Acoustic sensors to monitor critical assets (OIC 2019)
The NEMO Link converter station connects the electricity system of Belgium and Great Britain via subsea cables. The cooling systems of the converters ensures its safe operation. This already closely monitored cooling system serves as an ideal reference system to test a new type of sensors in a challenging environment. The goal of this POC is to understand if the sensors in combination with the Artificial Intelligence (AI) algorithm can provide additional health indicators to complement the existing monitoring and alert system. Beside the capability of the algorithm, we give answers to practical questions of mounting the sensors, ensuring stable operation and safe data transmission.
Three phases define this proof of concept:
- Firstly, a feasibility study describes the possibilities as well as the limitations of the project.
- In the second phase, the sensors to start collecting acoustic samples. Those samples cover typical operational modes of the system. That information enters a deep learning algorithm and together with Nemo Link experts, OKTO Acoustics trains its algorithm to define a healthy operation mode. Special attention is given to the cooling pumps that undergo the first maintenance interval during the POC. Differences before and after those measures shall deliver valuable insights on the status of the asset.
- In the last project phase, the monitoring system will go in live operation mode.
OKTO Acoustics won Elia Group’s Open Innovation Challenge is awarded with a budget of 20.000€ to run a proof-of-concept at Elia Group.
Mounting of sensors
OKTO Acoustic developed custom-made mounts to attach the sensors on the assets of the cooling system. The special environment is adding another layer of complexity to this project.
Training the algorithm
Automatic detection of unhealthy operation or faults requires the sampling of those cases. Since this is not possible for a system in operation, the analysis is based small deviations in the sound spectrum before and after maintenance measures. Additionally the neural network is trained on the different standard operation modes of the cooling system such as pump switches and different valve positions. Operational log files serve as a basis and Nemo Link’s technical experts provide expertise that allows OKTO Acoustics to train the algorithm ex-post and to prepare for live operation.
After training of the basic operation modes, the system goes into live operation. The system needs to prove its capability of providing the current operation mode and the state of each monitored asset out of the complex set of information. In case the system proves to operate successfully, Nemo Link is considering a long-term test of the smart sensors.
Currently the sensors are mounted and samples are tested.