CN114664056B - Method and system for distinguishing gas leakage and biogas exceeding - Google Patents
Method and system for distinguishing gas leakage and biogas exceeding Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 31
- 230000008859 change Effects 0.000 claims description 58
- 230000002093 peripheral effect Effects 0.000 claims description 55
- 238000004364 calculation method Methods 0.000 claims description 41
- 238000012937 correction Methods 0.000 claims description 19
- 238000012549 training Methods 0.000 claims description 11
- 230000007613 environmental effect Effects 0.000 claims description 9
- 230000032683 aging Effects 0.000 claims description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 8
- 239000000463 material Substances 0.000 claims description 6
- 239000005416 organic matter Substances 0.000 claims description 6
- 238000012795 verification Methods 0.000 claims description 5
- 230000004069 differentiation Effects 0.000 claims description 4
- 230000001105 regulatory effect Effects 0.000 claims description 4
- 239000000758 substrate Substances 0.000 claims 1
- 239000007789 gas Substances 0.000 description 113
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 14
- 238000012423 maintenance Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 4
- 238000005070 sampling Methods 0.000 description 4
- 239000002737 fuel gas Substances 0.000 description 3
- 239000003345 natural gas Substances 0.000 description 3
- OTMSDBZUPAUEDD-UHFFFAOYSA-N Ethane Chemical compound CC OTMSDBZUPAUEDD-UHFFFAOYSA-N 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000011269 treatment regimen Methods 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 229910001018 Cast iron Inorganic materials 0.000 description 1
- 229910000831 Steel Inorganic materials 0.000 description 1
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- 238000010586 diagram Methods 0.000 description 1
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- 239000000203 mixture Substances 0.000 description 1
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- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 239000004016 soil organic matter Substances 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/12—Alarms for ensuring the safety of persons responsive to undesired emission of substances, e.g. pollution alarms
- G08B21/16—Combustible gas alarms
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Abstract
The embodiment of the specification provides a method and a system for distinguishing gas leakage from biogas overproof, wherein the method comprises the following steps: determining a plurality of influence coefficients of the alarm points; calculating leakage factor coefficients of the alarm points according to the influence coefficients; and distinguishing whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient. The invention can improve the accuracy of distinguishing the gas leakage from the biogas exceeding standard.
Description
Technical Field
One or more embodiments of the present disclosure relate to the field of gas detection technology, and in particular, to a method and system for distinguishing between gas leakage and biogas overproof.
Background
Currently, in towns, a large number of valve wells, catch water wells and hidden spaces and airtight spaces of commercial supercomplexes exist, and in these complex environments, the problems of gas leakage risk and biogas overstock exist at the same time. At present, a fuel gas concentration alarm with a remote transmission function is generally deployed for monitoring, but the main components of fuel gas and methane are methane, and the fuel gas concentration alarm cannot distinguish the two conditions. Therefore, after the alarm is triggered, an operation and maintenance person carries a gas chromatograph to go to the site for sampling, analysis is carried out to obtain a result, and then a corresponding robbery and maintenance strategy is started. Or through regular personnel inspection, the leakage detector and personnel experience distinguish whether the gas leakage or the biogas exceeds the standard.
The gas concentration alarm is a detector for detecting the concentration of gas, the core original component of the gas concentration alarm is a gas sensor, the gas concentration alarm is installed in a place where gas leakage possibly occurs, and the detector is triggered to alarm when the concentration of gas in the air exceeds a set value. After triggering the alarm, an audible and visual alarm signal is sent to the outside, if an alarm host and an alarm receiving center are connected, the alarm can be networked, and meanwhile, exhaust equipment can be automatically started, a gas pipeline valve can be closed, and the like, so that the safety of life and property is ensured. In civil safety precaution engineering, the gas concentration alarm is used for household gas leakage alarm, and is also widely applied to various places where the leakage of the combustible gas is easy to occur, such as oil refineries, oil depots, chemical plants, liquefied gas stations and the like. The gas concentration alarm can be installed in a wall-mounted mode, the number of channels can be set according to requirements, and each channel corresponds to one detector. Through the cooperation with the detector, the central processor performs various processes on the data uploaded by the detector, and finally, the display of the data is completed.
Wherein, the gas chromatograph can be used for distinguishing natural gas and methane. The detection of the presence of ethane is an accepted method for distinguishing biogas, natural gas or other pipeline gases by DVGW. When the gas sample is detected to contain ethane, the gas can be determined to be natural gas or other combustible gas in the gas transmission pipeline, otherwise, the gas is underground methane.
The existing differentiation schemes have the following disadvantages: the gas alarm can not directly distinguish whether the gas leaks or the biogas exceeds the standard, and manual on-site sampling verification is needed; from the time when the personnel arrive at the site and the sampling is confirmed, a long time is needed, the corresponding robbery maintenance strategy cannot be started at the first time, and the occurrence of safety accidents cannot be controlled earlier; the risk of misoperation and missed detection exists in manual detection and experience judgment; there is a risk of erroneous judgment.
Disclosure of Invention
One or more embodiments of the present specification describe a method and system for distinguishing between gas leakage and biogas overproof.
In a first aspect, an embodiment of the present invention provides a method for distinguishing between gas leakage and biogas overproof, including:
Determining a plurality of influence coefficients of the alarm points; wherein the plurality of influence coefficients comprises: topology influence coefficient, equipment influence coefficient, gas change trend influence coefficient, history alarm coefficient, correlation alarm coefficient, environment influence coefficient and correction coefficient; the topology influence coefficient is an influence coefficient of peripheral equipment distribution conditions of the alarm point on the alarm point, the equipment influence coefficient is an influence coefficient of peripheral equipment aging conditions of the alarm point on the alarm point, the gas change trend influence coefficient is an influence coefficient of gas change trend of the alarm point on the alarm point, and the associated alarm coefficient is an influence coefficient of historical alarm conditions around the alarm point on the alarm point;
Calculating leakage factor coefficients of the alarm points according to the influence coefficients;
And distinguishing whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient.
In a second aspect, an embodiment of the present invention provides a system for distinguishing between gas leakage and biogas overproof, including:
A determining module for: determining a plurality of influence coefficients of the alarm points; wherein the plurality of influence coefficients comprises: topology influence coefficient, equipment influence coefficient, gas change trend influence coefficient, history alarm coefficient, correlation alarm coefficient, environment influence coefficient and correction coefficient; the topology influence coefficient is an influence coefficient of peripheral equipment distribution conditions of the alarm point on the alarm point, the equipment influence coefficient is an influence coefficient of peripheral equipment aging conditions of the alarm point on the alarm point, the gas change trend influence coefficient is an influence coefficient of gas change trend of the alarm point on the alarm point, and the associated alarm coefficient is an influence coefficient of historical alarm conditions around the alarm point on the alarm point;
A calculation module for: calculating leakage factor coefficients of the alarm points according to the influence coefficients;
A distinguishing module for: and distinguishing whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient.
According to the method and the system for distinguishing the gas leakage from the biogas overproof, provided by the embodiment of the invention, the influence coefficients of factors such as the gas change trend, the environmental factors, the topology factors, the equipment factors and the like are calculated, then the leakage factor coefficient is calculated, and finally whether the gas leakage or the biogas overproof is distinguished according to the leakage factor coefficient. The method and the device solve the problem that whether gas leakage or biogas exceeding standard is carried out in a hidden space or a closed space is solved, so that corresponding maintenance strategy can be started conveniently, risks can be controlled better in advance, and potential safety accidents are avoided. Compared with the mode of distinguishing only through gas components in the prior art, the distinguishing scheme provided by the embodiment of the invention is more accurate.
Drawings
In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present description, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow diagram of a method of distinguishing between gas leakage and biogas overproof in one embodiment of the present disclosure.
Detailed Description
The following describes the scheme provided in the present specification with reference to the drawings.
In a first aspect, the present invention provides a method for distinguishing between gas leakage and biogas overproof, see fig. 1, the method comprising the steps S1 to S3 of:
s1, determining a plurality of influence coefficients of an alarm point;
Wherein the plurality of influence coefficients comprises: topology influence coefficient, equipment influence coefficient, gas change trend influence coefficient, history alarm coefficient, correlation alarm coefficient, environment influence coefficient and correction coefficient; the topology influence coefficient is an influence coefficient of peripheral equipment distribution conditions of the alarm point on the alarm point, the equipment influence coefficient is an influence coefficient of peripheral equipment aging conditions of the alarm point on the alarm point, the gas change trend influence coefficient is an influence coefficient of gas change trend of the alarm point on the alarm point, and the associated alarm coefficient is an influence coefficient of historical alarm conditions around the alarm point on the alarm point.
It can be understood that the topology influence coefficient is the influence degree of the distribution situation of the peripheral equipment on the alarm point, and in the specific implementation, the topology influence coefficient can be calculated by a first calculation formula, where the first calculation formula includes:
T(n(g1+gn)*t1/2)
Wherein T is the topology influence coefficient, g1 is a parameter of equipment distribution condition within a preset close range, and the preset close range is smaller than a peripheral range; gn is a parameter representing the distribution of devices in a peripheral range, n is a radius of the peripheral range, the peripheral range is a range with n as a radius centered on the alarm point, and t1 is a ratio between the number of associated devices and the total number of devices in the peripheral range. Wherein n may be 5,10,15 , 50.
For example, the radius is 50 meters, the conditions of the horizontal distribution distance, the number and the like of the pipe network, the pressure regulating box and the valve well within the radius range of 50 meters centering on the alarm point are acquired, and then the parameter gn for representing the distribution condition of the equipment within the range can be calculated. t is the ratio between the number of devices associated with the alarm point in the range and the total number of devices in the range, and the parameter t represents the association ratio between the devices and the alarm point.
It can be understood that the device influence coefficient is the influence degree of the aging condition of the peripheral device on the alarm point. In a specific implementation, the device influence coefficient may be calculated by a second calculation formula, where the second calculation formula includes:
SS1+S2+S3
Sin(a1+an)/2
an1L1*(L-e*PA)/r*r
an2L2*e*Pn
an3L3*e*Pn
Wherein S is the influence coefficient of the equipment in the peripheral range, S1 is the influence coefficient of the equipment in the early stage, S2 is the influence coefficient of the equipment in the peripheral range in the middle stage, S3 is the influence coefficient of the equipment in the peripheral range in the later stage, si is the influence coefficient of the equipment in the peripheral range in the stage i, and i is 1, 2 and 3; a1 is a device state parameter within a preset close range; the preset close range is smaller than the peripheral range; n is the radius of a peripheral range, and the peripheral range is a range taking the alarm point as the center and taking n as the radius; an is equipment state parameters in a peripheral range, and an1, an2 and an3 are equipment state parameters of a gas pipe network, a valve well and a pressure regulating cabinet; l 1L2L3 is the equipment material coefficient of the gas pipe network, the valve well and the regulator cubicle respectively, e is the pipe network pressure constant, pn is the fatigue parameter of equipment, L is the distance between the pipeline of the gas pipe network and the nearest endpoint of the alarm point, PA is the pipeline pressure change rate of the gas pipe network, and r is the radius of the gas pipe network.
The device has different influences on the alarm point in different stages, so that the early stage, the middle stage and the later stage of the device are considered, and the influence on the alarm point is smaller in the middle stage and larger in the early stage and the later stage because the device is the most stable in the middle stage. Si=n (a1+an)/2 is used to calculate the influence coefficient of the corresponding stage, whether early, middle or late. It can be understood that the influence of different peripheral devices on the alarm point is different, so that an a1=l 1 (L-e PA)/r calculation is adopted for the gas pipe network; for a valve well, using an an2=l 2 epn calculation; for the regulator cubicle, an an3=l 3 epn calculation is used. The materials of the equipment are generally PE, steel and cast iron, and different types of materials have different material coefficients. For fatigue parameters Pn of the equipment, when the equipment is a pipe network delivered in nearly 3 months or an old pipe network over 15 years, pn=3.36pp, and p=equipment service life/equipment maintenance life. The pipe network pressure constant e takes different values for different radii, e.g. e1, e2, e3, en=en-1 + (1.3l1) for radii of 10 meters, 20 meters and 30 meters.
It is understood that the historical alarm coefficients are local historical alarm coefficients. In a specific implementation, the historical alert coefficient may be calculated using a third calculation formula, where the third calculation formula includes:
Cs1+1/3s2+1/7s3+1/30s4
Where C is the history alarm coefficient, s1 is the number of alarms within a range of 2 km around the alarm point within 24 hours before the alarm time of the alarm point, s2 is the number of alarms within a range of 2 km around the alarm point within 72 hours before the alarm time of the alarm point, s3 is the number of alarms within a range of 2 km around the alarm point within one week before the alarm time of the alarm point, s3 is the number of alarms within a range of 2 km around the alarm point around the periphery within one month before the alarm time of the alarm point.
In a specific implementation, the association alarm coefficient may be calculated by using a fourth calculation formula, where the fourth calculation formula includes:
Gs5+1/2s6+1/5s7
Wherein G is the associated alarm coefficient, and s5, s6 and s7 are the alarm times within a range of 50 meters, 200 meters and 500 meters with the alarm point as the center and the radius within a certain time respectively.
In specific implementation, determining the gas change trend influence coefficient of the alarm point may include:
Determining the gas change trend experience value of the alarm point;
Determining a gas change stage of the alarm point according to the empirical value, and determining a corresponding gas change trend influence coefficient according to the gas change stage;
Wherein the gas change phase comprises an early failure period, an occasional failure period and a depletion failure period; the gas change trend influence coefficient corresponding to the early failure period is-1.4Q1, the gas change trend influence coefficient corresponding to the accidental failure period is Q2, and the gas change trend influence coefficient corresponding to the wear failure period is 1.4Q3, Q1< -1.3, -1.3< Q2<1.3, and 1.3< Q3.
In practice, the gas change trend of the alarm point, that is, the empirical value of the gas change trend, can be determined empirically. And then determining the change stage of the gas component of the alarm point according to the empirical value, and then determining the corresponding gas change trend influence coefficient according to different gas change stages.
In particular implementations, determining the environmental impact coefficient of the alert point may include:
Acquiring the organic matter content, the pH value and the water content of the environment where the alarm point is located; and determining the environmental impact coefficient according to the organic matter content, the pH value and the water content.
For example, the soil organic matter content is u, the pH value is H, the water content is W, sampling is carried out by taking 10 cubic meters of the periphery of an alarm point as a unit, and the environmental impact coefficient is calculated by taking 9 samples.
In specific implementation, determining the correction coefficient of the alarm point may include:
Determining the number of alarms of the alarm point in a past preset time range and corresponding distinguishing errors, fitting a relation equation between the number of alarms and the distinguishing errors, and determining the correction coefficient according to the relation equation obtained by fitting; wherein, the relation equation is: b=2d (x-0.5) +k, d is the number of alarms, b is the corresponding differentiation error, and K is the correction coefficient.
For example, an error of the number of alarms and the discrimination result of the alarm points in the past one month, an error of the number of alarms and the discrimination result of the alarm points in the past two months, an error of the number of alarms and the discrimination result of the alarm points in the past 3 months, an error of the number of alarms and the discrimination result of the alarm points in the past 4 months, an error of the number of alarms and the discrimination result of the alarm points in the past 5 months, an error of the number of alarms and the discrimination result of the alarm points in the past 6 months, and equation fitting is performed based on these 6 sets of data to obtain b=2d (x-0.5) +k, from which K can be obtained.
S2, calculating leakage factor coefficients of the alarm points according to the influence coefficients;
In specific implementation, S2 may specifically include: calculating the leakage factor coefficient using a fifth calculation formula, the fifth calculation formula including:
X(T*S+Q)*1/2C*1/4G+K
Wherein X is the leakage factor coefficient, T is the topology influence coefficient, S is the equipment influence coefficient, Q is the gas change trend influence coefficient, C is the history alarm coefficient, G is the association alarm coefficient, and K is the correction coefficient.
S3, distinguishing whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient.
In specific implementation, S3 may include: if the leakage factor coefficient is in a first range, the alarm point is gas leakage; if the leakage factor is in the second range, the alarm point is that biogas exceeds standard; and if the leakage factor coefficient is not in the first range and is not in the second range, sending a prompt for performing manual verification.
For example, if X M, it is determined that gas is leaking; if X epsilon N, judging that the biogas exceeds the standard; if and are judged to be other.
In specific implementation, after distinguishing, the method provided by the invention can further comprise:
S4, if the alarm point is determined to be gas leakage, determining the gas leakage grade of the alarm point according to the magnitude of the leakage factor coefficient, and starting a corresponding disposal strategy according to the gas leakage grade; if the alarm point is determined to be the biogas exceeding standard, determining the biogas exceeding standard grade of the alarm point according to the size of the leakage factor coefficient, and starting a corresponding disposal strategy according to the biogas exceeding standard grade;
for example, whether the gas leakage or the biogas exceeds the standard, the serious level of the alarm can be distinguished according to the difference of the X value, so that corresponding 1,2 and 3-level emergency plans and treatment strategies are started.
S5, if the distinguishing result is consistent with the checking result of the personnel on site, taking the plurality of influence coefficients and the corresponding distinguishing result as a training sample, and adding the training sample into a sample library; and performing parameter adjustment on the fifth calculation formula according to training samples in the sample library.
In practice, after the discrimination result is obtained, the corresponding staff member is also arranged to go to the site for processing. Personnel can judge whether the distinguishing result is correct according to the field condition. If the distinguishing result is consistent with the field condition, namely the distinguishing result is correct, the distinguishing result and corresponding each influence coefficient can be used as a training sample to be added into a sample library. And then, carrying out parameter adjustment on the fifth calculation formula by using the samples in the sample library, so that the fifth calculation formula is more and more accurate.
If the distinguishing result is other, the checking is needed to be carried out on site manually, if the gas leakage or the biogas exceeds the standard, the corresponding result and each influence coefficient are used as a training sample and added into a sample library, and the fifth calculation formula is updated.
It can be understood that the method is mainly used for distinguishing whether the gas leakage or the biogas overscale is in the hidden space or the closed space, so that corresponding maintenance strategy can be started conveniently, risks can be controlled better in advance, and potential safety accidents can be avoided. Because the topological relation of peripheral gas equipment and facilities, the ageing condition of the equipment and facilities, the gas composition and the change trend characteristics thereof, city and environment factors, the alarm history of the land and the associated alarm conditions within a certain range around are all important factors for distinguishing biogas exceeding or gas leakage, leakage factor coefficients can be calculated according to the factors, and the distinction can be carried out according to the leakage factor coefficients.
That is, the method calculates the factors such as the gas components, the environmental factors, the topological factors, the equipment factors and the like of the alarm points, and judges whether the gas leakage or the biogas exceeds the standard or not through an algorithm; and according to the severity level of the alarm obtained by distinguishing, starting an emergency plan and a treatment strategy of corresponding level. Meanwhile, the result can be incorporated into a sample library, so that better support is provided for the next alarm judgment. Compared with the prior art, the method is more accurate in judgment only according to the gas components.
It can be understood that the method can provide more accurate dangerous situation, and can be combined with an emergency plan of an enterprise to provide guarantee for subsequent processing judgment through specific rating standards, leakage gas types and the like. The safety accident rate can be effectively reduced, correct rescue measures are started at the first time aiming at gas leakage accidents, accident loss is reduced, and safer guarantee is provided for the safety of staff.
In practice, the method is applied to a plurality of gas enterprises, and has better effects and accuracy rate of over 95 percent.
In a second aspect, the present invention provides a system for distinguishing between gas leakage and biogas overproof comprising:
A determining module for: determining a plurality of influence coefficients of the alarm points; wherein the plurality of influence coefficients comprises: topology influence coefficient, equipment influence coefficient, gas change trend influence coefficient, history alarm coefficient, correlation alarm coefficient, environment influence coefficient and correction coefficient; the topology influence coefficient is an influence coefficient of peripheral equipment distribution conditions of the alarm point on the alarm point, the equipment influence coefficient is an influence coefficient of peripheral equipment aging conditions of the alarm point on the alarm point, the gas change trend influence coefficient is an influence coefficient of gas change trend of the alarm point on the alarm point, and the associated alarm coefficient is an influence coefficient of historical alarm conditions around the alarm point on the alarm point;
A calculation module for: calculating leakage factor coefficients of the alarm points according to the influence coefficients;
A distinguishing module for: and distinguishing whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient.
In a specific implementation, the topology influence coefficient is calculated by a first calculation formula, where the first calculation formula includes:
T(n(g1+gn)*t1/2)
Wherein T is the topology influence coefficient, g1 is a parameter of equipment distribution condition within a preset close range, and the preset close range is smaller than a peripheral range; gn is a parameter representing the distribution of devices in a peripheral range, n is a radius of the peripheral range, the peripheral range is a range with n as a radius centered on the alarm point, and t1 is a ratio between the number of associated devices and the total number of devices in the peripheral range.
In a specific implementation, the device influence coefficient is calculated by a second calculation formula, where the second calculation formula includes:
SS1+S2+S3
Sin(a1+an)/2
an1L1*(L-e*PA)/r*r
an2L2*e*Pn
an3L3*e*Pn
Wherein S is the influence coefficient of the equipment in the peripheral range, S1 is the influence coefficient of the equipment in the early stage, S2 is the influence coefficient of the equipment in the peripheral range in the middle stage, S3 is the influence coefficient of the equipment in the peripheral range in the later stage, si is the influence coefficient of the equipment in the peripheral range in the stage i, and i is 1, 2 and 3; a1 is a device state parameter within a preset close range; the preset close range is smaller than the peripheral range; n is the radius of a peripheral range, and the peripheral range is a range taking the alarm point as the center and taking n as the radius; an is equipment state parameters in a peripheral range, and an1, an2 and an3 are equipment state parameters of a gas pipe network, a valve well and a pressure regulating cabinet; l 1L2L3 is the equipment material coefficient of the gas pipe network, the valve well and the regulator cubicle respectively, e is the pipe network pressure constant, pn is the fatigue parameter of equipment, L is the distance between the pipeline of the gas pipe network and the nearest endpoint of the alarm point, PA is the pipeline pressure change rate of the gas pipe network, and r is the radius of the gas pipe network.
In a specific implementation, the historical alarm coefficient is calculated by adopting a third calculation formula, and the third calculation formula comprises:
Cs1+1/3s2+1/7s3+1/30s4
Where C is the history alarm coefficient, s1 is the number of alarms within a range of 2 km around the alarm point within 24 hours before the alarm time of the alarm point, s2 is the number of alarms within a range of 2 km around the alarm point within 72 hours before the alarm time of the alarm point, s3 is the number of alarms within a range of 2 km around the alarm point within one week before the alarm time of the alarm point, s3 is the number of alarms within a range of 2 km around the alarm point around the periphery within one month before the alarm time of the alarm point.
In a specific implementation, the association alarm coefficient is calculated by a fourth calculation formula, where the fourth calculation formula includes:
Gs5+1/2s6+1/5s7
Wherein G is the associated alarm coefficient, and s5, s6 and s7 are the alarm times in the range of 50 meters, 200 meters and 500 meters with the alarm point as the center and the radius respectively.
In specific implementation, determining the gas change trend influence coefficient of the alarm point comprises the following steps:
Determining the gas change trend experience value of the alarm point;
determining a gas change stage of the alarm point according to the empirical value, and determining a corresponding gas change trend influence coefficient according to the gas change stage; wherein the gas change phase comprises an early failure period, an occasional failure period and a depletion failure period; the gas change trend influence coefficient corresponding to the early failure period is-1.4Q1, the gas change trend influence coefficient corresponding to the accidental failure period is Q2, and the gas change trend influence coefficient corresponding to the wear failure period is 1.4Q3, Q1< -1.3, -1.3< Q2<1.3, and 1.3< Q3.
In a specific implementation, determining an environmental impact coefficient of an alarm point includes: acquiring the organic matter content, the pH value and the water content of the environment where the alarm point is located; determining the environmental impact coefficient according to the organic matter content, the pH value and the water content;
Or determining a correction factor for the alert point, including: determining the number of alarms of the alarm point in a past preset time range and corresponding distinguishing errors, fitting a relation equation between the number of alarms and the distinguishing errors, and determining the correction coefficient according to the relation equation obtained by fitting; wherein, the relation equation is: b=2d (x-0.5) +k, d is the number of alarms, b is the corresponding differentiation error, and K is the correction coefficient.
In a specific implementation, the calculating the leakage factor coefficient of the alarm point according to the influence coefficients includes: calculating the leakage factor coefficient using a fifth calculation formula, the fifth calculation formula including:
X(T*S+Q)*1/2C*1/4G+K
Wherein X is the leakage factor coefficient, T is the topology influence coefficient, S is the equipment influence coefficient, Q is the gas change trend influence coefficient, C is the history alarm coefficient, G is the association alarm coefficient, and K is the correction coefficient;
Correspondingly, the determining whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient comprises: if the leakage factor coefficient is in a first range, the alarm point is gas leakage; if the leakage factor is in the second range, the alarm point is that biogas exceeds standard; and if the leakage factor coefficient is not in the first range and is not in the second range, sending a prompt for performing manual verification.
In particular implementations, the system further includes:
If the alarm point is determined to be gas leakage, determining the gas leakage level of the alarm point according to the leakage factor coefficient, and starting a corresponding disposal strategy according to the gas leakage level; if the alarm point is determined to be the biogas exceeding standard, determining the biogas exceeding standard grade of the alarm point according to the size of the leakage factor coefficient, and starting a corresponding disposal strategy according to the biogas exceeding standard grade;
If the distinguishing result is consistent with the checking result of the personnel on site, taking the plurality of influence coefficients and the corresponding distinguishing result as a training sample, and adding the training sample into a sample library; and performing parameter adjustment on the fifth calculation formula according to training samples in the sample library.
It may be appreciated that in the system provided by the embodiments of the present invention in the second aspect, the explanation, examples, beneficial effects, etc. of the content may refer to the corresponding parts in the above method, and will not be repeated herein.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.
Those skilled in the art will appreciate that in one or more of the examples described above, the functions described in the present invention may be implemented in hardware, software, a pendant, or any combination thereof. When implemented in software, these functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention in further detail, and are not to be construed as limiting the scope of the invention, but are merely intended to cover any modifications, equivalents, improvements, etc. based on the teachings of the invention.
Claims (9)
1. A method of distinguishing between gas leakage and biogas overproof comprising:
Determining a plurality of influence coefficients of the alarm points; wherein the plurality of influence coefficients comprises: topology influence coefficient, equipment influence coefficient, gas change trend influence coefficient, history alarm coefficient, correlation alarm coefficient, environment influence coefficient and correction coefficient; the topology influence coefficient is an influence coefficient of peripheral equipment distribution conditions of the alarm point on the alarm point, the equipment influence coefficient is an influence coefficient of peripheral equipment aging conditions of the alarm point on the alarm point, the gas change trend influence coefficient is an influence coefficient of gas change trend of the alarm point on the alarm point, and the associated alarm coefficient is an influence coefficient of historical alarm conditions around the alarm point on the alarm point;
Calculating leakage factor coefficients of the alarm points according to the influence coefficients;
Distinguishing whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient;
The calculating the leakage factor coefficient of the alarm point according to the influence coefficients comprises the following steps: calculating the leakage factor coefficient using a fifth calculation formula, the fifth calculation formula including:
X(T*S+Q)*1/2C*1/4G+K
Wherein X is the leakage factor coefficient, T is the topology influence coefficient, S is the equipment influence coefficient, Q is the gas change trend influence coefficient, C is the history alarm coefficient, G is the association alarm coefficient, and K is the correction coefficient;
Correspondingly, the determining whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient comprises: if the leakage factor coefficient is in a first range, the alarm point is gas leakage; if the leakage factor is in the second range, the alarm point is that biogas exceeds standard; and if the leakage factor coefficient is not in the first range and is not in the second range, sending a prompt for performing manual verification.
2. The method of claim 1, wherein the topology influence coefficient is calculated by a first calculation formula comprising:
T(n(g1+gn)*t1/2)
Wherein T is the topology influence coefficient, g1 is a parameter of equipment distribution condition within a preset close range, and the preset close range is smaller than a peripheral range; gn is a parameter representing the distribution of devices in a peripheral range, n is a radius of the peripheral range, the peripheral range is a range with n as a radius centered on the alarm point, and t1 is a ratio between the number of associated devices and the total number of devices in the peripheral range.
3. The method of claim 1, wherein the device influence coefficient is calculated by a second calculation formula comprising:
SS1+S2+S3
Sin(a1+an)/2
an1L1*(L-e*PA)/r*r
an2L2*e*Pn
an3L3*e*Pn
Wherein S is the influence coefficient of the equipment in the peripheral range, S1 is the influence coefficient of the equipment in the early stage, S2 is the influence coefficient of the equipment in the peripheral range in the middle stage, S3 is the influence coefficient of the equipment in the peripheral range in the later stage, si is the influence coefficient of the equipment in the peripheral range in the stage i, and i is 1, 2 and 3; a1 is a device state parameter within a preset close range; the preset close range is smaller than the peripheral range; n is the radius of a peripheral range, and the peripheral range is a range taking the alarm point as the center and taking n as the radius; an is equipment state parameters in a peripheral range, and an1, an2 and an3 are equipment state parameters of a gas pipe network, a valve well and a pressure regulating cabinet; l 1L2L3 is the equipment material coefficient of the gas pipe network, the valve well and the regulator cubicle respectively, e is the pipe network pressure constant, pn is the fatigue parameter of equipment, L is the distance between the pipeline of the gas pipe network and the nearest endpoint of the alarm point, PA is the pipeline pressure change rate of the gas pipe network, and r is the radius of the gas pipe network.
4. The method of claim 1, wherein the historical alert coefficient is calculated using a third calculation formula comprising:
Cs1+1/3s2+1/7s3+1/30s4
Where C is the history alarm coefficient, s1 is the number of alarms within a range of 2 km around the alarm point within 24 hours before the alarm time of the alarm point, s2 is the number of alarms within a range of 2 km around the alarm point within 72 hours before the alarm time of the alarm point, s3 is the number of alarms within a range of 2 km around the alarm point within one week before the alarm time of the alarm point, s3 is the number of alarms within a range of 2 km around the alarm point around the periphery within one month before the alarm time of the alarm point.
5. The method of claim 1, wherein the associated alarm coefficient is calculated using a fourth calculation formula, the fourth calculation formula comprising:
Gs5+1/2s6+1/5s7
Wherein G is the associated alarm coefficient, and s5, s6 and s7 are the alarm times in the range of 50 meters, 200 meters and 500 meters with the alarm point as the center and the radius respectively.
6. The method of claim 1, wherein determining a gas trend impact coefficient for an alert point comprises:
Determining the gas change trend experience value of the alarm point;
Determining a gas change stage of the alarm point according to the empirical value, and determining a corresponding gas change trend influence coefficient according to the gas change stage; wherein the gas change phase comprises an early failure period, an occasional failure period and a depletion failure period; the gas change trend influence coefficient corresponding to the early failure period is-1.4Q1, the gas change trend influence coefficient corresponding to the accidental failure period is Q2, the gas change trend influence coefficient corresponding to the loss failure period is 1.4Q3, Q1< -1.3, -1.3< Q2<1.3, and 1.3< Q3.
7. The method of claim 1, wherein the step of determining the position of the substrate comprises,
Determining an environmental impact coefficient of an alert point, comprising: acquiring the organic matter content, the pH value and the water content of the environment where the alarm point is located; determining the environmental impact coefficient according to the organic matter content, the pH value and the water content;
Or determining a correction factor for the alert point, including: determining the number of alarms of the alarm point in a past preset time range and corresponding distinguishing errors, fitting a relation equation between the number of alarms and the distinguishing errors, and determining the correction coefficient according to the relation equation obtained by fitting; wherein, the relation equation is: b=2d (x-0.5) +k, d is the number of alarms, b is the corresponding differentiation error, and K is the correction coefficient.
8. The method as recited in claim 1, further comprising:
If the alarm point is determined to be gas leakage, determining the gas leakage level of the alarm point according to the leakage factor coefficient, and starting a corresponding disposal strategy according to the gas leakage level; if the alarm point is determined to be the biogas exceeding standard, determining the biogas exceeding standard grade of the alarm point according to the size of the leakage factor coefficient, and starting a corresponding disposal strategy according to the biogas exceeding standard grade;
If the distinguishing result is consistent with the checking result of the personnel on site, taking the plurality of influence coefficients and the corresponding distinguishing result as a training sample, and adding the training sample into a sample library; and performing parameter adjustment on the fifth calculation formula according to training samples in the sample library.
9. A system for distinguishing between gas leakage and biogas overproof comprising:
A determining module for: determining a plurality of influence coefficients of the alarm points; wherein the plurality of influence coefficients comprises: topology influence coefficient, equipment influence coefficient, gas change trend influence coefficient, history alarm coefficient, correlation alarm coefficient, environment influence coefficient and correction coefficient; the topology influence coefficient is an influence coefficient of peripheral equipment distribution conditions of the alarm point on the alarm point, the equipment influence coefficient is an influence coefficient of peripheral equipment aging conditions of the alarm point on the alarm point, the gas change trend influence coefficient is an influence coefficient of gas change trend of the alarm point on the alarm point, and the associated alarm coefficient is an influence coefficient of historical alarm conditions around the alarm point on the alarm point;
A calculation module for: calculating leakage factor coefficients of the alarm points according to the influence coefficients;
A distinguishing module for: distinguishing whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient;
The calculating the leakage factor coefficient of the alarm point according to the influence coefficients comprises the following steps: calculating the leakage factor coefficient using a fifth calculation formula, the fifth calculation formula including:
X(T*S+Q)*1/2C*1/4G+K
Wherein X is the leakage factor coefficient, T is the topology influence coefficient, S is the equipment influence coefficient, Q is the gas change trend influence coefficient, C is the history alarm coefficient, G is the association alarm coefficient, and K is the correction coefficient;
Correspondingly, the determining whether the alarm point is gas leakage or biogas exceeding according to the range of the leakage factor coefficient comprises: if the leakage factor coefficient is in a first range, the alarm point is gas leakage; if the leakage factor is in the second range, the alarm point is that biogas exceeds standard; and if the leakage factor coefficient is not in the first range and is not in the second range, sending a prompt for performing manual verification.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2452497A1 (en) * | 2002-12-16 | 2004-06-16 | Air Products And Chemicals, Inc. | Odorized seals for the detection of gas leak |
| CN107228740A (en) * | 2016-03-23 | 2017-10-03 | 中国石油化工股份有限公司 | Leakage inline diagnosis method in gas valve |
| CN108518582A (en) * | 2018-01-09 | 2018-09-11 | 丁五行 | Mixed gas suitable for mass flow mixing method fills error compensating method and device |
| CN208141572U (en) * | 2018-03-14 | 2018-11-23 | 南京邮电大学 | A kind of factory's fuel gas detection alarm system based on distributed network |
| CN112102586A (en) * | 2020-09-17 | 2020-12-18 | 杭州海康威视系统技术有限公司 | Fatigue driving warning method, device and equipment |
| KR102372724B1 (en) * | 2021-08-19 | 2022-03-10 | (주)파이브텍 | Managing system for biogas plant using computer vision technology |
| CN114819878A (en) * | 2022-03-29 | 2022-07-29 | 新奥新智科技有限公司 | Operation insurance displaying method and system for gas engineering and computer readable medium |
-
2022
- 2022-03-29 CN CN202210318231.1A patent/CN114664056B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2452497A1 (en) * | 2002-12-16 | 2004-06-16 | Air Products And Chemicals, Inc. | Odorized seals for the detection of gas leak |
| CN107228740A (en) * | 2016-03-23 | 2017-10-03 | 中国石油化工股份有限公司 | Leakage inline diagnosis method in gas valve |
| CN108518582A (en) * | 2018-01-09 | 2018-09-11 | 丁五行 | Mixed gas suitable for mass flow mixing method fills error compensating method and device |
| CN208141572U (en) * | 2018-03-14 | 2018-11-23 | 南京邮电大学 | A kind of factory's fuel gas detection alarm system based on distributed network |
| CN112102586A (en) * | 2020-09-17 | 2020-12-18 | 杭州海康威视系统技术有限公司 | Fatigue driving warning method, device and equipment |
| KR102372724B1 (en) * | 2021-08-19 | 2022-03-10 | (주)파이브텍 | Managing system for biogas plant using computer vision technology |
| CN114819878A (en) * | 2022-03-29 | 2022-07-29 | 新奥新智科技有限公司 | Operation insurance displaying method and system for gas engineering and computer readable medium |
Non-Patent Citations (2)
| Title |
|---|
| Quantification of methane gas leakages using remote sensing and sensor data fusion;Sören Dierks，et al,;《2017 IEEE Sensors Applications Symposium (SAS)》;全文 * |
| 穿越水体天然气管道的泄漏气和沼气的辨别技术;程磊等;《中国安全生产科学技术》;第17卷(第1期);全文 * |
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