A data analysis-based multi-oil product pipeline corrosion rate prediction method

Abstract

The present application relates to a kind of based on data analysis's multi-oil product conveying pipeline corrosion rate prediction method, the field for data analysis technique, the method includes: obtaining the first parameter corresponding to conveying pipeline and the second parameter corresponding to multiple oil products, and determine the probability value of exciting conveying pipeline corrosion risk;If probability value is greater than first preset threshold, obtain the third parameter corresponding to target time node;Based on the first parameter, the second parameter and third parameter, determine the conveying pipeline corrosion degree of target time node;According to the conveying pipeline corrosion degree of multiple target time nodes, determine the multi-oil product conveying pipeline corrosion rate in the target time period formed by multiple target time nodes.This application improves the accuracy of conveying pipeline corrosion rate prediction, and then improves the operability and accuracy of corrosion residual life prediction.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis, in particular to a multi-oil product pipeline corrosion rate prediction method based on data analysis. BACKGROUND

[0002] Pipeline transportation is generally considered to be the safest and most economical way to transport fluids that require a large amount of and long distance, mainly transporting natural gas or oil, from crude oil to gasoline, kerosene, diesel and heavy fuel, as the oil and gas industry is booming, thousands of kilometers of pipelines have been installed worldwide under various deep water and soil conditions, the global economy relies heavily on a large pipeline network to transport energy, pipelines are susceptible to various damage and aging defects, and the most common cause of pipeline failure is corrosion and the like, related technologies mainly predict corrosion remaining life prediction by establishing Monte Carlo Simulation and other distribution models, but due to many uncertain factors in the corrosion remaining life prediction work, the defect development law under actual working conditions is difficult to determine, in addition, there is mutual influence between the many influencing factors of pipeline corrosion, which increases the difficulty of corrosion remaining life prediction work, therefore, it is urgent to propose a multi-oil product pipeline corrosion rate prediction method based on data analysis that can improve the operability and accuracy of corrosion remaining life prediction. SUMMARY

[0003] Therefore, it is necessary to provide a multi-oil product pipeline corrosion rate prediction method based on data analysis that can improve the operability and accuracy of corrosion remaining life prediction in view of the above technical problems.

[0004] In a first aspect, a multi-oil product pipeline corrosion rate prediction method based on data analysis is provided, the method comprising: obtaining a first parameter corresponding to a pipeline and a second parameter corresponding to a plurality of oil products, the first parameter comprising at least a parameter for describing the physical and chemical properties of the pipeline, and the second parameter comprising at least a parameter for describing the physical properties and chemical composition of the oil product; based on the first parameter and the second parameter, determining a probability value of triggering the corrosion risk of the pipeline; in response to the probability value being greater than a first preset threshold, obtaining a third parameter corresponding to a target time node, the third parameter being used to describe the environmental parameters of the position where the pipeline is located; based on the first parameter, the second parameter and the third parameter, determining the corrosion degree of the pipeline at the target time node; and determining the corrosion rate of the multi-oil product pipeline in a target time period composed of a plurality of target time nodes according to the corrosion degrees of the pipeline at the plurality of target time nodes.

[0005] Optionally, the obtaining the first parameter and / or the second parameter comprises: obtaining the first parameter corresponding to the conveying pipeline based on design drawings of the conveying pipeline; obtaining the second parameter corresponding to the plurality of oil products based on parameters uploaded on a conveying end of the oil products; and uploading the obtained first parameter and the second parameter to a processor.

[0006] Optionally, after obtaining the first parameter and / or the second parameter and / or the third parameter, the method further comprises: preprocessing the first parameter and / or the second parameter and / or the third parameter, storing the preprocessed first parameter and / or the second parameter and / or the third parameter into corresponding databases respectively, and marking the databases.

[0007] Optionally, determining the probability value of triggering the corrosion risk of the conveying pipeline based on the first parameter and the second parameter comprises: defining a parameter set corresponding to the first parameter as , defining a parameter set corresponding to the second parameter as , calculating a first corrosion coefficient based on the parameter set corresponding to the first parameter, and calculating a second corrosion coefficient based on the parameter set corresponding to the second parameter; wherein the calculation method of the first corrosion coefficient comprises:

[0008] ;

[0009] wherein, represents the first corrosion coefficient, represents the number of physical property parameters in the parameter set, represents the corrosion resistance of the th physical property, represents the physical property deviation coefficient, represents the chemical property deviation coefficient, represents the number of chemical property parameters in the parameter set, represents the stability coefficient of the th chemical property, ; wherein the calculation method of the second corrosion coefficient comprises:

[0010] ;

[0011] wherein, represents the second corrosion coefficient, represents the adjustment function, represents the number of parameters in the parameter set, represents the corrosion degree of the th physical property parameter, represents the corrosion degree of the The corrosivity coefficients of each chemical component parameter are determined; based on the first corrosion coefficient and the second corrosion coefficient, the probability value for triggering corrosion risk in the transport pipeline is determined.

[0012] Optionally, determining the probability value that triggers corrosion risk in the transport pipeline based on the first corrosion coefficient and the second corrosion coefficient includes: inputting the first corrosion coefficient and the second corrosion coefficient into a probability value calculation function to determine the probability value that triggers corrosion risk in the transport pipeline, wherein the probability value calculation function includes:

[0013] ;

[0014] ;

[0015] in, Represents the probability value. Represents constant coefficients. Indicates time, express The cumulative number of oil product switching times at any given moment. Represents a probability function. This represents the sum of the database tag values ​​corresponding to the parameters; the probability value is defined as the probability value that triggers the corrosion risk of the transport pipeline.

[0016] Optionally, in response to the probability value being greater than a first preset threshold, obtaining the third parameter corresponding to the target time node includes: comparing the probability value with the first preset threshold; and in response to the probability value being greater than the first preset threshold, obtaining the third parameter corresponding to the target time node based on the geographical location of the transport pipeline.

[0017] Optionally, determining the corrosion degree of the transport pipeline at the target time node based on the first parameter, the second parameter, and the third parameter includes: defining the parameter set corresponding to the third parameter as follows: The third corrosion coefficient is calculated and determined based on the parameter set corresponding to the third parameter. The calculation method for the third corrosion coefficient includes:

[0018] ;

[0019] in, Indicates the third corrosion coefficient. Indicates the first The corrosivity coefficient of each environmental parameter. The number of parameters is indicated; based on the first corrosion coefficient corresponding to the first parameter, the second corrosion coefficient corresponding to the second parameter, and the third corrosion coefficient corresponding to the third parameter, the corrosion degree of the transport pipeline at the target time node is determined.

[0020] Optionally, the determining the corrosion degree of the transportation pipeline at the target time node based on the first corrosion coefficient corresponding to the first parameter, the second corrosion coefficient corresponding to the second parameter, and the third corrosion coefficient corresponding to the third parameter comprises: inputting the first corrosion coefficient, the second corrosion coefficient, and the third corrosion coefficient into a corrosion degree evaluation model, and determining the corrosion degree of the transportation pipeline at the target time node based on an output value of the corrosion degree evaluation model, wherein the corrosion degree evaluation model comprises:

[0021] ;

[0022] wherein, represents a model output value, represents an adjustment constant, represents an evaluation function.

[0023] Optionally, the determining the corrosion rate of the multi-oil product transportation pipeline in the target time period composed of the plurality of target time nodes based on the corrosion degrees of the transportation pipeline at the plurality of target time nodes comprises: determining the corrosion rate of the multi-oil product transportation pipeline in the target time period composed of the plurality of target time nodes based on the corrosion degrees of the transportation pipeline at the plurality of target time nodes and time intervals between the plurality of target nodes.

[0024] Optionally, the method further comprises: evaluating a service life of the transportation pipeline based on the corrosion rate of the multi-oil product transportation pipeline in the target time period; and sending early warning information to a terminal in response to the service life being less than or equal to a second preset threshold.

[0025] In a second aspect, a computer device is provided, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the following steps when executing the computer program: obtaining a first parameter corresponding to a transportation pipeline and a second parameter corresponding to a plurality of oil products, wherein the first parameter at least comprises parameters for describing physical properties and chemical properties of the transportation pipeline, and the second parameter at least comprises parameters for describing physical properties and chemical components of the oil products; determining a probability value of triggering a corrosion risk of the transportation pipeline based on the first parameter and the second parameter; in response to the probability value being greater than a first preset threshold, obtaining a third parameter corresponding to a target time node, wherein the third parameter is used to describe environmental parameters of a location where the transportation pipeline is located; determining a corrosion degree of the transportation pipeline at the target time node based on the first parameter, the second parameter, and the third parameter; and determining a corrosion rate of a multi-oil product transportation pipeline in a target time period composed of a plurality of target time nodes based on the corrosion degrees of the transportation pipeline at the plurality of target time nodes.

[0026] In a third aspect, a computer readable storage medium is provided, and a computer program is stored on the computer readable storage medium. The computer program, when executed by a processor, implements the following steps: obtaining a first parameter corresponding to a conveying pipeline and a second parameter corresponding to a plurality of oil products, wherein the first parameter at least includes a parameter for describing a physical property and a chemical property of the conveying pipeline, and the second parameter at least includes a parameter for describing a physical property and a chemical composition of the oil product; determining a probability value of triggering a corrosion risk of the conveying pipeline based on the first parameter and the second parameter; in response to the probability value being greater than a first preset threshold, obtaining a third parameter corresponding to a target time node, wherein the third parameter is used to describe an environmental parameter of a location where the conveying pipeline is located; determining a corrosion degree of the conveying pipeline at the target time node based on the first parameter, the second parameter, and the third parameter; and determining a corrosion rate of the conveying pipeline for the plurality of oil products in a target time period composed of a plurality of target time nodes according to the corrosion degrees of the conveying pipeline at the plurality of target time nodes.

[0027] In a fourth aspect, a computer program product is provided, and the computer program product includes a computer program. The computer program, when executed by a processor, implements the following steps: obtaining a first parameter corresponding to a conveying pipeline and a second parameter corresponding to a plurality of oil products, wherein the first parameter at least includes a parameter for describing a physical property and a chemical property of the conveying pipeline, and the second parameter at least includes a parameter for describing a physical property and a chemical composition of the oil product; determining a probability value of triggering a corrosion risk of the conveying pipeline based on the first parameter and the second parameter; in response to the probability value being greater than a first preset threshold, obtaining a third parameter corresponding to a target time node, wherein the third parameter is used to describe an environmental parameter of a location where the conveying pipeline is located; determining a corrosion degree of the conveying pipeline at the target time node based on the first parameter, the second parameter, and the third parameter; and determining a corrosion rate of the conveying pipeline for the plurality of oil products in a target time period composed of a plurality of target time nodes according to the corrosion degrees of the conveying pipeline at the plurality of target time nodes.

[0028] The above-mentioned data analysis-based multi-oil product pipeline corrosion rate prediction method comprises: acquiring a first parameter corresponding to the pipeline and a second parameter corresponding to the plurality of oil products, wherein the first parameter at least includes parameters for describing the physical properties and chemical properties of the pipeline, and the second parameter at least includes parameters for describing the physical properties and chemical components of the oil products; based on the first parameter and the second parameter, a probability value of exciting the corrosion risk of the pipeline is determined; in response to the probability value being greater than a first preset threshold, a third parameter corresponding to a target time node is acquired, the third parameter being used to describe the environmental parameters of the position where the pipeline is located; based on the first parameter, the second parameter and the third parameter, the corrosion degree of the pipeline at the target time node is determined; and according to the corrosion degrees of the pipeline at a plurality of target time nodes, the corrosion rate of the multi-oil product pipeline in a target time period composed of the plurality of target time nodes is determined. The present application determines the corrosion rate of the pipeline by fusing a plurality of modal parameters such as the oil products, the pipeline and the environment, thereby improving the accuracy of the pipeline corrosion rate prediction. The residual life of the pipeline is evaluated by the pipeline corrosion rate, thereby improving the operability and accuracy of the corrosion residual life prediction. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1 An application environment diagram of the data analysis-based multi-oil product pipeline corrosion rate prediction method in one embodiment.

[0030] Figure 2 A flowchart of the data analysis-based multi-oil product pipeline corrosion rate prediction method in one embodiment.

[0031] Figure 3 An internal structure diagram of the computer device in one embodiment. DETAILED DESCRIPTION

[0032] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0033] It should be understood that, in the description of the present application, unless the context clearly requires otherwise, the terms "comprise", "comprise", and the like in the entire specification should be interpreted as inclusive rather than exclusive or exhaustive meaning; that is, as "including but not limited to".

[0034] It should also be understood that the terms "first", "second" and the like are used to describe purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0035] It should be noted that the terms "S1", "S2" and the like are only used for the purpose of describing the steps and do not specifically refer to the order or sequence, nor do they limit the present application. They are only used to facilitate the description of the method of the present application and cannot be understood as indicating the order of the steps. In addition, the technical solutions of various embodiments can be combined with each other, but it must be based on the realization of ordinary skilled in the art. When the combination of technical solutions contradicts each other or cannot be realized, it should be considered that the combination of technical solutions does not exist and is not within the protection scope required by the present application.

[0036] The method for predicting the corrosion rate of a multi-oil product pipeline based on data analysis provided by the present application can be applied to the application environment as shown in Figure 1 . Among them, the terminal 102 communicates with the data processing platform set on the server 104 through the network, wherein the terminal 102 can be but is not limited to various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices, and the server 104 can be realized by an independent server or a server cluster composed of multiple servers.

[0037] In one embodiment, as shown in Figure 2 , a method for predicting the corrosion rate of a multi-oil product pipeline based on data analysis is provided. Taking the terminal in Figure 1 as an example, the method includes the following steps:

[0038] S1: Obtain the first parameter corresponding to the pipeline and the second parameter corresponding to the plurality of oil products, wherein the first parameter at least includes the parameter for describing the physical property and chemical property of the pipeline, and the second parameter at least includes the parameter for describing the physical property and chemical composition of the oil product.

[0039] It should be noted that the physical property parameter of the pipeline can include density, mechanical property and thermal property, etc. The chemical property parameter of the pipeline can include corrosion resistance, etc. The physical property parameter of the oil product can include density and viscosity, etc. The chemical composition parameter of the oil product can include sulfur content, acid value, water content, etc. The parameter without specific numerical value can be evaluated and graded by expert experience to determine the parameter value for subsequent calculation, that is, its belonging grade is defined as the parameter value. The method for evaluating the grade based on expert experience is a common method, and its specific process is not described here.

[0040] In some specific embodiments, obtaining the first parameter and / or the second parameter includes: obtaining the first parameter corresponding to the conveying pipeline based on the design drawings of the conveying pipeline; obtaining the second parameter corresponding to the plurality of oil products based on the parameters uploaded from the oil conveying end; and uploading the obtained first parameter and second parameter to the processor. The design drawings can be obtained by the engineering department, and the oil conveying end is the starting end of oil conveying. The starting end can determine the specific oil product by manual uploading or machine detection, thereby determining its specific component parameter values. After obtaining the parameters, they can be uploaded to the processor for fusion processing.

[0041] In some specific embodiments, after obtaining the first parameter and / or the second parameter and / or the third parameter, the method further includes: preprocessing the first parameter and / or the second parameter and / or the third parameter, storing the preprocessed first parameter and / or the second parameter and / or the third parameter into corresponding databases respectively, and marking the databases. The preprocessing method includes data cleaning and normalization, which are common methods, and the specific process will not be described in detail here. Furthermore, the databases are marked using markers, which can be 1, 2, 3, etc.

[0042] S2: Based on the first parameter and the second parameter, determine the probability value that triggers the corrosion risk of the transport pipeline.

[0043] In some specific implementations, determining the probability value that triggers corrosion risk in the transport pipeline based on the first parameter and the second parameter includes: defining the parameter set corresponding to the first parameter as... Define the parameter set corresponding to the second parameter as follows: A first corrosion coefficient is calculated and determined based on the parameter set corresponding to the first parameter, and a second corrosion coefficient is calculated and determined based on the parameter set corresponding to the second parameter; wherein, the method for calculating the first corrosion coefficient includes:

[0044] ;

[0045] in, Indicates the first corrosion coefficient. This indicates the number of physical attribute parameters in the parameter set. Indicates the first Corrosion resistance, a physical property Indicates the physical property deviation coefficient. Indicates the chemical property deviation coefficient. This indicates the number of chemical property parameters in the parameter set. Indicates the first The stability coefficient of a chemical property The physical property deviation coefficient and the chemical property deviation coefficient are correction coefficients, and specific values can be determined through multiple experiments.

[0046] The calculation method of the second corrosion coefficient comprises:

[0047] ;

[0048] The second corrosion coefficient is represented by K2. The adjustment function is represented by f. The number of parameters in the parameter set is represented by N. The corrosion degree of the first physical property parameter is represented by K1. The corrosion degree of the first physical property parameter is represented by K1. The corrosion degree of the first physical property parameter is represented by K1. The corrosion degree of the first physical property parameter is represented by K1. The corrosion degree of the first physical property parameter is represented by K1.

[0049] Based on the first corrosion coefficient and the second corrosion coefficient, a probability value of triggering the corrosion risk of the conveying pipeline is determined, comprising: inputting the first corrosion coefficient and the second corrosion coefficient into a probability value calculation function to determine the probability value of triggering the corrosion risk of the conveying pipeline, the probability value calculation function comprising:

[0050] ;

[0051] ;

[0052] The probability value is represented by P. The constant coefficient is represented by C. The time is represented by t. The cumulative value of the oil product switching frequency at the time t is represented by S(t). The probability function is represented by f. The sum of the database mark values corresponding to the parameters is represented by Σ. The probability value is defined as the probability value of triggering the corrosion risk of the conveying pipeline. S3: In response to the probability value being greater than a first preset threshold, a third parameter corresponding to a target time node is obtained, the third parameter being used to describe an environmental parameter of a position where the conveying pipeline is located.

[0053] It should be noted that the first preset threshold can be set according to actual needs, and the third parameter can include temperature, humidity and other factors that affect the corrosion rate or factors that can cause the corrosion of the conveying pipeline.

[0054]

[0055] ​In some specific implementations, in response to the probability value being greater than a first preset threshold, obtaining the third parameter corresponding to the target time node includes: comparing the probability value with the first preset threshold; in response to the probability value being greater than the first preset threshold, obtaining the third parameter corresponding to the target time node based on the geographical location of the pipeline, wherein the third parameter can be obtained through weather forecasts or professional sensors in various locations.

[0056] S4: Based on the first parameter, the second parameter and the third parameter, determine the corrosion degree of the transport pipeline at the target time node.

[0057] In some specific implementations, this step specifically includes: defining the parameter set corresponding to the third parameter as... The third corrosion coefficient is calculated and determined based on the parameter set corresponding to the third parameter. The calculation method for the third corrosion coefficient includes:

[0058] ;

[0059] in, Indicates the third corrosion coefficient. Indicates the first The corrosivity coefficient of each environmental parameter. Indicates the number of parameters.

[0060] Determining the corrosion level of the pipeline at a target time point based on the first corrosion coefficient corresponding to the first parameter, the second corrosion coefficient corresponding to the second parameter, and the third corrosion coefficient corresponding to the third parameter includes: inputting the first corrosion coefficient, the second corrosion coefficient, and the third corrosion coefficient into a corrosion assessment model; and determining the corrosion level of the pipeline at the target time point based on the output value of the corrosion assessment model, wherein the corrosion assessment model includes:

[0061] ;

[0062] in, This represents the model output value. Represents the adjustment constant. Let represent the evaluation function, which, along with the probability function, is a linear function of the first order, such as y = kx + b, where y is the adjustment coefficient or evaluation coefficient, k is the weight coefficient, 1 / x is the total number of parameters, and b is the bias coefficient.

[0063] S5: Determine the corrosion rate of multi-oil product transportation pipelines within a target time period consisting of multiple target time nodes based on the corrosion degree of the transportation pipelines at multiple target time nodes.

[0064] In some embodiments, the step specifically comprises: determining the oil product pipeline corrosion rate in the target time period composed of the plurality of target time nodes according to the pipeline corrosion degrees of the plurality of target time nodes.

[0065] Determining the oil product pipeline corrosion rate in the target time period composed of the plurality of target time nodes according to the pipeline corrosion degrees of the plurality of target time nodes and the time intervals between the plurality of target nodes, that is, the ratio between the difference in pipeline corrosion degrees and the time interval.

[0066] In some embodiments, the method further comprises: based on the oil product pipeline corrosion rate in the target time period, evaluating the service life of the pipeline, that is, the time value at which the pipeline is damaged can be calculated and determined by the current thickness and the corrosion rate, and the calculation method is a commonly used method, and the specific process is not described here; and in response to the service life being less than or equal to a second preset threshold, sending a warning message to the terminal, wherein the second preset threshold can be set according to actual needs.

[0067] In the above-mentioned data analysis-based oil product pipeline corrosion rate prediction method, the method comprises: obtaining a first parameter corresponding to the pipeline and a second parameter corresponding to a plurality of oil products, wherein the first parameter at least includes parameters for describing the physical properties and chemical properties of the pipeline, and the second parameter at least includes parameters for describing the physical properties and chemical components of the oil products; based on the first parameter and the second parameter, determining a probability value of triggering the corrosion risk of the pipeline; in response to the probability value being greater than a first preset threshold, obtaining a third parameter corresponding to a target time node, wherein the third parameter is used to describe the environmental parameters of the position where the pipeline is located; based on the first parameter, the second parameter and the third parameter, determining the pipeline corrosion degree of the target time node; and determining the oil product pipeline corrosion rate in the target time period composed of the plurality of target time nodes according to the pipeline corrosion degrees of the plurality of target time nodes. The present application determines the pipeline corrosion rate by fusing a plurality of oil products, pipelines and environmental parameters, thereby improving the accuracy of the pipeline corrosion rate prediction, and improving the operability and accuracy of the corrosion residual life prediction by evaluating the residual life of the pipeline based on the pipeline corrosion rate.

[0068] It should be understood that, although Figure 2 The steps in the flowchart of FIG. 1 are displayed in sequence according to the direction of the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, Figure 2At least one part of the steps in the method can include a plurality of sub-steps or a plurality of stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of the sub-steps or stages is not necessarily sequential, but can be alternately or alternately executed with other steps or sub-steps or stages of other steps.

[0069] In one embodiment, a computer device, which can be a terminal, is provided, and an internal structure diagram of the computer device can be as shown in Figure 3 The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The network interface of the computer device is configured to communicate with external terminals through network connection. The computer program is executed by the processor to implement a method for predicting corrosion rate of multi-oil product pipeline based on data analysis. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0070] Those skilled in the art can understand that Figure 3 The structure shown in the above embodiment is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0071] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it performs the following steps: S1: acquiring a first parameter corresponding to the transport pipeline and a second parameter corresponding to multiple oil products, wherein the first parameter includes at least parameters describing the physical and chemical properties of the transport pipeline, and the second parameter includes at least parameters describing the physical properties and chemical composition of the oil products; S2: determining a probability value that triggers corrosion risk in the transport pipeline based on the first parameter and the second parameter; S3: in response to the probability value being greater than a first preset threshold, acquiring a third parameter corresponding to a target time node, wherein the third parameter describes the environmental parameters of the location of the transport pipeline; S4: determining the corrosion degree of the transport pipeline at the target time node based on the first parameter, the second parameter, and the third parameter; S5: determining the corrosion rate of the multi-oil product transport pipeline within a target time period consisting of multiple target time nodes based on the corrosion degree of the transport pipeline at multiple target time nodes.

[0072] In one embodiment, when the processor executes the computer program, it further performs the following steps: based on the design drawings of the conveying pipeline, it obtains the first parameter corresponding to the conveying pipeline; based on the parameters uploaded by the conveying end of the oil, it obtains the second parameter corresponding to the plurality of oil products; and uploads the obtained first parameter and second parameter to the processor.

[0073] In one embodiment, when the processor executes the computer program, it further performs the following steps: preprocessing the first parameter and / or the second parameter and / or the third parameter, storing the preprocessed first parameter and / or the second parameter and / or the third parameter into the corresponding databases respectively, and marking the databases.

[0074] In one embodiment, when the processor executes the computer program, it further performs the following steps: defining the parameter set corresponding to the first parameter as... Define the parameter set corresponding to the second parameter as follows: A first corrosion coefficient is calculated and determined based on the parameter set corresponding to the first parameter, and a second corrosion coefficient is calculated and determined based on the parameter set corresponding to the second parameter; wherein, the method for calculating the first corrosion coefficient includes:

[0075] ;

[0076] in, Indicates the first corrosion coefficient. This indicates the number of physical attribute parameters in the parameter set. Indicates the first Corrosion resistance, a physical property Indicates the physical property deviation coefficient. represents a chemical property deviation coefficient, represents a number of chemical property parameters in a parameter set, represents a stability coefficient of the th chemical property, ; wherein the calculation method of the second corrosion coefficient comprises:

[0077] ;

[0078] wherein, represents a second corrosion coefficient, represents an adjustment function, represents a number of parameters in a parameter set, represents a corrosion degree of the th physical property parameter, represents a corrosion degree of the th chemical component parameter; and based on the first corrosion coefficient and the second corrosion coefficient, a probability value of triggering a corrosion risk of the conveying pipeline is determined.

[0079] In one embodiment, when the processor executes the computer program, the following steps are also implemented: inputting the first corrosion coefficient and the second corrosion coefficient into a probability value calculation function to determine the probability value of triggering the corrosion risk of the conveying pipeline, wherein the probability value calculation function comprises:

[0080] ;

[0081] ;

[0082] wherein, represents a probability value, represents a constant coefficient, represents time, represents an accumulated value of oil product switching times at the th moment, represents a probability function, represents a sum of database marker values corresponding to the parameters; and the probability value is defined as the probability value of triggering the corrosion risk of the conveying pipeline.

[0083] In one embodiment, when the processor executes the computer program, the following steps are also implemented: comparing the probability value with a first preset threshold value; and in response to the probability value being greater than the first preset threshold value, acquiring a third parameter corresponding to a target time node according to a geographical location of the conveying pipeline.

[0084] In one embodiment, when the processor executes the computer program, the following steps are also implemented: defining a parameter set corresponding to the third parameter as , the third corrosion coefficient is determined based on a parameter set corresponding to the third parameter, and a calculation method of the third corrosion coefficient comprises:

[0085] ;

[0086] wherein, denotes the third corrosion coefficient, denotes a corrosion coefficient of the first environmental parameter, denotes a corrosion coefficient of the second environmental parameter, and denotes a number of parameters; based on the first corrosion coefficient corresponding to the first parameter, the second corrosion coefficient corresponding to the second parameter, and the third corrosion coefficient corresponding to the third parameter, a corrosion degree of the transportation pipeline at the target time node is determined.

[0087] In an embodiment, when the processor executes the computer program, the following steps are also implemented: the first corrosion coefficient, the second corrosion coefficient, and the third corrosion coefficient are input into a corrosion degree evaluation model, and based on an output value of the corrosion degree evaluation model, a corrosion degree of the transportation pipeline at the target time node is determined, wherein the corrosion degree evaluation model comprises:

[0088] ;

[0089] wherein, denotes the model output value, denotes an adjustment constant, denotes an evaluation function.

[0090] In an embodiment, when the processor executes the computer program, the following steps are also implemented: based on the corrosion degrees of the transportation pipeline at the plurality of target time nodes and time intervals between the plurality of target nodes, a corrosion rate of the multi-oil product transportation pipeline in a target time period composed of the plurality of target time nodes is determined.

[0091] In an embodiment, when the processor executes the computer program, the following steps are also implemented: based on the corrosion rate of the multi-oil product transportation pipeline in the target time period, a service life of the transportation pipeline is evaluated; and in response to the service life being less than or equal to a second preset threshold, warning information is sent to the terminal.

[0092] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it performs the following steps: S1: Obtaining a first parameter corresponding to the transport pipeline and a second parameter corresponding to multiple oil products, wherein the first parameter includes at least parameters for describing the physical and chemical properties of the transport pipeline, and the second parameter includes at least parameters for describing the physical properties and chemical composition of the oil products; S2: Determining a probability value that triggers corrosion risk in the transport pipeline based on the first parameter and the second parameter; S3: In response to the probability value being greater than a first preset threshold, obtaining a third parameter corresponding to a target time node, wherein the third parameter describes the environmental parameters of the location of the transport pipeline; S4: Determining the corrosion degree of the transport pipeline at the target time node based on the first parameter, the second parameter, and the third parameter; S5: Determining the corrosion rate of the multi-oil product transport pipeline within a target time period consisting of multiple target time nodes based on the corrosion degree of the transport pipeline at multiple target time nodes.

[0093] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining a first parameter corresponding to the conveying pipeline based on the design drawings of the conveying pipeline; obtaining a second parameter corresponding to the plurality of oil products based on the parameters uploaded by the oil conveying end; and uploading the obtained first parameter and second parameter to the processor.

[0094] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: preprocessing the first parameter and / or the second parameter and / or the third parameter, storing the preprocessed first parameter and / or the second parameter and / or the third parameter into the corresponding databases respectively, and marking the databases.

[0095] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: defining the parameter set corresponding to the first parameter as... Define the parameter set corresponding to the second parameter as follows: A first corrosion coefficient is calculated and determined based on the parameter set corresponding to the first parameter, and a second corrosion coefficient is calculated and determined based on the parameter set corresponding to the second parameter; wherein, the method for calculating the first corrosion coefficient includes:

[0096] ;

[0097] in, Indicates the first corrosion coefficient. This indicates the number of physical attribute parameters in the parameter set. Indicates the first Corrosion resistance, a physical property Indicates the physical property deviation coefficient. Indicates the chemical property deviation coefficient. This indicates the number of chemical property parameters in the parameter set. Indicates the first The stability coefficient of a chemical property The calculation method for the second corrosion coefficient includes:

[0098] ;

[0099] in, This represents the second corrosion coefficient. Represents the adjustment function. This indicates the number of parameters in the parameter set. Indicates the first Corrosion degree, a physical property parameter Indicates the first The corrosivity coefficients of each chemical component parameter are determined; based on the first corrosion coefficient and the second corrosion coefficient, the probability value for triggering corrosion risk in the transport pipeline is determined.

[0100] In one embodiment, when the computer program is executed by a processor, it further performs the following steps: inputting the first corrosion coefficient and the second corrosion coefficient into a probability value calculation function to determine the probability value that triggers corrosion risk in the transport pipeline, the probability value calculation function including:

[0101] ;

[0102] ;

[0103] in, Represents the probability value. Represents constant coefficients. Indicates time, express The cumulative number of oil product switching times at any given moment. Represents a probability function. This represents the sum of the database tag values ​​corresponding to the parameters; the probability value is defined as the probability value that triggers the corrosion risk of the transport pipeline.

[0104] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: comparing the probability value with a first preset threshold; and in response to the probability value being greater than the first preset threshold, obtaining a third parameter corresponding to the target time node based on the geographical location of the delivery pipeline.

[0105] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: defining the parameter set corresponding to the third parameter as... , and determining a third corrosion coefficient based on a parameter set corresponding to the third parameter, wherein the method for calculating the third corrosion coefficient comprises:

[0106] ;

[0107] wherein, represents the third corrosion coefficient, represents a corrosion coefficient of the first environmental parameter, represents a corrosion coefficient of the second environmental parameter, and represents a number of parameters; and determining the corrosion degree of the transportation pipeline at the target time node based on the first corrosion coefficient corresponding to the first parameter, the second corrosion coefficient corresponding to the second parameter, and the third corrosion coefficient corresponding to the third parameter.

[0108] In one embodiment, the computer program, when executed by the processor, further implements the following steps: inputting the first corrosion coefficient, the second corrosion coefficient, and the third corrosion coefficient into a corrosion degree evaluation model, and determining the corrosion degree of the transportation pipeline at the target time node based on an output value of the corrosion degree evaluation model, wherein the corrosion degree evaluation model comprises:

[0109] ;

[0110] wherein, represents the model output value, represents an adjustment constant, represents an evaluation function.

[0111] In one embodiment, the computer program, when executed by the processor, further implements the following steps: determining a corrosion rate of the multi-oil product transportation pipeline in a target time period composed of the plurality of target time nodes based on the corrosion degrees of the transportation pipeline at the plurality of target time nodes and time intervals between the plurality of target nodes.

[0112] In one embodiment, the computer program, when executed by the processor, further implements the following steps: evaluating a service life of the transportation pipeline based on the corrosion rate of the multi-oil product transportation pipeline in the target time period; and sending a warning message to a terminal in response to the service life being less than or equal to a second preset threshold.

[0113] In one embodiment, a computer program product is provided, which comprises a computer program, the computer program, when executed by a processor, implements the following steps: S1: acquiring a first parameter corresponding to a conveying pipeline and a second parameter corresponding to a plurality of oil products, the first parameter at least including a parameter for describing physical properties and chemical properties of the conveying pipeline, and the second parameter at least including a parameter for describing physical properties and chemical components of the oil products; S2: determining a probability value of triggering a corrosion risk of the conveying pipeline based on the first parameter and the second parameter; S3: in response to the probability value being greater than a first preset threshold, acquiring a third parameter corresponding to a target time node, the third parameter being used to describe an environmental parameter of a location where the conveying pipeline is located; S4: determining a corrosion degree of the conveying pipeline at the target time node based on the first parameter, the second parameter and the third parameter; and S5: determining a corrosion rate of the plurality of oil products conveying pipelines in a target time period composed of a plurality of target time nodes according to the corrosion degrees of the conveying pipelines at the plurality of target time nodes.

[0114] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by a computer program instructing related hardware, and the computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, the computer program can include the processes of the above-mentioned embodiments. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct RAM bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM).

[0115] The technical features of the above embodiments can be combined in any manner. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present disclosure.

[0116] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be noted that for ordinary skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which are within the scope of protection of the present application.

Claims

1. A method for predicting corrosion rates in multi-oil pipelines based on data analysis, characterized in that, The method includes: Obtain a first parameter corresponding to the transport pipeline and a second parameter corresponding to multiple oil products. The first parameter includes at least parameters for describing the physical and chemical properties of the transport pipeline, and the second parameter includes at least parameters for describing the physical properties and chemical composition of the oil products. Based on the first parameter and the second parameter, determine the probability value that triggers the corrosion risk of the transport pipeline; In response to the probability value being greater than a first preset threshold, a third parameter corresponding to the target time node is obtained, the third parameter being used to describe the environmental parameters of the location of the delivery pipeline; Based on the first parameter, the second parameter, and the third parameter, the corrosion level of the transport pipeline at the target time point is determined; Based on the corrosion rate of the pipeline at multiple target time points, determine the corrosion rate of the multi-oil pipeline within a target time period consisting of multiple target time points; Based on the first parameter and the second parameter, the probability value for inducing corrosion risk in the transport pipeline is determined as follows: Define the parameter set corresponding to the first parameter as follows: Define the parameter set corresponding to the second parameter as follows: The first corrosion coefficient is calculated and determined based on the parameter set corresponding to the first parameter, and the second corrosion coefficient is calculated and determined based on the parameter set corresponding to the second parameter. The method for calculating the first corrosion coefficient includes: ； in, Indicates the first corrosion coefficient. This indicates the number of physical attribute parameters in the parameter set. Indicates the first Corrosion resistance, a physical property Indicates the physical property deviation coefficient. Indicates the chemical property deviation coefficient. This indicates the number of chemical property parameters in the parameter set. Indicates the first The stability coefficient of a chemical property ; The calculation method for the second corrosion coefficient includes: ； in, This represents the second corrosion coefficient. Represents the adjustment function. This indicates the number of parameters in the parameter set. Indicates the first Corrosion degree, a physical property parameter Indicates the first Corrosion coefficient of each chemical component parameter; Based on the first corrosion coefficient and the second corrosion coefficient, the probability value of triggering corrosion risk in the transport pipeline is determined; Based on the first corrosion coefficient and the second corrosion coefficient, the probability value for inducing corrosion risk in the transport pipeline is determined as follows: The first corrosion coefficient and the second corrosion coefficient are input into a probability value calculation function to determine the probability value that triggers corrosion risk in the pipeline. The probability value calculation function includes: ； ； in, Represents the probability value. Represents constant coefficients. Indicates time, express The cumulative number of oil product switching times at any given moment. Represents a probability function. This represents the sum of the database tag values ​​corresponding to the parameters; The probability value is defined as the probability value that triggers the corrosion risk of the transport pipeline.

2. The method for predicting corrosion rates of multi-oil pipelines based on data analysis according to claim 1, characterized in that, Obtaining the first parameter and / or the second parameter includes: Based on the design drawings of the conveying pipeline, obtain the first parameter corresponding to the conveying pipeline; Based on the parameters uploaded from the oil delivery end, the second parameters corresponding to the multiple oil products are obtained; The first and second parameters obtained are uploaded to the processor.

3. The method for predicting corrosion rates of multi-oil pipelines based on data analysis according to claim 2, characterized in that, After obtaining the first parameter and / or the second parameter and / or the third parameter, the method further includes: The first parameter and / or the second parameter and / or the third parameter are preprocessed, and the preprocessed first parameter and / or the second parameter and / or the third parameter are stored in the corresponding databases, and the databases are marked.

4. The method for predicting corrosion rates of multi-oil pipelines based on data analysis according to claim 3, characterized in that, In response to the probability value being greater than a first preset threshold, the third parameter corresponding to the target time node is obtained, including: The probability value is compared with a first preset threshold. In response to the probability value being greater than a first preset threshold, a third parameter corresponding to the target time node is obtained based on the geographical location of the transport pipeline.

5. The method for predicting corrosion rates of multi-oil pipelines based on data analysis according to claim 4, characterized in that, Based on the first parameter, the second parameter, and the third parameter, determining the corrosion level of the pipeline at the target time point includes: Define the parameter set corresponding to the third parameter as follows: The third corrosion coefficient is calculated and determined based on the parameter set corresponding to the third parameter. The calculation method for the third corrosion coefficient includes: ； in, Indicates the third corrosion coefficient. Indicates the first The corrosivity coefficient of each environmental parameter. Indicates the number of parameters; Based on the first corrosion coefficient corresponding to the first parameter, the second corrosion coefficient corresponding to the second parameter, and the third corrosion coefficient corresponding to the third parameter, the corrosion degree of the transport pipeline at the target time node is determined.

6. The method for predicting the corrosion rate of multi-oil pipelines based on data analysis according to claim 5, characterized in that, Based on the first corrosion coefficient corresponding to the first parameter, the second corrosion coefficient corresponding to the second parameter, and the third corrosion coefficient corresponding to the third parameter, the corrosion degree of the transport pipeline at the target time node is determined as follows: The first corrosion coefficient, the second corrosion coefficient, and the third corrosion coefficient are input into the corrosion assessment model. Based on the output value of the corrosion assessment model, the corrosion degree of the transport pipeline at the target time point is determined. The corrosion assessment model includes: ； in, This represents the model output value. Represents the adjustment constant. This represents the evaluation function.

7. The method for predicting corrosion rates of multi-oil pipelines based on data analysis according to claim 6, characterized in that, Based on the corrosion rate of the pipeline at multiple target time points, the corrosion rate of the multi-oil pipeline within a target time period consisting of multiple target time points is determined, including: Based on the corrosion rate of the pipeline at the multiple target time points and the time interval between the multiple target time points, the corrosion rate of the multi-oil pipeline within the target time period consisting of multiple target time points is determined.

8. The method for predicting corrosion rates of multi-oil pipelines based on data analysis according to claim 7, characterized in that, The method further includes: The service life of the pipeline is evaluated based on the corrosion rate of the multi-oil pipeline within the target time period. When the service life is less than or equal to a second preset threshold, a warning message is sent to the terminal.

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