A failure probability evaluation method for collapse of drill-and-blast tunnels based on multistate fuzzy Bayesian network

2020 ◽  
Vol 276 ◽  
pp. 105752 ◽  
Author(s):  
Guo-Hua Zhang ◽  
Wu Chen ◽  
Yu-Yong Jiao ◽  
Hao Wang ◽  
Cheng-Tang Wang
Keyword(s):  
Bayesian Network ◽  
Failure Probability ◽  
Evaluation Method ◽  
Probability Evaluation ◽  
Drill And Blast

Estimation of Failure Probability and its Applications in Reliability Data Analysis

2010 ◽  
Vol 118-120 ◽  
pp. 601-605
Author(s):  
Han Ming
Keyword(s):  
Parameter Estimation ◽  
Data Analysis ◽  
Bayesian Estimation ◽  
Failure Probability ◽  
Evaluation Method ◽  
Estimation Method ◽  
New Method ◽  
Reliability Parameter ◽  
Hierarchical Bayesian Estimation ◽  
Definition Of

Evaluation method of reliability parameter estimation needs to be improved effectively with the advance of science and technology. This paper develops a new method of parameter estimation, which is named E-Bayesian estimation method. In the case one hyper-parameter, the definition of E-Bayesian estimation of the failure probability is provided, moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation, and the property of E-Bayesian estimation of the failure probability are also provided. Finally, calculation on practical problems shows that the provided method is feasible and easy to perform.

Fault Detection and Discrimination of Rotating Machinery Using Frequency Symptom Parameter and Bayesian Network

2013 ◽  
Vol 470 ◽  
pp. 683-688
Author(s):  
Hai Yang Jiang ◽  
Hua Qing Wang ◽  
Peng Chen
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Bayesian Network ◽  
Frequency Domain ◽  
Evaluation Method ◽  
Roller Bearing ◽  
Rotating Machinery ◽  
Discrimination Index ◽  
Vibration Signals ◽  
Diagnosis Method

This paper proposes a novel fault diagnosis method for rotating machinery based on symptom parameters and Bayesian Network. Non-dimensional symptom parameters in frequency domain calculated from vibration signals are defined for reflecting the features of vibration signals. In addition, sensitive evaluation method for selecting good non-dimensional symptom parameters using the method of discrimination index is also proposed for detecting and distinguishing faults in rotating machinery. Finally, the application example of diagnosis for a roller bearing by Bayesian Network is given. Diagnosis results show the methods proposed in this paper are effective.

Failure probability analysis for emergency disconnect of deepwater drilling riser using Bayesian network

2018 ◽  
Vol 51 ◽  
pp. 42-53 ◽  
Author(s):  
Yuanjiang Chang ◽  
Guoming Chen ◽  
Xiangfei Wu ◽  
Jihua Ye ◽  
Bin Chen ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Failure Probability ◽  
Probability Analysis ◽  
Deepwater Drilling
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