CN108920421A - A kind of spot corrosion acts on the random failure probability evaluation method of failure of lower oil-gas pipeline system - Google Patents
A kind of spot corrosion acts on the random failure probability evaluation method of failure of lower oil-gas pipeline system Download PDFInfo
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Abstract
The invention discloses the random failure probability evaluation method of failure that a kind of spot corrosion acts on lower oil-gas pipeline system, include the following steps:1) in moment t, the corrosion depth and corrosion length of hot spot are measured;2) residual intensity of oil-gas pipeline corrosion point in moment t is calculated;3) oil-gas pipeline corrosion point random residual intensity is calculated;4) mean function and auto-covariance function of oil-gas pipeline corrosion point random residual intensity Z (t) are calculated;5) according to step 4) calculate random residual intensity Z andCross covariance function;6) based on the failure probability for passing through probability theory for the first time and calculating oil-gas pipeline system in Analysis of structural reliability;7) the random failure probability of the single hot spot of t moment is calculated;8) the random failure probability P of the oil-gas pipeline system under moment t time point corrosiveness is calculatedf,s(t), this method is capable of the random failure probability of the lower oil-gas pipeline system of accurate evaluation spot corrosion effect.
Description
Technical field
The invention belongs to oil-gas pipeline conveying technology field, it is related to a kind of spot corrosion and acts on the random of lower oil-gas pipeline system
Probability Evaluation method.
Background technique
After reform and opening-up, Chinese Petroliferous pipeline enterprise also enters the stage of reform and development, not only introduces a large amount of external oil
Feed channel correlation advanced technology, and positive ground learning overseas advanced management experience, so that oil-gas pipeline construction in China's is whole
Body level significantly improves.Typical example is exactly West-East National Gas Transmission Project, is always about 4000 kilometers, be China's independence designed, designed and
The natural gas pipeline projects of first world-class level of construction.So far, China has formd the base passed through from east to west, stretched from the north to the south
This piping network conveys to ensureing that oil gas field is stablized, meets industrial production and people's lives to the needs of the oil gas energy, it is ensured that society
Economic lasting, the stable, balanced development of meeting, there is very important meaning.
In Land petroleum pipe conveying procedure, locating geological disaster type is more, environmental aspect is complicated, with runing time
Growth, corrosion default will lead to tube wall finally unbearable operating pressure and cause pipeline failure, therefore carry out Land petroleum
The corrosion failure of pipeline is studied, to the predictive ability for improving pipeline failure accident, it is ensured that pipe safety operation, stable supply have
Significance.Corrosion is to cause oil-gas pipeline failure most common to be also most important factor, under extraneous such environmental effects, appoint
The material of what pipeline all can be by different degrees of corrosion failure, and generally corrosion phenomenon can be increasingly tighter over time
Weight, eventually thoroughly leads to pipeline failure.Oil-gas pipeline mainly faces two kinds of corrosive environments, first is that the outer corruption of Pipeline Crossing Program soil
Environment is lost, second is that H in pumped (conveying) medium2S、CO2Etc. harmful substances constitute internal corrosion environment.U.S. 1992-2012 is total to be occurred
Pipeline accident 10798 rises, wherein accident caused by corroding accounts for 18.5%;All pipeline things that Canadian 2000-2012 occurs
Therefore middle corrosion leakage accident accounts for more than half.The etching problem of China's oil-gas pipeline is also very prominent, and domestic scholars pass through to Sichuan
The statistics discovery of natural gas line accident is saved, 39.5% accident is as caused by corrosive pipeline;The east that 2013 Qingdaos occur
Yellow Pipeline Leak explodes in special major accident, investigation display corrosion be cause pipe perforation to leak major reason it
One.
Corrosion destruction caused by pipeline is divided into volume type and destroys (local corrosion), diffusion-type destruction (spot corrosion and hydrogen drum
Bubble) and crack type destruction (stress corrosion cracking and corrosion fatigue) three categories.It is based primarily upon elastic-plastic fracture mechanics analysis at present
Method evaluates the crack type destruction of corrosion pipeline using Failure Assessment diagram technology;It is broken for the volume type of corrosion pipeline
It is bad, the local corrosion defect of the interpretational criterias such as DNV-RP-F101 and method assessment pipeline is generallyd use in the world;Now both at home and abroad
There are many method that evaluation of corrosion pipeline diffusion-type destroys, most representative to include:APl579 criterion, ASME B31G criterion etc.,
But since evaluation procedure is excessively complicated, it is difficult to apply in engineering, is usually to borrow commenting for volume type corrosion failure in real process
Valence method evaluates it, these methods are often based upon the corrosion condition of homogeneous corrosion rate assessment pipeline, is corrosion pipeline
Integrity assessment provides theories integration, but in practice it should also be taken into account that influence of the variation of environment to pipe corrosion condition, because
This needs to construct a kind of appraisal procedure, and the random failure that this method can evaluate oil-gas pipeline system under spot corrosion acts on is general
Rate, to assess the corrosion failure situation of oil-gas pipeline.
Summary of the invention
It is an object of the invention to overcome the above-mentioned prior art, a kind of lower oil-gas pipeline of spot corrosion effect is provided
The random failure probability evaluation method of failure of system, this method are capable of the random mistake of the lower oil-gas pipeline system of accurate evaluation spot corrosion effect
Imitate probability.
In order to achieve the above objectives, spot corrosion of the present invention acts on the random failure probability assessment of lower oil-gas pipeline system
Method includes the following steps:
1) relevant parameter of oil-gas pipeline system and the relevant parameter of each corrosion monitoring point are obtained, wherein oil-gas pipeline system
The relevant parameter of system includes the outer dia D, wall thickness b, operating pressure P of oil-gas pipeline0And yield strength σy, corrosion monitoring
The relevant parameter of point includes the depth h of hot spot0, length k0, depth direction corrosion rate v1And length direction corrosion rate v2;
2) in moment t, corrosion depth h (t)=h of hot spot is measured0+v1T and corrosion length k (t)=k0+v2t;
3) residual intensity of oil-gas pipeline corrosion point in moment t is calculated
4) consider oil-gas pipeline corrosion point residual intensity randomness, introduce stochastic variable β, then oil-gas pipeline corrosion point with
Machine residual intensity Z (t)=Z1(t)×β;
5) the mean function μ of oil-gas pipeline corrosion point random residual intensity Z (t) is calculatedZ(t)=E [Z (t)]=Z1(t)×E
[β]=Z1(t) and auto-covariance function CZZ(ti,tj)=λ2ρ2Z1(ti)Z1(tj), wherein λ is the variation coefficient of stochastic variable β,
ρ2For Z (t) in random change procedure different time points tiWith tjIncidence coefficient;
6) according to step 5) calculate random residual intensity Z andCross covariance function
Wherein,AndFor stochastic variable Z andMean value and standard deviation, ρ1It is random
Variable Z withRelated coefficient;
7) it according to Gaussian random process theory, is obtained by step 6):
8) based on the failure probability for passing through probability theory for the first time and calculating oil-gas pipeline system in Analysis of structural reliabilityWherein, Pf(0) when being moment t=0 oil-gas pipeline system failure rate, v is upper logical rate, upper logical
Rate v determines by Rice's criterion, i.e.,
For the P in moment t0Variation slope,For the time-derivative of Z (t) in random process, φ and Φ are respectively standard normal density
Function and standard normal distribution function;
9) due to the failure probability P of oil-gas pipeline system under moment t=0 time point corrosivenessf(0)=0, constant P0Change
Change slopeThe then random failure probability of the single hot spot of t moment
10) the random failure probability P of the oil-gas pipeline system under moment t time point corrosiveness is calculatedf,s(t), whereinPf,s(t) system is caused to be lost at random for i-th of hot spot in moment t on oil-gas pipeline
The probability of effect, n are hot spot number present on oil-gas pipeline.
The concrete operations of step 3) are:
31) residual intensity of oil-gas pipeline corrosion point is calculatedWherein, σfFor Oil/Gas Pipe
Fluid stress in road, A are projected area of the local corrosion defect in oil-gas pipeline y direction, A0It is original before corrosive pipeline
Y direction projected area, M be corrosion pipeline failure before bulging factor, wherein A=h × k, A0=b × k, σf=1.15
σy, then the residual intensity of oil-gas pipeline corrosion point
32) then in moment t, the residual intensity of oil-gas pipeline corrosion point
The concrete operations that the failure probability of oil-gas pipeline system is calculated in step 8) are:
81) in t moment, the random residual intensity Z (t) of oil-gas pipeline corrosion point is down to oil-gas pipeline system normal operation
Operating pressure P0When following, oil-gas pipeline system is in failure state, then the failure probability P of oil-gas pipeline systemf(t)=P [H≤
0]=P [Z (t)≤P0];
82) probability theory is passed through for the first time according in Analysis of structural reliability, the failure probability of oil-gas pipeline system can be with
It is converted toWherein, Pf(0) be moment t=0 when oil-gas pipeline system failure rate, v be it is upper
Logical rate;
83) since the average value of upper logical rate v is smaller, then the failure probability of oil-gas pipeline system can be expressed as
Using corrosion depth h (t)=h of linear model measurement hot spot in step 2)0+v1T and corrosion length k (t)=k0
+v2t。
The invention has the advantages that:
Spot corrosion of the present invention acts on the random failure probability evaluation method of failure of lower oil-gas pipeline system in concrete operations
When, it is not single that Probability Model is established according to traditional oil-gas pipeline thrashing criterion, but on its basis, it utilizes
The probability theory that passes through for the first time in fail-safe analysis is transformed Probability Model, to improve the true and reliable of assessment result
Property, specifically, considering that the randomness of oil-gas pipeline corrosion point residual intensity introduces stochastic variable β, to calculate oil-gas pipeline corrosion
Point random residual intensity is then based in Analysis of structural reliability for the first time so that the result of assessment is more in line with actual conditions
The random failure probability that probability theory calculates the single hot spot of t moment is passed through, and according to the random failure of the single hot spot of t moment
The random failure probability of probability calculation oil-gas pipeline system under moment t time point corrosiveness, with the mistake of quantitative evaluation pipeline
The time is imitated, theory support is provided for the practical corrosion progress for grasping pipeline, provides guidance for the reasonable maintenance decision of early excise.
Detailed description of the invention
Fig. 1 pipeline spot corrosion schematic diagram;
Flow chart Fig. 2 of the invention;
The System failure probability curve graph sought under Fig. 3 distinct methods;
Fig. 4 different correlation coefficient ρs2To the influence diagram of System failure probability;
Fig. 5 different operating pressure P0To the influence diagram of System failure probability;
Fig. 6 different corrosion rate v1And v2To the influence diagram of System failure probability;
Influence diagram of Fig. 7 different line size D and b to System failure probability;
Fig. 8 different yield strength σyTo the influence diagram of System failure probability.
Specific embodiment
The invention will be described in further detail with reference to the accompanying drawing:
Referring to Figure 1 and Figure 2, spot corrosion of the present invention acts on the random failure probability assessment side of lower oil-gas pipeline system
Method includes the following steps:
1) relevant parameter of oil-gas pipeline system and the relevant parameter of each corrosion monitoring point are obtained, wherein oil-gas pipeline system
The relevant parameter of system includes the outer dia D, wall thickness b, operating pressure P of oil-gas pipeline0And yield strength σy, corrosion monitoring
The relevant parameter of point includes the depth h of hot spot0, length k0, depth direction corrosion rate v1And length direction corrosion rate v2;
2) in moment t, corrosion depth h (t)=h of hot spot is measured0+v1T and corrosion length k (t)=k0+v2t;
3) residual intensity of oil-gas pipeline corrosion point in moment t is calculated
4) consider oil-gas pipeline corrosion point residual intensity randomness, introduce stochastic variable β, then oil-gas pipeline corrosion point with
Machine residual intensity Z (t)=Z1(t)×β;
5) the mean function μ of oil-gas pipeline corrosion point random residual intensity Z (t) is calculatedZ(t)=E [Z (t)]=Z1(t)×E
[β]=Z1(t) and auto-covariance function CZZ(ti,tj)=λ2ρ2Z1(ti)Z1(tj), wherein λ is the variation coefficient of stochastic variable β,
ρ2For Z (t) in random change procedure different time points tiWith tjIncidence coefficient;
6) according to step 5) calculate random residual intensity Z andCross covariance function
Wherein,AndFor stochastic variable Z andMean value and standard deviation, ρ1It is random
Variable Z withRelated coefficient;
7) it according to Gaussian random process theory, is obtained by step 6):
8) based on the failure probability for passing through probability theory for the first time and calculating oil-gas pipeline system in Analysis of structural reliabilityWherein, Pf(0) when being moment t=0 oil-gas pipeline system failure rate, v is upper logical rate, upper logical
Rate v determines by Rice's criterion, i.e.,
For the P in moment t0Variation slope,For the time-derivative of Z (t) in random process, φ and Φ are respectively standard normal density
Function and standard normal distribution function;
9) due to the failure probability P of oil-gas pipeline system under moment t=0 time point corrosivenessf(0)=0, constant P0Change
Change slopeThe then random failure probability of the single hot spot of t moment
10) the random failure probability P of the oil-gas pipeline system under moment t time point corrosiveness is calculatedf,s(t), whereinPf,s(t) system is caused to be lost at random for i-th of hot spot in moment t on oil-gas pipeline
The probability of effect, n are hot spot number present on oil-gas pipeline.
The concrete operations of step 3) are:
31) residual intensity of oil-gas pipeline corrosion point is calculatedWherein, σfFor Oil/Gas Pipe
Fluid stress in road, A are projected area of the local corrosion defect in oil-gas pipeline y direction, A0It is original before corrosive pipeline
Y direction projected area, M be corrosion pipeline failure before bulging factor, wherein A=h × k, A0=b × k, σf=1.15
σy, then the residual intensity of oil-gas pipeline corrosion point
32) then in moment t, the residual intensity of oil-gas pipeline corrosion point
The concrete operations that the failure probability of oil-gas pipeline system is calculated in step 8) are:
81) in t moment, the random residual intensity Z (t) of oil-gas pipeline corrosion point is down to oil-gas pipeline system normal operation
Operating pressure P0When following, oil-gas pipeline system is in failure state, then the failure probability P of oil-gas pipeline systemf(t)=P [H≤
0]=P [Z (t)≤P0];
82) probability theory is passed through for the first time according in Analysis of structural reliability, the failure probability of oil-gas pipeline system can be with
It is converted toWherein, Pf(0) be moment t=0 when oil-gas pipeline system failure rate, v be it is upper
Logical rate;
83) since the average value of upper logical rate v is smaller, then the failure probability of oil-gas pipeline system can be expressed as
Using corrosion depth h (t)=h of linear model measurement hot spot in step 2)0+v1T and corrosion length k (t)=k0
+v2t。
In Fig. 3, intend the specific step that method calculates spot corrosion oil-gas pipeline failure probability with Monte Carlo mould (Monte-Carlo)
It is rapid as follows:
1a) construct function of state W=Z (t)-P of spot corrosion pipeline0, wherein P0The operation operated normally for pipe-line system
Pressure,h0、k0、σy、v1、v2, b and D be basic stochastic variable;
2a) determine k0、σy、v1, the stochastic variables such as b and D probability density function f (xi) and probability-distribution function F (xi);
3a) to each stochastic variable, multiple equally distributed random numbers are generated between [0,1]
Wherein, i indicates variable number, i=1,2 ..., n, and j indicates number realization, j=
1,2 ..., N;
4a) for given F (xij), can be by step 3a) in formulaSolve corresponding xij, so
For each variable xi, every simulation is primary, and one group of random number (x can be obtained1j, x2j, x3j..., xnj);
Obtained random number 5a) will be simulated every time and substitute into step 1a) in function of state, to calculate W value, when W value is less than
Zero, meter failure 1 time;
6a) repeat step 3a), 4a) and 5a), carry out n times simulation, amount to failure L times, the then failure of oil-gas pipeline system
Probability Pf(T)=L/N, wherein T is the runing time of pipe-line system.
Emulation experiment
Choosing one section of intact petroleum pipeline that grade is X60 is research object, collects pipeline and evaluates relevant specific number
According to as shown in table 1.
Table 1
The early stage range estimation intact smooth no etch pit of oil-gas pipeline, is detected without leak source, over time, respective location can be seen
To etch pit, monitoring point corrosion data is as shown in table 2.
Table 2
From the figure 3, it may be seen that the change curve that the System failure probability that two methods solve increases at any time is similar, the mistake of system
It is smaller to imitate probability, probability curve variation is more close, this shows that the acceptable risk of system is lower, and the present invention is more effective.
As shown in Figure 4, system fault probability curve tendency under the conditions of different related coefficients is close, so existing different
The influence that related coefficient between the time point of level of breakage fails to oil-gas pipeline is negligible;In addition, being managed according to random process
Correlative study discovery is referred to, the probability of event generation can be exaggerated to the hypothesis of non-correlation between different time points, make spot corrosion
The deterioration of oil-gas pipeline obtains conservative assessment, can prevent that pipeline leakage accident occurs in advance.
As shown in Figure 5, with the growth of operating pressure, the safe life of oil-gas pipeline has significant change, for example, when being
When acceptable probability of malfunction of uniting is 0.1, the operating pressure of system becomes 6.65Mpa from 4.95Mpa, the oil under spot corrosion effect
Feed channel safe life was become 15 years from 32 years, which can help maintenance management person under the acceptable operating pressure of system
Clearly implement the time of pipeline maintenance.
It will be appreciated from fig. 6 that corrosion rate is to influence the key factor of piping system failures probability, spot corrosion oil-gas pipeline system
Under identical acceptable assessment level, if corrosion rate v1=0.1mm/ and v2=4.5mm/ becomes v1=0.2mm/
And v2When=9mm/, the safe life of system was become 12 years from 25 years;If corrosion rate reduces by one times, the safe longevity of system
Life was become 38 years from 25 years.Therefore, accurately the corrosion rate of measurement point corrosion pipeline is pre- to the reliability of oil-gas pipeline system
It surveys critically important.
As shown in fig. 7, spot corrosion pipe-line system is under identical acceptable assessment level, when pipeline geometric dimension by
When DN600 becomes DN900, the safe life of system was become 22 years from 12 years, this illustrates that oil-gas pipeline system other parameters are kept
When constant, the duct wall of large-diameter pipeline is thicker, and the probability that pipe-line system breaks down is lower.
As shown in figure 8, the failure probability curvilinear motion of oil-gas pipeline system is similar under the conditions of different yield strengths,
The failure probability of system is smaller, and probability curve variation is more close, this shows that the acceptable risk of system is lower, and yield strength is to point
The failure probability of corrosion pipeline system influences smaller.
The content that description in the present invention is not described in detail belongs to the known existing disclosure of professional and technical personnel in the field
Technology, and the above embodiments are only used to illustrate the present invention, and not limitation of the present invention.Although disclosing for the purpose of illustration
Related embodiment and attached drawing of the invention, but it will be appreciated by those skilled in the art that;It is of the invention and appended not departing from
Spirit and scope of the claims in, it is various replacement, variation, modification be all possible.Therefore, all equivalent technical solutions
Scope of the invention is also belonged to, scope of patent protection of the invention should be defined by the claims, and should not be limited to most preferably implement
Example and attached drawing disclosure of that.
Claims (4)
1. the random failure probability evaluation method of failure that a kind of spot corrosion acts on lower oil-gas pipeline system, which is characterized in that including following
Step:
1) relevant parameter of oil-gas pipeline system and the relevant parameter of each corrosion monitoring point are obtained, wherein oil-gas pipeline system
Relevant parameter includes the outer dia D, wall thickness b, operating pressure P of oil-gas pipeline0And yield strength σy, corrosion monitoring point
Relevant parameter includes the depth h of hot spot0, length k0, depth direction corrosion rate v1And length direction corrosion rate v2;
2) in moment t, corrosion depth h (t)=h of hot spot is measured0+v1T and corrosion length k (t)=k0+v2t;
3) residual intensity of oil-gas pipeline corrosion point in moment t is calculated
4) randomness for considering oil-gas pipeline corrosion point residual intensity, introduces stochastic variable β, then oil-gas pipeline corrosion point remains at random
Residual strength Z (t)=Z1(t)×β;
5) the mean function μ of oil-gas pipeline corrosion point random residual intensity Z (t) is calculatedZ(t)=E [Z (t)]=Z1(t)×E[β]
=Z1(t) and auto-covariance function CZZ(ti,tj)=λ2ρ2Z1(ti)Z1(tj), wherein λ is the variation coefficient of stochastic variable β, ρ2
For Z (t) in random change procedure different time points tiWith tjIncidence coefficient;
6) according to the calculated result of step 5) calculate random residual intensity Z andCross covariance function
Wherein,AndFor stochastic variable Z andMean value and standard deviation, ρ1It is random
Variable Z withRelated coefficient;
7) it according to Gaussian random process theory, is obtained by step 6):
8) based on the failure probability for passing through probability theory for the first time and calculating oil-gas pipeline system in Analysis of structural reliabilityWherein, Pf(0) when being moment t=0 oil-gas pipeline system failure rate, v is upper logical rate, upper logical
Rate v determines by Rice's criterion, i.e.,
For the P in moment t0Variation slope,For the time-derivative of Z (t) in random process, φ and Φ are respectively standard normal density
Function and standard normal distribution function;
9) due to the failure probability P of oil-gas pipeline system under moment t=0 time point corrosivenessf(0)=0, constant P0Variation it is oblique
RateThe then random failure probability of the single hot spot of t moment
10) the random failure probability P of the oil-gas pipeline system under moment t time point corrosiveness is calculatedf,s(t), whereinPf,s(t) system is caused to be lost at random for i-th of hot spot in moment t on oil-gas pipeline
The probability of effect, n are hot spot number present on oil-gas pipeline.
2. spot corrosion according to claim 1 acts on the random failure probability evaluation method of failure of lower oil-gas pipeline system, special
Sign is that the concrete operations of step 3) are:
31) residual intensity of oil-gas pipeline corrosion point is calculatedWherein, σfFor in oil-gas pipeline
Fluid stress, A are projected area of the local corrosion defect in oil-gas pipeline y direction, A0For the longitudinal axis original before corrosive pipeline
Direction projection area, M are the bulging factor before corrosion pipeline failure, wherein A=h × k, A0=b × k, σf=1.15 σy, then oily
The residual intensity of feed channel hot spot
32) then in moment t, the residual intensity of oil-gas pipeline corrosion point
3. spot corrosion according to claim 1 acts on the random failure probability evaluation method of failure of lower oil-gas pipeline system, special
Sign is that the concrete operations that the failure probability of oil-gas pipeline system is calculated in step 8) are:
81) in t moment, the random residual intensity Z (t) of oil-gas pipeline corrosion point is down to the operation of oil-gas pipeline system normal operation
Pressure P0When following, oil-gas pipeline system is in failure state, then the failure probability P of oil-gas pipeline systemf(t)=P [H≤0]=
P[Z(t)≤P0];
82) probability theory is passed through for the first time according in Analysis of structural reliability, the failure probability of oil-gas pipeline system can be converted
ForWherein, Pf(0) be moment t=0 when oil-gas pipeline system failure rate, v be upper logical speed
Rate;
83) since the average value of upper logical rate v is smaller, then the failure probability of oil-gas pipeline system can be expressed as
4. spot corrosion according to claim 1 acts on the random failure probability evaluation method of failure of lower oil-gas pipeline system, special
Sign is, using corrosion depth h (t)=h of linear model measurement hot spot in step 2)0+v1T and corrosion length k (t)=k0+
v2t。
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CN113592252A (en) * | 2021-07-12 | 2021-11-02 | 武汉理工大学 | Port crude oil loading risk visualization deduction method in task mode |
CN114528700A (en) * | 2022-01-26 | 2022-05-24 | 西安三维应力工程技术有限公司 | Method for determining residual strength of oil pipe containing corrosion pits |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2013169241A1 (en) * | 2012-05-09 | 2013-11-14 | Bp Corporation North America Inc. | Predictive corrosion coupons from data mining |
CN104807966A (en) * | 2015-04-30 | 2015-07-29 | 上海化学工业区公共管廊有限公司 | Residual intensity and residual life computing method for pipe gallery pipelines |
CN104834783A (en) * | 2015-05-12 | 2015-08-12 | 江苏科技大学 | Parameterized construction method of numerical model of pit-corrosion-randomly-distributed cylindrical shell |
CN105302946A (en) * | 2015-10-13 | 2016-02-03 | 中国石油天然气股份有限公司 | Method and apparatus for determining reliability of corrosive pipeline |
-
2018
- 2018-06-15 CN CN201810620963.XA patent/CN108920421A/en active Pending
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2013169241A1 (en) * | 2012-05-09 | 2013-11-14 | Bp Corporation North America Inc. | Predictive corrosion coupons from data mining |
CN104807966A (en) * | 2015-04-30 | 2015-07-29 | 上海化学工业区公共管廊有限公司 | Residual intensity and residual life computing method for pipe gallery pipelines |
CN104834783A (en) * | 2015-05-12 | 2015-08-12 | 江苏科技大学 | Parameterized construction method of numerical model of pit-corrosion-randomly-distributed cylindrical shell |
CN105302946A (en) * | 2015-10-13 | 2016-02-03 | 中国石油天然气股份有限公司 | Method and apparatus for determining reliability of corrosive pipeline |
Non-Patent Citations (3)
Title |
---|
CHUN QINGLI: "Failure assessment and safe life prediction of corroded oil and gas pipelines", 《JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING》 * |
邵剑文: "海底管道的健康监测***与评估研究", 《万方数据库》 * |
骆正山 等: "Frechet分布的海底油气管道腐蚀预测", 《腐蚀与防护》 * |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110263364A (en) * | 2019-05-05 | 2019-09-20 | 四川大学 | A kind of oil-gas pipeline corrosion defect residual intensity algorithm considering decaying time variation |
CN112949190A (en) * | 2021-03-08 | 2021-06-11 | 西南石油大学 | Fuzzy random reliability assessment method for crack defect-containing pipeline based on R6-FAD and BP-MCS |
CN113252547A (en) * | 2021-03-31 | 2021-08-13 | 中车青岛四方机车车辆股份有限公司 | Aluminum alloy corrosion fatigue risk grade evaluation method based on environmental threshold |
CN113592252A (en) * | 2021-07-12 | 2021-11-02 | 武汉理工大学 | Port crude oil loading risk visualization deduction method in task mode |
CN113592252B (en) * | 2021-07-12 | 2023-08-08 | 武汉理工大学 | Port crude oil loading risk visual deduction method in task mode |
CN114528700A (en) * | 2022-01-26 | 2022-05-24 | 西安三维应力工程技术有限公司 | Method for determining residual strength of oil pipe containing corrosion pits |
CN114528700B (en) * | 2022-01-26 | 2024-04-09 | 西安三维应力工程技术有限公司 | Method for determining residual strength of oil pipe containing corrosion pit |
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