Intelligent sensing geopolymer concrete sensor and preparation method and application thereof

Abstract

This invention belongs to the field of intelligent concrete material technology, specifically disclosing an intelligent sensing geopolymer concrete sensor, its preparation method, and its application. The intelligent sensing geopolymer concrete sensor includes a geopolymer concrete body and a distributed monitoring electrode array disposed within the geopolymer concrete body. The total weight of the geopolymer concrete body, based on 100%, consists of the following raw materials by weight: 40-45% geopolymer cementitious material, 25-30% fine aggregate, 15-20% coarse aggregate, 0.8-1.2% carbon nanotubes, 3-5% lead zirconate titanate piezoelectric particles, 0.4-0.6% polycarboxylate dispersant, 2-4% ultrafine silica fume, 0.1-0.2% organosilicon defoamer, and the balance being deionized water. Based on the synergistic effect of the carbon nanotube conductive network and the lead zirconate titanate piezoelectric particles, high-precision, multi-dimensional monitoring of dynamic and static damage is achieved, with stable and reliable signals.

Description

Technical Field

[0001] This invention belongs to the field of intelligent concrete material technology, specifically relating to an intelligent sensing geopolymer concrete sensor, its preparation method, and its application. Background Technology

[0002] Traditional methods for monitoring internal damage in concrete structures primarily rely on strain gauges, fiber optic sensors, or periodic non-destructive testing. Strain gauges are susceptible to environmental influences, have poor durability, and can only provide information at localized points. Fiber optic sensors are complex to install, costly, and lack sensitivity to minute cracks. Non-destructive testing struggles to achieve real-time, continuous, and large-scale online monitoring, exhibiting low efficiency and significant latency, thus failing to meet the urgent needs of modern large-scale infrastructure for early warning of hidden damage and life-cycle health management.

[0003] Geopolymer concrete, as a novel green cementitious material, has shown great potential in structural repair, reinforcement, and new construction in harsh environments such as industrial buildings, bridges, tunnels, and marine engineering, thanks to its rapid hardening, early strength, high temperature resistance, corrosion resistance, low shrinkage, and excellent interfacial bonding properties. However, during long-term service, geopolymer concrete structures can also develop and propagate microcracks due to factors such as load fatigue, environmental erosion, freeze-thaw cycles, and shrinkage stress, ultimately leading to structural performance degradation or even failure. Existing monitoring methods are insufficient to efficiently and accurately capture the early micro-damage evolution process within the structure.

[0004] In recent years, smart concrete technology, which incorporates conductive / piezoelectric functional materials into cement matrices to endow them with self-sensing capabilities, has become a research hotspot. Monitoring methods based on resistance changes or piezoelectric effects have been extensively explored. However, existing technologies generally have significant limitations: single resistance methods are susceptible to interference from environmental temperature and humidity, have poor signal stability, and are insensitive to non-penetrating microcracks; single piezoelectric methods require an external excitation source, making the system complex, and the dispersion, polarization efficiency, and interfacial compatibility of piezoelectric particles in concrete directly affect signal quality. Furthermore, existing smart concrete sensors often suffer from insufficient sensitivity, narrow linear range, poor long-term stability, and low integration with structural health monitoring systems, making it difficult to achieve high-precision, high-reliability distributed real-time monitoring, which severely restricts their large-scale application in practical engineering. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent sensing geopolymer concrete sensor, its preparation method, and its application. The geopolymer concrete sensor is based on the synergistic effect of carbon nanotube conductive networks and lead zirconate titanate piezoelectric particles to achieve real-time, high-precision, distributed sensing and early warning of internal stress and strain states and early damage of the structure.

[0006] A smart sensing geopolymer concrete sensor includes a geopolymer concrete body and a distributed monitoring electrode array disposed within the geopolymer concrete body; The total weight of the geopolymer concrete body, calculated as 100%, consists of the following raw materials by weight: 40%~45% geopolymer cementitious material, 25%~30% fine aggregate, 15%~20% coarse aggregate, 0.8%~1.2% carbon nanotubes, 3%~5% lead zirconate titanate piezoelectric particles, 0.4%~0.6% polycarboxylic acid dispersant, 2%~4% ultrafine silica fume, 0.1%~0.2% organosilicon defoamer, and the balance being deionized water.

[0007] The ultrafine silica fume described in this invention has a specific surface area ≥20000 m² as measured by the BET nitrogen adsorption method. 2 Amorphous silicon powder with an average particle size of ≤100nm and a SiO2 mass content of ≥92% per kg.

[0008] Preferably, the geopolymer cementitious material is composed of metakaolin powder and an alkali activator mixed at a mass ratio of 1:(0.6~1.0). The metakaolin powder is an oven-dry basis powder.

[0009] Preferably, the specific surface area of ​​the metakaolin powder is 400~500m² / kg, wherein the content of SiO2 and Al2O3 is ≥85%; the alkali activator is a water glass solution with a modulus of 3.2 and a solid content of 38%~40%.

[0010] Preferably, the carbon nanotubes are multi-walled carbon nanotubes with a diameter of 10-20 nm, a length of 5-10 μm, and a carboxyl functional group content of 0.5%-1.0% by mass; the lead zirconate titanate piezoelectric particles have an average particle size of 50-100 μm and a piezoelectric constant d. 33 ≥450pC / N, Curie temperature ≥350℃.

[0011] Preferably, the polycarboxylic acid dispersant has a solid content of 40% to 45% and a pH value of 7 to 8.

[0012] Preferably, the fine aggregate is natural sand with a particle size ≤ 5 mm, and the coarse aggregate is crushed stone with a particle size of 5~10 mm.

[0013] Preferably, the distributed monitoring electrode array consists of multiple pairs of copper-plated metal electrodes arranged in parallel at equal intervals. More preferably, the metal electrodes are any one of 304 stainless steel, 316L stainless steel, TC4 titanium alloy, or oxygen-free copper, and the metal electrodes are cylindrical rods. More preferably, the thickness of the copper plating is 5~20μm.

[0014] The method for preparing the intelligent sensing geopolymer concrete sensor includes the following steps: Step S1. Add deionized water and polycarboxylic acid dispersant to a mixer and stir at 800~1000 r / min for 3~5 min; then add carbon nanotubes and continue stirring and dispersing at 2000~2500 r / min for 20~30 min to obtain conductive slurry; Step S2. Add geopolymer cementitious material, fine aggregate, coarse aggregate, and ultrafine silica fume sequentially to the conductive slurry, and stir at 1500~1800 r / min for 10-15 min to form a concrete matrix; Step S3. Add lead zirconate titanate piezoelectric particles to the concrete matrix and stir at 1200~1500 r / min for 8~12 min; finally add organosilicon defoamer and stir at 800~1000 r / min for 5~8 min to obtain sensor slurry; Step S4. Pour the sensor slurry into a mold, insert the distributed monitoring electrode array, compact it by vibration, and cure it for 24 hours at 20±2℃ and relative humidity ≥95% to form a prefabricated sensor unit; or directly pour the sensor slurry into a designated position on the concrete structure to be monitored, simultaneously insert the distributed monitoring electrode array, compact it by vibration, and then perform standard curing simultaneously with the concrete structure to be monitored to form a direct sensor unit. Step S5. Apply a polarized electric field to the prefabricated sensor unit or the direct sensor unit to perform polarization processing, thereby obtaining the intelligent sensing geopolymer concrete sensor.

[0015] Preferably, the electric field strength of the polarization treatment is 2~3kV / mm, the polarization temperature is 80~100℃, and the polarization time is 30~60min; the curing is carried out by drying in an oven at 90℃~95℃ for 25~30min; and the standard curing conditions are a temperature of 20±2℃, a relative humidity of ≥95%, and a curing age of not less than 28d.

[0016] The monitoring system based on the intelligent sensing geopolymer concrete sensor is characterized by comprising an embedded sensor unit, a signal excitation and acquisition unit, a data processing and damage diagnosis unit, and a data transmission unit connected in sequence. The embedded sensor unit includes at least one intelligent sensing geopolymer concrete sensor, which is installed at the point to be monitored. The signal excitation and acquisition unit includes a constant voltage source, a current amplifier, and a charge amplifier connected in parallel. The constant voltage source is used to apply an excitation voltage of no more than 3V to the distributed monitoring electrode array. The current amplifier is used to acquire the loop current signal caused by the change in the conductive network of the carbon nanotube. The charge amplifier is used to acquire the piezoelectric charge signal generated by the stress on the lead zirconate titanate piezoelectric particles. The data processing and damage diagnosis unit receives current and charge signals from the signal excitation and acquisition unit, analyzes the signal change patterns based on the resistance tomography algorithm and piezoelectric sensor signal processing technology, completes stress-strain state identification, damage location positioning, damage degree assessment, and triggers an early warning signal when the signal characteristics exceed a preset threshold. The data transmission unit transmits the processed data and early warning information to the remote monitoring center.

[0017] Preferably, the monitoring system operates at a frequency of once per second to once per day.

[0018] Preferably, the data processing and damage diagnosis unit analyzes the signal path and its variation characteristics of the distributed monitoring electrode array to achieve distributed mapping of stress-strain field and damage within the sensor coverage area.

[0019] Preferably, the correspondence between the degree of damage (crack width) and the signal change pattern and early warning in this invention is as follows: (I) Normal state / no damage: The resistivity of the monitored area changes steadily without sudden increase, and the piezoelectric signal amplitude does not attenuate. The structure is judged to be normal, and there is no early warning; (II) Level 1 early warning: When the resistivity of the monitored area suddenly increases within the range of (20%~80%), and the attenuation rate of the piezoelectric signal amplitude is within the range of (10%~30%), microcracks with a width of <0.05mm are generated inside the concrete. The system judges this as microscopic damage and crack initiation, triggering a Level 1 early warning, prompting increased attention and daily inspections; (III) Level 2 early warning: When the resistivity of the monitored area suddenly increases within the range of [80%~150%), and the attenuation rate of the piezoelectric signal amplitude is within the range of [30%~60%), the corresponding crack width is ≥0.05mm and <0.2mm, triggering a Level 2 early warning, indicating early visible cracks and obvious damage, requiring on-site professional testing; (IV) Level 3 warning: When the resistivity of the monitored area suddenly increases by ≥150% or shows an open circuit state, and the attenuation rate of the piezoelectric signal amplitude is ≥60%, the corresponding crack width is ≥0.2mm, reaching the crack limit of general concrete structure specifications, triggering a Level 3 warning, indicating that the structure is seriously damaged, there are macro cracks, the safety risk is high, and reinforcement and repair measures must be taken immediately.

[0020] The location of the damage is the monitoring point of the intelligent sensing geopolymer concrete sensor, which conforms to the above-mentioned change pattern.

[0021] The advantages of this invention are as follows: 1. Dual-signal collaborative sensing enables high-precision, multi-dimensional monitoring of dynamic and static damage: A three-dimensional continuous conductive network constructed from carbon nanotubes in a geopolymer concrete matrix allows for real-time sensing of resistance / impedance changes caused by matrix deformation under load and the initiation and propagation of microcracks, achieving continuous capture of static damage from initiation to propagation. Simultaneously, the positive piezoelectric effect and active sensing characteristics of lead zirconate titanate piezoelectric particles accurately respond to stress and strain generated by dynamic loads, capturing the real-time structural response under dynamic conditions such as impact and vibration. These two approaches form a synergistic and complementary system of "full-domain static damage monitoring + precise dynamic load response," overcoming the core shortcomings of existing single resistance methods, which are susceptible to environmental interference, and single piezoelectric methods, which have narrow monitoring dimensions. Verified by standard working condition tests, the sensor of this invention has a measured resistance change rate of ≥80% for microcracks with a width of 0.05mm; a stable response with a linear correlation coefficient of ≥0.99 for static strain of 10με level; and a highly sensitive linear response for dynamic stress of 0.1MPa level. Its monitoring accuracy, anti-interference ability and monitoring coverage are significantly better than existing smart concrete sensors with a single sensing mode. 2. Strong environmental adaptability and long-term stable and reliable signal: The geopolymer concrete matrix used in this invention has superior resistance to high alkali corrosion, resistance to wet-dry cycles, and low shrinkage deformation characteristics compared to ordinary cement matrix. It is highly compatible with the elastic modulus and thermal expansion coefficient of the concrete to be monitored, achieving deformation coordination and long-term interface synergy with the main structure. Combined with copper-plated anti-corrosion metal electrodes, it effectively resists long-term erosion from the high-alkali and humid environment inside the concrete. Simultaneously, the use of a low-voltage DC excitation strategy of ≤3V, combined with a polling acquisition mode of a distributed electrode array, significantly suppresses electrochemical corrosion and polarization effects of the electrodes, fundamentally solving the core defect of continuous baseline drift in traditional sensors. Verified by accelerated aging tests in standard environments, under harsh conditions of repeated temperature fluctuations from -20℃ to 80℃ and constant high humidity of 95%RH, the annual baseline drift rate of the sensor in this invention is ≤3%, far superior to traditional embedded strain gauges and cement-based smart sensors, solving the problems of susceptibility to environmental temperature and humidity interference, rapid signal attenuation, and insufficient long-term monitoring reliability in existing technologies. 3. Excellent structural compatibility and convenient construction across all scenarios: The core matrix of this invention's sensor is geopolymer concrete, whose coefficient of thermal expansion and modulus of elasticity are highly compatible with the C30~C50 ordinary concrete most commonly used in domestic engineering. This ensures deformation coordination with the main structure from the intrinsic material properties, completely avoiding problems such as additional stress, interface debonding, and signal distortion caused by material performance mismatch in traditional sensors. Standard operating condition tests have verified that the 28-day shear bond strength between this sensor and ordinary concrete is ≥2.5MPa, demonstrating excellent interfacial bonding performance. Furthermore, this sensor is compatible with two full-scenario construction modes: it can be prefabricated into standardized sensor units in the factory and directly embedded in the pre-set locations on the main structure; or it can be directly poured on-site at the monitoring location, simultaneously poured and cured with the main structure, achieving integrated "structure-sensing" molding. Furthermore, the polarization process of this invention is fully compatible with conventional concrete curing systems. Precast units can be polarized in advance and then directly brought to the site, while in-situ cast units can be polarized on-site after the standard curing of the main structure is completed. No complicated special post-treatment procedures are required, which greatly reduces the difficulty and cost of on-site construction. 4. Distributed Monitoring and Lifecycle Cost Advantages: Based on multi-path signal acquisition and intelligent diagnostic algorithms using electrode arrays, damaged areas can be accurately located and the degree of damage assessed, achieving spatial mapping of the internal state of the structure. The geopolymer matrix raw material has low cost and significant advantages for large-scale production. This integrated solution replaces the need for a large number of externally deployed point sensors, significantly reducing installation and maintenance costs and system complexity. The lifecycle cost is more than 40% lower than the traditional "structure + independent monitoring system" model. Attached Figure Description

[0022] Figure 1 A schematic diagram showing the locations of sensors embedded inside a concrete beam; Among them, 1-intelligent sensing geopolymer concrete sensor, 2-signal transmission line, 3-bridge structural component. Detailed Implementation

[0023] Example 1: 1. An intelligent sensing geopolymer concrete sensor, shaped like a cube with dimensions of 100mm × 100mm × 100mm, comprising a geopolymer concrete body and a distributed monitoring electrode array disposed within the geopolymer concrete body; The total weight of the geopolymer concrete body is calculated as 100%, and it is composed of the following raw materials by weight: 42% geopolymer cementitious material, 28% fine aggregate, 18% coarse aggregate, 1% carbon nanotubes, 4% lead zirconate titanate piezoelectric particles, 0.5% polycarboxylic acid dispersant, 3% ultrafine silica fume, 0.1% organosilicon defoamer, and the balance is deionized water. The geopolymer cementitious material is composed of oven-dry basis metakaolin powder and alkali activator mixed at a mass ratio of 1:0.8; the specific surface area of ​​the metakaolin powder is 450 m² / kg, and the total mass content of SiO2 and Al2O3 in the metakaolin powder is 85%; the alkali activator is a water glass solution with a modulus of 3.2 and a solid content of 39%. The ultrafine silica fume has a specific surface area of ​​25,000 m², as measured by the BET nitrogen adsorption method. 2 Amorphous silica powder with an average particle size of 50 nm and a SiO2 mass content of 95% per kg; The carbon nanotubes are multi-walled carbon nanotubes with a diameter of 15 nm, a length of 8 μm, a purity of 98.5%, and a carboxyl functional group content of 0.8% by mass. The lead zirconate titanate piezoelectric particles have an average particle size of 75 μm and a piezoelectric constant d. 33 It has a strength of 480 pC / N, a Curie temperature of 380℃, and a purity of 99.5%. The polycarboxylic acid dispersant is Jiangsu Subote PCA-I polycarboxylic acid high-efficiency dispersant with a solid content of 43% and a pH value of 7. The fine aggregate is natural river sand with a particle size ≤ 5 mm, and the coarse aggregate is continuously graded basalt crushed stone with a particle size of 5~10 mm. The silicone defoamer is Dow Corning DC-1410 silicone defoamer; The distributed monitoring electrode array consists of two sets of 304 stainless steel electrode pairs with copper plating arranged at intervals. Each set of electrode pairs includes two parallel cylindrical electrode rods with a diameter of 2 mm, a length of 90 mm, and a copper plating layer thickness of 10 μm. The distance between the two electrode rods in the same set of electrode pairs is 20 mm, and the center-to-center distance between the two sets of electrode pairs is 60 mm. The electrode pairs are buried in the center along the height direction of the cube.

[0024] 2. The method for preparing the intelligent sensing geopolymer concrete sensor: Step S1. Add deionized water and polycarboxylic acid dispersant to a mixer and stir at 900 r / min for 4 min; then add carbon nanotubes and continue stirring and dispersing at 2200 r / min for 28 min to obtain a uniform conductive slurry. Step S2. Add geopolymer cementitious material, fine aggregate, coarse aggregate, and ultrafine silica fume to the conductive slurry in sequence, and stir at 1600 r / min for 12 min to form a well-homogeneous concrete matrix; Step S3. Add lead zirconate titanate piezoelectric particles to the concrete matrix and stir at 1300 r / min for 10 min; finally add an organosilicon defoamer and stir at 900 r / min for 6 min to obtain the sensor slurry; Step S4. The sensor slurry is poured into a 100mm×100mm×100mm steel mold, a distributed monitoring electrode array is inserted, and after being vibrated and compacted, it is cured for 24 hours at 20±2℃ and relative humidity ≥95%. After demolding, it is placed in an oven and kept at 90℃ for 30 minutes to complete the curing, forming a prefabricated sensor unit. Step S5. Subsequently, in a constant temperature environment of 85°C silicone oil bath, a DC polarization electric field of 2.5kV / mm is applied to the distributed monitoring electrode array for 45 minutes for polarization treatment. After natural cooling to room temperature, the intelligent sensing geopolymer concrete sensor is obtained.

[0025] 3. A monitoring system based on the aforementioned intelligent sensing geopolymer concrete sensor includes an embedded sensor unit, a signal excitation and acquisition unit, a data processing and damage diagnosis unit, and a data transmission unit that are connected in sequence by electrical connection. The embedded sensor unit includes multiple intelligent sensing geopolymer concrete sensors, which are installed at the monitoring points. The signal excitation and acquisition unit includes a constant voltage source, a current amplifier, and a charge amplifier connected in parallel. The constant voltage source is used to apply a DC excitation voltage of no more than 3V to the distributed monitoring electrode array. The current amplifier is used to acquire the loop current signal caused by the change in the conductive network of the carbon nanotube. The charge amplifier is used to acquire the piezoelectric charge signal generated by the stress on the lead zirconate titanate piezoelectric particles. The data processing and damage diagnosis unit receives current and charge signals from the signal excitation and acquisition unit, analyzes the signal change patterns based on the resistance tomography algorithm and piezoelectric sensor signal processing technology, identifies the stress-strain state, locates the damage location, assesses the degree of damage, and triggers an early warning signal. The data transmission unit transmits the processed data and early warning information to the remote monitoring center; The operating frequency of the monitoring system can be adjusted from once per second to once per day. The data processing and damage diagnosis unit analyzes the signal path and its variation characteristics of the distributed monitoring electrode array to achieve distributed mapping of stress-strain field and damage within the sensor coverage area. The relationship between the degree of damage (crack width) and the signal change pattern and early warning is as follows: (I) Normal state / no damage: The resistivity of the monitored area changes steadily without sudden increase, and the piezoelectric signal amplitude does not attenuate. The structure is judged to be normal, and there is no early warning; (II) Level 1 early warning: When the resistivity of the monitored area increases suddenly in the range of (20%~80%), and the attenuation rate of the piezoelectric signal amplitude is in the range of (10%~30%), microcracks with a width of <0.05mm are generated inside the concrete. The system judges this as microscopic damage and crack initiation, triggering a Level 1 early warning, prompting increased attention and daily inspections; (III) Level 2 early warning: When the resistivity of the monitored area increases suddenly in the range of [80%~150%), and the attenuation rate of the piezoelectric signal amplitude is in the range of [30%~60%), the corresponding crack width is ≥0.05mm and <0.2mm, triggering a Level 2 early warning, indicating early visible cracks and obvious damage, requiring on-site professional testing; (IV) Level 3 warning: When the resistivity of the monitored area suddenly increases by ≥150% or shows an open circuit state, and the attenuation rate of the piezoelectric signal amplitude is ≥60%, the corresponding crack width is ≥0.2mm, reaching the crack limit of general concrete structure specifications, triggering a Level 3 warning, indicating that the structure is seriously damaged, there are macro cracks, the safety risk is high, and reinforcement and repair measures must be taken immediately.

[0026] 4. The monitoring system based on the aforementioned intelligent sensing geopolymer concrete sensor is used to monitor the concrete bridge structure. The intelligent sensing geopolymer concrete sensor (1) is fixed at a preset position at the bottom of the mid-span of the bridge structural member (3) to ensure that it has no electrical contact with the steel reinforcement mesh inside the beam. Figure 1 As shown, the beam concrete is poured and cured to the specified age. Multiple intelligent sensing polymer concrete sensors (1) are connected in sequence to the signal excitation and acquisition unit, the data processing and damage diagnosis unit, and the data transmission unit via signal transmission lines (2); the signal transmission lines (2) are weather-resistant shielded twisted-pair cables; the signal excitation and acquisition unit and the data processing and damage diagnosis unit are installed in the beam end protection box or in the remote monitoring room; The monitoring frequency is set to once per minute; a constant voltage source applies a 2V DC voltage to the electrode pair as the excitation voltage, and the current amplifier collects the loop current changes of each path in real time; the charge amplifier collects the piezoelectric charge signal of each electrode pair in real time; the data processing and damage diagnosis unit receives the current signal and charge signal, inverts the resistivity distribution of the monitoring area based on the resistivity tomography algorithm, and extracts the signal amplitude change, spatial correlation and spectral characteristics based on the piezoelectric sensor signal processing technology; when the intelligent sensing geopolymer concrete sensor in the bottom area of ​​the span is detected to have a resistivity surge range of [80%~150%) and a piezoelectric signal amplitude attenuation rate range of [30%~60%), the system determines that a crack with a width ≥0.05mm and <0.2mm has appeared at the monitoring point, immediately triggers a level two early warning, and transmits the relevant data to the remote monitoring center.

[0027] 5. Performance Verification Testing The sensor prepared in this embodiment was subjected to standard operating condition performance testing, and the results are as follows: ① Microcrack identification performance: Under a crack with a width of 0.05 mm, the measured average resistance change rate is 87.2%, which meets the design requirement of ≥80%; it has a stable linear response to static strain of 10 με level and dynamic stress of 0.1 MPa level, with linear correlation coefficients of 0.992 and 0.995, respectively; ② Long-term stability performance: Under temperature fluctuations of -20℃ to 80℃ and high humidity of 95%RH, the signal baseline drift rate after one year of service is 2.12%, which meets the design requirement of ≤3% / year; ③ Interface compatibility performance: The average 28-day interfacial shear bond strength with C40 ordinary concrete is 3.27 MPa, which meets the design requirement of ≥2.5 MPa.

[0028] Example 2: 1. An intelligent sensing geopolymer concrete sensor, shaped like a cube with dimensions of 100mm × 100mm × 100mm, comprising a geopolymer concrete body and a distributed monitoring electrode array disposed within the geopolymer concrete body; The total weight of the geopolymer concrete body is calculated as 100%, and it is composed of the following raw materials by weight: 40% geopolymer cementitious material, 25% fine aggregate, 20% coarse aggregate, 1.2% carbon nanotubes, 3% lead zirconate titanate piezoelectric particles, 0.4% polycarboxylic acid dispersant, 4% ultrafine silica fume, 0.1% organosilicon defoamer, and the balance is deionized water. The geopolymer cementitious material is composed of oven-dry basis metakaolin powder and an alkali activator mixed at a mass ratio of 1:0.6; the specific surface area of ​​the metakaolin powder is 400 m². 2 / kg, the total mass content of SiO2 and Al2O3 in the metakaolin powder is 90%; the alkali activator is a water glass solution with a modulus of 3.2 and a solid content of 38%; The ultrafine silica fume has a specific surface area of ​​22,000 m², as measured by the BET nitrogen adsorption method. 2 Amorphous silica powder with an average particle size of 80 nm and a SiO2 content of 94% per kg; The carbon nanotubes are multi-walled carbon nanotubes with a diameter of 10 nm, a length of 5 μm, a purity of 98%, and a carboxyl functional group content of 0.5% by mass. The lead zirconate titanate piezoelectric particles have an average particle size of 50 μm and a piezoelectric constant d. 33 It has a strength of 450 pC / N, a Curie temperature of 350℃, and a purity of 99%. The polycarboxylic acid dispersant is BASF Melflux 2651F, a high-efficiency polycarboxylic acid dispersant with a solid content of 40% and a pH value of 8. The fine aggregate is natural river sand with a particle size ≤ 5 mm, and the coarse aggregate is continuously graded granite crushed stone with a particle size of 5~10 mm. The silicone defoamer is Jiangsu Sixin SXP-101 silicone defoamer; The distributed monitoring electrode array consists of two sets of spaced-alternating oxygen-free copper electrode pairs with copper plating on the surface. Each electrode pair contains two parallel cylindrical electrode rods with a diameter of 2 mm, a length of 90 mm, and a copper plating layer thickness of 5 μm. The distance between the two electrode rods in the same electrode pair is 20 mm, and the center-to-center distance between the two sets of electrode pairs is 60 mm. The electrode pairs are buried in the center along the height direction of the cube.

[0029] 2. The method for preparing the intelligent sensing geopolymer concrete sensor: Step S1. Add deionized water and polycarboxylate dispersant to a mixer and stir at 800 r / min for 5 min; then add carbon nanotubes and continue stirring and dispersing at 2000 r / min for 30 min to obtain a uniform conductive slurry. Step S2. Add geopolymer cementitious material, fine aggregate, coarse aggregate, and ultrafine silica fume to the conductive slurry in sequence, and stir at 1500 r / min for 15 min to form a well-homogeneous concrete matrix; Step S3. Add lead zirconate titanate piezoelectric particles to the concrete matrix and stir at 1200 r / min for 12 min; finally add an organosilicon defoamer and stir at 800 r / min for 8 min to obtain the sensor slurry; Step S4. The sensor slurry is poured into a 100mm×100mm×100mm steel mold, a distributed monitoring electrode array is inserted, and after being vibrated and compacted, it is cured for 24 hours at 20±2℃ and relative humidity ≥95%. After demolding, it is placed in an oven and kept at 95℃ for 25 minutes to complete the curing, forming a prefabricated sensor unit. Step S5. Subsequently, in a constant temperature environment of 100°C silicone oil bath, a DC polarization electric field of 3kV / mm is applied to the distributed monitoring electrode array for 30 minutes for polarization treatment. After natural cooling to room temperature, the intelligent sensing geopolymer concrete sensor is obtained.

[0030] 3. Performance Verification Testing The sensor prepared in this embodiment was subjected to standard operating condition performance testing, and the results are as follows: ① Microcrack identification performance: Under a crack with a width of 0.05 mm, the measured average resistance change rate is 82.5%, which meets the design requirement of ≥80%; it has a stable linear response to static strain of 10 με level and dynamic stress of 0.1 MPa level, with linear correlation coefficients of 0.990 and 0.993, respectively. ② Long-term stability performance: Under temperature fluctuations of -20℃ to 80℃ and high humidity of 95%RH, the signal baseline drift rate after one year of service is 2.75%, which meets the design requirement of ≤3% / year; ③ Interface compatibility performance: The average 28-day interfacial shear bond strength with C40 ordinary concrete is 2.84 MPa, which meets the design requirement of ≥2.5 MPa.

[0031] Example 3: 1. An intelligent sensing geopolymer concrete sensor, comprising a geopolymer concrete body and a distributed monitoring electrode array disposed within the geopolymer concrete body; The total weight of the geopolymer concrete body, calculated as 100%, is composed of the following raw materials by weight: 45% geopolymer cementitious material, 30% fine aggregate, 15% coarse aggregate, 0.8% carbon nanotubes, 5% lead zirconate titanate piezoelectric particles, 0.6% polycarboxylic acid dispersant, 2% ultrafine silica fume, 0.2% organosilicon defoamer, and the balance being deionized water. The geopolymer cementitious material is composed of oven-dry metakaolin powder and an alkali activator mixed at a mass ratio of 1:1; the specific surface area of ​​the metakaolin powder is 500 m². 2 / kg, the total mass content of SiO2 and Al2O3 in the metakaolin powder is 85%; the alkali activator is a water glass solution with a modulus of 3.2 and a solid content of 40%; The ultrafine silica fume has a specific surface area of ​​28,000 m², as measured by the BET nitrogen adsorption method. 2 Amorphous silicon powder with an average particle size of 30 nm and a SiO2 content of 96% per kg; The carbon nanotubes are multi-walled carbon nanotubes with a diameter of 20 nm, a length of 10 μm, a purity of 99%, and a carboxyl functional group content of 1.0% by mass. The lead zirconate titanate piezoelectric particles have an average particle size of 100 μm and a piezoelectric constant d. 33 It has a strength of 500 pC / N, a Curie temperature of 360℃, and a purity of 99.5%. The polycarboxylic acid dispersant is Clariant Geniosol P90 polycarboxylic acid high-efficiency dispersant with a solid content of 45% and a pH value of 8. The fine aggregate is natural river sand with a particle size ≤ 5 mm, and the coarse aggregate is continuously graded basalt crushed stone with a particle size of 5~10 mm. The silicone defoamer is Dow Corning DC-1410 silicone defoamer; The distributed monitoring electrode array consists of three sets of TC4 titanium alloy electrode pairs with copper plating arranged at intervals. Each electrode pair contains two parallel cylindrical electrode rods with a diameter of 2 mm and a copper plating layer thickness of 20 μm. The distance between the two electrode rods in the same electrode pair is 20 mm, and the center-to-center distance between two adjacent electrode pairs is 50 mm. The electrode pairs are buried parallel to the stress direction of the structure to be monitored.

[0032] 2. The method for preparing the intelligent sensing geopolymer concrete sensor: Step S1. Add deionized water and polycarboxylic acid dispersant to a mixer and stir at 1000 r / min for 3 min; then add carbon nanotubes and continue stirring and dispersing at 2500 r / min for 20 min to obtain a uniform conductive slurry. Step S2. Add geopolymer cementitious material, fine aggregate, coarse aggregate, and ultrafine silica fume to the conductive slurry in sequence, and stir at 1800 r / min for 10 min to form a well-homogeneous concrete matrix; Step S3. Add lead zirconate titanate piezoelectric particles to the concrete matrix and stir at 1500 r / min for 8 min; finally add an organosilicon defoamer and stir at 1000 r / min for 5 min to obtain the sensor slurry. Step S4. Directly pour the sensor slurry into the designated position of the concrete structure to be monitored, simultaneously insert the distributed monitoring electrode array, and after compaction by vibration, perform standard curing (curing conditions: temperature 20±2℃, relative humidity ≥95%) simultaneously with the concrete structure to be monitored to complete the curing and form a direct sensor unit; Step S5. Subsequently, a constant temperature heating cable is used to heat the electrode area to 80°C and keep it at that temperature. A DC polarization electric field of 2kV / mm is applied to the distributed monitoring electrode array for 60 minutes for polarization treatment. After natural cooling to room temperature, the intelligent sensing geopolymer concrete sensor is obtained.

[0033] 3. A monitoring system based on the aforementioned intelligent sensing geopolymer concrete sensor includes an embedded sensor unit, a signal excitation and acquisition unit, a data processing and damage diagnosis unit, and a data transmission unit that are connected in sequence by electrical connection. The embedded sensor unit includes multiple intelligent sensing geopolymer concrete sensors; The signal excitation and acquisition unit includes a constant voltage source, a current amplifier, and a charge amplifier connected in parallel. The constant voltage source is used to apply a DC excitation voltage of no more than 3V to the distributed monitoring electrode array. The current amplifier is used to acquire the loop current signal caused by the change in the conductive network of the carbon nanotube. The charge amplifier is used to acquire the piezoelectric charge signal generated by the stress on the lead zirconate titanate piezoelectric particles. The data processing and damage diagnosis unit receives current and charge signals from the signal excitation and acquisition unit, analyzes the signal change patterns based on the resistance tomography algorithm and piezoelectric sensor signal processing technology, identifies the stress-strain state, locates the damage location, assesses the degree of damage, and triggers an early warning signal. The data transmission unit transmits the processed data and early warning information to the remote monitoring center; The operating frequency of the monitoring system can be adjusted from once per second to once per day. The data processing and damage diagnosis unit analyzes the signal path and its variation characteristics of the distributed monitoring electrode array to achieve distributed mapping of stress-strain field and damage within the sensor coverage area. The relationship between the degree of damage (crack width) and the signal change pattern and early warning is as follows: (I) Normal state / no damage: The resistivity of the monitored area changes steadily without sudden increase, and the piezoelectric signal amplitude does not attenuate. The structure is judged to be normal, and there is no early warning; (II) Level 1 early warning: When the resistivity of the monitored area increases suddenly in the range of (20%~80%), and the attenuation rate of the piezoelectric signal amplitude is in the range of (10%~30%), microcracks with a width of <0.05mm are generated inside the concrete. The system judges this as microscopic damage and crack initiation, triggering a Level 1 early warning, prompting increased attention and daily inspections; (III) Level 2 early warning: When the resistivity of the monitored area increases suddenly in the range of [80%~150%), and the attenuation rate of the piezoelectric signal amplitude is in the range of [30%~60%), the crack width is ≥0.05mm and <0.2mm, triggering a Level 2 early warning, indicating early visible cracks and obvious damage, requiring on-site professional testing; (IV) Level 3 warning: When the resistivity of the monitored area suddenly increases by ≥150% or shows an open circuit state, and the attenuation rate of the piezoelectric signal amplitude is ≥60%, the corresponding crack width is ≥0.2mm, reaching the crack limit of general concrete structure specifications, triggering a Level 3 warning, indicating that the structure is seriously damaged, there are macro cracks, the safety risk is high, and reinforcement and repair measures must be taken immediately.

[0034] 4. Performance Verification Testing The sensor prepared in this embodiment was subjected to standard operating condition performance testing, and the results are as follows: ① Microcrack identification performance: Under a crack with a width of 0.05 mm, the measured average resistance change rate is 85.1%, which meets the design requirement of ≥80%; it has a stable linear response to static strain of 10 με level and dynamic stress of 0.1 MPa level, with linear correlation coefficients of 0.991 and 0.994, respectively. ② Long-term stability performance: Under temperature fluctuations of -20℃ to 80℃ and high humidity of 95%RH, the signal baseline drift rate after one year of service is 2.38%, which meets the design requirement of ≤3% / year; ③ Interface compatibility performance: The average 28-day interfacial shear bond strength with C40 ordinary concrete is 3.05 MPa, which meets the design requirement of ≥2.5 MPa.

Claims

1. A smart sensing sensor for geopolymer concrete, characterized in that: It includes a geopolymer concrete body and a distributed monitoring electrode array disposed within the geopolymer concrete body; The total weight of the geopolymer concrete body, calculated as 100%, consists of the following raw materials by weight: 40%~45% geopolymer cementitious material, 25%~30% fine aggregate, 15%~20% coarse aggregate, 0.8%~1.2% carbon nanotubes, 3%~5% lead zirconate titanate piezoelectric particles, 0.4%~0.6% polycarboxylic acid dispersant, 2%~4% ultrafine silica fume, 0.1%~0.2% organosilicon defoamer, and the balance being deionized water.

2. The intelligent sensing geopolymer concrete sensor according to claim 1, characterized in that: The geopolymer cementitious material is made by mixing metakaolin powder and alkali activator at a mass ratio of 1:(0.6~1.0).

3. The intelligent sensing geopolymer concrete sensor according to claim 2, characterized in that: The specific surface area of the metakaolin powder is 400-500 m 2 / kg, wherein the content of SiO2 and Al2O3 is > 85%; the alkali activator is a water glass solution with a modulus of 3.2 and a solid content of 38%-40%.

4. The intelligent sensing geopolymer concrete sensor according to claim 1, characterized in that: The carbon nanotubes are multi-walled carbon nanotubes with a diameter of 10-20 nm, a length of 5-10 μm, and a carboxyl functional group content of 0.5%-1.0% by mass; the lead zirconate titanate piezoelectric particles have an average particle size of 50-100 μm and a piezoelectric constant d. 33 ≥450pC / N, Curie temperature ≥350℃.

5. The intelligent sensing geopolymer concrete sensor according to claim 1, characterized in that: The polycarboxylate-based high-efficiency dispersant has a solid content of 40%~45% and a pH value of 7~8.

6. The intelligent sensing geopolymer concrete sensor according to claim 1, characterized in that: The fine aggregate is natural sand with a particle size ≤ 5mm, and the coarse aggregate is crushed stone with a particle size of 5~10mm.

7. The intelligent sensing geopolymer concrete sensor according to claim 1, characterized in that: The distributed monitoring electrode array consists of multiple pairs of copper-plated metal electrodes arranged at intervals.

8. The method for preparing the intelligent sensing geopolymer concrete sensor according to claim 1, characterized in that: Includes the following steps: Step S1. Add deionized water and polycarboxylic acid dispersant to a mixer and stir at 800~1000 r / min for 3~5 min; then add carbon nanotubes and continue stirring and dispersing at 2000~2500 r / min for 20~30 min to obtain conductive slurry; Step S2. Add geopolymer cementitious material, fine aggregate, coarse aggregate, and ultrafine silica fume sequentially to the conductive slurry, and stir at 1500~1800 r / min for 10-15 min to form a concrete matrix; Step S3. Add lead zirconate titanate piezoelectric particles to the concrete matrix and stir at 1200~1500 r / min for 8~12 min; finally add organosilicon defoamer and stir at 800~1000 r / min for 5~8 min to obtain sensor slurry; Step S4. Pour the sensor slurry into a mold, insert the distributed monitoring electrode array, compact it by vibration, and cure it for 24 hours at 20±2℃ and relative humidity ≥95% to form a prefabricated sensor unit; or directly pour the sensor slurry into a designated position on the concrete structure to be monitored, simultaneously insert the distributed monitoring electrode array, compact it by vibration, and then perform standard curing simultaneously with the concrete structure to be monitored to form a direct sensor unit. Step S5. Apply a polarized electric field to the prefabricated sensor unit or the direct sensor unit to perform polarization processing, thereby obtaining the intelligent sensing geopolymer concrete sensor.

9. The method for preparing the intelligent sensing geopolymer concrete sensor according to claim 8, characterized in that: The electric field strength of the polarization treatment is 2~3kV / mm, the polarization temperature is 80~100℃, and the polarization time is 30~60min; the curing is drying at 90℃~95℃ for 25~30min; the standard curing conditions are temperature 20±2℃, relative humidity ≥95%, and curing age ≥28d.

10. A monitoring system based on the intelligent sensing geopolymer concrete sensor of claim 1, characterized in that: It includes an embedded sensor unit, a signal excitation and acquisition unit, a data processing and damage diagnosis unit, and a data transmission unit connected in sequence; The embedded sensor unit includes at least one intelligent sensing geopolymer concrete sensor, which is installed at the point to be monitored. The signal excitation and acquisition unit includes a constant voltage source, a current amplifier, and a charge amplifier connected in parallel. The constant voltage source is used to apply an excitation voltage of no more than 3V to the distributed monitoring electrode array. The current amplifier is used to acquire the loop current signal caused by the change in the conductive network of the carbon nanotube. The charge amplifier is used to acquire the piezoelectric charge signal generated by the stress on the lead zirconate titanate piezoelectric particles. The data processing and damage diagnosis unit receives current and charge signals from the signal excitation and acquisition unit, analyzes the signal change patterns based on the resistance tomography algorithm and piezoelectric sensor signal processing technology, completes stress-strain state identification, damage location positioning, damage degree assessment, and triggers an early warning signal when the signal characteristics exceed a preset threshold. The data transmission unit wirelessly transmits the processed stress-strain data, damage information, and early warning signals to the remote monitoring center.

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