An indentation method for measuring welding residual stress: Estimation of stress-free indentation curve using BP neural network prediction model

The measurement of welding residual stress (WRS) is necessary to formulate the stress control strategies, in order to ensure the reliability of engineering structures during their service life. The instrumented indentation technique can detect surface residual stress nondestructively with an acceptable accuracy, making it a desirable option for in-situ applications. However, it is difficult to meet the requirement for stress-free samples, particularly in the case of welded joints with non-uniform mechanical properties. In this work, the impact of stress-free indentation curves on determining WRS is furtherly studied based on the previously proposed indentation energy difference method. The WRS in a mismatched welded plate is measured using single reference method and distributed reference method, respectively. The study suggests that using the single reference method can lead to significant errors in determining the sign and magnitude of WRS in the weld zone. A prediction model combining the continuous spherical indentation (CSI) method and Back Propagation (BP) neural network is proposed to obtain the stress-free indentation curves of local positions nondestructively. And the CSI-BP method is verified through reverse finite element analysis and experiments.