HDPE pipe deformation data analysis and restoration method and system based on multi-source data

Abstract

The invention discloses an HDPE pipe deformation data analysis and restoration method and system based on multi-source data, and relates to the field of deformation data analysis and restoration. Accurate deformation prediction of an HDPE pipe under a composite working condition is achieved through load-temperature bivariate input and correlation modeling of deformation position coordinates; the model can process coupling deformation modes of axial tension and radial compression at the same time, and prediction errors are controlled within an engineering allowable range; a printing parameter combination with the minimum material consumption is automatically screened in an iterative optimization mode, material consumption is reduced on the premise that the repairing quality is guaranteed, dynamic adjustment of a repairing strategy is achieved, it is guaranteed that the ring stiffness retention rate of the repaired pipeline meets the requirement, and the hydrostatic test passing rate is increased; and through cross validation of historical deformation data and real-time monitoring data, the repair reliability is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the field of deformation data analysis and repair, and in particular, relates to a method and system for HDPE pipe deformation data analysis and repair based on multi-source data. Background Art

[0002] HDPE (High Density Polyethylene) pipes have excellent chemical stability, good corrosion resistance, and a smooth inner wall. In landfills and tailings dams, HDPE pipes are widely used to collect and drain leachate. Extensive field monitoring results indicate that the temperature inside the landfill is very high. Unlike ordinary buried pipes, HDPE pipes in landfill projects are subject to high temperatures in addition to loads. Given that laying HDPE pipes in landfills is an irreversible process, once laid and the landfill is operational, they cannot be repaired or replaced. Therefore, studying the deformation characteristics of HDPE pipes under the combined effects of load and temperature has important engineering significance and practical value. Traditional HDPE pipe deformation prediction methods lack modeling of multi-factor coupling effects, making it difficult to accurately reflect the impact of temperature and load on pipe deformation under actual working conditions; in addition, existing printing compensation technologies usually use fixed empirical values for adjustment and cannot dynamically respond to changes in material deformation characteristics. Summary of the Invention

[0003] In response to the problems in the related art, the present invention proposes a HDPE pipe deformation data analysis and repair method and system based on multi-source data to overcome the above-mentioned technical problems existing in the existing related art.

[0004] To solve the above technical problems, the present invention is achieved through the following technical solutions: The present invention is a method for analyzing and repairing HDPE pipe deformation data based on multi-source data, comprising the following steps: S1. Set a number of load test data and temperature test data; S2. Perform deformation tests on multiple HDPE pipe test samples according to the test data set in S1 and obtain the corresponding average values of maximum axial deformation data and maximum radial deformation data; S3, using the average value of the axial maximum deformation data and the radial maximum deformation data obtained in S2, the load test data set, and the temperature test data set to construct a HDPE pipe deformation mapping model; S4, inputting the current actual load and temperature data around the HDPE into the HDPE pipe deformation mapping model for mapping; S5. Obtain the deformation position coordinates corresponding to the axial maximum deformation data and the radial maximum deformation data of multiple HDPE pipe test samples in S2, the printing volume during the printing process, the printing position coordinate data, and the axial and radial deformation difference before and after the application of load and temperature, and construct a pipe printing deformation mapping model; S6. According to the data obtained by mapping in S4 and the pipe printing deformation mapping model, the printing volume and printing position corresponding to the current HDPE pipe printing operation are iteratively adjusted, and the minimum printing volume and corresponding printing position are selected.

[0005] Preferably, the S1 comprises the following steps: S11. Set a number of HDPE pipe samples for testing to obtain a set of HDPE pipe test samples; then set a set of HDPE pipe deformation controlled variables, wherein the set of HDPE pipe deformation controlled variables includes load and temperature; S12, setting a load test data interval and a temperature test data interval; setting a plurality of load test data and temperature test data according to the load test data interval and the temperature test data interval to obtain a load test data set and a temperature test data set; By setting up multiple HDPE pipe test samples, the sporadic nature of the HDPE pipe deformation data obtained is reduced, ensuring the comparability and repeatability of the experimental data; by using preset data intervals to generate load and temperature data sets, a gradient coverage of key deformation influencing factors is achieved, which can avoid test blind spots and improve data collection efficiency. Preferably, said S2 comprises the following steps: S21, combining the data in the load test data set and the temperature test data set in pairs to obtain a pipe deformation controlled variable data combination set; S22. Based on the HDPE pipe test sample set, apply load and temperature to each HDPE pipe test sample using the pipe deformation controlled variable data combination set. After the load and temperature are applied, measure the maximum axial deformation data and the maximum radial deformation data of each HDPE pipe test sample and calculate the average values to obtain a pipe test maximum axial deformation data set and a pipe test maximum radial deformation data set. Through the dual-variable combination test of load and temperature, the limitations of traditional single-factor testing are overcome; the simultaneous acquisition of axial and radial deformation data helps to reveal the anisotropic deformation law of HDPE pipes under different load and temperature conditions, and provides data support for the subsequent construction of a mapping model for axial and radial deformation data.

[0006] Preferably, the step S3 includes the following steps: S31, constructing a HDPE pipe axial maximum deformation mapping model based on the pipe deformation controlled variable data set and the pipe test axial maximum deformation data set; Constructing a HDPE pipe radial maximum deformation mapping model based on the pipe deformation controlled variable data set and the pipe test radial maximum deformation data set; The HDPE pipe axial maximum deformation mapping model and the HDPE pipe radial maximum deformation mapping model respectively adopt a radial basis function-fully connected hybrid network model and a convolutional capsule network model; By modeling the correlation between the load-temperature dual variable and deformation data, the nonlinear response law of the material in the composite stress field can be quantified, significantly improving the prediction accuracy; the deformation data output by the model provides data guidance for the subsequent printing of the shape memory polymer composite material layer on the outer wall of the pipe.

[0007] Preferably, the S4 comprises the following steps: S41, obtaining the maximum axial deformation data and the maximum radial deformation data of each HDPE pipe test sample after the load and temperature are applied in S22, and obtaining a historical maximum axial deformation data set and a historical maximum radial deformation data set; Then, a coordinate system is established for each HDPE pipe test sample using the same coordinate origin; and based on the established coordinate system, the deformation position coordinates corresponding to the axial maximum deformation data and the radial maximum deformation data of each HDPE pipe test sample are obtained to obtain a historical axial deformation position coordinate set and a historical radial deformation position coordinate set; S42, setting printing parameters for the shape memory polymer composite material and several types of the shape memory polymer composite material for printing on the HDPE tube to obtain a composite material printing parameter type set; the composite material printing parameter type set includes a printing position and a printing amount; S43. Set the current HDPE pipe; use a temperature sensor and a mechanical sensor to collect and calculate average load and temperature data around the HDPE pipe to obtain average load data and average temperature data of the current pipe; input the average load data and average temperature data of the current pipe into an HDPE pipe axial maximum deformation mapping model and an HDPE pipe radial maximum deformation mapping model for mapping, respectively, to obtain the current pipe axial maximum deformation data and the current pipe radial maximum deformation data; By establishing a standardized coordinate system and deformation position coordinate set, accurate quantitative analysis of the deformation behavior of HDPE pipes under different working conditions is achieved; the use of a unified coordinate origin makes the test data from different batches and different test conditions comparable, which is conducive to the establishment of a pipeline full life cycle performance evaluation system.

[0008] Preferably, the S5 comprises the following steps: S51. Perform a shape memory polymer composite material printing operation on each HDPE pipe test sample in S41, obtain composite material printing volume data, printing position coordinate data, and absolute values of axial and radial deformation differences of each HDPE pipe test sample after the applied load and temperature are removed and before the applied load and temperature are applied, to obtain a historical pipe printing volume dataset, a historical pipe printing position coordinate dataset, a historical pipe axial deformation difference dataset, and a historical pipe radial deformation difference dataset; S52, constructing a tube printing axial deformation mapping model and a tube printing radial deformation mapping model based on the historical maximum axial deformation dataset, the historical maximum radial deformation dataset, the historical axial deformation position coordinate set, the historical radial deformation position coordinate set, the historical tube printing amount dataset, the historical tube printing position coordinate dataset, the historical tube axial deformation difference dataset, and the historical tube radial deformation difference dataset; The construction of a deformation difference dataset can verify the effectiveness of different printing parameters on pipeline shape recovery; the constructed axial / radial deformation mapping model can predict the deformation recovery effect under a specific printing scheme, providing a visual decision-making tool for pipeline repair and reducing trial and error costs.

[0009] Preferably, the tube printing axial deformation mapping model and the tube printing radial deformation mapping model in S52 respectively adopt a 3D convolutional neural network model and a graph neural network model; 3D convolutional neural networks can effectively model the three-dimensional deposition effect of composite materials on the pipe surface; graph neural networks are suitable for processing the circumferential continuity constraints of radial deformation of HDPE pipes.

[0010] Preferably, the S6 comprises the following steps: S61, setting a current tube axial deformation threshold and a current tube radial deformation threshold; when the current tube maximum axial deformation data is greater than or equal to the current tube axial deformation threshold or the current tube maximum radial deformation data is greater than or equal to the current tube radial deformation threshold, performing a shape memory polymer composite material printing operation on the current HDPE tube and proceeding to S62; S62, obtaining the preset current print volume, the preset current print position, and the corresponding value ranges in the print operation in S61, and obtaining the current print volume value range and the current print position value range; S63, setting a current tube axial deformation difference threshold, a current tube radial deformation difference threshold, a current tube axial deformation position coordinate interval, and a current tube radial deformation position coordinate interval; Traversing the current tube axial deformation position coordinate interval, inputting the preset current printing amount, the preset current printing position, the current tube axial maximum deformation data, and the traversed current tube axial deformation position coordinates into a tube printing axial deformation mapping model for mapping, until the traversal of the current tube axial deformation position coordinate interval is completed, thereby obtaining a current tube axial deformation difference value set; Then, the current tube radial deformation position coordinate interval is traversed, and the preset current printing amount, the preset current printing position, the current tube radial maximum deformation data, and the traversed current tube radial deformation position coordinate are input into the tube printing radial deformation mapping model for mapping, until the traversal of the current tube radial deformation position coordinate interval is completed, thereby obtaining a current tube radial deformation difference value set; S64, adjusting the printing volume and printing position in the current composite material printing process according to the current tube axial deformation difference threshold, the current tube radial deformation difference threshold, the current tube axial deformation difference set, and the current tube radial deformation difference set; after the adjustment is completed, obtaining current final printing volume data and current final printing position coordinate data; S65, performing an actual deformation correction printing operation on the current HDPE pipe according to the current final printing amount data and the current final printing position coordinate data; Through iterative traversal, the coordinates of each position that may cause deformation are mapped in turn to ensure that the situations when various deformations occur can be taken into account and further measures can be taken.

[0011] Preferably, the S64 includes the following steps: S641. When an axial deformation difference value greater than or equal to the current tube axial deformation difference threshold value exists in the current tube axial deformation difference value set or a radial deformation difference value greater than or equal to the current tube radial deformation difference threshold value exists in the current tube radial deformation difference value set, the preset current printing amount and the preset current printing position are adjusted simultaneously by traversing the current printing amount value interval and the current printing position value interval, and S63 is repeated until no axial deformation difference value greater than or equal to the current tube axial deformation difference threshold value exists in the current tube axial deformation difference value set and no radial deformation difference value greater than or equal to the current tube radial deformation difference threshold value exists in the current tube radial deformation difference value set; and the current printing amount data of the current traversal is recorded. S642, repeating the process of traversing the current print volume value interval and the current print position value area in S641 until the traversal is completed, and obtaining a current record of qualified print volume data set; The minimum print amount data and the corresponding print position coordinate data in the currently recorded qualified print amount data set are used as the current final print amount data and the current final print position coordinate data; Through the dual loop structure of threshold judgment and interval traversal, real-time dynamic optimization of printing parameters is achieved to ensure that the restoration effect always meets the preset deformation tolerance requirements; the minimum qualified printing volume screening strategy is adopted to significantly reduce material consumption while ensuring the quality of the restoration.

[0012] The HDPE pipe deformation data analysis and repair system based on multi-source data includes an HDPE pipe deformation test application data setting module, an HDPE deformation test module, an HDPE pipe deformation mapping model construction module, a historical pipe deformation position coordinate acquisition module, a composite material printing parameter type setting module, a current pipe deformation data mapping module, a pipe printing deformation mapping model construction module, and a current pipe printing parameter adjustment module.

[0013] The present invention has the following beneficial effects: 1. The present invention achieves accurate deformation prediction of HDPE pipes under complex working conditions through modeling the association between load-temperature dual variable input and deformation position coordinates. The model can simultaneously handle the coupled deformation modes of axial tension and radial compression, and the prediction error is controlled within the engineering allowable range. Iterative optimization is used to automatically select printing parameter combinations with the minimum material usage, reducing material consumption while ensuring repair quality, realizing dynamic adjustment of repair strategies, ensuring that the ring stiffness retention rate of the repaired pipeline meets the requirements, and improving the pass rate of hydrostatic test. Cross-validation of historical deformation data and real-time monitoring data significantly improves repair reliability.

[0014] 2. The present invention achieves precise quantitative analysis of the deformation behavior of HDPE pipes under different working conditions by establishing a standardized coordinate system and a deformation position coordinate set, providing a complete deformation feature database for pipeline structure reliability assessment. The establishment of a historical deformation data set and a position coordinate set provides a spatial positioning basis for parameter setting of the shape memory polymer repair solution, so that the determination of the printing position and printing volume has data support, avoiding redundancy or insufficiency of repair materials. The integration of deformation data under load and temperature can reveal the influence of complex environmental factors on pipeline performance, providing a theoretical basis for the development of printing parameters for composite materials with environmental adaptability. The use of a unified coordinate origin makes the test data from different batches and different test conditions comparable, which is conducive to the establishment of a pipeline full life cycle performance evaluation system.

[0015] 3. The present invention uses an iterative traversal method to map the coordinates of each position where deformation may occur in turn, ensuring that the situations when various deformations occur can be taken into account and further measures can be taken; this overcomes the problem that the specific position coordinates of the axial and radial deformation of the current HDPE pipe under the combined effects of load and temperature are difficult to predict in advance.

[0016] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 Schematic diagram of the process of the HDPE pipe deformation data analysis and repair method based on multi-source data of the present invention; Figure 2 A schematic diagram of the process of constructing a deformation mapping model for HDPE pipes according to the present invention; Figure 3 A schematic diagram of the process of constructing a pipe printing deformation mapping model and printing a current HDPE pipe according to the present invention; Figure 4 A schematic diagram of the process of adjusting printing parameters according to the present invention; Figure 5 Schematic diagram of the modules of the HDPE pipe deformation data analysis and repair system based on multi-source data of the present invention; Figure 6 This is a temperature change curve diagram during the stress deformation test of HDPE pipe under a load of 50 kN according to the present invention; Figure 7 This is a schematic diagram of the deformation data of section I after loading for 70 minutes according to the present invention; Figure 8 This is a schematic diagram of the deformation data of section I after loading for 8710 min according to the present invention; Figure 9 This is a schematic diagram of the deformation data of Section II after loading for 70 minutes according to the present invention; Figure 10 This is a schematic diagram of the deformation data of Section II after loading for 8710 min according to the present invention; Figure 11 This is a schematic diagram of the deformation data of section III after loading for 70 minutes in the present invention; Figure 12 This is a schematic diagram of the deformation data of section III after loading for 8710 min according to the present invention; Figure 13 This is a schematic diagram of deformation data caused by loads in the present invention; Figure 14 This is a schematic diagram of deformation data caused by temperature increase in the present invention; Figure 15 This is a schematic diagram of the cross-sectional strain of the HDPE pipe I of the present invention; Figure 16This is a schematic diagram of the strain of the HDPE pipe II section of the present invention; Figure 17 This is a schematic diagram of the strain of the HDPE pipe section III of the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0020] Example 1

[0021] See also Figure 1-4 This embodiment is a method for analyzing and repairing HDPE pipe deformation data based on multi-source data, comprising the following steps: S1. Set a number of load test data and temperature test data; Said S1 comprises the following steps: S11. Set a number of HDPE pipe samples for testing to obtain a set of HDPE pipe test samples; then set a set of HDPE pipe deformation controlled variables, wherein the set of HDPE pipe deformation controlled variables includes load and temperature; S12, setting a load test data interval and a temperature test data interval; setting a plurality of load test data and temperature test data according to the load test data interval and the temperature test data interval to obtain a load test data set and a temperature test data set; By setting up multiple HDPE pipe test samples, the sporadic nature of HDPE pipe deformation data obtained when load and temperature are subsequently applied is reduced, ensuring the comparability and repeatability of experimental data, thereby ensuring the accuracy of the subsequent mapping model between HDPE pipe deformation data, load, and temperature. By setting up load test data sets and temperature test data sets, a test data basis is provided for subsequent testing of HDPE pipe test samples. The use of preset data intervals to generate load and temperature data sets achieves gradient coverage of key deformation influencing factors, avoiding test blind spots and improving data collection efficiency. The collaborative test design of the load-temperature dual variable can accurately simulate the deformation mechanism of the pipeline under actual working conditions, providing multi-dimensional data support for the selection, design, and life prediction of HDPE pipes in actual processes. S2. Perform deformation tests on multiple HDPE pipe test samples according to the test data set in S1 and obtain the corresponding average values of maximum axial deformation data and maximum radial deformation data; The S2 comprises the following steps: S21, combining the data in the load test data set and the temperature test data set in pairs to obtain a pipe deformation controlled variable data combination set; S22. Based on the HDPE pipe test sample set, apply load and temperature to each HDPE pipe test sample using the pipe deformation controlled variable data combination set. After the load and temperature are applied, measure the maximum axial deformation data and the maximum radial deformation data of each HDPE pipe test sample and calculate the average values to obtain a pipe test maximum axial deformation data set and a pipe test maximum radial deformation data set. For example, a stress deformation test of HDPE pipe under 50 kN load was conducted to obtain relevant test data. 50 kPa corresponds to a landfill unit height of 5 m in a Class II landfill. Each new landfill unit generates an incremental load on the leachate collection pipe (HDPE pipe). The total test duration was 6 days. The temperature curve during the test was as follows: Figure 6 shown.

[0022] The test data show that when the temperature control box is set at 60°C, after three days of heat transfer, the temperature of sensor No. 1 close to the side wall of the model box is 59.6037°C, the temperature of sensor No. 2 buried in the sand is 54.3935°C, and the temperature of sensor No. 3 close to the HDPE pipe wall is 52.534°C. This indicates that after three days of heat transfer, the temperature around the HDPE pipe reaches 52.534°C. When the temperature control box is set at 80°C, after three days of heat transfer, the temperature of sensor No. 1, sensor No. 2, sensor No. 3, and sensor No. 3 reach 79.5234°C, 72.911°C, and 69.8379°C, respectively. This indicates that after three days of heat transfer, the temperature around the HDPE pipe reaches 69.8379°C. This temperature data provides a reference for the subsequent analysis of pipeline deformation.

[0023] The deformation of the HDPE pipe section I before temperature control is as follows: Figure 7 As shown in the figure, with the application of load, the vertical and horizontal deformations of the HDPE pipe increase. The vertical deformation ΔDv is negative, indicating compression, while the horizontal deformation ΔDh is positive, indicating tension. After 50 kPa loading, the pipe's ΔDv is -0.2079 mm and ΔDh is 0.1565 mm; ΔDv is -0.189%D mm and ΔDh is 0.142%D. Comparing the results of the force-deformation test of an HDPE pipe with a diameter-to-thickness ratio of 26 at room temperature, at 50 kPa, the results are ΔDv = -0.1857 mm and ΔDh = 0.1509 mm, a difference of 4.1% to 10.76%. This indicates that when conducting force-deformation tests on HDPE pipes, under the same load conditions, the test results can vary by 4.1% to 10.76%.

[0024] The deformation data after 6 days of temperature control is as follows Figure 8As shown in the figure, after three days of temperature control at 60 °C, ΔDv increased to -0.2292 mm, which is 1.1 times that before temperature control, and ΔDh increased to 0.1687 mm, which is 1.078 times that before temperature control; after three days of temperature control at 80 °C, ΔDv increased to -0.2960 mm, which is 1.424 times that before temperature control; ΔDh increased to 0.1808 mm, which is 1.155 times that before temperature control.

[0025] After 50 kPa loading is completed, the deformation of the HDPE pipe II section is as follows: Figure 9 As shown in Figure 1, similar to section I, with the application of load, the vertical and horizontal deformations of the HDPE pipe increase. The vertical deformation ΔDv is negative, indicating compression; the horizontal deformation ΔDh is positive, indicating tension. After the 50 kPa loading is completed, ΔDv = -0.1983 mm, and ΔDh = 0.1482 mm.

[0026] The deformation after 6 days of temperature control is as follows Figure 10 As shown in the figure, after three days of temperature control at 60°C, ΔDv increased to -0.2357 mm, 1.189 times that before temperature control; ΔDh increased to 0.1750 mm, 1.18 times that before temperature control. After three days of temperature control at 80°C, ΔDv increased to -0.2604 mm, 1.31 times that before temperature control; ΔDh increased to 0.1865 mm, 1.26 times that before temperature control.

[0027] After 50 kPa loading is completed, the deformation of the HDPE pipe section III is as follows: Figure 11 As shown in the figure, similar to sections I and II, with the application of load, the vertical and horizontal deformations of the HDPE pipe increase. The vertical deformation ΔDv is negative, indicating compression; the horizontal deformation ΔDh is positive, indicating tension. After the 50 kPa loading is completed, the pipeline ΔDv = -0.2018 mm, and ΔDh = 0.1514 mm.

[0028] The deformation data after 6 days of temperature control is as follows Figure 12 As shown in the figure, after three days of temperature control at 60°C, ΔDv increased to -0.2372 mm, 1.175 times that before temperature control; ΔDh increased to 0.1705 mm, 1.126 times that before temperature control. After three days of temperature control at 80°C, ΔDv increased to -0.2692 mm, 1.33 times that before temperature control; ΔDh increased to 0.182 mm, 1.2 times that before temperature control.

[0029] comprehensive Figure 8 、 Figure 10 and Figure 12 It can be seen that as the temperature increases, the deformation of the three cross sections of the HDPE pipe increases linearly, and the deformation growth rate tends to slow down over time.

[0030] Take the average value of the deformation of the three sections and express the deformation caused by load and temperature separately. Figure 13 and Figure 14 As can be seen, from 0 to 50 kPa, ΔDv / D increases from 0 to -0.1843%, and ΔDh / D increases from 0 to 0.1382%. Keeping the load constant, as the temperature control boundary temperature increases from 10°C to 60°C, ΔDv / D increases from -0.1843% to -0.2128%, a -0.0285% increase; ΔDh / D increases from 0.1382% to 0.1558%, a 0.0176% increase. Subsequently, as the temperature control boundary temperature increases from 60°C to 80°C, ΔDv / D increases from -0.2128% to -0.2502%, a -0.0374% increase; and ΔDh / D increases from 0.1558% to 0.1665%, a 0.0107% increase.

[0031] After 50 kN loading, the strains of sections I, II, and III of the HDPE pipe are as follows: Figure 15 、 Figure 16 and Figure 17 As shown. The circumferential strain values of HDPE pipes increase with the increase of load. The strains at 0°, 45°, and 180° are positive, which indicates tension; the strains at 90°, 270°, and 315° are negative, which indicates compression. The compression value at 270°, i.e., the bottom of the pipe, is the largest. This is the same as the results of the HDPE stress deformation test at room temperature. The circumferential strain values at 0° and 180° have the same sign and are similar in size, which is consistent with the fact that 0° and 180° are in symmetrical positions, i.e., the two points are symmetrical and the stress states are also symmetrical. The strain value at 0° is positive, indicating tension; the strain value at 90° is negative, indicating compression; there is a transition region from tension to compression between 0° and 90°. Similarly, there is a transition region from tension to compression between 0° and 270°; When applying load to HDPE pipe test samples, an electro-hydraulic servo system can be used to achieve precise loading rates, in conjunction with a pressure-maintaining mechanism. When measuring the temperature of HDPE pipe test samples, embedded heating plates and a distributed temperature sensor network are evenly arranged around the HDPE pipe test samples to adjust the temperature and ensure uniform heating throughout the pipe body. In addition, by integrating fiber Bragg grating strain sensing with 3D laser scanning technology, the maximum axial deformation data and the maximum radial deformation data can be simultaneously captured. Through dual-variable combined testing of load and temperature, the true deformation characteristics of HDPE pipes under complex environmental conditions can be systematically evaluated, overcoming the limitations of traditional single-factor testing. Combined testing covering both extreme and typical operating conditions provides a basis for reliability verification in practical engineering scenarios such as pipeline burial in cold regions and high-temperature fluid transportation. Simultaneously acquiring axial and radial deformation data helps reveal the anisotropic deformation patterns of HDPE pipes under varying loads and temperatures, providing data support for the subsequent construction of a mapping model for axial and radial deformation data. Through standardized load accuracy control (±0.5kN) and temperature gradient settings, a reproducible test benchmark is established, enhancing the accuracy of product performance evaluation. S3, using the average value of the axial maximum deformation data and the radial maximum deformation data obtained in S2, the load test data set, and the temperature test data set to construct a HDPE pipe deformation mapping model; The S3 includes the following steps: S31, constructing a HDPE pipe axial maximum deformation mapping model based on the pipe deformation controlled variable data set and the pipe test axial maximum deformation data set; Constructing a HDPE pipe radial maximum deformation mapping model based on the pipe deformation controlled variable data set and the pipe test radial maximum deformation data set; Preferably, the S31 includes the following steps: S311, respectively construct the initial radial basis function-fully connected hybrid network model and the initial convolutional capsule network model; the specific structure can be referred to as follows, RBF-FC Hybrid Network: 1. Input layer: 2 nodes (load value, temperature value); RBF hidden layer: 32 Gaussian kernel units, σ = 0.5; 3. Activation function: Softplus (smooth ReLU variant); 4. Fully connected layer structure: FC1: 64 nodes + LeakyReLU (α=0.1), FC2: 32 nodes + ELU activation; 5. Output layer: 1-node (axial deformation) linear output; residual connection is used to skip the RBF layer, and the batch normalization layer is placed after FC1; ‌Convolutional Capsule Network‌ 1. Feature extraction module: Convolutional layer Conv1D: 16 channels, kernel size 5, stride 1; 2. Maximum pooling layer: pooling size is 2; 3. Activation function: Swish; 4. Capsule Network Module: Primary capsule layer: 8 capsules, 16-dimensional vector, dynamic routing iteration 3 times; 5. Fully connected decoder: FC1: 32 nodes + GELU activation; 6. Dropout layer: 0.3 ratio; 7. Output layer: 1 node (radial deformation) Sigmoid constraint; The initial radial basis function-fully connected hybrid network model and the initial convolutional capsule network model both require a mean square error loss function, and it is recommended to use the adaptive moment estimation optimizer (AdamW) for training. In this way, an autoencoder can be introduced for pre-training to enhance feature extraction capabilities in small sample scenarios. S312, constructing a first training data ratio and a second training data ratio; using the first training data ratio to divide the pipe deformation controlled variable data set and the pipe test axial maximum deformation data set to obtain a first training data set and a first test data set; Using the second training data ratio, data division is performed on the pipe deformation controlled variable data set and the pipe test radial maximum deformation data set to obtain a second training data set and a second test data set; S313, setting a first training error threshold and a second training error threshold; using the first training data set to train the initial radial basis function-fully connected hybrid network model; during the training process, when the training error is less than the first training error threshold, stopping the training to obtain a trained radial basis function-fully connected hybrid network model; otherwise, continuing the training; Using the second training data set to train the initial convolutional capsule network model; during the training process, when the training error is less than the second training error threshold, stopping the training to obtain the trained convolutional capsule network model; otherwise, continuing the training; S314. Setting a first test accuracy threshold and a second test accuracy threshold; testing the trained radial basis function-fully connected hybrid network model using the first test data set; obtaining first test accuracy data after the test is completed; and using the trained radial basis function-fully connected hybrid network model as the HDPE pipe axial maximum deformation mapping model when the first test accuracy data is greater than or equal to the first test accuracy threshold. The trained convolutional capsule network model is then tested using the second test data set; after the test is completed, the second test accuracy data is obtained; when the second test accuracy data is greater than or equal to the second test accuracy threshold, the trained convolutional capsule network model is used as the HDPE pipe radial maximum deformation mapping model.

[0032] The radial basis function-fully connected hybrid network model accurately captures the nonlinear mapping relationship between load, temperature, and axial deformation through a Gaussian kernel function. Its local response characteristics can effectively identify the critical point of material yield, while the vector neurons of the convolutional capsule network can model the multi-dimensional geometric characteristics of radial deformation. In addition, the radial basis function-fully connected hybrid network model reduces dependence on the amount of axial data, and the equivariance characteristics of the convolutional capsule network enhance the stability of radial predictions under unseen working conditions. By correlating load-temperature dual variables with deformation data, the nonlinear response of materials in composite stress fields can be quantified, significantly improving prediction accuracy. Collaborative analysis of axial and radial deformation models can identify potential failure modes (such as buckling or creep rupture) of pipelines under extreme operating conditions, providing a two-dimensional basis for safety assessment. The deformation data output by the model provides data guidance for the subsequent printing of shape memory polymer composite layers on the outer wall of the pipe. S4, inputting the current actual load and temperature data around the HDPE into the HDPE pipe deformation mapping model for mapping; The S4 comprises the following steps: S41, obtaining the maximum axial deformation data and the maximum radial deformation data of each HDPE pipe test sample after the load and temperature are applied in S22, and obtaining a historical maximum axial deformation data set and a historical maximum radial deformation data set; Then, a coordinate system is established for each HDPE pipe test sample using the same coordinate origin; and based on the established coordinate system, the deformation position coordinates corresponding to the axial maximum deformation data and the radial maximum deformation data of each HDPE pipe test sample are obtained to obtain a historical axial deformation position coordinate set and a historical radial deformation position coordinate set; S42, setting printing parameters for the shape memory polymer composite material and several types of the shape memory polymer composite material for printing on the HDPE tube to obtain a composite material printing parameter type set; the composite material printing parameter type set includes a printing position and a printing amount; S43. Set the current HDPE pipe; use a temperature sensor and a mechanical sensor to collect and calculate average load and temperature data around the HDPE pipe to obtain average load data and average temperature data of the current pipe; input the average load data and average temperature data of the current pipe into an HDPE pipe axial maximum deformation mapping model and an HDPE pipe radial maximum deformation mapping model for mapping, respectively, to obtain the current pipe axial maximum deformation data and the current pipe radial maximum deformation data; By establishing a standardized coordinate system and deformation position coordinate set, accurate quantitative analysis of the deformation behavior of HDPE pipes under different working conditions is achieved, providing a complete deformation feature database for pipeline structural reliability assessment; the establishment of historical deformation data sets and position coordinate sets provides a spatial positioning basis for parameter setting of shape memory polymer repair solutions, so that the determination of printing position and printing volume has data support, avoiding redundant or insufficient repair materials; integrating deformation data under load and temperature can reveal the influence of complex environmental factors on pipeline performance, and provide a theoretical basis for the development of environmentally adaptable composite material printing parameters; using a unified coordinate origin makes the test data from different batches and different test conditions comparable, which is conducive to the establishment of a pipeline full life cycle performance evaluation system; in addition, the current maximum axial deformation data of the pipe and the current maximum radial deformation data of the pipe are obtained through mapping, providing data support for determining the optimal printing parameters when printing composite materials for the current HDPE pipe in the future; S5. Obtain the deformation position coordinates corresponding to the axial maximum deformation data and the radial maximum deformation data of multiple HDPE pipe test samples in S2, the printing volume during the printing process, the printing position coordinate data, and the axial and radial deformation difference before and after the application of load and temperature, and construct a pipe printing deformation mapping model; The S5 comprises the following steps: S51. Perform a shape memory polymer composite material printing operation on each HDPE pipe test sample in S41, obtain composite material printing volume data, printing position coordinate data, and absolute values of axial and radial deformation differences of each HDPE pipe test sample after the applied load and temperature are removed and before the applied load and temperature are applied, to obtain a historical pipe printing volume dataset, a historical pipe printing position coordinate dataset, a historical pipe axial deformation difference dataset, and a historical pipe radial deformation difference dataset; S52, constructing a tube printing axial deformation mapping model and a tube printing radial deformation mapping model based on the historical maximum axial deformation dataset, the historical maximum radial deformation dataset, the historical axial deformation position coordinate set, the historical radial deformation position coordinate set, the historical tube printing amount dataset, the historical tube printing position coordinate dataset, the historical tube axial deformation difference dataset, and the historical tube radial deformation difference dataset; Preferably, the S52 includes the following steps: S521, constructing an initial 3D convolutional neural network model and an initial graph neural network model respectively; S522, using the historical maximum axial deformation dataset, the historical axial deformation position coordinate dataset, the historical tube printing amount dataset, the historical tube printing position coordinate dataset, and the historical tube axial deformation difference dataset to train and test the initial 3D convolutional neural network model; after the training and testing are completed, a tube printing axial deformation mapping model is obtained; The initial graph neural network model is trained and tested using the historical maximum radial deformation dataset, the historical radial deformation position coordinate dataset, the historical tube printing amount dataset, the historical tube printing position coordinate dataset, and the historical tube radial deformation difference dataset; after the training and testing are completed, a tube printing radial deformation mapping model is obtained; Initial 3D Convolutional Neural Network (3D-CNN): Input layer: receives a multidimensional tensor consisting of deformation coordinates (3D), printing volume, and printing position; Convolution module: 3 layers of 3D convolution kernels (16 / 32 / 64 channels), kernel size 3×3×3, stride 1×1×1; Activation function: LeakyReLU (α=0.1); Pooling layer: 3D maximum pooling (2×2×2); Attention module: spatial-channel dual attention mechanism; Fully connected layer: 2 layers of FC (256 / 128 nodes); Dropout rate is 0.3 Output layer: linear activation; Graph Neural Networks (GNNs) Graph structure: Node features: local deformation gradient + printing parameters; Edge features: tube segment curvature change rate; Graph convolution module: 3 layers of GraphSAGE convolution; Aggregation function: mean pooling; Time series processing: Bidirectional LSTM layer (64 units) processes the load history; Fusion layer: concatenates graph features and temporal features; 2-layer FC (128 / 64 nodes) Output layer: Sigmoid activation; The 3D convolutional neural network uses a cubic convolution kernel to simultaneously extract the spatial correlation features of printing position coordinates, deformation gradients, and print volume, effectively modeling the three-dimensional deposition effect of composite materials on pipe surfaces. Its multi-level convolutional structure can automatically identify the nonlinear coupling relationship between local deformation hotspots and printing parameters. The graph neural network uses a graph structure to express the mechanical transmission path between pipeline nodes and aggregates neighborhood deformation features through a message passing mechanism, making it suitable for handling the circumferential continuity constraints of radial deformation of HDPE pipes. Its edge feature modeling capability can accurately reflect the repair effect of printed materials on changes in pipe curvature. By integrating printing parameters and deformation recovery data, a quantitative evaluation system for shape memory polymer repair effects was established. This system provides data support for optimizing the printing volume of subsequent repair solutions and significantly improves the accuracy of the repair process. The construction of a deformation difference data set verifies the effectiveness of different printing parameters on pipeline shape recovery. An axial / radial deformation mapping model, constructed based on seven types of historical data sets, can predict the deformation recovery effect under specific printing solutions, providing a visual decision-making tool for pipeline repair and reducing trial-and-error costs. S6. According to the data mapped in S4 and the pipe printing deformation mapping model, the printing volume and printing position corresponding to the current HDPE pipe printing operation are iteratively adjusted, and the minimum printing volume and corresponding printing position are selected; The S6 comprises the following steps: S61, setting a current tube axial deformation threshold and a current tube radial deformation threshold; when the current tube maximum axial deformation data is greater than or equal to the current tube axial deformation threshold or the current tube maximum radial deformation data is greater than or equal to the current tube radial deformation threshold, performing a shape memory polymer composite material printing operation on the current HDPE tube and proceeding to S62; S62, obtaining the preset current print volume, the preset current print position, and the corresponding value ranges in the print operation in S61, and obtaining the current print volume value range and the current print position value range; S63, setting a current tube axial deformation difference threshold, a current tube radial deformation difference threshold, a current tube axial deformation position coordinate interval, and a current tube radial deformation position coordinate interval; Traversing the current tube axial deformation position coordinate interval, inputting the preset current printing amount, the preset current printing position, the current tube axial maximum deformation data, and the traversed current tube axial deformation position coordinates into a tube printing axial deformation mapping model for mapping, until the traversal of the current tube axial deformation position coordinate interval is completed, thereby obtaining a current tube axial deformation difference value set; Then, the current tube radial deformation position coordinate interval is traversed, and the preset current printing amount, the preset current printing position, the current tube radial maximum deformation data, and the traversed current tube radial deformation position coordinate are input into the tube printing radial deformation mapping model for mapping, until the traversal of the current tube radial deformation position coordinate interval is completed, thereby obtaining a current tube radial deformation difference value set; S64, adjusting the printing volume and printing position in the current composite material printing process according to the current tube axial deformation difference threshold, the current tube radial deformation difference threshold, the current tube axial deformation difference set, and the current tube radial deformation difference set; after the adjustment is completed, obtaining current final printing volume data and current final printing position coordinate data; The S64 includes the following steps: S641. When an axial deformation difference value greater than or equal to the current tube axial deformation difference threshold value exists in the current tube axial deformation difference value set or a radial deformation difference value greater than or equal to the current tube radial deformation difference threshold value exists in the current tube radial deformation difference value set, the preset current printing amount and the preset current printing position are adjusted simultaneously by traversing the current printing amount value interval and the current printing position value interval, and S63 is repeated until no axial deformation difference value greater than or equal to the current tube axial deformation difference threshold value exists in the current tube axial deformation difference value set and no radial deformation difference value greater than or equal to the current tube radial deformation difference threshold value exists in the current tube radial deformation difference value set; and the current printing amount data of the current traversal is recorded. S642, repeating the process of traversing the current print volume value interval and the current print position value area in S641 until the traversal is completed, and obtaining a current record of qualified print volume data set; The minimum print amount data and the corresponding print position coordinate data in the currently recorded qualified print amount data set are used as the current final print amount data and the current final print position coordinate data; Through a dual loop structure of threshold determination and interval traversal, real-time dynamic optimization of printing parameters is achieved. It can automatically identify areas with excessive deformation and trigger parameter adjustments to ensure that the repair effect always meets the preset deformation tolerance requirements. A minimum qualified print volume screening strategy is adopted to significantly reduce material consumption while ensuring repair quality. Furthermore, the axial and radial deformation indicators are simultaneously verified during the iterative adjustment process, effectively addressing parameter coupling interference under complex pipeline deformation conditions. S65, performing an actual deformation correction printing operation on the current HDPE pipe according to the current final printing amount data and the current final printing position coordinate data; For example, when using DN200 HDPE pipe (outer diameter 225mm), the axial deformation threshold is set to 3.2mm and the radial deformation threshold is set to 4.5mm. The repair procedure is triggered when an axial displacement ≥3.2mm or a radial expansion ≥4.5mm is detected; The preset print volume range is [15g / m, 35g / m], and the print position covers a sector-shaped area of ±60° on the pipe surface; the coordinate positioning accuracy reaches 0.1mm, and the position is marked using the polar coordinate system (r, θ); The initial print weight of 25g / m was input into the axial deformation model. The prediction results showed a 4.1mm deformation difference at the coordinate (1.2m, 30°) (exceeding the 3.5mm threshold). After three iterations, the optimal print weight was determined to be 18.6g / m; Radial repair adopts a layered printing strategy: the first layer of basic repair uses 12.3g / m (covering the 0°-120° area), and the second layer of reinforcement uses 7.2g / m (focusing on the 45°-75° high stress area); the total material consumption is reduced by 37% compared with the traditional process.

[0033] After repair, the axial residual deformation of the pipe is 0.8mm (less than 1.2mm tolerance), and the radial roundness error is 1.3mm (less than 1.5mm tolerance). After 500 pressure cycle tests (0.6-1.2MPa), the deformation retention rate is ≥92%; Through the dual judgment criteria of axial / radial deformation thresholds, accurate identification of pipeline damage and automatic control of repair timing are achieved, avoiding subjective errors in manual judgment; the threshold trigger mechanism ensures that repair operations are initiated only at the critical point of structural safety, which not only protects pipeline integrity but also saves repair materials; the dynamic mapping relationship between the deformation difference set and the printing parameters can automatically correct the printing strategy according to the actual repair effect, significantly improving the repair accuracy of shape memory polymers; the threshold-controlled on-demand repair mode reduces material waste, while the parameter range optimization shortens the trial and error cycle, comprehensively reducing maintenance costs, which is conducive to extending the service life of the pipeline and achieving full life cycle cost optimization; because the specific position coordinates of the axial and radial deformation of HDPE pipes under the combined effects of load and temperature are difficult to predict in advance, this solution uses an iterative traversal method to map the coordinates of each position that may cause deformation in turn, ensuring that the various deformation situations can be taken into account and further measures can be taken.

[0034] Example 2

[0035] See also Figure 5This embodiment discloses a system for analyzing and repairing HDPE pipe deformation data based on multi-source data. The system can implement the method of the above embodiment and includes an HDPE pipe deformation test application data setting module, an HDPE deformation test module, an HDPE pipe deformation mapping model construction module, a historical pipe deformation position coordinate acquisition module, a composite material printing parameter type setting module, a current pipe deformation data mapping module, a pipe printing deformation mapping model construction module, and a current pipe printing parameter adjustment module. The HDPE pipe deformation test application data setting module sets a plurality of load test data and temperature test data to obtain a load test data set and a temperature test data set; The HDPE deformation test module performs deformation tests on multiple HDPE pipe test samples according to the load test data set and the temperature test data set and obtains the average value of the corresponding axial maximum deformation data and radial maximum deformation data; The HDPE pipe deformation mapping model construction module uses the average value of the axial maximum deformation data and the radial maximum deformation data obtained by S2, the load test data set, and the temperature test data set to construct the HDPE pipe deformation mapping model; The historical pipe deformation position coordinate acquisition module acquires the deformation position coordinates corresponding to the axial maximum deformation data and radial maximum deformation data of multiple HDPE pipe test samples in S2; The composite material printing parameter type setting module sets several types of printing parameters for printing shape memory polymer composite materials on HDPE tubes; The current pipe deformation data mapping module inputs the current actual load and temperature data around the HDPE into the mapping model constructed in S3 for mapping; The tube printing deformation mapping model construction module obtains composite material printing amount data, printing position coordinate data, and axial and radial deformation difference before and after load and temperature application during the composite material printing process for each HDPE tube test sample, and then constructs the tube printing deformation mapping model based on the obtained data; The current tube printing parameter adjustment module cooperates with the data mapped in S4 and the tube printing deformation mapping model constructed in S5 to iteratively adjust the preset current printing volume and preset current printing position corresponding to the printing operation of the current HDPE tube, and selects the smallest current printing volume and corresponding current printing position.

[0036] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0037] The preferred embodiments of the invention disclosed above are intended only to help illustrate the invention. These preferred embodiments do not exhaust all details, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the content of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention.

Claims

1. The HDPE pipe deformation data analysis and repair method based on multi-source data is characterized by: The following steps are involved: S1. Set a number of load test data and temperature test data; S2. Perform deformation tests on multiple HDPE pipe test samples according to the test data set in S1 and obtain the corresponding average values of maximum axial deformation data and maximum radial deformation data; S3, using the average value of the axial maximum deformation data and the radial maximum deformation data obtained in S2, the load test data set, and the temperature test data set to construct a HDPE pipe deformation mapping model; S4, inputting the current actual load and temperature data around the HDPE into the HDPE pipe deformation mapping model for mapping; S5. Obtain the deformation position coordinates corresponding to the axial maximum deformation data and the radial maximum deformation data of multiple HDPE pipe test samples in S2, the printing volume during the printing process, the printing position coordinate data, and the axial and radial deformation difference before and after the application of load and temperature, and construct a pipe printing deformation mapping model; S6. According to the data obtained by mapping in S4 and the pipe printing deformation mapping model, the printing volume and printing position corresponding to the current HDPE pipe printing operation are iteratively adjusted, and the minimum printing volume and corresponding printing position are selected.

2. The HDPE pipe deformation data analysis and repair method based on multi-source data according to claim 1 is characterized in that: Said S1 comprises the following steps: S11. Set a number of HDPE pipe samples for testing to obtain a set of HDPE pipe test samples; then set a set of HDPE pipe deformation controlled variables, wherein the set of HDPE pipe deformation controlled variables includes load and temperature; S12, setting a load test data interval and a temperature test data interval; setting a plurality of load test data and temperature test data according to the load test data interval and the temperature test data interval to obtain a load test data set and a temperature test data set.

3. The HDPE pipe deformation data analysis and repair method based on multi-source data according to claim 2 is characterized in that: The S2 comprises the following steps: S21, combining the data in the load test data set and the temperature test data set in pairs to obtain a pipe deformation controlled variable data combination set; S22. Based on the HDPE pipe test sample set, the pipe deformation controlled variable data combination set is used to apply load and temperature to each HDPE pipe test sample. After the application, the axial maximum deformation data and the radial maximum deformation data of each HDPE pipe test sample are measured and the average values are calculated to obtain the pipe test axial maximum deformation data set and the pipe test radial maximum deformation data set.

4. The HDPE pipe deformation data analysis and repair method based on multi-source data according to claim 3 is characterized in that: The S3 includes the following steps: S31, constructing a HDPE pipe axial maximum deformation mapping model based on the pipe deformation controlled variable data set and the pipe test axial maximum deformation data set; Constructing a HDPE pipe radial maximum deformation mapping model based on the pipe deformation controlled variable data set and the pipe test radial maximum deformation data set; The HDPE pipe axial maximum deformation mapping model and the HDPE pipe radial maximum deformation mapping model respectively adopt a radial basis function-fully connected hybrid network model and a convolutional capsule network model.

5. The HDPE pipe deformation data analysis and repair method based on multi-source data according to claim 4 is characterized in that: The S4 comprises the following steps: S41, obtaining the maximum axial deformation data and the maximum radial deformation data of each HDPE pipe test sample after the load and temperature are applied in S22, and obtaining a historical maximum axial deformation data set and a historical maximum radial deformation data set; Obtain the deformation position coordinates corresponding to the axial maximum deformation data and the radial maximum deformation data of each HDPE pipe test sample, and obtain a historical axial deformation position coordinate set and a historical radial deformation position coordinate set; S42, setting printing parameters for the shape memory polymer composite material and several types of the shape memory polymer composite material for printing on the HDPE tube to obtain a composite material printing parameter type set; the composite material printing parameter type set includes a printing position and a printing amount; S43. Use temperature sensors and mechanical sensors to collect and calculate the average load and temperature data around the current HDPE pipe to obtain the average load data and the average temperature data of the current pipe; input the current average load data and the current average temperature data of the current pipe into the HDPE pipe axial maximum deformation mapping model and the HDPE pipe radial maximum deformation mapping model for mapping, to obtain the current pipe axial maximum deformation data and the current pipe radial maximum deformation data.

6. The HDPE pipe deformation data analysis and repair method based on multi-source data according to claim 5 is characterized in that: The S5 comprises the following steps: S51. Perform a shape memory polymer composite material printing operation on each HDPE pipe test sample in S41, obtain composite material printing volume data, printing position coordinate data, and absolute values of axial and radial deformation differences of each HDPE pipe test sample after the applied load and temperature are removed and before the applied load and temperature are applied, to obtain a historical pipe printing volume dataset, a historical pipe printing position coordinate dataset, a historical pipe axial deformation difference dataset, and a historical pipe radial deformation difference dataset; S52. Construct a tube printing axial deformation mapping model and a tube printing radial deformation mapping model based on the historical maximum axial deformation data set, the historical maximum radial deformation data set, the historical axial deformation position coordinate set, the historical radial deformation position coordinate set, the historical tube printing amount data set, the historical tube printing position coordinate data set, the historical tube axial deformation difference data set, and the historical tube radial deformation difference data set.

7. The HDPE pipe deformation data analysis and repair method based on multi-source data according to claim 6 is characterized by: The tube printing axial deformation mapping model and the tube printing radial deformation mapping model described in S52 respectively adopt a 3D convolutional neural network model and a graph neural network model.

8. The HDPE pipe deformation data analysis and repair method based on multi-source data according to claim 7 is characterized in that: The S6 comprises the following steps: S61, setting a current tube axial deformation threshold and a current tube radial deformation threshold; when the current tube maximum axial deformation data is greater than or equal to the current tube axial deformation threshold or the current tube maximum radial deformation data is greater than or equal to the current tube radial deformation threshold, performing a shape memory polymer composite material printing operation on the current HDPE tube and proceeding to S62; S62, obtaining the preset current print volume, the preset current print position, and the corresponding value ranges in the print operation in S61, and obtaining the current print volume value range and the current print position value range; S63, setting a current tube axial deformation difference threshold, a current tube radial deformation difference threshold, a current tube axial deformation position coordinate interval, and a current tube radial deformation position coordinate interval; Traversing the current tube axial deformation position coordinate interval, inputting the preset current printing amount, the preset current printing position, the current tube axial maximum deformation data, and the traversed current tube axial deformation position coordinates into a tube printing axial deformation mapping model for mapping, until the traversal of the current tube axial deformation position coordinate interval is completed, thereby obtaining a current tube axial deformation difference value set; Then, the current tube radial deformation position coordinate interval is traversed, and the preset current printing amount, the preset current printing position, the current tube radial maximum deformation data, and the traversed current tube radial deformation position coordinate are input into the tube printing radial deformation mapping model for mapping, until the traversal of the current tube radial deformation position coordinate interval is completed, thereby obtaining a current tube radial deformation difference value set; S64, adjusting the printing volume and printing position in the current composite material printing process according to the current tube axial deformation difference threshold, the current tube radial deformation difference threshold, the current tube axial deformation difference set, and the current tube radial deformation difference set; after the adjustment is completed, obtaining current final printing volume data and current final printing position coordinate data; S65 , performing an actual deformation correction printing operation on the current HDPE pipe according to the current final printing amount data and the current final printing position coordinate data.

9. The HDPE pipe deformation data analysis and repair method based on multi-source data according to claim 8, characterized in that: The S64 includes the following steps: S641. When an axial deformation difference value greater than or equal to the current tube axial deformation difference threshold value exists in the current tube axial deformation difference value set or a radial deformation difference value greater than or equal to the current tube radial deformation difference threshold value exists in the current tube radial deformation difference value set, the preset current printing amount and the preset current printing position are adjusted simultaneously by traversing the current printing amount value interval and the current printing position value interval, and S63 is repeated until no axial deformation difference value greater than or equal to the current tube axial deformation difference threshold value exists in the current tube axial deformation difference value set and no radial deformation difference value greater than or equal to the current tube radial deformation difference threshold value exists in the current tube radial deformation difference value set; and the current printing amount data of the current traversal is recorded. S642, repeating the process of traversing the current print volume value interval and the current print position value area in S641 until the traversal is completed, and obtaining a current record of qualified print volume data set; The minimum print amount data and the corresponding print position coordinate data in the currently recorded qualified print amount data set are used as the current final print amount data and the current final print position coordinate data.

10. A system for implementing the HDPE pipe deformation data analysis and repair method based on multi-source data according to any one of claims 1 to 9, characterized in that: It includes an HDPE pipe deformation test application data setting module, an HDPE deformation test module, an HDPE pipe deformation mapping model construction module, a historical pipe deformation position coordinate acquisition module, a composite material printing parameter type setting module, a current pipe deformation data mapping module, a pipe printing deformation mapping model construction module, and a current pipe printing parameter adjustment module; The HDPE pipe deformation test application data setting module sets a plurality of load test data and temperature test data to obtain a load test data set and a temperature test data set; The HDPE deformation test module performs deformation tests on multiple HDPE pipe test samples according to the load test data set and the temperature test data set and obtains the average value of the corresponding axial maximum deformation data and radial maximum deformation data; The HDPE pipe deformation mapping model construction module uses the average value of the axial maximum deformation data and the radial maximum deformation data obtained by S2, the load test data set, and the temperature test data set to construct the HDPE pipe deformation mapping model; The historical pipe deformation position coordinate acquisition module acquires the deformation position coordinates corresponding to the axial maximum deformation data and radial maximum deformation data of multiple HDPE pipe test samples in S2; The composite material printing parameter type setting module sets several types of printing parameters for printing shape memory polymer composite materials on HDPE tubes; The current pipe deformation data mapping module inputs the current actual load and temperature data around the HDPE into the mapping model constructed in S3 for mapping; The tube printing deformation mapping model construction module obtains composite material printing amount data, printing position coordinate data, and axial and radial deformation difference before and after load and temperature application during the composite material printing process for each HDPE tube test sample, and then constructs the tube printing deformation mapping model based on the obtained data; The current tube printing parameter adjustment module cooperates with the data mapped in S4 and the tube printing deformation mapping model constructed in S5 to iteratively adjust the preset current printing volume and preset current printing position corresponding to the printing operation of the current HDPE tube, and selects the smallest current printing volume and corresponding current printing position.

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