Towards Risk-Informed PBSHM: Populations as Hierarchical Systems

Author:

Hughes A. J.,Gardner P.,Worden K.

Publisher

Springer Nature Switzerland

Reference21 articles.

1. Farrar, C.R., Worden, K.: Structural Health Monitoring: A Machine Learning Perspective. Wiley, Hoboken (2013)

2. Rytter, A.: Vibration Based Inspection of Civil Engineering Structures. Ph.D. Thesis, Aalborg University (1993)

3. Schöbi, R., Chatzi, E.N.: Maintenance planning using continuous-state partially observable Markov decision processes and non-linear action models processes and non-linear action models. Struct. Infrastruct. Eng. 12(8), 977–994 (2016)

4. Vega, M.A., Todd, M.D.: A variational Bayesian neural network for structural health monitoring and cost-informed decision-making in miter gates. Struct. Health Monit. 21, 1475921720904543 (2020)

5. Hughes, A.J., Barthorpe, R.J., Dervilis, N., Farrar, C.R., Worden, K.: A probabilistic risk-based decision framework for structural health monitoring. Mech. Syst. Signal Process. 150, 107339 (2021)

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