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Predictive maintenance for wind turbines
Extended gearbox life and optimum machine utilisation
ZF Friedrichshafen AG is a leading global technology group in driveline and chassis technology as well as active and passive safety technology. With integrated solutions, the ZF Aftermarket Division guarantees the performance and efficiency of vehicles and machines throughout their life cycle.
As a component manufacturer in the wind turbine gearbox sector, the company has been involved in predictive maintenance since 2016. . Wind turbines are often situated in remote locations and are difficult to access due to their height. Damage detection, maintenance or unscheduled failures are therefore time-consuming and cost-intensive.
That’s why a system has been developed to carry out load monitoring. It serves to detect early stage failures and provides the means to identify optimisation potential for wind turbine operation.
+49 7541 70078-767Predictive maintenance for intelligent wind turbine gearboxes
Connecting turbines to a cloud-based platform creates significant added value. The gathered data can be used to make predictions regarding the behaviour of the wind turbine gearbox.
In the event of damage, the machine knows in advance which parts needs to be repaired or replaced. What’s more, the information about the operational behavior of the gearbox enables predictive intervention.
This allows the service life of gearboxes to be extended, achieving optimal control of wind farms. ZF is playing a pioneering role in predictive maintenance, other words.
„ZF’s cloud-based predictive maintenance solution is used to visualise loads and optimisation potential during operation of wind turbines, including detailed calculations for wind turbine gearboxes. It also serves as a platform for cloud-based collaboration with other partners in the field of condition monitoring for wind turbines. The backend developed by doubleSlash in the Microsoft Azure cloud processes data in real time, while the frontend formats the data for presentation to the user.“
Dr.-Ing. Andreas Vath // Industrial Technology Division // ZF Industrieantriebe Witten GmbH
The system monitors the entire wind turbine drivetrain during operation, and a 'virtual twin' of the gearbox is created based on the data gathered. This allows the performance and condition of the wind turbine to be monitored and predicted remotely.
The backend developed by doubleSlash in the Microsoft Azure cloud processes data in real time, and the frontend developed with Angular and TypeScript formats the data for presentation to the user.
The ZF Predictive Maintenance Cloud also serves as a platform for cloud collaboration with other partners in the field of condition monitoring for wind turbines.
Data management and IoT competency for a rapidly implementable predictive maintenance solution
doubleSlash was involved in the ‘Predictive Maintenance for Wind Turbines’ project as a strategic software partner and provided support in project management, data visualisation and backend development with Microsoft Azure for networking the systems.
Clear and effective presentation of the live data (using Live Data View) was particularly important to support initial analysis, as was the option of integrating other key players for an integrated customer experience.
The project was implemented using agile scrum methodology and accompanied by doubleSlash right from the first prototype to the finished solution.
Our services:
- Agile project management
- Technical and IT conception
- IoT architecture
- Agile software development
- IoT backend development
- Frontend development and data visualisation
- Development of an environment for data analysis
- Optimisation of data storage
- Optimisation of calculation algorithms
Technologies used:
Microsoft Azure (IoTHub, Stream Analytics, Service Bus, Azure AD, SQL, Blob Storage)
Python
Visual Studio Teamservices 2017
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