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Feature detection and monitoring of eddy current imaging data by means of wavelet based singularity analysis.

This paper describes the first report of method for identification of transient changes and turbulent features in the eddy current data. The proposed method is unique as it is fundamentally noise immune. It has significant relevance to feature extraction and characterisation in all areas of condition monitoring including NDT testing and fault diagnosis. The proposed method has significantly contributed to the successful funding bid from EPSRC (EP/I037326). Practically, it can be used for early warning of wind turbines when faults are still at an incipient stage, which has attracted collaborations from power companies like Wind Prospect Ltd and TNEI.