

*NN: Neutral Networks

   Retraining NN   

   Failure Database   

Turbit Copilot


Failure Mode Prediction

  • Prediction of the failure modes, root causes and possible solutions with AI

  • Individual plots and explanations depending on root causes

  • All available data is input data for the Failure Mode Prediction


Relevance Prediction

  • Relevance Prediction of each alert

  • All Users and Turbit’s customer success engineers are labeling the data

  • All available data is input data for the Relevance Prediction


Event Similarity

  • Displays similar events of the same wind turbine and wind park when Turbit sends a new alert

  • The Similar Event Score is built up with raw data and data from Turbit Modules and KPIs in production


PDF AI Reader (Beta Version)

  • AI PDF Classification and content extraction


  • Monitoring, alerting, and statistics about the completeness of documents and service reports


  • Alerts for abnormal oil analysis data or incomplete maintenance protocols


Turbit Partner Ecosystem






Wind  Software Vendors







With Turbit's solutions and the straightforward collaboration, we get a much better view of our asset base. A real added value for technical operations and asset management.

Oliver Kayser ~ SAB WindTeam

Start with Turbit

Connect your operations software stack to Turbit or upload SCADA data.

Book a demo and learn how Turbit AI changes operation and maintenance for wind turbines.


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