Three-Level Data Organization
Organize source images, defects, reviews and reports by wind farm, turbine and blade.
WIND TURBINE INSPECTION PLATFORM
Wind-Turbine Inspection Platform
Organize Discrete Images into Blade-Level, Reviewable and Traceable Inspection Results
Organizes inspection data by wind farm, turbine and blade, connecting blade-image organization and stitching, AI suspect screening, expert review, historical comparison and multi-level reporting.
PRODUCT OVERVIEW
Preserve Not Only Images, but Their Blade, Position and Review Conclusion
The platform associates field images with wind farm, turbine, blade and surface orientation. AI output is treated as suspected defects for professionals to confirm, exclude, grade and annotate.
Raw images, detection records, human reviews and reports can be retained by project, supporting retrieval, periodic comparison and maintenance planning.
Blade-Image Organization
Organize and stitch local images of one blade into a continuous blade-level view.
AI Pre-Screening + Human Review
AI outputs suspected defects for professional confirmation, exclusion, grading and annotation.
History and Reports
Retain historical results by project for periodic comparison and multi-level reports.
Six-Step Process from Raw Field Images to Traceable Reports
Data completeness, acquisition angle and clarity directly affect stitching and AI results. Platform output requires professional review before maintenance use.
Import and Validate
Import inspection images, routes and turbine data and verify files and metadata.
Organize and Stitch Blades
Organize images by turbine, blade and surface direction into continuous blade views.
AI Suspected-Defect Detection
Use deployed models to output suspected position, type and confidence.
Expert Review
Confirm or exclude suspects and annotate severity, position and size.
Historical Alignment
Link current results to historical inspections for professional change comparison.
Report and Archive
Summarize reviewed results and generate blade-, turbine- or farm-level reports.
Layered Organization of Data, Algorithms, Business Logic and Review Interfaces
A layered architecture stores source data, algorithm output and human conclusions separately for traceability.
Application Interaction Layer
- Wind Farm / Turbine / Blade Views
- Review and Annotation Workspace
- History and Report View
Core Business Layer
- Data Import and Organization
- Stitching, Screening and Review
- Historical Alignment and Report Management
AI and Algorithm Layer
- Defect Detection Models
- Image Stitching and Registration
- Historical Defect Association
Data Layer
- Basic Data and Routes
- Source / Stitched Images
- Defect, Review and Report Records
STRUCTURED DATA
Navigate from Wind-Farm Overview to Turbine and Individual Blade
A three-level hierarchy gives every image, suspect, review and report a clear owner, reducing reliance on folder names and memory.
01Wind Farm→02Turbine→03Blade→04Surfaces and Defects
WIND FARM / TURBINE / BLADE
- Offshore Wind FarmProject and Inspection History
- WTG-01Turbine Parameters and Three Blades
- Blade A · Windward SurfaceSource Images, Stitched Views and Review Results
- DEFECT-004Type, Severity, Position, Size and Records
Review Defect Distribution, Severity and Source Images at Blade Level
The interface organizes results by Blade A/B/C and windward, leeward, leading-edge and other directions. Suspects trace back to images and enter review.
IMAGE STITCHING
Organize Multiple Local Images into a Continuous Unwrapped Blade View
Using image features, capture pose and project parameters, the platform matches, optimizes and blends images into a continuous blade-surface view.
Stitch quality depends on overlap, angle, exposure, texture, motion blur and completeness. Source high-resolution images must remain available when stitched views are used for browsing and location.
IMG 01IMG 02IMG 03IMG 04
Feature Matching · Pose Optimization · Image FusionBLADE PANORAMAAI Flags Suspected Items; Professionals Make the Final Determination
The platform can deploy models for different defect types. AI results include suspected location, type and confidence and are not final conclusions.
Surface Cracks
Visible linear or network cracking requires source-image and professional confirmation.
Coating Loss
Suspected peeling, flaking or exposed-substrate coating areas.
Corrosion
Visible corrosion, oxidation or pitting.
Surface Damage
Suspected physical damage from dents, scratches, impact or lightning.
Combine Suspect Screening, Image Verification and Severity Annotation in One Review Workflow
Suspect Ranking
Filter review items by type, confidence, blade region and time.
Multi-Source Image Verification
Jointly view source, stitched and project-supported enhanced images.
Confirm / Exclude / Observe
Professionals issue conclusions; AI output is not treated as a final defect.
Severity and Annotation
Record type, severity, position, size, contour and notes.
AI Suspects→Professional Review→Confirm / Exclude / Observe→Archive and Report
HISTORICAL COMPARISON
Relocate Changes at the Same Defect Position along the Timeline
For blades with alignable historical data, the platform associates images and defects from the same region, shows changes in size, severity and new findings, and retains human verification.
Historical association depends on acquisition angle, calibration, image quality, blade pose and completeness and must not be treated as a structural-life conclusion.
Initial Record
Source Images, Position and Review Conclusion
Periodic Reinspection
Spatial Alignment and Human Verification
Change Analysis
Size, Severity and New-Finding Comparison
Output Results at Blade, Turbine and Wind-Farm Management Levels
Blade LevelReport
Unwrapped view, defect list, distribution, details and history.
Turbine LevelReport
Three-blade summary, statistics, priority issues and history.
Wind-Farm LevelReport
Completion status, turbine summary, type/severity distribution and priority list.
Reports can be viewed online and exported to PDF, Word and other project formats. Templates, statistics, maintenance recommendations and approval workflows require customer confirmation.
Build Blade Records for Periodic Inspection, Special Checks and Maintenance Validation
Periodic Onshore Wind-Farm Inspection
Batch-organize multi-turbine data under a unified review and reporting workflow.
Detailed Offshore Turbine Inspection
Manage blade-defect records for high-salt-spray environments and limited maintenance windows.
End-of-Warranty Inspection
Create traceable records including source images, location, review and reports.
Post-Event Emergency Assessment
Quickly summarize new suspects and priority turbines after typhoons, lightning or hail.
Maintenance-Effectiveness Validation
Associate pre- and post-maintenance inspections to help professionals verify treated areas.
Clear Roles for Flight Acquisition, Mission Monitoring and Result Analysis
01 / COLLECT04 / ANALYZE
Wind-Turbine Drone Inspection
Acquire multi-view blade images as required by the mission.
02 / EXECUTEINES Onboard Navigation
Connect positioning, flight control and mission actions for aircraft execution.
03 / MONITORWind Inspection AGS Ground Station
Configure turbine missions, monitor dynamic inspection and retain manual intervention.
Wind-Turbine Inspection Platform
Organize imagery, AI suspects, human review, history and reports.
TURN INSPECTIONS INTO TRACEABLE RECORDS
Contact the Product Team ↗Trace Every Blade Inspection back to Source Images, Review Process and Report Conclusions
Provide wind-farm scale, acquisition method, sample data, defect standards and reporting requirements, and we will help confirm platform configuration and deployment.