Bearing Failure and Analysis

Abstract

Chris and Fred discuss how bearings fail. Bearings are among the most common components used in products and systems. So, how do they go wrong?

Key Points

Join Chris and Fred as they discuss how bearings fail, in response to a question from one of our listeners whose organization has experienced some bearing failures in wind turbines (all of which were caused by ‘systemic’ or endemic root causes). So, how do bearings fail?

Topics include:

• Simple answer – spalling. Spalling is a type of fatigue unique to bearings, caused by the slight friction forces that the rotating balls exert on the race surface they roll over. Spalling leads to pitting, which increases friction, which in turn heats things up, causing them to expand, which adds stresses, and ultimately accelerates the growth of cracks and pits, until the ball bearing (in many cases) literally explodes.
• And when it comes to testing or life data analysis … you often test or observe bearings where a number have failed … leaving a number that is still working. The times at which we last observed those to be still working are what we call ‘censored data points’ and need to be included in the analysis.
• How can you predict the times at which bearings will fail by inspection? With difficulty. Non-Destructive Inspection (NDI) is often used to measure the depth of fatigue cracks, but it becomes challenging with bearings. You need to pull the balls or rollers out and then look at the races they roll over. This is very challenging. Vibration analysis provides a warning of impending failure, as those pits often cause vibration. Until pits appear, you are blind!
• What about refurbishment? We do that with a log with ‘big’ bearings. But does the refurbishment make the bearing as good as new? … as good as old? … as good as something in between? This comes from what we call the ‘general renewal’ theory, and it misses the maintenance-induced failures that you get whenever you perform maintenance.
• So what do you do? Do whatever works best to understand how your system fails. Perhaps you could consider degradation modeling, or utilize your existing data (if you have a large dataset), or explore alternative approaches.

Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.

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Show Notes

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