Scientist creates artificial intelligence algorithm to monitor machinery health

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An artificial intelligence algorithm greatly increases accuracy in diagnosing the health of complex mechanical systems. In blind tests using data coming from highly unpredictable and real-life situations, the algorithm consistently achieves over 90 percent accuracy, say the researchers.

“The ability to extract dependable and actionable information from the vibration of machines will allow businesses to keep their assets running for longer while spending far less in maintenance. Also, the investment to get there will be just software,” says Dr. Teixeira, who is the technical lead for the Health and Usage Monitoring Systems (HUMS) analytics project at UAH’s Reliability and Failure Analysis Laboratory (RFAL).

In blind tests using data coming from highly unpredictable and real-life situations, the algorithm consistently achieves over 90 percent accuracy, says Dr. Teixeira.

Read the source article at ScienceDaily