Damage identification of offshore jacket platforms in a digital twin framework considering optimal sensor placement

Wang, Mengmeng; Incecik, Atilla; Feng, Shizhe; Gupta, Munish Kumar; Królczyk, Grzegorz; Li, Zhixiong

doi:10.1016/j.ress.2023.109336

Cited by 11 publications

(3 citation statements)

References 53 publications

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“…Wang et al [190] proposed an offshore platform sensor position fractional order optimization method and applied the effective independence method to experimentally study the fractional order placement of the sensors and validated the method with an offshore platform in Jinzhou as an example. A digital twin framework with OSP to accurately calculate the modal response and identify the damage rate of an offshore jacket platform was proposed by Wang et al [191]. The OSP model was validated using a multi-objective Lichtenberg's algorithm for sensor number/location optimization, and the proposed method was validated using an offshore jacket platform.…”

Section: Othersmentioning

confidence: 99%

“…Civera et al [204] used the dual objective function of AutoMAC and CrossMAC with the NSGA-II algorithm to investigate Fossano's church. Wang et al [191] proposed a new digital twin (DT) framework based on optimal sensor placement for accurately calculating the modal response and identifying the damage rate of an offshore conduit rack platform. Its OSP model adopts the multi-objective Lichtenberg algorithm (MOLA) for optimizing the number and placement of sensors, which achieves a good balance between the cost of sensors and the accuracy of modal computation.…”

Section: Optimal Sensor Placement Under Multiple Objectivesmentioning

confidence: 99%

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Advancements in Optimal Sensor Placement for Enhanced Structural Health Monitoring: Current Insights and Future Prospects

Wang,

Chen,

Yao

et al. 2023

Buildings

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Structural health monitoring (SHM) is critical to maintaining safe and reliable civil infrastructure, but the optimal design of an SHM sensing system, i.e., optimal sensor placement (OSP), remains a complex challenge. Based on the existing literature, this paper presents a comprehensive review of OSP strategies for SHM. It covers the key steps in OSP, from evaluation criteria to efficient optimization algorithms. The evaluation criteria are classified into six groups, while the optimization algorithms are roughly categorized into three classes. The advantages and disadvantages of each group of methods have been summarized, aiming to benefit the OSP strategy selection in future projects. Then, the real-world implementation of OSP on bridges, high-rise buildings, and other engineering structures, is presented. Based on the current progress, the challenges of OSP are recognized; its future development directions are recommended. This study equips researchers/practitioners with an integrated perspective on state-of-the-art OSP. By highlighting key developments, persistent challenges, and prospects, it is expected to bridge the gap between theory and practice.

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Section: Othersmentioning

confidence: 99%

Section: Optimal Sensor Placement Under Multiple Objectivesmentioning

confidence: 99%

Advancements in Optimal Sensor Placement for Enhanced Structural Health Monitoring: Current Insights and Future Prospects

Wang,

Chen,

Yao

et al. 2023

Buildings

View full text Add to dashboard Cite

show abstract

“…The OSP problem has garnered attention across various fields for an extended period, as rapid data sampling, analysis, and decision-making for complex systems can be archived with limited measurements. There are tremendous OSP methods developed for structural health monitoring systems [19][20][21], intelligent manufacturing systems [22], fluid control systems [23,24], wireless sensor networks [25], building monitoring systems [26], pipeline systems [27], hydraulic control systems [28], environmental monitoring systems, thermal systems [29], Internet of Things (IoT) systems [30], condition monitoring systems [31,32], etc., and most of these methods are based on high-dimensional data decomposition methods or heuristic optimization algorithms. The data-driven decomposition methods have elegant mathematical expressions, but they are mostly applicable to component-level OSP problems.…”

Section: Introductionmentioning

confidence: 99%

A Novel Optimal Sensor Placement Method for Optimizing the Diagnosability of Liquid Rocket Engine

Ma,

Zhong,

Zhai

et al. 2024

Aerospace

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There are hundreds of various sensors used for online Prognosis and Health Management (PHM) of LREs. Inspired by the fact that a limited number of key sensors are selected for inflight control purposes in LRE, it is practical to optimal placement of redundant sensors for improving the diagnosability and economics of PHM systems. To strike a balance between sensor cost, real-time performance and diagnosability of the fault diagnosis algorithm in LRE, this paper proposes a novel Optimal Sensor Placement (OSP) method. Firstly, a Kernel Extreme Learning Machine-based (KELM) two-stage diagnosis algorithm is developed based on a system-level failure simulation model of LRE. Secondly, hierarchical diagnosability metrics are constructed to formulate the OSP problem in this paper. Thirdly, a Hierarchy Ranking Evolutionary Algorithm-based (HREA) two-stage OSP method is developed, achieving further optimization of Pareto solutions by the improved hypervolume indicator. Finally, the proposed method is validated using failure simulation datasets and hot-fire test-run experiment datasets. Additionally, four classical binary multi-objective optimization algorithms are introduced for comparison. The testing results demonstrate that the HREA-based OSP method outperforms other classical methods in effectively balancing the sensor cost, real-time performance and diagnosability of the diagnosis algorithm. The proposed method in this paper implements system-level OSP for LRE fault diagnosis and exhibits the potential for application in the development of reusable LREs.

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Enhanced Lichtenberg algorithm: a discussion on improving meta-heuristics

et al. 2023

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Damage identification of offshore jacket platforms in a digital twin framework considering optimal sensor placement

Cited by 11 publications

References 53 publications

Advancements in Optimal Sensor Placement for Enhanced Structural Health Monitoring: Current Insights and Future Prospects

Advancements in Optimal Sensor Placement for Enhanced Structural Health Monitoring: Current Insights and Future Prospects

A Novel Optimal Sensor Placement Method for Optimizing the Diagnosability of Liquid Rocket Engine

Enhanced Lichtenberg algorithm: a discussion on improving meta-heuristics

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