Modified iron aggregate electromagnetic fingerprint-based pumped storage asphalt anti-seepage panel detection method and system

Abstract

The method and system for detecting pumped storage asphalt impervious face plate based on modified iron aggregate electromagnetic fingerprint belong to the field of nondestructive testing of water conservancy projects, and solve the problems that traditional detection is easy to damage the face plate, difficult to identify early internal damage, poor positioning, and unable to detect globally. The method adds modified iron aggregate to the impervious material, prepares test pieces in the laboratory at a constant temperature, collects electromagnetic fingerprints to establish a benchmark library, collects initial installation data after the construction of the face plate, uses a patrol vehicle with a combined positioning and dual-frequency eddy current sensor and an underwater wall climbing robot to regularly scan globally, and registers and differentiates the measured data and the initial installation data, and distinguishes micro cracks and seepage diseases according to electromagnetic phase and amplitude differences. The matching system is divided into three modules of laboratory calibration, field inspection and data processing, and the mechanical and electrical connection relationships of each component are clearly configured. The present application is nondestructive testing, the positioning error is less than 1 cm, the deep and shallow diseases are identified layer by layer, it is suitable for steep slope dry and wet areas of reservoirs, can early warn seepage, and the detection efficiency and coverage range are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of non-destructive testing technology for water conservancy projects, and in particular to a testing method and system for pumped storage asphalt anti-seepage panels based on electromagnetic fingerprinting of modified iron aggregates. Background Technology

[0002] Pumped storage power stations, as core peak-shaving and energy storage facilities in new power systems, simultaneously undertake multiple functions such as peak shaving and valley filling, frequency and phase regulation, and emergency backup. The seepage prevention performance of their upper and lower reservoirs directly determines the safe and stable operation of the power station. Asphalt concrete anti-seepage panels, with their advantages of excellent deformation adaptability, stable seepage prevention performance, and strong durability, are widely used in reservoir and dam seepage prevention systems and are key structures to ensure reservoir water storage and long-term dam service. The panel working conditions are complex. During the construction phase, construction defects such as uneven distribution of modified aggregates and local density differences are prone to occur. During long-term service, they are continuously subjected to the coupled effects of periodic water level fluctuations, temperature changes, reservoir water pressure, and uneven dam settlement, which can easily lead to surface micro-cracks, aggregate slippage, and deep pores, which gradually develop into hidden seepage channels. If various hidden dangers cannot be accurately identified in the early stage, they will continue to deteriorate into panel bulging and through leakage, seriously threatening the safe operation of the power station. Therefore, the industry urgently needs an intelligent non-destructive testing method that can cover the entire area, detect layers, and trace data.

[0003] I. Deficiencies of Traditional Manual and Physicochemical Testing Methods Currently, the engineering sites still largely rely on four traditional testing methods: manual visual inspection, core drilling, water pressure testing, and conventional ultrasonic testing. Each method has significant shortcomings and is insufficient to meet the needs of refined operation and maintenance. 1. Manual visual inspection can only identify exposed damage on the surface of the panel, but cannot detect internal fine cracks and deep seepage. The test results rely on subjective judgment of personnel, and there is no unified quantitative evaluation standard, resulting in an extremely high rate of missed detection. 2. Core drilling and water pressure testing are both destructive tests. Core drilling will permanently damage the overall structure of the waterproof panel, and can only be used for single-point sampling and testing, with a very small coverage area. Large-area testing is costly and has poor representativeness. 3. Conventional ultrasonic testing has limited penetration depth in heterogeneous asphalt concrete media, and its sensitivity in identifying early micro-cracks and slight changes in moisture content is insufficient, making it difficult to provide early warning of potential leakage.

[0004] II. Existing automated non-destructive testing patent technologies have inherent shortcomings. The mainstream automated non-destructive testing solutions in the industry are mainly divided into two categories: ground-penetrating radar inspection and aerial image visual inspection. Both of these technologies still have insurmountable technical limitations. For example, the ground-penetrating radar defect diagnosis method for asphalt concrete panels disclosed in CN107941825A relies on electromagnetic wave inversion of the internal structure, core drilling to calibrate the dielectric constant, and three-dimensional modeling and imaging. However, it has several shortcomings: First, the dielectric constants of asphalt, aggregate, and water are poorly distinguishable, and it cannot quantitatively differentiate between three types of defects: aggregate agglomeration, surface microcracks, and deep water saturation seepage. Second, the calibration process requires core drilling, which still damages the seepage prevention structure, and single-point calibration cannot guarantee a unified benchmark across the entire area. Third, the radar signal is interfered with by the steel reinforcement and metal support of the dam slope and environmental clutter, and the deep and shallow echoes are coupled with each other, resulting in poor layer identification accuracy. Fourth, there is no integrated automatic inspection equipment for dams with a slope of 1:1.5 to 1:1.7, and only manual handheld survey lines can be used for data collection, resulting in low efficiency for full-area detection.

[0005] For example, the crack identification method based on aerial image pixel analysis disclosed in CN119090801A relies on optical image grayscale calculation to identify surface cracks, which has fundamental limitations in its applicable scenarios: First, optical signals cannot penetrate the asphalt surface layer, and seepage and aggregate slippage defects at a depth of 5-20cm cannot be detected at all, resulting in large-scale missed detection of deep defects; Second, lighting, water surface reflection, reservoir fog, and slab surface stains can seriously interfere with imaging, making it difficult to unify the threshold for microcrack identification, leading to frequent false detections and missed detections; Third, it lacks supporting high-precision positioning and layered detection hardware, and can only qualitatively determine the existence of cracks, without outputting quantitative indicators such as defect depth, three-dimensional coordinates, and seepage development degree; Fourth, it is only suitable for surface defect inspection during the operation and maintenance phase, and does not support aggregate uniformity quality acceptance during the construction phase, resulting in a single detection scenario.

[0006] In addition, neither of the above two types of automated testing solutions has built a standardized material electromagnetic fingerprint benchmark library, and it is impossible to establish a full-cycle data comparison system of "laboratory standard test specimens - initial paving panel - service panels over the years". The disease evolution process lacks traceable data support, and there is no complete integrated system that integrates laboratory calibration, automated inspection of land and water areas, and intelligent differential analysis.

[0007] In summary, traditional manual, core drilling, and water pressure testing methods suffer from drawbacks such as structural damage, narrow coverage, and low detection efficiency. Conventional ultrasonic, existing ground-penetrating radar, and image-based non-destructive technologies also have multiple limitations, including the inability to detect deep-seated defects, the inability to classify and quantify defects, poor environmental interference resistance, and the lack of standardized full-cycle comparison benchmarks. Existing complete sets of equipment cannot simultaneously meet the needs of automated, layered detection of steep slopes above and below water, and cannot meet the dual scenarios of construction quality acceptance and early leakage warning during long-term service. To address these technological gaps in the industry, this invention proposes a detection method and system for pumped-storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting. This aims to comprehensively overcome the shortcomings of existing technologies and provide a standardized, reproducible, high-precision, and intelligent detection solution for the entire lifecycle operation and maintenance of pumped-storage asphalt anti-seepage panels, including construction acceptance and long-term leakage warning. Summary of the Invention

[0008] The technical problem to be solved by this invention is to provide a method and system for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting, which solves the problems of existing pumped storage asphalt anti-seepage panel detection methods, such as inability to identify early internal damage, small coverage of destructive testing, inability of conventional testing to detect layered damage, lack of water and land-based inspection equipment, lack of unified comparison benchmarks, poor accuracy in locating defects, and delayed leakage warning.

[0009] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: This invention provides a method and system for detecting pumped storage asphalt anti-seepage panels based on electromagnetic fingerprinting of modified iron aggregate, as detailed below: A method for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting includes the following steps: Step 1: Preparation of modified magnetic seepage-proof material: Prepare hydraulic asphalt concrete seepage-proof material with surface-modified iron aggregate; the surface-modified iron aggregate is passivated iron sand or stainless steel magnetic powder coated with epoxy resin film, and the dosage is 3%~8% of the total mass of asphalt concrete; the epoxy resin film can isolate water and avoid secondary damage to the panel caused by the corrosion and expansion of magnetic aggregate.

[0010] Step 2: Establishment of Laboratory Benchmark Electromagnetic Fingerprint: A standard specimen of 300mm×300mm×50mm was cast using a polytetrafluoroethylene / high-strength epoxy resin mold; the specimen was placed in an environmental control chamber with a temperature control accuracy of ±0.5℃ and adjusted to 20℃±2℃ for 24 hours; a three-axis high-precision scanning frame with a positioning accuracy of ±0.1mm was used, equipped with an array probe, to complete the XY grid scanning with a lift distance of 5mm±0.5mm and a step distance of 5mm; the array probe integrates a detection coil, which is electrically connected to the acquisition device to collect the excitation impedance, phase angle, and induced current amplitude point by point, thus constructing a laboratory benchmark three-dimensional database.

[0011] Step 3: On-site paving and initial installation benchmark collection: Modified asphalt concrete is paved and compacted on-site to form an impermeable panel. After the panel cools to room temperature, a full-area scanning device is used to obtain the initial installation three-dimensional database. The initial installation database is compared with the laboratory benchmark database to verify the uniformity of on-site paving and construction quality.

[0012] Step 4: Periodic scanning of the entire service area: The slope is inspected using a tracked inspection vehicle towed by a traction system, and the underwater area is scanned and a measured 3D database is collected using an amphibious adsorption-type wall-climbing robot; the inspection is divided into two frequencies: routine full-area monitoring every quarter and in-depth survey during the dry season every year; The inspection vehicle is equipped with an RTK-GPS antenna and an inertial navigation module, forming an RTK-GPS+IMU combined positioning system with a horizontal positioning error of <1cm and an elevation error of <1.5cm. The inspection vehicle has a flexible suspension system mounted under the chassis, with a multi-channel pulsed eddy current sensor array fixed at the bottom of the suspension system. Fine-tuning wheels are mounted at the four corners of the bottom of the suspension system. By relying on the fine-tuning wheels to contact the panel, the probe is stably maintained at a constant lift distance of 5mm±1mm. The sensor array has a single scan width of 0.5~1m. The vehicle body has a built-in lithium battery to power all onboard electrical equipment; the electromagnetic signals collected by the sensor array are transmitted to the transmission module, which communicates wirelessly with the shore base station to transmit detection data back in real time. It adopts a dual-frequency alternating magnetic field of 100kHz and 1kHz for layered detection. The 100kHz high frequency identifies surface crack damage in the 0~5cm surface detection area, while the 1kHz low frequency detects deep damage and internal seepage in the 5~20cm deep detection area. The inspection vehicle is compatible with anti-seepage panels with a slope of 1:1.5~1:1.7.

[0013] Step 5: Difference Matrix Construction: Accurately align the measured 3D database with the initial 3D database in terms of coordinates, and perform difference operations to generate a difference matrix.

[0014] Step 6, Defect Classification and Judgment: If the local phase shift and amplitude change rate of the difference matrix are <10%, it is judged as microcracks, aggregate displacement and micro-damage; if the local amplitude jump and amplitude change rate are >30%, it is judged as internal water saturation and moisture seepage defects, and the plane coordinates and distribution range of the defects are marked simultaneously.

[0015] The pumped-storage asphalt lining panel detection system based on modified iron aggregate electromagnetic fingerprinting is used to implement the aforementioned detection method for pumped-storage asphalt lining panels based on modified iron aggregate electromagnetic fingerprinting. The system is divided into three main units: Laboratory Initial State Measurement Device: Includes a non-magnetic, non-metallic mold, a three-axis high-precision CNC scanning frame, an array-type electromagnetic induction probe, an environmental control chamber, a signal acquisition device, and a detection coil. The non-magnetic mold is placed inside the environmental control chamber to avoid electromagnetic interference, and the molded specimen is contained inside the mold. The three-axis high-precision scanning frame is mounted above the environmental control chamber, and the array-type probe is fixed at the moving end of the scanning frame. The array-type probe integrates a detection coil, which is electrically connected to the acquisition device through a signal line. The mold is made of polytetrafluoroethylene or high-strength epoxy resin. The environmental control chamber can simulate service conditions in the full temperature range of -20℃ to 80℃, and the three-axis scanning frame achieves millimeter-level precise grid acquisition.

[0016] Field-in-service panel inspection device: includes a traction system, a ramp tracked inspection vehicle, an RTK-GPS antenna, an inertial navigation module, a suspension system, fine-tuning wheels, a multi-channel pulse eddy current sensor array, a lithium battery, a transmission module, a base station, and an amphibious adsorption wall-climbing robot. The traction system is mechanically connected to the inspection vehicle, towing it to move along the slope. The RTK-GPS antenna and inertial navigation module are fixed to the top of the inspection vehicle, and the two are electrically connected to form a combined positioning system. The suspension system is flexibly installed under the chassis of the inspection vehicle, with a sensor array fixed at the lower end of the suspension system. Fine-tuning wheels are installed at the four corners of the bottom of the suspension system, and the fine-tuning wheels are in contact with the panel surface. The lithium battery is built into the body of the inspection vehicle and is electrically connected to the positioning equipment, sensor array, and transmission module for unified power supply. The sensor array collects signals and connects to the transmission module, which wirelessly communicates with the base station. The inspection vehicle is equipped with soft rubber tracks to avoid scratching the anti-seepage panel. An amphibious climbing robot is provided independently, specifically for underwater submerged section inspection.

[0017] The data processing and analysis system includes a data storage module, a data preprocessing module, a differential calculation module, a damage diagnosis module, and a visualization module. The storage module stores baseline, initial installation, and previous inspection data in a hierarchical manner. The preprocessing module performs noise removal, distance correction, and coordinate registration of multi-source data. The differential calculation module outputs a standardized differential matrix. The damage diagnosis module automatically distinguishes damage types based on amplitude and phase thresholds. The visualization module generates damage / seepage distribution cloud maps and automatically outputs standardized operation and maintenance inspection reports.

[0018] This invention achieves early, high-precision, and full-area detection of microscopic damage and seepage in the asphalt concrete anti-seepage layer by uniformly incorporating surface-modified iron aggregate and utilizing the principle of electromagnetic induction. This overcomes the shortcomings of existing detection technologies in terms of detection range, detection accuracy, and damage type identification capabilities.

[0019] The method and system for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting provided by this invention have the following beneficial effects: 1. This invention constructs a uniform electromagnetic response medium by incorporating surface passivated epoxy-coated modified iron aggregate into asphalt concrete, which converts microcracks, aggregate slippage, and saturated water seepage inside the panel into quantifiable electromagnetic signals, thus solving the technical defects of traditional detection that cannot identify early hidden microscopic damage and has a delayed early warning of leakage.

[0020] 2. The modified magnetic aggregate of this invention has an outer epoxy resin film that isolates water and oxygen, which can prevent the aggregate from rusting and expanding during long-term service, avoid secondary cracking and damage to the panel caused by magnetic fillers, and improve the long-term service stability of the anti-seepage panel.

[0021] 3. This invention sets up an independent laboratory initial state measurement device, establishes a laboratory constant temperature standardized specimen scanning process, and establishes a unified electromagnetic fingerprint benchmark three-dimensional database to eliminate data deviations caused by construction and temperature, and solves the problem that existing detection methods lack unified reference standards and cannot quantitatively evaluate defects.

[0022] 4. After the paving is completed, the present invention simultaneously collects the initial three-dimensional database of the site and compares it with the laboratory benchmark, which can quickly verify the uniformity of the asphalt concrete paving and the construction quality on site, and screen out the inherent seepage defects in the construction stage in advance.

[0023] 5. The inspection vehicle of this invention is equipped with an RTK-GPS antenna and an inertial navigation module to form a combined positioning system, which achieves millimeter-level coordinate matching and a planar positioning error of less than 1cm, thus solving the shortcomings of traditional non-destructive testing in terms of rough defect positioning and inability to accurately locate leakage points.

[0024] 6. This invention is equipped with 1kHz and 100kHz dual-frequency pulse eddy current layer detection technology, which corresponds to the detection area of ​​0~5cm surface layer and 5~20cm deep layer, respectively. It can distinguish between shallow microcracks and deep seepage, and overcome the shortcomings of insufficient penetration depth and inability to identify defects in layers by ultrasound and radar.

[0025] 7. This invention uses a winch traction system to pull a tracked inspection vehicle on a slope, which is compatible with 1:1.5~1:1.7 steep slope anti-seepage panels. It is equipped with a sensor array with a single scan width of 0.5~1m to achieve continuous full-area scanning in a grid-like manner, which completely solves the problems of small coverage and easy omissions in traditional single-point detection.

[0026] 8. The present invention is equipped with an amphibious adsorption-type wall-climbing robot, which can complete the automated inspection of underwater submerged panels, achieve full coverage of above-water and underwater anti-seepage panels, and fill the gap in the technology of automated non-destructive inspection of underwater areas.

[0027] 9. This invention sets up a dual inspection cycle of quarterly routine monitoring and annual dry season in-depth survey, taking into account both long-term dynamic tracking and comprehensive in-depth investigation, adapting to the periodic rise and fall of water level in pumped storage power stations, and continuously tracking the trend of damage evolution.

[0028] 10. The entire process of this invention does not require drilling, grooving, or water pressure testing. It is a purely non-destructive testing method that does not damage the structural integrity of the asphalt concrete anti-seepage panel, thus solving the defects of traditional testing methods that damage the anti-seepage system.

[0029] 11. The sensor array of the present invention is assembled through a suspension system and is equipped with a fine-tuning wheel to adapt to the slight undulations of the panel, so as to stably maintain a constant lift distance of 5mm±1mm, avoid electromagnetic data distortion caused by lift distance fluctuations, and improve the repeatability and reliability of detection results.

[0030] 12. The inspection vehicle of this invention is powered by a built-in lithium battery and is equipped with a transmission module for wireless communication with the shore base station. On-site detection data is transmitted back in real time. In conjunction with the integrated data processing and analysis system, it automatically completes noise reduction, coordinate alignment, differential calculation, and intelligent defect identification. There is no need for manual point-by-point comparison, which greatly shortens the detection and analysis cycle and reduces labor costs.

[0031] 13. This invention sets a differentiated defect judgment threshold, and accurately distinguishes between two types of defects: micromechanical damage and water seepage by phase offset and amplitude change rate. It can output damage distribution map and seepage distribution map respectively, which makes it easier for operation and maintenance personnel to formulate targeted maintenance and treatment plans.

[0032] 14. The complete testing system of this invention is divided into three modular units: laboratory calibration device, on-site inspection device, and data processing system. The equipment is easy to disassemble, assemble, and transport, and can be adapted to the testing of seepage prevention panels of pumped storage reservoirs with different capacities and slopes. It has strong engineering versatility.

[0033] 15. This invention uses an environmental control chamber to simulate a wide temperature range of -20℃ to 80℃, eliminating the interference of temperature changes on electromagnetic detection parameters. The laboratory benchmark data closely matches the actual service environment on site, resulting in more reliable test results. Attached Figure Description

[0034] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a schematic diagram of the overall process of the damage detection method of the present invention; Figure 2 This is a schematic diagram of the laboratory initial state measuring device of the present invention; Figure 3 This is a schematic diagram of the inclined tracked inspection vehicle of the present invention; Figure 4 This is a schematic diagram of the layered structure of the waterproof panel of the present invention; In the diagram: 1. Mold; 2. Specimen; 3. Scanning frame; 4. Probe; 5. Environmental control chamber; 6. Acquisition device; 7. Detection coil; 8. Inspection vehicle; 9. Traction system; 10. RTK-GPS antenna; 11. Inertial navigation module; 12. Multi-channel pulse eddy current sensor array; 13. Suspension system; 14. Fine-tuning wheel; 15. Lithium battery; 16. Transmission module; 17. Base station; 18. Surface detection area; 19. Deep detection area. Detailed Implementation

[0035] The technical solutions of the present invention will be further described below with reference to the embodiments and accompanying drawings: Example 1 This embodiment provides a method for detecting pumped-storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting. Figure 1 , Figure 2As shown, this embodiment is used for factory quality verification after the asphalt anti-seepage panel of a pumped storage power station is completed, and specifically includes the following six steps: Step 1: Preparation of modified iron aggregate hydraulic asphalt concrete seepage prevention material The matrix uses 70# road petroleum asphalt, and the aggregate gradation adopts AC-13C fine-grained type; the modified iron aggregate is 200 mesh reduced iron powder, and the surface is passivated: the iron powder is immersed in epoxy resin E44 for 30 minutes, dried to form a 0.03mm insulating film, and the total amount of iron aggregate is 5% of the total mass of asphalt concrete; the mixing temperature is 160℃, and the density after compaction is 2.42g / cm³, and water is isolated to prevent the aggregate from rusting and expanding.

[0036] Step 2: Preparation of standard laboratory specimens and establishment of a benchmark electromagnetic fingerprint database 1) Molding mold 1: The mold is made of PTFE (Polytetrafluoroethylene) and is a one-piece milled non-magnetic mold with an inner cavity size of 300mm×300mm×50mm and a wall thickness of 15mm. It is free of metal impurities to avoid electromagnetic interference. The mixed modified asphalt concrete is filled into the mold 1 and statically compacted to obtain standard specimen 2. 2) Temperature-controlled standing: Place the mold 1 containing the test specimen 2 into the constant temperature environment control chamber 5. The chamber model is GDW-100 high and low temperature test chamber, with a temperature control range of -20℃ to 80℃ and a temperature control accuracy of ±0.5℃. Set the temperature to 20℃ and stand for 24 hours to eliminate internal temperature stress. 3) Mesh Electromagnetic Scanning: The three-axis high-precision scanning gantry 3 uses a gantry-type X / Y / Z three-axis slide module, model XYZ-800, with a positioning repeatability of ±0.01mm; the lower end of the scanning gantry's Z-axis is rigidly fixed with an array probe 4, and the probe integrates a detection coil 7 wound with Φ0.1mm pure copper enameled wire, with 120 turns; the detection coil 7 is connected to a multi-channel signal acquisition device 6 (model NI-USB6363, National Instruments Universal Serial Bus6363) via shielded twisted-pair cable; 4) Scanning parameters: X / Y axis movement step 5mm, probe lifting distance from the surface of specimen 2 5mm±0.5mm, excitation signal 1kHz, 100kHz dual-frequency synchronous output; excitation impedance, phase offset, and induced current amplitude are collected point by point, and the data are stored in the industrial control computer to build a laboratory benchmark three-dimensional database, which serves as the sole reference standard for on-site paving quality evaluation.

[0037] Step 3: On-site paving and initial assembly data collection Modified asphalt concrete was laid in layers on site to form the dam slope seepage prevention panel, with a single layer thickness of 5cm and a total of 4 layers. After paving, the surface was allowed to cool naturally to 25℃. The inclined tracked inspection vehicle 8 of Example 4 was equipped with a sensor array for full-area scanning to collect the overall electromagnetic data of the panel and generate an initial three-dimensional database. The initial database was compared with the laboratory benchmark database grid by grid. If the amplitude deviation of a single grid was >15%, it was determined that the iron aggregate distribution in the area was uneven and marked as a construction defect area.

[0038] Step 4: This embodiment is a preliminary inspection upon completion, and the service cycle inspection steps are not performed at this time.

[0039] Step 5: Generation of the difference matrix The initial 3D database and laboratory benchmark database were precisely aligned based on the RTK coordinate grid. The built-in difference function of MATLAB (Matrix Laboratory) was used to perform point-by-point difference calculations to output a standardized difference matrix. The matrix grid size was unified with the laboratory scanning grid at 5mm×5mm.

[0040] Step 6: Identification of Construction Defects Read the differential matrix parameters: if the phase offset is >8° and the amplitude change rate is <10%, it is determined that the aggregate distribution in the surface detection area is sparse; if the amplitude jumps and the change rate is >30%, it is determined that there is local aggregate accumulation; output the defect coordinates and distribution area simultaneously to complete the paving quality acceptance.

[0041] Example 2 In another preferred embodiment, based on Embodiment 1, this embodiment provides a method for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting, such as... Figure 1 , Figure 3 and Figure 4 As shown, this embodiment is for quarterly inspection of the seepage prevention panel of the pumped storage dam with a slope of 1:1.6 after 2 years of operation. Steps 1 to 3 are completely consistent with those in embodiment 1. The benchmark database and the initial installation database are stored in advance. Step 4: Global hierarchical periodic scan 1) Inspection cycle settings: one routine full-area scan per quarter, and an in-depth survey during the dry season (December) each year; 2) Water slope inspection equipment: The winch traction system 9 (model JK-2T electric winch) pulls the tracked inspection vehicle 8 along the dam slope; the inspection vehicle is equipped with an RTK-GPS high-precision antenna 10 (Real-Time Kinematic Global Positioning System, model ZED-F9P, planar positioning error ≤1cm) and a MEMS inertial navigation module 11 (Micro-Electro-Mechanical System, model MPU6050, six-axis gyroscope accelerometer), and the two are combined to calculate the global coordinates of the panel; 3) Sensors and Lift-off Control: An elastic suspension system 13 is installed under the chassis of the inspection vehicle 8, with a multi-channel pulse eddy current sensor array 12 (model ET400) fixed at the lower end of the suspension; Φ20mm polyurethane micro-adjustment wheels 14 are installed at the four corners of the suspension, with soft polyurethane material attached to the surface detection area 18 of the panel, adapting to the concavity and convexity of the panel surface, and stably maintaining a constant lift-off distance of 5mm; the sensor array 12 synchronously outputs a 100kHz high-frequency signal to detect the 0~5cm surface detection area 18, and a 1kHz low-frequency signal to penetrate the 5~20cm deep detection area 19; 4) Power supply and data transmission: The vehicle power supply adopts a 48V 100Ah lithium iron phosphate vehicle lithium battery 15, with a built-in BMS (Battery Management System) protection board, providing uninterrupted power supply for 12 hours; the sensor-collected signals are connected to the 5G wireless transmission module 16 (5th Generation Mobile Communication Technology, model EC200S industrial-grade communication module), and wirelessly communicate with the shore base station 17 based on TCP / IP (Transmission Control Protocol / Internet Protocol) to transmit layered electromagnetic raw data back in real time; 5) Underwater area detection: The seepage prevention panel in the submerged section is independently scanned by an amphibious adsorption wall-climbing robot (model CW-500). The wall-climbing robot is equipped with the same pulse eddy current sensor array to collect 19 data in the deep underwater detection area and completely stitch together the full-area real-time three-dimensional database of the panel.

[0042] Step 5: Differential calculation of measured data The coordinate grids of the measured 3D database from this inspection were registered with the initial 3D database of the completed paving. The phase and amplitude differences were calculated grid by grid to generate a global difference matrix.

[0043] Step 6: Classification and identification of service defects 1. Local phase shift and amplitude change rate of the difference matrix <10%: It is determined that microcracks and aggregate displacement-type mechanical damage have appeared in the surface detection area 18. 2. Local amplitude jump in the difference matrix and amplitude change rate > 30%: Indicates internal seepage and soil saturation seepage in the deep detection area 19; Based on the differential matrix, all disease plane coordinates and vertical layer depths are marked, and damage distribution maps and seepage distribution maps are automatically generated to predict the risk of seepage and dam failure in advance.

[0044] Example 3 In another preferred embodiment, this embodiment is based on embodiment 1, such as... Figures 2 to 4 As shown, this embodiment provides a pumping-storage asphalt anti-seepage panel detection system based on modified iron aggregate electromagnetic fingerprinting, which is used to implement the pumping-storage asphalt anti-seepage panel detection method based on modified iron aggregate electromagnetic fingerprinting described in embodiments 1 and 2 above.

[0045] This embodiment is an integrated system adapted for non-destructive testing of asphalt concrete anti-seepage panels in pumped storage power stations. It integrates three major functional units: laboratory initial state calibration, on-site comprehensive inspection across land and water, and intelligent data processing and analysis, forming a complete set of integrated testing equipment. Based on the electromagnetic fingerprint response mechanism of modified iron aggregate, the system achieves fully automated testing throughout the entire process—including construction quality inspection, early microscopic damage identification, deep leakage defect assessment, and risk warning—through a closed-loop logic of "laboratory benchmark calibration—on-site data acquisition—differential intelligent discrimination"—for anti-seepage panels on steep slopes and in alternating wet and dry conditions in pumped storage power stations.

[0046] The entire system comprises three main parts: a laboratory initial state measurement device, an on-site service panel inspection device, and a data processing and analysis system. These three units are complementary and interconnected, employing a unified 1kHz / 100kHz dual-frequency electromagnetic detection mechanism, a 5mm standard scanning grid, a constant 5mm±1mm probe lift-off distance, and an RTK-GPS+MEMS combined positioning and registration mechanism. All detection data is uniformly processed and analyzed using the MATLAB platform, ensuring consistent testing standards, traceable results, and controllable errors throughout the entire process.

[0047] The laboratory initial state measurement device is responsible for establishing a standardized and traceable electromagnetic fingerprint benchmark database, eliminating errors in materials, temperature, and equipment systems. The field-service panel inspection device is divided into a tracked inspection device for steep slopes above water and an underwater adsorption-type climbing inspection device, achieving precise data collection across the entire dam surface steep slope of 1:1.5~1:1.7, covering both dry and wet conditions, and stratifying deep and shallow layers. The data processing and analysis system is responsible for data preprocessing, coordinate registration, differential calculation, intelligent classification of defects, and visualization output, accurately distinguishing between mechanical damage and water seepage defects. The entire system does not require damage to the panel structure, has high detection accuracy, comprehensive coverage, and a high degree of automation, making it suitable for the long-term periodic inspection needs of pumped storage power stations.

[0048] Example 4 In another preferred embodiment, based on Embodiment 3, this embodiment provides a detection system for pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting, such as... Figure 2 As shown, this device is used for standardized collection of electromagnetic fingerprints of test specimens and the establishment of a unified benchmark database. 1. Parts list and materials / models: (1) Non-magnetic mold 1: integral PTFE (Polytetrafluoroethylene) CNC milling, inner cavity 300mm×300mm×50mm, without any ferromagnetic metal parts, to avoid interference with alternating magnetic field; (2) Standard specimen 2: Compacted specimen of modified iron aggregate asphalt concrete with the mix proportion of Example 1; (3) Three-axis high-precision scanning frame 3: XYZ-800 gantry slide module, aluminum alloy anodized non-magnetic frame, three-axis servo motor drive, repeatability accuracy ±0.01mm; (4) Array probe 4: Nylon shell non-magnetic probe housing with detection coil 7 embedded inside; (5) Copper detection coil 7: Φ0.1mm high-purity oxygen-free copper enameled wire, 120 turns of toroidal winding, inner diameter 20mm; (6) Constant temperature environment control chamber 5: GDW-100 high and low temperature test chamber, stainless steel inner liner, temperature control range -20℃~80℃, temperature control accuracy ±0.5℃; (7) Multi-channel signal acquisition device 6: NI-USB6363 (National Instruments Universal Serial Bus 6363, National Instruments Universal Serial Bus Synchronous Acquisition Card), eight channels synchronously acquire impedance, phase and current signals; 2. Mechanical and electrical connections: A non-magnetic mold 1 is stably placed on the bottom platform of the inner cavity of the constant temperature environment control chamber 5. The mold 1 is filled with a compacted standard specimen 2. A three-axis high-precision scanning frame 3 is straddling the top outside of the environment control chamber 5. The Z-axis vertical telescopic actuator is rigidly fixed with a threaded array probe 4. The array probe 4 is encapsulated with a copper detection coil 7. Shielded signal lines are led out from both ends of the detection coil 7, pass through the sealed wiring hole of the chamber, and are electrically connected to the NI-USB6363 acquisition device 6 outside the chamber. The acquisition device 6 is connected to the industrial control computer through a network cable and stores electromagnetic data based on MATLAB (Matrix Laboratory) software.

[0049] 3. Complete workflow: The mold 1 containing specimen 2 is placed in the environmental control chamber 5 and kept at a constant temperature of 20℃ for 24 hours. The triaxial scanning frame 3 drives the array probe 4 to move at a uniform speed with a step size of 5mm along the X / Y axis, while the Z axis is fixed at a height of 5mm. The dual-frequency detection coil 7 continuously collects electromagnetic signals across the entire area of ​​the specimen, and the acquisition device 6 synchronously stores all grid data to generate a laboratory benchmark three-dimensional database that can be used for on-site comparison, providing a unified calibration benchmark for construction and service testing.

[0050] Example 5 In another preferred embodiment, based on Embodiment 3, this embodiment provides a detection system for pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting, such as... Figure 3 and Figure 4 As shown, this device is used for automated, layered, non-destructive testing of the seepage prevention panels on the slopes of pumped storage dams.

[0051] 1. Parts list and materials / models: (1) Inclined tracked inspection vehicle 8: XP-16 inclined tracked inspection vehicle, chassis carbon steel sprayed with anti-corrosion epoxy paint, tracks made of thickened nitrile soft rubber material, which does not scratch the asphalt anti-seepage panel. (2) Winch traction system 9: JK-2T electric winch, wire rope diameter 8mm, rated traction force 20kN, suitable for 1:1.5~1:1.7 dam slope traction operation; (3) RTK-GPS high-precision antenna 10: ZED-F9P differential positioning antenna (Real-Time Kinematic Global Positioning System), with positioning accuracy of ±1cm in plane and ±2cm in elevation; (4) MEMS inertial navigation module 11: MPU6050 six-axis gyroscope accelerometer (Micro-Electro-Mechanical System) to compensate for slope tilt positioning error; (5) Multi-channel pulsed eddy current sensor array 12: ET400 dual-channel pulsed eddy current probe group, simultaneously outputting 1kHz / 100kHz excitation signals; (6) Elastic suspension system 13: 65Mn spring steel elastic hanger, which flexibly buffers road surface undulations; (7) Polyurethane fine adjustment wheel 14: Φ20mm solid polyurethane roller, wear-resistant and non-magnetic, fits the detection area 18 on the panel surface; (8) Lithium iron phosphate vehicle lithium battery 15: 48V 100Ah energy storage lithium battery with built-in BMS (Battery Management System) protection board, providing continuous power supply for 12 hours; (9) 5G wireless transmission module 16: EC200S industrial-grade 5G communication module (5th Generation Mobile Communication Technology), supporting real-time data pass-through of TCP / IP (Transmission Control Protocol / Internet Protocol); 2. Mechanical assembly, electrical, and communication connections: The traction wire rope of the winch traction system 9 is connected to the mechanical lock at the front of the tracked inspection vehicle 8, which pulls the inspection vehicle up and down along the dam slope. The RTK-GPS high-precision antenna 10 and MEMS inertial navigation module 11 are bolted to the roof of the inspection vehicle 8, and the two are electrically connected via a serial port to form a combined positioning unit. The upper end of the elastic suspension system 13 is hinged to the underside of the chassis of the inspection vehicle 8. The multi-channel pulse eddy current sensor array 12 is fixed to the bottom flange of the suspension. Polyurethane fine-tuning wheels 14 are mounted at the four corners of the suspension, and the fine-tuning wheels directly abut against the surface detection area of ​​the seepage-proof panel. Domain 18; The lithium iron phosphate vehicle-mounted lithium battery 15 is built into the sealed compartment of the inspection vehicle body, and supplies power to the combined positioning unit, sensor array 12 and 5G wireless transmission module 16 through branch power lines; The shielded cable of the signal output end of the sensor array 12 is connected to the 5G wireless transmission module 16, and the transmission module communicates wirelessly with the shore base station 17 based on the TCP / IP protocol to transmit the original data of surface and deep layer detection in real time; It is equipped with an independent amphibious adsorption climbing robot (CW-500) for automated scanning operations in the underwater deep detection area 19.

[0052] 3. On-site workflow: The winch traction system 9 pulls the inspection vehicle 8 at a constant speed along the dam slope. The RTK-GPS+MEMS combined positioning unit records the grid coordinates of each grid on the panel in real time. The elastic suspension 13, together with the polyurethane fine-tuning wheel 14, adapts to the unevenness of the panel surface and stably maintains the sensor detection lifting distance of 5mm. The sensor array 12 synchronously collects electromagnetic data from the surface layer (0~5cm) and the deep layer (5~20cm), and transmits it back to the base station 17 in real time via the 5G module. The background MATLAB software performs differential calculations between the measured data and the initial database to automatically identify micro-cracks and internal seepage defects, realizing full-area, layered, non-destructive automated inspection of the anti-seepage panel in the dry and wet areas of the steep slope.

[0053] Example 6 In another preferred embodiment, based on embodiments 3 to 5, this embodiment provides a pumped storage asphalt anti-seepage panel detection system based on modified iron aggregate electromagnetic fingerprinting. This device is used for automated layered non-destructive testing of the water-land anti-seepage panel of the pumped storage dam slope.

[0054] This embodiment is the background computing and discrimination subsystem of the entire testing system, which is mounted on an industrial control computer. It interacts bidirectionally with the laboratory initial state measurement device in Embodiment 4 and the field service panel inspection device in Embodiment 5 to realize the entire process of test data storage, preprocessing, differential calculation, disease diagnosis, and visualization report generation.

[0055] 1. Basic Hardware Configuration The industrial control host, model IPC-6806, is equipped with a Core i7 processor, 32GB of RAM, a 4TB industrial solid-state drive, a gigabit wired network port, an industrial wireless network card, and comes pre-installed with Windows Server 2019 operating system. It deploys the MATLAB (Matrix Laboratory) R2023b data processing platform and supports parallel reading and writing of multi-channel massive three-dimensional electromagnetic databases.

[0056] 2. Composition and Operating Logic of the Five Major Functional Modules (1) Data storage module: A three-level partitioned storage architecture is set up. The first partition stores the laboratory benchmark three-dimensional database, the second partition stores the panel paving initial installation three-dimensional database, and the third partition stores the measured three-dimensional database of each inspection over the years. A standardized storage format with timestamps and coordinate codes is adopted. The database is compatible with RTK positioning grid coordinates and can be quickly retrieved by dam section, inspection date, and panel layer area.

[0057] (2) Data preprocessing module: Built-in adaptive noise filtering algorithm to automatically filter out field vibration and electromagnetic interference noise; has the functions of lifting distance error correction and temperature drift compensation; after receiving the original layered electromagnetic data returned by the inspection device, it automatically completes coordinate grid registration, and the grid size is unified to 5mm×5mm to eliminate the coordinate deviation of laboratory and field equipment acquisition.

[0058] (3) Differential calculation module: retrieve the initial three-dimensional database of the same dam section and the current measured three-dimensional database, perform differential calculation on the excitation impedance, phase offset and induced current amplitude grid by grid, automatically generate a global standardized differential matrix, and bind the panel plane coordinates and layer depth parameters synchronously to distinguish the 0~5cm surface detection area and the 5~20cm deep detection area.

[0059] (4) Damage diagnosis module: It has a built-in two-level disease judgment threshold logic, and the threshold parameters are fixed in the program: when the local phase shift of the difference matrix and the amplitude change rate are <10%, the mechanical damage label is output to judge the surface micro-cracks and aggregate displacement defects; when the local amplitude of the difference matrix jumps and the amplitude change rate is >30%, the seepage disease label is output to judge the deep water saturated seepage defects; the three quantitative indicators of disease center coordinates, disease coverage area and disease longitudinal depth are output simultaneously.

[0060] (5) Visualization output module: retrieves the difference matrix and disease judgment results, automatically generates two-dimensional planar disease cloud map and longitudinal layered profile diagram; generates standardized test report according to water conservancy engineering test specifications. The report includes benchmark library parameters, inspection equipment parameters, difference matrix statistical values, disease distribution list, leakage risk level warning prompts, and supports local export of PDF (Portable Document Format) and online printing on local area network.

[0061] 3. End-to-end data interaction workflow During the laboratory calibration phase, the NI-USB6363 acquisition device of Example 4 uploads the electromagnetic fingerprint data of the standard specimen to the data storage module of this system via a network cable to establish a benchmark file. During on-site inspection, the 5G wireless transmission module 16 of Example 5 uploads the layered measured electromagnetic data to the industrial control host in real time. After the data preprocessing module completes the calibration and registration, the differential calculation module retrieves the corresponding dam section's initial installation database to generate a differential matrix. The damage diagnosis module automatically identifies the type and extent of the damage. Finally, the visualization module outputs a damage cloud map and a test report, completing the entire intelligent analysis closed loop of the test data.

[0062] In the preferred embodiment, in step 1, the surface-modified iron aggregate is iron sand or stainless steel magnetic powder that has undergone surface passivation treatment and is coated with an epoxy resin film. The dosage of the surface-modified iron aggregate in the asphalt concrete is 3% to 8% of the total mass of the asphalt concrete. This configuration, through the dual treatment of surface passivation and epoxy resin coating, effectively isolates the iron aggregate from direct contact with the asphalt matrix, fundamentally inhibiting oxidation and corrosion of the aggregate during its service life, and preventing secondary cracking or peeling of the panel due to rust expansion. Strictly controlling the dosage within the range of 3% to 8% ensures that the aggregate is uniformly dispersed in the concrete matrix to form a stable electromagnetic response medium, while preventing the mechanical and waterproof properties of the asphalt concrete itself from being weakened by excessive dosage. The epoxy resin-coated iron aggregate has good interfacial adhesion to the asphalt matrix and is not easily detached under temperature cycling and repeated loading, ensuring that the electromagnetic fingerprint signal remains stable and reliable throughout the entire service life, providing a reliable benchmark for subsequent differential comparison.

[0063] In the preferred embodiment, the inclined tracked inspection vehicle 8 described in step 4 is towed by a winch traction system 9 and is equipped with an RTK-GPS+IMU combined positioning system consisting of an RTK-GPS antenna 10 and an inertial navigation module 11, as well as a multi-channel pulse eddy current sensor array 12. The RTK-GPS+IMU combined positioning system has a planar positioning error of less than 1 cm and an elevation positioning error of less than 1.5 cm. The multi-channel pulse eddy current sensor array 12 has a single scan width of 0.5 m to 1 m and is fixed by a flexible suspension system 13. The suspension system 13 is equipped with fine-tuning wheels 14 to maintain a constant probe lift-off distance of 5 mm ± 1 mm. The inspection vehicle 8 is powered by an on-board lithium battery 15, and the detection data is transmitted to the shore base station 17 in real time via a wireless transmission module 16. With the above settings, the planar error is controlled within 1 cm and the elevation error is controlled within 1.5 cm by RTK-GPS and IMU fusion positioning, ensuring that the on-site collected coordinates are strictly aligned with the laboratory reference coordinates, providing a high-precision spatial reference for differential calculation. The flexible suspension system, combined with the fine-tuning wheel 14, stabilizes the probe lift-off distance at 5mm±1mm, eliminating interference from electromagnetic signals caused by lift-off distance fluctuations due to slope undulations. A single scan width of 0.5m~1m, combined with a tracked mobile platform, achieves continuous full-area coverage, significantly improving inspection efficiency. A lithium battery 15, coupled with 5G wireless transmission, enables real-time data feedback, allowing inspection personnel to instantly monitor panel status and quickly make maintenance decisions.

[0064] In the preferred embodiment, the detection in step 4 employs a dual-frequency alternating magnetic field layered detection method with 1kHz and 100kHz frequencies. The 100kHz high-frequency signal is used to detect surface damage in the 0-5cm surface detection area 18 of the geomembrane panel, while the 1kHz low-frequency signal is used to detect deep damage and seepage in the 5-20cm deep detection area 19. This configuration, through the synergistic effect of the 100kHz high-frequency and 1kHz low-frequency signals, achieves full-thickness coverage detection of the geomembrane panel from the surface to the depth. The 100kHz high-frequency signal, due to the skin effect, concentrates in the 0-5cm surface area 18, exhibiting high sensitivity to micro-cracks and aggregate displacement; the 1kHz low-frequency signal penetrates to a depth of 5-20cm in the deep area 19, effectively identifying internal saturation and seepage channels. This dual-frequency layered detection mechanism avoids the trade-off between detection depth and sensitivity inherent in single-frequency signals, allowing surface defects and deep seepage defects to be acquired simultaneously in the same scan, significantly improving the completeness and accuracy of the detection.

[0065] In the preferred embodiment, the frequency of the periodic full-area scanning of the panel in step 4 is divided into two categories: routine monitoring is carried out once a quarter, and in-depth survey is carried out once a year during the dry season. The inclined tracked inspection vehicle 8 is adapted to asphalt concrete anti-seepage panels with a slope of 1:1.5 to 1:1.7. The above settings establish a graded inspection mechanism based on the damage evolution law and the power station operation cycle. The quarterly routine scan promptly captures the initiation and expansion trend of early microscopic damage such as microcracks and aggregate slippage, providing data support for preventive maintenance. The in-depth survey is carried out during the dry season every year, when the reservoir water level is the lowest and the panel water pressure is the lowest, which is conducive to the 1kHz low-frequency signal penetrating to the deep area 19 to accurately identify the latent seepage channels and eliminate the interference of high water pressure on the detection signal. The inspection vehicle 8 is adapted to a slope of 1:1.5 to 1:1.7, covering the commonly used panel slope range of pumped storage power stations, and can be put into use without additional modification, improving the equipment versatility and engineering applicability.

[0066] In the preferred embodiment, the damage discrimination criteria in step 6 are as follows: A phase shift in a local area of ​​the difference matrix with an amplitude change rate less than 10% is classified as micro-cracks or aggregate displacement-type micro-damage; an amplitude jump in a local area of ​​the difference matrix with an amplitude change rate greater than 30% is classified as internal water saturation or moisture seepage defects. These criteria establish a quantitative discrimination standard based on the differential response laws of phase and amplitude to different defect types in the principle of electromagnetic induction. Micro-damage such as micro-cracks and aggregate displacement mainly alters the phase characteristics of the electromagnetic signal while having a limited impact on the amplitude; therefore, a phase shift with a superimposed amplitude change rate of less than 10% is used as the judgment criterion. Seepage defects, due to the significant increase in medium conductivity caused by moisture intervention, result in a large amplitude jump; therefore, an amplitude change rate greater than 30% is used as the judgment threshold. The setting of these two thresholds ensures that the identification of micro-damage and seepage defects does not interfere with each other, avoiding misjudgment, and simultaneously provides a quantitative basis for the graded assessment of damage severity.

[0067] In the preferred embodiment, the laboratory initial state determination device includes a non-magnetic, non-metallic mold 1, which is placed inside an environmental control chamber 5, containing the molded specimen 2. A triaxial high-precision scanning frame 3 is mounted above the environmental control chamber 5, and an array probe 4 is fixedly installed at the movable execution end of the triaxial high-precision scanning frame 3. Detection coils 7 are integrated inside the array probe 4, and the detection coils 7 are electrically connected to the acquisition device 6 via signal lines. The mold 1 is made of polytetrafluoroethylene or high-strength epoxy resin, and the environmental control chamber 5 is used to simulate a temperature environment of -20℃ to 80℃. With these settings, the non-magnetic mold 1 avoids interference from metal materials on the electromagnetic field, ensuring the purity and reliability of the electromagnetic fingerprint data. The environmental control chamber 5 covers a temperature range of -20℃ to 80℃, fully simulating the temperature conditions of the anti-seepage panel throughout its entire lifecycle from construction to service, making the laboratory benchmark data and the field measured data have comparable temperature benchmarks. The three-axis high-precision scanning frame 3 drives the array probe 4 to complete the grid scanning with millimeter-level positioning accuracy. The detection coil 7 simultaneously collects the excitation impedance, phase angle and induced current amplitude. The generated initial three-dimensional database provides a high-precision spatial reference for differential comparison, ensuring the consistency of detection data throughout the entire life cycle from the source.

[0068] In a preferred embodiment, the on-site service panel inspection device includes a winch traction system 9, which is detachably mechanically connected to a ramp-tracked inspection vehicle 8 for towing the inspection vehicle 8 along the slope. An RTK-GPS antenna 10 and an inertial navigation module 11 are both fixedly installed on the top of the inspection vehicle 8, and are electrically connected to form a combined positioning system. A suspension system 13 is flexibly mounted under the chassis of the inspection vehicle 8, and a multi-channel pulse eddy current sensor array 12 is also installed under the chassis of the inspection vehicle 8. Fine-tuning wheels 14 are located at the four corners of the bottom of the suspension system 13, and these wheels are fitted to the surface of the waterproof panel. A lithium battery 15 is built into the body of the inspection vehicle 8. Pool 15 is electrically connected to RTK-GPS antenna 10, inertial navigation module 11, multi-channel pulse eddy current sensor array 12, and transmission module 16, respectively, to power all onboard equipment. Electromagnetic detection signals collected by multi-channel pulse eddy current sensor array 12 are transmitted to transmission module 16 via lines. Transmission module 16 is wirelessly connected to base station 17 to achieve real-time data transmission. The tracks on the bottom of inspection vehicle 8 are made of soft rubber. An amphibious adsorption-type wall-climbing robot is independently configured for underwater panel inspection. With these features, the winch traction system 9 and inspection vehicle 8 are detachably connected, facilitating rapid transfer of equipment between panels of different slopes. The soft rubber tracks provide sufficient traction while avoiding mechanical damage to the anti-seepage panels. The suspension system 13, in conjunction with four corner micro-adjustment wheels 14, ensures the sensor array remains in contact with the panel surface, maintaining a constant lifting distance. A unified power supply from lithium battery 15 simplifies onboard wiring, and the 5G transmission module 16 transmits data back to base station 17 in real time, enabling simultaneous detection and decision-making. The amphibious wall-climbing robot extends the detection range from above the water surface to the underwater area, achieving full water level coverage detection of the anti-seepage panel and eliminating blind spots.

[0069] In the preferred embodiment, the data processing and analysis system includes: a data storage module for storing a laboratory baseline 3D database, an initial assembly 3D database, and previous inspection measurement 3D databases; a data preprocessing module for filtering out detection noise, correcting lift-off distance interference, and aligning the coordinates of multi-source data; a differential calculation module for performing differential calculations between the measured data and the initial assembly data, and outputting a differential matrix; a damage diagnosis module for distinguishing between microscopic damage and seepage defects based on the phase and amplitude change thresholds of the differential matrix; and a visualization module for generating panel damage and seepage distribution cloud maps and automatically outputting standardized inspection reports. These features construct a complete processing chain from data acquisition to report output. The data storage module uniformly manages the three sets of 3D databases—the baseline, the initial assembly, and previous inspection databases—ensuring data traceability. The preprocessing module eliminates system errors through noise filtering and lift-off distance correction, and coordinate alignment ensures that the measured and baseline data are comparable within the same spatial reference system. The differential matrix output by the differential calculation module presents damage characteristics in terms of phase and amplitude quantification, and the damage diagnosis module automatically classifies and distinguishes between microscopic damage and seepage defects based on preset thresholds. The visualization module generates damage and seepage distribution cloud maps and automatically outputs standardized detection reports, providing maintenance personnel with clear decision-making basis and significantly shortening the response cycle for detection and repair.

[0070] In summary, this invention proposes a method and system for detecting pumped-storage asphalt anti-seepage panels based on electromagnetic fingerprinting of modified iron aggregate. By uniformly incorporating surface-modified iron aggregate into the asphalt concrete anti-seepage layer, the invention utilizes the principle of electromagnetic induction to achieve early, high-precision, and full-area detection of microscopic damage and seepage in the anti-seepage panel, overcoming the shortcomings of existing detection technologies in terms of detection range, accuracy, and damage type identification capabilities. This invention uniformly incorporates surface-passivated iron sand or stainless steel magnetic powder coated with an epoxy resin film into the hydraulic asphalt concrete anti-seepage layer as modified iron aggregate, constructing a detectable medium with uniform electromagnetic properties. This gives the originally electromagnetically inert asphalt concrete stable and measurable electromagnetic response characteristics. Simultaneously, a dual-benchmark differential comparison mechanism is established between a laboratory initial electromagnetic fingerprint reference three-dimensional database and a field initial configuration three-dimensional database. By comparing the difference matrix between the measured data and the initial configuration data, rather than directly comparing with the laboratory benchmark, systematic errors caused by differences in construction processes are effectively eliminated.

[0071] In terms of positioning and scanning, this invention integrates a combined positioning system consisting of an RTK-GPS antenna 10 and an inertial navigation module 11 onto a tracked inspection vehicle 8 on a slope. This, combined with a suspension system 13 and fine-tuning wheels 14, maintains a constant lift-off distance, achieving high-precision full-area scanning with a planar positioning error of less than 1 cm on steep slope panels. Detection utilizes a dual-frequency alternating magnetic field of 1kHz and 100kHz. Through collaborative layered detection using probe 4, the 100kHz high-frequency signal focuses on damage in the surface detection area 18, while the 1kHz low-frequency signal penetrates to the seepage in the deep detection area 19, simultaneously acquiring surface and deep defect information in a single scan. A quantitative damage discrimination criterion is established based on the phase shift and amplitude change parameters of the difference matrix. Microscopic damage is determined by a phase shift with an amplitude change rate less than 10%, while seepage defects are determined by an amplitude jump with a change rate greater than 30%, achieving automatic classification of the two types of defects. In addition, an amphibious adhesive wall-climbing robot is configured to be used independently for underwater panel inspection, extending the inspection range from above the water surface to underwater, eliminating underwater blind spots that traditional inspection vehicles cannot cover.

[0072] In terms of technical effectiveness, this invention modifies the iron aggregate through surface passivation and epoxy resin dual coating treatment. This not only imparts electromagnetic detectability to asphalt concrete but also completely resolves the technical contradiction of secondary damage to the panel caused by rust expansion of the iron aggregate during its service life, achieving a balance between functionality and durability. The multi-frequency eddy current layered detection mechanism overcomes the inherent contradiction between detection depth and sensitivity in single-frequency signals, enabling simultaneous identification of surface microcracks and deep seepage channels in the same scan. The detection integrity is significantly superior to existing non-destructive testing technologies such as ultrasonic and ground-penetrating radar. The dual-benchmark differential comparison mechanism, compared to direct comparison with laboratory benchmarks, effectively avoids the inherent differences in density, aggregate distribution, etc., between the laboratory standard specimen 2 and the field-paved panel, making the damage judgment results closer to the actual service condition of the panel and significantly reducing the false alarm rate. The RTK-GPS antenna 10, combined with the inertial navigation module 11 and the suspension system 13, maintains a constant lift-off distance of 5 mm ± 1 mm even on steep slopes of 1:1.5 to 1:1.7, solving the engineering problem of signal distortion caused by lift-off distance fluctuations in traditional detection equipment on steep slopes. Damage discrimination employs a dual-parameter threshold cross-validation of phase and amplitude. The identification criteria for detailed damage and seepage defects are completely different, and the two types of defects do not interfere with each other, eliminating the misjudgment problem common in single-parameter discrimination methods from a fundamental perspective. The tiered inspection strategy, combining quarterly routine monitoring with annual dry season in-depth surveys, addresses the dual needs of early damage warning and deep seepage investigation, ensuring precise matching of detection frequency with damage evolution patterns and power plant operating cycles, significantly improving the efficiency of detection resource utilization.

Claims

1. A method for detecting pumped-storage asphalt anti-seepage panels based on electromagnetic fingerprinting of modified iron aggregate, characterized in that, Includes the following steps: Step 1: Prepare hydraulic asphalt concrete seepage prevention layer material mixed with surface-modified iron aggregate; Step 2: Fabricate standard specimens and collect initial electromagnetic fingerprints to establish a laboratory benchmark three-dimensional database; Step 3: The on-site paving forms the seepage-proof panel. After the panel cools to room temperature, the on-site inspection device is used to carry out the initial installation test to obtain the initial installation three-dimensional database. The initial installation three-dimensional database is then compared with the laboratory benchmark three-dimensional database to verify the paving quality. Step 4: During the service life of the seepage-proof panel, the entire area of ​​the panel is scanned regularly to collect a measured three-dimensional database. The surface above water is inspected using a tracked inspection vehicle, and the underwater area is inspected using an amphibious adsorption-type wall-climbing robot. Step 5: Align the measured 3D database with the initial 3D database in terms of coordinates and perform difference calculations to obtain the difference matrix; Step 6: Determine the damage type and corresponding location of the seepage-proof panel based on the parameter change characteristics of the difference matrix.

2. The method for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting according to claim 1, characterized in that: In step 1, the surface-modified iron aggregate is iron sand or stainless steel magnetic powder that has undergone surface passivation treatment and is coated with an epoxy resin film. The amount of surface-modified iron aggregate in asphalt concrete is 3% to 8% of the total mass of asphalt concrete.

3. The method for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting according to claim 1, characterized in that, Step 2, which involves acquiring the initial electromagnetic fingerprint, includes the following steps: Step 2.1: Use a non-magnetic non-metallic mold (1) made of polytetrafluoroethylene or high-strength epoxy resin to pour standard asphalt concrete specimens (2). Step 2.2: Place the specimen (2) in an environmental control chamber with a temperature adjustment range of -20℃ to 80℃ and a temperature control accuracy of ±0.5℃, adjust the temperature to 20℃±2℃ and keep it at a constant temperature for 24 hours; Step 2.3: Using a three-axis high-precision CNC scanning frame (3) with a positioning accuracy of ±0.1mm, and equipped with an array electromagnetic induction probe (4), the specimen (2) is subjected to XY-axis grid scanning with a set lift-off distance and scanning step distance; Step 2.4: Using the acquisition device (6) and detection coil (7), record the excitation impedance, phase angle and induced current amplitude of each coordinate point to generate a laboratory reference three-dimensional database.

4. The method for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting according to claim 1, characterized in that: The inclined tracked inspection vehicle (8) described in step 4 is towed by a winch traction system (9) and is equipped with an RTK-GPS+IMU combined positioning system consisting of an RTK-GPS antenna (10) and an inertial navigation module (11) and a multi-channel pulse eddy current sensor array (12). The RTK-GPS+IMU combined positioning system has a planar positioning error of less than 1cm and an elevation positioning error of less than 1.5cm. The multi-channel pulse eddy current sensor array (12) has a single scan width of 0.5m~1m and is fixed by a flexible suspension system (13). The suspension system (13) is equipped with a fine-tuning wheel (14) to maintain the probe lift distance at a constant 5mm±1mm. The inspection vehicle (8) is powered by an on-board lithium battery (15), and the detection data is transmitted to the shore base station (17) in real time through a wireless transmission module (16).

5. The method for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting according to claim 1, characterized in that: The detection described in step 4 uses a 1kHz and 100kHz dual-frequency alternating magnetic field for layered detection; the 100kHz high-frequency signal is used to detect surface damage in the 0~5cm surface detection area (18) of the anti-seepage panel, and the 1kHz low-frequency signal is used to detect deep damage and seepage in the 5~20cm deep detection area (19) of the anti-seepage panel; the frequency of the regular full-area scanning of the panel is divided into two categories: regular monitoring is carried out once a quarter, and in-depth survey is carried out once a year during the dry season; the inclined tracked inspection vehicle (8) is adapted to asphalt concrete anti-seepage panels with a slope of 1:1.5~1:1.

7.

6. The method for detecting pumped storage asphalt anti-seepage panels based on modified iron aggregate electromagnetic fingerprinting according to claim 1, characterized in that, The damage discrimination criteria in step 6 are as follows: if a phase shift occurs in a local area of ​​the difference matrix and the amplitude change rate is less than 10%, it is judged as micro-cracks or aggregate displacement-type micro-damage; if an amplitude jump occurs in a local area of ​​the difference matrix and the amplitude change rate is greater than 30%, it is judged as internal saturation or water seepage defects.

7. A pumping-storage asphalt barrier panel testing system based on modified iron aggregate electromagnetic fingerprinting, which is a system for implementing the pumping-storage asphalt barrier panel testing method based on modified iron aggregate electromagnetic fingerprinting as described in any one of claims 1 to 6, characterized in that: It includes a laboratory initial condition measurement device, an on-site service panel inspection device, and a data processing and analysis system.

8. The pumped storage asphalt anti-seepage panel detection system based on modified iron aggregate electromagnetic fingerprinting according to claim 7, characterized in that: The laboratory initial state determination device includes a non-magnetic non-metallic mold (1), which is placed inside an environmental control chamber (5). The molded specimen (2) is placed inside the mold (1). A three-axis high-precision scanning frame (3) is mounted above the environmental control chamber (5). An array probe (4) is fixedly installed on the moving end of the three-axis high-precision scanning frame (3). A detection coil (7) is integrated inside the array probe (4). The detection coil (7) is electrically connected to the acquisition device (6) through a signal line. The mold (1) is made of polytetrafluoroethylene or high-strength epoxy resin. The environmental control chamber (5) is used to simulate a temperature environment of -20℃ to 80℃.

9. The pumped storage asphalt anti-seepage panel detection system based on modified iron aggregate electromagnetic fingerprinting according to claim 7, characterized in that: The field service panel inspection device includes a winch traction system (9), which is detachably mechanically connected to the inclined tracked inspection vehicle (8) for towing the inspection vehicle (8) to move along the slope; the RTK-GPS antenna (10) and the inertial navigation module (11) are both fixedly installed on the top of the inspection vehicle (8) and electrically connected to form a combined positioning system; the suspension system (13) is flexibly mounted under the chassis of the inspection vehicle (8), and a multi-channel pulse eddy current sensor array (12) is also installed under the chassis of the inspection vehicle (8); the four corners of the bottom of the suspension system (13) are provided with fine-tuning wheels (14), which are in contact with the surface of the anti-seepage panel; The lithium battery (15) is built into the body of the inspection vehicle (8). The lithium battery (15) is electrically connected to the RTK-GPS antenna (10), the inertial navigation module (11), the multi-channel pulse eddy current sensor array (12), and the transmission module (16) to power all the on-board equipment. The electromagnetic detection signal collected by the multi-channel pulse eddy current sensor array (12) is transmitted to the transmission module (16) through the line. The transmission module (16) is wirelessly connected to the base station (17) to realize the real-time transmission of detection data. The bottom track of the inspection vehicle (8) is made of soft rubber. The amphibious adsorption wall-climbing robot is independently configured for underwater panel detection.

10. The pumped storage asphalt anti-seepage panel detection system based on modified iron aggregate electromagnetic fingerprinting according to claim 7, characterized in that, The data processing and analysis system includes: The data storage module is used to store the laboratory baseline 3D database, the initial 3D database, and the 3D database measured during each inspection. The data preprocessing module is used to filter out detection noise, correct for lift-off distance interference, and complete the coordinate alignment of multi-source data. The difference calculation module is used to perform difference calculations between the measured data and the initial setup data, and output the difference matrix. The damage diagnosis module distinguishes between microscopic damage and seepage defects based on the phase and amplitude change thresholds of the difference matrix. The visualization module generates panel damage and seepage distribution cloud maps and automatically outputs standardized test reports.

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