Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost

Mehrjoo, Azin; Song, Mingming; Moaveni, Babak; Papadimitriou, Costas; Hines, Eric M.

doi:10.1016/j.ymssp.2021.108787

Cited by 25 publications

(15 citation statements)

References 42 publications

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“…Based on the results in Figure 3b, it is reasonable to use 9 sensors placed at their optimal positions since the information gained is 91% of U all max and the increase in information gain by adding a sensor at a time is relatively small. Such information gain should be weighted with the cost of the information [67] so that a cost-effective and highly informative sensor configuration is obtained.…”

Section: Information Gain Versus Number Of Sensorsmentioning

confidence: 99%

“…In these methods a measure of the information gained from the sensor data, such as mutual information, relative entropy and Kullback-Leibler divergence (KLdiv) computed from a Bayesian formulation is optimized with respect to the sensor locations. OSP techniques based on information-theoretic methods for virtual sensing has also proposed based on either modal expansion technique [65][66][67] or filtering techniques [68,69].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Information theoretic-based optimal sensor placement for virtual sensing using augmented Kalman filtering

Tulay

Sedehi

Katafygiotis

et al. 2023

Mechanical Systems and Signal Processing

Self Cite

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Section: Information Gain Versus Number Of Sensorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Information theoretic-based optimal sensor placement for virtual sensing using augmented Kalman filtering

Tulay

Sedehi

Katafygiotis

et al. 2023

Mechanical Systems and Signal Processing

Self Cite

View full text Add to dashboard Cite

“…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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“…The cost composition of the offshore wind farms includes the super structure, financial expenditure, foundation, power drive and construction costs, as shown in Figure 1 (Data source 4 ). Although the offshore jacket structures accounts for only about 5% of the total cost of the wind farms, they play a vital role for the normal operation of the wind turbines because the health condition of the jacket structures directly determines the service life of the wind turbines.…”

Section: Introductionmentioning

confidence: 99%

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Leng

Gardoni

Wang

et al. 2023

Structural Health Monitoring

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Structural health monitoring (SHM) has been recognized as a useful tool for safety management and risk reduction of offshore wind farms. In complex offshore environment, jacket structures of offshore wind turbines are prone to damages due to corrosion and fatigue. Effective SHM on jacket structures can substantially reduce their operation risk and costs. This work reviews the latest progress on the SHM of offshore wind jacket structures. The achievements in the structural damage identification, location, quantification, and remaining useful life (RUL) estimation are respectively introduced in detail, and existing challenges are discussed. Possible solutions to the challenges using the Digital Twin (DT) technology are put forward. The DT is able to mirror a real jacket structure into a virtual model, and Bayesian updating can refresh the virtual model parameters in real-time to keep consistency between virtual model and physical structure; then, just-in-time SHM can be carried out for jacket structures by performing damage detection, location, quantification, and RUL estimation using the virtual model. As a result, the DT may provide engineers and researchers a practicable tool for safety monitoring and risk reduction of fixed foundation offshore wind structures.

show abstract

Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost

Cited by 25 publications

References 42 publications

Information theoretic-based optimal sensor placement for virtual sensing using augmented Kalman filtering

Information theoretic-based optimal sensor placement for virtual sensing using augmented Kalman filtering

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

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

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