Non-Destructive Residual Strain Prediction Using the Binary Pattern of Eddy Current

In recent years, non-destructive evaluation (NDE) has attracted increasing attentions. Different electromagnetic signals have been used for studying the microstructure of materials. However, the features extracted for NDE share the limitation that these features were separately designed and roughly assembled. In order to overcome this limitation, a group of features that include the basic binary pattern of eddy current (BPE) and three improved features named simple-BPE, spat-BPE, and direction BPE (DBPE) are proposed to predict the residual strain (RS). Four features are designed through encoding the modulus variation of multi-frequency, multi-spatial, and multi-direction eddy current signal. In the experiment part, two types of experiments are used to test our four features. Based on the results, the performance of BPE-based methods outperforms the conventional features. Within four proposed features, the best prediction accuracy (0.03057997 for C45E4 and 0.03167161 for AlCu4Mg1) is obtained by adopting spat-BPE; the most efficient feature is simple-BPE, and a balanced performance is achieved by BPE and DBPE, performed not as good as the other three features. It has been proved that our binary-encoding-based features are beneficial to building the relationship between the NDE signal and the property of material (e.g., RS) and could be applied to a wide range of applications.