6 Critical Wind Turbine Blade Defects (and How New Technologies Are Solving Them)

6 Critical Wind Turbine Blade Defects (and How New Technologies Are Solving Them)

5 Mar 2024 Written by Naomi Stol Zamir

Wind turbines are a prevalent renewable energy source, but a turbine’s efficiency depends on identifying any defects as soon as possible. Then, corrective actions can be taken to keep each component operating as efficiently as possible.

Turbine blades are critical to the energy output of every turbine. However, blades are directly subjected to the elements and high wind loads, necessitating frequent inspections and maintenance to keep them operational.

As such, inspections and maintenance aim to prevent wind turbine problems related to blades that can escalate to decreased power generation or require costly repairs. New technologies have enabled wind farms to inspect turbine blades rapidly while enabling predictive maintenance to keep turbines operating at their best. 

For example, a recent study found that drone-based inspections, compared to rope inspections, can reduce operational costs by 70% while reducing lost revenue due to downtime by up to 90%.

In this article, we’ll be breaking down the most common problems plaguing wind turbine blades and how the latest technologies help identify and mitigate them.

 

Common Blade Defects

Identifying and repairing blade defects before they escalate into more severe problems is critical to operating a wind farm. Thorough and frequent inspections are necessary to identify these blade issues so they can be repaired before they worsen.

Before we dive further into how new technologies keep turbines in operation, let’s discuss common defects that may harm turbines if left unchecked.

 

1. Erosion

One of the most common and potentially damaging blade defects is erosion, typically on the leading edge of blades. The consistent impact of wind, rain, and airborne particles like dust and sand can make an impact over time.

If not identified and repaired, erosion can affect the aerodynamic efficiency of the blade and lead to lower energy production. Over time, unchecked erosion can lead to severe structural damage and require expensive repairs. Staying aware of wind turbine blade erosion and making repairs when possible is crucial.

 

2. Corrosion

Coastal and offshore turbines are subjected to salt water, which can lead to material degradation. Wind mill blade material is designed to be as resilient as possible but will still be affected by external conditions. Inspections and maintenance help identify corrosion and schedule repairs to prevent corrosive damage from affecting performance or structural conditions.

 

3. Surface Cracks

Cracks may appear in various areas across the surface of the turbine blades, such as longitudinal, transverse, and diagonal. Identifying these cracks as soon as possible allows them to be repaired before they begin compromising the blade’s integrity. Otherwise, these cracks may lead to catastrophic failure.

 

4. Open Bond Line

Bond joints are specific portions of a turbine blade glued together with strong adhesives. The glued joints found throughout a turbine blade often become weakened over time, which is expected wear and tear. An open bond line can cause blades to detach or fail. 

Wind turbine blade manufacturing aims to create more durable bonds continually, but it’s still crucial for wind farms to stay on top of bond line wear and tear.

 

5. Lightning Strike Damage

Wind turbine accidents are not unheard of, and lightning strikes and intense weather can significantly damage blades and other components. Lightning strikes can lead to burns or complete structural compromise.

What’s the best way to respond to this damage? Deploying technicians soon after a lightning strike is crucial to identifying the full extent of the damage and schedule repairs as soon as possible.

 

6. Leading Edge Damage

The leading edges of different wind turbine blades will be affected by damage based on altitude and size. Birds, hail, and other debris can significantly harm the leading edges as they face the direction of the wind. Frequent inspections can help identify this type of damage to keep turbines operational.

 

Challenges with Traditional Inspection Methods

Wind turbines have traditionally been inspected with rope inspections, requiring technicians to scale the structure. Other methods, such as visual inspections from the ground, also fell short in many areas compared to newer methods.

 

A few of the core challenges with relying on traditional inspections are:

  • Hazards and safety: Rope inspections require technicians with specialized equipment to reach the turbines and introduce significant risk. Equipment malfunction and falls can be life-threatening.
  • Time and cost efficiency: Scaling a turbine is time-intensive and requires reliable equipment, creating direct costs for the operation. Additionally, extended necessary downtime affects overall profitability.
  • Inconsistent results: Data capture is often inconsistent when relying solely on manual inspections. Different technicians may identify and document data in varying ways, affecting maintenance scheduling and overall data analytics.

 

Leading Edge Technologies Transforming Blade Inspections

Finding the right wind turbine inspection solution is crucial to overcoming the challenges we explored above. New technologies like drones, autonomous drone software, and AI-powered analytics can go far in identifying and correcting possible problems before they have a greater effect on the operation.

Let’s break down a few technologies that changed how wind farms inspect and maintain turbine blades.

 

Automated Drone Inspections

Drones are used to inspect external and structural components of wind turbines to sidestep the need for traditional methods of inspections. 

Manually piloted and autonomous drones both provide significant advantages over other options, with autonomous drone software enabling the next level of turbine inspections. A few of the potent benefits of autonomous drone inspections are:

  • Scalability: Autonomous drones are substantially more time-effective than conventional methods. As a result, turbines can better scale these processes as new assets are added or as inspection frequency increases.
  • Safety: Unlike rope inspections, autonomous drones reach necessary altitudes while technicians remain safely on the ground. Keep your teams out of harm’s way while inspecting each turbine thoroughly.
  • Consistent data: Autonomous drones inspect every turbine in the same way, ensuring all turbine data is consistent. This consistency is critical to identifying issues and prioritizing repairs.
  • Cost reduction: Decreasing inspection downtime and rapidly detecting potential issues greatly reduce the costs of operating a wind farm. Additionally, repairing minor issues before they worsen is necessary to prevent degraded output or unplanned downtime.

 

AI-Powered Analytics

Analytics are critical to the success of a wind farm, and the latest evolution of AI-powered solutions has created a new level of defect detection and overall efficiency. Depending on the platform, analytics platforms can go beyond only reporting the present state of wind turbines and also enable predictive maintenance for every turbine.

For example, vHive’s analytics platform analyzes data from drone inspections to closely identify current defects and predict maintenance schedules. Our platform works with digital twins and drone inspections to generate actionable insights to help manage your wind farm effectively.

Every platform offering AI-driven analytics will depend on data capture and availability to provide valuable insights. Evaluating whether any given platform will integrate with related processes is crucial.

 

Role of Digital Twins in Proactive Maintenance

Digital twins are virtual models that replicate the physical characteristics of real-world assets and are found in a variety of industries. A wind turbine digital twin aims to replicate the individual turbine, including known issues and operations status.

Using digital twins helps lead to cost savings and takes predictive maintenance even further. Additionally, technicians can leverage these tools to create time-effective inspection and maintenance schedules thanks to easy visualization of the entire wind farm.

Adopt vHive for Next-Gen Wind Farm Technologies

Most of the turbine blade defects and issues we’ve explored above begin small and then escalate over time. Detecting wind turbine blade problems as soon as possible is critical to scheduling repairs before they worsen.

Fortunately, new technologies have made it significantly easier to conduct rapid inspections and have granular insights into every wind turbine. Autonomous drones, AI analytics, and digital twins are powerful technologies that allow organizations to cut costs, increase efficiency, and benefit from predictive maintenance.

vHive is an industry leader in these advanced technologies, all developed to help wind farms to meet the needs of wind farms. Are you ready to learn more about how our platform can reduce costs, increase efficiency, and maximize every asset? Book a demo today to see how vHive can benefit your entire operation.

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