A Markovian-Bayesian Network for Risk Analysis of High Speed and Conventional Railway Lines Integrating Human Errors

2015 ◽  
Vol 31 (3) ◽  
pp. 193-218 ◽  
Author(s):  
Enrique Castillo ◽  
Aida Calviño ◽  
Zacarías Grande ◽  
Santos Sánchez-Cambronero ◽  
Inmaculada Gallego ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
High Speed ◽  
Human Errors

scholarly journals Probabilistic Safety Analysis of High Speed and Conventional Lines Using Bayesian Networks

2016 ◽  
Author(s):  
Zacarias Grande Andrade ◽  
Enrique Castillo Ron ◽  
Alan O'Connor ◽  
Maria Nogal
Keyword(s):  
Bayesian Network ◽  
High Speed ◽  
Human Error ◽  
Driver Behavior ◽  
Safety Evaluation ◽  
Safety Analysis ◽  
Human Errors ◽  
Maintenance Costs ◽  
Railway Line ◽  
Probabilistic Safety

A Bayesian network approach is presented for probabilistic safety analysis (PSA) of railway lines. The idea consists of identifying and reproducing all the elements that the train encounters when circulating along a railway line, such as light and speed limit signals, tunnel or viaduct entries or exits, cuttings and embankments, acoustic sounds received in the cabin, curves, switches, etc. In addition, since the human error is very relevant for safety evaluation, the automatic train protection (ATP) systems and the driver behavior and its time evolution are modelled and taken into account to determine the probabilities of human errors. The nodes of the Bayesian network, their links and the associated probability tables are automatically constructed based on the line data that need to be carefully given. The conditional probability tables are reproduced by closed formulas, which facilitate the modelling and the sensitivity analysis. A sorted list of the most dangerous elements in the line is obtained, which permits making decisions about the line safety and programming maintenance operations in order to optimize them and reduce the maintenance costs substantially. The proposed methodology is illustrated by its application to several cases that include real lines such as the Palencia-Santander and the Dublin-Belfast lines.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3428

An Offshore Risk Analysis Method Using Fuzzy Bayesian Network

2009 ◽  
Vol 131 (4) ◽  
Author(s):  
J. Ren ◽  
I. Jenkinson ◽  
J. Wang ◽  
D. L. Xu ◽  
J. B. Yang
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Dynamic Environment ◽  
Engineering System ◽  
Human Errors ◽  
Expert Opinions ◽  
Offshore Engineering ◽  
Proposed Model ◽  
High Level ◽  
System Variables

The operation of an offshore installation is associated with a high level of uncertainty because it usually operates in a dynamic environment in which technical and human and organizational malfunctions may cause possible accidents. This paper proposes a fuzzy Bayesian network (FBN) approach to model causal relationships among risk factors, which may cause possible accidents in offshore operations. The FBN model explicitly represents cause-and-effect assumptions between offshore engineering system variables that may be obscured under other modeling approaches like fuzzy reasoning and Monte Carlo risk analysis. The flexibility of the method allows for multiple forms of information to be used to quantify model relationships, including formally assessed expert opinions when quantitative data are lacking in early design stages with a high level of innovation or when only qualitative or vague statements can be made. The model is also a modular representation of uncertain knowledge due to randomness and vagueness. This makes the risk and safety analysis of offshore engineering systems more functional and easier in many assessment contexts. A case study of the collision risk between a floating production, storage and offloading unit and the authorized vessels due to human errors during operation is used to illustrate the application of the proposed model.

A Bayesian-Network-based Approach to Risk Analysis in Runway Excursions

2019 ◽  
Vol 72 (5) ◽  
pp. 1121-1139 ◽  
Author(s):  
Fernando Calle-Alonso ◽  
Carlos J. Pérez ◽  
Eduardo S. Ayra
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Exploratory Analysis ◽  
Hypothesis Tests ◽  
Aircraft Accidents ◽  
Risk Scenarios ◽  
Key Variables ◽  
Expert Recommendations

Aircraft accidents are extremely rare in the aviation sector. However, their consequences can be very dramatic. One of the most important problems is runway excursions, when an aircraft exceeds the end (overrun) or the side (veer-off) of the runway. After performing exploratory analysis and hypothesis tests, a Bayesian-network-based approach was considered to provide information from risk scenarios involving landing procedures. The method was applied to a real database containing key variables related to landing operations on three runways. The objective was to analyse the effects over runway overrun excursions of failing to fulfil expert recommendations upon landing. For this purpose, the most influential variables were analysed statistically, and several scenarios were built, leading to a runway ranking based on the risk assessed.

Fuzzy-support vector machine geotechnical risk analysis method based on Bayesian network

2019 ◽  
Vol 16 (8) ◽  
pp. 1975-1985 ◽  
Author(s):  
Yang Liu ◽  
Jian-jing Zhang ◽  
Chong-hao Zhu ◽  
Bo Xiang ◽  
Dong Wang
Keyword(s):  
Support Vector Machine ◽  
Risk Analysis ◽  
Bayesian Network ◽  
Support Vector ◽  
Analysis Method ◽  
Fuzzy Support Vector Machine ◽  
Geotechnical Risk

Operation-oriented reliability and availability evaluation for onboard high-speed train control system with dynamic Bayesian network

2018 ◽  
Vol 233 (3) ◽  
pp. 455-469 ◽  
Author(s):  
Lei Jiang ◽  
Yiliu Liu ◽  
Xiaomin Wang ◽  
Mary Ann Lundteigen
Keyword(s):  
Control System ◽  
Bayesian Network ◽  
High Speed ◽  
Dynamic Bayesian Network ◽  
Dynamic Bayesian Networks ◽  
High Speed Train ◽  
Train Control ◽  
Train Control System ◽  
Onboard System ◽  
Reliability And Availability

The reliability and availability of the onboard high-speed train control system are important to guarantee operational efficiency and railway safety. Failures occurring in the onboard system may result in serious accidents. In the analysis of the effects of failure, it is significant to consider the operation of an onboard system. This article presents a systemic approach to evaluate the reliability and availability for the onboard system based on dynamic Bayesian network, with taking into account dynamic failure behaviors, imperfect coverage factors, and temporal effects in the operational phase. The case studies are presented and compared for onboard systems with different redundant strategies, that is, the triple modular redundancy, hot spare double dual, and cold spare double dual. Dynamic fault trees of the three kinds of onboard system are constructed and mapped into dynamic Bayesian networks. The forward and backward inferences are conducted not only to evaluate the reliability and availability but also to recognize the vulnerabilities of the onboard systems. A sensitivity analysis is carried out for evaluating the effects of failure rates subject to uncertainties. To improve the reliability and availability, the recovery mechanism should be paid more attention. Finally, the proposed approach is validated with the field data from one railway bureau in China and some industrial impacts are provided.

scholarly journals Identification of RBC and WBC Count in Human Blood Using ARM Based Instrumentation

2015 ◽  
Vol 11 (1) ◽  
pp. 145-150
Author(s):  
B. Basavanagoud ◽  
K. Priya
Keyword(s):  
Conventional Method ◽  
High Speed ◽  
Low Cost ◽  
Blood Analysis ◽  
Medical Sciences ◽  
Accurate Analysis ◽  
Human Errors ◽  
Arm Processor ◽  
Wbc Count ◽  
Human Fluids

The rapid growth in microelectronics and crunching RISC in the field of bio-medical sciences incorporated of soft tools to diagnose various parameters of human fluids. Conventional method of blood sample analysis makes use of laboratory technique of titration, which is operator-dependent and results in lot of errors depending on the skill of the technician. In order to eliminate the human errors involved in the conventional method, in this paper an attempt has been made to present a capillary centrifuge technique driven by high speed DC motor fed by Morgan chopper and controlled by powerful ARM processor. It results in accurate analysis of the blood samples. The various techniques involved in accurate sensing of speed using timer and generation of firing pulses to thyristor in the Morgan chopper is judiciously achieved. This paper clearly brings out the advantages of the proposed blood measurement technique which effectively gives blood analysis faster and at a low cost.

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