Advancements in Fault Detection and Continuous Monitoring in Wind Turbines
15 patents in this list
Updated:
Wind turbines operate in harsh environments due to which they can experience wear and tear. This can lead to faults that reduce efficiency, cause downtime, and increase maintenance costs.
However, to keep wind turbines running smoothly and uninterrupted numerous advancements in fault detection systems have emerged. This page explores those developments.
1. Wind Turbine Power Performance Monitoring and Fault Detection Method
VESTAS WIND SYSTEMS A/S, 2021
Monitoring and assessing power performance changes of wind turbines to detect if their power output degrades over time, indicating potential issues that need to be addressed. The method involves comparing the actual power output of monitored wind turbines to the predicted power output based on wind speed data from nearby reference turbines. Deviations indicate degraded performance. A transfer function is generated to estimate power output at the monitored turbines based on reference turbine wind speeds, allowing ongoing monitoring without additional sensors.
2. Ice Buildup Detection on Wind Turbine Blades Using Natural Frequency Shift Analysis
FOS4X GMBH, 2020
Determining ice buildup on wind turbine blades to prevent hazardous ice shedding and blade imbalances. The method involves comparing natural frequency shifts due to ice buildup to a known base shift factor. Measuring blade natural frequencies identifies the current shift factor which can then be used to determine the ice buildup quantity.
3. Lightning Strike Detection and Analysis System for Wind Turbine Protection
DEHN + SÖHNE GMBH + CO. KG, 2020
Sensing lightning-current parameters at installations with capturing devices and lightning-current diversion paths, like wind turbines, using sensors on the paths to detect lightning strikes. These sensors provide yes/no indications of strikes at each location. A central unit collects the strike data and analyzes it to evaluate the effects of the strikes on the installation.
4. LiDAR-Based Blade Condition Monitoring System for Wind Turbines
VESTAS WIND SYSTEMS A/S, 2020
A system for monitoring the state of wind turbine blades without using strain sensors or accelerometers. The system determines blade state parameters using 3D scans of the blades collected from a LiDAR system. It compares the scans to reference models to identify blade deformations, deflections, and other parameters. This allows monitoring of blade conditions like deflection, twist, vibration, and pitch without installing many sensors inside the blades.
5. Autonomous Drone-Based Inspection System for Wind Turbine Blades
Michael Naderhirn, Peter Langthaler, 2020
Automated inspection of surfaces like wind turbine blades using unmanned aircraft. The inspection involves using a camera-equipped drone that autonomously flies near the surface, like a rotor blade, while recording images. Continuous position sensing allows stitching the images into an overall surface view. This is then automatically inspected for defects. The drone can stay a fixed distance from the surface by measuring its position so that stitched images create a full view.
6. Electrical Property Monitoring System for Airborne Wind Turbine Tether Health Assessment
Makani Technologies LLC, 2020
Monitor the health of the tether used to connect airborne wind turbines (AWTs) to the ground. A system uses probes to measure electrical properties along the tether's strength members. Changes in the measured properties indicate stress, strain, and potential damage to the tether. Regular monitoring can detect damage before failure.
7. Predictive Fault Detection and Maintenance Scheduling System for Wind Turbines
DOOSAN HEAVY INDUSTRIES & CONSTRUCTION CO., LTD., 2020
A wind power plant management system that uses data from the wind turbines and environment to predict faults and plan maintenance. The system collects data on the wind turbine work environment and uses a normal state model to predict faults before they occur. It estimates the remaining time until a fault occurs and schedules maintenance to prevent failures.
8. Advanced Sensor and Algorithm-Based Monitoring System for Wind Turbine Optimization and Fault Detection
fos4X GmbH, 2019
Monitoring and controlling wind turbines using improved sensors and algorithms to optimize performance and reduce damage. The monitoring involves measuring acceleration and vibrations in rotor blades to detect torsional instability, ice formation, and other issues. Key features include using fiber-optic sensors positioned effectively on the blades, analog filtering to avoid aliasing and signal processing techniques like subspace identification to extract useful data.
9. Camera-Based Blade Deflection Monitoring System for Wind Turbine Structural Integrity Assessment
Steffen Bunge, 2019
Detecting blade deflection to assess wind turbine structural integrity without expensive instrumentation like strain gauges. A method using cameras mounted at the root of the turbine blades pointed towards the tips. The cameras capture video of the blades in operation. Analyzing the video frame by frame allows for determining the tip deflection relative to the root. Changes in deflection over time can indicate structural damage.
10. Hybrid Sensing System for Condition Monitoring and Fault Detection in Wind Turbines
Laborelec CVBA, 2019
Enabling condition monitoring of wind turbines, especially related to fatigue issues, by effectively measuring shaft torque and load variations. The monitoring system uses selective sensing of electrical and mechanical parts and switches between them based on grid connection. When connected to the grid, electrical measurements provide torque information. When disconnected, mechanical measurements are used. The system also leverages models of turbine components to estimate torque from available measurements.
11. Elastic Coupling Condition Monitoring in Wind Turbine Drive Trains
Adwen GmbH, 2018
Monitoring the condition of the elastic coupling in a wind turbine drive train to detect wear or aging. This involves using sensors in the coupling to measure parameters like axial, radial, tangential and rotational forces. Changes in these signals can indicate degradation of the coupling and the elastic elements can be replaced.
12. Diagnostic Method for Wind Turbine Generator Systems Through Signal Monitoring and Analysis
Shu Yu Cao, Bing Li, Anshuman Tripathi, Hock Heng Thia, Rasool Beevi D-O Mohamed Arif, Kheng Hong Ang, 2018
Method for diagnosing faults in wind turbine generator systems through data monitoring and comparison. The method involves receiving sets of signals from sensors monitoring different aspects of the turbine system like electrical characteristics, high frequency components, and low frequency components. These sets of signals are conditionally filtered and downsampled before comparing them against reference values to detect and locate faults.
13. In-Flight Rotor Blade Ice Detection System Testing for Wind Turbines Without Operational Interruption
Nordex Energy GmbH, 2018
Testing of an in-flight rotor blade ice detection system for a wind turbine that can be carried out more easily and without interrupting turbine operation. The testing involves modifying values of operating and environmental parameters provided to the detection system to simulate conditions that would indicate icing. The system should then still output a warning based on the modified data.
14. Lightning-Current Detection and Analysis for Optimized Maintenance of Wind Turbines
DEHN + SÕHNE GMBH + CO. KG, 2018
A method for accurately sensing lightning-current parameters at installations like buildings and wind turbines, to enable improved evaluation and optimized maintenance of these installations. The method uses a network of simple lightning-current detection sensors placed on the lightning-diversion paths and capturing devices of the installation. These sensors only provide a yes/no indication of lightning current events at their specific location. The sensors wirelessly transmit their data to a central evaluation unit. This allows identifying which parts of the installation experienced lightning strikes. The central unit also contains high-accuracy lightning-current measurement sensors for detailed analysis. By combining the strike locations and detailed current parameters, the method provides a comprehensive view of how lightning impacts the installation.
15. Wind Turbine Blade Monitoring Using Oscillation Analysis for Ice and Damage Detection
Robert Bosch GmbH, 2018
Method for detecting changes in a wind turbine blade, such as ice formation, using existing equipment. The method involves exciting blade oscillations using the turbine's own drive system, then monitoring the oscillation patterns for changes that indicate ice buildup or blade damage. The turbine's control system can be programmed to periodically excite blade oscillations and analyze the response to detect any changes over time. This allows low-cost sensors to be used, since the excitations generate large enough oscillations for detection.
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The innovations on display here demonstrate several methods for detecting faults in wind turbines. Certain techniques examine variations in power production to detect possible problems. Others concentrate on particular dangers, such as ice accumulation on blades or lightning strikes.