Predictive Maintenance: Difference between revisions

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{{Disclaimer}}
{{Disclaimer}}
''This page is about the applications of machine learning (ML) in the context of predictive maintenance. For an overview of predictive maintenance more generally, please see the [https://en.wikipedia.org/wiki/Predictive_maintenance Wikipedia page] on this topic.''


Quickly detecting power system faults can help reduce power system waste or improve the utilization of low-carbon energy resources. ML can help detect faults in real time from sensor data, or even forecast them ahead of time to enable preemptive maintenance.
Quickly detecting power system faults can help reduce power system waste or improve the utilization of low-carbon energy resources. ML can help detect faults in real time from sensor data, or even forecast them ahead of time to enable preemptive maintenance.

Revision as of 13:47, 26 August 2021

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This page is part of the Climate Change AI Wiki, which aims provide resources at the intersection of climate change and machine learning. This page is about the applications of machine learning (ML) in the context of predictive maintenance. For an overview of predictive maintenance more generally, please see the Wikipedia page on this topic.

Quickly detecting power system faults can help reduce power system waste or improve the utilization of low-carbon energy resources. ML can help detect faults in real time from sensor data, or even forecast them ahead of time to enable preemptive maintenance.

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