An artificial intelligence algorithm created by University of Alabama in Huntsville (UAH) principal research scientist Dr. Rodrigo Teixeira greatly increases accuracy in diagnosing the health of complex mechanical systems.
“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.
If you can detect a fault before it becomes serious, then you can plan ahead and reduce the time machinery spends idle in the shop. As we all know, time is money.
“This technology is in the trial stage.
A patented passive cooling system for computer processors that’s undergoing optimization at The University of Alabama in Huntsville(UAH) could save U.S. consumers more than $6.3 billion per year in energy costs associated with running their computer cooling fans.
Imagine what it could do if in global use.
The system, which was awarded $10,000 in 2014 UAH Charger Innovation Funds, uses convection to circulate 3M’s Fluorinert FC-72 liquid through channels in a computer’s processor and then into a heat sink that serves as an external radiator.
Its adoption could save computer manufacturers $540 million annually in manufacturing material costs by eliminating fans and associated wiring. Energy and materials savings are based on a future in which 300 million machines are in use in the U.S.