Operation railway tunnel lining crack repairing method and repairing system

Abstract

The invention provides an operation railway tunnel lining crack repairing method and repairing system, and aims to solve the problems of low repairing quality and low construction efficiency in the prior art. According to the method, tunnel cracks are accurately detected through a laser scanner and an ultrasonic imager, the cracks are classified in combination with a data processing system, proper repairing materials are selected, and intelligent spraying, intelligent grouting and reinforcing devices are adopted for filling and repairing. Meanwhile, real-time monitoring and reinforcing of the repairing quality are achieved through the micro crack sensor and the remote monitoring system, and stability and long-term effectiveness after repairing are ensured.

Description

Technical Field

[0001] The present invention relates to the field of tunnel repair, and in particular to a method and a system for repairing cracks in a lining of an operating railway tunnel. Background Art

[0002] With the development of railway transportation, the maintenance and repair of railway tunnels has gradually become a key issue. Due to the long-term influence of factors such as traffic flow and temperature difference, tunnels often have cracks and damage of varying degrees. At present, conventional tunnel repair methods mostly rely on manual inspection and construction, and the repair materials are often traditional grouting materials and simple coatings. This method is not only time-consuming and labor-intensive, but also difficult to ensure the consistency and durability of the repair effect. In the prior art, some methods use automated equipment, but these methods have problems such as low automation, poor repair accuracy, and inaccurate selection of repair materials, resulting in unsatisfactory tunnel repair effects and even affecting the service life of the tunnel.

[0003] The current repair scheme lacks automated means for accurate classification of crack types and targeted repair, as well as a system for post-quality monitoring and automatic reinforcement. Therefore, an efficient, accurate and sustainable repair method is urgently needed to ensure the quality of tunnel repair and reduce maintenance costs and cycles. Summary of the invention

[0004] The main purpose of the present invention is to provide a method and a system for repairing cracks in the lining of an operating railway tunnel, so as to at least solve the problem of low quality of tunnel lining repair in the prior art.

[0005] In order to achieve the above object, the first aspect of the present invention provides a method for repairing cracks in a lining of an operating railway tunnel, which specifically comprises the following steps: Step 1: Laser surface detection: Use a laser scanner to quickly detect the tunnel surface to obtain information on the width, depth and direction of the cracks; Step 2, ultrasonic depth detection: Use ultrasonic imager to perform depth detection, obtain the depth data of the crack, and combine the information obtained by laser scanner to further accurately locate the three-dimensional spatial distribution of the crack; Step 3, crack classification: The data processing system is used to analyze the crack characteristics of the acquired information to determine the types of cracks, which include shallow cracks, deep cracks and through cracks. The depth of shallow cracks is less than 10 mm, the depth of deep cracks is greater than or equal to 10 mm and less than 50 mm, and the depth of through cracks is greater than or equal to 50 mm. Step 4. Selection of repair materials: Select matching repair materials according to the crack type. For shallow cracks, use permeable polymer materials; for deep cracks, use nano-reactive grouting materials to solidify the inside of the cracks; for through cracks, use high-strength grouting materials combined with mechanical reinforcement devices; Step 5: Intelligently fill and repair the cracks: Step 1: Use an intelligent spraying system to pre-coat a bonding enhancement layer in the crack area. The bonding enhancement layer is a polymer resin coating with a bonding strength of 1.5MPa-3MPa and a curing time of 30min-120min; Step 2: Use intelligent grouting device to automatically adjust grouting pressure and flow rate according to crack depth; Step 3: Use flexible sealing material for secondary covering; Step 6: Repair quality monitoring: Step 1: Install micro crack sensors at the repaired site to monitor crack changes in real time and upload data to the remote monitoring system; Step 2: Use ultrasonic waves to detect the filled area. If new cracks are detected, the remote monitoring system will automatically alarm and start the mechanical automatic reinforcement device for secondary repair.

[0006] Furthermore, in step 1, the laser scanner is a three-dimensional laser radar scanning device, the scanning accuracy of the three-dimensional laser radar scanning device is 0.05mm-0.1mm, and the measurement range is 0.5m-30m; the three-dimensional laser radar scanning device outputs the acquired three-dimensional coordinate data of the crack to the data processing system.

[0007] Furthermore, in step 2, the ultrasonic imager adopts phased array ultrasonic detection technology, the frequency range of the ultrasonic imager is 1 MHz-10 MHz, and the detection depth range is 10 mm-100 mm.

[0008] Furthermore, in step 5, the flexible sealing material is a polymer elastomer, and the elongation of the polymer elastomer is greater than or equal to 300% to adapt to the micro-deformation of the tunnel structure caused by temperature changes.

[0009] According to another aspect of the present invention, there is provided a system for repairing cracks in the lining of an operating railway tunnel, which is applied to any of the above-mentioned methods for repairing cracks in the lining of an operating railway tunnel, and the system for repairing cracks in the lining of an operating railway tunnel comprises: a data processing system, which analyzes information collected by a laser surface scanner and an ultrasonic imager to determine the type of cracks; an intelligent spraying system, which pre-coats an adhesive reinforcement layer on the cracks; an intelligent grouting device, which cooperates with the intelligent spraying system to perform intelligent filling and repair on the cracks; a micro crack sensor, which is arranged at the repair completion site to monitor crack changes in real time and upload data to a remote monitoring system; and a mechanical automatic reinforcement device, which cooperates with the micro crack sensor to monitor the repair quality of the repair completion site.

[0010] Furthermore, the data processing system comprises: A first data module, wherein the laser scanner and the ultrasonic imager transmit data to the first data module; A second data module, wherein the first data module inputs the received data into the second data module, and the second data module performs classification operations based on the width, depth, and orientation of the cracks, and outputs the type of cracks; The third data module, the second data module sends the crack classification result to the third data module, the third data module generates a construction instruction and sends a control signal to the intelligent grouting device to perform the repair operation.

[0011] Furthermore, the intelligent spraying system includes: a spraying robot, which adopts a six-axis robotic arm; a spraying pump, the spraying pump pressure range is 0.5MPa-3MPa, and the spraying thickness is controlled to be 0.2mm-2mm; a permeable polymer coating, and the viscosity of the permeable polymer coating is 200-800cP.

[0012] Furthermore, the intelligent grouting device includes: an adjustable grouting pump, the grouting pressure range of the adjustable grouting pump is 0.2MPa-5MPa; a sensor control system, the sensor control system monitors the slurry filling situation in real time to prevent material overflow or uneven filling; a grouting material delivery system, the grouting material delivery system includes multiple independently controllable grouting pipelines to meet the repair needs of different crack types.

[0013] Furthermore, the micro crack sensor includes a MEMS strain sensor and a wireless data transmission module. The operating frequency range of the MEMS strain sensor is 10 Hz-100 Hz, and the collected data is transmitted to the remote monitoring system through the wireless data transmission module.

[0014] Furthermore, the mechanical automatic reinforcement device includes: a robotic arm, which is provided with an adjustable nozzle, and the opening diameter range of the adjustable nozzle is 1mm-5mm to meet the filling requirements of different crack sizes; a robot control system, which analyzes crack monitoring data to automatically determine whether reinforcement is needed; and a secondary grouting module, which reinforces the penetrating cracks.

[0015] Compared with the prior art, the method and system for repairing cracks in the lining of an operating railway tunnel of the present invention have the following beneficial effects: First, by using the combined application of a laser scanner and an ultrasonic imager, accurate detection of tunnel cracks is achieved, greatly improving detection efficiency and accuracy. Secondly, appropriate repair materials are selected according to the depth and type of the cracks, and accurate filling is performed through an intelligent spraying system and an intelligent grouting device to ensure the continuity and stability of the repair effect. In addition, the combination of flexible sealing materials and self-healing materials enhances the adaptability of the tunnel structure, and can effectively cope with changes in ambient temperature and crack expansion that may occur during long-term use. The repair status is continuously tracked through a real-time monitoring system. If new cracks are found, the system can automatically start the reinforcement device for secondary repair, thereby ensuring that the repair effect is not affected by the external environment. This method not only improves the repair quality and construction efficiency, but also greatly reduces the risks and errors of manual operations, and has strong practicality and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings constituting a part of the present application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 It is a flow chart of the method for repairing cracks in the lining of an operating railway tunnel; Figure 2 It is a flowchart for intelligent filling and repairing of cracks; Figure 3 It is a repair quality monitoring flow chart. DETAILED DESCRIPTION

[0017] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0018] The present invention is further described below in conjunction with the accompanying drawings: In the figure: As attached Figures 1 to 3 As shown, according to the first aspect of the present invention, a method for repairing cracks in the lining of an operating railway tunnel is provided, wherein the method for repairing cracks in the lining of an operating railway tunnel specifically comprises the following steps: Step 1: Laser surface detection: Use a laser scanner to quickly detect the tunnel surface to obtain information on the width, depth and direction of the cracks; Step 2, ultrasonic depth detection: Use ultrasonic imager to perform depth detection, obtain the depth data of the crack, and combine the information obtained by laser scanner to further accurately locate the three-dimensional spatial distribution of the crack; Step 3, crack classification: The crack characteristics of the acquired information are analyzed through the data processing system to determine the types of cracks, which include shallow cracks, deep cracks and through cracks. Shallow cracks are less than 10 mm deep, corresponding to micro-damage on the casing surface, accounting for more than 70% of the total cracks; deep cracks are greater than or equal to 10 mm and less than 50 mm deep, involving local failure of the structural layer, which is easy to cause leakage expansion; through cracks are greater than or equal to 50 mm deep, threatening the overall bearing safety of the tunnel; by introducing a machine learning model, the classification accuracy rate is increased from 75% based on manual experience to 98.5%, avoiding material adaptation errors caused by misjudgment of the type; Step 4, selection of repair materials: Select matching repair materials according to the type of cracks. For shallow cracks, permeable polymer materials with a viscosity of 200-800cP can be used to fill 0.1mm micro-cracks through capillary action. The penetration rate is 5mm / s, which is 3 times higher than that of traditional epoxy resins, and the bonding strength with the concrete interface after curing is ≥3MPa; for deep cracks, nano-reactive grouting materials are matched, which produce a volume expansion rate of 6%-8% during curing, effectively compensating for structural shrinkage and deformation, and the 28-day compressive strength reaches 45MPa, and the durability is 4 times higher than that of ordinary cement-based materials; for through cracks, 60MPa-level high-strength grouting materials can be used in combination with prestressed carbon fiber plates for mechanical reinforcement to form a rigid-flexible composite reinforcement system that can withstand a crack expansion rate of 0.2mm / year, and the repair life is extended to more than 15 years; Step 5: Intelligently fill and repair the cracks: Step 1: Use an intelligent spraying system to pre-coat a bonding enhancement layer in the crack area. The bonding enhancement layer is a polymer resin coating with a bonding strength of 1.5MPa-3MPa and a curing time of 30min-120min; Step 2: Use intelligent grouting device to automatically adjust grouting pressure and flow rate according to crack depth; Step 3: Use flexible sealing material for secondary covering; Step 6: Repair quality monitoring: Step 1: Install micro crack sensors at the repaired site to monitor crack changes in real time and upload data to the remote monitoring system; Step 2: Use ultrasonic waves to detect the filled area. If new cracks are detected, the remote monitoring system will automatically alarm and start the mechanical automatic reinforcement device for secondary repair.

[0019] Furthermore, a 3D laser radar scanning device with a scanning accuracy of 0.05mm-0.1mm is used to quickly detect the tunnel surface. The device achieves full-section coverage scanning with a measurement range of 0.5m-30m, and can complete the inspection of a single ring lining within 5 minutes. Compared with the more than 20% missed detection rate of traditional manual visual inspection, this technology accurately captures the contours of cracks with a width of ≥0.1mm through millimeter-level precision 3D coordinate data output, eliminates the problem of misjudgment of crack direction caused by naked eye observation, and provides a high-resolution surface model for subsequent repairs.

[0020] Furthermore, in step 2, a phased array ultrasonic imager with adjustable frequency of 1MHz-10MHz is configured to cross-verify the crack depth in combination with laser scanning data. This technology can accurately identify hidden cracks inside the liner through the 10mm-100mm penetration depth detection capability, reducing the depth measurement error from ±5mm of the traditional percussion method to ±0.8mm. By fusing the laser point cloud and ultrasonic imaging data, a three-dimensional spatial distribution model of the crack is constructed, achieving a crack end positioning accuracy of ±2mm, which completely solves the problem of insufficient grouting or excessive repair caused by misjudgment of depth in traditional methods.

[0021] Furthermore, in step 5, a high molecular weight elastomer with an elongation of ≥300% is used for surface sealing, which can adaptively absorb a deformation of 1.5 mm under a temperature difference of ±20°C, and reduce the secondary cracking rate of hard sealants by 95%.

[0022] According to another aspect of the present invention, there is provided a system for repairing cracks in the lining of an operating railway tunnel, which is applied to any of the above-mentioned methods for repairing cracks in the lining of an operating railway tunnel, and the system for repairing cracks in the lining of an operating railway tunnel comprises: a data processing system, which analyzes information collected by a laser surface scanner and an ultrasonic imager to determine the type of cracks; an intelligent spraying system, which pre-coats an adhesive reinforcement layer on the cracks; an intelligent grouting device, which cooperates with the intelligent spraying system to perform intelligent filling and repair on the cracks; a micro crack sensor, which is arranged at the repair completion site to monitor crack changes in real time and upload data to a remote monitoring system; and a mechanical automatic reinforcement device, which cooperates with the micro crack sensor to monitor the repair quality of the repair completion site.

[0023] Furthermore, the data processing system comprises: The first data module, the laser scanner and the ultrasonic imager transmit data to the first data module, the first data module can integrate the millimeter-level precision point cloud data output by the laser scanner and the internal defect information provided by the ultrasonic imager to construct a three-dimensional digital twin model of the crack, and the data fusion error is ≤0.1mm; The second data module: the first data module inputs the received data into the second data module, and the second data module performs classification operations based on the crack width, depth, and direction, and outputs the crack type; the second data module runs a crack classification algorithm based on a convolutional neural network, and completes the crack type determination within 8 seconds, with an accuracy rate 23.5% higher than that of manual work; The third data module: the second data module sends the crack classification result to the third data module. The third data module generates construction parameters such as pressure, flow, material consumption, etc. according to the classification result. The control instruction transmission delay is less than 50ms to ensure the consistency of the repair process.

[0024] Furthermore, the intelligent spraying system includes: a spraying robot, which uses a six-axis robotic arm equipped with a laser positioning sensor to achieve ±0.1mm trajectory accuracy spraying on the curved lining surface, with a construction efficiency of 5m² / min; a spraying pump, with a pressure range of 0.5MPa-3MPa, and the coating thickness is adjusted by pressure feedback, with a fluctuation rate of ≤3% within the range of 0.2mm-2mm to avoid material accumulation or incomplete coverage; a permeable polymer coating, with a viscosity of 200-800cP and a gradient viscosity formula, which automatically matches the penetration rate for 0.1mm-2mm cracks, and shortens the curing time from the traditional 72 hours to 120 minutes; a 0.5MPa-3MPa spray pump is controlled by a six-axis robotic arm to form a 0.2mm-2mm thick polymer resin transition layer in the crack area, which increases the interface bonding strength between the new and old materials from the traditional 2.5MPa of manual brushing to 4.2MPa, and reduces the risk of peeling by 80%.

[0025] Furthermore, the intelligent grouting device includes: an adjustable grouting pump, which is equipped with a pressure-flow closed-loop control system and a grouting pressure range of 0.2MPa-5MPa, so that when grouting a 50mm deep crack, the terminal slurry flow rate is stabilized at 10cm / s±5%; a sensor control system, which monitors the slurry filling situation in real time to prevent material overflow or uneven filling, and can effectively reduce the occurrence rate of hollowing; a grouting material delivery system, which includes multiple independently controllable grouting pipelines to meet the repair needs of different crack types, greatly improving material utilization.

[0026] Furthermore, the micro crack sensor includes a MEMS strain sensor and a wireless data transmission module. The MEMS strain sensor adopts 10Hz-100Hz high-frequency sampling to capture the 0.005mm level instantaneous deformation caused by train vibration, thereby improving the monitoring effect; and transmits the collected data to the remote monitoring system through the wireless data transmission module. The wireless data transmission module can adopt the LoRa wireless transmission module to achieve stable communication at a distance of 500m in the complex electromagnetic environment of the tunnel, with a data packet loss rate of less than 0.01%.

[0027] Furthermore, the mechanical automatic reinforcement device includes: a robotic arm, which is provided with an adjustable nozzle, and the opening diameter of the adjustable nozzle ranges from 1mm to 5mm to meet the filling requirements of different crack sizes, thereby achieving grouting with a positioning accuracy of ±0.2mm in a narrow space; a robot control system, which analyzes the crack monitoring data to automatically determine whether reinforcement is needed, accurately and quickly, avoiding human errors; a secondary grouting module, which can use nano-modified grouting materials to form an interpenetrating network structure on the existing repair layer, and the interface bonding strength is increased by 40%.

[0028] Embodiment 1

[0029] During the maintenance of an operating railway tunnel, a 3D laser radar scanning device is first used to comprehensively scan the tunnel surface to quickly detect the width, depth and direction of cracks. The laser scanner can provide high-precision scanning data of 0.05mm-0.1mm to ensure the accuracy and detail of crack information. With this data, combined with the geometry of the tunnel, the system can generate an accurate 3D spatial distribution of cracks to help targeted operations for subsequent repair work. This method can avoid the errors and time consumption caused by traditional manual measurement and improve the efficiency of repair operations.

[0030] Furthermore, a phased array ultrasonic imager is used for depth detection. The frequency range of this device is 1MHz-10MHz, and it can detect cracks up to 100mm deep. Compared with traditional crack depth detection technology, ultrasonic imagers can provide more accurate depth information, avoiding the limitations of relying solely on surface crack detection. Combined with the surface information obtained by laser scanning, the depth data can further accurately locate the crack position, thereby improving the repair accuracy.

[0031] After the data processing system aggregates the scanning and imaging data, it automatically determines the crack type through the preset crack classification model. According to the crack depth and nature, the system will classify the cracks into shallow cracks with a depth of less than 10mm, deep cracks with a depth of 10mm to 50mm, and through cracks with a depth of more than 50mm. This automatic classification step not only reduces the error of manual intervention, but also improves the classification accuracy and ensures the targeted selection of repair materials.

[0032] Different repair materials are used according to the type of cracks. For shallow cracks, epoxy resin-based penetrants are used. This is a permeable polymer material that can penetrate the crack surface and form a strong bonding layer, thereby effectively preventing moisture penetration and increasing the durability of the repair layer. For deep cracks, nano-sodium silicate grouting materials are used. This material can penetrate deep into the cracks and undergo a curing reaction to form a solid repair layer, enhance structural strength, and prevent the cracks from continuing to expand. For through cracks, high-strength cement-based grouting materials are used in combination with mechanical reinforcement devices for double repair. The mechanical reinforcement device can ensure that the slurry evenly fills the depth of the crack by precisely controlling the pressure and flow rate, and provides real-time monitoring during the repair process to prevent material overflow or uneven filling.

[0033] During the repair process, a six-axis spray robot was used for intelligent spraying to evenly apply the bonding reinforcement layer to the crack area. The working pressure of the spray pump was controlled within the range of 0.5MPa-3MPa, and the spray thickness was controlled within the range of 0.2mm-2mm to ensure uniform coverage of the material. The efficiency and precision of this operation cannot be achieved in traditional manual spraying, which greatly shortens the construction period and improves the quality of repair.

[0034] Subsequently, an intelligent grouting device was used for automated grouting. The grouting pump was able to automatically adjust the pressure and flow rate according to the depth of the cracks, so that the slurry could evenly fill the cracks and solidify. The sensor control system in this process monitored the slurry filling in real time, avoiding excessive grouting or uneven filling, and further ensuring the quality of the repair.

[0035] After the repair is completed, polyurethane sealant is used for secondary covering. This flexible sealing material has an elongation of more than 300% and can adapt to the slight deformation of the tunnel structure caused by temperature changes, effectively avoiding the subsequent expansion of cracks.

[0036] In order to ensure the quality of repair, MEMS strain sensors and micro crack sensors are installed. These sensors can monitor the changes of cracks in real time and upload the data to the remote monitoring system through wireless data transmission modules. If new cracks are detected or problems occur in the repair area, the system will automatically alarm and start the mechanical automatic reinforcement device for secondary repair.

[0037] This embodiment effectively solves the problems of incomplete repair, frequent manual intervention, and long repair cycle existing in traditional repair methods through precise crack detection, automated repair technology, and intelligent monitoring system, greatly improves the efficiency and quality of tunnel repair, and ensures the long-term stability and safety of the repair effect.

[0038] Embodiment 2

[0039] In this embodiment, first, a three-dimensional lidar scanner is used to detect tunnel cracks and obtain geometric information of the cracks, including data such as the width, depth, and orientation of the cracks. These data are used for subsequent determination of crack types and selection of repair materials. Next, a phased array ultrasonic imager is used to measure the crack depth, and the frequency range of the ultrasonic waves is 1 MHz - 10 MHz to ensure accurate detection of the crack depth. Through the data processing system, combining the data obtained from laser scanning and ultrasonic imaging, the system classifies the cracks. For smaller cracks, polyurethane sealant is used for repair, while for larger cracks, especially dynamic cracks, such as cracks affected by temperature changes, thermoplastic polyurethane elastomer (TPU) is used. It has an elongation rate of over 300% and can adapt to the minute deformation of the cracks to prevent re-cracking. Using thermoplastic polyurethane elastomer (TPU) as the repair material can effectively solve common problems in tunnel crack repair, such as poor sealing and low durability. TPU has excellent elasticity and wear resistance, can adapt to the minute deformation of the tunnel structure due to temperature changes, and prevent cracks from re-cracking. The construction of TPU is simple and the curing speed is fast, which can effectively shorten the repair time and improve the construction efficiency. In addition, during the repair of through cracks, a mechanical reinforcement device is combined and a high-strength cement-based grouting material is used for double repair. This cement-based grouting material can effectively fill the through cracks, enhance the stability of the repair layer, and avoid possible future crack propagation.

[0040] During the repair process, the intelligent spraying system sprays a reinforcement layer in the crack area to ensure uniform distribution and increase the adhesion and repair effect of the material. The grouting pump uses adjustable pressure and flow rate to ensure that the slurry evenly fills the cracks. Subsequently, real-time monitoring is carried out through a micro-crack sensor and a MEMS strain sensor, and the data is uploaded to the remote monitoring system through a wireless data transmission module. If it is found that the cracks change further, the system will activate the automatic reinforcement mechanism for secondary repair. This embodiment highlights the use of thermoplastic polyurethane elastomer (TPU), which can adapt to the micro-deformation of the tunnel structure due to temperature changes and is particularly suitable for the repair of dynamic cracks. By combining flexible repair materials and mechanical reinforcement, this embodiment can enhance the adaptability and stability of the repair area while maintaining long-term sealing, and is particularly suitable for the repair of tunnel cracks affected by temperature changes.

[0041] Embodiment III

[0042] In this embodiment, a three-dimensional laser radar scanner is first used to detect the cracks in the tunnel to obtain geometric information of the cracks, including data such as the width, depth and direction of the cracks. These data are used for the subsequent determination of the crack type and the selection of repair materials. Next, a phased array ultrasonic imager is used to measure the crack depth to ensure accurate detection of the crack depth. The frequency range of the ultrasonic wave is 1MHz-10MHz. Through the data processing system, combined with the data obtained by laser scanning and ultrasonic imaging, the system classifies the cracks. For smaller cracks, epoxy resin grouting materials are used for repair; for larger cracks, especially dynamic cracks affected by temperature changes, silicone elastomers are selected, which have excellent weather resistance and UV resistance, can adapt to the small deformation of the tunnel caused by temperature changes, and effectively prevent the recurrence of cracks. Silicone elastomers have stronger temperature resistance and shear resistance, which effectively improves the long-term stability of the repair, especially in high temperature and long-term humid environments, and can ensure the integrity of the tunnel structure. Compared with traditional repair materials, silicone elastomers show better elasticity and adaptability in tunnel environments with large temperature changes. Through the application of this material, the common problem of crack recurrence can be effectively avoided. For the repair of through cracks, cement-based high-strength grouting materials are used for double repair. This type of material has the characteristics of high strength, good durability, and is suitable for high-pressure grouting. During the repair process, an intelligent spraying system is used to spray the reinforcement layer in the crack area to ensure good adhesion between the repair layer and the substrate, thereby increasing the repair effect of the material. The grouting pump uses adjustable pressure and flow rate to ensure that the slurry fills the cracks evenly. Subsequently, real-time monitoring is carried out through micro crack sensors and MEMS strain sensors, and data is uploaded to the remote monitoring system through a wireless data transmission module. If further changes are found in the cracks, the system will activate the automatic reinforcement mechanism for secondary repair.

[0043] Embodiment 4

[0044] In this embodiment, a three-dimensional laser radar scanner is first used to detect the cracks in the tunnel to obtain the geometric information of the cracks, including the width, depth and direction of the cracks. These data are used for the subsequent determination of the crack type and the selection of repair materials. Next, a phased array ultrasonic imager is used to measure the crack depth to ensure accurate detection of the crack depth, and the ultrasonic frequency range is 1MHz-10MHz. Through the data processing system, combined with the data obtained by laser scanning and ultrasonic imaging, the system classifies the cracks. For smaller cracks, polyurethane resin is used for repair; for larger cracks, especially dynamic cracks affected by temperature changes, acrylic elastomer is selected, and the use of acrylic elastomer as a repair material can effectively adapt to the micro-deformation of the tunnel structure caused by temperature changes, and is particularly suitable for the repair of dynamic cracks. The chemical stability and high and low temperature resistance of the material enable it to maintain excellent repair effects in various harsh environments. Compared with traditional repair materials, acrylic elastomers can provide higher temperature adaptability, reduce repair failures caused by temperature differences, and are particularly suitable for tunnel environments with large temperature differences. For the repair of through cracks, high-strength grouting materials are used for filling to provide strong adhesion and durability. During the repair process, an intelligent spraying system is used to spray a reinforcement layer on the crack area to ensure the repair effect of the crack area and good adhesion of the material. The grouting pump automatically adjusts the grouting pressure and flow rate according to the depth of the crack to ensure that the slurry fills the crack evenly. Subsequently, real-time monitoring is carried out through micro crack sensors and MEMS strain sensors, and the data is transmitted to the remote monitoring system through a wireless data transmission module. If further changes are found in the crack, the system will start the automatic reinforcement mechanism for secondary repair.

[0045] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for repairing cracks in lining of an operating railway tunnel, characterized in that: The following steps are involved: Step 1: Laser surface detection: Use a laser scanner to quickly detect the tunnel surface to obtain information on the width, depth and direction of the cracks; Step 2, ultrasonic depth detection: Use ultrasonic imager to perform depth detection, obtain the depth data of the crack, and combine the information obtained by laser scanner to further accurately locate the three-dimensional spatial distribution of the crack; Step 3, crack classification: The acquired information is analyzed for crack characteristics by a data processing system to determine the type of cracks, which include shallow cracks, deep cracks and through cracks. The shallow cracks are less than 10 mm deep, the deep cracks are greater than or equal to 10 mm and less than 50 mm deep, and the through cracks are greater than or equal to 50 mm deep. Step 4, selection of repair materials: select matching repair materials according to the crack type. For the shallow cracks, use permeable polymer materials; for the deep cracks, use nano-reactive grouting materials to solidify the inside of the cracks; for the through cracks, use high-strength grouting materials combined with mechanical reinforcement devices; Step 5: Intelligently fill and repair the cracks: Step 1: Use an intelligent spraying system to pre-coat a bonding enhancement layer in the crack area. The bonding enhancement layer is a polymer resin coating with a bonding strength of 1.5MPa-3MPa and a curing time of 30min-120min; Step 2: Use intelligent grouting device to automatically adjust grouting pressure and flow rate according to crack depth; Step 3: Use flexible sealing material for secondary covering; Step 6: Repair quality monitoring: Step 1: Install micro crack sensors at the repaired site to monitor crack changes in real time and upload data to the remote monitoring system; Step 2: Use ultrasonic waves to detect the filled area. If new cracks are detected, the remote monitoring system will automatically alarm and start the mechanical automatic reinforcement device for secondary repair.

2. The method for repairing cracks in the lining of an operating railway tunnel according to claim 1, characterized in that: In step 1, the laser scanner is a three-dimensional laser radar scanning device, the scanning accuracy of the three-dimensional laser radar scanning device is 0.05mm-0.1mm, and the measurement range is 0.5m-30m; the three-dimensional laser radar scanning device outputs the acquired three-dimensional coordinate data of the crack to the data processing system.

3. The method for repairing cracks in lining of an operating railway tunnel according to claim 1, characterized in that: In step 2, the ultrasonic imager adopts phased array ultrasonic detection technology, the frequency range of the ultrasonic imager is 1 MHz-10 MHz, and the detection depth range is 10 mm-100 mm.

4. The method for repairing cracks in lining of an operating railway tunnel according to claim 1, characterized in that: In step 5, the flexible sealing material is a polymer elastomer, and the elongation of the polymer elastomer is greater than or equal to 300% to adapt to the micro-deformation of the tunnel structure caused by temperature changes.

5. An operating railway tunnel lining crack repair system, characterized in that: The operating railway tunnel lining crack repair system is applied to the operating railway tunnel lining crack repair method according to any one of claims 1 to 4, and the operating railway tunnel lining crack repair system comprises: a data processing system, wherein the data processing system analyzes the information collected by the laser surface scanner and the ultrasonic imager to determine the type of crack; An intelligent spraying system, wherein the intelligent spraying system pre-coats an adhesive reinforcement layer on the cracks; An intelligent grouting device, which cooperates with the intelligent spraying system to intelligently fill and repair the cracks; A micro crack sensor is arranged at the repaired position to monitor crack changes in real time and upload the data to a remote monitoring system; A mechanical automatic reinforcement device cooperates with the micro crack sensor to monitor the repair quality of the repaired area.

6. The operating railway tunnel lining crack repair system according to claim 5, characterized in that: The data processing system comprises: A first data module, wherein the laser scanner and the ultrasonic imager transmit data to the first data module; a second data module, wherein the first data module inputs the received data into the second data module, and the second data module performs classification operation based on the width, depth and direction of the crack, and outputs the type of the crack; The third data module, the second data module sends the crack classification result to the third data module, and the third data module generates a construction instruction and sends a control signal to the intelligent grouting device to perform a repair operation.

7. The operating railway tunnel lining crack repair system according to claim 5, characterized in that: The intelligent spraying system includes: a spraying robot, which adopts a six-axis robotic arm; a spraying pump, the pressure range of the spraying pump is 0.5MPa-3MPa, and the spraying thickness is controlled to be 0.2mm-2mm; a permeable polymer coating, and the viscosity of the permeable polymer coating is 200-800cP.

8. The operating railway tunnel lining crack repair system according to claim 5, characterized in that: The intelligent grouting device includes: an adjustable grouting pump, the grouting pressure range of the adjustable grouting pump is 0.2MPa-5MPa; a sensor control system, the sensor control system monitors the slurry filling situation in real time to prevent material overflow or uneven filling; a grouting material delivery system, the grouting material delivery system includes multiple independently controllable grouting pipelines to meet the repair needs of different crack types.

9. The operating railway tunnel lining crack repair system according to claim 5, characterized in that: The micro crack sensor includes a MEMS strain sensor and a wireless data transmission module. The operating frequency range of the MEMS strain sensor is 10 Hz-100 Hz, and the collected data is transmitted to the remote monitoring system through the wireless data transmission module.

10. The operating railway tunnel lining crack repair system according to claim 5, characterized in that: The mechanical automatic reinforcement device includes: a robotic arm, which is provided with an adjustable nozzle, and the opening diameter range of the adjustable nozzle is 1mm-5mm to meet the filling requirements of different crack sizes; a robot control system, which analyzes crack monitoring data to automatically determine whether reinforcement is needed; and a secondary grouting module, which reinforces the through cracks.

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