CN111104720B - Monitoring point arrangement method for underground space gas explosion risk prevention and control - Google Patents

Monitoring point arrangement method for underground space gas explosion risk prevention and control Download PDF

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CN111104720B
CN111104720B CN201911270790.4A CN201911270790A CN111104720B CN 111104720 B CN111104720 B CN 111104720B CN 201911270790 A CN201911270790 A CN 201911270790A CN 111104720 B CN111104720 B CN 111104720B
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袁宏永
侯龙飞
付明
端木维可
钱新明
袁梦琦
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Anhui Theone Safety Technology Co ltd
Hefei Zezhong City Intelligent Technology Co ltd
Beijing Institute of Technology BIT
Hefei Institute for Public Safety Research Tsinghua University
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Hefei Zezhong City Intelligent Technology Co ltd
Beijing Institute of Technology BIT
Hefei Institute for Public Safety Research Tsinghua University
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Abstract

The invention discloses a monitoring point arrangement method for underground space gas explosion risk prevention and control, which constructs an effective monitoring point arrangement strategy by combining a total system risk value, the investment reasonability of monitoring point arrangement and the system risk control rate, can optimize to the maximum benefit value, is beneficial to saving capital investment and obtaining the maximum detection efficiency so as to find the gas pipeline leakage condition in time and avoid secondary disasters caused by gas leakage, and has an important effect on ensuring the safe operation of urban gas. The invention also creatively introduces the sensor prediction effect into the explosion risk calculation of the adjacent underground space on the basis of the traditional risk calculation method, and calculates the total risk value of the system by taking all the adjacent underground spaces in the gas pipeline leakage influence range as a whole.

Description

Monitoring point arrangement method for underground space gas explosion risk prevention and control
Technical Field
The invention relates to the technical field of danger prevention and control monitoring, in particular to a monitoring point arrangement method for underground space gas explosion risk prevention and control.
Background
Along with the rapid expansion of urban population and the gradual expansion of urban areas, the popularization of natural gas application brings about the rapid expansion of the scale of urban gas pipelines. Due to the complexity of urban underground pipelines, once a gas pipeline leaks, the gas pipeline is easy to diffuse to adjacent underground spaces such as rain sewage, electric power and the like, and large-scale explosion is caused.
At present, two methods for detecting and monitoring urban gas pipeline leakage include an SCADA monitoring system and a manual regular inspection. The SCADA system monitors the pressure and flow of each node in real time, but only effectively monitors sudden pressure drop caused by large-scale leakage of pipelines, and cannot find micro leakage in a pipe network. The manual regular inspection is to find tiny leakage of the gas pipe network by adopting manual inspection modes such as a handheld combustible gas detection terminal, a combustible gas detection vehicle and the like, but the method has poor real-time performance.
Under the condition that pipeline leakage cannot be found well at the initial stage of leakage at present, a method for effectively solving the problem of pipeline leakage is to monitor places where gas pipelines are likely to gather after leakage, namely underground spaces where the gas pipelines are adjacent or intersected, for example, a rainwater and sewage well, a gas valve well, an electric power well and the like around the pipelines, avoid explosion accidents in the spaces after leakage while finding gas leakage, and have important significance for guaranteeing safe operation of urban gas pipelines and safety of lives and properties of people.
However, the number of adjacent underground spaces in the peripheral region of the gas pipeline is large and uneven, it is not practical to monitor all the adjacent underground spaces, and it is desirable to select an adjacent underground space with a large explosion risk and a good monitoring effect from the adjacent underground spaces to arrange sensors, but this selection process has certain difficulty.
Through retrieval, the method for determining the CO2 geological storage leakage risk monitoring points has the Chinese patent publication number CN106354983A, in the method, risk grade division and sequencing are carried out on positions of carbon dioxide leakage risks through a historical data fitting and numerical simulation method, and then point positions with large leakage risks are appointed and monitored; the method is not suitable for high-risk underground air monitoring, such as in commercial areas in cities, particularly in crossroad sections, the distribution density of adjacent underground spaces is high, the explosion risk is high, and the method is obviously not suitable for monitoring the underground air.
Through retrieval, the Chinese patent publication No. CN109443526A is a noise map-based point location arrangement method for noise automatic monitoring equipment, the method mainly determines the number of monitoring points according to city scale and road density, distributes the number of the measuring points according to the total length of road types, determines the road to be monitored by calculating equivalent sound level and road length in a noise map, and finally arranges the specific positions of the monitoring points according to a related method; the method needs to lay factors such as various roads in the process of laying monitoring points, belongs to a relatively fixed measuring point laying method, and does not provide the content of optimizing the measuring points and predicting the effect of the monitoring points.
Through retrieval, the Chinese patent publication No. CN103713097A discloses a point location arrangement method for investigating heavy metal pollution conditions of bottom sediment of a large-area water body, wherein the point location arrangement is divided into two stages, investigative monitoring is implemented in the first stage, and thick line arrangement is carried out on heavy-point rivers; in the second stage, heavy-point monitoring is implemented, and encryption point location arrangement is carried out; particularly, in the second stage, the degree of heavy metal pollution of the sediment is evaluated according to the investigation result of the first stage and relevant standards, and then point positions are arranged among different classified point positions in an encrypted manner by adopting a dichotomy method; the patent designs a corresponding point distribution strategy aiming at a monitored object, the point distribution strategy is difficult to be applied to the researched object of the invention, and a process for optimizing a measuring point does not exist in the patent.
Through retrieval, the patent of China has been CN107451695A a mine carbon monoxide sensor non-blind area optimization arrangement method, this patent has proposed a CO sensor non-blind area arrangement method taking into account carbon monoxide high risk point and monitoring coverage to the defect of the existing monitoring means, establish the comprehensive optimization arrangement model with the help of graph theory and set coverage theory, in order to adopt the heuristic optimization algorithm to solve, have defined objective function and constraint condition; the sensor layout position in the patent is in a roadway of a mine, and is different from the research object of the invention, and meanwhile, the monitoring effect of the sensor is not considered in the patent; in addition, the calculation result of the ant colony algorithm in the patent is not unique, so the scheme obtained by the patent is not necessarily the optimal scheme.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides the monitoring point arrangement method for underground space gas explosion risk prevention and control, which can quickly and accurately obtain the optimal monitoring point arrangement scheme, obtain the total explosion risk of the underground space adjacent to the control target pipeline to the maximum extent at lower cost, so as to find the gas pipeline leakage condition in time, avoid secondary disasters caused by gas leakage and play an important role in ensuring the safe operation of urban gas.
In order to achieve the purpose, the invention adopts the following technical scheme that:
a monitoring point arrangement method for underground space gas explosion risk prevention and control comprises the following steps:
s41, N adjacent lower spaces are included in the peripheral region omega of the target pipe section B, and the N adjacent lower spaces in the peripheral region omega form a set Lay; presetting that sensors are arranged in the N adjacent lower spaces;
s42, performing first elimination on the set Lay: selecting one adjacent underground space from the N adjacent underground spaces in which the sensors are installed, and removing the sensor in the selected one adjacent underground space;
the first-culled set Lay, i.e., the first-culled peripheral region Ω includes: n-1 adjacent underground spaces with sensors and one adjacent underground space without sensors;
after the set Lay is removed for the first time, calculating the SIRD of the monitoring points arranged after the first removal 1 Calculating the risk control rate R of the system after the first elimination 1 * ；
S43, according to the mode of the step S42, sequentially carrying out k-time elimination on the set Lay after the k-1-time elimination: selecting one adjacent underground space from the N-k +1 adjacent underground spaces in which the sensors are installed, and removing the sensor in the selected one adjacent underground space;
the k-th culled set Lay comprises: n-k adjacent subterranean spaces having sensors mounted thereon, and k adjacent subterranean spaces having no sensors mounted thereon;
after the k-th elimination is carried out on the set Lay, the investment reasonableness SIRD distributed by the monitoring points after the k-th elimination is calculated k Calculating the risk control rate R of the system after the first elimination k * ；
S44, taking the residual distribution points as the abscissa, wherein the residual distribution points refer to; after a certain rejection, the number of adjacent underground spaces of the left non-removed sensors in the set Lay; respectively taking the investment reasonableness of the monitoring point layout after the elimination and the system risk control rate after the elimination as vertical coordinates, and normalizing the two vertical coordinates; fitting and drawing two relation curves, which are respectively: investment reasonableness SIRD arranged between certain elimination and monitoring point after the elimination k Relationship curve between the two, the system risk control rate R after a certain rejection and the rejection k * The relationship between them;
s45, the number of the remaining points corresponding to the intersection points of the two curves is m, the sensors are installed in m adjacent underground spaces of the left sensors which are not removed in the set Lay after the N-m times of rejection, and the optimal strategy of the arrangement by taking the sensors which are not installed in the adjacent underground spaces of the N-m removed sensors as monitoring points is adopted.
In steps S42-S43, calculating the investment rationality SIRD distributed by the monitoring points after the k-th elimination k ：
Figure BDA0002314111480000041
Wherein R' represents a total system risk value for the target pipe segment B when no sensors are installed in all N adjacent lower spaces of the peripheral region Ω; r k Representing the total system risk value of the target pipe section B when the sensors are installed in N-k adjacent lower spaces of the peripheral region omega after the kth elimination; e k And the total investment of safety engineering required for installing the sensors in the total N-k adjacent lower spaces in the peripheral region omega after the k-th elimination is shown.
In steps S42-S43, calculating the system risk control rate R after the k-th elimination k * ：
Figure BDA0002314111480000042
Wherein R' represents a total system risk value for the target pipe segment B when no sensors are installed in all N adjacent lower spaces of the peripheral region Ω; r k And (4) when the sensors are arranged in N-k adjacent lower spaces of the peripheral region omega after the kth rejection, the total system risk value of the target pipe section B is shown.
In steps S42-S43, selecting one adjacent underground space from a plurality of adjacent underground spaces with sensors installed, and removing the sensor in the selected adjacent underground space; the adjacent underground space is selected in the following mode:
and sequentially removing the sensors in the adjacent underground spaces with the sensors, respectively calculating the total system risk value of the target pipe section B with the sensors in each adjacent underground space removed, finding out the minimum value of the total system risk value, selecting one adjacent underground space of the removed sensor corresponding to the minimum system risk value, and removing the sensor in the selected adjacent underground space.
When one adjacent underground space is selected from a plurality of adjacent underground spaces provided with sensors, if two or more same minimum system risk total values exist, the two or more adjacent underground spaces of the removed sensors corresponding to the minimum system risk total values are respectively selected, and the sensors in the two or more selected adjacent underground spaces are respectively removed, namely two or more parallel removal schemes are generated, and two or more parallel optimal strategies are correspondingly generated.
The calculation mode of the total system risk value of the target pipe section B comprises the following steps:
s1, dispersing a target pipe section B, dispersing the target pipe section B into L infinitesimal pipe sections, establishing a risk evaluation model of a single infinitesimal pipe section on a single adjacent underground space A, and calculating the risk contribution degree R (A, L) of the first infinitesimal pipe section on the single adjacent underground space A:
R(A,l)＝P L (l)·P D (A,l)·P I (A)·C(A)；
wherein A represents an adjacent subterranean space; l denotes the L-th microcell segment, L =1,2, … L; r represents a risk contribution degree; p L A probability representative value representing gas leakage; p D A probability characterizing value representing diffusion after leakage; p is I A probability-characterizing value representing an ignition; c represents the influence degree of the accident;
r (A, l) represents the risk contribution of the l-th infinitesimal pipe section to a single adjacent subsurface space A;
P L (l) Representing the probability characteristic value of leakage of the ith infinitesimal pipe section;
P D (A, l) represents the probability characteristic value of diffusion to a single adjacent underground space A after the leakage of the ith infinitesimal pipe section;
P I (A) A probability representative value representing a single adjacent subsurface space A firing;
c (A) represents the influence degree of the consequence of the accident of the single adjacent underground space A
S2, N adjacent lower spaces A exist in a peripheral region omega of the target pipe section B; establishing a risk evaluation model of a single infinitesimal pipe section to the peripheral region omega, and calculating the risk contribution degree R (omega, l) of the ith infinitesimal pipe section to the peripheral region omega, wherein the method comprises the following specific steps:
s21, in the N adjacent underground spaces of the peripheral region omega, x adjacent underground spaces are provided with sensors, and the x adjacent underground spaces provided with the sensors are called as one type of adjacent underground spaces; the other N-x adjacent underground spaces are not provided with the sensors, and the N-x adjacent underground spaces without the sensors are called two types of adjacent underground spaces;
whereby x class-adjacent underground spaces form a class I set T ，
Figure BDA0002314111480000051
Wherein the superscript T represents a type of adjacent subterranean space; />
Figure BDA0002314111480000052
Representing an ith class of adjacent subterranean spaces;
forming a class II set I by the N-x class II adjacent underground spaces F ，
Figure BDA0002314111480000053
Wherein superscript F represents two classes of adjacent subterranean spaces; />
Figure BDA0002314111480000054
Representing the jth adjacent underground space of the second type;
the sensor is used for detecting the gas leakage, the correct detection coefficient of the sensor is alpha, and the value range of the alpha is 0-1;
s22, the gas leaked from the first micro-element pipe section is not filled in an adjacent underground space
Figure BDA0002314111480000061
Probability detected by an internal sensor>
Figure BDA0002314111480000062
Comprises the following steps:
Figure BDA0002314111480000063
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0002314111480000064
means that the gas leaked from the ith micro-element pipe section is not treated by a type of adjacent underground space->
Figure BDA0002314111480000065
Probability of sensor detection within; />
Figure BDA0002314111480000066
Means that the l-th section of the infinitesimal pipe diffuses into an adjacent underground space->
Figure BDA0002314111480000067
A probability characterizing value of (a);
s23, the first micro-element pipe section causes two types of adjacent underground spaces when gas leakage occurs
Figure BDA0002314111480000068
I.e. the risk contribution of the adjacent underground space, in which no sensor is installed, to the surrounding area omega>
Figure BDA0002314111480000069
Comprises the following steps:
Figure BDA00023141114800000610
wherein the content of the first and second substances,
Figure BDA00023141114800000611
means for two adjacent underground spaces->
Figure BDA00023141114800000612
Risk contribution to the peripheral region Ω; />
Figure BDA00023141114800000613
Means that the l-th microcell section is corresponding to two adjacent underground spaces>
Figure BDA00023141114800000614
The risk contribution of (c); pi represents the sign of the quadrature,
Figure BDA00023141114800000615
Figure BDA00023141114800000616
means that the gas leaked from the l-th section of the micro-element tube is not treated by a type of adjacent underground space->
Figure BDA00023141114800000617
Probability of sensor detection within;
s24, leading to a type of adjacent underground space when the first micro-element pipe section generates gas leakage
Figure BDA00023141114800000618
I.e. the risk contribution of the adjacent underground space in which the sensor is installed to the surrounding area Ω>
Figure BDA00023141114800000619
Comprises the following steps:
Figure BDA00023141114800000620
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA00023141114800000621
represents a type of adjacent underground space->
Figure BDA00023141114800000622
Risk contribution to the peripheral region Ω; />
Figure BDA00023141114800000623
Means that the ith micro-element pipe section is paired with a type of adjacent underground space->
Figure BDA00023141114800000624
The risk contribution of (c); pi represents the sign of the quadrature,
Figure BDA00023141114800000625
Figure BDA00023141114800000626
means that the gas leaked from the ith micro-element pipe section is not treated by a type of adjacent underground space->
Figure BDA00023141114800000627
Probability of sensor detection within; alpha represents a detection correct coefficient of the sensor;
s25, the risk contribution degree R (omega, l) of the first micro-element pipe section to the peripheral area omega when gas leakage occurs is as follows:
Figure BDA00023141114800000628
s3, establishing a risk evaluation model of the target pipe section B to the peripheral region omega, and calculating the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega, wherein the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega is the total system risk value R of the target pipe section B;
summing the risk contribution degrees R (omega, l) of the single infinitesimal pipe section to the peripheral region omega in the step S2 to obtain the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega, so as to obtain a total system risk value R of the target pipe section B:
Figure BDA0002314111480000071
the invention also provides a method for calculating the total system risk value of the target pipe section, which comprises the following steps:
s1, dispersing a target pipe section B, dispersing the target pipe section B into L infinitesimal pipe sections, establishing a risk evaluation model of a single infinitesimal pipe section to a single adjacent underground space A, and calculating the risk contribution degree R (A, L) of the first infinitesimal pipe section to the single adjacent underground space A;
wherein A represents an adjacent subterranean space; l denotes the L-th infinitesimal tube section, L =1,2, … L; r represents a risk contribution degree;
s2, N adjacent lower spaces A exist in a peripheral region omega of the target pipe section B; establishing a risk evaluation model of a single infinitesimal pipe section to the peripheral region omega, and calculating the risk contribution degree R (omega, l) of the ith infinitesimal pipe section to the peripheral region omega;
and S3, establishing a risk evaluation model of the target pipe section B to the peripheral region omega, and calculating the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega, wherein the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega is the total system risk value R of the target pipe section B.
In step S1, the risk contribution R (a, l) of the ith infinitesimal pipe segment to a single adjacent subsurface space a:
R(A,l)＝P L (l)·P D (A,l)·P I (A)·C(A)；
wherein A represents an adjacent subterranean space; l denotes the L-th infinitesimal tube section, L =1,2, … L; r represents a risk contribution degree; p is L A probability representative value representing gas leakage; p D A probability characterizing value representing diffusion after leakage; p I A probability-characterizing value representing an ignition; c represents the influence degree of the consequences of an accident;
r (A, l) represents the risk contribution of the l-th infinitesimal pipe section to a single adjacent subsurface space A;
P L (l) Representing the probability characterization value of the leakage of the ith infinitesimal pipe section;
P D (A, l) represents a probability characteristic value of diffusion to a single adjacent underground space A after the leakage of the l-th micro-element pipe section;
P I (A) A probability-representative value representing a single adjacent subsurface space A firing;
c (a) represents the degree of impact of the outcome of an accident occurring in a single adjacent underground space a.
In step S2, calculating a risk contribution degree R (Ω, l) of the ith infinitesimal pipe segment to the peripheral region Ω includes the following steps:
s21, in the N adjacent lower spaces of the peripheral region omega, x adjacent lower spaces are provided with sensors, and the x adjacent lower spaces provided with the sensors are called adjacent underground spaces; the other N-x adjacent underground spaces are not provided with sensors, and the N-x adjacent underground spaces without the sensors are called as second-type adjacent underground spaces;
whereby x class-adjacent underground spaces form a class I set T ，
Figure BDA0002314111480000081
Wherein the superscript T represents a type of adjacent subterranean space; />
Figure BDA0002314111480000082
Representing an ith class of adjacent subterranean spaces;
forming a class II set I by N-x class II adjacent underground spaces F ，
Figure BDA0002314111480000083
Wherein superscript F represents two classes of adjacent subterranean spaces; />
Figure BDA0002314111480000084
Representing the jth adjacent underground space of the second type;
the sensor is used for detecting gas leakage, and the correct detection coefficient of the sensor is alpha;
s22, the gas leaked by the first micro element pipe section is not leaked by one type of adjacent underground space
Figure BDA0002314111480000085
Probability detected by an internal sensor->
Figure BDA0002314111480000086
Comprises the following steps:
Figure BDA0002314111480000087
wherein the content of the first and second substances,
Figure BDA0002314111480000088
means that the l-th section of infinitesimal pipes diffuses into an adjacent type of underground space after leaking>
Figure BDA0002314111480000089
The probability characterization value of (2);
s23, the first micro-element pipe section causes two types of adjacent underground spaces when gas leakage occurs
Figure BDA00023141114800000810
I.e. the risk contribution of the adjacent underground space, in which no sensor is installed, to the surrounding area omega>
Figure BDA00023141114800000811
Comprises the following steps:
Figure BDA00023141114800000812
wherein the content of the first and second substances,
Figure BDA00023141114800000813
means that the l-th microcell section is corresponding to two adjacent underground spaces>
Figure BDA00023141114800000814
The risk contribution of (c); pi represents an integrating symbol and->
Figure BDA00023141114800000815
Figure BDA00023141114800000816
Means that the gas leaked from the ith micro-element pipe section is not treated by a type of adjacent underground space->
Figure BDA00023141114800000817
Probability of sensor detection within;
s24, when gas leakage occurs in the first micro element pipe section, a type of adjacent underground space is caused
Figure BDA00023141114800000818
I.e. the risk contribution of the adjacent underground space in which the sensor is installed to the surrounding area omega>
Figure BDA00023141114800000819
Comprises the following steps:
Figure BDA00023141114800000820
wherein the content of the first and second substances,
Figure BDA00023141114800000821
represents the l-th section of a microcell section in combination with a type of adjacent underground space>
Figure BDA00023141114800000822
The risk contribution of (c); pi denotes a sign of multiplication, and>
Figure BDA0002314111480000091
Figure BDA0002314111480000092
means that the gas leaked from the ith micro-element pipe section is not treated by a type of adjacent underground space->
Figure BDA0002314111480000093
Probability of sensor detection within; alpha represents the correct detection coefficient of the sensor, and the value range of alpha is 0-1;
s25, the risk contribution degree R (omega, l) of the first micro-element pipe section to the peripheral area omega when gas leakage occurs is as follows:
Figure BDA0002314111480000094
in step S3, summing the risk contribution degrees R (Ω, l) of the single infinitesimal pipe segment in step S2 to the peripheral region Ω, so as to obtain the risk contribution degree R (Ω, B) of the target pipe segment B to the peripheral region Ω, thereby obtaining the total system risk value R of the target pipe segment B:
Figure BDA0002314111480000095
the invention has the advantages that:
(1) The invention constructs an effective monitoring point arrangement strategy by combining a total risk value of a system, investment reasonableness of arrangement of monitoring points and a risk control rate of the system, can optimize to a maximum benefit value, is beneficial to saving capital investment and obtaining maximum detection efficiency so as to find the leakage condition of the gas pipeline in time, avoid secondary disasters caused by gas leakage and play an important role in ensuring safe operation of urban gas.
(2) On the basis of a traditional risk calculation method, the invention creatively introduces the sensor prediction effect into the explosion risk calculation of adjacent underground spaces, and calculates the total risk value of the system by taking all the adjacent underground spaces in the gas pipeline leakage influence range as a whole.
Drawings
Fig. 1 is a flow chart of a method for preventing and controlling the gas explosion risk of an underground space.
FIG. 2 is a flowchart of a method for monitoring point placement according to the present invention.
FIG. 3 is a graph of two relationships plotted according to the present embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a method for preventing and controlling gas explosion risks in an underground space comprises the following steps:
s1, establishing a risk assessment model of a single infinitesimal pipe section to a single adjacent underground space A.
Because the position from any point on the pipe section to the adjacent underground space is different and the probability of gas diffusion to the adjacent underground space A is also different, when the risk of explosion of a single adjacent underground space A caused by leakage of a certain pipe section is calculated, analysis should be carried out from each point on the pipe section, therefore, the pipe section, namely a target pipe section B needs to be discretized, the target pipe section B is discretized into L infinitesimal pipe sections, the distance between each infinitesimal pipe section and the single adjacent underground space A is respectively calculated, and the probability characteristic value P of diffusion of each infinitesimal pipe section to the single adjacent underground space A after leakage is obtained D And thus the risk contribution degree R of each micro element pipe section to the single adjacent underground space A is obtained.
The risk contribution R (a, l) of the ith infinitesimal pipe segment to a single adjacent subsurface space a is:
R(A,l)＝P L (l)·P D (A,l)·P I (A)·C(A)；
wherein A represents an adjacent subterranean space; l denotes the L-th infinitesimal tube section, L =1,2, … L; r represents a risk contribution degree; p L A probability representative value representing gas leakage; p D A probability-characterizing value representing diffusion after leakage; p I A probability-characterizing value representing an ignition; c represents the influence degree of the accident;
r (A, l) represents the risk contribution of the l-th infinitesimal pipe section to a single adjacent subsurface space A;
P L (l) Represents the l-th infinitesimalA probability characteristic value of leakage of the pipe section;
P D (A, l) represents a probability characteristic value of diffusion to a single adjacent underground space A after the leakage of the l-th micro-element pipe section;
P I (A) A probability representative value representing a single adjacent subsurface space A firing;
c (A) represents the influence degree of the consequences of an accident in a single adjacent underground space A;
in the present invention, P L (l)、P I (A) The value of C (A) can be selected according to actual conditions or relevant documents, namely the value can be obtained by the prior art;
P D the values of (A, l) are related to the distance from a leakage point, namely the l-th micro-element pipe section to a single adjacent underground space A, and in combination with the relevant research results of the German Water gas institute (DVGW), the following relation exists between the possibility that gas leakage can be detected in the underground space corresponding to one inspection well and the distance between the gas leakage and the leakage point:
Figure BDA0002314111480000111
wherein d is the distance from the inspection well to the center point of the infinitesimal element, d max The maximum distance that the combustible gas can diffuse under the representation covering medium is 10 to 15 min The general diffusion distance of combustible gas leakage is represented, and the value range is 2-3; p d And the monitoring probability of the gas leakage at the center point of the infinitesimal element can be monitored for the position of the inspection well.
And S2, establishing a risk evaluation model of the single infinitesimal pipe section to the peripheral region omega.
Since there may be a plurality of adjacent underground spaces a in the peripheral region Ω of one micro-element pipe section, i.e., a leakage of one micro-element pipe section may cause explosion of the plurality of adjacent underground spaces a.
Assuming that N adjacent underground spaces exist in the peripheral region Ω of the l-th micro-element pipe section, and among the N adjacent underground spaces, x adjacent underground spaces in which sensors are installed exist, and each of the x adjacent underground spaces in which a sensor is installed is referred to as a type of adjacent underground space; the other N-x adjacent underground spaces are not provided with sensors, and the N-x adjacent underground spaces without the sensors are called two types of adjacent underground spaces.
Whereby x class-adjacent underground spaces form a class I set T ，
Figure BDA0002314111480000112
Wherein the superscript T represents a type of adjacent subterranean space; />
Figure BDA0002314111480000113
Representing the ith class of adjacent subterranean spaces.
Forming a class II set I by the N-x class II adjacent underground spaces F ，
Figure BDA0002314111480000114
Wherein superscript F represents two classes of adjacent subterranean spaces; />
Figure BDA0002314111480000115
Representing the jth two-class adjacent subterranean space.
The sensor is used for detecting the gas leakage, the correct detection coefficient of the sensor is alpha, and the value range of the alpha is 0-1.
The gas leaked from the first micro-element pipe section is not contained in a type of adjacent underground space
Figure BDA0002314111480000116
Probability detected by an internal sensor->
Figure BDA0002314111480000117
Comprises the following steps:
Figure BDA0002314111480000118
wherein the content of the first and second substances,
Figure BDA0002314111480000119
represents the ith infinitesimal tube segmentDiffused to a type of adjacent underground space after leakage>
Figure BDA00023141114800001110
The probability of (c) characterizes the value.
The first micro-element pipe section causes two types of adjacent underground spaces when gas leakage occurs
Figure BDA0002314111480000121
I.e. the risk contribution of the adjacent underground space, in which no sensor is installed, to the surrounding area omega>
Figure BDA0002314111480000122
Comprises the following steps:
Figure BDA0002314111480000123
wherein the content of the first and second substances,
Figure BDA0002314111480000124
means that the l-th microcell section is corresponding to two adjacent underground spaces>
Figure BDA0002314111480000125
The risk contribution of (c); pi denotes a sign of multiplication, and>
Figure BDA0002314111480000126
Figure BDA0002314111480000127
means that the gas leaked from the ith micro-element pipe section is not treated by a type of adjacent underground space->
Figure BDA0002314111480000128
The probability of detection by the sensor.
The first micro-element pipe section causes a type of adjacent underground space when gas leakage occurs
Figure BDA0002314111480000129
I.e. adjacent underground spaces in which sensors are installedThe risk contribution to the peripheral region Ω ->
Figure BDA00023141114800001210
Comprises the following steps:
Figure BDA00023141114800001211
wherein the content of the first and second substances,
Figure BDA00023141114800001212
means that the ith micro-element pipe section is paired with a type of adjacent underground space->
Figure BDA00023141114800001213
The risk contribution of (c); pi represents a symbol of summation, and>
Figure BDA00023141114800001214
Figure BDA00023141114800001215
means that the gas leaked from the ith micro-element pipe section is not treated by a type of adjacent underground space->
Figure BDA00023141114800001216
Probability of detection by the sensor within; α represents a detection accuracy coefficient of the sensor.
The risk contribution degree R (Ω, l) to the peripheral region Ω when the gas leakage occurs in the ith infinitesimal pipe segment is:
Figure BDA00023141114800001217
by analogy, the risk contribution degree R (Ω, L) to the peripheral region Ω when the gas leakage occurs in each infinitesimal pipe section, L =1,2, … L, is obtained respectively.
And S3, calculating a system risk total value R of the target pipe section B, namely calculating a risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega.
Summing the risk contribution degrees R (omega, l) of the discrete single infinitesimal pipe section in the step S2 to the peripheral region omega to obtain a total system risk value R of the target pipe section B:
Figure BDA00023141114800001218
and S4, establishing an optimization strategy for monitoring point arrangement, namely establishing an optimization strategy for sensor arrangement, aiming at the target pipe section B, and acquiring an optimal monitoring point arrangement strategy.
As shown in fig. 2, the method for monitoring point deployment includes the following steps:
s41, the peripheral region omega of the target pipe section B comprises N adjacent lower spaces in total, the N adjacent lower spaces in the peripheral region Ω constitute a set Lay, lay = { a 1 ,A 2 ，…A N }; it is preset that the N adjacent lower spaces are all provided with sensors.
S42, removing the set Lay for the first time: one adjacent underground space is selected from the N adjacent underground spaces each having the sensor mounted thereon, and the sensor in the selected one adjacent underground space is removed.
The first-culled set Lay, i.e., the first-culled peripheral region Ω includes: n-1 adjacent subterranean spaces with sensors installed, and one adjacent subterranean space without sensors installed.
After the set Lay is removed for the first time, calculating the SIRD of the monitoring points arranged after the first removal 1 Calculating the risk control rate R of the system after the first elimination 1 * 。
S43, according to the mode of the step S42, sequentially carrying out k-time elimination on the set Lay after the k-1-time elimination: one adjacent underground space is selected from the N-k +1 adjacent underground spaces in which the sensors are installed, and the sensor in the selected one adjacent underground space is removed.
The k-th culled set Lay comprises: n-k adjacent subterranean spaces with sensors installed, and k adjacent subterranean spaces without sensors installed.
After the k-th elimination is carried out on the set Lay, the investment reasonableness SIRD distributed by the monitoring points after the k-th elimination is calculated k Calculating the risk control rate R of the system after the first elimination k * 。
S44, taking the residual distribution points as the abscissa, wherein the residual distribution points refer to; after a certain number of culling, the number of adjacent underground spaces left in the set Lay without the sensors removed; respectively taking the investment reasonableness of the monitoring point layout after the elimination and the system risk control rate after the elimination as vertical coordinates, and normalizing the two vertical coordinates to make the values of the two coordinate tables consistent; fitting and drawing two relation curves, which are respectively: investment reasonableness SIRD arranged between certain elimination and monitoring point after the elimination k Relationship curve between the two, the system risk control rate R after a certain rejection and the rejection k * The relationship between them.
S45, the number of the remaining distribution points corresponding to the intersection points of the two curves is m, m adjacent underground spaces of the sensors which are not removed and are left in the set Lay after the N-m times of rejection are provided with the sensors, and the optimal strategy for distributing the sensors which are not provided with the sensors in the adjacent underground spaces of the N-m removed sensors and are not provided with the sensors as monitoring points is adopted.
As shown in fig. 3, in this embodiment, a pipe segment with a length of 365 meters in a certain university in the background is taken as a target pipe segment B, a peripheral region Ω of the target pipe segment B includes 121 neighboring spaces in common, and according to the above method, two relation curves are finally fitted and drawn as shown in fig. 3, an intersection point of the two curves is 11, that is, the number of remaining distribution points is 11, and the corresponding rejection number is 110, so that, for the target pipe segment B in this embodiment, the optimal strategy for the distribution of monitoring points is as follows: after 110 times of culling, the sensors are selected to be installed in the remaining 11 adjacent lower spaces without the sensors being removed, and the sensors are selected not to be installed in the 110 adjacent lower spaces with the sensors being removed.
In the steps S42 to S43, the investment reasonableness SIRD distributed by the monitoring points after the k-th elimination is calculated k ：
Figure BDA0002314111480000141
Wherein R' represents a total system risk value for the target pipe segment B when no sensors are installed in all N adjacent lower spaces of the peripheral region Ω; r k The total system risk value of the target pipe section B is shown when sensors are installed in N-k adjacent lower spaces of the peripheral region omega after the kth elimination; e k And the total investment of safety engineering required for installing the sensors in the total N-k adjacent lower spaces in the peripheral region omega after the k-th elimination is shown.
In steps S42-S43, calculating the system risk control rate R after the k-th elimination k * ：
Figure BDA0002314111480000142
Wherein, R' represents a total system risk value of the target pipe segment B when no sensor is installed in all N adjacent subsurface spaces of the peripheral region Ω; r k And (4) when the sensors are installed in N-k adjacent lower spaces of the peripheral region omega after the kth elimination, the total system risk value of the target pipe section B is shown.
In steps S42 to S43, in the case of elimination: selecting one adjacent underground space from the plurality of adjacent underground spaces in which the sensors are installed, and removing the sensor in the selected one adjacent underground space; the adjacent underground space is selected in the following mode:
and sequentially removing the sensors in the adjacent underground spaces with the sensors, respectively calculating the total system risk value after the sensors in each adjacent underground space are removed, finding out the minimum value of the total system risk value, selecting one adjacent underground space of the removed sensor corresponding to the minimum system risk value, and removing the sensor in the selected adjacent underground space.
In steps S42 to S43, when one adjacent underground space is selected from the plurality of adjacent underground spaces each having the sensor installed therein, if two or more same minimum total system risk values exist, the two or more adjacent underground spaces of the removed sensor corresponding to the minimum total system risk values are respectively selected, and the sensors in the two or more selected adjacent underground spaces are respectively removed, that is, two or more parallel removal schemes are generated, and correspondingly, two or more parallel optimal layout strategies are also generated, similar to different branches of a tree diagram. And the decision maker evaluates the parallel optimal layout strategies to determine the final optimal layout strategy.
The invention is not to be considered as limited to the specific embodiments shown and described, but is to be understood to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.

Claims (7)

1. A monitoring point arrangement method for underground space gas explosion risk prevention and control is characterized by comprising the following steps:
s41, N adjacent lower spaces are included in the peripheral region omega of the target pipe section B, and the N adjacent lower spaces in the peripheral region omega form a set Lay; presetting that sensors are arranged in the N adjacent lower spaces;
s42, removing the set Lay for the first time: selecting one adjacent underground space from the N adjacent underground spaces in which the sensors are installed, and removing the sensor in the selected one adjacent underground space;
the first-culled set Lay, i.e., the first-culled peripheral region Ω includes: n-1 adjacent underground spaces with sensors and one adjacent underground space without sensors;
after the set Lay is removed for the first time, calculating the SIRD of the monitoring points arranged after the first removal 1 Calculating the risk control rate R of the system after the first elimination 1 * ；
S43, according to the mode of the step S42, sequentially carrying out k-time elimination on the set Lay after the k-1-time elimination: selecting one adjacent underground space from the N-k +1 adjacent underground spaces in which the sensors are installed, and removing the sensor in the selected one adjacent underground space;
the k-th eliminated set Lay comprises: n-k adjacent subterranean spaces with sensors installed, and k adjacent subterranean spaces without sensors installed;
after the k-th elimination is carried out on the set Lay, the investment reasonableness SIRD distributed by the monitoring points after the k-th elimination is calculated k Calculating the risk control rate R of the system after the first elimination k * ；
S44, taking the residual distribution points as the abscissa, wherein the residual distribution points refer to; after a certain number of culling, the number of adjacent underground spaces left in the set Lay without the sensors removed; respectively taking the investment reasonableness of the monitoring point layout after the elimination and the system risk control rate after the elimination as vertical coordinates, and normalizing the two vertical coordinates; fitting and drawing two relation curves, which are respectively: investment reasonableness SIRD arranged between certain elimination and monitoring point after the elimination k Relationship curve between, the system risk control rate R after a certain rejection and the rejection k * The relationship between them;
s45, the number of the remaining points corresponding to the intersection points of the two curves is m, the sensors are installed in m adjacent underground spaces of the left sensors which are not removed in the set Lay after the N-m times of rejection, and the optimal strategy of the arrangement by taking the sensors which are not installed in the adjacent underground spaces of the N-m removed sensors as monitoring points is adopted.
2. The method for laying monitoring points for underground space gas explosion risk prevention and control according to claim 1, wherein in the steps S42 to S43, the investment reasonableness SIRD of monitoring point laying after the k-th elimination is calculated k ：
Figure FDA0004011698390000021
Wherein, R' represents a total system risk value of the target pipe segment B when no sensor is installed in all N adjacent subsurface spaces of the peripheral region Ω; r is k Representing the total system risk value of the target pipe section B when the sensors are installed in N-k adjacent lower spaces of the peripheral region omega after the kth elimination; e k And the total investment of safety engineering required for installing the sensors in the total N-k adjacent lower spaces in the peripheral region omega after the k-th elimination is shown.
3. The method for arranging monitoring points for underground space gas explosion risk prevention and control according to claim 1, wherein in steps S42-S43, the system risk control rate R after the k-th elimination is calculated k * ：
Figure FDA0004011698390000022
Wherein R' represents a total system risk value for the target pipe segment B when no sensors are installed in all N adjacent lower spaces of the peripheral region Ω; r k And (4) when the sensors are arranged in N-k adjacent lower spaces of the peripheral region omega after the kth rejection, the total system risk value of the target pipe section B is shown.
4. The method for arranging monitoring points facing underground space gas explosion risk prevention and control according to claim 1, wherein in steps S42 to S43, one adjacent underground space is selected from a plurality of adjacent underground spaces each provided with a sensor, and the sensor in the selected adjacent underground space is removed; the adjacent underground space is selected in the following mode:
and sequentially removing the sensors in the adjacent underground spaces with the sensors, respectively calculating the total system risk value of the target pipe section B with the sensors in the adjacent underground spaces removed, finding out the minimum value of the total system risk value, selecting one adjacent underground space with the removed sensor corresponding to the minimum total system risk value, and removing the sensor in the selected adjacent underground space.
5. The method as claimed in claim 4, wherein when selecting one adjacent underground space from the plurality of adjacent underground spaces each having a sensor, if there are two or more same minimum total system risk values, the two or more adjacent underground spaces having the removed sensor corresponding to the minimum total system risk value are selected, and the sensors in the two or more selected adjacent underground spaces are removed, i.e. two or more parallel removal schemes are generated, and two or more parallel optimal strategies are correspondingly generated.
6. The method for laying monitoring points facing underground space gas explosion risk prevention and control according to claim 2, 3 or 4, wherein the calculation mode of the total system risk value of the target pipe section B comprises the following steps:
s1, dispersing a target pipe section B, dispersing the target pipe section B into L infinitesimal pipe sections, establishing a risk evaluation model of a single infinitesimal pipe section to a single adjacent underground space A, and calculating the risk contribution degree R (A, L) of the first infinitesimal pipe section to the single adjacent underground space A:
R(A,l)＝P L (l)·P D (A,l)·P I (A)·C(A)；
wherein A represents an adjacent subterranean space; l denotes the L-th infinitesimal tube section, L =1,2, … L; r represents a risk contribution degree; p L A probability representative value representing gas leakage; p D A probability-characterizing value representing diffusion after leakage; p I A probability-characterizing value representing an ignition; c represents the influence degree of the accident;
r (A, l) represents the risk contribution of the l-th infinitesimal pipe section to a single adjacent subsurface space A;
P L (l) Representing the probability characteristic value of leakage of the ith infinitesimal pipe section;
P D (A,l) Representing the probability characteristic value of diffusion to a single adjacent underground space A after the leakage of the ith infinitesimal pipe section;
P I (A) A probability-representative value representing a single adjacent subsurface space A firing;
c (A) represents the effect degree of the accident of a single adjacent underground space A
S2, N adjacent lower spaces A exist in a peripheral region omega of the target pipe section B; establishing a risk evaluation model of a single infinitesimal pipe section to the peripheral region omega, and calculating the risk contribution degree R (omega, l) of the ith infinitesimal pipe section to the peripheral region omega, wherein the method comprises the following specific steps:
s21, in the N adjacent lower spaces of the peripheral region omega, x adjacent lower spaces are provided with sensors, and the x adjacent lower spaces provided with the sensors are called adjacent underground spaces; the other N-x adjacent underground spaces are not provided with sensors, and the N-x adjacent underground spaces without the sensors are called as second-type adjacent underground spaces;
whereby x class-adjacent underground spaces form a class I set T ，
Figure FDA0004011698390000041
Wherein the superscript T represents a type of adjacent subterranean space;
Figure FDA0004011698390000042
representing an ith class of adjacent subterranean spaces;
forming a class II set I by the N-x class II adjacent underground spaces F ，
Figure FDA0004011698390000043
Wherein superscript F represents two classes of adjacent subterranean spaces;
Figure FDA0004011698390000044
representing the jth adjacent underground space of the second type;
the sensor is used for detecting the gas leakage, the correct detection coefficient of the sensor is alpha, and the value range of the alpha is 0-1;
s22, the gas leaked from the first micro-element pipe section is not filled in an adjacent underground space
Figure FDA0004011698390000045
Probability of sensor detection in
Figure FDA0004011698390000046
Comprises the following steps:
Figure FDA0004011698390000047
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0004011698390000048
the gas indicating the leakage of the first micro-element pipe section is not filled by a type of adjacent underground space
Figure FDA00040116983900000431
Probability of sensor detection within;
Figure FDA0004011698390000049
indicating that the first infinitesimal pipe segment diffuses into a type of adjacent underground space after leaking
Figure FDA00040116983900000410
A probability characterizing value of (a);
s23, the first micro-element pipe section causes two types of adjacent underground spaces when gas leakage occurs
Figure FDA00040116983900000411
I.e. the risk contribution of the adjacent underground space without installed sensors to the peripheral region omega
Figure FDA00040116983900000412
Comprises the following steps:
Figure FDA00040116983900000413
wherein the content of the first and second substances,
Figure FDA00040116983900000414
representing two types of adjacent underground spaces
Figure FDA00040116983900000415
Risk contribution to the peripheral region Ω;
Figure FDA00040116983900000416
representing the first infinitesimal pipe segment to the second type of adjacent underground space
Figure FDA00040116983900000417
The risk contribution of (c); pi represents a sign of the quadrature,
Figure FDA00040116983900000418
Figure FDA00040116983900000419
the gas indicating the leakage of the first micro-element pipe section is not filled by a type of adjacent underground space
Figure FDA00040116983900000420
Probability of sensor detection within;
s24, leading to a type of adjacent underground space when the first micro-element pipe section generates gas leakage
Figure FDA00040116983900000421
I.e. the risk contribution of the adjacent underground space in which the sensor is installed to the peripheral region omega
Figure FDA00040116983900000422
Comprises the following steps:
Figure FDA00040116983900000423
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA00040116983900000424
representing a type of adjacent subterranean space
Figure FDA00040116983900000425
Risk contribution to the peripheral region Ω;
Figure FDA00040116983900000426
representing the first pair of infinitesimal pipe sections
Figure FDA00040116983900000427
The risk contribution of (c); pi represents a sign of the quadrature,
Figure FDA00040116983900000428
Figure FDA00040116983900000429
the gas indicating the leakage of the first micro-element pipe section is not filled by a type of adjacent underground space
Figure FDA00040116983900000430
Probability of sensor detection within; alpha represents a detection correct coefficient of the sensor;
s25, the risk contribution degree R (omega, l) of the first micro-element pipe section to the peripheral area omega when gas leakage occurs is as follows:
Figure FDA0004011698390000051
s3, establishing a risk evaluation model of the target pipe section B to the peripheral region omega, and calculating the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega, wherein the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega is the total system risk value R of the target pipe section B;
summing the risk contribution degrees R (omega, l) of the single infinitesimal pipe section to the peripheral region omega in the step S2 to obtain the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega, so as to obtain a total system risk value R of the target pipe section B:
Figure FDA0004011698390000052
7. the method for calculating the total system risk value of the target pipe section is characterized by comprising the following steps of:
s1, dispersing a target pipe section B, dispersing the target pipe section B into L infinitesimal pipe sections, establishing a risk evaluation model of a single infinitesimal pipe section to a single adjacent underground space A, and calculating the risk contribution degree R (A, L) of the first infinitesimal pipe section to the single adjacent underground space A;
wherein A represents an adjacent subterranean space; l denotes the L-th infinitesimal tube section, L =1,2, … L; r represents a risk contribution degree;
s2, N adjacent lower spaces A exist in a peripheral region omega of the target pipe section B; establishing a risk evaluation model of a single infinitesimal pipe section to the peripheral region omega, and calculating the risk contribution degree R (omega, l) of the ith infinitesimal pipe section to the peripheral region omega;
s3, establishing a risk evaluation model of the target pipe section B to the peripheral region omega, and calculating the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega, wherein the risk contribution degree R (omega, B) of the target pipe section B to the peripheral region omega is the total system risk value R of the target pipe section B;
in step S1, the risk contribution R (a, l) of the ith infinitesimal pipe segment to a single adjacent subsurface space a:
R(A,l)＝P L (l)·P D (A,l)·P I (A)·C(A)；
wherein A represents an adjacent subterranean space; l denotes the L-th infinitesimal tube section, L =1,2, … L; r represents a risk contribution degree; p L A probability representative value representing gas leakage; p D Summary of indicating diffusion after leakageA rate characterizing value; p I A probability-characterizing value representing an ignition; c represents the influence degree of the accident;
r (A, l) represents the risk contribution of the l-th infinitesimal pipe section to a single adjacent subsurface space A;
P L (l) Representing the probability characteristic value of leakage of the ith infinitesimal pipe section;
P D (A, l) represents a probability characteristic value of diffusion to a single adjacent underground space A after the leakage of the l-th micro-element pipe section;
P I (A) A probability representative value representing a single adjacent subsurface space A firing;
c (A) represents the influence degree of the consequences of an accident in a single adjacent underground space A;
in step S2, calculating a risk contribution degree R (Ω, l) of the ith infinitesimal pipe segment to the peripheral region Ω includes the following steps:
s21, in the N adjacent underground spaces of the peripheral region omega, x adjacent underground spaces are provided with sensors, and the x adjacent underground spaces provided with the sensors are called as one type of adjacent underground spaces; the other N-x adjacent underground spaces are not provided with sensors, and the N-x adjacent underground spaces without the sensors are called as second-type adjacent underground spaces;
whereby x class-adjacent underground spaces form a class I set T ，
Figure FDA0004011698390000061
Wherein the superscript T represents a type of adjacent subterranean space;
Figure FDA0004011698390000062
representing an ith class of adjacent subterranean spaces;
forming a class II set I by the N-x class II adjacent underground spaces F ，
Figure FDA0004011698390000063
Wherein superscript F represents two classes of adjacent subterranean spaces;
Figure FDA0004011698390000064
representing the jth adjacent underground space of the second type;
the sensor is used for detecting gas leakage, and the correct detection coefficient of the sensor is alpha;
s22, the gas leaked from the first micro-element pipe section is not filled in an adjacent underground space
Figure FDA0004011698390000065
Probability of sensor detection in
Figure FDA0004011698390000066
Comprises the following steps:
Figure FDA0004011698390000067
wherein the content of the first and second substances,
Figure FDA0004011698390000068
indicating that the first section of micro-element pipe diffuses into an adjacent underground space after leaking
Figure FDA0004011698390000069
A probability characterizing value of (a);
s23, the first micro-element pipe section causes two types of adjacent underground spaces when gas leakage occurs
Figure FDA00040116983900000610
I.e. the risk contribution of the adjacent underground space without installed sensors to the peripheral region omega
Figure FDA00040116983900000611
Comprises the following steps:
Figure FDA00040116983900000612
wherein the content of the first and second substances,
Figure FDA00040116983900000613
representing the first infinitesimal pipe segment to two adjacent underground spaces
Figure FDA00040116983900000614
The risk contribution of (c); pi represents a sign of the quadrature,
Figure FDA0004011698390000071
Figure FDA0004011698390000072
the gas indicating the leakage of the first micro-element pipe section is not filled by a type of adjacent underground space
Figure FDA0004011698390000073
Probability of sensor detection within;
s24, leading to a type of adjacent underground space when the first micro-element pipe section generates gas leakage
Figure FDA0004011698390000074
I.e. the risk contribution of the adjacent underground space in which the sensor is installed to the peripheral region omega
Figure FDA0004011698390000075
Comprises the following steps:
Figure FDA0004011698390000076
wherein the content of the first and second substances,
Figure FDA0004011698390000077
representing the first pair of infinitesimal pipe sections
Figure FDA0004011698390000078
The risk contribution of (c); pi represents a sign of the quadrature,
Figure FDA0004011698390000079
Figure FDA00040116983900000710
the gas indicating the leakage of the first micro-element pipe section is not filled by a type of adjacent underground space
Figure FDA00040116983900000711
Probability of sensor detection within; alpha represents the correct detection coefficient of the sensor, and the value range of alpha is 0-1;
s25, the risk contribution degree R (omega, l) of the first micro-element pipe section to the peripheral area omega when gas leakage occurs is as follows:
Figure FDA00040116983900000712
in step S3, summing the risk contribution degrees R (Ω, l) of the single infinitesimal pipe segment in step S2 to the peripheral region Ω, so as to obtain the risk contribution degree R (Ω, B) of the target pipe segment B to the peripheral region Ω, thereby obtaining the total system risk value R of the target pipe segment B:
Figure FDA00040116983900000713
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CN111564023B (en) * 2020-05-14 2021-09-03 清华大学合肥公共安全研究院 Method and system for setting leakage alarm threshold of buried gas pipeline
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106504312A (en) * 2016-11-04 2017-03-15 北京石油化工学院 The triple assessment method of gas buried pipe network system risk
RU2016139458A (en) * 2016-10-07 2018-04-13 Акционерное общество "Южный научно-исследовательский и проектно-конструкторский институт морского флота" The method of determining the level of environmental risk during oil spills and oil products
CN108764681A (en) * 2018-05-18 2018-11-06 北京理工大学 A kind of adjacent underground space methods of risk assessment of burning line leak and system
CN108985619A (en) * 2018-07-12 2018-12-11 清华大学合肥公共安全研究院 A kind of adjacent underground space risk of explosion appraisal procedure of burning line
CN110107815A (en) * 2018-11-08 2019-08-09 清华大学合肥公共安全研究院 The leakage detection method and device of gas pipeline

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2016139458A (en) * 2016-10-07 2018-04-13 Акционерное общество "Южный научно-исследовательский и проектно-конструкторский институт морского флота" The method of determining the level of environmental risk during oil spills and oil products
CN106504312A (en) * 2016-11-04 2017-03-15 北京石油化工学院 The triple assessment method of gas buried pipe network system risk
CN108764681A (en) * 2018-05-18 2018-11-06 北京理工大学 A kind of adjacent underground space methods of risk assessment of burning line leak and system
CN108985619A (en) * 2018-07-12 2018-12-11 清华大学合肥公共安全研究院 A kind of adjacent underground space risk of explosion appraisal procedure of burning line
CN110107815A (en) * 2018-11-08 2019-08-09 清华大学合肥公共安全研究院 The leakage detection method and device of gas pipeline

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
城市燃气管道泄漏致灾混合概率风险评估研究;王春雪等;《中国安全科学学报》;20161215(第12期);全文 *

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