CN106910015A - Heat supply secondary network risk of leakage appraisal procedure based on FAHP - Google Patents
Heat supply secondary network risk of leakage appraisal procedure based on FAHP Download PDFInfo
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Abstract
The present invention relates to heating network line leakage field, to propose a kind of method to the assessment of secondary network risk of leakage, and according to the risk of leakage grading index of secondary network come determine subregion dress table, set intellectual monitoring point, so as to build a set of more rational intelligent leak detection system.The technical solution adopted by the present invention is that the heat supply secondary network risk of leakage appraisal procedure based on Fuzzy AHP FAHP, step is as follows：Step 1, investigated and summarized the reason for leak heat supply pipeline, established the principal element of pipe leakage；Step 2, heat supply secondary network risk of leakage Grade is set up, P={ certain heating network risk of leakage }.Present invention is mainly applied to heating network line leakage occasion.
Description
Technical field
The present invention relates to heating network line leakage field, more particularly to a kind of secondary network risk of leakage assessment and
Monitoring point method for arranging.
Background technology
The energy resource structure stepped into China under " 13 " plan is reformed, energy Internet technology high speed development.
In northern China Urban Areas, distributed energy central heating progressively replaces traditional district heating pattern.Take in view of transformation
With and difficulty of construction, the realization of current prefecture-level city's central heating pattern is on the basis of one-level heating network is extended, progressively simultaneously
Connection traditional area heating network is used as secondary network.The continuous expansion of central heating network, not only brings huge economic effect
Benefit, also provides engineering foundation to realize that energy intelligentized is utilized.But, in practical engineering application, first-level pipeline network and two grades
The seepy question of pipe network is extremely serious, causes very big loss and wastes.For this problem, the U of patent CN 202834780 are provided
A kind of heating network leakage alignment system, is made up of control centre, control system and infrared thermometer, can be accurate rapidly
The position that leaks of determination heating network.The A of patent CN 102033969 provide a kind of Water supply network system and side
Method, utilizes " subregion dress table method " to install the devices such as flowmeter and set monitoring point, and determine using pipe network model performance indications
The treatment strategy of each leak source.The A of patent CN 101907228 provide a kind of heat supply pipeline leak testing and monitoring system, use
Heat supply steel pipe and pipeline compensator and micro-computer technology with detection line, can accurately, in real time reflect the work of heat supply pipeline
State and malfunction, signal can be detected on the spot, it is also possible to which teletransmission is monitored, and accomplishes pipeline intelligent control truly
System.The A of patent CN 1367374 provide a kind of heat-supply network failure quick detection system, by control centre's sum pipe network
Individual remote transmission terminal composition, for the quick detection positioning of the failure such as heating network booster and leakage.
But from the point of view of with regard to current prior art, solving the problems, such as and investigating in pipe network water leakage, one-level pipe is not being accounted for
The greatest differences of net and secondary network, simultaneously because by district heating pipe network improving secondary network newness degree not
Together, secondary network is monitored with same standard can not meet requirement.The present invention is intended to provide a kind of leak secondary network
The method of risk assessment, and according to the risk of leakage grading index of secondary network come determine subregion dress table, set intellectual monitoring point
Method.
The content of the invention
To overcome the deficiencies in the prior art, the present invention is directed to propose a kind of method to the assessment of secondary network risk of leakage,
And according to the risk of leakage grading index of secondary network come determine subregion dress table, set intellectual monitoring point so that build it is a set of more
Plus rational intelligence leak detection system.The technical solution adopted by the present invention is, two grades of the heat supply based on Fuzzy AHP FAHP
Pipeline network leak methods of risk assessment, step is as follows：
Step 1, investigated and summarized the reason for leak heat supply pipeline, established the principal element of pipe leakage；
Step 2, heat supply secondary network risk of leakage Grade is set up, P={ certain heating network risk of leakage }, tool
Body includes following sub-step；
Step 21, structure evaluate collection S, heat supply secondary network risk of leakage grade classification are I low-risk level, II compared with low-risk
Level, III medium risk level, IV high risk level, V excessive risks five grades of level, i.e. S={ I, II, III, IV, V }, using full marks
100 points of systems, it is (0,20), (20,40), (40,60), (60,80), (80,100) that correspondence score value is interval, as shown in table 1；
Table 1
| Grade | Ⅰ | Ⅱ | Ⅲ | Ⅳ | V |
| Levels of risk | It is low | It is relatively low | It is medium | It is higher | It is high |
| Score value is interval | (0,20) | (20,40) | (40,60) | (60,80) | (80,100) |
Step 22, determine grade evaluation points, build evaluation points collection U, then U={ use time, corrosive pipeline, valve
Failure, weld seam rupture, compensator is damaged }；
Step 23, determine heat supply secondary network to be evaluated, set up hierarchy Model；
Step 24, based on Fuzzy AHP FAHP, calculate the weight of each grade evaluation points；
Step 25, the correlation function value for calculating each evaluation index；
Step 26, the correlation function value for determining heat supply secondary network；
Step 27, the grade for determining heat supply secondary network.
Wherein, the weight computations of each grade evaluation index in step 24 are：
Judgment matrix D of the every grade evaluation points of step 241, construction to heat supply secondary network；
Step 242, the arithmetic mean of instantaneous value after 5 row vectors normalization of matrix D is will determine that as weight vectors, as the following formula
Calculate：
In formula, dii'It is two factor judgment values, i and i' is the subscript sequence number of the evaluation index.
Wherein, the correlation function value calculating process of each evaluation index is in step 25：
Calculation Estimation factor uiOn pipeline leakage risk class PjThe correlation function K of (j=1,2 ..., 5)j(si):
Work as si∈sjiWhen,
WhenWhen,
If ρ (si,spi)≠ρ(si,sji), then
If ρ (si,spi)=ρ (si,sji), then Kj(si)=- ρ (si,sji)-1
Wherein, siIt is evaluation points uiRisk score value, sjiEvaluation points are on wind described in j-th described in i-th
The score value of dangerous grade is interval, ρ (si,sji) represent the risk score value of evaluation points described in i-th with its score value interval
Away from ρ (si,spi) represent the risk score value of evaluation points described in i-th and risk total score interval spiAway from；
Wherein, each parameter calculating formula is as follows：
|sji|=| bji-aji|
bji, ajiRespectively risk score value interval sjiBound, bpi, apiRespectively risk total score interval spiIt is upper and lower
Limit.
The correlation function value of heat supply secondary network described in step 26 is calculated as follows：
The risk of leakage grade determination process of the heat supply secondary network described in step 27 is as follows：
Risk class when taking the corresponding heat supply secondary network correlation function maximum is evaluation result, i.e.,
M (P)=max Mj(P)
M (P) is the evaluation result, and the risk class corresponding to it is the leakage wind of the heat supply secondary network to be evaluated
Dangerous grade.
The step of being arranged present invention additionally comprises subregion dress table and monitoring point：
First according to evaluation model, secondary network is carried out into risk of leakage grade assessment, secondly statistics heat supply secondary network
The quantity of key position, including the easy leakage of valve, weld seam, compensator position, by secondary network risk of leakage grade it is identical,
The similar region of key position quantity is divided into an area, uses management of the same race and monitoring method；Risk of leakage grade is high, crucial portion
Monitoring point being arranged pipe network more than bit quantity more；Meanwhile, at the position of the easily leakage such as heat supply secondary network valve, weld seam, compensator
Arrangement monitoring point, installs the measurement of correlation instrument such as flow sensor, pressure sensor；Monitoring point cloth executed as described above is postponed, with reference to
Distribution GIS, builds intelligent monitor system, and the system is passed by control centre, data transmission set and flow, pressure
Sensor is constituted, by the data acquisition of each sensor terminal, after returning to control centre, and by microprocessor calculation procedure,
Real-time hydraulic regime is drawn, corresponding system pressure diagram is correspondingly formed；If pipeline is leaked, the hydraulic pressure in corresponding geographical position
Can then reduce, realize leaking the positioning of pipeline section with this.
The features of the present invention and beneficial effect are：
The present invention is intended to provide a kind of method to the assessment of secondary network risk of leakage, and according to the leakage wind of secondary network
Dangerous grading index come determine subregion dress table, set intellectual monitoring point.Highlight heat supply first-level pipeline network, secondary network engineering it is poor
The opposite sex, the risk of leakage grading index assessment that foundation is carried out to secondary network, and combine method for arranging of the index to monitoring point
Optimize, to realize standardization, digitlization, the intelligentized development of central heating system, so as to improve the peace of central heating
Full property and economy.
Brief description of the drawings：
Fig. 1 heat supply secondary network risk of leakage estimation flow figures.
Fig. 2 hierarchy Model figures.
Fig. 3 leaks pipeline section positioning flow figure.
Fig. 4 data handling procedure schematic diagrames of the present invention.
Specific embodiment
There is significant difference in the first-level pipeline network of the central heating system transformed by district heating, with secondary network in pipe
Should be treated with a certain discrimination in road monitoring leak detection and decision-making technique, and existing patent does not consider this difference and makes countermeasure.
Meanwhile, in Practical Project case, the secondary network for being incorporated to central heating system often has different use times, new and old journey
Degree differs, and it should not be monitored using same standard.Therefore, the present invention is intended to provide a kind of to secondary network risk of leakage
The method of assessment, and according to the risk of leakage grading index of secondary network come determine subregion dress table, set intellectual monitoring point so that
Build a set of more rational intelligent leak detection system.
To solve the above problems, it is an object of the invention to provide a kind of heat supply secondary network risk of leakage grade evaluation side
Method, and the method for determining subregion dress table, intellectual monitoring point being set according to the risk of leakage grading index of secondary network.As schemed
Shown in 1.
Present invention firstly provides a kind of heat supply secondary network risk of leakage grade evaluation method, comprise the following steps：
The reason for step 1, tissue associated specialist are leaked heat supply pipeline is investigated and is summarized, and establishes the master of pipe leakage
Want factor；
Step 2, heat supply secondary network risk of leakage Grade is set up, P={ certain heating network risk of leakage }, tool
Body includes following sub-step；
Step 21, structure evaluate collection S, heat supply secondary network risk of leakage grade classification are I low-risk level, II compared with low-risk
Level, III medium risk level, IV high risk level, V excessive risks five grades of level, i.e. S={ I, II, III, IV, V }.Using full marks
100 points of systems, it is (0,20), (20,40), (40,60), (60,80), (80,100) that correspondence score value is interval, as shown in table 1；
Table 1
| Grade | Ⅰ | Ⅱ | Ⅲ | Ⅳ | V |
| Levels of risk | It is low | It is relatively low | It is medium | It is higher | It is high |
| Score value is interval | (0,20) | (20,40) | (40,60) | (60,80) | (80,100) |
Step 22, determine grade evaluation points, build evaluation points collection U.Then U={ use time, corrosive pipeline, valve
Failure, weld seam rupture, compensator is damaged }；
Step 23, determine heat supply secondary network to be evaluated, set up hierarchy Model, as a result as shown in Figure 2.；
Step 24, based on Fuzzy AHP FAHP (fuzzy analytic hierarchy process), calculate
The weight of each grade evaluation points；
Step 25, the correlation function value for calculating each evaluation index；
Step 26, the correlation function value for determining heat supply secondary network；
Step 27, the grade for determining heat supply secondary network.
Wherein, the weight computations of each grade evaluation index in step 24 are：
Judgment matrix D of the every grade evaluation points of step 241, construction to heat supply secondary network；
Step 242, the arithmetic mean of instantaneous value after 5 row vectors normalization of matrix D is will determine that as weight vectors, as the following formula
Calculate：
In formula, dii’It is two factor judgment values, i and i' is the subscript sequence number of the evaluation index.
Wherein, the correlation function value calculating process of each evaluation index is in step 25：
Calculation Estimation factor uiOn pipeline leakage risk class PjThe correlation function K of (j=1,2 ..., 5)j(si):
Work as si∈sjiWhen,
WhenWhen,
If ρ (si,spi)≠ρ(si,sji), then
If ρ (si,spi)=ρ (si,sji), then Kj(si)=- ρ (si,sji)-1
Wherein, siIt is evaluation points uiRisk score value, sjiEvaluation points are on wind described in j-th described in i-th
The score value of dangerous grade is interval, ρ (si,sji) represent the risk score value of evaluation points described in i-th with its score value interval
Away from ρ (si,spi) represent evaluation points described in i-th risk score value and the total score it is interval away from.
Wherein, each parameter calculating formula is as follows：
|sji|=| bji-aji|
bji, ajiRespectively risk score value interval sjiBound, bpi, apiRespectively risk total score interval spiIt is upper and lower
Limit,
The correlation function value of heat supply secondary network described in step 26 is calculated as follows：
The risk of leakage grade determination process of the heat supply secondary network described in step 27 is as follows：
Risk class when taking the corresponding heat supply secondary network correlation function maximum is evaluation result, i.e.,
M (P)=max Mj(P)
M (P) is the evaluation result, and the risk class corresponding to it is the leakage wind of the heat supply secondary network to be evaluated
Dangerous grade.
Secondly, a kind of method that the present invention provides subregion dress table and monitoring point arrangement.
Because heat supply secondary network quantity is more and property is different, it is necessary to carry out partition management.The foundation of subregion is confession
The quantity of hot secondary network grade and its key position.First according to evaluation model, secondary network is carried out into risk of leakage grade
Assessment.Secondly the quantity of heat supply secondary network key position, such as position of valve, weld seam, compensator easily leakage are counted.By two
The level region that pipeline network leak risk class is identical, key position quantity is similar is divided into an area, uses management of the same race and monitoring side
Method.Monitoring point being arranged risk of leakage grade pipe network high more.Meanwhile, easily let out in heat supply secondary network valve, weld seam, compensator etc.
The position arrangement monitoring point of leakage, installs the measurement of correlation instrument such as flow sensor, pressure sensor.Monitoring point arrangement executed as described above
Afterwards, combining geographic information system (GIS), builds intelligent monitor system.The system is by control centre, data transmission set and stream
Amount, pressure sensor composition.By the data acquisition of each sensor terminal, after returning to control centre, by microprocessor
Calculation procedure, draws real-time hydraulic regime, is correspondingly formed corresponding system pressure diagram.It is corresponding geographical if pipeline is leaked
The hydraulic pressure of position can then be reduced, and realize leaking the positioning of pipeline section with this.As shown in Figure 3.
The present invention is described in further detail below by specific embodiment and with reference to accompanying drawing.
It is collected and summarizes by the leakage accident data to certain Practical Project case central heating secondary network, draws
The scoring of its every disclosure risk evaluation points, is shown in Table 2.
The appraisal result of the risk of leakage evaluation points of table 2 certain Practical Project case central heating secondary network
| Evaluation index U | Use time | Corrosive pipeline | Failsafe valve | Weld seam ruptures | Compensator is damaged |
| Pipe network score s to be evaluated | 68 | 59 | 52 | 42 | 32 |
The risk class score value interval of evaluation points is shown in Table 3.
The risk class of the evaluation points of table 3
Described in step 23 based on Fuzzy AHP, construct every evaluation points siTo the heat supply diode
The judgment matrix D of net.
The arithmetic mean of instantaneous value after 5 row vectors that will determine that matrix D normalization described in step 24 is pressed as weight vectors
Following formula is calculated：
Then every evaluation points siFor the weight α of heat supply secondary network risk of leakage gradeiAs shown in table 4.
The every evaluation points s of table 4iFor the weight α of heat supply secondary network risk of leakage gradei
| 0.3297 | 0.3297 | 0.1648 | 0.1099 | 0.0659 |
Calculation Estimation factor u described in step 25iOn pipeline leakage risk class PjThe association letter of (j=1,2 ..., 5)
Number Kj(si):
Work as si∈sjiWhen,
WhenWhen,
If ρ (si,spi)≠ρ(si,sji), then
If ρ (si,spi)=ρ (si,sji), then Kj(si)=- ρ (si,sji)-1
Wherein, each parameter calculating formula is as follows：
|sji|=| bji-aji|
Calculate correlation function value of each evaluation points on each risk of leakage grade and be shown in Table 5.
Correlation function value of each evaluation points of table 5 on each risk of leakage grade
The correlation function value of the heat supply secondary network described in step 26 is calculated as follows：
Weight and each evaluation points correlation function value are substituted into, the correlation function value of heat supply secondary network is drawn, 6 are shown in Table.
The correlation function value of the heat supply secondary network of table 6
| Risk class | Ⅰ | Ⅱ | Ⅲ | Ⅳ | V |
| Mj(P) | -0.4952 | -0.2698 | 0.5824 | 0.0368 | -0.3540 |
Risk class when taking the corresponding heat supply secondary network correlation function maximum described in step 27 is evaluation
As a result, i.e.,
M (P)=max Mj(P)
M (P)=max M as shown in Table 4j(P)=0.5824, in III grade of risk of leakage grade, i.e., heat supply two to be evaluated
The risk of leakage grade of level pipe network is III grade.
Ibid step, the risk of leakage grade of another heat supply secondary network to be evaluated is II grade.By statistics, two pipeline section
The position quantity of the easily leakage such as valve, weld seam, compensator is similar, then two pipeline section is not in a subregion, and risk of leakage grade
For the installation of the measurement of correlation instrument such as III grade of pipeline flow sensor, pressure sensor is II grade more than risk of leakage grade
Pipeline section.
Monitoring point cloth executed as described above is postponed, combining geographic information system (GIS), builds intelligent monitor system.The system by
Control centre, data transmission set and flow, pressure sensor composition.By the data acquisition of each sensor terminal, return
After returning to control centre, by microprocessor calculation procedure, real-time hydraulic regime is drawn, be correspondingly formed corresponding system hydraulic pressure
Figure.If pipeline is leaked, the hydraulic pressure in corresponding geographical position can then be reduced, and realize leaking the positioning of pipeline section with this.
Claims (5)
1. a kind of heat supply secondary network risk of leakage appraisal procedure based on FAHP, it is characterized in that, step is as follows：
Step 1, investigated and summarized the reason for leak heat supply pipeline, established the principal element of pipe leakage；
Step 2, heat supply secondary network risk of leakage Grade is set up, P={ certain heating network risk of leakage }, specific bag
Include following sub-step；
Step 21, build evaluate collection S, heat supply secondary network risk of leakage grade classification be I low-risk level, II relatively low levels of risk,
III medium risk level, IV high risk level, V excessive risks five grades of level, i.e. S={ I, II, III, IV, V }, using 100 points of full marks
System, it is (0,20), (20,40), (40,60), (60,80), (80,100) that correspondence score value is interval, as shown in table 1；
Table 1
Step 22, determine grade evaluation points, build evaluation points collection U, then U=use time, corrosive pipeline, failsafe valve,
Weld seam is ruptured, and compensator is damaged }；
Step 23, determine heat supply secondary network to be evaluated, set up hierarchy Model；
Step 24, based on Fuzzy AHP FAHP, calculate the weight of each grade evaluation points；
Step 25, the correlation function value for calculating each evaluation index；
Step 26, the correlation function value for determining heat supply secondary network；
Step 27, the grade for determining heat supply secondary network.
2. the heat supply secondary network risk of leakage appraisal procedure of FAHP is based on as claimed in claim 1, it is characterized in that, wherein,
The weight computations of each grade evaluation index in step 24 are：
Judgment matrix D of the every grade evaluation points of step 241, construction to heat supply secondary network；
Step 242, will determine that matrix D 5 row vectors normalization after arithmetic mean of instantaneous value as weight vectors, count as the following formula
Calculate：
In formula, dii' is two factor judgment values, and i and i' is the subscript sequence number of the evaluation index.
3. the heat supply secondary network risk of leakage appraisal procedure of FAHP is based on as claimed in claim 1, it is characterized in that, step 25
In the correlation function value calculating process of each evaluation index be：
Correlation function Kjs (si) of the Calculation Estimation factor ui on pipeline leakage risk class Pj (j=1,2 ..., 5):
As si ∈ sji,
WhenWhen,
If ρ (si,spi)≠ρ(si,sji), then
If ρ (si,spi)=ρ (si,sji), then Kj(si)=- ρ (si,sji)-1
Wherein, si is the risk score value of evaluation points ui, and sji is evaluation points described in i-th on risk described in j-th etc.
The score value of level is interval, ρ (si,sji) represent the risk score value of evaluation points described in i-th with its score value interval away from ρ
(si,spi) represent the risk score value of evaluation points described in i-th and risk total score interval spiAway from；
Wherein, each parameter calculating formula is as follows：
|sji|=| bji-aji|
bji, ajiRespectively risk score value interval sjiBound, bpi, apiRespectively risk total score interval spiBound.
4. the heat supply secondary network risk of leakage appraisal procedure of FAHP is based on as claimed in claim 2, it is characterized in that, step 26
The correlation function value of the heat supply secondary network is calculated as follows：
The risk of leakage grade determination process of the heat supply secondary network described in step 27 is as follows：
Risk class when taking the corresponding heat supply secondary network correlation function maximum is evaluation result, i.e.,
M (P)=max Mj(P)
M (P) is the evaluation result, and the risk class corresponding to it is risk of leakage of the heat supply secondary network to be evaluated etc.
Level.
5. the heat supply secondary network risk of leakage appraisal procedure of FAHP is based on as claimed in claim 1, it is characterized in that, also include
The step of subregion dress table is arranged with monitoring point：First according to evaluation model, secondary network is carried out into risk of leakage grade assessment, its
It is secondary statistics heat supply secondary network key position quantity, including the easy leakage of valve, weld seam, compensator position, by diode
The region that net risk of leakage grade is identical, key position quantity is similar is divided into an area, uses management of the same race and monitoring method；Let out
Risk class is high for leakage, arrange monitoring point the pipe network more than key position quantity more；Meanwhile, in heat supply secondary network valve, weld seam, benefit
The position arrangement monitoring point of the easily leakage such as device is repaid, the measurement of correlation instrument such as flow sensor, pressure sensor are installed；It is executed as described above
Monitoring point cloth is postponed, combining geographic information system GIS, builds intelligent monitor system, and the system is set by control centre, data transfer
Standby and flow, pressure sensor composition, by the data acquisition of each sensor terminal, after returning to control centre, pass through
Microprocessor calculation procedure, draws real-time hydraulic regime, is correspondingly formed corresponding system pressure diagram；If pipeline is leaked,
The hydraulic pressure in corresponding geographical position can then be reduced, and realize leaking the positioning of pipeline section with this.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108764745A (en) * | 2018-06-05 | 2018-11-06 | 中国石油大学(北京) | A kind of dangerous liquid pipe leakage risk evaluating method and device |
| CN109886506A (en) * | 2019-03-14 | 2019-06-14 | 重庆大学 | A kind of water supply network booster risk analysis method |
| CN110232520A (en) * | 2019-06-12 | 2019-09-13 | 深圳市燃气集团股份有限公司 | A kind of method for early warning and system based on pipeline integrity |
| CN110822297A (en) * | 2019-11-08 | 2020-02-21 | 西南石油大学 | Pipeline safety state evaluation method and stepped boosting pipeline safety re-production method |
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| CN110822297B (en) * | 2019-11-08 | 2021-02-02 | 西南石油大学 | Pipeline safety state evaluation method and stepped boosting pipeline safety re-production method |
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