Pipeline stress prediction method and device based on multi-source information fusion

Abstract

The invention relates to the technical field of oil and gas pipeline monitoring, in particular to a pipeline stress prediction method based on multi-source information fusion, and the method comprises the steps: S1, building a feature database which comprises the structural feature parameters of a monitored pipeline; s2, establishing a stress database, wherein the stress database comprises a stress threshold and a stress calculation formula corresponding to the structural characteristic parameters; s3, acquiring pipeline stress data and position information of each monitoring point; s4, determining structural characteristic parameters of the to-be-predicted pipe section; and S5, determining a stress threshold value and a stress calculation formula of the to-be-predicted pipe section, and performing calculation and judgment. According to the method, stress thresholds and stress calculation formulas under various structural characteristic parameters are fully considered, the actual stress of the to-be-predicted pipe section with special structural characteristics is obtained in a calculation mode, and then the operation condition of the pipeline is judged, so that the monitoring result can be closer to the actual condition, and the accuracy of the pipeline monitoring result is improved; and the pipeline stress at the non-monitoring point part is predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas pipeline monitoring, and in particular to a pipeline stress prediction method and device based on multi-source information fusion. Background Art

[0002] With the continuous development of my country's oil and gas pipeline construction projects, pipelines will inevitably pass through areas with complex topography. These areas are very prone to geological disasters, causing oil and gas pipelines to fail or even break and be damaged. In order to monitor the safety of pipelines in these areas, strain gauges are usually attached to the surface of the pipeline, and the stress conditions of the pipeline where the strain gauges are located are obtained by collecting strain data.

[0003] However, when there are special structural features such as welds and defects on the pipeline, stress concentration is more likely to occur at the special structural features. The stress value at the special structural features will be higher than that in the surrounding areas and it is more likely to be damaged. If only the stress data measured by the strain gauge is used as the action indicator, it will be impossible to accurately obtain the deformation of the pipeline at non-monitoring points, especially the strain conditions at the special structural features. If strain gauges are added separately at the special structural features for strain monitoring, the complexity of the monitoring system will increase, and the monitoring effect will be greatly affected by environmental factors.

[0004] Therefore, there is an urgent need for a technical solution to solve the technical problem that the existing buried pipeline stress monitoring does not fully consider the special structural characteristics of the pipeline, which affects the monitoring results. Summary of the invention

[0005] The purpose of the present invention is to provide a pipeline stress prediction method and device based on multi-source information fusion to address the technical problem that the existing buried pipeline stress monitoring does not fully consider the special structural characteristics of the pipeline, which affects the monitoring results.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A pipeline stress prediction method based on multi-source information fusion includes the following steps:

[0008] S1. Establishing a feature database, wherein the feature database includes structural feature parameters of the monitored pipeline;

[0009] S2. Establishing a stress database, wherein the stress database includes stress thresholds and stress calculation formulas corresponding to the structural characteristic parameters;

[0010] S3, obtaining pipeline stress data and location information of each monitoring point;

[0011] S4, determining the structural characteristic parameters of the pipe section to be predicted;

[0012] S5. Determine the stress threshold and stress calculation formula of the pipe section to be predicted, and perform calculation and judgment.

[0013] The present invention provides a pipeline stress prediction method based on multi-source information fusion. The monitored pipe section is a pipe section provided with stress monitoring equipment to form a plurality of monitoring points. The pipe section to be predicted is a pipe section located between adjacent or close monitoring points, which is a certain section in the monitored pipe section. The structural characteristic parameters of the pipe section to be predicted can be determined through the position information of the pipe section to be predicted at the monitoring point or the adjacent monitoring point. Then, the actual stress of the pipe section to be predicted with special structural characteristics can be obtained by calculation while fully considering the stress thresholds and stress calculation formulas under various structural characteristic parameters. Then, the operation status of the pipeline can be judged, so that the monitoring result can be closer to the actual situation, the accuracy of the pipeline monitoring result can be improved, and the prediction of the pipeline stress at the non-monitoring point can be realized.

[0014] As a preferred solution of the present invention, the structural characteristic parameters include pipeline parameters, defect parameters and weld parameters. The pipeline parameters include pipe type, pipeline diameter, pipeline type, pipeline wall thickness, pipeline mileage, and pressure; the defect parameters include defect type, defect location, and defect size; and the weld parameters include weld type and weld size. Pipeline parameters are used to express the influence of the pipeline itself on stress, defect parameters are used to express the influence of special structural features on the pipeline on the corresponding stress, and weld parameters are used to express the influence of welds on pipeline stress. For example, pipeline types include straight pipes, elbows, tees, and reducers. Defect types include pores, pits, undercuts, and cracks. Defect locations include the location of defects on the pipeline cross section and the mileage data of defects.

[0015] As a preferred solution of the present invention, in S5, the calculation includes substituting the larger value of the adjacent stress values ​​obtained at each monitoring point along the axial direction of the pipe section to be predicted into the stress calculation formula as the monitoring stress value, so as to obtain the maximum stress at the corresponding special structural feature.

[0016] As a preferred embodiment of the present invention, the stress calculation formula includes considering the actual pipeline stress as the product of the enhancement factor and the stress of the defect-free pipeline, the enhancement factor includes the influence function of the structural characteristic parameters on the pipeline stress, and the defect-free pipeline stress includes the maximum stress when there are no defects, welds, or variable cross-sections on the pipeline.

[0017] As a preferred solution of the present invention, the method for establishing the stress database includes:

[0018] S2.1. Establish a finite element model for pipeline stress analysis;

[0019] S2.2. Analyze the influence of structural characteristic parameters on stress threshold;

[0020] S2.3. Determine the factors affecting the stress of the monitored pipeline;

[0021] S2.4, calculation formula for fitting the effect of single factor on pipeline stress;

[0022] S2.5, fitting the calculation formula of the influence of multiple factors on pipeline stress;

[0023] S2.6. Express the calculation formulas of S2.4 and S2.5 using the stress calculation formula for defect-free pipelines.

[0024] As a preferred solution of the present invention, S2.3 uses a linear regression method to determine the influencing factors of the monitored pipeline stress.

[0025] As a preferred solution of the present invention, the stress influencing factors determined by S2.3 ignore the secondary influencing factors and retain the main influencing factors, which include pipe material, pipe diameter, wall thickness and pressure.

[0026] As a preferred embodiment of the present invention, the stress calculation formula includes:

[0027] σ max =F[f(x,d,e,P),f(j,c,h)]×[σ] max ;

[0028] Where:

[0029] f(x,d,e,p) represents the influence function of pipe material, pipe diameter, wall thickness and pressure on pipeline stress, which is dimensionless;

[0030] f(j,c,h) represents the influence function of pipeline variable cross-section, defects, and welds on pipeline stress. It is rewritten as f(c) when only affected by defects, rewritten as f(c,h) when there are defects on the weld, and rewritten as f(j,h) when the pipeline has variable cross-section;

[0031] [σ] max Indicates stress of defect-free pipeline;

[0032] σ max Indicates the actual stress of the pipe.

[0033] A pipeline stress prediction device based on multi-source information fusion adopts the above pipeline stress prediction method based on multi-source information fusion, and includes:

[0034] Stress monitoring equipment, used to obtain pipeline stress data at each monitoring point;

[0035] Terminal server, with built-in feature database and stress database, is used to calculate and judge the stress condition of the pipe section to be predicted;

[0036] Data acquisition and transmission mechanism, used for communication connection between stress monitoring equipment and terminal server;

[0037] The power supply mechanism is used to supply power to the stress monitoring equipment and the data acquisition and transmission mechanism.

[0038] The pipeline stress prediction device based on multi-source information fusion of the present invention requires less structural equipment, can be combined with the above-mentioned stress prediction method to achieve improved monitoring effect, and can predict the actual stress of the pipeline at non-monitoring points.

[0039] In summary, due to the adoption of the above technical solution, the beneficial effects of the pipeline stress prediction method based on multi-source information fusion of the present invention are:

[0040] It can obtain the actual stress of the predicted pipe section with special structural characteristics by calculation while fully considering the stress threshold and stress calculation formula under various structural characteristic parameters, and then judge the operation status of the pipeline, so that the monitoring results can be closer to the actual situation, improve the accuracy of pipeline monitoring results, and realize the prediction of pipeline stress at non-monitoring points;

[0041] The beneficial effects of the pipeline stress prediction device based on multi-source information fusion of the present invention are:

[0042] The required structural equipment is relatively small, and the above-mentioned stress prediction method can be combined to improve the monitoring effect and predict the actual stress of the pipeline at non-monitoring points. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a flow chart of a pipeline stress prediction method based on multi-source information fusion of the present invention;

[0044] Figure 2 It is a schematic diagram of the process of establishing the stress database described in the present invention;

[0045] Figure 3 This is a structural schematic diagram of a pipeline stress prediction device based on multi-source information fusion in Example 3.

[0046] icon:

[0047] 1-stress monitoring equipment, 11-strain gauge, 2-data acquisition and transmission mechanism, 21-data collector, 22-data transmitter, 23-router, 3-terminal server, 4-power supply mechanism, 41-solar cell, 42-power supply. DETAILED DESCRIPTION

[0048] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0049] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0050] Example 1

[0051] like Figure 1-Figure 2 As shown, a pipeline stress prediction method based on multi-source information fusion includes the following steps:

[0052] S1. Establishing a feature database, wherein the feature database includes structural feature parameters of the monitored pipeline.

[0053] Specifically, the structural characteristic parameters include pipeline parameters, defect parameters and weld parameters, wherein the pipeline parameters include pipe type, pipeline diameter, pipeline type, pipeline wall thickness, pipeline mileage, and pressure, which are used to express the influence of the structure corresponding to the pipeline itself on the stress; the pipeline type can be a straight pipe, a bent pipe, a tee, or a reducer; the defect parameters include defect type, defect position, and defect size, which are used to express the influence of special structural features on the pipeline on the corresponding stress, and the defect types include pores, pits, undercuts, and cracks; the defect position includes the position of the defect on the pipeline cross section and the mileage data of the defect; the weld parameters include weld type and weld size, which are used to express the influence of the weld on the pipeline stress.

[0054] Specifically, the defect parameters and weld parameters are numbered in advance, and the feature information corresponding to the above defect parameters and weld parameters is tabulated in the feature database in the form of an orthogonal table.

[0055] S2. Establishing a stress database, wherein the stress database includes stress thresholds and stress calculation formulas corresponding to the structural characteristic parameters.

[0056] Specifically, the stress database includes the pipeline stress threshold and stress calculation formula under the influence of a single structural characteristic parameter, as well as the pipeline stress threshold and stress calculation formula under the coupling of multiple structural characteristic parameters. The pipeline stress threshold is the maximum stress of the pipeline under different pipeline parameters, different defect parameters, and different weld parameters obtained according to the finite element simulation results, so as to realize the pipeline stress prediction under different structural characteristic parameters.

[0057] S3. Obtain pipeline stress data and location information of each monitoring point.

[0058] Specifically, after strain monitoring is performed at each monitoring point by stress monitoring equipment, corresponding stress data and position information can be obtained through data processing, so as to be used for real-time remote monitoring and positioning of pipeline stress changes of the monitored pipeline.

[0059] S4. Determine the structural characteristic parameters of the pipe section to be predicted.

[0060] Specifically, by acquiring the position information of the pipe section to be predicted, the structural characteristic parameters of the pipe section to be predicted can be obtained according to a feature database established in advance.

[0061] S5. Determine the stress threshold and stress calculation formula of the pipe section to be predicted, and perform calculation and judgment.

[0062] Specifically, according to the structural characteristic parameters of the pipe section to be predicted, the pipeline stress threshold and stress calculation formula corresponding to the corresponding structural characteristic parameters can be obtained in the stress database, and the actual stress of the pipe section to be predicted under special structural characteristics can be calculated in combination with the pipeline stress value obtained by monitoring, and then it can be judged whether the pipeline operation status meets the requirements based on the stress threshold.

[0063] In the present embodiment, a pipeline stress prediction method based on multi-source information fusion is provided. The monitored pipe section is a pipe section provided with stress monitoring equipment to form a plurality of monitoring points. The pipe section to be predicted is a pipe section located between adjacent or close monitoring points, which is a certain section of the monitored pipe section. When prediction is required, the structural characteristic parameters of the pipe section to be predicted are determined according to the position information of the pipe section to be predicted. Then, the larger value of the adjacent stress values ​​along the axis direction of the pipe section to be predicted obtained by each monitoring point is substituted into the corresponding stress calculation formula as the monitoring stress value to calculate and obtain the actual stress of the pipe section to be predicted. Under the condition that the stress thresholds and stress calculation formulas under various structural characteristic parameters are fully considered, the actual stress of the pipe section to be predicted with special structural characteristics can be obtained by calculation, and then the operation status of the pipeline can be judged, so that the monitoring result can be closer to the actual situation, the accuracy of the pipeline monitoring result can be improved, and the prediction of the pipeline stress at the non-monitoring point can be realized.

[0064] Example 2

[0065] In this embodiment, a pipeline stress prediction method based on multi-source information fusion is provided. Based on the embodiment 1, the method for establishing the stress database includes:

[0066] S2.1. Establish a finite element model for pipeline stress analysis;

[0067] S2.2. Analyze the influence of structural characteristic parameters on stress threshold;

[0068] S2.3. Determine the factors affecting the stress of the monitored pipeline;

[0069] S2.4, calculation formula for fitting the effect of single factor on pipeline stress;

[0070] S2.5, fitting the calculation formula of the influence of multiple factors on pipeline stress;

[0071] S2.6. Express the calculation formulas of S2.4 and S2.5 using the stress calculation formula for defect-free pipelines.

[0072] Preferably, the stress calculation formula includes considering the actual pipeline stress as the product of an enhancement factor and a defect-free pipeline stress, wherein the enhancement factor includes an influence function of the structural characteristic parameters on the pipeline stress, and the defect-free pipeline stress includes the maximum stress when there are no defect parameters and weld parameters on the pipeline.

[0073] Specifically, considering that the pipeline must have a weld at a position with a variable cross-section, the defect parameters and weld parameters on the pipeline correspondingly include defects, welds and pipeline variable cross-sections, and the defect-free pipeline stress includes the maximum stress when there are no defects, welds and pipeline variable cross-sections on the pipeline.

[0074] Preferably, S2.3 uses a linear regression method to determine the stress influencing factors of the monitored pipeline. The stress influencing factors determined by S2.3 ignore secondary influencing factors and retain primary influencing factors, and the primary influencing factors include pipe material, pipe diameter, wall thickness and pressure.

[0075] Preferably, the stress calculation formula includes:

[0076] σ max =F[f(x,d,e,P),f(j,C,M)]×[0], max ;

[0077] Where:

[0078] f(x,d,e,p) represents the influence function of pipe material, pipe diameter, wall thickness and pressure on pipeline stress, which is dimensionless;

[0079] f(j,c,h) represents the influence function of pipeline variable cross-section, defects, and welds on pipeline stress. It is rewritten as f(c) when only affected by defects, rewritten as f(c,h) when there are defects on the weld, and rewritten as f(j,h) when the pipeline has variable cross-section;

[0080] [σ] max Indicates stress of defect-free pipeline;

[0081] σ max Indicates the actual stress of the pipe.

[0082] It should be noted that different types of defects correspond to different characteristic parameters, so that different types of defects correspond to different stress influencing factors. For example, the characteristic parameters corresponding to pit defects include length, width and depth, the characteristic parameters corresponding to pore defects include pore diameter and pore position, the defect parameters corresponding to crack defects include crack size and crack position, and the characteristic parameters corresponding to welds include weld size, weld misalignment, weld shape and weld material.

[0083] This embodiment takes a pit defect as an example to illustrate the fitting process of the stress calculation formula:

[0084] Step 1: Determine stress influencing parameters: When there is a pit defect in the pipeline, analyze the influence of the pit defect on the pipeline stress, and determine the factors affecting pipeline stress, including pipe diameter D, pipe wall thickness e, pressure P, pit length L, pit width m, and pit depth n;

[0085] Step 2: Construct a stress test table: In order to analyze the effect of pit size on pipeline stress, the pit length L, pit width m, and pit depth n are dimensionless, and the dimensionless length is obtained. Dimensionless width m / π and dimensionless depth n / e, and an orthogonal table showing pipe diameter D, wall thickness e, pressure P, dimensionless length Dimensionless width m / π, dimensionless depth n / e, stress of complete pipeline and stress of pipeline with pit defects simulated by finite element software;

[0086] Step 3: Construct the pipeline stress calculation formula corresponding to the pit defect: Use the dimensionless size parameters of the pit to construct the pipeline stress calculation formula σ 完整 Refers to the stress of a non-defective pipeline under the same working conditions. When the pipeline is only subjected to internal pressure, σ 完整 =PD / 2e;

[0087] Step 4: Simplify and solve the stress calculation formula: Consider the stress calculation formula Only σ 完整 is a primary independent variable, and the other three independent variables may be secondary or even multiple independent variables. The calculation formula is divided into The calculation formula of n / e and m / π is By controlling the variables and substituting the data in the stress test table into the three equations for multivariate high-order nonlinear regression analysis, all the unknown parameters in the equations can be obtained.

[0088] Example 3

[0089] like Figure 3 As shown, a pipeline stress prediction device based on multi-source information fusion adopts a pipeline stress prediction method based on multi-source information fusion in Example 1, and includes a stress monitoring device 1, a terminal server 3, a data acquisition and transmission mechanism 2 and a power supply mechanism 4.

[0090] Among them, the stress monitoring equipment is used to obtain the pipeline stress data of each monitoring point, including a plurality of strain gauges 11 attached to the pipeline. The strain gauges 11 are arranged at intervals along the longitudinal direction of the pipeline according to the pipeline mileage data and the defect mileage data. A plurality of strain gauges 11 form a group and are connected to a data acquisition and transmission mechanism 2 via wires. Each data acquisition and transmission mechanism 2 is communicatively connected to a terminal server 3.

[0091] Preferably, in this embodiment, 4-8 strain gauges 11 are arranged at intervals along the circumference of the pipeline to form stress monitoring units at different positions around the pipeline to realize strain monitoring of the pipeline section. The stress monitoring units are arranged at intervals along the longitudinal direction of the pipeline. Multiple stress monitoring units form a group of wires connected to a data acquisition and transmission mechanism 2, and each data acquisition and transmission mechanism 2 is communicatively connected to a terminal server 3.

[0092] Furthermore, the data acquisition and transmission mechanism 2 includes a data acquisition device 21, a data transmission device 22 and a router 23 connected in sequence. The router 23 is communicatively connected to the terminal server 3. The terminal server 3 has a built-in feature database and a stress database for calculating and judging the stress of the pipe section to be predicted. When in use, the number of strain gauge 11 signals correspondingly collected by the data acquisition device 21 at the same time can be adjusted according to actual conditions. For example, when the device is working, only the strain gauge signal of a certain section of the pipeline is collected. When the data collected by a certain strain gauge 11 in the section exceeds the set threshold, the number of strain gauge signals collected by the data acquisition device 21 is increased to realize the collection of the strain gauge 11 signal of the corresponding pipe section. In conjunction with the pipeline stress prediction method of Example 1, the safety status of the corresponding pipe section is obtained, so that the device can save power while ensuring normal operation, ensure the long-term use of the device, and help to extend the service life of the device.

[0093] Specifically, it also includes a power supply mechanism 4 for supplying power to the stress monitoring device 1 and the data acquisition and transmission mechanism 2. In this embodiment, the power supply mechanism 4 includes a solar cell 41 and a power supply 42. The solar cell 41 continuously supplies power to the electrical equipment in the stress monitoring device 1 and the data acquisition and transmission mechanism 2 through the power supply 42.

[0094] A pipeline stress prediction device based on multi-source information fusion in this embodiment requires less structural equipment, can be combined with the above-mentioned stress prediction method to achieve improved monitoring effect, and can predict the actual stress of the pipeline at the non-monitoring point. When in use, the strain gauge 11 transmits the strain of the pipeline monitoring point to the data collector 21, and the data collector 21 automatically calculates the stress of the pipeline monitoring point according to the relationship between stress and strain, and then transmits the position data of the strain gauge 11 and the stress data of the pipeline monitoring point together to the data transmitter 22, and the data transmitter 22 uploads these data together to the terminal server 3 through the router 23. After receiving these data, the terminal server 3 automatically searches for pipeline parameters, defect parameters, and weld parameters between adjacent strain gauges 11 in the feature database according to the position information of the strain gauge 11, and then searches for the corresponding pipeline stress calculation formula in the stress database according to the pipeline parameters, defect parameters, and weld parameters, and then substitutes the larger value of the stress values ​​monitored by the adjacent strain gauges 11 as the monitoring stress value into the stress calculation formula, so that the maximum stress at the corresponding defect, weld, and pipeline cross-section change can be obtained.

[0095] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A pipeline stress prediction method based on multi-source information fusion, characterized in that: The steps include: S1. Establishing a feature database, wherein the feature database includes structural feature parameters of the monitored pipeline; S2. Establishing a stress database, wherein the stress database includes stress thresholds and stress calculation formulas corresponding to the structural characteristic parameters; S3, obtaining pipeline stress data and location information of each monitoring point; S4, determining the structural characteristic parameters of the pipe section to be predicted; S5. Determine the stress threshold and stress calculation formula of the pipe section to be predicted, and perform calculation and judgment.

2. The pipeline stress prediction method based on multi-source information fusion according to claim 1 is characterized in that: The structural characteristic parameters include pipeline parameters, defect parameters and weld parameters. The pipeline parameters include pipe type, pipeline diameter, pipeline type, pipeline wall thickness, pipeline mileage, and pressure; the defect parameters include defect type, defect location, and defect size; the weld parameters include weld type and weld size.

3. The pipeline stress prediction method based on multi-source information fusion according to claim 1 is characterized in that: In S5, the calculation includes substituting the larger value of the adjacent stress values ​​along the axis direction of the pipe section to be predicted obtained at each monitoring point into the stress calculation formula as the monitoring stress value.

4. A pipeline stress prediction method based on multi-source information fusion according to any one of claims 1 to 3, characterized in that: The stress calculation formula includes considering the actual pipeline stress as the product of the enhancement factor and the stress of the defect-free pipeline, the enhancement factor includes the influence function of the structural characteristic parameters on the pipeline stress, and the defect-free pipeline stress includes the maximum stress when there are no defects, welds, or variable cross-sections on the pipeline.

5. The pipeline stress prediction method based on multi-source information fusion according to claim 4 is characterized in that: The method for establishing the stress database comprises: S2.

1. Establish a finite element model for pipeline stress analysis; S2.

2. Analyze the influence of structural characteristic parameters on stress threshold; S2.

3. Determine the factors affecting the stress of the monitored pipeline; S2.4, calculation formula for fitting the effect of single factor on pipeline stress; S2.5, fitting the calculation formula of the influence of multiple factors on pipeline stress; S2.

6. Express the calculation formulas of S2.4 and S2.5 using the stress calculation formula for defect-free pipelines.

6. The pipeline stress prediction method based on multi-source information fusion according to claim 5 is characterized in that: S2.3 Linear regression method is used to determine the factors affecting the stress of the monitored pipeline.

7. The pipeline stress prediction method based on multi-source information fusion according to claim 6 is characterized in that: S2.3 The stress influencing factors determined ignore the secondary influencing factors and retain the main influencing factors, which include pipe material, pipe diameter, wall thickness and pressure.

8. The pipeline stress prediction method based on multi-source information fusion according to claim 1 is characterized in that: The stress calculation formula includes: σ max =F[f(x,d,e,p),f(j,c,h)]×[σ] max ; Where: f(x,d,e,p) represents the influence function of pipe material, pipe diameter, wall thickness and pressure on pipeline stress, which is dimensionless; f(j,c,h) represents the influence function of pipeline variable cross-section, defects, and welds on pipeline stress. It is rewritten as f(c) when only affected by defects, rewritten as f(c,h) when there are defects on the weld, and rewritten as f(j,h) when the pipeline has variable cross-section; [σ] max Indicates stress of defect-free pipeline; σ max Indicates the actual stress of the pipe.

9. A pipeline stress prediction device based on multi-source information fusion, characterized in that: A pipeline stress prediction method based on multi-source information fusion as claimed in claim 1 is adopted, and includes: Stress monitoring equipment (1), used to obtain pipeline stress data at each monitoring point; The terminal server (3) has a built-in feature database and a stress database, which are used to calculate and determine the stress condition of the pipe section to be predicted; A data acquisition and transmission mechanism (2) is used to communicate and connect the stress monitoring device and the terminal server; The power supply mechanism (4) is used to supply power to the stress monitoring device (1) and the data acquisition and transmission mechanism (2).

10. The pipeline stress prediction device based on multi-source information fusion according to claim 9, characterized in that: The stress monitoring device (1) comprises a plurality of strain gauges (11), wherein the plurality of strain gauges (11) are connected in groups to the data acquisition and transmission mechanism (2); the data acquisition and transmission mechanism (2) comprises a data acquisition device (21), a data transmission device (22) and a router (23) connected in sequence, wherein the router (23) is communicatively connected to the terminal server (3); and the power supply mechanism (4) comprises a solar power supply mechanism.

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