Non-excavation type repairing method for municipal low-pressure pipeline

Abstract

The invention relates to the technical field of trenchless repair, and discloses a trenchless repair method for a municipal low-pressure pipeline, which comprises the following specific steps: step 1, pretreatment of the inner wall of the pipeline: alternately washing the inner wall of the pipeline through high-pressure water jet with the pressure of 50-80MPa and gas pulse with the frequency of 2-5Hz, repeatedly washing for more than or equal to 3 times, and removing attachments on the wall of the pipeline; 2, three-dimensional defect surveying and mapping are conducted, a pipeline robot carrying a laser scanner is adopted to generate a 3D topological graph of the inner wall of the pipeline, and an area with the pipe diameter deformation exceeding 2% is marked. The inner wall of the pipeline can be deeply cleaned and repaired from the inner wall of the pipeline through inner wall pretreatment of alternate flushing of high-pressure water jet and gas pulse, large-area pavement excavation is avoided through non-excavation type repair, interference to traffic and resident life is reduced, long-time road blocking is not needed in the construction process, and the construction efficiency is improved. Traffic jam and inconvenience in travel caused by construction are reduced, and the urban operation efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of trenchless repair technology, specifically a trenchless repair method for municipal low-pressure pipelines. Background Technology

[0002] Municipal low-pressure pipelines are pipeline systems used in municipal engineering to transport fluids at relatively low operating pressures. They are widely used in various fields such as urban water supply, drainage, and gas supply. Trenchless repair refers to a series of technical methods for repairing underground municipal low-pressure pipelines without large-scale ground excavation.

[0003] Currently, urban underground gas pipeline systems are generally facing problems such as aging and corrosion. Traditional maintenance methods usually require large-scale road excavation, which is not only time-consuming and labor-intensive, but also seriously affects traffic and residents' lives, impacts the urban environment, and is inefficient. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a trenchless repair method for municipal low-pressure pipelines, solving the problems of requiring large-scale road excavation, affecting traffic and residents' lives, impacting the urban environment, and resulting in low work efficiency.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a trenchless repair method for municipal low-pressure pipelines, comprising the following specific steps: Step 1: Pre-treatment of the inner wall of the pipe. The inner wall of the pipe is flushed alternately with high-pressure water jets at a pressure of 50-80MPa and air pulses at a frequency of 2-5Hz. The flushing is repeated ≥3 times to remove the deposits on the pipe wall. Step 2, 3D defect mapping: A pipeline robot equipped with a laser scanner is used to generate a 3D topological map of the inner wall of the pipeline, marking areas where the pipe diameter deformation exceeds 2%. Step 3: AI defect classification. Based on convolutional neural networks, semantic segmentation is performed on pipe endoscope images to identify three types of defects: through cracks, localized corrosion, and surface scratches. Repair priority maps are then generated according to the leakage risk level. Step 4: Segmented injection of composite material. The two-component UV-cured composite material containing a nano-silica reinforcement layer and glass fiber prepreg is injected into the pipeline in segments, with each segment not exceeding 5 meters in length. Step 5: Gradient photocuring. The composite material is pressed tightly against the tube wall by an inflatable airbag. An adjustable ultraviolet light source with a wavelength of 280-420nm is used to irradiate the material at a constant speed of V=K / D. At the same time, the light intensity is adjusted in real time according to the temperature feedback from the distributed optical fiber sensor to complete the gradient curing of the material.

[0006] Preferably, the air pulse in step one is dry compressed air with a water content ≤100ppm, and the single alternation interval between the water jet and the air pulse is 30-60 seconds.

[0007] Preferably, in step three, a convolutional neural network is used to perform semantic segmentation of the defects, and the classification criteria include: Class I defects: through-cracks or holes, which require priority repair; Class II defects: localized corrosion depth ≥ 30% of pipe wall thickness, requiring suboptimal repair; Class III defects: Surface scratches or corrosion depth less than 10% of the pipe wall thickness, repair can be postponed.

[0008] Preferably, in step four, the two-component UV-curable composite material includes: Component A: Modified epoxy acrylate resin containing 10-15wt% nano silica, with viscosity controlled at 500-800cps; Component B: Glass fiber prepreg with a fiber areal density of 200-300 g / m², and the fiber orientation is staggered with the pipe axis at ±45°.

[0009] Preferably, the nano-silica has a particle size of 20-50 nm, its surface is modified with a silane coupling agent, and the uniformity deviation of its mixing with the resin matrix is ​​≤5%.

[0010] Preferably, the operating parameters of the tunable wavelength ultraviolet light source satisfy: The wavelength range is 280-420nm, and the light intensity is automatically adjusted according to the type of pipe. Polyethylene pipes use the 300-350nm band, and cast iron pipes use the 380-420nm band. The moving speed V of the light source and the diameter D of the pipe satisfy the following relationship: V=K / D, where K is a correction factor of 150-200, in m·mm / min.

[0011] Preferably, the dynamic curing control includes: The pipe wall temperature is monitored in real time using distributed fiber optic sensors, and the temperature is controlled to be ≤80℃. Adjust the power of the ultraviolet light source according to the material curing exothermic curve to achieve an interfacial bonding strength of 15-20 MPa.

[0012] Preferably, the repair layer thickness is 0.8-1.5mm, and the pressure resistance test standard for the repaired pipeline is: no leakage after holding the pressure at 1.5 times the working pressure for 30 minutes.

[0013] Preferably, in step two, the laser scanner of the pipeline robot has an accuracy of ±0.1mm, and the 3D topology map is automatically uploaded to the cloud database for historical damage trend analysis after it is generated.

[0014] Preferably, the glass fiber prepreg is stored at a temperature of 5-25°C and needs to be preheated at 40-50°C for 10-15 minutes before use to eliminate internal air bubbles.

[0015] This invention provides a trenchless repair method for municipal low-pressure pipelines. It has the following advantages: 1. This invention repairs pipelines using a trenchless method. It utilizes alternating high-pressure water jets and air pulses for internal wall pretreatment, which can deeply clean the pipeline inner wall, removing oil stains and corrosion products. Repairing from the inner wall of the pipeline avoids large-scale road excavation, reduces interference with traffic and residents' lives, and eliminates the need for long-term road closures during construction, thus reducing traffic congestion and travel inconvenience caused by construction and improving the efficiency of urban operations.

[0016] 2. This invention utilizes a pipeline robot equipped with a laser scanner for 3D defect mapping. Combined with AI defect grading, it can accurately identify and classify various defects, including through cracks, localized corrosion, and surface scratches, and generate a repair priority map. This makes the repair work more targeted, avoids blind repair, and improves repair efficiency and quality. The segmented injection and gradient photocuring molding process of composite materials can ensure that the repair material is evenly distributed and fully cured in the pipeline, forming a strong and high-performance repair layer, thereby improving the overall performance and service life of the pipeline.

[0017] 3. This invention utilizes high-pressure water and air synergistic cleaning with alternating 50-80MPa water jets and 2-5Hz air pulses, increasing the cleaning efficiency by 3 times per cycle and shortening the pretreatment time to 2-4 hours. Dynamic ultraviolet curing with an adjustable light source of 280-420nm, combined with a V=K / D moving speed, ensures that the curing time for a single 5-meter pipe section is ≤10 minutes. The overall construction cycle is reduced to 40% of the traditional method, and the traffic impact time is reduced from 7 days to 12 hours. No road repair or earthwork transportation is required, resulting in a 60% reduction in overall construction costs. Attached Figure Description

[0018] Figure 1 This is a flowchart of a trenchless repair method for municipal low-pressure pipelines according to the present invention. Detailed Implementation

[0019] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see the appendix Figure 1This invention provides a trenchless repair method for municipal low-pressure pipelines, comprising the following specific steps: Step 1: Pre-treatment of the inner wall of the pipe. The inner wall of the pipe is flushed alternately with high-pressure water jets at a pressure of 50-80MPa and air pulses at a frequency of 2-5Hz. The flushing is repeated ≥3 times to remove the deposits on the pipe wall. High-pressure water jets utilize their powerful impact force to effectively remove oil stains and corrosion products from pipe walls. Air pulses, through instantaneous high-pressure gas impact, further remove fine particles and stubborn deposits remaining in the water jet, avoiding the limitations of a single cleaning method. After treatment, the surface roughness Ra of the pipe wall is ≤5μm, which greatly improves the adhesion between the subsequent repair material and the pipe wall. Alternating flushing can thoroughly clean the inner walls of pipes, providing a clean and good base surface for subsequent repair work; Step 2, 3D defect mapping: A pipeline robot equipped with a laser scanner is used to generate a 3D topological map of the inner wall of the pipeline, marking areas where the pipe diameter deformation exceeds 2%. Principle: Pipeline robots equipped with laser scanners can emit laser beams. By measuring the time difference between the emission and reception of the laser beam, the distance between various points on the inner wall of the pipeline can be calculated, thereby constructing a 3D topology map. The generated 3D topology map can intuitively display the shape and defects of the pipe's inner wall, and mark areas where the pipe diameter deformation exceeds the threshold, thereby providing data support for repair decisions; The pipeline robot's laser scanner has an accuracy of ±0.1mm, which can capture tiny defects and deformations. After the 3D topology map is generated, it is automatically uploaded to the cloud database for historical damage trend analysis, which helps to predict potential problems and formulate prevention and repair strategies in advance. Step 3: AI defect classification. Based on convolutional neural networks, semantic segmentation is performed on pipe endoscope images to identify three types of defects: through cracks, localized corrosion, and surface scratches. Repair priority maps are then generated according to the leakage risk level. Convolutional neural networks learn from a large number of labeled pipe endoscope images, enabling them to automatically extract features from the images and classify and grade defects based on these features. Defect classification can help determine the order of repairs and key areas, making the repair work more targeted and efficient; After training, the convolutional neural network used achieves a localization error of <2cm for Class I defects and an accuracy rate of ≥97% in determining repair priority. It can significantly reduce invalid repair areas and improve the utilization efficiency of repair resources. Step 4: Segmented injection of composite material. The two-component UV-cured composite material containing a nano-silica reinforcement layer and glass fiber prepreg is injected into the pipeline in segments, with each segment not exceeding 5 meters in length. Nano-silica can fill the micropores of resin, improving the density and strength of composite materials. The staggered arrangement of glass fiber prepreg can enhance the mechanical properties of pipes in different directions, improving their compressive and tensile strength. By injecting in stages, the composite material can be evenly distributed within the pipe, thus playing a role in reinforcement and repair. The combination of composite materials can effectively repair pipeline defects and improve the overall performance and service life of pipelines; Step 5: Gradient photocuring. The composite material is pressed tightly against the tube wall by an inflatable airbag. An adjustable ultraviolet light source with a wavelength of 280-420nm is used to irradiate the material at a constant speed of V=K / D. At the same time, the light intensity is adjusted in real time according to the temperature feedback from the distributed optical fiber sensor to complete the gradient curing of the material.

[0021] The inflatable airbag provides uniform pressure, allowing the composite material to adhere tightly to the tube wall. The specific wavelength of the adjustable ultraviolet light source can trigger the curing reaction of the composite material. By controlling the moving speed and light intensity of the light source, the gradient curing of the material can be achieved. Ensure that the composite material fully cures inside the pipe to form a repair layer, thereby improving the pipe's sealing and strength; By monitoring the pipe wall temperature in real time and adjusting the light intensity, the temperature during the curing process can be effectively controlled, avoiding the degradation of material properties caused by overheating. After curing, the interface bonding strength reaches 15-20MPa, and the repair layer thickness is 0.8-1.5mm, enabling the repaired pipe to withstand 1.5 times the working pressure for 30 minutes without leakage.

[0022] In step one, the air pulse uses dry compressed air with a water content of ≤100ppm, and the single alternation interval between the water jet and the air pulse is 30-60 seconds.

[0023] In step three, a convolutional neural network is used to perform semantic segmentation of the defects. The classification criteria include: Class I defects: through-cracks or holes, which require priority repair; Class II defects: localized corrosion depth ≥ 30% of pipe wall thickness, requiring suboptimal repair; Class III defects: Surface scratches or corrosion depth less than 10% of the pipe wall thickness, repair can be postponed.

[0024] In step four, the two-component UV-cured composite material includes: Component A: Modified epoxy acrylate resin containing 10-15wt% nano silica, with viscosity controlled at 500-800cps; Component B: Glass fiber prepreg with a fiber areal density of 200-300 g / m², and the fiber orientation is staggered with the pipe axis at ±45°.

[0025] The nano-silica has a particle size of 20-50nm, its surface is modified with a silane coupling agent, and the uniformity deviation of mixing with the resin matrix is ​​≤5%.

[0026] The operating parameters of the tunable wavelength ultraviolet light source meet the following requirements: The wavelength range is 280-420nm, and the light intensity is automatically adjusted according to the type of pipe. Polyethylene pipes use the 300-350nm band, and cast iron pipes use the 380-420nm band. The moving speed V of the light source and the diameter D of the pipe satisfy the following relationship: V=K / D, where K is a correction factor of 150-200, in m·mm / min.

[0027] Dynamic curing control includes: The pipe wall temperature is monitored in real time using distributed fiber optic sensors, and the temperature is controlled to be ≤80℃. Adjust the power of the ultraviolet light source according to the material curing exothermic curve to achieve an interfacial bonding strength of 15-20 MPa.

[0028] The repair layer thickness is 0.8-1.5mm, and the pressure resistance test standard for the repaired pipeline is: no leakage after holding the pressure at 1.5 times the working pressure for 30 minutes.

[0029] In step two, the laser scanner of the pipeline robot has an accuracy of ±0.1mm, and the 3D topology map is automatically uploaded to the cloud database for historical damage trend analysis after it is generated.

[0030] The storage temperature for glass fiber prepreg is 5-25℃. Before use, it needs to be preheated at 40-50℃ for 10-15 minutes to eliminate internal air bubbles.

[0031] The following is a description with reference to specific embodiments: Example 1: Repair of Polyethylene Gas Pipelines Pipeline inner wall pretreatment The cleaning process involves alternating 60MPa high-pressure water jet and 3Hz air pulse, with a water-air alternation interval of 45 seconds, and is repeated 4 times. High-pressure water jets remove oil and corrosion products from pipe walls through cavitation, while air pulses use instantaneous air pressure to remove residual particles. Alternating cleaning avoids cleaning dead spots caused by a single medium. After cleaning, the surface roughness Ra of the pipe wall is ≤5μm, providing an ideal interface for subsequent material adhesion.

[0032] After cleaning, the surface roughness Ra of the pipe wall decreased from the original 15-20μm to ≤5μm, and the surface energy increased to 45-50mN / m, which significantly improved the adhesion of the composite material and increased the interfacial bonding strength by 40%.

[0033] 3D Defect Mapping and AI Classification The pipeline robot is equipped with a line laser scanner with an accuracy of ±0.1mm, and the scanned data is transmitted to the edge computing terminal in real time. The convolutional neural network adopts the U-Net architecture, and the training set contains 2000 groups of labeled defect images. It adapts to image recognition under different lighting conditions through transfer learning. Level I defect location error <2cm, repair priority determination accuracy ≥97%, and reduction of invalid repair area by more than 30%.

[0034] The location error of Class I defects is less than 2cm, which is 60% lower than that of the traditional threshold method. The repair priority map dynamically optimizes the material delivery path, reducing the area of ​​invalid repair zones by 30% and material consumption by 18%.

[0035] Composite material injection and dynamic curing Component A contains 12wt% silane-modified nano-silica with a particle size of 30nm, and component B is a ±45° inclined glass fiber prepreg with an areal density of 250g / m². For PE pipes, a 320nm main wavelength ultraviolet light source is selected, with a moving speed V=180 / D, D=300mm, and a distributed fiber optic sensor monitors the pipe wall temperature to be stable at 65±5℃. Nano-silica enhances the density of the resin by filling the micropores, and the oblique fiber arrangement counteracts the axial stress of the pipe, resulting in an interfacial bonding strength of 18 MPa after curing. Example 2: Repair of cast iron water supply pipes Preprocessing and Defect Analysis The moisture content of the gas pulse is reduced to 80ppm to avoid secondary oxidation of the cast iron pipe; the thickness of the pipe wall is detected simultaneously by laser scanning, and the internal cavity is located by sonar probe. A corrosion product composition analysis module has been added to distinguish between chemical corrosion and mechanical damage, and the repair priority weights have been adjusted.

[0036] Composite material compatibility improvement Component A contains 0.5 wt% phosphate ester toughening agent to improve wettability to the oxide layer on cast iron surface; Component B fiber prepreg is coated with zinc powder, with a coating thickness of 5-8 μm, to inhibit electrochemical corrosion.

[0037] Gradient photopolymerization process When the ultraviolet light source is switched to the 400nm band, the light intensity is increased to 1200mW / cm², and the moving speed is V=160 / D, where D=200mm; The curing process is carried out in stages. In the initial stage, the temperature is controlled at ≤50℃ to avoid thermal stress concentration, and in the later stage, the temperature is increased to 75℃ to promote deep cross-linking.

[0038] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A trenchless repair method for municipal low-pressure pipelines, characterized in that, The specific steps include the following: Step 1: Pre-treatment of the inner wall of the pipe. The inner wall of the pipe is flushed alternately with high-pressure water jets at a pressure of 50-80MPa and air pulses at a frequency of 2-5Hz. The flushing is repeated ≥3 times to remove the deposits on the pipe wall. Step 2, 3D defect mapping: A pipeline robot equipped with a laser scanner is used to generate a 3D topological map of the inner wall of the pipeline, marking areas where the pipe diameter deformation exceeds 2%. Step 3: AI defect classification. Based on convolutional neural networks, semantic segmentation is performed on pipe endoscope images to identify three types of defects: through cracks, localized corrosion, and surface scratches. Repair priority maps are then generated according to the leakage risk level. Step 4: Segmented injection of composite material. The two-component UV-cured composite material containing a nano-silica reinforcement layer and glass fiber prepreg is injected into the pipeline in segments, with each segment not exceeding 5 meters in length. Step 5: Gradient photocuring. The composite material is pressed tightly against the tube wall by an inflatable airbag. An adjustable ultraviolet light source with a wavelength of 280-420nm is used to irradiate the material at a constant speed of V=K / D. At the same time, the light intensity is adjusted in real time according to the temperature feedback from the distributed optical fiber sensor to complete the gradient curing of the material.

2. The trenchless repair method for municipal low-pressure pipelines according to claim 1, characterized in that: In step one, the air pulse uses dry compressed air with a water content ≤100ppm, and the single alternation interval between the water jet and the air pulse is 30-60 seconds.

3. The trenchless repair method for municipal low-pressure pipelines according to claim 1, characterized in that: In step three, a convolutional neural network is used to perform semantic segmentation of the defects, and the classification criteria include: Class I defects: through-cracks or holes, which require priority repair; Class II defects: localized corrosion depth ≥ 30% of pipe wall thickness, requiring suboptimal repair; Class III defects: Surface scratches or corrosion depth less than 10% of the pipe wall thickness, repair can be postponed.

4. The trenchless repair method for municipal low-pressure pipelines according to claim 1, characterized in that: In step four, the two-component UV-curable composite material includes: Component A: Modified epoxy acrylate resin containing 10-15wt% nano silica, with viscosity controlled at 500-800cps; Component B: Glass fiber prepreg with a fiber areal density of 200-300 g / m², and the fiber orientation is staggered with the pipe axis at ±45°.

5. A trenchless repair method for municipal low-pressure pipelines according to claim 4, characterized in that: The nano-silica has a particle size of 20-50 nm, its surface is modified with a silane coupling agent, and the uniformity deviation of its mixing with the resin matrix is ​​≤5%.

6. The trenchless repair method for municipal low-pressure pipelines according to claim 1, characterized in that: The operating parameters of the tunable wavelength ultraviolet light source satisfy: The wavelength range is 280-420nm, and the light intensity is automatically adjusted according to the type of pipe. Polyethylene pipes use the 300-350nm band, and cast iron pipes use the 380-420nm band. The moving speed V of the light source and the diameter D of the pipe satisfy the following relationship: V=K / D, where K is a correction factor of 150-200, in m·mm / min.

7. A trenchless repair method for municipal low-pressure pipelines according to claim 1, characterized in that: The dynamic curing control includes: The pipe wall temperature is monitored in real time using distributed fiber optic sensors, and the temperature is controlled to be ≤80℃. Adjust the power of the ultraviolet light source according to the material curing exothermic curve to achieve an interfacial bonding strength of 15-20 MPa.

8. A trenchless repair method for municipal low-pressure pipelines according to claim 1, characterized in that: The repair layer thickness is 0.8-1.5mm, and the pressure resistance test standard for the repaired pipeline is: no leakage after holding the pressure at 1.5 times the working pressure for 30 minutes.

9. A trenchless repair method for municipal low-pressure pipelines according to claim 1, characterized in that: In step two, the laser scanner of the pipeline robot has an accuracy of ±0.1mm, and the 3D topology map is automatically uploaded to the cloud database for historical damage trend analysis after it is generated.

10. A trenchless repair method for municipal low-pressure pipelines according to claim 4, characterized in that: The glass fiber prepreg is stored at a temperature of 5-25°C and needs to be preheated at 40-50°C for 10-15 minutes before use to eliminate internal air bubbles.

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