Remote monitoring

Improved availability with Artificial Intelligence

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Improved availability with A.I.

By using advanced data analytics, artificial intelligence and deep learning, our Equipment Health Monitoring system (EHM) gives you real-time insights into your equipment.

A web based portal provides precise information about performance and component lifetime so that any negative trends can be mitigated at an early stage, ensuring optimised operation at all times.

Optimised performance with remote monitoring

The energy sector is undergoing a digital transformation, and the industrial Internet Of Things (IOT) is helping improve the safety, productivity, accessibility and sustainability of our energy systems. A rising electricity demand, and the gradual move from fossil fuels to renewables, and from centralised grids to distributed power systems, have lead to increased system complexity that is being solved with digitalisation.

Medium-speed engines have an essential role in the future energy mix, as they provide dispatchable back-up power to balance the instable electricity generation from renewables. Your Bergen medium-speed equipment can now become digitalised, and thus be compatible with tomorrows energy systems, ensuring the highest levels of availability for critical power generation.

The last couple of years Bergen medium-speed engines have been delivered EHM-ready, meaning that a few simple measures are all that’s needed to go online with the equipment. Engines delivered before this became standard, can be retrofitted.

When signing up for EHM, you will be given access to a web based portal where you can monitor your equipment literally from anywhere in the world. The data is displayed through a user-friendly web application, providing unparalleled real-time insight to your equipment. And our service technicians have the same information readily available, so that advice and reports can be shared seamlessly.

The system captures data from multiple sensors and translates it into a single output that makes it possible to quickly identify areas of concern. Deep learning is used for detection of anomalies and for calculating remaining useful life of components. This opens for condition based maintenance (under development), where the overall performance is kept at its peak at all times with minimum operational costs.

Remote technical support is lifted to a higher level, where high quality, real-time data, makes it possible to prevent any issues from escalating. With EHM our technical experts can also perform advanced troubleshooting remotely, making sure many of the issues are solved rapidly, without the need to travel to site.

Optimal performance

  • Proactive failure prediction and prevention
  • Less unplanned stops and shorter stops when they occur
  • Advanced remote digital support with diagnostic capabities
  • Fast response times and virtual troubleshooting
  • Access to real-time operational data
  • Historical data and trend analysis
  • Monthly technical reports
  • Optimised utilisation of all engine components
  • Easy maintenance planning without costly surprises

Edge computing and Advanced Machine Learning

Our industry-pioneering concept leverages Edge Computing (on-site computation and data storage), a cloud-based Internet of Things platform and Advanced Machine Learning (AML) to provide unparalleled insight into your equipment. The combination of these technolgies enables secure, fast and stable two-way communication between the plant and the cloud, where both you and our technical experts have access.

Using the EHM dashboard, service technicians and remote service engineers are able to gain real-time insight into engine performance and health, enabling them to identify potential issues and intervene early to substantially reduce operating, maintenance and downtime costs.

Gain actionable insights

A single Bergen medium-speed engine can have more than 200 sensors transmitting a vast amount of data that measures all aspects of an engine’s health and performance at any given moment. Our EHM is a system for capturing and storing this abundance of data and subjecting it to Advanced Machine Learning (AML) algorithms in order to perform predictions on engine health. The predictions are translated into actionable equipment insights and visualisations that are accessible remotely via a tablet or a computer.

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