I understand mechanical fatigue as a Process Control Engineer (we care !). But fatigue of a data set is a bit esoteric for my small brain ? Especially a sinusoidal data set ... must look at it again . Spring fatigue of a car suspension, that is real as a 100000 km car suspension in the rocky desert is more damaged than same km on nice highway.
On 3/28/2007 6:26:37 PM, jmG wrote: >On 3/28/2007 5:08:55 PM, rsoloski wrote: >>The purpose of the sinusoidal >>dataset was only to show by >>example the usage of the cycle >>count routines. >__________________ > >OK, then adapt to real data > >jmG ___________________
... read more, read the attached.
Unless the "Rainflow cycle" applies to real life, you have not proved your proposal is usable as demonstrated in the first part of the work sheet. Raw data from capture should always (most of the time) be smoothed . Then below Marlett you can apply the Mathcad "local Min/Max". It locates all "peak/Valley", not missing any . In fact if "Rainflow cycle fatigue" purports to count all reversal of the 1rst derivative, then the part of the project below Marlett is done correct using the "local Min/Max".
The last part of the project is not done, i.e: pack all "Peak/Valley" and center them at the mean of the data set ...
Interesting project, thanks for the idea. This project will surely be welcome in the future.