As an acoustical engineer by trade, one of my acoustic consultancy’s specialisations is to monitor, assess and advise on wind farm noise levels. And this is where the story begins. We were told by a partner that experienced technicians could detect faults just by listening to the changes in sound generated by wind turbine blades. As acousticians we were intrigued.
That was six years ago. We decided to start a journey to see if we could create a device which could save the wind industry time and money using ‘intelligent listening’.
Since that day, we’ve travelled across Europe, the USA and Australia multiple times talking to experts across the industry and trialling our device, Ping Monitor.
Last year, we formally established the company Ping Services. This year we’ve completed a successful seed funding round raising over US$500,000 to help us commercialise the Ping Monitor device. We’ve also won a highly coveted Good Design Award for product design too.
The rate of progression has been phenomenal. But let’s go back to where it started and deep dive into the issues we see in our industry and where we are trying to help.
The problem
Wind turbine rotor blades have a relatively large failure frequency compared with other wind turbine elements; at around 23 per cent of the total number of turbine breakdowns.
Operation and maintenance (O&M) has been shown to contribute to around 25 to 30 per cent of the total costs of offshore wind power.
The current turbine blade maintenance approach is to repair damage as necessary. Repairs are carried out following a periodic survey of the rotor blades, which are undertaken through visual means using drones, ground based cameras or rope access.
This approach is sufficient when damage propagates slowly, however, some damage can develop rapidly. The late detection of damage can result at best in expensive major repairs and at worst blade replacement or blade failure leading to both large scale repair costs and power generation loss due to extended downtime.
Condition monitoring is widely used in the wind turbine industry to predict and reduce the risk of failures in rotating components such as bearings, gear boxes and generators. There is, however, currently no widely adopted method to continuously monitor the health of wind turbine blades.
Preventative maintenance of turbine blades provides the potential to extend a blade’s life span to support O&M decisions and avoid major failure events. Operators of large wind farm with thousands of turbines are looking for solutions to reduce costs and concurrently increase turbine efficiencies.
