Reliability and Safety Modelling of the Electrical Control System of the Subsea Control Module Based on Markov and Multiple Beta Factor Model

Wang, Xiangyu; Jia, Peng; Lizhang, Hanyi; Wang, Liquan; Yun, Feihong; Wang, Honghai

doi:10.1109/access.2018.2889104

Cited by 13 publications

(7 citation statements)

References 35 publications

(45 reference statements)

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“…In most reliability studies, the failure rate of each equipment is usually simplified to a constant value due to the lack of basic data such as failure records of partial equipment. Wang et al [8] established a reliability model for the electrical control system of the subsea control module by markov processes and multiple beta factor model using the constant failure rate (CFR) and its value range. When assessing the reliability and safety of subsea Christmas tree, Pang et al [9] converted the failure rate of hydraulic and electronic components which obey an exponential distribution and mechanical components with Weibull distribution into a constant.…”

Section: Introductionmentioning

confidence: 99%

Reliability Study of Parameter Uncertainty Based on Time-Varying Failure Rates with an Application to Subsea Oil and Gas Production Emergency Shutdown Systems

Zuo

Yin

et al. 2021

Processes

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The failure rate of equipment during long-term operation in severe environment is time-varying. Most studies regard the failure rate as a constant, ignoring the reliability evaluation error caused by the constant. While studying failure data that are few and easily missing, it is common to focus only on the uncertainty of reliability index rather than parameter of failure rate. In this study, a new time-varying failure rate model containing time-varying scale factor is established, and a statistical-fuzzy model of failure rate cumulated parameter is established by using statistical and fuzzy knowledge, which is used to modify the time-varying failure rate model. Subsequently, the theorem of the upper boundary existence for the failure rate region is proposed and proved to provide the failure rate cumulated parameter when the failure rate changes the fastest. The proposed model and theorem are applied to analyze the reliability of subsea emergency shutdown system in the marine environment for a long time. The comparison of system reliability under time-varying failure rate and constant failure rate shows that the time-varying failure rate model can eliminate the evaluation error and is consistent with engineering. The reliability intervals based on the failure rate model before and after modification are compared to analyze differences in uncertainty, which confirm that the modified model is more accurate and more practical for engineering.

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Section: Introductionmentioning

confidence: 99%

Reliability Study of Parameter Uncertainty Based on Time-Varying Failure Rates with an Application to Subsea Oil and Gas Production Emergency Shutdown Systems

Zuo

Yin

et al. 2021

Processes

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“…Safety is described as being secure against the unacceptable risk of any direct or indirect physical injury or damage to the health of people, ensued of the damaged equipment or environmental issues 16 . Safety standards determine the magnitude of safety enhancement related to a Safety Instrumented Function (SIF) based on the Safety Integrity Levels (SIL) 17 .…”

Section: Introductionmentioning

confidence: 99%

“…Also, their failure rate prediction model was based on Bayesian Networks. Wang et al 16 studied the reliability and safety of electrical parts included in SCM using Markov processes and multiple beta factor models. They utilized Matlab software to simulate the gradual decrease in system reliability and safety.…”

Section: Introductionmentioning

confidence: 99%

SIL analysis of subsea control system components based on a typical OREDA database

Mahmoudi

2021

Quality & Reliability Eng

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Proper performance evaluation of subsea system components is of high significance for reliable operation and remote monitoring or the replacement of the components before the occurrence of any failure. As a part of subsea systems, subsea control system (SCS) plays a key role in accomplishing a reliable performance. Hence, achieving knowledge of the components' failure rates is highly important in the safety analysis of SCS. To the author's knowledge, limited work is done on the safety analysis of SCS using failure rates for a multitude of components. Also, the number of research papers that are based on industrial works is restricted. Hence, this paper aims to provide a noticeable contribution in fulfilling the referred gap. For this purpose, a safety integrity-level (SIL) analysis is proposed based on a typical OREDA database. In the implementation of the proposed SIL, a failure mode classification table is provided for a selection of SCS components. This is followed by the estimation of several parameters, such as the total time in service, as well as obtaining the values of critical failure rates.The analysis indicates that signal failure is the failure mode occurring more than the other ones. Also, the subsea electronic module yields the highest value of critical failure rates. Besides, a comparison of parameter values is provided for two different versions of the utilized database.

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“…Liu [16] presented a Markov method to analyze the reliability of the electrical control system of a subsea blowout preventer stack. Wang used Markov processes to model the reliability for the electrical control system of the subsea control module [17] and enhanced the reliability within the given space [18]. Fuzzy theory and Markov technology have been increasingly used in reliability and risk analysis studies.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Markov Model for Risk and Reliability Prediction of Engineering Systems: A Case Study of a Subsea Wellhead Connector

et al. 2020

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In production environments, failure data of a complex system are difficult to obtain due to the high cost of experiments; furthermore, using a single model to analyze risk, reliability, availability and uncertainty is a big challenge. Based on the fault tree, fuzzy comprehensive evaluation and Markov method, this paper proposed a fuzzy Markov method that takes the full advantages of the three methods and makes the analysis of risk, reliability, availability and uncertainty all in one. This method uses the fault tree and fuzzy theory to preprocess the input failure data to improve the reliability of the input failure data, and then input the preprocessed failure data into the Markov model; after that iterate and adjust the model when uncertainty events occur, until the data of all events have been processed by the model and the updated model obtained, which best reflects the system state. The wellhead connector of a subsea production system was used as a case study to demonstrate the above method. The obtained reliability index (mean time to failure) of the connector is basically consistent with the failure statistical data from the offshore and onshore reliability database, which verified the accuracy of the proposed method.

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Reliability and Safety Modelling of the Electrical Control System of the Subsea Control Module Based on Markov and Multiple Beta Factor Model

Cited by 13 publications

References 35 publications

Reliability Study of Parameter Uncertainty Based on Time-Varying Failure Rates with an Application to Subsea Oil and Gas Production Emergency Shutdown Systems

Reliability Study of Parameter Uncertainty Based on Time-Varying Failure Rates with an Application to Subsea Oil and Gas Production Emergency Shutdown Systems

SIL analysis of subsea control system components based on a typical OREDA database

A Fuzzy Markov Model for Risk and Reliability Prediction of Engineering Systems: A Case Study of a Subsea Wellhead Connector

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