Wind Turbine Blade Integrity Survey
& Condition Data Management
AISS-BladeEdge Wind Turbine Blade Integrity Surveys & Data Management
Make sense of BIG DATA and Maximise Annual Energy Production (AEP)
Wind farm asset managers recognise the cost efficiencies and safety benefits of drone surveys.
However, many asset managers are flooded with imagery and video of their turbines with no efficient means of consolidating, categorising, prioritising and ultimately extracting the true value from the data.
Intrinsic value of the information is lost because the data was not captured to meet the needs of a condition based monitoring (CBM) and reliability centred maintenance (RCM) programs.
AIS wind turbine blade condition surveys capture, process, and present data to the wind turbine asset managers with CBM and RCM programs in mind.
We use BladeEdge ™ technology that makes sense of big data and directly helps wind turbine asset managers to maximise annual energy production.
Leverage machine learning technology and big data tools.
Using our custom drone platforms and BladeEdge ™ technology we transform big data into actionable condition information that support operational decisions.
Make informed maintenance, repair and management decisions.
Our blade survey programs identify blade anomalies before they become structural integrity or turbine efficiency issues.
We enable better informed decisions on pro-active maintenance to maximise blade efficiency and effective life. (1) (2)
Eliminate HSE risks
AIS Wind Turbine surveys eliminate Health & Safety risks associated with conventional and costly rope access inspection methods.
Access critical information any time.
Our technology provides 24/7 secure access to your blade condition data for every turbine on your wind farm.
AIS blade integrity survey programs include.
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Initial (baseline) condition data capture.
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Onsite quality assurance and quality control of the data capture process to maximise capture efficiency and eliminate capture re-work.
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Automatic anomaly detection using machine learning algorithms to identify, qualify and prioritise blade anomalies.
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Blade specific survey reports. (Every blade on every turbine is uniquely catalogued)
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24/7 Secure access to all data for use in your asset maintenance management process.
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Scheduled and condition prioritised follow-up blade integrity surveys.
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Un-scheduled (call-out) surveys in response to extreme weather events (Lightning strikes, Hail storms, etc..).