The Challenge
- Client has many signals from his turbines, but no access to them
- Old protocols and interfaces making access to sensor data difficulty
- No user management
- No clear security concept
The Approach
- Data value analysis to identify data trends with benefits for the client
- Implement a time series database to save collected data
- Implement a REST API for easy access of the data
- Develop and implement user management based on roles and security levels
- Develop and finalize security concept for the REST API and the underlying system
- Running all SW components on separated docker containers with an internal network to provide maximum security, usability, interchangeable
Result & Added Value
- Robust SW due to integration level testing of the REST API therefore testing underlying components
- Results of the data value analysis not limited to the predictive maintenance aspect
- Running predictive maintenance algorithms for the turbines and subcomponents for an optimal maintenance cycle
- A robust time series database enabling collecting of important signals
- Currently providing trend tables for those signal data for further analysis
- Security concept for further use by the client
- Simple deployment due to using docker containers on Linux machines
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