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Multiaxial sensor placement optimization in structural health monitoring using distributed wolf algorithm

机译：基于分布式Wolf算法的结构健康监测中的多轴传感器布置优化

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摘要

Optimal sensor placement technique plays a key role in the design of an effective structural health monitoring system. Recent advances in sensing technologies have also promoted using multiaxial sensors to perform efficiently and economically monitoring for civil engineering structures. However, the available evaluation criteria for the optimal sensor placement can only guarantee that the optimization is conducted in a single structural direction but not in multi-dimension space, which may result in the non-optimal placement of multiaxial sensors. To tackle this issue thoroughly, a new multiaxial optimal criterion termed as the triaxial modal assurance criterion is developed by taking account into three translational degrees of freedom as a single unit in the Fisher information matrix. Afterwards, a novel distributed wolf algorithm is proposed to improve the optimization performance in identifying the best sensor locations. The dual-structure coding method is improved and adopted to represent the solution. The shuffling strategy is proposed to enhance the searching capability and convergence performance. The attacking process is also modified to prevent the algorithm from being trapped in a local minimum. The effectiveness of the proposed scheme is investigated by the benchmark structure developed by the University of Central Florida, USA. The results clearly demonstrate that the proposed distributed wolf algorithm outperforms the existing algorithm in its global optimization capability. Copyright © 2015 John Wiley & Sons, Ltd.
机译：最佳的传感器放置技术在有效的结构健康监测系统的设计中起着关键作用。传感技术的最新进展也促进了使用多轴传感器来对土木工程结构进行有效且经济的监控。但是，用于最佳传感器放置的可用评估标准只能保证优化是在单个结构方向上进行的，而不能在多维空间中进行，这可能会导致多轴传感器的放置不是最佳。为了彻底解决该问题，通过在Fisher信息矩阵中将三个平移自由度作为一个单元考虑在内，开发了一种称为三轴模态保证准则的新多轴最优准则。此后，提出了一种新颖的分布式狼算法，以提高识别最佳传感器位置时的优化性能。对双结构编码方法进行了改进，并采用它来表示解决方案。提出了改组策略，以提高搜索能力和收敛性能。还修改了攻击过程，以防止算法陷入局部最小值。美国中央佛罗里达大学开发的基准结构研究了该计划的有效性。结果清楚地表明，所提出的分布式狼算法在全局优化能力方面优于现有算法。版权所有©2015 John Wiley＆Sons，Ltd.

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