Optimization of sensor placement for structural health monitoring: a review

Abstract

The deployment cost of the structural health monitoring (SHM) system is the major argument against the more widespread use of the structural health monitoring techniques. Optimization of sensor placement offers an opportunity to reduce the cost of the SHM system without compromising on the quality of the monitoring approach. Several studies in the area of optimization of sensor placement for SHM applications have been undertaken but the approach has been rather application specific. This article is an attempt to present an unbiased state of the art of the work carried out in the area. The article is targeted towards researchers working in the field of structural health monitoring and optimization of sensor placement as well as practising engineers. This article reviews the work in the area of optimization of sensor placement. It first presents the definition of the optimization problem and then describes each step of the optimization. The current state of the art is then classified based on the techniques for which the optimization of sensor placement has been optimized. The article covers vibration-based monitoring, strain monitoring and elastic wave-based monitoring, as in the eyes of the authors these three techniques are most commonly used and accepted in the SHM community. The article later discusses the different optimization algorithms that have been applied in the literature. The article highlights the different pitfalls of the optimization algorithms and the countermeasures different researchers have proposed to overcome the known shortcomings. In the later section, the multi-objective optimization or the problem definition, keeping in mind the structural as well as executional demands, is discussed. A section has also been developed to showcase the use of optimization of sensor placement techniques’ data fusion–based systems.

Layout Optimization of Multi-Type Sensors and Human Inspection Tools With Probabilistic Detection of Localized Damages for Pipelines

“…(iii) Only a handful of previous works on optimal sensor placement have considered cost-effectiveness while maximizing probabilistic detection of damages [10], [23]. Additionally, simplifying assumptions, such as having a fixed number of the same-type sensors and a one-dimensional sensor network, are used in the corresponding literature to minimize the computational cost of multi-type sensor optimization models [5], [6], [9], [17], [24], [25]. Moreover, the literature on human inspection is more focused on optimizing inspection time rather than deciding on inspection location and tool type [4], [7], [23].…”

A Real-Valued Genetic Algorithm for Optimization of Sensor Placement for Guided Wave-Based Structural Health Monitoring

“…The research in the area of GW in metallic structures is quite extensive, but the work in the area of sensor placement is quite limited. Ostachowicz et al [5] present an excellent review of the techniques used in the optimization of sensor placement with a special section dedicated to the optimization of sensor placement for GW-based SHM. The literature can be divided into primarily 3 areas.…”

Placement of distributed crack sensor on I‐shaped steel girders of medium‐span bridges, using available field data

“…There have been many studies on the optimum placement of sensors on bridges for structural health monitoring. Ostachowicz et al have done a comprehensive review on sensor placement for three types of SHM: vibration monitoring, strain monitoring, and wave propagation–based monitoring . Kaveh et al have used a two‐stage optimization to place sensors for modal identification of the structure .…”

“…Ostachowicz et al have done a comprehensive review on sensor placement for three types of SHM: vibration monitoring, strain monitoring, and wave propagation-based monitoring. 27 Kaveh et al have used a two-stage optimization to place sensors for modal identification of the structure. 28 Argyris et al presented a Bayesian platform for crack identification on plates using strain measurements.…”