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Real time fatigue data

Real time fatigue data

(OP)
I am looking for help !

I have "accumulation rainflow" data for propshaft torques, and I need to understand the overall "damage" that this would cause.  My data is a matrix of Mean Torque and Torque Amplitude, with the individual cells showing the accumulated cycles at each condition.

If all the data was simple bi-directional fatigue (i.e. with mean torque =0), then I think I know how to combine the data following miners rule.  But I am not sure how to manage offset torques.  Should I use something like the Goodman rule? and if so how do I apply it?

Thanks for any advice !

RE: Real time fatigue data

I vaguely remember that dislocations are propelled by strain changes, therefore the mean strain makes no difference for high cycle fatigue. This is borne out by the Bosch blue book, which always talks in terms of stress ranges.

Low cycle fatigue is a different animal.

 

Cheers

Greg Locock

I rarely exceed 1.79 x 10^12 furlongs per fortnight

RE: Real time fatigue data

(OP)
Thanks Greg

The data I have includes some very low torque / high cycle data, but it also includes some very high torque / low cycle data.  That means I have a mix of high and low cycle data, hence the reason I think I need to take the mean torques into account.  An example would be something like 20 cycles of 1500Nm mean torque with +/- 200Nm.  If the ultimate strength of the part was say 2000Nm, then the max torque of this combination (1700Nm) is getting pretty close.  I think this must be more "damaging" than just +/-200Nm with no mean torque offset?

Dave

RE: Real time fatigue data

I agree. However, to discuss this any further I'd have to go and read about it, which i guess you can do with more enthusiasm than I.

Looks like the Coffin-Manson Law applies,and use Goodman's rule to account for the offset.

  

Cheers

Greg Locock

I rarely exceed 1.79 x 10^12 furlongs per fortnight

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