Data Managing for Predictive Maintenance of Turbine Engines
In 2012, we were contacted by a global energy leader that provides equipment, solutions, and services across the energy value chain from generation to consumption. The project was connected with turbine engines and generators predominantly used in aviation and the power industry.
Ensure reliable monitoring of the turbine engines by measuring and analyzing their vibrational characteristics.
Provide reliable acquisition, display, and configuration of the parameters of turbine engines to precisely monitor their status.
To succeed with the project, we needed to create and implement a module for storing and retrieving the data the client collects from vibration monitoring sensors installed on all the engines.
First, we collected data samples from up to 300,000 sensors each providing sample data measures once per second. The application contained, organized, and saved this volume of data.
Then, we designed and implemented robust storage to save, retrieve, process and maintain raw data collected over a certain period of time. The data is stored in a set of highly indexed binary data files that are managed by a pluggable service component.
- Software architecture and design
- Implementation and optimizations
- Software debugging and unit testing
- Functional and performance testing
- Warranty support
The delivered hub plugin supplies data for continuous monitoring of the turbine engines, which allows for effective predictive maintenance.