Suslu Burak, Ali Fakhre, Jennions Ian K
Integrated Vehicle Health Management Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Bedfordshire MK43 0AL, UK.
Sensors (Basel). 2023 Sep 12;23(18):7819. doi: 10.3390/s23187819.
Complex systems involve monitoring, assessing, and predicting the health of various systems within an integrated vehicle health management (IVHM) system or a larger system. Health management applications rely on sensors that generate useful information about the health condition of the assets; thus, optimising the sensor network quality while considering specific constraints is the first step in assessing the condition of assets. The optimisation problem in sensor networks involves considering trade-offs between different performance metrics. This review paper provides a comprehensive guideline for practitioners in the field of sensor optimisation for complex systems. It introduces versatile multi-perspective cost functions for different aspects of sensor optimisation, including selection, placement, data processing and operation. A taxonomy and concept map of the field are defined as valuable navigation tools in this vast field. Optimisation techniques and quantification approaches of the cost functions are discussed, emphasising their adaptability to tailor to specific application requirements. As a pioneering contribution, all the relevant literature is gathered and classified here to further improve the understanding of optimal sensor networks from an information-gain perspective.
复杂系统涉及在集成车辆健康管理（IVHM）系统或更大的系统中监测、评估和预测各种系统的健康状况。健康管理应用依赖于能够生成有关资产健康状况有用信息的传感器；因此，在考虑特定约束的同时优化传感器网络质量是评估资产状况的第一步。传感器网络中的优化问题涉及在不同性能指标之间进行权衡。这篇综述论文为复杂系统传感器优化领域的从业者提供了全面的指导方针。它针对传感器优化的不同方面，包括选择、布置、数据处理和运行，引入了通用的多视角成本函数。该领域的分类法和概念图被定义为这个广阔领域中有价值的导航工具。讨论了成本函数的优化技术和量化方法，强调了它们适应特定应用需求的能力。作为一项开创性贡献，这里收集并分类了所有相关文献，以从信息增益的角度进一步加深对最优传感器网络的理解。
