Damage detection of structures using blind source separation and multifractal detrend fluctuation analysis

Today, structural health monitoring techniques that can detect damage in early stages have become very important. For these reason, such techniques must be able to detect slight damages. However, a large number of algorithms that have proposed so far for damage detection are unable to identify early-stage damages. One of the approaches that can be employed is multifractal method. In this paper, a damage detection technique is proposed based on multifractal detrend fluctuation analysis and blind source separation. In the first stage, the accuracy of three methods of blind source separation is compared and the most efficient method in decomposing structural vibration signals is selected. These methods include blind modal identification, combined method, and sparse coding. Three structural models are employed to investigate efficiency of the procedures which consists of a range of numerical MDOF model with limited degree of freedom to real structures. In the second stage, a damage index is proposed based on the width of multifractal spectrum. Results show that the aforementioned method is able to identify various damage patterns and can detect slight damages.