Wind Turbine Condition Monitoring

1. Need for Condition Monitoring

The current wind energy trend is the use of larger wind turbines in remote locations, which are increasingly offshore, for optimal wind conditions. Both the size and location factors have led to maintenance challenges that are unique compared to traditional power generation systems:

1. No walkaround maintenance – Unlike other power generation equipment, walkaround maintenance checks are not feasible due to the difficulty and expense of physically reaching the wind turbine.  
2. High maintenance costs – Maintenance costs are high due to the cost of traveling to remote locations and the need for an expensive crane large enough to lift needed parts to the nacelle.  
3. Higher propensity for failure – Gearboxes and related mechanical components are designed with weight savings in mind, leaning toward a higher probability of stress-induced failure.

In addition, constantly changing loads and highly variable operating conditions create high mechanical stress on wind turbines. This high degree of stress demands a high degree of maintenance.  

The wind energy industry typically uses a reactive maintenance approach or run-to-failure maintenance. This form of maintenance has been shown to be the most costly Operations and Maintenance (O&M) practice available to operators.  

All of these factors lead to an increased O&M cost that ultimately affects the Cost of Energy (COE) metric used for evaluating the project feasibility and return on investment. For more information about the COE metric, read the following report from Sandia National Laboratories:

Wind Turbine Reliability: Understanding and Minimizing Wind Turbine Operation and Maintenance Costs

More simply, the Electric Power Research Institute (EPRI) has detailed case studies in the electric power industry and has shown that reactive maintenance (running the machine until it fails) is the least effective and the most costly approach to power generation equipment maintenance. EPRI's comparative maintenance costs are listed below:

1. Reactive maintenance (run to failure) costs $17.00 USD per horsepower per year (This is the baseline.)
2. Preventive maintenance (scheduled maintenance according to the manufacturer's recommendations) costs $24.00 USD per horsepower per year (a savings of 24 percent compared to reactive maintenance)
3. Predictive maintenance (using condition monitoring to predict maintenance needs) costs $9.00 USD per horsepower per year (a savings of 47 percent compared to reactive maintenance)

If turbine components are allowed to run to failure, the overall energy production is significantly decreased due to unscheduled downtime. At the same time, the cost of rushed parts and crane operations, as well as collateral damage caused by the failing component leading to additional damage, further increases maintenance costs. Reactive maintenance costs are then significant cost increases far above the cost of predictive maintenance using an online condition monitoring system. The condition monitoring system’s function is to continuously monitor components and predict mechanical problems, enabling operators to schedule maintenance and avoid catastrophic failures.

To learn more about wind turbine maintenance and condition monitoring from the World Wind Energy Association, read the following report:

Wind Turbine Maintenance and Condition Monitoring Report

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2. National Instruments Condition Monitoring Solutions

National Instruments provides a unique solution to the condition monitoring market. As a technology provider, it is an NI focus to provide generator/gearbox manufacturers or wind turbine integrators the hardware and software to design a high-performance, low-cost, unique solution for monitoring wind turbines and wind turbine components. NI focuses on providing the newest, industry-proven signal processing algorithms for extracting the key features of a signal to predict machine component health. These algorithms include order analysis, cepstral analysis, bearing modulation detection, wavelets, AR modeling, power quality, power factor, rainfall stress cycle analysis, and many other statistical analysis algorithms. With NI LabVIEW software, you can use these built-in signal processing algorithms, import text codes (such as C and other math scripts), and easily design unique and evolutionary algorithms.  

For example, studies show that gearbox and gearbox bearings are among the most common failure points of wind turbines. Gearbox and bearing vibration analysis using accelerometers is an accepted tool to monitor and predict bearing and gearbox failures. However, the multitude of vibration sources in a multistage wind turbine gearbox results in a complex array of gear mesh, modulation, and running speed vibrations.  

Correct analysis of gearbox vibrations requires a high-resolution spectrum analyzer. Fundamentally, this involves a wide-bandwidth vibration signal sampling instrument capable of recording a long duration time waveform record. In other words, the condition monitoring solution must have sample rates of 51.2 kHz or better and have the ability to store records exceeding 2 MB of binary time waveform records. The NI CompactRIO platform offers these capabilities. Further, advanced spectral analysis including zoom FFT and zoom order spectrum further clarify high-frequency vibration characteristics without losing sideband data. Sideband analysis helps the vibration analyst determine which meshing gears are at fault.  

This open, flexible NI LabVIEW and CompactRIO environment has led to the following benefits:

1. Lower cost – NI focuses on low-cost, powerful technologies for the advantage and consumption of service suppliers, wind turbine integrators, and OEMs.
2. Custom solutions – NI provides developers the ability to easily design unique monitoring solutions, surpassing the abilities of traditional condition monitoring solutions.
3. OEM focused – NI works with more than 900 developer partners to provide custom, ready-to-run solutions at significantly reduced costs.
4. Integration of control and monitoring – the NI platform has the ability to integrate control and monitoring on one platform for advanced model-based control and monitoring feedback.

To learn more about condition monitoring signal processing algorithms, visit:

Essential Wind Energy Technologies and Signal Processing Fundamentals

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3. Control System Integration and Communication Protocol Support

One of the big differences with a system based on NI technologies as compared to other products – besides lower cost and unique signal processing – is the integration capabilities of the control system. With the NI platform, it is possible to integrate control and monitoring on a single device or by communication between devices. The NI platforms are capable of communicating with onboard Ethernet, RS232 and RS485, Modbus, OPC, CAN, Fieldbus, PROFIBUS, or even proprietary communications protocols. This flexibility in communication enables the NI system to easily integrate with other devices in the wind turbine nacelle. 

For more information on control system design, visit:

Wind Turbine Control System Design and Deployment

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4. NI Products for Condition Monitoring

National Instruments offers a wide range of signal conditioning equipment to interface with different sensors such as vibration, strain, acoustics, temperature, voltage current and electrical power, and so on. Using standard communications protocols, oil particulate counts and fiber-optic sensing can add to the condition monitoring device. It is this mixed-measurement capability that makes National Instruments a leader in condition monitoring. 

For more information on the recommended NI modules for condition monitoring, read:

National Instruments Products for Wind Turbine Condition Monitoring

Distributed Condition Monitoring Example for Wind Turbines

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5. Case Studies

The NI LabVIEW, CompactRIO, USB, and PXI platforms are widely used in design verification, factory testing, field diagnostics, and the online monitoring of wind turbines and wind turbine components. Review these case studies to learn more.  

1. Reducing Test Time and Increasing Quality in Final Control System Tests for Wind Turbines – Using NI TestStand and LabVIEW with NI PXI instruments for signal conditioning to develop a standard automated test system.
2. Developing a Wind Turbine Assembly Dynamic Diagnostics System for ACCIONA Wind Power Using LabVIEW – Developing a system in accordance with ACCIONA quality standards for the dynamic characterization of wind turbines during the post-assembly-testing stage that is powerful, reliable, and flexible in terms of installation and use as well as within budget.
3. Siemens Wind Power Develops a Hardware-in-the-Loop Simulator for Wind Turbine Control System Software Testing – Creating a new real-time test system for hardware-in-the-loop (HIL) testing of the embedded control software releases of Siemens wind turbine control systems using NI TestStand, the LabVIEW Real-Time and LabVIEW FPGA modules, and the NI PXI platform.
4. Testing Wind Turbines for Noise Emissions with NI LabVIEW – Developing a custom measurement system that uses the NI PXI dynamic signal acquisition module to measure acoustic data from microphones and offers advanced measurement and analysis using Wind Turbine and noiseLAB software.
5. Wind Turbine Main Gearbox Test Stand by GE Wind Energy – Using NI products to develop a wind turbine gearbox test stand for vibration testing.
6. Electric Generator Automated Quality Control Test System by GES Siemsa – Using NI products to develop an automated quality control system with configurable sensor inputs.
7. Data Acquisition System Laboratory Testing of Wind Turbines CENER by GES Siemsa – Using NI products to develop a mixed-measurement generator monitoring solution.
8. Integrating CompactRIO Meteologgers in a Wind SCADA – Programming and integrating an application using CompactRIO hardware and LabVIEW software to acquire, transmit, and store high-frequency signals.
9. Developing an Online Wind Farm Condition Monitoring System with Centralized Data Collection – Developing a diagnostic network to automatically track the status of wind turbines with centralized access so that users can take advantage of the captured signals for offline analysis.
10. Rugged Monitoring System for Bearing by FAG Procheck, Bearing Manufacturer – Using CompactRIO to develop an online machine condition monitoring solution.
11. LabVIEW and CompactRIO Keep Power Plants Online – Using VESKI’s Computerized Diagnostic System (CoDiS) monitoring software with LabVIEW and CompactRIO to provide a continuous, local area network (LAN)-compatible vibration monitoring system.
12. DIAGEN, remote diagnostic system for large electric power generators – Creating a real-time monitoring system based on the CompactRIO platform to safely perform real-time data acquisition and postprocessing of the same effectively.

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6. Application Areas

Find more information on NI condition monitoring offerings in their individual application areas:

1. Power quality monitoring
2. Machine condition monitoring
3. Structural health monitoring