Framatome’s EMPATH and ECMS data collection and continuous monitoring systems are flexible hybrid expert/ML/AI systems that also allow for real-time and historical data science. MotorDoc LLC and MotorDocAI are partnered with Framatome for hardware distribution, algorithm development, application and technical support, and deployment strategies. This provides a global development and support organization that was initially focused on nuclear power but has expanded well into industrial and other utilities including on and off-shore wind.
The infrastructure is extremely flexible and present systems (hardware/software) in their basic form are based upon the original licensed patents from Oak Ridge National Labs starting in 1992 (developed prior to 1988). The system has continued through various iterations towards the present day hybrid-system and various pre-2000 remote applications. The present version of EMPATH and ECMS were released in association with MotorDoc LLC in 2017 with EMPATH software version 7.0 and advancements to industry specific (ie: wind power and solar transformers) with the release of version 8.0. The expert algorithms provide immediate first data responses in less than 1 minute with other ML/AI and data science capabilities to perform TTFE (time to failure estimation).
There are multiple variations of infrastructure that are possible, such as shown in Figure 1. The technology applied in this overview is the Framatome ANP ECMS continuous monitoring system which utilizes the EMPATH™ software and prognostics algorithms, as well as EMPATH data collectors. The system utilizes a hybrid edge/cloud platform with the ability to communicate via local network, internet, cellular modem and related options for remote alerts and dashboards including additional data science capabilities (Figure 1). Each channel described includes three phases of voltage and current. However, depending on the application, can be brought down to a single phase of current or even applied to DC machines (including mobile).
Following is one scenario for front-end power data collection. In this case, a single lighting panel at a commercial facility.
As these are just the basics, please contact us for more information at info@motordoc.com for more details or to see the data science example above.