Some results on change detection based on advanced signal processing paradigm

Anisia Culea-Florescu, D. Aiordachioaie
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Abstract

This work considers the problem of change detection of working regimes from industrial processes, e.g. electric machines with rotation elements, and which generates mechanical vibrations. Two approaches are considered: (i) based on signal processing and pattern recognition methods; (ii) based on sparse methods. The objective of the paper is to evaluate the preliminary results obtained by the above approaches and to promote methods based on sparse representations and computations for change detection problems, as alternative to classical methods based on transform or pattern recognition. The results are encouraging and suggest that more studies on the method of sparse computation as an optimal candidate for change detection from time detection point of view is needed.
基于先进信号处理范式的变化检测
这项工作考虑了工业过程中工作状态的变化检测问题,例如,具有旋转元件的电机,并产生机械振动。考虑了两种方法:(i)基于信号处理和模式识别方法;(ii)基于稀疏方法。本文的目的是评估上述方法获得的初步结果,并推广基于稀疏表示和计算的方法来解决变化检测问题,作为基于变换或模式识别的经典方法的替代方法。结果令人鼓舞,并表明从时间检测的角度对稀疏计算作为变化检测的最佳候选方法进行更多的研究是必要的。
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