Dynamic Bayesian Network for Aircraft Wing Health Monitoring Digital Twin

By Chenzhao Li, Sankaran Mahadevan, Y. Ling, Sergio Choze, Liping Wang. 2017

308 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/391ea7ef17e33b432d5b38b59a0529375b9d92ea

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

In Control and Systems Engineering

Citations in the corpus

A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies (2022, methodology): “Five out of the 12 topcited papers concentrate on fault diagnostics and prognostics of physical assets using digital twin (Xu et al., 2019; Li et al., 2017; Glaessgen and Stargel, 2012; Jain et al., 2019; Tuegel et al., 2011).”
A probabilistic graphical model foundation for enabling predictive digital twins at scale (2020, background): “Structural digital twins have shown promise in 56 virtual health monitoring, certification, and predictive main- 57 tenance [2, 3, 4, 5].”
A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications (2019, background): “In [81] authors discussed a DT exploiting a modiﬁed dynamic Bayesian network structure to con-trol the state of aircraft wings.”
An application framework of digital twin and its case study (2018, methodology): “Li et al. (2017) use the concept of a dynamic Bayesian network to build a versatile probabilistic model for diagnosis and prognosis in order to realize the DT vision to fulfill airframe health monitoring.”
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective (2019, methodology): “We refer to recent studies on the use of the Kalman filter [199] and particle filter [200] in the digital twin applications.”
Characterising the Digital Twin: A systematic literature review (2020, background): “The vast majority of these processes can be covered by the activities of simulation, modelling, and optimisation [2] [3] [4] [5] [7] [9] [12] [15] [17] [16] [20] [21] [27] [30] [33] [36] [35] [40] [48] [49] [52] [54] [55] [10] [56] [58] [61] [64] [70] [71] [73] [75] [74] [85] [87] [89] [92] [94] [95”
Digital Twin in Industry: State-of-the-Art (2019, methodology): “The DT model led to more accurate diagnosis and prognosis based on a case study of the leading edge of aircraft wings [45].”