Qualification of Austenitic Stainless Steels for the Development of Load-Sensitive Material Sensors

Abstract

To detect mechanical overloads on the component directly in operation, a metastable material can be used as a load-sensitive sensor when combined with an eddy current testing system. In order to find a suitable metastable sensor material that exhibits microstructural changes at an early stage before fatigue failure, quasi-static tensile tests and cyclic rotating bending tests were carried out with the austenitic stainless steels 1.4301 (2 batches), 1.4305, 1.4541 and 1.4550. For the detection of microstructural changes, electromagnetic testing was used in-situ in the tensile test and ex-situ between the rotating bending test after a pre-defined number of cycles. The investigated materials 1.4301 batch2 and 1.4550 showed the largest signal changes and the lowest austenite stability both in the tensile test and under cyclic bending load. Due to the better mechanical properties, 1.4301 batch2 should be preferred. The order of the austenitic stainless steels tested was similar in terms of transformation behavior in both tests. Thus, the tensile test combined with in-situ electromagnetic testing appears to have potential as a suitable benchmark test for austenite stability. With regard to the cyclic bending stress, an overload of the specimens could be detected for the materials 1.4301 batch2, 1.4305, 1.4541 and for the 1.4550 on the basis of a significant amplitude change. At low bending stresses, uncritical for structural integrity, no increase in amplitude was measured. The results have shown that an early detection of overloads is possible with several materials, however, the potential for detecting overloads varies between materials and also between individual batches. In addition, it has been observed that as the bending stress increases, the gradient of the change in amplitude over the number of cycles increases as well. Thus, with a known number of cycles, it could be possible to classify the previous load spectrum based on the difference in amplitude between two measurements.