4.4. Comparison between predictions and experiments
The stress measured at different speeds in the above experiments was
substituted into the matlab fitting program, and the fitting curve was
expressed as Eq.(17) based on Eq.(1). The fatigue life of fan blades
under different working conditions was calculated (Fig. 9) as listed in
Table 5. Substitute the number of cycles measured in the above test into
Eq.(14).The cumulative fatigue life was shown in Table 6.The predicted
fatigue life was compared with the experimental data, the relative
errors between the predicted results and the experimental data were
shown in Table 5 and Table 6. It could be seen that the relative
deviations between theoretical prediction and experimental results with
revolving speeds of 1600, 1800, 2000 and 2200r/min were about 10.0%,
2.5%, 3.9% and 11.1% respectively, and the error between cumulative
fatigue life test and Miner’s theoretical calculation was 10.8% with
acceptable dispersion. Therefore, the improved method based on the
concept of nominal stress could effectively predict of the fatigue
lifetime of complex fan blades.
In addition, it is well known that fatigue life outcomes tend to be much
dispersed [45]. Therefore, in general, the general rule and analysis
results of high reliability can be obtained through repeated large
sample experiments. Under the circumstances, resources often limit the
number of experiments. When more specimens and more stress levels are
noticed for fatigue tests, more accurate fatigue properties would be
determined which makes results more accurate.
It was clear that through modified method (6) and (7), fatigue lifetime
of fan blades subjected to different rotating speed conditions could
conveniently and easily be predicted by the minimum data set of a small
number of experimental fans without any additional experimental studies.
In short, the fatigue life of fan blades under different working
conditions could be predicted only by obtaining the maximum stress of
fan blades’ model and S-N curve of materials. The correlation
between prediction results and actual experimental results was
relatively good.
Conclusions
A method of predicting fatigue life based on the S-N curve and
mean stress was proposed in this study, and a special application
dedicated to the ventilation cooling system of high-speed-train was
investigated. The effectiveness of the prediction model was confirmed
through a comparison with fatigue bench test system. The primary
conclusions were summarized as follows:
- The maximum stress of the fan was calculated by using the finite
element method, and the stress concentration was located at the root
of the blade.
- The fatigue prediction model was based on mean stress and also took
several specificities of the fan structure (SCF, surface quality
coefficient…) into consideration. By means of the S-Ncurve of the material, the fan’s life was predicted by using this new
prediction model according to equivalent life curve and cumulative
damage criterion.
- The fan fatigue test system with adjustable frequency was built.
Experimental results showed that the method was successful, in which
reasonable correlation was achieved between predictions and actual
experiments. To reduce stress concentration and improve service life,
making an arc or a stress groove at the blade root was recommended.