National Instruments Products for Wind Turbine Condition Monitoring

Publish Date: Mar 29, 2016 | 5 Ratings | 4.40 out of 5 | Print

Overview

This document discusses some of the major components of a wind turbine you should monitor and which NI devices and software you can use to do this. Wind turbine monitoring encompasses monitoring for control applications as well as preventive measures. Preventive monitoring is necessary to extend turbine life cycle, schedule maintenance, and predict fault conditions. The following list of preventive monitoring types is not an all-encompassing list. Depending on your application, you may need to use other types of preventive monitoring.

Table of Contents

  1. Introduction
  2. Hardware Overview
  3. Vibration
  4. Oil Quality
  5. Strain
  6. Acoustic
  7. Temperature
  8. Power Quality
  9. Recommended Modules
  10. Software
  11. Summary

1. Introduction

The wind energy industry faces a constant state of evolution because of challenges such as the pressure to be competitive with other types of energy production and the growing need to reduce operating and maintenance costs. Condition monitoring offers you a way to reduce the cost of ownership for these critical machines by predicting failures before they occur, which helps you effectively schedule proper maintenance.

A wind turbine monitoring system is built around the asset being monitored, with the measurements chosen based on the parameters most likely to indicate failure. A typical block diagram for a wind turbine monitoring system is shown in Figure 1. Sensors and hardware are used to acquire physical signals, and then software is used to analyze these signals into a meaningful machine condition and predict failure.

Figure 1. Block Diagram of a Typical Wind Turbine Condition Monitoring System

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2. Hardware Overview

You can measure a variety of physical signals based on your assets of interest, from vibration and strain to temperature and oil quality. By measuring these different signals together, you can generate a better picture of the assets state.

NI offers a main platform for reading the information from these different sensors: C Series. C Series is an industrial, portable form factor ideal for distributed monitoring or portable diagnostics. However, for some specific cases, PXI offers a higher performance, higher-channel-count system for use in test setups or much larger monitoring systems.

 

C Series PXI
  • Rugged operating spec (temperature and shock)
  • Medium-channel-count systems (3 to 256)
  • Portable or fixed implementation
  • USB, Ethernet, WiFi or integrated processor based controller/chassis options
  • Sample rates at more than 50 kS/s per channel
  • High performance and processing
  • High-channel-count systems (500+)
  • Solid-state hard drives for rugged data storage
  • Ethernet, Modbus, RS232, and many other industrial buses
  • Sample rates at more than 200 kS/s per channel

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3. Vibration

Vibration monitoring is one of the most important aspects in wind turbine monitoring because it helps determine the condition of rotating equipment. In a wind turbine, this equipment consists of the main bearing, gearbox, and generator. Figure 2 shows where you can place vibration sensors to read data in the axial and radial directions. Depending on the applicable frequency range, you can use either position sensors (low range), velocity sensors (mid range), or accelerometers (high range) for this measurement. These vibration sensors are rigid mounted to the component of interest and return an analog signal proportional to the instantaneous local motion. An acquisition device that has a high sampling rate, high dynamic range, and antialiasing is ideal for this type of measurement. For more information on accelerometers, read the Sound and Vibration Transducers Guide.

Figure 2. Vibration Measurement Points in a Wind Turbine.

You also can monitor vibrations on the turbine structure at the base and on the nacelle. This provides information concerning structural bending and the aerodynamic effect of the wind. From this sensor data, you can determine if any monitored components have problems before they are damaged (for example, cracked gear tooth, broken bearing, and so on). For rotating equipment, the sensor data must undergo order analysis to display the data harmonics. These harmonics provide insight into the component performance and allow for easier diagnosis. Consult the Order Analysis Fundamentals and Performing Order Analysis documentation for more information.

 You can choose from a variety of C Series modules for vibration measurement.  Browse channel-count and performance options.

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4. Oil Quality

Oil is a key component in wind systems because improper lubrication can reduce efficiency and cause mechanical failures. Most bearing and gear wear results from incorrect oil lubrication and can lead to more serious problems in the turbine drive train. This monitoring consists of oil particle counting and moistness measurements.

You can use oil particle counting to determine the quality of oil and verify the existence of contaminants. These contaminants can come from either dirt and grit introduced into the system or from metal shavings and other particles that corrode and break off internal machine parts. Contaminant particles cause excessive wear, initiate rolling element bearing fatigue, and clog filters. Particle counters usually communicate with the RS232 protocol. 

Moisture measurements indicate the amount of water contamination in oil lubrication, which causes premature component failure and oxidization of the oil lubricant. Oil moisture sensors return their measurements through either an analog voltage or current or, similar to the particle counters, through RS232.

CompactRIO controllers have integrated RS232 ports you can use for communication. You can choose from a variety of C Series modules for voltage and current measurement. Browse channel-count and performance options.

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5. Strain

Strain monitoring, a common technique for determining structural health, is becoming increasingly more important in the wind turbine industry. Stress measurements are commonly made in a laboratory setting for blade lifetime testing. These stress measurements are made with sensors called metal foil strain gages. An acquisition device that can provide voltage excitation and bridge completion for the strain gage is ideal for this measurement. You can place the strain gages anywhere on the blade, but the distribution varies with the amount of sensors. Place the sensors in a configuration to optimally model the stress on the blade and take both the flapwise and edgewise directions into account. Figure 3 illustrates the difference between the flapwise and edgewise directions. 

Some turbine blade manufacturers embed fiber-optic sensors within the blade to simplify connections from the blade to the data logger and allow little to no degradation of the signal over a long distance. By using new fiber-optic sensing technology, monitoring the stress on the blade while rotating is easier and more accurate.

Figure 2. Flapwise and Edgewise Directions

You can choose from a variety of C Series modules for strain measurement. Browse the different options.

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6. Acoustic

Wind turbine noise impact measurements are most commonly used to ensure the wind system complies with standards such as IEC 61400-11:2002 (International Electrotechnical Commission). Acoustic monitoring uses microphones to measure the noise from the turbine both internally and externally. An acquisition device that has antialiasing and both a high sampling rate and dynamic range is ideal for this type of measurement. To learn more about microphone types, refer to the G.R.A.S Selection Guide for Microphones and Preamplifiers. The gearbox and the main bearing are important when monitoring internally, while the overall turbine noise is monitored externally. From the noise readings, you can determine the higher frequency components to predict possible faults. You can validate the noise compliance of the turbine by measuring signals like the sound power level and by sending the acoustic data through third-octave analysis. Note that you must have NI Sound and Vibration Analysis Software to perform third-order analysis.

You can choose from a variety of C Series modules available for these applications. Browse channel-count and performance options.

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7. Temperature

Temperature is another measurement you can use for preventive and predictive maintenance. You can measure it with a variety of sensors, but the most commonly used sensors for temperature measurement are thermocouples or resistance temperature detectors (RTDs). An acquisition device that has a narrow input range and cold-junction compensation is ideal for this measurement. Internal and external ambient temperatures are common structural health measurements. More importantly, temperature measurements of individual components, such as the generator’s rotor and stator, are important to diagnose and prevent issues in the turbine.

You can choose from a variety of C Series modules available for these applications. Browse channel-count and performance options.

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8. Power Quality

Power quality is a high-interest area for wind turbine monitoring because quality can degrade as a result of wind speed, turbulence, and switching events. While running the wind energy system, you must meet certain voltage and current requirements. Mainly, you need to make sure the alternating voltage and current move in step. Transformers are often placed between the generator output and the DAQ device to scale down the voltage to an acceptable level. Current clamps or current sensors that can convert high amperage into proportional low-voltage outputs are used to measure the output current. Acquisition devices with high voltage and current inputs as well as isolation are ideal for these measurements. 

The following types of analysis most greatly influence power quality: peak power output, reactive power, voltage fluctuations, and harmonics. You can make measurements on the low-voltage side of the turbine’s transformers to acquire the necessary data for the required analysis. The purpose of measuring the reactive power component is to determine if the voltage and current are in phase. The harmonics provide insight into all of the signals that exist in the output. Also, voltage fluctuations, or flickers, can be triggered by short-lived wind variations that have the ability to cause the power output to fluctuate as well. For more information on high-voltage or current measurements, refer to the High-Voltage Measurements and Isolation and Measuring High Current With National Instruments DAQ Devices documents.

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9. Recommended Modules

The following is a summary of the recommended  C Series and PXI modules for the various measurements that could be required by an oil and gas condition monitoring system.

  C Series PXI
Vibration NI 9232 NI PXIe-4496
Oil Quality (Voltage) NI 9205 NI PXIe-6341
Oil Quality (Current) NI 9203 NI PXI-6236
Strain NI 9237 NI PXIe-4330
Acoustics NI 9234 NI PXIe-4496

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10. Software

NI InsightCM™ 

NI InsightCM Enterprise is a software solution with tightly integrated hardware options for monitoring critical and ancillary rotating equipment. With this solution, you can acquire, analyze, and visualize data from a wide breadth of sensors to interpret the health of your machines with confidence. Companies can use this cost-effective, open, and flexible solution to monitor a larger percentage of their fleet and meet evolving maintenance requirements.

NI InsightCM allows you to acquire, manage, and analyze dynamic and static  sensor data, with the option of visualizing both raw data and results. Additionally NI InsightCM Server simplifies firmware deployment and device configuration as well as monitors the status of acquisition systems to ensure reliability of the monitoring solution. NI InsightCM also integrates with your TI infrastructure, enabling integration with popular database historians and existing IT software.

Figure 4. NI InsightCM Enterprise Architecture.

With the NI InsightCM Enterprise solution, data is automatically acquired using  NI condition monitoring systems based on CompactRIO, and transmitted to the server where it is stored. The NI InsightCM Server software calculates condition indicators and also manages the systems based on CompactRIO. The data is then available for remote viewing and analysis using the NI InsightCM Data Explorer client application. Data is also exportable as tags to third-party software packages running at the enterprise IT level.

When an alarm is configured, downloaded to the CompactRIO system, and its conditions triggered, a notification is emailed to specified maintenance specialists. Similarly, an alarm can be triggered by external prognostics or pattern recognition software running in the enterprise IT infrastructure. In both cases, a specialist can be alerted to open the NI InsightCM Data Explorer  to further investigate the fault.

The NI InsightCM Server includes comprehensive analytic and data management capabilities. In addition, the server offers a thin client for managing hardware devices, data, alarms, user permissions, equipment lists, and more. It also provides capabilities to export tags and feature calculations to additional maintenance and plant-monitoring software.

Figure 5. NI InsightCM Server Interface.

The NI InsightCM Data Explorer provides in-depth, interactive visualization and analysis of real-time and historical data for maintenance and equipment specialists. This application is designed for convenient, remote access to raw time-series data and calculated results. It includes standard vibration plot support and several key usability features.

Figure 6. NI InsightCM Data Explorer Interface

To learn more about using NI InsightCM for online condition monitoring applications refer to the NI InsightCM information page. 

NI LabVIEW

For oil condition monitoring, LabVIEW software combines advanced signal analysis with a user-defined GUI. Additionally, LabVIEW provides the tools for all of the data acquisition from the various NI hardware platforms and can even perform data logging and database communication.  

LabVIEW offers the flexibility of creating a monitoring system perfect for your application while providing all of the standard processing features, such as statistical analysis, fast Fourier transform (FFT), and root-mean-square (RMS) measurements, you find in any other analysis environment.

To learn more about using LabVIEW for condition monitoring, view the webcast Using LabVIEW for Embedded Condition Monitoring and Machine Protection.

NI Sound and Vibration Measurement Suite

For more advanced analysis than that provided by LabVIEW, take advantage of the Sound and Vibration Measurement Suite. This suite offers order analysis, waterfall plots, envelope analysis, and more add-ons to LabVIEW. Learn more about the Sound and Vibration Measurement Suite.

Figure 7. Orbit Plot and Analysis in LabVIEW

Figure 8. Waterfall Plots for Run-Up and Run-Down Analysis

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11. Summary

This document has covered some of the major aspects in a wind turbine system that you should monitor. These include vibration in the drive train, oil quality, and acoustic emissions. This list of monitoring types should be modified/expanded on a per-application basis. Wind turbine monitoring is mainly used for predictive maintenance reasons to find and fix a small problem before it progressively becomes worse. Monitoring is used heavily in control applications as well to employ the use of warning and safety features. To learn more about controlling a wind turbine, refer to Wind Turbine Control Methods. For more information about other monitoring types, view the following resources:

 

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