Inhaltszusammenfassung

The availability of reliable fatigue data is of continuous and often urgent need. The paper to be presented therefore intends to show how the potential of non-destructive testing methods, digitisation in metrology as well as signal processing can be combined in order to achieve a significant gain in information concerning the fatigue behaviour combined with a reduction of required experimental effort and cost. The new SteBLife approach is an enhanced short-time calculation method developed at...The availability of reliable fatigue data is of continuous and often urgent need. The paper to be presented therefore intends to show how the potential of non-destructive testing methods, digitisation in metrology as well as signal processing can be combined in order to achieve a significant gain in information concerning the fatigue behaviour combined with a reduction of required experimental effort and cost. The new SteBLife approach is an enhanced short-time calculation method developed at the Chair of Non-Destructive Testing and Quality Assurance at Saarland University, which takes into account that a material’s elastic-plastic reaction and hence relationship is non-linear. With respect to a test strategy, the number of fatigue experiments required to determine a material’s complete S-N-curve can be limited to three to five tests only (SteBLifemtc, mtc: multiple tests, trend curve and SteBLifemsb, msb: multiple tests, scatter bands) in cases that mean values and/or complete scatter bands of S-N-curves are required. If a trend S-N-curve is sufficient, the effort can be reduced to one single test only (SteBLifestc, stc: single test, trend curve) with a special step-shaped specimen. This leads to a significant improvement in efficiency when compared to the conventional way an S-N-curve is determined where a minimum of 15 fatigue tests is required. Within the work to be presented the SteBLife method is demonstrated for normalized SAE 1045 (C45E) steel. » weiterlesen» einklappen

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DDC Sachgruppe:
Ingenieurwissenschaften