CN115186515B

CN115186515B - Concrete drainage pipeline residual life prediction method and device

Info

Publication number: CN115186515B
Application number: CN202211034570.3A
Authority: CN
Inventors: 董顺; 张翰; 高潮
Original assignee: China Three Gorges Corp
Current assignee: China Three Gorges Corp
Priority date: 2022-08-26
Filing date: 2022-08-26
Publication date: 2023-07-04
Anticipated expiration: 2042-08-26
Also published as: CN115186515A

Abstract

The invention discloses a method and a device for predicting residual life of a concrete drainage pipeline. The method considers the time-varying characteristics of factors such as the compressive strength of the concrete and the like and the influence of the importance difference of the concrete drainage pipeline on the residual service life of the concrete drainage pipeline, and has more scientific and reasonable prediction process and more accurate and reliable prediction result.

Description

Concrete drainage pipeline residual life prediction method and device

Technical Field

The invention relates to the technical field of prediction of residual life of pipelines, in particular to a method and a device for predicting residual life of a concrete drainage pipeline.

Background

The drainage pipe network is an important component of the municipal pipe network system. The residual service life of the drainage pipeline is predicted by combining the factors such as the structural parameters of the active drainage pipeline, the importance and the like, the regional large-scale detection of the drainage pipeline can be effectively avoided, the operation and maintenance cost of the drainage pipeline is reduced, and an important decision basis is provided for making a drainage pipeline operation and maintenance scheme with prominent emphasis and some vectors.

Expert scholars at home and abroad develop a plurality of researches on the prediction of the residual life of the oil and gas pipeline and acquire staged research results, however, documents on the prediction of the residual life of the drainage pipeline, especially the concrete drainage pipeline, are rarely reported. In the prior art, a BP neural network model (which is a multi-layer feedforward neural network trained according to an error reverse propagation algorithm) is built based on corrosion defects in pipelines, conveying medium conditions, pipeline bodies and operation parameters, and is optimized through a limited storage BFGS algorithm (inverse rank 2 quasi-Newton method) and learning rate self-adaptive dynamic adjustment, so that the corrosion defects of natural gas pipelines are predicted, and a basis is provided for predicting the residual life of the natural gas pipelines; in the prior art, a residual life prediction model is established based on accelerated aging test data, and the oxidation induction period of the in-service polyethylene gas pipeline is acquired, so that the residual life of the in-service polyethylene gas pipeline is predicted; in the prior art, based on corrosion data of an oil and gas pipeline, a state equation and an observation equation of a state space model of the oil and gas pipeline are established, an inverse Gaussian-state corrosion degradation model is further established, and the residual life of the oil and gas pipeline is predicted according to the model.

The existing method for predicting the residual life of the oil and gas pipeline is difficult to be applied to a drainage pipeline, and is particularly difficult to be applied to a concrete drainage pipeline. The concrete drainage pipeline has obvious differences with the oil gas pipeline in the aspects of pipes, working environments, conveying media, damage forms and the like. Oil and gas pipelines are typically steel (or polyethylene) pipes, the main contributor to resistance decay being pipe corrosion (or aging), the failure mode of which is typically ductile failure; the conveying medium of the concrete drainage pipeline is mainly municipal sewage or rainwater, the main influencing factors of resistance attenuation are concrete carbonization, corrosion of sewage to concrete and steel bars and the like, and the damage form is mainly brittle failure. In addition, the existing oil and gas pipeline residual life prediction method fails to consider the influence of the difference in importance of the pipeline on the residual life of the oil and gas pipeline. Concrete drainage pipelines are usually buried under urban roads or commercial areas, different concrete drainage pipelines play different roles in municipal drainage systems, and the maintenance and repair costs are different, so that the influence of the importance difference of the pipelines on the residual life of the pipelines is necessary to be considered.

Disclosure of Invention

Therefore, the invention aims to overcome the defects that the existing residual life prediction method of the oil and gas pipeline is difficult to be applied to a concrete drainage pipeline and the influence of the difference of the importance of the pipeline on the residual life of the pipeline cannot be considered, and further provides the residual life prediction method and device applied to the concrete drainage pipeline.

The invention provides a concrete drainage pipeline residual life prediction method, which comprises the following steps:

acquiring load data born by a concrete drainage pipeline, and determining load effect combinations based on the load data born by the concrete drainage pipeline;

acquiring concrete drainage pipeline structure resistance influence factor data, and establishing a concrete drainage pipeline structure resistance attenuation model based on the concrete drainage pipeline structure resistance influence factor data;

constructing a concrete drainage pipeline structure function based on the load effect combination and a concrete drainage pipeline structure resistance attenuation model, and drawing a reliability index change curve according to the concrete drainage pipeline structure function;

acquiring target concrete drainage pipeline data and a reference reliability index, and generating a target reliability index based on the target concrete drainage pipeline data and the reference reliability index;

and matching the target reliability index with the reliability index change curve, and predicting the residual life of the target concrete drainage pipeline based on the matching result.

According to the method for predicting the residual life of the concrete drainage pipeline, provided by the invention, the load effect combination is determined based on load data born by the concrete drainage pipeline, the structural resistance attenuation model is built based on structural resistance influence factors of the concrete drainage pipeline, and then the functional function of the concrete drainage pipeline is built. And drawing a reliability index change curve according to the functional function of the concrete drainage pipeline structure, and predicting the residual life of the concrete drainage pipeline by using the curve. The method considers the time-varying characteristics of factors such as the compressive strength of the concrete and the like and the influence of the importance difference of the concrete drainage pipeline on the residual service life of the concrete drainage pipeline, and has more scientific and reasonable prediction process and more accurate and reliable prediction result.

Optionally, determining the loading effect combination based on loading data experienced by the concrete drain pipeline includes:

extracting load types and statistical parameters in load data born by a concrete drainage pipeline; the load type comprises vertical soil pressure, lateral soil pressure, ground stacking load, ground crowd load and ground vehicle load;

and obtaining the average radius of the concrete drainage pipeline, and determining the load effect combination based on the average radius of the concrete drainage pipeline and the statistical parameters.

Optionally, establishing a concrete drainage pipeline structure resistance attenuation model based on the concrete drainage pipeline structure resistance influence factor data comprises the following steps:

extracting the type of structural resistance influence factors in the structural resistance influence factor data of the concrete drainage pipeline; the structural resistance influence factor type comprises concrete compressive strength, steel bar tensile strength and steel bar cross-sectional area;

and acquiring the effective height of the section of the concrete drainage pipeline, the calculated section length of the concrete drainage pipeline and an average time-varying model corresponding to the structural resistance influence factor type, and establishing a structural resistance attenuation model of the concrete drainage pipeline based on the effective height of the section of the concrete drainage pipeline, the calculated section length of the concrete drainage pipeline and the average time-varying model.

Optionally, a concrete drainage pipeline structure resistance attenuation model is built based on the concrete drainage pipeline section effective height, the concrete drainage pipeline calculated section length and the average value time-varying model, wherein the concrete drainage pipeline structure resistance attenuation model is shown in the following formula:

in the above formula, R (T) represents the structural resistance of the concrete drainage pipeline, h ₀ Represents the effective height of the section of the concrete drainage pipeline, b represents the calculated section length of the concrete drainage pipeline, mu _X6 (T) represents an average time-varying model corresponding to the compressive strength of the concrete, mu _X7 (T) represents an average time-varying model corresponding to the cross-sectional area of the reinforcing steel bar, mu _X8 And (T) represents an average time-varying model corresponding to the tensile strength of the steel bar.

Optionally, constructing a concrete drainage pipeline structure function based on the load effect combination and the structural resistance attenuation model, and drawing a reliability index change curve according to the concrete drainage pipeline structure function, including:

constructing a concrete drainage pipeline structure function based on the load effect combination and the structure resistance attenuation model, and taking various loads born by the concrete drainage pipeline and various structure resistance influence factors of the concrete drainage pipeline as basic random variables of the concrete drainage pipeline structure function;

Determining reliability indexes of the concrete drainage pipeline under different service times based on the basic random variable;

and drawing a reliability index change curve based on the reliability indexes of the concrete drainage pipelines under different service times.

Optionally, generating the target reliability index based on the target concrete drain pipeline data and the reference reliability index includes:

collecting importance influence factor data of a concrete drainage pipeline, and constructing a pipeline importance evaluation index calculation model based on the importance influence factor data of the concrete drainage pipeline;

inputting the data of the target concrete drainage pipeline into a pipeline importance evaluation index calculation model to generate an importance evaluation index of the target concrete drainage pipeline;

and generating a target reliability index based on the benchmark reliability index and the importance evaluation index of the target concrete drainage pipeline.

Optionally, constructing a pipeline importance evaluation index calculation model based on the concrete drainage pipeline importance influence factor data includes:

respectively scoring the weight of the importance influence factors of the concrete drainage pipeline and the importance of the concrete drainage pipeline to generate a weight coefficient and a pipeline importance evaluation index;

determining a linear fitting coefficient based on the concrete drainage pipeline importance influence factor data, the weight coefficient and the pipeline importance evaluation index;

And constructing a pipeline importance evaluation index calculation model based on the concrete drainage pipeline importance influence factor data, the weight coefficient, the pipeline importance evaluation index and the linear fitting coefficient.

In a second aspect of the present application, there is also disclosed a concrete drainage pipeline remaining life prediction apparatus, comprising:

the determining module is used for acquiring load data born by the concrete drainage pipeline and determining load effect combinations of the load data born by the concrete drainage pipeline based on the load data born by the concrete drainage pipeline;

the building module is used for acquiring concrete drainage pipeline structure resistance influence factor data and building a concrete drainage pipeline structure resistance attenuation model based on the concrete drainage pipeline structure resistance influence factor data;

the drawing module is used for constructing a concrete drainage pipeline structure function based on the load effect combination and the concrete drainage pipeline structure resistance attenuation model, and drawing a reliability index change curve according to the concrete drainage pipeline structure function;

the generating module is used for acquiring the target concrete drainage pipeline data and the reference reliability index and generating the target reliability index based on the target concrete drainage pipeline data and the reference reliability index;

And the prediction module is used for matching the target reliability index with the reliability index change curve and predicting the residual life of the target concrete drainage pipeline based on the matching result.

Optionally, the determining module includes:

the first extraction submodule is used for extracting load types and statistical parameters in load data born by the concrete drainage pipeline; the load type comprises vertical soil pressure, lateral soil pressure, ground stacking load, ground crowd load and ground vehicle load;

and the first determining submodule is used for obtaining the average radius of the concrete drainage pipeline and determining a load effect combination based on the average radius of the concrete drainage pipeline and the statistical parameter.

Optionally, the establishing module includes:

the second extraction submodule is used for extracting load types and statistical parameters in load data born by the concrete drainage pipeline; the load type comprises vertical soil pressure, lateral soil pressure, ground stacking load, ground crowd load and ground vehicle load;

the second determining submodule is used for obtaining the effective height of the section of the concrete drainage pipeline, the calculated section length of the concrete drainage pipeline and the average time-varying model corresponding to the structural resistance influence factor type, and establishing the structural resistance attenuation model of the concrete drainage pipeline based on the effective height of the section of the concrete drainage pipeline, the calculated section length of the concrete drainage pipeline and the average time-varying model.

Optionally, the second model for determining the structural resistance attenuation of the concrete drain pipeline in the sub-module is shown in the following formula:

Optionally, the drawing module includes:

the construction submodule is used for constructing a concrete drainage pipeline structure function based on a load effect combination and a structure resistance attenuation model, and various loads born by the concrete drainage pipeline and various structure resistance influence factors of the concrete drainage pipeline are used as basic random variables of the concrete drainage pipeline structure function;

the third determining submodule is used for determining reliability indexes of the concrete drainage pipeline under different service times based on basic random variables;

and the drawing submodule is used for drawing a reliability index change curve based on the reliability indexes of the concrete drainage pipeline under different service times.

Optionally, the generating module includes:

the collecting sub-module is used for collecting importance influence factor data of the concrete drainage pipeline and constructing a pipeline importance evaluation index calculation model based on the importance influence factor data of the concrete drainage pipeline;

the first generation submodule is used for inputting the data of the target concrete drainage pipeline into the pipeline importance evaluation index calculation model to generate an importance evaluation index of the target concrete drainage pipeline;

and the second generation submodule is used for generating a target reliability index based on the reference reliability index and the importance evaluation index of the target concrete drainage pipeline.

Optionally, the collecting submodule includes:

the scoring unit is used for scoring the weight of the importance influence factors of the concrete drainage pipeline and the importance of the concrete drainage pipeline respectively, and generating a weight coefficient and a pipeline importance evaluation index;

the determining unit is used for determining a linear fitting coefficient based on the importance influence factor data of the concrete drainage pipeline, the weight coefficient and the importance evaluation index of the pipeline;

the construction unit is used for constructing a pipeline importance evaluation index calculation model based on the concrete drainage pipeline importance influence factor data, the weight coefficient, the pipeline importance evaluation index and the linear fitting coefficient.

In a third aspect of the present application, a computer device is also disclosed, comprising a processor and a memory, wherein the memory is for storing a computer program, the computer program comprising a program, the processor being configured to invoke the computer program to perform the method of the first aspect described above.

In a fourth aspect of the present application, embodiments of the present invention provide a computer-readable storage medium storing a computer program for execution by a processor to implement the method of the first aspect described above.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for predicting the residual life of a concrete drainage pipeline according to embodiment 1 of the present invention;

FIG. 2 is a flowchart of step S101 in embodiment 1 of the present invention;

FIG. 3 is a flowchart of step S102 in embodiment 1 of the present invention;

fig. 4 is a flowchart of step S103 in embodiment 1 of the present invention;

FIG. 5 is a flowchart of step S104 in embodiment 1 of the present invention;

FIG. 6 is a flowchart of step S1041 in embodiment 1 of the present invention;

FIG. 7 is a schematic block diagram of a concrete drainage pipeline remaining life prediction apparatus according to embodiment 2 of the present invention;

FIG. 8 is a schematic block diagram of the determination module 71 in embodiment 2 of the present invention;

FIG. 9 is a schematic block diagram of the setup module 72 in embodiment 2 of the present invention;

fig. 10 is a schematic block diagram of a drawing module 73 in embodiment 2 of the present invention;

FIG. 11 is a schematic block diagram of the generating module 74 in embodiment 2 of the present invention;

fig. 12 is a schematic block diagram of an acquisition sub-module 741 in embodiment 2 of the invention.

Detailed Description

The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

In the description of the present invention, it should be noted that the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

In addition, the technical features of the different embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.

Example 1

The embodiment provides a concrete drainage pipeline residual life prediction method, as shown in fig. 1, including:

s101, acquiring load data born by a concrete drainage pipeline, and determining a load effect combination based on the load data born by the concrete drainage pipeline.

S102, acquiring concrete drainage pipeline structure resistance influence factor data, and establishing a concrete drainage pipeline structure resistance attenuation model based on the concrete drainage pipeline structure resistance influence factor data.

S103, constructing a concrete drainage pipeline structure function based on the load effect combination and the concrete drainage pipeline structure resistance attenuation model, and drawing a reliability index change curve according to the concrete drainage pipeline structure function.

S104, acquiring target concrete drainage pipeline data and a reference reliability index, and generating a target reliability index based on the target concrete drainage pipeline data and the reference reliability index.

And S105, matching the target reliability index with the reliability index change curve, and predicting the residual life of the target concrete drainage pipeline based on a matching result.

Specifically, the pipe age of the target concrete drainage pipe in the current state is obtained, and the residual life of the target concrete drainage pipe and the residual life T of the target concrete drainage pipe are calculated based on the service life of the target concrete drainage pipe and the pipe age of the target concrete drainage pipe in the current state _R The calculation formula of (2) is as follows:

T _R ＝T _S -T _C

in the above, T _C T represents the pipe age of the target concrete drainage pipeline in the current state _S Indicating the service life of the target concrete drain pipeline.

According to the method for predicting the residual life of the concrete drainage pipeline, the load effect combination is determined based on load data borne by the concrete drainage pipeline, the concrete drainage pipeline structure resistance attenuation model is built based on the concrete drainage pipeline structure resistance influence factors, further the concrete drainage pipeline structure function is built, the reliability index change curve is drawn according to the concrete drainage pipeline structure function, the residual life of the concrete drainage pipeline is predicted by utilizing the reliability index change curve, the time-varying characteristics of the concrete compression strength and other factors and the influence of the concrete drainage pipeline importance difference on the residual life are considered, the prediction process is more scientific and reasonable, and the prediction result is more accurate and reliable.

Preferably, as shown in fig. 2, determining the load effect combination based on the load data of the concrete drainage pipeline in step S101 includes:

s1011, acquiring load types and statistical parameters (comprising average value and standard deviation) of load data born by the concrete drainage pipeline; wherein the load type includes a vertical earth pressure (X ₁ ) Lateral soil pressure (X) ₂ ) Ground pile load (X) ₃ ) Ground crowd load (X) ₄ ) And ground vehicle load (X) ₅ ) The method comprises the steps of carrying out a first treatment on the surface of the The statistical parameters of the various loads comprise average values and standard deviations.

Specifically, the vertical earth pressure (X ₁ ) Lateral soil pressure (X) ₂ ) Ground pile load (X) ₃ ) Ground crowd load (X) ₄ ) And ground vehicle load (X) ₅ ) The distribution types of the (B) are normal distribution, extremum I type distribution and extremum I type distribution respectively, and the average value mu thereof _X1 、μ _X2 、μ _X3 、μ _X4 、μ _X5 All can be calculated by referring to the design specification of the water supply and drainage engineering pipeline structure, and the standard deviation sigma thereof _X1 、σ _X2 、σ _X3 、σ _X4 、σ _X5 0.1 times the average value was taken.

S1012, acquiring the average radius of the concrete drainage pipeline, and determining the load effect combination based on the average radius of the concrete drainage pipeline and the statistical parameters.

Specifically, the load effect combination is related to the basic form adopted by the concrete drainage pipeline, and the specific relation is as follows: if the concrete drainage pipeline is a concrete foundation, taking the bending moment of the pipe top as a load effect; if the concrete drainage pipeline is a sand (soil) arc foundation, the bending moment of the bottom of the pipeline is used as a load effect. And obtaining bending moment coefficients corresponding to various loads by consulting a water supply and drainage engineering structure design manual.

Further, the bending moment of the top or bottom of the concrete drainage pipeline is taken as a load effect, and the calculation formula of the load effect combination S is as follows:

S＝R·(μ _X1 k ₁ +μ _X2 k ₂ +μ _X3 k ₃ +μ _X4 k ₄ +μ _X5 k ₅ )

in the above formula, S represents a load effect combination (N.mm/m, N.mu.mm/S), mu.m _X1 Mean value of vertical soil pressure (N/m, N/sec), mu _X2 Mean value (N/m), mu of lateral soil pressure _X3 Mean value (N/m), mu of the surface pile-up load _X4 Mean value (N/m), mu of ground crowd load _X5 Mean value (N/m), k representing ground vehicle load ₁ Represents the bending moment coefficient, k, corresponding to the vertical soil pressure ₂ Representing lateral directionBending moment coefficient, k, corresponding to soil pressure ₃ Represents the bending moment coefficient, k corresponding to the earth surface pile-up load ₄ Representing bending moment coefficient k corresponding to ground crowd load ₅ And R represents the average radius (mm) of the concrete drainage pipeline.

Further, the calculation formula of the average radius R of the concrete drainage pipeline is as follows:

in the above formula, D represents the inner diameter (mm) of the concrete drainage pipeline; t represents the wall thickness (mm) of the concrete drain pipe.

The embodiment takes the bending moment of the top or bottom of the concrete drainage pipeline as the load effect, thereby being more in line with the damage mode of the concrete drainage pipeline under the action of external load and being more in line with the actual engineering situation.

Preferably, as shown in fig. 3, the building of the concrete drainage pipeline structure resistance attenuation model based on the concrete drainage pipeline structure resistance influence factor data in step S102 includes:

s1021, extracting the structural resistance influence factor type in the structural resistance influence factor data of the concrete drainage pipeline; wherein the structural resistance influencing factor type comprises the compressive strength (X ₆ ) Cross-sectional area of reinforcing bar (X) ₇ ) Tensile strength of reinforcing steel bar (X) ₈ )。

S1022, acquiring an effective height of a section of the concrete drainage pipeline, a calculated section length of the concrete drainage pipeline and an average time-varying model corresponding to the structural resistance influence factor type, and establishing the structural resistance attenuation model of the concrete drainage pipeline based on the effective height of the section of the concrete drainage pipeline, the calculated section length of the concrete drainage pipeline and the average time-varying model.

Specifically, the average value mu of the compressive strength of the concrete _X6 The time-varying model of (T) is expressed as:

wherein mu _co The average value (MPa) of the 28-day compressive strength of the concrete is expressed, and the average value is related to the strength grade of the concrete and can be obtained by consulting the concrete structural design rule, and T is expressed as the service time (year) of a concrete drainage pipeline.

Standard deviation sigma of concrete compressive strength _X6 The time-varying model of (T) is expressed as:

σ _X6 (T)＝σ _co ·(0.0305T+1.2368)

wherein sigma _co The standard deviation (MPa) representing the 28-day compressive strength of concrete, which is related to the strength grade of concrete, can be obtained by referring to the concrete structural design Specification.

Further, the average value mu of the cross-sectional area of the steel bar _X7 The time-varying model of (T) is expressed as:

μ _X7 (T)＝A ₀ ·λ(T)

in the above, A ₀ Initial rebar section area (mm) for concrete drainage pipeline ² M), lambda (T) is the residual area percentage of the section of the steel bar, and the formula of lambda (T) is as follows:

wherein d ₀ Represents the initial diameter (mm) i of the steel bar used for the concrete drainage pipeline _corr Represents the annual average corrosion rate (mm/year) of the steel bar, T ₀ Represents the steel bar corrosion starting time (years), wherein the steel bar corrosion starting time T ₀ The calculation formula of (2) is as follows:

wherein c represents the thickness (mm) of the mortar protection layer of the concrete drainage pipeline, K represents the carbonization speed coefficient of the concrete, and the calculation formula of the carbonization speed coefficient of the concrete is as follows:

wherein alpha is ₁ Represents the correction coefficient of the cement variety, and is alpha to ordinary silicate cement ₁ =1.0, for slag cement α ₁ ＝1.3。

Standard deviation sigma of steel bar cross section area _X7 The time-varying model of (T) is expressed as:

σ _X7 (T)＝0.15·μ _X7 (T)

further, the average value mu of the tensile strength of the steel bars _X8 The time-varying model of (T) is expressed as:

In the above, mu _so Mean value (MPa), eta of ultimate tensile strength of steel bar when the steel bar is not corroded _s The calculation formula of the steel bar section loss rate is as follows:

η _s ＝1-λ(T)

standard deviation sigma of tensile strength of steel bar _X8 The time-varying model of (T) is expressed as:

σ _X8 (T)＝0.0719·μ _X8 (T)

further, the concrete drainage pipeline structure resistance attenuation model is shown as follows:

in the formula, R (T) represents the structural resistance (N.mm/m) of the concrete drainage pipeline, h ₀ Representing the effective height (mm, millimeter) of the section of the concrete drainage pipeline, and b represents the calculated section length (mm) of the concrete drainage pipeline, taking 1000; mu (mu) _X6 (T) represents an average time-varying model corresponding to the compressive strength of the concrete, mu _X7 (T) represents an average time-varying model corresponding to the tensile strength of the reinforcing steel bar, mu _X8 (T) represents the average value corresponding to the cross-sectional area of the reinforcing barAnd (5) changing the model.

The construction of the concrete drainage pipeline structure resistance attenuation model considers the influence of main factors such as concrete carbonization, corrosion of sewage to concrete and steel bars and the like on the concrete drainage pipeline structure resistance, and builds the structure resistance attenuation model based on the time-varying characteristics of the concrete compressive strength, the steel bar tensile strength and the cross-sectional area, so that the prediction of the residual life of the concrete drainage pipeline is more scientific and reasonable.

Preferably, as shown in fig. 4, in step S103, a concrete drainage pipe structure function is constructed based on the load effect combination and the structural resistance attenuation model, and a reliability index change curve is drawn according to the concrete drainage pipe structure function, which includes:

s1031, constructing a concrete drainage pipeline structure function based on the load effect combination and the structure resistance attenuation model, and taking various load influence factors and various structure resistance influence factors of the concrete drainage pipeline as basic random variables of the concrete drainage pipeline structure function.

The expression of the functional function of the concrete drainage pipeline structure is as follows:

R(T)-S＝g(X ₁ ，X ₂ ，X ₃ ，X ₄ ，X ₅ ，X ₆ ，X ₇ ，X ₈ )

wherein X is ₁ 、X ₂ 、X ₃ 、X ₄ 、X ₅ 、X ₆ 、X ₇ 、X ₈ The concrete is basically random variable, and represents vertical soil pressure, lateral soil pressure, ground stacking load, ground crowd load, ground vehicle load, concrete compressive strength, reinforcing steel bar tensile strength and reinforcing steel bar cross-sectional area respectively.

S1032, determining reliability indexes of the concrete drainage pipeline under different service times based on the basic random variables.

Specifically, the reliability index beta of the concrete drainage pipeline under different service times is calculated by adopting an inspection point method, and the method comprises the following steps:

(1) Assuming each basic random variationQuantity X _n Initial value X of (1) _n The initial value beta of the reliability index beta is assumed to be 0;

(2) For a substantially random variable X _n Non-normal variable X in (a) _i (ground pile-up load X) ₃ Ground crowd load X ₄ Ground vehicle load X ₅ ) Calculate the average value mu 'of the equivalent normal variables' _Xi And standard deviation sigma' _Xi And respectively replace the original average value mu _Xi And standard deviation sigma _Xi Wherein the average value μ 'of the equivalent normal variables' _Xi The following formula can be used for calculation:

wherein phi is ^-1 (. Cndot.) represents the inverse of the normal distribution function of the standard, F _i (. Cndot.) represents an abnormal variable X _i Probability distribution functions of (a) are provided.

Standard deviation sigma 'of equivalent normal variable' _Xi The following formula can be used for calculation:

wherein, the liquid crystal display device comprises a liquid crystal display device,

represents a standard normal distribution density function, f _i (. Cndot.) represents an abnormal variable X _i Probability density function of (a).

(3) Determining a direction cosine based on the mean and standard deviation of each substantially random variable X _n Direction cosine alpha of (2) _n The calculation formula of (2) is as follows:

(4) The directional cosine, the average value and the standard deviation of each random variable are substituted into the following formula, and then the reliability index beta is solved.

g(μ _X1 +α ₁ βσ _X1 ，μ _X2 +α ₂ βσ _X2 ，μ _X3 +α ₃ βσ _X3 ，μ _X4 +α ₄ βσ _X4 ，μ _X5 +α ₅ βσ _X5 ，μ _X6 +α ₆ βσ _X6 ，μ _X7 +α ₇ βσ _X7 ，μ _X8 +α ₈ βσ _X8 )＝0

(5) Based on the direction cosine, average value, standard deviation and reliability index beta of each random variable, the following formula is adopted to recalculate each basic random variable X _n Initial value X of (2) ^* _n 。

(6) Repeating the steps (2) - (5) until the relative difference value of the reliability index beta obtained by the two previous and subsequent calculation is less than 5%, thereby obtaining the reliability index of the concrete drainage pipeline under different service time.

S1033, drawing a reliability index change curve based on the reliability indexes of the concrete drainage pipeline under different service times.

Specifically, the service time is taken as an abscissa, and the reliability index of the concrete drainage pipeline is taken as an ordinate.

Preferably, as shown in fig. 5, generating the target reliability index based on the target concrete drain pipe data and the reference reliability index in step S104 includes:

s1041, collecting importance influence factor data of the concrete drainage pipeline, and constructing a pipeline importance evaluation index calculation model based on the importance influence factor data of the concrete drainage pipeline.

Specifically, the concrete drainage pipeline importance influence factor data comprise burial depth data, pipe diameter data, groundwater level data, ground area condition data and soil property data; the unit of the buried depth data, the pipe diameter data and the underground water level data is meter, the buried depth data and the pipe diameter data are respectively designed buried depth and designed pipe diameter, and the underground water level data is the difference between the underground water level elevation and the buried depth elevation; the ground area condition data and the soil property data are dimensionless parameters, and the values of the ground area condition data are optimal, good and poor and respectively correspond to 1.0, 0.5 and 0.1, and the ground area condition data are shown in the following table 1.

Table 1:

ground area condition	Excellent (excellent)	Good grade (good)	Difference of difference
				Regional attributes	Central business district	Traffic artery	Other motor vehicle lanes

Soil property data values are shown in the following table 2:

table 2:

soil properties	Excellent (excellent)	Good grade (good)	Difference of difference
				Number of standard cross N	≥30	(30，15)	≤15

S1042, inputting the data of the target concrete drainage pipeline into the pipeline importance evaluation index calculation model to generate an importance evaluation index of the target concrete drainage pipeline.

S1043, generating the target reliability index based on the reference reliability index and the target concrete drainage pipeline importance evaluation index.

Wherein the target reliability index beta _t The calculation formula of (2) is as follows:

β _t ＝β ₀ ·y _t

in the above, beta ₀ The index of the standard reliability can be obtained by referring to the unified design standard of the reliability of highway engineering structure, y _t And (5) representing an importance evaluation index of the target concrete drainage pipeline.

Preferably, as shown in fig. 6, the constructing a pipeline importance evaluation index calculation model based on the above-mentioned concrete drainage pipeline importance influence factor data in step S1041 includes:

s10411, respectively scoring the weight of the importance influence factors of the concrete drainage pipeline and the importance of the concrete drainage pipeline, and generating a weight coefficient and a pipeline importance evaluation index.

Specifically, according to concrete drainage pipeline data, inviting a plurality of experts to score and evaluate the weights and the pipeline importance of the importance influence factors (burial depth, pipe diameter, underground water level, ground area condition and soil property) of the concrete drainage pipeline, wherein the influence weight scoring range of each factor is 0-10, and the influence of the factors on the pipeline importance is more remarkable when the score is higher; the score of the importance of the pipeline ranges from 0 to 10, and the higher the score is, the more important the pipeline is.

Further, according to the expert scoring result, the weight coefficient is calculated by adopting the following formula:

in the above, lambda _i Represents a weight coefficient S _ji The j-th expert is used for scoring the influence weight of the influence factor i, i is 1-5, the j-th expert corresponds to the burial depth, the pipe diameter, the groundwater level, the ground area condition and the soil property, N is the number of experts, j is 1-N, and j corresponds to each expert.

Further, according to the expert scoring result, calculating a pipeline importance evaluation index by adopting the following formula:

in the above formula, y represents a pipeline importance evaluation index; a is that _j Representing scores for each expert for pipe importance.

S10412, determining a linear fitting coefficient based on the importance influence factor data of the concrete drainage pipeline, the weight coefficient and the importance evaluation index of the pipeline.

Specifically, based on the importance influence factor data of the concrete drainage pipeline, the weight coefficient and the importance evaluation index of the pipeline, obtaining a linear fitting coefficient gamma corresponding to each influence factor through multiple regression analysis _i 。

S10413, constructing a pipeline importance evaluation index calculation model based on the concrete drainage pipeline importance influence factor data, the weight coefficient, the pipeline importance evaluation index and the linear fitting coefficient.

Specifically, the expression of the pipe importance evaluation index calculation model is as follows:

wherein x is ₁ Data (m, x) representing concrete drainage pipeline burial depth ₂ Data (m) and x representing pipe diameter of concrete drainage pipeline ₃ Representing groundwater level data (m), x ₄ Representing ground area condition data (dimensionless), x ₅ Soil property data (dimensionless) are represented.

According to the embodiment, on the basis of considering the influence of factors such as the pipe burial depth and the pipe diameter on the importance of the concrete drainage pipe, the importance of the concrete drainage pipe is subjected to scientific and objective quantitative evaluation by adopting a method combining expert scoring and multiple regression analysis, and the quantitative index is used as an important basis for predicting the residual life of the concrete drainage pipe.

Example 2

The present embodiment provides a concrete drainage pipe remaining life prediction apparatus, as shown in fig. 7, including:

the determining module 71 is configured to obtain load data of the concrete drainage pipeline, and determine a load effect combination of the load data of the concrete drainage pipeline based on the load data of the concrete drainage pipeline.

The building module 72 is configured to obtain concrete drain pipe structure resistance influence factor data, and build a concrete drain pipe structure resistance attenuation model based on the concrete drain pipe structure resistance influence factor data.

And the drawing module 73 is used for constructing a concrete drainage pipeline structure function based on the load effect combination and the concrete drainage pipeline structure resistance attenuation model, and drawing a reliability index change curve according to the concrete drainage pipeline structure function.

The generating module 74 is configured to obtain the target concrete drainage pipeline data and the reference reliability index, and generate the target reliability index based on the target concrete drainage pipeline data and the reference reliability index.

The prediction module 75 is configured to match the target reliability index with the reliability index change curve, and predict the remaining life of the target concrete drainage pipeline based on the matching result.

T _R ＝T _S -T _C

According to the concrete drainage pipeline residual life prediction device, the load effect combination is determined based on load data borne by the concrete drainage pipeline, the concrete drainage pipeline structural resistance attenuation model is built based on the concrete drainage pipeline structural resistance influence factors, further the concrete drainage pipeline structural function is built, the reliability index change curve is drawn according to the concrete drainage pipeline structural function, the residual life of the concrete drainage pipeline is predicted by utilizing the reliability index change curve, the time-varying characteristics of the concrete compression strength and other factors and the influence of the concrete drainage pipeline importance difference on the residual life are considered, the prediction process is more scientific and reasonable, and the prediction result is more accurate and reliable.

Preferably, as shown in fig. 8, the determining module 71 includes:

the first extraction sub-module 711 is configured to extract a load type and a statistical parameter in load data received by the concrete drainage pipeline; wherein the load type includes a vertical earth pressure (X ₁ ) Lateral soil pressure (X) ₂ ) Ground pile load (X) ₃ ) Ground crowd load (X) ₄ ) And ground vehicle load (X) ₅ ) The method comprises the steps of carrying out a first treatment on the surface of the The statistical parameters of the various loads comprise an average value and a standard value.

A first determining sub-module 712 is configured to obtain an average radius of the concrete drain pipe, and determine the load effect combination based on the average radius of the concrete drain pipe and the statistical parameter.

S＝R·(μ _X1 k ₁ +μ _X2 k ₂ +μ _X3 k ₃ +μ _X4 k ₄ +μ _X5 k ₅ )

in the above formula, S represents a load effect combination (N.mm/m, N.mu.mm/S), mu.m _X1 Mean value of vertical soil pressure (N/m, N/sec), mu _X2 Mean value (N/m), mu of lateral soil pressure _X3 Mean value (N/m), mu of the surface pile-up load _X4 Mean value (N/m), mu of ground crowd load _X5 Mean value (N/m), k representing ground vehicle load ₁ Represents the bending moment coefficient, k, corresponding to the vertical soil pressure ₂ Representing the bending moment coefficient, k, corresponding to the lateral soil pressure ₃ Representing the earth's surfaceBending moment coefficient, k, corresponding to pile-up load ₄ Representing bending moment coefficient k corresponding to ground crowd load ₅ And R represents the average radius (mm) of the concrete drainage pipeline.

Preferably, as shown in fig. 9, the establishing module 72 includes:

a second extraction submodule 721 for extracting the structural resistance influence factor type in the structural resistance influence factor data of the concrete drainage pipeline; wherein the structural resistance influencing factors include concrete compressive strength (X ₆ ) Tensile strength of reinforcing steel bar (X) ₇ ) Cross-sectional area of reinforcing bar (X) ₈ ) The method comprises the steps of carrying out a first treatment on the surface of the The statistical parameters of each influence factor comprise an average value and a standard value.

A second determining submodule 722, configured to obtain an effective height of a section of the concrete drainage pipe, a calculated section length of the concrete drainage pipe, and an average time-varying model corresponding to the structural resistance influence factor type, and build the structural resistance attenuation model of the concrete drainage pipe based on the effective height of the section of the concrete drainage pipe, the calculated section length of the concrete drainage pipe, and the average time-varying model.

σ _X6 (T)＝σ _co ·(0.0305T+1.2368)

μ _X7 (T)＝A ₀ ·λ(T)

σ _X7 (T)＝0.15·μ _X7 (T)

η _s ＝1-λ(T)

σ _X8 (T)＝0.0719·μ _X8 (T)

in the formula, R (T) represents the structural resistance (N.mm/m) of the concrete drainage pipeline, h ₀ Representing the effective height (mm, millimeter) of the section of the concrete drainage pipeline, and b represents the calculated section length (mm) of the concrete drainage pipeline, taking 1000; mu (mu) _X6 (T) represents an average time-varying model corresponding to the compressive strength of the concrete, mu _X7 (T) represents an average time-varying model corresponding to the tensile strength of the reinforcing steel bar, mu _X8 And (T) represents an average time-varying model corresponding to the cross-sectional area of the reinforcing steel bar.

Preferably, as shown in fig. 10, the drawing module 73 includes:

and a constructing sub-module 731 for constructing a structural function of the concrete drainage pipeline based on the load effect combination and the structural resistance attenuation model, wherein the influence factors of various loads and various structural resistances of the concrete drainage pipeline are used as basic random variables of the structural function of the concrete drainage pipeline.

A third determination sub-module 732 is configured to determine reliability indicators for the concrete drain pipeline at different service times based on the substantially random variables.

(1) Assuming each basic random variable X _n Initial value X of (1) _n The initial value beta of the reliability index beta is assumed to be 0;

(5) Determining a direction cosine based on the mean and standard deviation of each substantially random variable X _n Direction cosine alpha of (2) _n The calculation formula of (2) is as follows:

(6) The directional cosine, the average value and the standard deviation of each random variable are substituted into the following formula, and then the reliability index beta is solved.

g(μ _X1 +α ₁ βσ _X1 ，μ _X2 +α ₂ βσ _X2 ，μ _X3 +α ₃ βσ _X3 ，μ _X4 +α ₄ βσ _X4 ，

μ _X5 +α ₅ βσ _X5 ，μ _X6 +α ₆ βσ _X6 ，μ _X7 +α ₇ βσ _X7 ，μ _X8 +α ₈ βσ _X8 )＝0

And the drawing submodule 733 is used for drawing a reliability index change curve based on the reliability indexes of the concrete drainage pipeline under different service times.

Preferably, as shown in fig. 11, the generating module 74 includes:

and the acquisition sub-module 741 is used for acquiring the importance influence factor data of the concrete drainage pipeline and constructing a pipeline importance evaluation index calculation model based on the importance influence factor data of the concrete drainage pipeline.

Table 1:

Soil property data values are shown in the following table 2:

table 2:

The first generation sub-module 742 is configured to input the target concrete drainage pipeline data into the pipeline importance evaluation index calculation model to generate a target concrete drainage pipeline importance evaluation index.

A second generation sub-module 743 for generating the target reliability index based on the reference reliability index and the target concrete drain pipe importance evaluation index.

β _t ＝β ₀ ·y _t

in the above, beta ₀ The standard reliability index can be obtained by referring to the unified design standard of the reliability of highway engineering structure; y is _t And (5) representing an importance evaluation index of the target concrete drainage pipeline.

Preferably, as shown in fig. 12, the collecting submodule 741 includes:

and the scoring unit 7411 is used for scoring the weight of the importance influence factors of the concrete drainage pipeline and the importance of the concrete drainage pipeline respectively to generate a weight coefficient and a pipeline importance evaluation index.

in the above, lambda _i The weight coefficient corresponding to each factor affecting the importance of the concrete drainage pipeline is represented; s is S _ji The influence weight scoring value of the j-th expert on the influence factor i is represented; i, taking 1 to 5, wherein the 1 to 5 correspond to the burial depth, pipe diameter, groundwater level, ground area condition and soil property respectively; n represents the number of specialists; j is 1 to N, which correspond to each expert respectively.

A determining unit 7412 for determining a linear fitting coefficient based on the concrete drain pipe importance influence factor data, the weight coefficient, and the pipe importance evaluation index.

A construction unit 7413 for constructing a pipeline importance evaluation index calculation model based on the concrete drain pipeline importance influence factor data, the weight coefficient, the pipeline importance evaluation index and the linear fitting coefficient.

Example 3

The embodiment provides a computer device, which comprises a memory and a processor, wherein the processor is used for reading instructions stored in the memory to execute the residual life prediction method of the concrete drainage pipeline in any method embodiment.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Example 4

The present embodiment provides a computer-readable storage medium storing computer-executable instructions that can perform a method for predicting remaining life of a concrete drainage pipeline in any of the above-described method embodiments. Wherein the storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.

It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.

Claims

1. The method for predicting the residual life of the concrete drainage pipeline is characterized by comprising the following steps of:

load data born by a concrete drainage pipeline are obtained, and a load effect combination is determined based on the load data born by the concrete drainage pipeline;

acquiring concrete drainage pipeline structure resistance influence factor data, and establishing a concrete drainage pipeline structure resistance attenuation model based on the concrete drainage pipeline structure resistance influence factor data; the concrete drainage pipeline structure resistance attenuation model is shown in the following formula:

in the above formula, R (T) represents the structural resistance of the concrete drainage pipeline, h ₀ Represents the effective height of the section of the concrete drainage pipeline, b represents the calculated section length of the concrete drainage pipeline, mu _X6 (T) represents an average time-varying model corresponding to the compressive strength of the concrete, mu _X7 (T) represents an average time-varying model corresponding to the cross-sectional area of the reinforcing steel bar, mu _X8 (T) represents an average time-varying model corresponding to the tensile strength of the steel bar; wherein, the average value mu of the compressive strength of the concrete _X6 The time-varying model of (T) is expressed as:

wherein mu _co The average value of the 28-day compressive strength of the concrete is represented, and T represents the service time of a concrete drainage pipeline;

average value mu of section area of steel bar _X7 The time-varying model of (T) is expressed as:

μ _X7 (T)＝A ₀ ·λ(T)

in the above, A ₀ The method is characterized in that the method is the initial steel bar cross-sectional area of a concrete drainage pipeline, and lambda (T) is the residual area percentage of the steel bar cross-section;

average mu of tensile strength of steel bar _X8 The time-varying model of (T) is expressed as:

in the above, mu _so Indicating steelAverage value of ultimate tensile strength eta when tendons are not corroded _s Representing the section loss rate of the steel bar;

constructing a concrete drainage pipeline structure function based on the load effect combination and the concrete drainage pipeline structure resistance attenuation model, and drawing a reliability index change curve according to the concrete drainage pipeline structure function;

and matching the target reliability index with the reliability index change curve, and predicting the residual life of the target concrete drainage pipeline based on a matching result.

2. A method of predicting remaining life of a concrete drainage pipeline as recited in claim 1, wherein said determining a load effect combination based on load data received by said concrete drainage pipeline comprises:

Extracting load types and statistical parameters in load data born by the concrete drainage pipeline; the load type comprises vertical soil pressure, lateral soil pressure, ground stacking load, ground crowd load and ground vehicle load;

and acquiring an average radius of the concrete drainage pipeline, and determining the load effect combination based on the average radius of the concrete drainage pipeline and the statistical parameter.

3. The method for predicting the residual life of a concrete drainage pipeline according to claim 1, wherein the building a concrete drainage pipeline structural resistance attenuation model based on the concrete drainage pipeline structural resistance influence factor data comprises the following steps:

extracting the structural resistance influence factor type in the structural resistance influence factor data of the concrete drainage pipeline; wherein the structural resistance influence factor type comprises concrete compressive strength, reinforcing steel bar tensile strength and reinforcing steel bar cross-sectional area;

and acquiring the effective height of the section of the concrete drainage pipeline, the calculated section length of the concrete drainage pipeline and an average time-varying model corresponding to the structural resistance influence factor type, and establishing the structural resistance attenuation model of the concrete drainage pipeline based on the effective height of the section of the concrete drainage pipeline, the calculated section length of the concrete drainage pipeline and the average time-varying model.

4. The method for predicting the residual life of a concrete drainage pipeline according to claim 1, wherein the constructing a concrete drainage pipeline structural function based on the load effect combination and the structural resistance attenuation model, and drawing a reliability index change curve according to the concrete drainage pipeline structural function, comprises:

determining reliability indexes of the concrete drainage pipeline under different service times based on the basic random variables;

5. The concrete drainage pipeline remaining life prediction method according to claim 1, wherein the generating a target reliability index based on the target concrete drainage pipeline data and the reference reliability index comprises:

inputting the target concrete drainage pipeline data into the pipeline importance evaluation index calculation model to generate a target concrete drainage pipeline importance evaluation index;

and generating the target reliability index based on the reference reliability index and the importance evaluation index of the target concrete drainage pipeline.

6. The method for predicting the residual life of a concrete drainage pipeline according to claim 5, wherein the constructing a pipeline importance evaluation index calculation model based on the concrete drainage pipeline importance influence factor data comprises:

7. A concrete drainage pipeline remaining life prediction device, comprising:

the building module is used for acquiring concrete drainage pipeline structure resistance influence factor data and building a concrete drainage pipeline structure resistance attenuation model based on the concrete drainage pipeline structure resistance influence factor data; the concrete drainage pipeline structure resistance attenuation model is shown in the following formula:

in the above-mentioned method, the step of,r (T) represents the structural resistance of the concrete drainage pipeline, h ₀ Represents the effective height of the section of the concrete drainage pipeline, b represents the calculated section length of the concrete drainage pipeline, mu _X6 (T) represents an average time-varying model corresponding to the compressive strength of the concrete, mu _X7 (T) represents an average time-varying model corresponding to the cross-sectional area of the reinforcing steel bar, mu _X8 (T) represents an average time-varying model corresponding to the tensile strength of the steel bar; wherein, the average value mu of the compressive strength of the concrete _X6 The time-varying model of (T) is expressed as:

μ _X7 (T)＝A ₀ ·λ(T)

in the above, mu _so Mean value of ultimate tensile strength, eta, of steel bars when the steel bars are not corroded _s Representing the section loss rate of the steel bar;

the generation module is used for acquiring target concrete drainage pipeline data and reference reliability indexes and generating target reliability indexes based on the target concrete drainage pipeline data and the reference reliability indexes;

and the prediction module is used for matching the target reliability index with the reliability index change curve and predicting the residual life of the target concrete drainage pipeline based on a matching result.

8. A computer device comprising a processor and a memory, wherein the memory is for storing a computer program, the processor being configured to invoke the computer program to perform the steps of the method according to any of claims 1-6.

9. A computer readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the method according to any of claims 1-6.