Ground-air-pipe multi-dimensional coupling PCCP pipeline health monitoring system and method

Abstract

The invention discloses a ground-air-pipe multi-dimensional coupling PCCP pipeline health monitoring system and method, and belongs to the technical field of underground pipeline safety monitoring, and the system comprises an InSAR air monitoring unit, an artificial corner reflector array and a distributed optical fiber sensing unit. The PCCP pipeline is monitored from the air through the InSAR technology, and ground surface settlement rate abrupt change points and non-linear deformation areas are extracted through InSAR time sequence analysis; an adjustable artificial corner reflector is arranged along a vertical projection area of the pipeline, so that the phase incoherence problem of the InSAR technology in pipeline monitoring is improved, and the InSAR phase stability is enhanced; distributed optical fibers are pre-buried in the PCCP manufacturing stage and used for collecting pipe body strain data in real time, an abnormal space correlation map is constructed in combination with InSAR time sequence analysis data, and the hidden damage position and probability of an underground pipeline are deduced and inversely deduced through Bayesian causality. Omni-directional and multi-dimensional health monitoring from the ground and the air to the pipeline is achieved, the monitoring precision and reliability are effectively improved, and a powerful guarantee is provided for safe operation of the PCCP.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of underground pipeline safety monitoring, in particular to a ground-air-pipe multi-dimensional coupling PCCP pipeline health monitoring system and method. BACKGROUND

[0002] With the acceleration of urbanization process and the continuous development of infrastructure construction, underground pipeline system plays a crucial role in key fields such as urban water supply, gas supply and drainage. PCCP pipe, as a widely used underground water pipeline, is widely used in long-distance water transmission and other key infrastructure projects due to its high strength, large diameter and good durability. However, PCCP pipe faces many challenges in long-term operation, such as geological disasters, soil erosion, pipe aging, internal pressure changes, etc. These factors may cause pipe cracks, leakage, deformation and even rupture, which seriously threaten the safe operation and service life of the pipe. Therefore, effective health monitoring of PCCP pipe to timely detect potential damage and disease is of great significance to ensure the safe operation of urban infrastructure.

[0003] Traditional underground pipeline monitoring methods mainly include manual inspection, ultrasonic detection, electromagnetic detection and other single technical means. Manual inspection relies on regular inspection by workers, which is inefficient and difficult to detect early minor damage; ultrasonic detection and electromagnetic detection can provide certain detection accuracy, but usually require pipe shutdown and limited detection range, making it difficult to achieve real-time and continuous monitoring of the pipe. In addition, most of these traditional methods can only detect damage on the surface or local area of the pipe, and it is difficult to detect hidden damage and early disease in the pipe. With the continuous expansion of the pipeline network and the increasing complexity of the operating environment, the limitations of traditional monitoring methods are increasingly prominent, and it is difficult to meet the high-precision, all-around monitoring needs of modern underground pipeline safe operation.

[0004] The present application discloses a ground-air-pipe multi-dimensional coupling PCCP pipeline health monitoring system and method, which belongs to the technical field of underground pipeline safety monitoring. The system integrates InSAR air monitoring unit, artificial corner reflector array and distributed optical fiber sensing unit to realize all-around, multi-dimensional health monitoring from ground, air to pipe itself. By InSAR time series analysis to extract surface subsidence rate mutation point and nonlinear deformation area, combined with artificial corner reflector to improve phase incoherence problem and enhance monitoring accuracy; at the same time, real-time acquisition of pipe body strain data by distributed optical fiber, combined with Bayesian causal inference to deduce the position and probability of hidden damage of underground pipeline. The present application not only effectively improves the monitoring accuracy and reliability, but also provides a strong guarantee for the safe operation of PCCP pipe, which has important theoretical and practical application value.

[0005] After checking, few patents in the public domain are related to the PCCP pipeline health monitoring system and method of ground-air-pipe multi-dimensional coupling. Some related patents are shown below:

[0006] CN116295145A discloses a tailing body safety monitoring system and method based on InSAR and optical fiber sensing technology. The satellite InSAR and unmanned aerial vehicle LiDAR data are used to investigate the real-time displacement of local displacement area of mining area and tailing accumulation body. At the same time, according to the safety monitoring well laid on the tailing body and the grid-shaped armored monitoring optical cable buried in the front end surface of the tailing body, the temperature, strain or deformation, displacement, microseismic event, change of underground water level and other parameters of the tailing body are monitored in real time. The possible landslide or dam break of the tailing body is reinforced in time, and early warning information is issued to avoid the occurrence of geological disasters such as dam break in time.

[0007] CN115563582A discloses a method, device and system for multi-scale evaluation of geological risk along oil and gas pipeline. The multi-source satellite monitoring data and ground-based monitoring data of the target area along the oil and gas pipeline are obtained, and the monitoring fusion data of the target area and the monitoring deformation trend graph are obtained by fusion processing, and then the target area is warned of geological disasters. The present application improves the data utilization efficiency and evaluation accuracy, and helps to maintain the safety of oil and gas pipelines.

[0008] The above patents mainly focus on above-ground structures, while PCCP pipelines are linear buried structures. The existing technology is difficult to transfer. Since the main failure mode of PCCP is the fracture of the steel wire of the pipe body or the deterioration of the concrete, it is necessary to combine distributed optical fiber to directly monitor the strain of the pipeline to find hidden structural problems. The existing technology has obvious limitations in target applicability, data fusion depth and damage positioning logic, and cannot solve the problem of fine evaluation of the whole chain from environmental monitoring to structural damage diagnosis of PCCP pipeline. SUMMARY

[0009] In view of the above-mentioned problems of existing technology in target applicability, data fusion depth, damage positioning logic and other aspects, a PCCP pipeline health monitoring system and method of ground-air-pipe multi-dimensional coupling are proposed, which provides real-time, global and high-credibility health status evaluation for PCCP pipeline, and significantly reduces the risk of pipe explosion.

[0010] The application provides a PCCP pipeline health monitoring system and method with ground-air-pipe multi-dimensional coupling, characterized in that the PCCP pipeline health monitoring system and method comprises an adjustable artificial corner reflector, an InSAR air monitoring unit and a distributed optical fiber, the artificial corner reflector is arranged above the ground and comprises an adjustable structure; remote sensing image data is collected through the InSAR air monitoring unit, and ground surface change information is obtained through data processing; the PCCP pipeline is arranged at a certain vertical distance from the ground, the distributed optical fiber is pre-buried in the PCCP pipeline, the terminal of the distributed optical fiber is connected with an optical fiber demodulator, and the PCCP pipeline and the ground are filled with backfill soil.

[0011] As preferred, for high-risk areas (such as joints and bends), encryption arrangement (interval ≤0.5m) is adopted.

[0012] As preferred, the core of the adjustable artificial corner reflector is preferably selected from an aluminum alloy or silver-plated glass fiber (reflectivity >80%) to enhance the echo intensity.

[0013] A PCCP pipeline health monitoring system and method with ground-air-pipe multi-dimensional coupling, characterized in that the method comprises the following steps:

[0014] S1: an array of adjustable artificial corner reflectors is arranged on the ground along the vertical projection area of the PCCP pipeline at a certain interval, for improving the InSAR phase stability;

[0015] S2: remote sensing image data is obtained through the InSAR air monitoring unit for processing and analysis, and deformation information of the PCCP pipeline area is obtained;

[0016] S3: the distributed optical fiber is pre-buried in the PCCP pipeline in the manufacturing stage, and connected with an optical fiber demodulator, for collecting pipe body strain and temperature data in real time;

[0017] S4: backfill soil is added after the PCCP pipeline is buried and backfilled to the ground;

[0018] S5: abnormal space correlation atlas is constructed by combining InSAR time sequence analysis data, and the position and probability of hidden damage of the underground pipeline are deduced by using Bayesian causal inference.

[0019] Further, the step S1 further comprises an adjustable structure, so that the posture and position can be adjusted according to different monitoring environments and requirements, and the angle between the normal vector of the reflector and the satellite line-of-sight vector is ≤2° through controller driving of a holder.

[0020] Further, the step S2 specifically comprises:

[0021] S21, InSAR image data collection:

[0022] The ascending and descending mode of Sentinel-1 satellite is used to collect SAR images alternately, the time baseline is less than or equal to 14 days, and the space baseline is less than or equal to 300 m, so as to enhance the spatial continuity of the interference phase; the image coverage range extends at least 200 m buffer along the longitudinal direction of the PCCP pipeline, so as to ensure the complete extraction of the deformation of the pipe section boundary.

[0023] S22, timing deformation analysis:

[0024] The SBAS-InSAR (small baseline subset) method is used to process more than 30 SAR images to calculate the annual deformation rate (mm / yr) and the cumulative settlement; the PS (permanent scatterer) point screening (set the coherence coefficient) is used to enhance the reliability of deformation monitoring on the pipeline path.

[0025] S23, pipeline linear deformation feature extraction:

[0026] Fixed interval deformation profile lines are generated along the center line of the PCCP pipeline to extract the vertical displacement (Δh) and the horizontal tension (Δx); when a deformation mutation point is detected, it is marked as a potential abnormal area.

[0027] Further, the step S3 specifically comprises:

[0028] S31: In the manufacturing stage of the PCCP pipeline, the distributed optical fiber is pre-embedded into the pipeline concrete structure according to the predetermined path, and it is ensured that it is closely combined with the pipeline, the pre-embedded path of the distributed optical fiber covers the key stress parts and the areas prone to temperature changes of the PCCP pipeline, including the middle part, the interface and the bending part of the pipeline. The distributed optical fiber is a fiber Bragg grating sensor (FBG) for real-time sensing of the strain and temperature change inside the pipeline.

[0029] S32: One end of the pre-embedded distributed optical fiber is connected to the optical fiber demodulator, and the optical fiber demodulator is connected to the data processing and analysis unit through a data transmission line, which includes a wired transmission line or a wireless transmission module, to ensure that the data can be transmitted to the data processing and analysis unit in real time to obtain accurate pipe strain and temperature data, and at the same time, the distributed optical fiber is calibrated periodically to ensure its measurement accuracy and reliability.

[0030] S33: The pipe strain and temperature data collected by the optical fiber demodulator are transmitted to the data processing and analysis unit for subsequent comprehensive analysis and health monitoring.

[0031] Further, the step S4 further comprises that after the PCCP pipeline is buried, the selected backfill needs to have certain compactness and stability, for protecting the pipeline and ensuring normal operation of the monitoring system; in the backfill process, the engineering design requirements are met, so as to avoid additional stress or damage to the PCCP pipeline; at the same time, necessary drainage and other facilities are arranged, so as to prevent rainwater or underground water from seeping into the backfill layer and causing erosion to the pipeline or increasing the complexity of the monitoring system.

[0032] Further, the step S5 specifically comprises:

[0033] S51, InSAR deformation anomaly detection and feature extraction:

[0034] The remote sensing image data acquired by the InSAR air monitoring unit is subjected to time series analysis, after pre-processing of InSAR image data at different time phases, including radiation correction, geometric correction and denoising processing, surface deformation information is calculated through an interference measurement algorithm, the settlement rate and nonlinear deformation area are extracted, and the extracted deformation information is subjected to time and space analysis, and the deformation anomaly area is identified.

[0035] S52, construction of abnormal spatial correlation atlas:

[0036] The surface deformation information obtained by the InSAR time series analysis is spatially aligned with the pipe body strain and temperature data collected by the distributed optical fiber, based on the spatially aligned data, a multi-dimensional abnormal correlation atlas is constructed, potential abnormal areas around the pipeline are identified, and features such as strain mutation, temperature anomaly and deformation rate are extracted.

[0037] S53, probability inversion calculation:

[0038] Using a Bayesian causal inference model, the position and probability of the underground pipeline hidden damage are inversely deduced according to the data features in the abnormal spatial correlation atlas, the prior probability of the underground pipeline hidden damage is first determined, the initial probability is set based on historical data and expert experience, the prior probability is updated according to the data features in the abnormal spatial correlation atlas, the posterior probability is obtained, the position and probability of the underground pipeline hidden damage are inversely deduced using the posterior probability, and a damage probability distribution map is generated.

[0039] Compared with the prior art, the application has the advantages and positive effects that:

[0040] The application provides a ground-air-pipeline multi-dimensional coupling PCCP pipeline health monitoring system and method. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed to be used in the embodiment description will be briefly introduced one by one. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor on the premise of not paying the creative labor.

[0042] Figure 1 A schematic diagram of the overall architecture of the ground-air-pipeline multi-dimensional coupling PCCP pipeline health monitoring system and method provided for embodiment 1 is shown in the figure.

[0043] Figure 2 A process schematic diagram of the ground-air-pipeline multi-dimensional coupling PCCP pipeline health monitoring system and method provided for embodiments 1-3 is shown in the figure.

[0044] In the above figures, 1 is an adjustable artificial corner reflector, 2 is an adjustable structure, 3 is the ground, 4 is a fiber demodulator, 5 is a distributed optical fiber, 6 is a PCCP pipeline, 7 is backfill soil, and 8 is an InSAR air monitoring unit. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the application will be described clearly and completely in combination with the drawings in the embodiments of the application. It should be noted that the embodiments of the application and the features in the embodiments can be combined with each other without conflict.

[0046] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the application. However, it will be apparent to one skilled in the art that the application can be practiced without the specific details set forth in this description, and that the application is not limited to the particular embodiments disclosed in detail herein.

[0047] Embodiment 1: Standard implementation process of PCCP pipeline health monitoring system and method of air-ground-tube multi-dimensional coupling.

[0048] 1. Adjustable artificial corner reflector (1) layout. On the ground (3) in the vertical projection area of the PCCP pipeline (6), an adjustable artificial corner reflector (1) is laid every 200 meters. In the high-risk area of the PCCP pipeline (6) such as the joint and elbow, the layout interval of the adjustable artificial corner reflector (1) is encrypted to 0.5 meters. The adjustable artificial corner reflector (1) is made of aluminum alloy material with a reflectivity of more than 80%, which can effectively enhance the reflection intensity of the InSAR signal. Each adjustable artificial corner reflector (1) is installed on the ground (3) through an adjustable structure (2), and a dedicated mounting bracket is used to fix the adjustable artificial corner reflector (1) to ensure its stability and adjustability of the reflection angle. The controller drives the pan-tilt to ensure that the angle between the normal vector of the reflector and the satellite line-of-sight vector does not exceed 2°, so as to ensure the best signal reflection effect.

[0049] 2. InSAR air monitoring. For the InSAR air monitoring unit (8), the ascending and descending modes of the Sentinel-1 satellite are used to alternately collect SAR images, the time baseline is controlled within 14 days, and the spatial baseline is controlled within 300 meters to enhance the spatial continuity of the interference phase. The image coverage range extends at least 200 meters along the longitudinal direction of the PCCP pipeline (6) buffer zone to ensure complete extraction of the deformation of the pipeline section boundary. At least 30 SAR images are processed using the SBAS-InSAR (small baseline set) method to calculate the annual deformation rate and cumulative settlement. The deformation monitoring reliability along the pipeline path is enhanced by permanent scatterer (PS) point screening (set the coherence coefficient ≥ 0.7). Fixed interval deformation profile lines (interval 50 meters) are generated along the center line of the PCCP pipeline (6) to extract the vertical displacement (Δh) and horizontal tension (Δx). When a deformation mutation point (vertical displacement Δh ≥ 5 mm, horizontal tension Δx ≥ 10 mm) is detected, it is marked as a potential abnormal area.

[0050] 3. Distributed optical fiber (5) pre-buried. During the manufacturing stage of the PCCP pipe (6), the distributed optical fiber (5) is pre-buried into the pipe concrete structure according to the predetermined path, ensuring its close combination with the pipe. The distributed optical fiber (5) is a fiber Bragg grating sensor (FBG) with a wavelength range of 1530-1570 nanometers, used for real-time sensing of strain and temperature changes inside the pipe. The strain measurement range is ±2000 micro-strain, and the temperature measurement range is -20°C to +80°C. The pre-buried path covers the key stress parts and temperature change prone areas of the pipe, including the middle part, the interface, and the bending part of the pipe. The pre-buried distributed optical fiber (5) is connected to the fiber demodulator (4) at one end, and the fiber demodulator (4) is connected to the data processing and analysis unit through a wired transmission line, ensuring that data can be transmitted to the data processing and analysis unit in real time. The distributed optical fiber (5) is calibrated every 6 months to ensure its measurement accuracy and reliability.

[0051] 4. Backfill soil (7) construction. Select backfill soil (7) with certain density and stability to protect the pipe and ensure the normal operation of the monitoring system. The compaction degree of the backfill soil (7) should not be less than 90% to ensure the stability of the soil around the pipe. During the backfilling process, special monitoring equipment is used to monitor the stress of the pipe. High-precision pressure sensors with an accuracy of ±0.1 MPa are used to ensure that the backfilling process does not cause additional stress or damage to the pipe.

[0052] 5. Data analysis and damage location. Perform time series analysis on the remote sensing image data obtained by the InSAR air monitoring unit (8), extract the surface subsidence rate and nonlinear deformation area, and perform spatio-temporal analysis on the extracted deformation information to identify abnormal deformation areas. Spatially align the surface deformation information obtained by InSAR time series analysis with the pipe body strain and temperature data collected by the distributed optical fiber (5), and based on the spatially aligned data, construct a multi-dimensional abnormal correlation graph to identify potential abnormal areas around the PCCP pipe (6). Extract features from the abnormal areas, including strain mutation, temperature anomaly, and deformation rate. Use the Bayesian causal inference model to reverse the location and probability of underground pipe hidden damage based on the data characteristics in the abnormal spatial correlation graph. First, determine the prior probability of underground pipe hidden damage, set the initial probability to 0.05 based on historical data and expert experience, update the prior probability to 0.1-0.3 based on the data characteristics in the abnormal spatial correlation graph, obtain the posterior probability, and use the posterior probability to reverse the location and probability of underground pipe hidden damage to generate a damage probability distribution map.

[0053] Embodiment 2: For a certain inter-provincial water diversion project, DN2400 PCCP pipes are used, with a total length of 150 km, passing through farmland, mountains, rivers and other terrains, and need to achieve millimeter-level deformation monitoring and full-life cycle monitoring. This embodiment aims to implement a PCCP pipe health monitoring system and method with ground-air-pipe multi-dimensional coupling. When conducting tests, the following steps need to be followed to ensure the correctness of the test results:

[0054] 1. One adjustable artificial corner reflector (aluminum alloy core, reflectivity 85%) is arranged every 100 m along the pipeline. The angle is dynamically adjusted by a motorized pan-tilt head (precision ±0.5°) to ensure that the satellite line-of-sight vector and the normal of the reflecting surface have an included angle of ≤2°, and the InSAR coherence coefficient is improved to above 0.75.

[0055] 2. The ascending and descending modes of Sentinel-1 satellite are used to alternately collect SAR images, with the time baseline controlled within 14 days and the spatial baseline controlled within 300 meters to enhance the spatial continuity of the interference phase. The image coverage range extends at least 200 meters along the longitudinal direction of the PCCP pipeline, ensuring the complete extraction of the deformation of the pipeline section boundary. At least 30 SAR images are processed by the SBAS-InSAR method to calculate the annual deformation rate and cumulative settlement, and the deformation monitoring reliability along the pipeline path is enhanced through permanent scatterer (PS) point screening. Fixed-interval deformation profile lines are generated along the center line of the pipeline to extract the vertical displacement (Δh) and horizontal tension (Δx). When a deformation mutation point is detected, it is marked as a potential abnormal area.

[0056] 3. During the PCCP manufacturing stage, fiber Bragg grating sensors (FBG) are pre-embedded in the pipeline concrete structure according to the predetermined path, ensuring that they are tightly combined with the pipeline and covering the joint area (up to 0.5 m). The fiber terminal is connected to the BOTDA demodulator to monitor strain (precision ±2με) and temperature (±0.5℃) in real time. At the same time, the distributed optical fiber is calibrated regularly to ensure its measurement accuracy and reliability.

[0057] 4. After the PCCP pipeline is buried, backfilling is carried out with backfill soil with certain density and stability. During backfilling, strict adherence to engineering design requirements is required to avoid additional stress or damage to the pipeline. At the same time, necessary drainage facilities are provided in the backfill soil to prevent rainwater or groundwater from seeping into the backfill layer and causing erosion or increasing the complexity of the monitoring system.

[0058] 5. The surface deformation information obtained by InSAR time series analysis is spatially aligned with the pipe body strain and temperature data collected by distributed optical fibers to construct a multi-dimensional abnormal correlation atlas, identify potential abnormal areas around the pipeline, construct a dynamic Bayesian network (DBN), and input nodes include: InSAR deformation (ground subsidence ≥5mm / yr), optical fiber strain mutation (≥50με), and underground water level (accessed through external sensors), output the location and probability of underground pipeline hidden damage, and generate a damage probability distribution map.

Claims

1. A PCCP pipeline health monitoring system and method with multi-dimensional coupling of ground, air and pipe, characterized by: The PCCP pipeline health monitoring system and method include an adjustable artificial corner reflector (1), an InSAR aerial monitoring unit (8), and a distributed optical fiber (5). The adjustable artificial corner reflector (1) is placed above the ground (3) and includes an adjustable structure (2). Remote sensing image data is collected by the InSAR aerial monitoring unit (8), and surface change information is obtained by data processing. A PCCP pipeline (6) is arranged at a certain vertical distance from the ground (3), and a distributed optical fiber (5) is pre-buried in the PCCP pipe. The terminal of the distributed optical fiber (5) is connected to an optical fiber demodulator (4). Backfill soil (7) is provided between the PCCP pipeline (6) and the ground (3).

2. A PCCP pipeline health monitoring system and method with multi-dimensional coupling of ground, air and pipe, characterized by: The method comprises the following steps: S1: An array of adjustable artificial corner reflectors (1) is arranged at a certain interval along the vertical projection area of ​​the PCCP pipeline (6) on the ground (3) to improve the InSAR phase stability; S2: remote sensing image data is acquired through the InSAR aerial monitoring unit (8) and processed and analyzed to obtain deformation information of the PCCP pipeline (6) area; S3: During the manufacturing stage, the distributed optical fiber (5) is pre-buried in the PCCP pipe (6) and connected to the optical fiber demodulator (4) for real-time collection of pipe body strain and temperature data; S4: After the PCCP pipe (6) is buried, backfill soil (7) needs to be added to fill it back to the ground (3); S5: Combine InSAR time series analysis data to construct an abnormal spatial correlation map, and use Bayesian causal inference to infer the location and probability of hidden damage to underground pipelines.

3. The PCCP pipeline health monitoring system and method with multi-dimensional coupling of ground, air and pipe according to claim 2 is characterized in that: The step S1 also includes an adjustable structure (2), so that the posture and position can be adjusted according to different monitoring environments and requirements, and the controller drives the pan-tilt platform so that the angle between the normal vector of the reflector and the satellite line of sight vector is ≤2°.

4. The PCCP pipeline health monitoring system and method with multi-dimensional ground-air-pipe coupling according to claim 2 is characterized in that: The step S2 specifically includes: S21, InSAR image data acquisition: The Sentinel-1 satellite was used to acquire SAR images in ascending and descending modes, with a temporal baseline of ≤14 days and a spatial baseline of ≤300 m, to enhance the spatial continuity of the interferometric phase. The image coverage extended along the longitudinal direction of the PCCP pipeline (6) with a buffer zone of at least 200 m to ensure the complete extraction of the boundary deformation of the pipeline segment. S22, time series deformation analysis: The SBAS-InSAR (Small Baseline Set) method is used to process 30 or more SAR images to calculate the annual deformation rate (mm / yr) and accumulated sedimentation. PS (Permanent Scatterer) point screening (with a set coherence coefficient) is used to enhance the reliability of deformation monitoring along the pipeline path. S23, pipeline linear deformation feature extraction: Deformation profiles are generated at fixed intervals along the centerline of the PCCP pipeline (6) to extract vertical displacement (Δh) and horizontal tension (Δx); when a sudden deformation change point is detected, it is marked as a potential abnormal area.

5. The PCCP pipeline health monitoring system and method with multi-dimensional coupling of ground, air and pipe according to claim 2 is characterized in that: The step S3 specifically includes: S31: During the manufacturing stage of the PCCP pipeline (6), the distributed optical fiber (5) is pre-buried in the concrete structure of the pipeline according to a predetermined path, and is ensured to be tightly integrated with the pipeline. The pre-buried path of the distributed optical fiber (5) covers the key stress-bearing parts and areas prone to temperature changes of the PCCP pipeline (6), including the middle part, the interface and the bending part of the pipeline; the distributed optical fiber (5) is a fiber grating sensor (FBG) for sensing the strain and temperature changes inside the pipeline in real time; S32: Connect one end of the pre-buried distributed optical fiber (5) to the optical fiber demodulator (4), and the optical fiber demodulator (4) is connected to the data processing and analysis unit via a data transmission line. The data transmission line includes a wired transmission line or a wireless transmission module to ensure that data can be transmitted to the data processing and analysis unit in real time to obtain accurate pipe body strain and temperature data. At the same time, the distributed optical fiber (5) is regularly calibrated to ensure its measurement accuracy and reliability; S33: The collected pipe body strain and temperature data are transmitted to the data processing and analysis unit via the optical fiber demodulator (4) for subsequent comprehensive analysis and health monitoring.

6. The PCCP pipeline health monitoring system and method with multi-dimensional coupling of ground, air and pipe according to claim 2 is characterized in that: The step S4 also includes that after the PCCP pipeline (6) is buried, the selected backfill soil (7) needs to have a certain density and stability to protect the pipeline and ensure the normal operation of the monitoring system; during the backfill process, it must comply with the engineering design requirements to avoid causing additional stress or damage to the PCCP pipeline (6); at the same time, necessary drainage facilities are set up to prevent rainwater or groundwater from seeping into the backfill layer and causing erosion of the pipeline or increasing the complexity of the monitoring system.

7. The PCCP pipeline health monitoring system and method with multi-dimensional coupling of ground, air and pipe according to claim 2 is characterized in that: The step S5 specifically includes: S51, InSAR deformation anomaly detection and feature extraction: The remote sensing image data acquired by the InSAR aerial monitoring unit (8) is subjected to time series analysis. After preprocessing the InSAR image data of different time phases, including radiation correction, geometric correction and noise removal, the surface deformation information is calculated by interferometry algorithm, the sedimentation rate and nonlinear deformation area are extracted, and the extracted deformation information is subjected to spatiotemporal analysis to identify the abnormal deformation area; S52, construction of abnormal spatial correlation map: The surface deformation information obtained by InSAR time series analysis is spatially aligned with the pipe body strain and temperature data collected by distributed optical fiber (5). Based on the spatially aligned data, a multi-dimensional anomaly correlation map is constructed to identify potential abnormal areas around the pipeline and extract features of the abnormal areas, including strain mutation, temperature anomaly, deformation rate and other features; S53, probability inversion calculation: Using the Bayesian causal inference model, the location and probability of hidden damage to underground pipelines are inferred based on the data characteristics in the abnormal spatial association map. First, the prior probability of hidden damage to underground pipelines is determined, and the initial probability is set based on historical data and expert experience. According to the data characteristics in the abnormal spatial association map, the prior probability is updated to obtain the posterior probability. The posterior probability is used to infer the location and probability of hidden damage to underground pipelines, and a damage probability distribution map is generated.

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