Statistical algorithms for eddy current signal and noise analysis

Accuracy of noise and signal models utilized in eddy current (EC) signal analysis plays a significant role in the performance. While many studies focus on development of accurate models for different EC probe signals, noise is commonly modeled using simplistic Gaussian models. Accurate noise model is as significant as the signal model in detection and classification tasks. In this paper, statistical models for representation and synthesis of EC measurement are developed. Filtering algorithms for different types of noise are also discussed. Considering EC signals as complex data, anomaly signal and random noise are modeled in the complex plane in rectangular form using Gaussian Mixture Models (GMM). Analysis results show that GMM along with noise filtering algorithms enhance performance of noisy EC signal analysis.