CN-121787199-B - Repairing method, device and equipment for flexible composite pipe and storage medium

CN121787199BCN 121787199 BCN121787199 BCN 121787199BCN-121787199-B

Abstract

The application discloses a method, a device, equipment and a storage medium for repairing a flexible composite pipe. The method comprises the steps of analyzing and processing service environment, material combination and load characteristics of a flexible composite pipe based on a temperature difference-pressure-medium-humidity-illumination five-field coupling accelerated ageing experimental field to obtain monitoring data, establishing a damage evolution model based on the monitoring data and a failure process of the flexible composite pipe, constructing a coupling constitutive model and performing finite element simulation verification, extracting characteristics of the monitoring data to obtain characteristic parameters, constructing a risk prediction model by combining the effective coupling constitutive model, determining a grading restoration strategy based on a prediction result, and executing restoration on the flexible composite pipe. The application can obviously improve the risk prediction precision and repair pertinence, effectively solve the cracking repair problem of the flexible composite pipe, reduce the maintenance cost and improve the service safety and reliability of the pipe.

Inventors

WENG GUANGYUAN
CHENG JIAQI
HAN ZHAOYANG
YANG FENGWEI
ZHU XIYU

Assignees

西安石油大学

Dates

Publication Date: 20260508
Application Date: 20260304

Claims (10)

1. A method of repairing a flexible composite pipe, comprising: Analyzing and processing service environment, material combination and load characteristics of the flexible composite pipe based on a coupling accelerated aging test field to obtain monitoring data, wherein the coupling accelerated aging test field is a five-field coupling accelerated aging test field of temperature difference-pressure-medium-humidity-illumination, and the monitoring data comprises temperature time sequence data, microscopic image data, acoustic emission signal data and material characteristic parameters; Dividing four continuous failure periods of a thermal stress accumulation period, an interface phase reconstruction period, a matrix microcrack bifurcation period and a destabilization fracture period based on the monitoring data and the failure process of the flexible composite pipe, determining a failure critical threshold value and a failure criterion corresponding to each failure period, obtaining a damage evolution equation corresponding to each failure period based on energy dissipation theory fitting, and establishing a damage evolution model; Constructing a coupling constitutive model based on the damage evolution model, and performing finite element embedding and simulation verification processing on the coupling constitutive model to obtain an effective coupling constitutive model; Performing feature extraction processing on the temperature time sequence data, the microscopic image data, the acoustic emission signal data and the material characteristic parameters to obtain characteristic parameters; constructing a dual-branch network model by taking the effective coupling constitutive model as a global model basis, integrating dual-branch characteristics in the dual-branch network model, and then combining the characteristic parameters to perform model training to obtain a risk prediction model for outputting stress cracking probability and residual life, wherein a first branch network is a graph neural network for extracting microscopic image characteristics and material characteristic characteristics, and a second branch network is a transducer network for extracting temperature time sequence characteristics and acoustic emission signal characteristics; carrying out prediction processing on the flexible composite pipe based on the risk prediction model to obtain a prediction result, and determining a hierarchical restoration strategy according to the prediction result; and repairing the flexible composite pipe based on the grading repairing strategy to obtain the repaired flexible composite pipe.
2. The method of claim 1, wherein the dividing the thermal stress accumulation period, the interface phase reconstruction period, the matrix microcrack bifurcation period, and the destabilizing fracture period based on the monitoring data and the failure process of the flexible composite pipe, determining a failure critical threshold and a failure criterion corresponding to each failure period, obtaining a damage evolution equation corresponding to each failure period based on energy dissipation theory fitting, and establishing a damage evolution model includes: Analyzing and processing the monitoring data to obtain a plurality of failure periods, wherein the failure periods comprise a thermal stress accumulation period, an interface phase reconstruction period, a matrix microcrack bifurcation period and a destabilization fracture period; acquiring failure critical thresholds corresponding to the temperature time sequence data, the microscopic image data, the acoustic emission signal data and the material characteristic parameters respectively; Performing quantization processing on a plurality of failure periods based on the failure critical threshold value to obtain failure criteria corresponding to the failure periods; Fitting the failure criterion, the temperature time sequence data, the microscopic image data, the acoustic emission signal data and the material characteristic parameters to obtain a damage evolution model corresponding to each failure period.
3. The method of claim 1, wherein the material characteristic parameters include interfacial bond strength, thermal expansion coefficient difference, and viscoelastic relaxation modulus, and wherein the performing feature extraction processing on the temperature time series data, the microscopic image data, the acoustic emission signal data, and the material characteristic parameters to obtain feature parameters includes: Performing wavelet packet decomposition and entropy value calculation processing on the temperature time sequence data, and extracting energy entropy, sample entropy, approximate entropy, maximum Lyapunov exponent and adjacent temperature difference change rate to obtain temperature time sequence characteristics; performing convolutional neural network analysis processing on the microscopic image data, and extracting crack length, width proportion, interface debonding area occupation ratio and fiber-matrix contact point number to obtain microscopic image characteristics; Performing short-time Fourier transform processing on the acoustic emission signal data, extracting the energy duty ratio, ringing count rate and rise time of a characteristic frequency band, and obtaining acoustic emission signal characteristics; Performing finishing analysis treatment on interface bonding strength, thermal expansion coefficient difference and viscoelastic relaxation modulus in the material characteristic parameters to obtain material characteristic features; And integrating the temperature time sequence characteristic, the microscopic image characteristic, the acoustic emission signal characteristic and the material characteristic to obtain characteristic parameters.
4. The method according to claim 1, wherein the constructing a dual-branch network model based on the effective coupling constitutive model as a global model basis, integrating dual-branch features in the dual-branch network model, and then performing model training in combination with the feature parameters to obtain a risk prediction model for outputting stress cracking probability and residual life, comprises: training the effective coupling constitutive model to obtain trained model parameters; performing aggregation optimization treatment on the trained model parameters to obtain a global model foundation; Constructing a dual-branch network model, wherein the dual-branch network model comprises a first branch network and a second branch network, the first branch network is used for extracting microscopic image characteristics and material characteristic characteristics, and the second branch network is used for extracting temperature time sequence characteristics and acoustic emission signal characteristics; And carrying out training parameter configuration and model training treatment on the dual-branch network model and the global model foundation to obtain a risk prediction model.
5. The method of claim 1, wherein the predicting the flexible composite pipe based on the risk prediction model to obtain a predicted result, and determining a hierarchical repair strategy according to the predicted result comprises: Acquiring real-time environment data and material state data of the flexible composite pipe; inputting the real-time environment data and the material state data into the risk prediction model for prediction processing to obtain a prediction result; Dividing the prediction result to obtain a damage grade; And carrying out repair mode matching treatment based on the damage grade to obtain a grading repair strategy, wherein the grading repair strategy comprises autonomous repair matching of embedded microcapsules, active sealing matching of shape memory polymer patches and emergency plugging matching of an in-pipe repair robot.
6. The method of claim 1, wherein the repairing the flexible composite pipe based on the hierarchical repairing strategy further comprises, after obtaining the repaired flexible composite pipe: Continuously monitoring the repaired area of the repaired flexible composite pipe, and collecting state data after repair related to strain, acoustic emission, temperature and leakage; performing comparative analysis treatment on the repaired flexible composite pipe and a preset repair success criterion to obtain a repair effect; Under the condition that the repair effect reaches the standard, carrying out iterative optimization on the risk prediction model according to the repair effect; Or under the condition that the repairing effect does not reach the standard and the maximum repairing attempt number is not reached, the repairing operation is re-executed after the grading repairing strategy is adjusted, and under the condition that the repairing effect does not reach the standard and the maximum repairing attempt number is reached, the flexible composite pipe is subjected to high-risk marking treatment, and the marked flexible composite pipe is obtained.
7. The method of claim 6, wherein the maximum number of repair attempts is 3.
8. A repair device for a flexible composite tube, comprising: The analysis module is used for analyzing and processing the service environment, the material combination and the load characteristics of the flexible composite pipe based on the coupling accelerated aging test field to obtain monitoring data, wherein the coupling accelerated aging test field is a five-field coupling accelerated aging test field of temperature difference-pressure-medium-humidity-illumination, and the monitoring data comprises temperature time sequence data, microscopic image data, acoustic emission signal data and material characteristic parameters; the construction module is used for dividing a thermal stress accumulation period, an interface phase reconstruction period, a matrix microcrack bifurcation period and a destabilization fracture period into four continuous failure periods based on the monitoring data and the failure process of the flexible composite pipe, determining a failure critical threshold value and a failure criterion corresponding to each failure period, obtaining a damage evolution equation corresponding to each failure period based on energy dissipation theory fitting, and establishing a damage evolution model; the construction module is further used for constructing a coupling constitutive model based on the damage evolution model, and performing finite element embedding and simulation verification processing on the coupling constitutive model to obtain an effective coupling constitutive model; the processing module is used for carrying out characteristic extraction processing on the temperature time sequence data, the microscopic image data, the acoustic emission signal data and the material characteristic parameters to obtain characteristic parameters; The processing module is further used for constructing a dual-branch network model by taking the effective coupling constitutive model as a global model basis, integrating dual-branch characteristics in the dual-branch network model, and then combining the characteristic parameters to perform model training to obtain a risk prediction model for outputting stress cracking probability and residual life, wherein the first branch network is a graph neural network for extracting microscopic image characteristics and material characteristic characteristics, and the second branch network is a transducer network for extracting temperature time sequence characteristics and acoustic emission signal characteristics; The processing module is further used for carrying out prediction processing on the flexible composite pipe based on the risk prediction model to obtain a prediction result, and determining a hierarchical restoration strategy according to the prediction result; And the processing module is also used for repairing the flexible composite pipe based on the grading repairing strategy to obtain the repaired flexible composite pipe.
9. A computer device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the program is executed.
10. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the method according to any one of claims 1 to 7.

Description

Repairing method, device and equipment for flexible composite pipe and storage medium Technical Field The application relates to the technical field of material repair, in particular to a repair method, device and equipment for a flexible composite pipe and a storage medium. Background With the rapid development of the fields of deep sea oil gas gathering and transportation, desert oil field exploitation, polar resource development and the like, the flexible composite pipe is widely applied as core transportation equipment. The service environment of the pipe presents extreme characteristics, and the pipe is not only subjected to severe temperature difference fluctuation of-60 ℃ to 120 ℃, but also needs to bear multi-field coupling effects such as internal pressure alternation of 0.1 to 15MPa, medium corrosion containing H 2S/CO2/Cl-, humidity change of 10 to 95 percent RH, outdoor ultraviolet irradiation and the like. For example, the flexible vertical pipe of a certain deep sea gas field in the south China sea is in a complex working condition of 30 ℃ of day and night temperature difference, 10MPa fluctuation of internal pressure and high-concentration Cl - corrosion for a long time, so that failure problems such as interface debonding and matrix cracking are frequent, the single maintenance cost is more than ten millions yuan, and the safety and the economy of oil and gas transportation are seriously affected. The related technology for repairing the flexible composite pipe cracking has obvious limitations that firstly, a failure mechanism analyzes fragmentation, the prior art mostly adopts static or single-field coupling experiments, a dynamic chain reaction of thermal stress accumulation-interface phase reconstruction-matrix microcrack bifurcation-fiber-matrix debonding in temperature difference circulation cannot be revealed, quantitative description of critical damage threshold values at each stage is lacking, secondly, the precision of a prediction model is insufficient, the correlation of nonlinear viscoelasticity, damage anisotropy and multi-mode data of materials is not considered in a traditional empirical formula, so that the stress cracking probability and residual life prediction error are always more than 30%, thirdly, engineering applicability and repair pertinence are poor, a prediction framework for multi-field data privacy protection is lacking, the repair mode is mostly single emergency treatment, grading accurate repair cannot be realized according to the damage degree, and intelligent operation and maintenance of a large-scale pipeline network is difficult to support. Therefore, how to accurately analyze the dynamic failure mechanism of the stress cracking of the flexible composite pipe under the multi-field coupling extreme environment, construct a high-precision risk prediction model, and realize hierarchical intelligent repair with strong pertinence and high suitability at the same time, thereby becoming a urgent problem to be solved for guaranteeing the safe service of the flexible composite pipe in the whole life cycle and reducing the operation and maintenance cost. Disclosure of Invention In view of the above, the method, the device, the equipment and the storage medium for repairing the flexible composite pipe provided by the embodiment of the application can analyze and process the service environment, the material combination and the load characteristics of the flexible composite pipe based on a temperature difference-pressure-medium-humidity-illumination five-field coupling accelerated aging experimental field to obtain monitoring data, establish a damage evolution model based on the monitoring data and the failure process of the flexible composite pipe, construct a coupling constitutive model and perform finite element simulation verification, extract characteristics of the monitoring data to obtain characteristic parameters, construct a risk prediction model by combining the effective coupling constitutive model, determine a grading repair strategy based on a prediction result, and execute repair on the flexible composite pipe. The repairing method, device and equipment for the flexible composite pipe and the storage medium provided by the embodiment of the application are realized as follows: the method for repairing the flexible composite pipe provided by the embodiment of the application comprises the following steps: Analyzing and processing service environment, material combination and load characteristics of the flexible composite pipe based on a coupling accelerated aging test field to obtain monitoring data, wherein the coupling accelerated aging test field is a five-field coupling accelerated aging test field of temperature difference-pressure-medium-humidity-illumination, and the monitoring data comprises temperature time sequence data, microscopic image data, acoustic emission signal data and material characteristic parameters; Dividing four continuous failure