Intelligent batching and identification tracking method for oil and gas module prefabricated pipeline

Abstract

The invention discloses an oil and gas module prefabricated pipeline intelligent batching and identification tracking method, which comprises the following steps: establishing an overall three-dimensional model of an oil and gas module, extracting a pipeline model, carrying out classification preprocessing on the pipeline model according to purposes to obtain pipeline models with different purposes, and importing the pipeline models into pipeline information database software. And comparing the geometric dimensions of the pipeline models with the geometric dimensions of the pipeline raw materials one by one by adopting an ant colony algorithm to obtain a technical scheme that each pipeline raw material can process the most pipeline models, and displaying a real-time progress deviation value of the prefabricated pipeline in real time in a computer through an electronic tag. The information of the prefabricated pipeline is identified and tracked, the construction progress data of the oil and gas module prefabricated pipeline can be monitored in real time, the real-time performance is high, the engineering cost is low, and it is guaranteed that the production information data of the oil and gas module prefabricated pipeline can be rapidly displayed in real time.

Description

Technical Field

[0001] The invention relates to a method for processing prefabricated pipelines on an oil platform, and in particular to an intelligent batching and identification tracking method for prefabricated pipelines of oil and gas modules. Background Art

[0002] The structure of the oil and gas module is an upper and lower layered structure. A large number of pipelines are required during the construction process. These pipelines usually need to be prefabricated first, and then distributed to storage sites for storage, and then transported to the construction site when needed. The existing pipeline batching and identification tracking method uses manual marking to record relevant information on the prefabricated pipeline, which can easily lead to information confusion of the prefabricated pipeline, and the construction process of the prefabricated pipeline cannot be tracked during the transportation of the pipeline; secondly, during the prefabrication process of the pipeline, some surplus materials cannot be reasonably utilized, resulting in a large amount of material waste, which increases the construction cost of the oil and gas module. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and provide an intelligent batching and identification tracking method for prefabricated pipelines of oil and gas modules, so that the raw materials of prefabricated pipelines can be rationally utilized, the construction process of prefabricated pipelines can be tracked in real time, and the construction efficiency of oil and gas modules can be improved.

[0004] The present invention provides an intelligent batching and identification tracking method for oil and gas module prefabricated pipelines, comprising the following steps:

[0005] Step 1: Establish an overall 3D model of the oil and gas module in 3D software;

[0006] Step 2: extract the pipeline model from the overall three-dimensional model of the oil and gas module, classify and preprocess the pipeline model according to its purpose to obtain pipeline models of different purposes, and then number the pipeline models of different purposes in sequence according to the set order, and then sub-number the pipeline models of the same purpose from small to large according to the construction order, and record the geometric size information and remarks of the pipeline model corresponding to each sub-category numbered pipeline model in the data table;

[0007] Step 3: Import all the data in the data table into the pipeline information database software;

[0008] Step 4: Data of m types of pipeline raw materials (l j , r j ) is input into the pipeline information database software of step 3, and the m kinds of raw materials are arranged in order from small to large according to the length of the pipeline raw materials; l j is the length of the jth pipeline raw material, r j is the radius of the jth pipeline raw material;

[0009] Step 5: Input the geometric dimensions of the pipeline model and the geometric dimensions of the pipeline raw material into the ant colony algorithm respectively, call the update_operator function in the ant colony algorithm, compare the geometric dimensions of the pipeline model with the geometric dimensions of the pipeline raw material one by one, and obtain the technical solution that can process the most pipeline models from each pipeline raw material;

[0010] Step 6: Select the pipeline raw material processing plan with the least remaining length of each pipeline raw material processing plan as the optimized pipeline processing plan, and output the pipeline processing plan;

[0011] Step 7: According to the processing plan of each pipeline raw material obtained in step 6, the pipeline raw materials are processed on site according to the geometric dimensions of the pipeline model to obtain prefabricated pipelines, and then electronic tags are attached to each section of the prefabricated pipeline and the information of each section of the prefabricated pipeline on the electronic tags is transmitted to the computer;

[0012] Step 8: The computer uses GEPHI to establish the construction progress correlation between the prefabricated pipeline and the construction schedule based on the data information in the electronic tag, and displays the actual construction period of the prefabricated pipeline in real time on the computer, and compares the actual construction period of the prefabricated pipeline with the set construction period to output the real-time progress deviation value;

[0013] Step nine, set the allowable progress deviation value Q(i) in the computer, compare the real-time progress deviation ΔQ(i) with the set allowable progress deviation value Q(i), if ΔQ(i) ≥ Q(i), it means that the construction process of the prefabricated pipeline is normal, and the prefabricated pipeline is marked as green, otherwise the prefabricated pipeline is marked as red, indicating construction delay.

[0014] The beneficial effects of the present invention are as follows: the present invention reasonably mixes the raw materials of the prefabricated pipeline, so that the raw materials of the prefabricated pipeline are rationally utilized, and at the same time the information of the prefabricated pipeline can be identified and tracked through electronic tags, so that the construction progress data of the oil and gas module prefabricated pipeline can be monitored in real time, with strong real-time performance and low engineering cost, thereby ensuring that the production information data of the oil and gas module prefabricated pipeline can be displayed in real time and quickly, and realizing real-time tracking of the production information of the oil and gas module prefabricated pipeline, reducing the time spent on querying information and improving the overall construction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The present invention is a flow chart of a method for intelligent batching and identification and tracking of oil and gas module prefabricated pipelines. DETAILED DESCRIPTION

[0016] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments:

[0017] like Figure 1 The method for intelligent batching and identification tracking of oil and gas module prefabricated pipelines of the present invention includes the following steps:

[0018] Step 1: Establish an overall 3D model of the oil and gas module in 3D software;

[0019] Step 2: extract the pipeline model from the overall three-dimensional model of the oil and gas module, classify and preprocess the pipeline model according to its purpose to obtain pipeline models of different purposes, and then number the pipeline models of different purposes in sequence according to the set order, and then sub-number the pipeline models of the same purpose from small to large according to the construction order, and record the geometric size information and remarks of the pipeline model corresponding to each sub-category numbered pipeline model in the data table. The specific steps are:

[0020] The first step is to classify and number the pipeline models according to their uses, such as domestic water pipelines (such as: 1), condensing water pipelines (such as: 2), etc.

[0021] The second step is to number the classified pipeline models in sequence according to their respective construction order (such as: 1.X), and record the pipeline model geometric size information and remarks corresponding to the pipeline model with the number, such as: pipeline model length information L x , the radius of the pipeline R x And the remark information DX, the remark information is usually the processing method such as welding, cutting, grinding, etc.;

[0022] The third step is to export the sub-category number of the pipeline model and the pipeline model geometric dimension information and remark information of the pipeline model corresponding to the sub-category number, and record them in a data table.

[0023] Step 3: Import all the data in the data table into the pipeline information database software;

[0024] Step 4: Data of m types of pipeline raw materials (l j , r j ) is input into the pipeline information database software in step 3, and the m raw materials are arranged in order from small to large according to the length of the pipeline raw materials, recorded as {(l1, r1), (l2, r2)…(l j , r j ), (l m , r m )};l j is the length of the jth pipeline raw material, r j is the radius of the jth pipeline raw material;

[0025] Step 5: Input the geometric dimensions of the pipeline model and the geometric dimensions of the pipeline raw material into the ant colony algorithm respectively, call the update_operator function in the ant colony algorithm, compare the geometric dimensions of the pipeline model with the geometric dimensions of the pipeline raw material one by one, and obtain the technical solution that can process the most pipeline models from each pipeline raw material;

[0026] Step 6: Select the pipeline raw material processing plan with the least remaining length of each pipeline raw material processing plan as the optimized pipeline processing plan, and output the pipeline processing plan;

[0027] Step 7: According to the processing plan of each pipeline raw material obtained in step 6, the pipeline raw materials are processed on site according to the geometric dimensions of the pipeline model to obtain prefabricated pipelines, and then electronic tags are attached to each section of the prefabricated pipeline and the information of each section of the prefabricated pipeline on the electronic tags is transmitted to the computer. The electronic tags include the type number NO.X, the geometric dimension information B(L x (prefabricated pipeline length information), R x (radius size of prefabricated pipeline)) and remarks information DX.

[0028] Step 8: The computer uses GEPHI to establish the construction progress correlation between the prefabricated pipeline and the construction schedule based on the data information in the electronic tag, and displays the actual construction period of the prefabricated pipeline in real time on the computer, and compares the actual construction period of the prefabricated pipeline with the set construction period to output the real-time progress deviation value ΔQ(i). The process is as follows:

[0029] The first step is to establish a real-time construction table for existing projects and set the geometric dimension information BX of the prefabricated pipeline as the unique identifier for the search;

[0030] The second step is to set the real-time construction table for the installation of prefabricated pipelines, and calculate the progress deviation ΔQ(i) between the planned construction time Q1(i) and the real-time construction time Q2(i). The formula of the calculation function is:

[0031] ΔQ(i)=Q1(i)-Q2(i)

[0032] Where i represents the number of the prefabricated pipeline, Q1(i) represents the planned construction time of the prefabricated pipeline, Q2(i) represents the recorded real-time construction time of the prefabricated pipeline, and ΔQ(i) represents the real-time progress deviation value;

[0033] Step nine, set the allowable progress deviation value Q(i) in the computer, compare the real-time progress deviation ΔQ(i) with the set allowable progress deviation value Q(i), if ΔQ(i) ≥ Q(i), it means that the construction process of the prefabricated pipeline is normal, and the prefabricated pipeline is marked as green, otherwise the prefabricated pipeline is marked as red, indicating construction delay.

[0034] The above-described embodiments are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. An intelligent batching and identification tracking method for oil and gas module prefabricated pipelines, characterized in that: The following steps are involved: Step 1: Establish an overall 3D model of the oil and gas module in 3D software; Step 2: extract the pipeline model from the overall three-dimensional model of the oil and gas module, classify and preprocess the pipeline model according to its purpose to obtain pipeline models of different purposes, and then number the pipeline models of different purposes in sequence according to the set order, and then sub-number the pipeline models of the same purpose from small to large according to the construction order, and record the geometric size information and remarks of the pipeline model corresponding to each sub-category numbered pipeline model in the data table; Step 3: Import all the data in the data table into the pipeline information database software; Step 4: Data of m types of pipeline raw materials (l j , r j ) is input into the pipeline information database software of step 3, and the m kinds of raw materials are arranged in order from small to large according to the length of the pipeline raw materials; l j is the length of the jth pipeline raw material, r j is the radius of the jth pipeline raw material; Step 5: Input the geometric dimensions of the pipeline model and the geometric dimensions of the pipeline raw material into the ant colony algorithm respectively, call the update_operator function in the ant colony algorithm, compare the geometric dimensions of the pipeline model with the geometric dimensions of the pipeline raw material one by one, and obtain the technical solution that can process the most pipeline models from each pipeline raw material; Step 6: Select the pipeline raw material processing plan with the least remaining length of each pipeline raw material processing plan as the optimized pipeline processing plan, and output the pipeline processing plan; Step 7: According to the processing plan of each pipeline raw material obtained in step 6, the pipeline raw materials are processed on site according to the geometric dimensions of the pipeline model to obtain prefabricated pipelines, and then electronic tags are attached to each section of the prefabricated pipeline and the information of each section of the prefabricated pipeline on the electronic tags is transmitted to the computer; Step 8: The computer uses GEPHI to establish the construction progress correlation between the prefabricated pipeline and the construction schedule based on the data information in the electronic tag, and displays the actual construction period of the prefabricated pipeline in real time on the computer, and compares the actual construction period of the prefabricated pipeline with the set construction period to output the real-time progress deviation value; Step nine, set the allowable progress deviation value Q(i) in the computer, compare the real-time progress deviation ΔQ(i) with the set allowable progress deviation value Q(i), if ΔQ(i) ≥ Q(i), it means that the construction process of the prefabricated pipeline is normal, and the prefabricated pipeline is marked as green, otherwise the prefabricated pipeline is marked as red, indicating construction delay.

2. The intelligent batching and identification tracking method for oil and gas module prefabricated pipeline according to claim 1 is characterized by: The specific steps of step one are: The first step is to classify and number the pipeline models according to their uses; The second step is to sequentially number the classified pipeline models according to their respective construction sequences; and record the geometric dimension information and remarks of the pipeline models corresponding to the numbered pipeline models; The third step is to export the sub-category number of the pipeline model and the pipeline model geometric dimension information and remark information of the pipeline model corresponding to the sub-category number, and record them in a data table.

3. The intelligent batching and identification tracking method for oil and gas module prefabricated pipeline according to claim 1 is characterized by: The specific process of step eight is as follows: The first step is to establish a real-time construction table for existing projects and set the geometric size information of prefabricated pipelines as the unique identifier for search; The second step is to set the real-time construction table for the installation of prefabricated pipelines, and calculate the progress deviation ΔQ(i) between the planned construction time Q1(i) and the real-time construction time Q2(i). The formula of the calculation function is: ΔQ(i)=Q1(i)-Q2(i) Where i represents the number of the prefabricated pipeline, Q1(i) represents the planned construction time of the prefabricated pipeline, Q2(i) represents the recorded real-time construction time of the prefabricated pipeline, and ΔQ(i) represents the real-time progress deviation value.

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