Efficient reliability assessment method for bridges based on Markov Chain Monte Carlo (MCMC) with Metropolis-Hasting Algorithm (MHA). Issue 1 (October 2020)

• Record Type: Journal Article
• Authors: Zhang, Liye; Dong, Lijuan; Cheng, Shoushan; Li, Wanheng; Wang, Bingjian; Liu, Hanyong; Chen, Ke
• Is Part Of: IOP conference series. Volume 580:Issue 1(2020)
• Publication Date: 2020-10
• Subjects: Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/580/1/012030
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: Reliability assessment plays a vital roles in bridge health monitoring (BHM) technique. The analysis results of inspection data and monitoring data, such as numerical data, image data and video data, are not well due to there is no efficient reliability assessment method. This paper analysed the applied effect of Markov Chain Monte Carlo (MCMC) simulation method. The subset simulation method is used to analyse small failure probability events. Furthermore, the reliability assessment process based on Markov Chain Monte Carlo (MCMC) simulation method with Metropolis-Hasting Algorithm (MHA) is proposed. The advantage of this method is to improve the application efficiency and accuracy of reliability assessment based on BHM data.