Urban natural gas pipeline failure multi-factor multi-mode probability analysis method and application thereof

A natural gas pipeline and probability analysis technology, applied in the field of oil and gas storage and transportation risk control, to achieve the effect of improving comprehensiveness and accelerating effectiveness

Inactive Publication Date: 2013-01-09
CHANGZHOU UNIV
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Problems solved by technology

The Bayesian analysis of the failure probability of urban gas pipelines is also limited to the two-state correction of corrosion factors and th...

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  • Urban natural gas pipeline failure multi-factor multi-mode probability analysis method and application thereof
  • Urban natural gas pipeline failure multi-factor multi-mode probability analysis method and application thereof
  • Urban natural gas pipeline failure multi-factor multi-mode probability analysis method and application thereof

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[0042] 1. Basic data

[0043] Choose a certain section of natural gas transmission pipeline from Changzhou Neiganghua Gas Company, which is located under the sidewalk at the intersection of Beitanghe Road and Qingyang Road in Wujin District. Its specification is φ720mm×8(9)mm; the pipe material is T / S -52k16Mn, X-52; design pressure 4.0MPa, current output is 700×10 4 m 3 / d.

[0044] 2. Establish a Bayesian network failure probability model

[0045] The Bayesian network failure probability model is the same figure 1 , The basic event probability data uses the data in Table 1.

[0046] 3. Calculate the probability of the top event before correction

[0047] According to the above pipeline failure Bayesian network model, the connection strength (conditional probability table) as shown in Table 2, Table 3 and Table 4 can be listed respectively. Using Hugin Expert software, the following figure 2 Calculation model, according to the data in Table 1, enter X 3 , X 4 With B 1 , X 5 , X 6 Wit...

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Abstract

The invention discloses an urban natural gas pipeline failure multi-factor multi-mode probability analysis method and application thereof. The method emphasizes at modification research for failure states due to main factors such as corrosion, design, operation management, environments and third-party damage causing pipeline failure, a Bayesian network probability calculation model for a natural gas pipeline is established, single-factor multi-mode, two-factor multi-mode and multi-factor multi-mode situations of pipeline failure are respectively and quantitatively calculated, and pipeline failure tip event probability and structural importance of basic factors are obtained. By the method, the unique reasoning capability of a Bayesian network in complicated risk treatment system analysis is made full use of, comprehensiveness, predictability and systematicness of quantitative analysis of safety failure of an urban natural gas pipeline are improved, and a certain referential meaning for risk management and failure handling of the natural gas pipeline is achieved.

Description

Technical field [0001] The invention relates to a multi-factor polymorphic probability analysis method for failure of urban natural gas pipelines and its application, and particularly relates to the quantitative calculation of the polymorphic probability of failure factors of natural gas pipelines, and belongs to the field of oil and gas storage and transportation risk control. Background technique [0002] As the scale of urban natural gas construction continues to expand and its use continues to spread, its combustion and explosion characteristics have also brought more and more potential safety hazards to the normal production and life of cities, and urban natural gas pipelines often pass through densely populated areas. Once pipeline failure occurs, leakage occurs , It is easy to cause serious public safety problems. [0003] According to statistics from the U.S. Pipeline Safety Office, from January 1986 to December 2001, there were 1,286 accidents on gas pipelines across the U...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 郝永梅赵文鑫邢志祥
Owner CHANGZHOU UNIV
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