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Intelligent wind turbine blade monitoring – the benefits

George Marsh

Structural health monitoring (SHM) of wind turbine drive trains is now regarded as an essential part of any MW class of wind turbine and has a dual pay-off for wind energy, as George Marsh found out when he examined an innovative solution from Insensys.

The above comment is especially true for larger wind turbines and those located offshore. Operators value SHM, insurers may well insist on it and there are a number of proven systems on the market. The technology enables owners and operators to save financially by maximising the performance of their assets and dynamically scheduling inspection and maintenance.

However, there is currently one section of the turbine – the turbine rotor – that is not routinely monitored, yet can provide much information about the turbine's operational performance, health and energy yield.

Insensys Ltd, based near Southampton, UK, has developed an innovative fibre optical blade load sensing approach that not only provides an invaluable layer of SHM, but also facilitates Individual Pitch Control (IPC). This is potentially rather significant.

As Phil Rhead, business development manager, wind energy, explains, “Using blade load sensing elements to enable the pitch of a standard wind turbine's blades to be controlled individually, rather than collectively as generally happens at present, secures a better balance of conditions around very large rotors. This allows turbine designers to specify larger rotors for a given machine than would otherwise be viable. As a result, such turbines can capture more energy from the wind”.

Alternatively, says Rhead, the designer can trade this advantage for a lighter, cheaper structure to capture the same amount of energy or, in a retrofit situation, achieve greater reliability and longer life in an existing installation. Insensys' CEOMartin Jones, who five years ago founded the company together with Damon Roberts, technical board member, adds that this form of advanced wind turbine control can enhance installation safety and reduce costs per kWh.


Rotors for large wind turbines today can be 90 to 130 metres in diameter, and the areas swept are consequently huge. This can result in drive trains and structures being subjected to effects that are scarcely evident on smaller machines. In particular, the wind field over the swept area is far less uniform. Wind gradient, the rise in wind speed that naturally occurs with increasing distance from the ground, means that greater wind speeds are seen at the top of the rotor than at the bottom. Add to this the variations in gust strength and turbulence that may occur over a sizeable area, and it is clear why one blade can encounter conditions that are substantially different to those at another.

If the wind load at each blade could be sensed and the blade could be pitched independently to accommodate it, then the rotor could be operated in a more balanced condition, avoiding the imposition of out-of-balance forces on the hub, drive train and tower.

These adverse forces can unduly stress downstream structures and components, and exacerbate the cumulative effects of fatigue. Reducing the stress reduces the potential for damage over time and prolongs the turbine's operational life. At the same time, the ability to make key components lighter and smaller enables designers to counter the seemingly inexorable rise in mass that is a feature of modern turbine evolution. Plus, of course, increasing wind energy capture and cost reduction remain constant aims for turbine designers.

Whilst growing in size and mass, wind turbines have also become more difficult to inspect, service and repair. SHM can facilitate remote inspection and, by detecting faults in their earliest stages, enable measures to be taken that counter their further development, thereby avoiding expensive failures later. Run to failure is not an operational option with large multi-megawatt machines today. Insensys deploys monitoring technology that significantly extends the capability of conventional techniques based mainly on accelerometers and FFT (fast Fourier transform) analysis.

At the core of the Insensys approach is the use of optical fibre sensors to measure load rather than conventional electrical strain gauges. This has major advantages. FO sensors are small, light and easily embedded in composite structures or bonded to components. They are physically compatible with glass fibre reinforced plastic (GRP), the material most turbine blades plus certain hub and nacelle components are made from, and do not disrupt composite properties.

They are easily incorporated into the laminate as part of any of the normal production processes – hand lay-up, vacuum infusion, pre-preg etc. FO sensors do not conduct electricity and are not susceptible to electromagnetic interference (EMI) or damage through lightning strikes. They have excellent long-term static and dynamic fatigue performance, and are able to withstand high levels of shock and vibration. They can be produced in volume inexpensively.

Optical heart

Fibre optical cables can be regarded as conductors of light rather than electricity. They can do this because they are made up of concentric layers of glass having different properties such that light is internally reflected back into the core rather than escaping. If the fibre bends, the way different wavelengths within the light passing through the optic are reflected and refracted is altered and this results in a change in the wavelength (colour) spectrum emerging from the end of the fibre. The amount of this alteration is a measure of the amount of bend in the fibre.

If the fibre optic (FO) is embedded within a wind turbine blade, it will bend as the blade bends in response to applied loads. Thus, if the differences between the original unaltered light and that emerging from a bending fibre could be analysed, this would provide a measure of the strain the wind turbine blade is experiencing due to wind strength.

One way of examining this difference is to bring the altered light together with a sample of the unaltered light such that the two interfere with each other. Studies of the various wavelength relationships within the consequent interference pattern as it changes in response to bending loads can reveal even the slightest amount of bend. Because the system is so sensitive, it can be used to measure the strain in any component to which a FO strain gauge is bonded, not just those of composite material.

Analysing interference fringe patterns is an activity for scientific laboratories, not a function easily incorporated into industrial processes. A way is needed by which the strain-induced spectral change can be more easily quantified, preferably electronically.

The answer is to engineer diffraction gratings into the sensors. Fibre Bragg gratings (FBGs), so called after the scientist who pioneered use of the effect, emit light at a single wavelength (colour) when broadband (white) light is directed at them. The precise wavelength (colour) of the emission varies according to the amount of strain to which the fibre containing the FBG is subjected.

Because the FBG wavelength increases linearly with the applied load, it offers a direct measurement of strain. Measurement accuracy is high over a large strain range. The Insensys OEM-1000 Series Load Monitoring System provides a measurement resolution of 0.8 microstrain over a range of +/− 4500 microstrain, which is more than adequate to cover all likely rotor blade load conditions. Measurements are made in real time at a frequency of 500Hz.

FBGs are easily incorporated into optical fibres as part of the fibre manufacturing process. Over 100 sensing elements can be written into a single 250-micron diameter optical fibre – a simple way of providing multiple sensor installation and connectivity. Each grating consists of a series of very closely spaced bands of glass having different refractive indices, such that the boundaries between the bands can reflect incident light.

When light from a source located at one end of the optical fibre encounters the FBG, some of the incident light is reflected back from the boundaries. If the inter-band separation distances and the light wavelength ‘tally’, the reflections from successive bands are additive and the FBG transmits the single resulting wavelength, suppressing others. This emission is analogous to the ‘interference wavelength’ – the peak-to-peak distance of the interference waveform mentioned above.

When the fibre is strained, the relationship between the Bragg grating fringes or separations and the wavelength of the reflected light alters. Consequently, the wavelength emitted by the FBG changes. The monochromatic Bragg emission is readily converted to an electrical analogue suitable for subsequent digital electronic processing. Unfortunately, FBG sensors are affected by temperature as well as strain, so temperature-compensating electronics have to be part of the subsequent processing chain.


An Insensys system for application to a wind turbine rotor comprises three channels, one per blade. Four strain sensors (typically) located mutually at right angles at the root of each blade provide two pairs of strain measurements, one pair each for edgewise and flapwise bending moments.

This number is considered optimum for most in-service systems, though as many as 60 sensors might be fitted to a prototype system for test purposes. Sensors are either embedded during blade manufacture or retrofitted, and are connected to looped optical fibres that are similarly embedded or bonded to the blade. For each blade, a connector box embedded or retrofitted at the blade root provides all necessary connections between the blade and the hub, as well as light sources for projecting light along the optical fibres.

An interrogator unit in the blade hub interrogates the fibre sensors and receives the responses. The system operates on a time division multiple access (TDMA) basis, an electronic technology that maximises channel efficiency by allocating capacity on the basis of time slots. Sensor responses are passed to a processor that converts the results into a form suitable for input to the WT's programmable logic controller (PLC) or blade pitch controller. As a result, the PLC or computer commands blade pitch movements, both individually and collectively, according to the wind conditions prevailing at each blade.

Combining the Insensys-instigated pitch command terms with those emanating from the WT manufacturer's own control system to best effect, can be a complex multi-dimensional problem.

Here, Insensys has relied on the expertise of a leading provider of pitch control algorithms, Garrad Hassan, whose Bristol office has developed the necessary advanced individual pitch control algorithm for incorporation into the overall control logic. The two companies, whose collaborative relationship extends back several years, have worked closely together to ensure that the Insensys system design meets the requirements of the algorithm.

Tony Mercer, head of control system activities at Garrad Hassan comments, “we regard independent pitch control as a must have for the next generation of larger turbines. By using the latest control techniques, combined with reliable load measurement throughout the life of the wind turbine, we can improve its structural efficiency, cope with a wider range of adverse flow conditions and permit a larger, higher-yield rotor for a given nacelle and support structure.”

Insensys has also worked directly with a number of wind turbine manufacturers to integrate its system with their own proprietary control systems, so augmenting them with independent blade control capability.

Health monitoring

Although wind turbine rotors are an obvious focus for the Insensys load measurement technology, Phil Rhead points out that application is not limited to these. “We have put FBG strain gauges on turbine hubs, shafts, nacelles and even towers,” he says. “In fact you can use an optical strain gauge wherever you can put an electrical one. This makes it a practical and desirable system for structural health monitoring.”

He adds that, nevertheless, rotors are one of the areas of the turbine that can most benefit from monitoring. Among the most expensive wind turbine components, rotors are hard to inspect and still rely largely on manual inspection. Moreover, they are responsible for some of the heaviest and potentially most destructive loads seen by the drive train, especially when they are out of balance. They present, though, a challenging environment for any monitoring technology. Phil Rhead highlights in particular the fact that lightning strikes are not infrequent.

“All the signal paths within a fibre optical system are resistant to electromagnetic interference and substantially lightning proof,” he declares. “Compare that with conventional systems where, for example, lightning frequently tracks back to the in-hub amplifiers, which then have to be replaced”.

Rhead states that, while electrical (resistive) strain gauging is still the dominant technology for test and measurement companies, the conviction has grown over the last five years that optical technology is an inherently superior alternative. Industry insiders feel that it is only a matter of time before it becomes the measurement standard for all applications.

“I believe this is the only reliable way to do it [measure strain]” asserts Rhead. “Lightning strikes frequently destroy and de-bond conventional electrical sensors as well as damaging their associated electronics. The chances of a strike increase with turbine size and height, and with offshore location”. And he adds, “we've had our system trialled by leading turbine manufacturers, test houses and research labs and have not yet had a sensor fail during operation”.

While conceding that FO sensors are more expensive than conventional electrical strain gauges, Rhead argues that, by the time installation time and cost are taken into account, costings for commissioned systems are similar for both solutions. Experience with certain prototype wind turbines fitted with dozens of FO sensors for test and qualification purposes suggests that the economics are acceptable and that large amounts of data can be harvested successfully by this method.

The Insensys technology interfaces readily with other manufacturers' monitoring and control systems. This has been amply demonstrated in a collaboration with SKF Condition Monitoring, a company that specialises in monitoring gears and rolling bearings, components that account for a significant proportion of wind turbine failures.

Catching faults early is important since an unnoticed drive train defect in a US$1500 bearing, say, could ultimately lead to a US$100,000 gearbox replacement, a US$50,000 generator rewind, and a US$70,000 bill for accessing the failed components. ProCon is the company's condition monitoring system, intended to avoid expensive repairs.

SKF contends that monitoring both blade health and drive train health with the same integrated system improves the quality of SHM overall by relating drive train degradation to the rotor-induced forcing loads that cause it. A bonus from relating cause and effect in this way, the company points out, is that results recorded over time can help manufacturers to improve the design of turbine components and help operators to devise effective load reduction strategies.

A number of SKF clients, such as renewable energy provider Enertag, use ProCon to monitor their drive train components. Installed in each turbine's machine compartment, the system continually monitors levels of vibration at specific drive train gears and bearings. Data analysis then establishes the condition of the monitored component, identifying faults such as pitting or spalling (bearings) or damaged teeth (gears). Adding the ability to sense drive train input loads, both static and cyclic, in real time augments the system's power to diagnose a range of defects such as mechanical imbalance or looseness, shaft bending, failing couplings, structural resonances and even weak foundations.

Monitoring a dozen or more sensors in a rotor 30 times each second, the Insensys instrumentation rapidly generates large amounts of data. The system performs statistical analyses on blade bending data in both time and frequency domains to extract key information and passes this ‘summary’ data to the condition monitoring system.

Alternatively, it is passed to a data logger for subsequent retrieval and analysis. From the data, the system can calculate individual blade loads and, further, can make inferences about blade condition – especially if more sensors are installed in the blade than the two pairs at the root. Storing and analysing load service histories for the blades enables their residual fatigue lives to be predicted. Though this is not yet an exact science for composites, due to the still limited knowledge of the long-term degradation behaviour of these highly variable materials, the experience base is constantly growing, permitting on-going refinement of the predictive algorithm.

Resolving the edgewise and flapwise loads in the plane of the rotor enables the input torque to the drive shaft to be calculated. Plotting this over time shows the magnitude and variability of the drive torque and indicates whether recommended maximum levels are being exceeded, reducing intended service life. Resolving blade root bending moments in the horizontal and vertical directions enables offset loads on the drive shaft to be determined. Shaft bearings are designed to accommodate axial loads and continual excessive dynamic loading offset from this plane can accelerate degradation. Calculation of a resultant load vector will indicate whether or not there is prolonged offset loading.

Currently Insensys is working hard to expand its SHM capability, having seriously entered the condition monitoring (as distinct from individual blade pitch control) business only in the last 18 months. It offers a range of standard solutions suitable for new-build or retrofit applications. These include load monitoring units designed for hub PLC/pitch cabinet installation, stand-alone hub installation or R&D applications. The company also welcomes the opportunity to customise solutions for specific turbines and manufacturers.

There is a growing focus on software development. Says Rhead, “we're progressively bringing in automatic analysis. For instance, we now do trend analysis and are adding fatigue and lifetime prediction to our own data reduction software. Future rotor monitoring software will typically encompass cumulative load counting, residual lifetime estimation, critical event monitoring and frequency analysis”.

He claims significant interest from turbine manufacturers and operators and reports that the present technology is currently on 13 different types of turbine produced by 10 manufacturers. He predicts major market uptake, pointing out that the optically-based solution is under active consideration for many wind turbines now in their early conceptual or design stages.

“Sophisticated electrical power utilities are used to having lots of data,” argues Rhead. “Wind energy has hitherto operated with relatively little; we believe that, as the scale of wind energy grows, particularly in the offshore sector, turbine manufacturers will find it in their interests to provide more data. Strain measurements, obtained through reliable optical means, will be an essential part of this”.

CEO Martin Jones agrees, adding that Insensys is well placed to succeed with its leading-edge technology because of its dual contribution to reliable, economic wind farm operation. “Using the same technology to capture a larger proportion of the available wind energy while also expanding the scope of structural health monitoring is our unique selling proposition,” he says. “We think it's one that has wide market appeal”.

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