yet2 is supporting the United States Bureau of Reclamation (USBR) to identify data analysis solutions (software/platforms/models) that can reduce and prevent failures and guide maintenance events in hydroelectric power generation plants. With the many data streams Reclamation already collects from various power generation equipment, Reclamation is seeking to identify and monitor useful relationships between multiple data streams so as to identify signals of deterioration, impending failures, or other operational issues, as well as to trigger preventative action when anomalies occur. To do this, Reclamation is exploring primarily AI/ML-enabled data analysis software and platforms.
Details
Desired features and outcomes of the AI anomaly detection software/platform/tools being sought include:
- Identification of dangerous and anomalous data patterns that signal potential deterioration, impending failures, and other operational issues
- Ability to learn from previous events to enable prediction, early-detection, and prevention of impending failure events and dangerous deterioration
- Integrated triggering of automated avoidance/prevention measures, based on anomalous conditions identified and detected
- Enablement of predictive maintenance to avoid failures and dangerous deterioration, as well as unnecessary outages for inspections
- Efficient system design via consideration of the normal way the quantities react to changes in machine operation and/or user changes and therefore minimizing the number of specific data streams and data relationships to monitor on a continuing basis for failure signals
At this stage in their search, Reclamation is open to considering application-specific end-to-end solutions, application agnostic “building-block” tools/platforms, and everything on the application development spectrum in between.
Know of a Relevant Technology and Company?
If you would like to submit an innovative technology and associated company to be considered by our client, Reclamation, for partnership, please contact Megan Waldock (mwaldock@yet2.com).
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