CN112529273B - Method and system for predicting number trend of hidden dangers of urban buried gas pipeline - Google Patents
Method and system for predicting number trend of hidden dangers of urban buried gas pipeline Download PDFInfo
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Abstract
The invention discloses a method and a system for predicting the number trend of hidden dangers of urban buried gas pipelines, wherein the method comprises the following steps: acquiring the current quantity of various hidden dangers and the current total quantity of the hidden dangers; acquiring the hidden danger treatment number in the prediction period; acquiring hidden danger increment in a prediction period; acquiring the total hidden danger amount in the prediction period according to the current total hidden danger amount, the number of hidden danger treatments in the prediction period and the hidden danger increment in the prediction period; the invention has the advantages that: the trend prediction of the number of the hidden dangers is more accurate.
Description
Technical Field
The invention relates to the technical field of gas safety supervision, in particular to a method and a system for predicting the number trend of hidden dangers of urban buried gas pipelines.
Background
Along with the obvious acceleration of the urbanization process of China, the urban operation system is increasingly complex, the safety risk is continuously increased, the risk taking gas as an example is particularly prominent, urban gas risk management and control are important links of safety management, hidden dangers need to be managed, accidents occur based on the evolution of the hidden dangers, and therefore the trend of the hidden dangers is controlled, and a manager can know the development condition of the hidden dangers of a gas pipeline along with the time lapse. Meanwhile, based on the predictive analysis of the historical data on the future potential hazard trend development, comprehensive overall planning on the potential hazard treatment can be realized, the potential hazard points are controlled in advance, and the situation that the rain is not on the ground is achieved.
At present, many prediction methods are available, most of which are based on raw data to perform prediction, and correlation function fitting is performed by analyzing the existing trend of the raw data, and future trend prediction is performed according to the fitting function. Chinese patent publication No. CN110209999A discloses a method for predicting a failure trend of a vehicle-mounted device, wherein the described prediction method is to fit various failure data to form a regression model, examine the adaptability of the regression model, and finally use the regression model to predict the failure of the device, the main method is to perform comprehensive analysis by using raw data, and the prediction of the whole data often eliminates the difference between the raw data of different types, which greatly reduces the prediction accuracy.
Disclosure of Invention
The invention aims to solve the technical problem that the existing method and system for predicting the number trend of the hidden dangers of the urban buried gas pipeline have low prediction accuracy.
The invention solves the technical problems through the following technical means: a method for predicting the number trend of hidden dangers of urban buried gas pipelines comprises the following steps:
acquiring a hidden danger set, and summing all hidden danger quantities of all pipe sections according to the hidden danger set to acquire the current various hidden danger quantities and the current hidden danger total quantity;
the number of treatment of each hidden danger in the prediction period is multiplied by the strengthening coefficient of each hidden danger treatment to obtain the number of treatment of the hidden danger in the prediction period;
summing the A-type hidden danger increment and the B-type hidden danger increment in the prediction period to obtain the prediction period hidden danger increment, wherein the A-type hidden danger is unavoidable hidden danger or hidden danger which does not need to be predicted, and the B-type hidden danger is hidden danger which needs to be predicted;
and acquiring the total hidden danger amount in the prediction period according to the current total hidden danger amount, the number of hidden danger treatments in the prediction period and the hidden danger increment in the prediction period.
According to the method, the number of various current hidden dangers and the total number of the current hidden dangers are obtained, on the basis, the final hidden danger trend prediction result is obtained by combining the number of the current hidden dangers with the prediction value of the reduction of the hidden dangers through the number of hidden danger treatment (namely prediction of reduction of the hidden dangers) in the prediction period and prediction of the increment of the hidden dangers, the prediction mode is not to comprehensively analyze original data, the difference among the original different types of data cannot be eliminated through prediction of the whole data, and therefore the prediction accuracy can be effectively improved.
Further, the acquiring of the current various hidden danger quantities and the current hidden danger total quantity includes:
acquiring a hidden danger set D ═ D1,D2,D3,D4,D5,D6,D7,...,DiIn which D isiRepresenting the i-th hidden danger;
by the formula De＝∑DniObtaining the total amount of the current hidden troubles, wherein DniIndicating the ith potential hazard for the nth pipe segment.
Further, the obtaining of the prediction period hidden danger treatment number comprises:
by the formula Dig＝Dig1×fiAcquiring the treatment number of the ith hidden danger in the prediction period, wherein Dig1Representing the i-th planned treatment quantity of the hidden troubles, fiExpressing the strengthening coefficient of the i-th hidden danger treatment;
by the formula fi＝1+Ze(DiT) obtaining the strengthening coefficient for treating the ith hidden danger, wherein Ze(DiT) represents the influence of the issuing of the e-th policy and the development of activities on the actual treatment quantity of the i-th hidden danger;
by the formula
Acquiring the influence of the issuing of the e-th policy and the development of the activity on the actual treatment amount of the i-th hidden trouble, wherein,
shows the actual treatment hidden danger quantity during the issuing of the e-th policy and the developing period of the activity,
the number of hidden dangers of plan treatment during the issuing and the activity developing period of the e-th policy is shown;
by the formula Dg＝∑DigAnd acquiring the hidden danger treatment number in the prediction period.
Further, the obtaining of the forecast period hidden danger increment comprises:
by the formula Dn＝DA+DBObtaining a forecast period hidden danger increment, wherein the forecast period hidden danger increment is represented, DAIndicates class A hidden danger increment, DBRepresenting a class B hidden danger increment.
And furthermore, the A-type hidden dangers comprise hidden dangers that the space between the gas pipeline and other pipelines or the embedding mode does not meet the national standard requirement, the mode that the gas pipeline passes through the highway or the railway does not meet the national relevant regulation hidden dangers, the hidden dangers of illegal tie occupation, the hidden dangers of insufficient safety space and the hidden dangers of geological disasters, the A-type hidden dangers do not have time characteristics or have unobvious time characteristics, and when the pipe network general investigation or the geological disasters general investigation is carried out, the hidden dangers are found to exist, and the A-type hidden danger increment is obtained.
Still further, the acquiring process of the type B hidden danger increment is as follows:
acquiring a set of indexes related to the ith hidden danger
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger;
reducing and removing redundant influence factors in the index set related to the ith hidden danger by using a rough reduction algorithm to form an influence index reduced set conforming to the local actual condition
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger in accordance with the local actual condition;
according to the state of the influence factor, the simplified set of the influence indexes is subjected to redundancy removal to form a subset Di,y,o 
Representing the mth element in the subset;
by the formula
Obtaining the probability of occurrence of corresponding hidden dangers of the subset, wherein Di,y,oRepresenting the No. o state of an index set related to the No. i hidden danger, wherein U is historical maintenance record, the statistical years of emergency record, and NDi,y,oLeakage appears in the gas pipe section conforming to the No. o state in U yearNumber of leaks, RDi,y,oIndicating the total number of the gas pipe sections conforming to the No. o state;
a set D of indexes relevant to the ith hidden dangeri' and the probability P of occurrence of corresponding hidden danger of the subsetDi,y,oThe method comprises the steps that the potential hazard quantity is expected to be output for input of a BP neural network, the BP neural network is trained through data with the preset quantity in the early stage, and an ith potential hazard possibility prediction model of the expected internal combustion gas is obtained;
the method comprises the steps of obtaining the expectation of the number of i-th hidden dangers of the nth section of gas pipe section in the prediction period, accumulating the expectation of all kinds of hidden dangers to obtain the expected accumulated value of the number of the hidden dangers of the nth section of gas pipe section in the prediction period, and summing the expected total number of the corresponding predicted hidden dangers of all the gas pipe sections in the area to be analyzed, namely the B-type hidden danger increment of the area to be analyzed.
Further, the obtaining of the total predicted period hidden danger amount according to the total current hidden danger amount, the number of potential danger treatments in the predicted period and the predicted period hidden danger increment includes:
by the formula Dp＝De-Dg+DnObtaining the total amount of hidden troubles in the prediction period, wherein DpRepresenting the total amount of risk during the prediction period.
The invention also provides a system for predicting the number trend of the hidden dangers of the urban buried gas pipeline, which comprises the following steps:
the current hidden danger total quantity acquisition module is used for acquiring a hidden danger set, and summing all hidden danger quantities of all pipe sections according to the hidden danger set to acquire current hidden danger quantities and current hidden danger total quantities;
the hidden danger treatment number acquisition module in the prediction period is used for obtaining the product of the treatment number of each hidden danger in the prediction period and the strengthening coefficient of each hidden danger treatment to acquire the hidden danger treatment number in the prediction period;
the system comprises a prediction period hidden danger increment obtaining module, a prediction period hidden danger increment obtaining module and a prediction period hidden danger increment obtaining module, wherein the prediction period hidden danger increment obtaining module is used for summing an A-type hidden danger increment and a B-type hidden danger increment in a prediction period to obtain the prediction period hidden danger increment, the A-type hidden danger is an unavoidable or non-prediction hidden danger, and the B-type hidden danger is a hidden danger needing prediction;
and the prediction period hidden danger total quantity obtaining module is used for obtaining the prediction period hidden danger total quantity according to the current hidden danger total quantity, the prediction period hidden danger treatment number and the prediction period hidden danger increment.
Further, the current hidden danger total amount obtaining module is further configured to:
acquiring a hidden danger set D ═ D1,D2,D3,D4,D5,D6,D7,...,DiIn which D isiRepresenting the i-th hidden danger;
by the formula De＝∑DniObtaining the total amount of the current hidden troubles, wherein DniIndicating the ith potential hazard for the nth pipe segment.
Furthermore, the forecast period hidden danger abatement number obtaining module is further configured to:
by the formula Dig＝Dig1×fiAcquiring the treatment number of the ith hidden danger in the prediction period, wherein Dig1Representing the i-th planned treatment quantity of the hidden troubles, fiExpressing the strengthening coefficient of the i-th hidden danger treatment;
by the formula fi＝1+Ze(DiT) obtaining the strengthening coefficient for treating the ith hidden danger, wherein Ze(DiT) represents the influence of the issuing of the e-th policy and the development of activities on the actual treatment quantity of the i-th hidden danger;
by the formula
Acquiring the influence of the issuing of the e-th policy and the development of the activity on the actual treatment amount of the i-th hidden trouble, wherein,
shows the actual treatment hidden danger quantity during the issuing of the e-th policy and the developing period of the activity,
the number of hidden dangers of plan treatment during the issuing and the activity developing period of the e-th policy is shown;
by the formula Dg＝∑DigAnd acquiring the hidden danger treatment number in the prediction period.
Further, the forecast period hidden danger increment obtaining module is further configured to:
by the formula Dn＝DA+DBObtaining a forecast period hidden danger increment, wherein the forecast period hidden danger increment is represented, DAIndicates class A hidden danger increment, DBRepresenting a class B hidden danger increment.
And furthermore, the A-type hidden dangers comprise hidden dangers that the space between the gas pipeline and other pipelines or the embedding mode does not meet the national standard requirement, the mode that the gas pipeline passes through the highway or the railway does not meet the national relevant regulation hidden dangers, the hidden dangers of illegal tie occupation, the hidden dangers of insufficient safety space and the hidden dangers of geological disasters, the A-type hidden dangers do not have time characteristics or have unobvious time characteristics, and when the pipe network general investigation or the geological disasters general investigation is carried out, the hidden dangers are found to exist, and the A-type hidden danger increment is obtained.
Still further, the acquiring process of the type B hidden danger increment is as follows:
acquiring a set of indexes related to the ith hidden danger
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger;
reducing and removing redundant influence factors in the index set related to the ith hidden danger by using a rough reduction algorithm to form an influence index reduced set conforming to the local actual condition
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger in accordance with the local actual condition;
according to the state of the influence factor, the simplified set of the influence indexes is subjected to redundancy removal to form a subset Di,y,o 
Representing the mth element in the subset;
by the formula
Obtaining the probability of occurrence of corresponding hidden dangers of the subset, wherein Di,y,oRepresenting the No. o state of an index set related to the No. i hidden danger, wherein U is historical maintenance record, the statistical years of emergency record, and NDi,y,oThe number of gas pipe sections which meet the No. o state in U year and have leakage, RDi,y,oIndicating the total number of the gas pipe sections conforming to the No. o state;
a set D of indexes relevant to the ith hidden dangeri' and the probability P of occurrence of corresponding hidden danger of the subsetDi,y,oThe method comprises the steps that the potential hazard quantity is expected to be output for input of a BP neural network, the BP neural network is trained through data with the preset quantity in the early stage, and an ith potential hazard possibility prediction model of the expected internal combustion gas is obtained;
the method comprises the steps of obtaining the expectation of the number of i-th hidden dangers of the nth section of gas pipe section in the prediction period, accumulating the expectation of all kinds of hidden dangers to obtain the expected accumulated value of the number of the hidden dangers of the nth section of gas pipe section in the prediction period, and summing the expected total number of the corresponding predicted hidden dangers of all the gas pipe sections in the area to be analyzed, namely the B-type hidden danger increment of the area to be analyzed.
Further, the prediction period hidden danger total amount obtaining module is further configured to:
by the formula Dp＝De-Dg+DnObtaining the total amount of hidden troubles in the prediction period, wherein DpRepresenting the total amount of risk during the prediction period.
The invention has the advantages that: according to the method, the number of various current hidden dangers and the total number of the current hidden dangers are obtained, on the basis, the final hidden danger trend prediction result is obtained by combining the number of the current hidden dangers with the prediction value of the reduction of the hidden dangers through the number of hidden danger treatment (namely prediction of reduction of the hidden dangers) in the prediction period and prediction of the increment of the hidden dangers, the prediction mode is not to comprehensively analyze original data, the difference among the original different types of data cannot be eliminated through prediction of the whole data, and therefore the prediction accuracy can be effectively improved.
Drawings
Fig. 1 is a flowchart of a method for predicting the number trend of hidden dangers of urban buried gas pipelines, disclosed in embodiment 1 of the present invention;
FIG. 2 is a schematic view of analysis of the attention degree of hidden danger treatment in the method for predicting the number trend of the hidden dangers of the urban buried gas pipeline disclosed in embodiment 1 of the invention;
fig. 3 is a flowchart for acquiring a type B hidden danger increment in the method for predicting the number trend of the hidden dangers of the urban buried gas pipeline disclosed in embodiment 1 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all 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.
Example 1
As shown in fig. 1, a method for predicting a trend of the number of hidden dangers of an urban buried gas pipeline includes:
acquiring a hidden danger set, and summing all hidden danger quantities of all pipe sections according to the hidden danger set to acquire the current various hidden danger quantities and the current hidden danger total quantity;
the number of treatment of each hidden danger in the prediction period is multiplied by the strengthening coefficient of each hidden danger treatment to obtain the number of treatment of the hidden danger in the prediction period;
summing the A-type hidden danger increment and the B-type hidden danger increment in the prediction period to obtain the prediction period hidden danger increment, wherein the A-type hidden danger is unavoidable hidden danger or hidden danger which does not need to be predicted, and the B-type hidden danger is hidden danger which needs to be predicted;
and acquiring the total hidden danger amount in the prediction period according to the current total hidden danger amount, the number of hidden danger treatments in the prediction period and the hidden danger increment in the prediction period.
Step S1, acquiring the current various hidden danger quantity and the current hidden danger total quantity, including:
and dividing the gas pipe network into pipe sections according to the factors such as pressure level, pipe type, embedding mode, service age, anticorrosive coating type and the like, and expressing the pipe sections by using Ln, wherein n represents the nth pipe section.
Acquiring main hidden danger types of the local gas pipeline according to data such as historical maintenance records, emergency treatment records and inspection records of the buried gas pipeline of the local gas enterprise, including but not limited to cross-crossing hidden danger D1Construction defect hidden danger D2And pipeline aging hidden danger D3Hidden danger of pipeline corrosion D4Third party destruction hidden danger D5Potential danger of insufficient safety spacing D6Natural disaster hidden danger D7And the like,
i.e. the set of hidden dangers can be expressed as D ═ D1,D2,D3,D4,D5,D6,D7,...,DiIn which D isiRepresenting the i-th hidden danger;
by the formula De＝∑DniObtaining the total amount of the current hidden troubles, wherein DniIndicating the ith potential hazard for the nth pipe segment.
And step S2, acquiring the treatment number of the hidden dangers in the prediction period, wherein the treatment number comprises the following steps:
by the formula Dig＝Dig1×fiAcquiring the treatment number of the ith hidden danger in the prediction period, wherein Dig1Representing the i-th planned treatment quantity of the hidden troubles, fiExpressing the strengthening coefficient of the i-th hidden danger treatment;
the hidden danger plan governing quantity can be obtained according to but not limited to a geological disaster governing plan, a gas pipe network transformation plan, a gas group safety work plan and the like. For example, when the treatment of a certain geological disaster point is completed, the hidden trouble of gas pipeline leakage caused by the geological disaster is eliminated. And if the hidden trouble exists in the gas pipeline, the hidden trouble of the gas pipeline is eliminated.
The enhancement coefficient for treating the hidden danger refers to the enhancement effect on the treatment quantity of the hidden danger when external policies and activities are carried out, and plays a positive role in reducing the quantity of the hidden danger under the influence of the issuance and the development of the policies such as important instructions related to gas, safe production meetings, safety inspection, special treatment of the hidden danger and the like of state hospitals, provinces, cities, districts, counties and gas companies.
By the formula fi＝1+Ze(DiT) obtaining the strengthening coefficient for treating the ith hidden danger, wherein Ze(DiT) represents the influence of the issuing of the e-th policy and the development of activities on the actual treatment quantity of the i-th hidden danger;
by the formula
Acquiring the influence of the issuing of the e-th policy and the development of the activity on the actual treatment amount of the i-th hidden trouble, wherein,
shows the actual treatment hidden danger quantity during the issuing of the e-th policy and the developing period of the activity,
the number of hidden dangers of plan treatment during the issuing and the activity developing period of the e-th policy is shown; as shown in fig. 2, a schematic diagram of analyzing the importance of the hidden danger control is shown.
By the formula Dg＝∑DigAnd acquiring the hidden danger treatment number in the prediction period.
And step S3, acquiring the forecast period hidden danger increment, comprising the following steps:
1) classification of hidden dangers
The hidden danger increment of the buried gas pipeline refers to the number of newly increased hidden dangers in the period from the current time point to the predicted time point. The hidden danger of the gas pipeline mainly comprises:
1) cross-passing hidden trouble D1. Mainly divided into two categories, including hidden trouble D of insufficient space between gas pipeline and other pipelines11And the way of the gas pipeline passing through the road or the railway does not conform to the related national regulation hidden danger D12. Gas lines and other pipesThe hidden trouble of insufficient line spacing is divided into two categories, namely, the spacing between the gas pipeline and other pipelines or the burying mode does not meet the national standard requirement D111. Secondly, the gas pipeline and other pipelines can not meet the safety requirement, namely, the buried gas pipeline is diffused to the adjacent pipeline through soil after leaking to gather the hidden explosion danger D112And when the adjacent pipelines are full of water and the like, the hidden troubles disappear.
2) Hidden trouble of construction defect D2. Mainly means that the welding seam has air holes or sand holes, the coating is damaged during construction, the anticorrosive coating is not uniformly coated, and the selected materials do not meet the purchasing standard.
3) Hidden danger of pipeline aging D3. The hidden trouble that the pipeline is aged and damaged after the pipeline is in service in the end stage is indicated.
4) Hidden danger of pipeline corrosion D4. The corrosion of pipelines is mainly divided into chemical corrosion and electrochemical corrosion, which are related to the pH value of soil, point position, pipeline material, wall thickness, type of anticorrosive coating and the like.
5) Third party destruction hazard D5. The third party damage hidden danger comprises the vehicle rolling hidden danger D51And the potential hazard of illegal ring occupation52And the third party construction hidden danger D53。
Hidden danger of vehicle rolling51. Firstly, for a pipeline which does not adopt a protection measure, when the buried depth of the pipeline is less than 0.5m, a motor vehicle rolls the pipeline; and secondly, rolling the pipeline by a load truck or a load engineering truck when the buried depth of the pipeline is 0.5-0.8 m.
Hidden danger of illegal circle occupation52. Comprises a civil house, an enclosing wall and a shed pressure occupying pipeline; the height of the pipeline is more than 2m, and the occupied pressure of the garbage is less than 0.8 m; the large-scale mechanical equipment occupies a pipeline with the pressure burying depth less than 0.8 m.
Third party construction hidden danger D53. The third-party construction refers to third-party construction behaviors of mechanical excavation, drilling, blasting and the like in the range of 5m on two sides of the central line of the pipeline.
6) Hidden danger of insufficient safety spacing D6. The distance between the buried gas pipeline and a civil house, an enclosure, a shed ring and a pole tower plate is insufficient according to the national standard.
7) Natural disaster hidden danger D7. Refers to natural disaster geminate transistorsThe stability of the road causes influences including the influence of geological disasters71Extreme weather influence hidden danger D72. See table 1 for a list of hidden danger types of buried gas pipelines.
TABLE 1 buried gas pipeline hidden danger types List
| Numbering | Type of hidden danger | Properties of |
| D1 | Cross-passing hidden trouble | - |
| D11 | Hidden trouble of insufficient space between gas pipeline and other pipelines | - |
| D111 | The distance between the gas pipeline and other pipelines or the burying mode does not meet the national standard requirement | A |
| D112 | The gas pipeline and other pipelines do not meet the safety requirements | B |
| D12 | The way that the gas pipeline passes through the road or the railway does not conform to the related national regulation hidden danger | A |
| D2 | Hidden trouble of construction defect | B |
| D3 | Hidden trouble of pipeline aging | B |
| D4 | Hidden danger of pipeline corrosion | B |
| D5 | Hidden danger of third party destruction | - |
| D51 | Hidden danger of vehicle rolling | B |
| D52 | Hidden danger of illegal circle occupation | A |
| D53 | Hidden danger of third party construction | B |
| D6 | Hidden trouble of insufficient safety space | A |
| D7 | Hidden danger of natural disaster | - |
| D71 | Hidden danger of geological disaster | A |
| D72 | Hidden danger of extreme weather | B |
In summary, the hidden troubles of the gas pipeline can be classified into A, B types according to the duration.
Class A hazards are referred to as unavoidable or unpredicted hazards, including D111The distance between the gas pipeline and other pipelines or the burying mode does not meet the national standard requirement, D12The mode of gas pipeline crossing road or railway does not conform to the relevant national regulation hidden danger D52Hidden danger of illegal lane occupation6Hidden danger of insufficient safety spacing, D7Potential geological hazards and the like. The hidden dangers such as the distance between a gas pipeline and other pipelines or the burying mode do not meet the national standard requirements, and the hidden dangers exist during pipeline planning and burying; or if the hidden danger of the geological disaster exists, the hidden danger appears when relevant departments of the local government recognize that the gas pipeline is positioned in the influence range of the geological disaster, and the hidden danger disappears after the treatment of the geological disaster is finished. Namely, the A-type hidden danger has no time characteristic or is unobvious, and when the pipe network general survey or the geological disaster general survey is carried out, the hidden danger is found, namely, the hidden danger increment exists. The acquisition mode of the type a hidden danger is shown in table 2.
TABLE 2 acquisition of class A hidden danger increments
The B-type hidden troubles are called predictable hidden troubles, such as gas pipelines and other pipesThe thread does not meet the safety requirements D112Hidden trouble of construction defect D2Pipe aging hidden danger D3Hidden danger of pipeline corrosion D4Potential rolling danger D of vehicle51Third party construction hidden danger D53Extreme weather hazard D72And the hidden dangers have certain time characteristics, and quantity prediction can be carried out.
Thus, by formula Dn＝DA+DBObtaining a forecast period hidden danger increment, wherein the forecast period hidden danger increment is represented, DAIndicates class A hidden danger increment, DBRepresenting a class B hidden danger increment.
As shown in fig. 3, the process of acquiring the B-type hidden danger increment includes:
obtaining an index set related to the occurrence of the ith hidden danger by methods such as a Delphi method, literature research, field survey or historical maintenance record analysis
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger;
performing fuzzification description (such as good, bad, poor, good and the like) on the index set index, and taking whether hidden danger exists as a decision attribute;
reducing and removing redundant influence factors in the index set related to the ith hidden danger by using a rough reduction algorithm to form an influence index reduced set conforming to the local actual condition
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger in accordance with the local actual condition;
reduced set of indicators due to influence
The internal part of indexes can not be obtained, so that deletion is needed, the deletion is redundancy removal, and the influence index simplified set is subjected to redundancy removal to form a subset according to the state of influence factors
Representing the mth element in the subset;
by the formula
Obtaining the probability of occurrence of corresponding hidden dangers of the subset, wherein Di,y,oRepresenting the No. o state of an index set related to the No. i hidden danger, wherein U is historical maintenance record, the statistical years of emergency record, and NDi,y,oThe number of gas pipe sections which meet the No. o state in U year and have leakage, RDi,y,oIndicating the total number of the gas pipe sections conforming to the No. o state;
a set D of indexes relevant to the ith hidden dangeri' and the probability P of occurrence of corresponding hidden danger of the subsetDi,y,oThe method comprises the steps that for the input of a BP neural network, the expectation of the number of hidden dangers is output, the BP neural network is trained through the data of the preset number in the early stage, the prediction model of the possibility of the ith hidden danger of the expected internal combustion gas is obtained, the prediction model of the possibility of the hidden dangers is expressed in a black box form, no specific mapping relation mathematical equation exists, the constructed BP neural network can obtain the output quantity through inputting the input quantity once the construction is successful;
and acquiring corresponding index predicted values in the prediction period of each gas pipeline through reliable information sources such as weather forecast and the like. When the prediction period is longer, the index prediction value may have various results (such as sunny days, light rain, heavy rain and the like), and the index prediction value with the maximum positive correlation with the hidden danger is used as a calculation index;
the method comprises the steps of obtaining the expectation of the number of i-th hidden dangers of the nth section of gas pipe section in the prediction period, accumulating the expectation of all kinds of hidden dangers to obtain the expected accumulated value of the number of the hidden dangers of the nth section of gas pipe section in the prediction period, and summing the expected total number of the corresponding predicted hidden dangers of all the gas pipe sections in the area to be analyzed, namely the B-type hidden danger increment of the area to be analyzed.
In addition, when the index influencing the occurrence of the hidden danger is relatively single, the hidden danger increment can be obtained by analyzing and predicting the index in time series.
Examples of the relevant prediction method are given below.
Predicting the amount of hidden corrosion trouble of pipeline (theoretical formula method)
To the hidden trouble of pipeline corrosion D4The quantity can be predicted by adopting a pipeline corrosion depth growth prediction power function model constructed by Velazquez:
d(T)＝k(t-t0)n
in the formula: t is t0For the time (years) when corrosion pits begin to appear, the values of clay, clay loam and sandy clay loam are respectively 3.05, 3.06 and 2.57, and when the soil type is unknown, 2.88 is taken. The parameters k and n are empirical corrosion constants. In the formula:
k＝0.608-0.00018rp-0.0654ph-0.00026re+0.000974cc-0.000639bc-0.000122sc (11)
n＝0.896+0.519pp+0.00465wc-0.0099bd+0.431ct
wherein the letter means redox potential rp (mV), ph, pipe-to-ground potential pp (mV), soil resistivity re (Ω. m), water content wc (%), soil volume weight bd (g/mL), chloride content cc (ppm), bicarbonate content bc (ppm), sulfate content sc (ppm), and preservative type ct.
The formula d (T) k (t-t)0)nIs converted into
And d is the wall thickness of the pipeline, and the prediction of the occurrence time of corrosion perforation of the pipeline can be realized through the above formula. And counting the number of the pipe sections reaching the predicted corrosion perforation time in the prediction period, namely the corrosion hidden danger increment.
② third party construction hidden danger quantity (Artificial intelligence algorithm)
For the number D of the third-party construction hidden troubles53And the influence parameters are third-party construction activities within the range of 5m on two sides of the central line of the pipeline. The construction activities in a short period can calculate the construction hidden danger increment of the third party by counting the number of the construction activities of the third party in the range of 5m on two sides of the central line of the pipeline which is started in the prediction period of the government construction activity management system.
The prediction of the long-term hidden danger increment can be predicted through an artificial intelligence algorithm such as Holt' winner. Firstly, according to the total construction period, the construction point is divided into three sections { sgy1}, { sgy2}, and { sgy3} according to one month, half year, and more than half year, the time sequence of the construction point is respectively formed, the original data is smoothed for one time, the difference between the data is weakened by smoothing, and then Holt' winner prediction is used, and the processed effect is as follows. And counting the total sigma sgy of the construction hidden danger points of the three intervals in the prediction period.
The third party construction hazard increment Δ sg is expressed as
ΔD53＝∑sgx-∑sgy
Where Σ sgx is the number of existing construction point hazards.
The type B hidden danger increment also has associated factors, and the general type B hidden danger increment associated factors are shown in table 3.
TABLE 3 type B hidden danger increment correlation factor
Step S4: obtaining the total amount of the hidden dangers in the prediction period according to the total amount of the current hidden dangers, the number of the hidden dangers in the prediction period and the hidden danger increment in the prediction period, wherein the steps are as follows:
by the formula Dp＝De-Dg+DnObtaining the total amount of hidden troubles in the prediction period, wherein DpRepresenting the total amount of risk during the prediction period. In addition, a hidden danger game curve can be drawn according to the hidden danger increment and the hidden danger decrement to represent the change of treatment capacity, so that the later-stage hidden danger treatment work is convenient to deploy.
Example 2
Corresponding to embodiment 1 of the present invention, embodiment 2 of the present invention further provides a system for predicting a trend of the number of hidden dangers of an urban buried gas pipeline, where the system includes:
the current hidden danger total quantity acquisition module is used for acquiring a hidden danger set, and summing all hidden danger quantities of all pipe sections according to the hidden danger set to acquire current hidden danger quantities and current hidden danger total quantities;
the hidden danger treatment number acquisition module in the prediction period is used for obtaining the product of the treatment number of each hidden danger in the prediction period and the strengthening coefficient of each hidden danger treatment to acquire the hidden danger treatment number in the prediction period;
the system comprises a prediction period hidden danger increment obtaining module, a prediction period hidden danger increment obtaining module and a prediction period hidden danger increment obtaining module, wherein the prediction period hidden danger increment obtaining module is used for summing an A-type hidden danger increment and a B-type hidden danger increment in a prediction period to obtain the prediction period hidden danger increment, the A-type hidden danger is an unavoidable or non-prediction hidden danger, and the B-type hidden danger is a hidden danger needing prediction;
and the prediction period hidden danger total quantity obtaining module is used for obtaining the prediction period hidden danger total quantity according to the current hidden danger total quantity, the prediction period hidden danger treatment number and the prediction period hidden danger increment.
Specifically, the current hidden danger total amount obtaining module is further configured to:
acquiring a hidden danger set D ═ D1,D2,D3,D4,D5,D6,D7,...,DiIn which D isiRepresenting the i-th hidden danger;
by the formula De＝∑DniObtaining the total amount of the current hidden troubles, wherein DniIndicating the ith potential hazard for the nth pipe segment.
Specifically, the prediction period hidden danger treatment number acquisition module is further configured to:
by the formula Dig＝Dig1×fiAcquiring the treatment number of the ith hidden danger in the prediction period, wherein Dig1Representing the i-th planned treatment quantity of the hidden troubles, fiExpressing the strengthening coefficient of the i-th hidden danger treatment;
by the formula fi＝1+Ze(DiT) obtaining the strengthening coefficient for treating the ith hidden danger, wherein Ze(DiT) shows the issue of the e-th policy and the development of the actioninfluence of the actual treatment amount of the i kinds of hidden dangers;
by the formula
Acquiring the influence of the issuing of the e-th policy and the development of the activity on the actual treatment amount of the i-th hidden trouble, wherein,
shows the actual treatment hidden danger quantity during the issuing of the e-th policy and the developing period of the activity,
the number of hidden dangers of plan treatment during the issuing and the activity developing period of the e-th policy is shown;
by the formula Dg＝∑DigAnd acquiring the hidden danger treatment number in the prediction period.
Specifically, the forecast period hidden danger increment obtaining module is further configured to:
by the formula Dn＝DA+DBObtaining a forecast period hidden danger increment, wherein the forecast period hidden danger increment is represented, DAIndicates class A hidden danger increment, DBRepresenting a class B hidden danger increment.
Specifically, the A-type hidden dangers comprise that the distance between a gas pipeline and other pipelines or the embedding mode does not accord with the national standard requirements, the mode that the gas pipeline passes through a road or a railway does not accord with the national relevant regulated hidden dangers, the violation trapping potential danger, the hidden danger of insufficient safety distance and the hidden danger of geological disasters, the A-type hidden dangers do not have time characteristics or have unobvious time characteristics, and when the pipe network general survey or the geological disasters general survey, the A-type hidden danger increment is obtained by finding the existence of the hidden dangers.
Specifically, the process for acquiring the B-type hidden danger increment includes:
acquiring a set of indexes related to the ith hidden danger
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger;
reducing and removing redundant influence factors in the index set related to the ith hidden danger by using a rough reduction algorithm to form an influence index reduced set conforming to the local actual condition
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger in accordance with the local actual condition;
according to the state of the influence factor, the simplified set of the influence indexes is subjected to redundancy removal to form a subset Di,y,o 
Representing the mth element in the subset;
by the formula
Obtaining the probability of occurrence of corresponding hidden dangers of the subset, wherein Di,y,oRepresenting the No. o state of an index set related to the No. i hidden danger, wherein U is historical maintenance record, the statistical years of emergency record, and NDi,y,oThe number of gas pipe sections which meet the No. o state in U year and have leakage, RDi,y,oIndicating the total number of the gas pipe sections conforming to the No. o state;
a set D of indexes relevant to the ith hidden dangeri' and the probability P of occurrence of corresponding hidden danger of the subsetDi,y,oThe method comprises the steps that the potential hazard quantity is expected to be output for input of a BP neural network, the BP neural network is trained through data with the preset quantity in the early stage, and an ith potential hazard possibility prediction model of the expected internal combustion gas is obtained;
the method comprises the steps of obtaining the expectation of the number of i-th hidden dangers of the nth section of gas pipe section in the prediction period, accumulating the expectation of all kinds of hidden dangers to obtain the expected accumulated value of the number of the hidden dangers of the nth section of gas pipe section in the prediction period, and summing the expected total number of the corresponding predicted hidden dangers of all the gas pipe sections in the area to be analyzed, namely the B-type hidden danger increment of the area to be analyzed.
Specifically, the prediction period hidden danger total amount obtaining module is further configured to:
by the formula Dp＝De-Dg+DnObtaining the total amount of hidden troubles in the prediction period, wherein DpRepresenting the total amount of risk during the prediction period.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A method for predicting the number trend of hidden dangers of urban buried gas pipelines is characterized by comprising the following steps:
acquiring a hidden danger set, and summing all hidden danger quantities of all pipe sections according to the hidden danger set to acquire the current various hidden danger quantities and the current hidden danger total quantity;
the number of treatment of each hidden danger in the prediction period is multiplied by the strengthening coefficient of each hidden danger treatment to obtain the number of treatment of the hidden danger in the prediction period; the specific process is as follows: by the formula Dig＝Dig1×fiAcquiring the treatment number of the ith hidden danger in the prediction period, wherein Dig1Representing the i-th planned treatment quantity of the hidden troubles, fiExpressing the strengthening coefficient of the i-th hidden danger treatment;
by the formula fi＝1+Ze(DiT) obtaining the strengthening coefficient for treating the ith hidden danger, wherein Ze(DiT) represents the influence of the issuing of the e-th policy and the development of activities on the actual treatment quantity of the i-th hidden danger;
by the formula
Acquiring the influence of the issuing of the e-th policy and the development of the activity on the actual treatment amount of the i-th hidden trouble, wherein,
shows the actual treatment hidden danger quantity during the issuing of the e-th policy and the developing period of the activity,
the number of hidden dangers of plan treatment during the issuing and the activity developing period of the e-th policy is shown;
by the formula Dg＝∑DigAcquiring the hidden danger treatment number in the prediction period;
summing the A-type hidden danger increment and the B-type hidden danger increment in the prediction period to obtain the prediction period hidden danger increment, wherein the A-type hidden danger is unavoidable hidden danger or hidden danger which does not need to be predicted, and the B-type hidden danger is hidden danger which needs to be predicted;
and acquiring the total hidden danger amount in the prediction period according to the current total hidden danger amount, the number of hidden danger treatments in the prediction period and the hidden danger increment in the prediction period.
2. The method for predicting the number trend of the hidden dangers of the urban buried gas pipeline according to claim 1, wherein the step of acquiring the number of various current hidden dangers and the total number of the current hidden dangers comprises the following steps:
acquiring a hidden danger set D ═ D1,D2,D3,D4,D5,D6,D7,...,DiIn which D isiRepresenting the i-th hidden danger;
by the formula De＝∑DniObtaining the total amount of the current hidden troubles, wherein DniIndicating the ith potential hazard for the nth pipe segment.
3. The method for predicting the number trend of the hidden dangers of the urban buried gas pipeline according to claim 1, wherein the obtaining of the forecast period hidden danger increment comprises the following steps:
by the formula Dn＝DA+DBObtaining a forecast period hidden danger increment, wherein the forecast period hidden danger increment is represented, DAIndicates class A hidden danger increment, DBRepresenting a class B hidden danger increment.
4. The method for predicting the quantity and the trend of the hidden dangers of the urban buried gas pipeline according to claim 3, wherein the A-type hidden dangers comprise hidden dangers that the distance between the gas pipeline and other pipelines or the burying mode does not accord with the national standard requirements, the gas pipeline passes through a road or a railway mode does not accord with the national relevant regulation hidden dangers, the hidden dangers of illegal tie occupation, the hidden dangers of insufficient safety distance and the hidden dangers of geological disasters, the A-type hidden dangers do not have time characteristics or have unobvious time characteristics, and when the pipe network general survey or the geological disasters general survey, the hidden dangers are found to exist, so that the A-type hidden danger increment is obtained.
5. The method for predicting the number trend of the hidden dangers of the urban buried gas pipeline according to claim 3, wherein the acquisition process of the B-type hidden danger increment is as follows:
acquiring a set of indexes related to the ith hidden danger
Wherein the content of the first and second substances,
the b-th influence index representing the i-th hidden danger;
reducing and removing redundant influence factors in the index set related to the ith hidden danger by using a rough reduction algorithm to form an influence index reduced set conforming to the local actual condition
Wherein the content of the first and second substances,
representation and local realityThe b-th influence index of the ith hidden danger consistent with the actual situation;
forming a subset by carrying out redundancy removal on the influence index simplified set according to the state of the influence factor
Representing the mth element in the subset;
by the formula
Obtaining the probability of occurrence of corresponding hidden dangers of the subset, wherein Di,y,oRepresenting the No. o state of an index set related to the No. i hidden danger, wherein U is historical maintenance record, the statistical years of emergency record, and NDi,y,oThe number of gas pipe sections which meet the No. o state in U year and have leakage, RDi,y,oIndicating the total number of the gas pipe sections conforming to the No. o state;
a set D of indexes relevant to the ith hidden dangeri' and the probability P of occurrence of corresponding hidden danger of the subsetDi,y,oThe method comprises the steps that the potential hazard quantity is expected to be output for input of a BP neural network, the BP neural network is trained through data with the preset quantity in the early stage, and an ith potential hazard possibility prediction model of the expected internal combustion gas is obtained;
the method comprises the steps of obtaining the expectation of the number of i-th hidden dangers of the nth section of gas pipe section in the prediction period, accumulating the expectation of all kinds of hidden dangers to obtain the expected accumulated value of the number of the hidden dangers of the nth section of gas pipe section in the prediction period, and summing the expected total number of the corresponding predicted hidden dangers of all the gas pipe sections in the area to be analyzed, namely the B-type hidden danger increment of the area to be analyzed.
6. The method for predicting the number trend of the hidden dangers of the urban buried gas pipeline according to the claim 3, wherein the step of obtaining the total number of the hidden dangers in the prediction period according to the current total number of the hidden dangers, the number of the hidden dangers in the prediction period and the hidden danger increment in the prediction period comprises the following steps:
by the formula Dp＝De-Dg+DnObtaining the total amount of hidden troubles in the prediction period, wherein DpRepresenting the total amount of risk during the prediction period.
7. A system for predicting the number trend of hidden dangers of urban buried gas pipelines is characterized by comprising the following steps:
the current hidden danger total quantity acquisition module is used for acquiring a hidden danger set, and summing all hidden danger quantities of all pipe sections according to the hidden danger set to acquire current hidden danger quantities and current hidden danger total quantities;
the hidden danger treatment number acquisition module in the prediction period is used for obtaining the product of the treatment number of each hidden danger in the prediction period and the strengthening coefficient of each hidden danger treatment to acquire the hidden danger treatment number in the prediction period; the specific process is as follows: by the formula Dig＝Dig1×fiAcquiring the treatment number of the ith hidden danger in the prediction period, wherein Dig1Representing the i-th planned treatment quantity of the hidden troubles, fiExpressing the strengthening coefficient of the i-th hidden danger treatment;
by the formula fi＝1+Ze(DiT) obtaining the strengthening coefficient for treating the ith hidden danger, wherein Ze(DiT) represents the influence of the issuing of the e-th policy and the development of activities on the actual treatment quantity of the i-th hidden danger;
by the formula
Acquiring the influence of the issuing of the e-th policy and the development of the activity on the actual treatment amount of the i-th hidden trouble, wherein,
shows the actual treatment hidden danger quantity during the issuing of the e-th policy and the developing period of the activity,
the number of hidden dangers of plan treatment during the issuing and the activity developing period of the e-th policy is shown;
by the formula Dg＝∑DigAcquiring the hidden danger treatment number in the prediction period;
the system comprises a prediction period hidden danger increment obtaining module, a prediction period hidden danger increment obtaining module and a prediction period hidden danger increment obtaining module, wherein the prediction period hidden danger increment obtaining module is used for summing an A-type hidden danger increment and a B-type hidden danger increment in a prediction period to obtain the prediction period hidden danger increment, the A-type hidden danger is an unavoidable or non-prediction hidden danger, and the B-type hidden danger is a hidden danger needing prediction;
and the prediction period hidden danger total quantity obtaining module is used for obtaining the prediction period hidden danger total quantity according to the current hidden danger total quantity, the prediction period hidden danger treatment number and the prediction period hidden danger increment.
8. The system for predicting the number trend of the hidden dangers of the urban buried gas pipeline according to claim 7, wherein the current hidden danger total amount obtaining module is further configured to:
acquiring a hidden danger set D ═ D1,D2,D3,D4,D5,D6,D7,...,DiIn which D isiRepresenting the i-th hidden danger;
by the formula De＝∑DniObtaining the total amount of the current hidden troubles, wherein DniIndicating the ith potential hazard for the nth pipe segment.
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