Windrover Case Study

Real Damage. Real
Results.

On 17 March 2026, Windrover detected a CAT4–CAT5 Surface Gap Damage through continuous acoustic monitoring. A drone inspection performed on 29 March 2026 confirmed the damage exactly where the system had identified it.

By detecting the defect four months before the scheduled annual inspection, the operator was able to intervene early, reduce maintenance costs by approximately 50%, and prevent further blade deterioration.

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1000+
Turbines
Monitored
40+
Blades
Saved
10
Countries
4.2M+
Hours of
Blade Data
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A field-proven library of blade damage scenarios detected, classified, and tracked by Windrover across different turbine environments.

Windrover In Action

From Detection To Decision


01

Detect

AI scans blade imagery across environments to detect anomalies.

02

Classify

Findings are classified by type, severity, and location.

03

Track

Conditions are tracked over time to monitor progression.

04

Verify

AI and expert review confirm accuracy and reduce false positives.

05

Repair

Actionable insights guide maintenance planning and prioritization.

06

Failure Prevented

Proactive intervention prevents failure, reduces downtime, and maximizes uptime.

i

Windrover does not stop at detection.

Global Operations

Proven Across Offshore and Onshore Wind Farms

Live CoverageMonitoring 24/7 In Real Operating
Conditions
Case Study MarkersClick A Location To Explore Real
Customer Results

Deployment Locations
10+

Deployment Intensity

LowHigh
1000+
TURBINES
80+
TURBINE MODELS
10
COUNTRIES
4.2M+
HOURS OF BLADE DATA
40+
BLADES SAVED
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