Regularization strategies have attracted attention in the structural damage detection (SDD) field. However, there is lack of studies on regularization strategies for damage patterns in the existing methods. This paper proposes regularization strategies for contiguous and noncontiguous damages of structures and performs comparative studies. The objective functions are first defined to consider effects of strategies on SDD by adding distinct norm penalties, and then are solved by the particle swarm optimization (PSO). Three numerical simulation models are employed to assess the applicability of three strategies. The results show that the l2 norm regularization is suitable for detecting multiple damages, the l1 norm regularization performs well in contiguous damages, and the sparsest solutions can be obtained by the l1/2 norm regularization.

中文翻译：

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结构连续和非连续损伤检测的正则化策略

正则化策略在结构损伤检测（SDD）领域引起了人们的关注。然而，现有方法中缺乏对损伤模式正则化策略的研究。本文提出了结构连续和非连续损伤的正则化策略，并进行了比较研究。首先定义目标函数以通过添加不同的范数惩罚来考虑策略对 SDD 的影响，然后通过粒子群优化 (PSO) 求解。采用三个数值模拟模型来评估三种策略的适用性。结果表明，l2范数正则化适用于检测多重损伤，l1范数正则化在连续损伤中表现良好，并且可以通过l1/2规范正则化。