As the world becomes increasingly digitised, sensors are being deployed in sectors as varied as aerospace to zoology to monitor performance of equipment, risks to assets, or the impact of changing environmental conditions.
And acoustic emission technology, that has commonly been used to monitor damage to structure such as bridges, is now being utilised by the wind industry as a more efficient way to detect damages to blades.
Wind turbine blades are one of the most complex structural parts of a wind turbine due their intricate geometry and configuration of materials. Demanding loading conditions mean that the blade needs adequate stiffness, good buckling resistance and extreme structural strength.
But blades can suffer damage from lightning strikes; high energy impacts from weather and wildlife; blade skin ruptures and perforations (including those caused by leading-edge erosion); and cracking and delaminations due to harsh environmental conditions or small manufacturing defects.
Blade damage can reduce energy production by disturbing the smoothness and flow of the blades – a major feature in how they generate energy. Damage can lead to blade failure if severe enough.
Yet, inspection of blade health has typically been carried out infrequently, with some blades being inspected every few months, while others can go well over a year without undergoing inspection and testing.
The height of blades from the ground makes spotting damage extremely challenging. Use of drones for inspection has become common, but drones cannot detect damage inside the blade. Vibration detection technologies are also used to monitor changes in the pattern of vibrations as the turbine turns that could indicate a fault. But this is not very precise, since vibration patterns can be affected by an unrelated event, such as a truck passing by.
Real-time, 24/7 monitoring
In contrast, AE technology such as that used by Sensoria™ wind blade monitor – developed and manufactured by MISTRAS Group (NYSE: MG)– can find damages that are not open to the surface, and in real time. AE sensors can be installed on turbine blades to monitor their integrity constantly by “listening” to the sounds of growing cracks, breaking fibres and other forms of active damage.
AE sensors can detect the noise made by damage forming in a material which cannot be heard by the human ear. Even small-scale damage emits minor frequencies and energy releases that are picked up by AE sensors.
The sensors then notify the data acquisition box located in the turbine hub, and users receive a real-time mobile alert to check the Sensoria™ Insights data portal, an easily-accessible web-based portal that contains all current and historical blade data. Operators can use the data to make better-informed decisions on whether to take immediate action to send teams out to mitigate the damage, including by requesting MISTRAS’ own technicians and drone pilots through Sensoria™ Dispatch. All data on blade health is stored in the portal, and can be accessed from anywhere in the world.
If the damage is not serious, repairs can still be made at the next scheduled time. Constant monitoring of blade condition can help wind farm operators plan stocks of spare parts, eliminating the common practice of keeping quantities of spare parts in storage just in case a blade fails.
Low LCOE
“If a wind turbine operator conducts an inspection and then a week later the turbine gets hit by lightning, they may not find that damage until the next scheduled inspection, which could be upwards of a year or two.
“With AE, you can install the sensors once and then they constantly listen for blade integrity issues, and the operator will know about it as soon as it happens” says Keith Respet, MISTRAS Group’s renewables product line manager.
AE should be used to complement manned inspections of turbine blades, not replace them completely. Though it can alert operators to a problem, it cannot provide information on exactly what type of damage has occurred, nor its severity. But its main benefit is to immediately alert operators to a problem, so a technician can assess it and identify the best maintenance strategy.
“It means operators can do scheduled maintenance less often and keep their turbines running in the meantime, rather than shutting them down every six months just to check if something is wrong even if nothing has suggested this,” says Respet.
In short, by enabling problems to be fixed before they become more serious, AE sensors maximise the performance of wind turbine blades, and avoids costly downtime, and knock-on impacts on the wind farm’s levelised cost of energy.
Find out more about how Sensoria provides Edge-to-Edge Intelligence to help maximise blade uptime and performance here.