Intelligent permeation grouting process and device for concrete crack self-repairing material

Abstract

The invention relates to an intelligent permeation grouting process and device for concrete crack self-repairing. The intelligent permeation grouting process and device are suitable for crack detection and repairing of a newly-built concrete structure. The device comprises a blood vessel network embedded into concrete, a crack detection sensor, a control module, a pumping module and a self-repairing material storage module, and automatic detection and repairing of cracks are achieved. The technological process comprises crack detection, data analysis, grouting parameter determination, material injection and repair monitoring. Through the automation and intelligence technology, the repairing efficiency and precision are remarkably improved, and the device is suitable for large structures such as bridges and tunnels.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine technology, and in particular to an intelligent penetration grouting process and device for concrete crack self-repairing materials. Background Art

[0002] Concrete is widely used in infrastructure such as buildings, bridges, and tunnels due to its high strength and low cost. However, concrete is susceptible to cracks when exposed to mechanical stress, temperature fluctuations, or chemical attack. These cracks can allow liquid or gas to penetrate, accelerating steel corrosion and reducing structural durability. Traditional repair methods, such as manual grouting or surface patching, are time-consuming and costly. They also struggle to address deep or small cracks, require frequent manual inspections, and are inefficient.

[0003] In recent years, self-healing concrete technology, which enables autonomous repair through embedded microcapsules or vascular networks, has shown potential for extending the lifespan of structures. However, existing technologies rely on passive triggering mechanisms and lack real-time crack detection and intelligent control, limiting their efficiency and applicability. Summary of the Invention

[0004] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of this application to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions should not be used to limit the scope of the present invention.

[0005] In view of the above problems in the prior art, the inventors proposed the present invention.

[0006] Therefore, the purpose of the present invention is to overcome the deficiencies in the prior art and provide an intelligent penetration grouting process and device for concrete crack self-repairing materials.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: a device for a self-repairing material for concrete cracks, comprising: a vascular network embedded in a concrete structure, configured to deliver the self-repairing material to the crack location; a plurality of sensors embedded in the concrete structure, configured to detect the presence, location, and size of cracks; a control module in communication with the plurality of sensors, configured to receive crack detection data, analyze crack characteristics, and determine grouting parameters; a pumping module connected to the vascular network, configured to inject the self-repairing material into the vascular network according to grouting parameters; A storage module for storing self-repairing materials, wherein the self-repairing materials include a bacterial suspension and nutrients thereof.

[0008] As a preferred embodiment of the device of the concrete crack self-repairing material of the present invention, the vascular network includes hollow tetrahedral units made of 3D-printed polylactic acid (PLA), the units forming a three-dimensional network structure with a channel diameter of 3-5 mm, supporting multiple repairs.

[0009] As a preferred solution of the device of the concrete crack self-repairing material of the present invention, the multiple sensors are distributed optical fiber strain sensors with a spatial resolution of 5-10 cm and a strain measurement accuracy of ±1 microstrain, and preferably use a polyimide coating to resist the alkaline environment of concrete.

[0010] As a preferred embodiment of the device for the self-repairing material for concrete cracks of the present invention, the self-repairing material is a bacterial suspension containing Bacillus subtilis spores at a concentration of 10^8-10^9 spores / ml, and the nutrient solution includes yeast extract, urea and calcium chloride with a viscosity of 5-10 centipoise.

[0011] As a preferred solution of the device of the concrete crack self-repairing material of the present invention, the control module includes a microcontroller running a machine learning algorithm, preferably a classifier based on a support vector machine, for analyzing sensor data and predicting crack expansion trends.

[0012] As a preferred solution of the device for the concrete crack self-repairing material of the present invention, the pumping module is a two-component injection pump equipped with an online mixer, the grouting pressure is controlled at 2-5 bar, and the flow rate range is 0.1-10 ml / min.

[0013] An intelligent penetration grouting process for concrete crack self-repairing materials, which includes: using embedded sensors to detect cracks in concrete structures; Analyze crack detection data to determine the location, width and depth of cracks; Determine grouting parameters based on crack analysis results, including the volume of self-repairing material and grouting pressure; The self-healing material is injected into the vascular network embedded in the concrete structure according to the grouting parameters; Use embedded sensors to monitor the repair process and verify crack sealing effectiveness.

[0014] As a preferred solution of the intelligent penetration grouting process of the concrete crack self-repairing material described in the present invention, detecting cracks includes using an optical fiber strain sensor to monitor strain changes and identifying anomalies exceeding three times the standard deviation of the mean through a statistical process control algorithm.

[0015] As a preferred solution of the intelligent penetration grouting process of the concrete crack self-repairing material described in the present invention, the analysis of crack detection data includes using a support vector machine algorithm to classify crack types, estimate crack width and depth, and predict crack expansion in combination with a finite element model.

[0016] As a preferred solution of the device of the concrete crack self-repairing material of the present invention, it further includes a monitoring module configured to use ultrasonic testing to verify the repair effect.

[0017] Beneficial effects of the present invention: By integrating embedded sensors and intelligent control modules, the present invention enables real-time detection and automated repair of cracks, significantly reducing manual intervention and improving repair efficiency. The design of the vascular network allows the precise delivery of self-healing materials to cracks, reducing material waste and supporting multiple repairs, thereby extending the service life of concrete structures. The use of bacteria-based self-healing materials, which metabolize to produce calcium carbonate to fill cracks, enhances the sustainability of repairs and reduces environmental impact. The present invention is particularly suitable for new concrete structures, such as bridges and tunnels, providing an efficient and economical maintenance solution for the construction industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 Schematic diagram of the device structure logic of the method of the present invention. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the embodiments of the specification.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1 This embodiment provides a device for a concrete crack self-repairing material.

[0024] Specifically, the device system includes the following modules: Vascular network: Specifically, the vascular network was manufactured using 3D printing technology and consisted of hollow tetrahedral units (TETs) made of polylactic acid (PLA), each with a side length of 50 mm, an internal channel diameter of 5 mm, and a wall thickness of 1 mm.

[0025] Preferably, tetrahedral elements are connected at nodes to form a three-dimensional network structure, which is embedded in the formwork before concrete pouring to ensure coverage of the entire bridge deck. Furthermore, the vascular network is designed as a system of independently addressable channels, allowing the self-healing material to be precisely delivered to the crack location.

[0026] As an implementation, PLA was chosen for its biodegradability and compatibility with concrete. The channel wall thickness can be adjusted to 0.5-2 mm depending on the structural requirements. Alternatively, the vascular network can be constructed using other polymer materials, such as acrylonitrile butadiene styrene (ABS) or nylon, to meet the needs of different environments.

[0027] Sensor module: Specifically, the sensor module uses a distributed optical fiber strain sensor, preferably an optical fiber sensor based on Brillouin optical frequency domain analysis (BOFDA), with a spatial resolution of 10 cm and a strain measurement accuracy of ±1 microstrain.

[0028] Fiber optic sensors are preferably embedded along the steel bars or concrete matrix to a depth of 50 mm to ensure detection of surface and internal cracks. Furthermore, 4-6 sensor points are arranged per square meter of concrete to cover key stress-bearing areas, such as the mid-span and support areas of the bridge deck.

[0029] In one embodiment, the fiber optic sensor uses a polyimide coating to withstand the highly alkaline environment of concrete. Alternatively, a fiber Bragg grating (FBG) sensor or an acoustic emission sensor can be used to meet different detection requirements. The sensor is connected to a data acquisition unit via a fiber optic multiplexer, transmitting real-time strain data to the control module.

[0030] Control module: Specifically, the control module is an industrial computer based on a quad-core processor, equipped with 16GB of memory and 128GB of storage, running crack detection and grouting control software.

[0031] Preferably, the software integrates a machine learning algorithm based on a support vector machine (SVM), trained on historical strain data, to identify the presence, location, width, and depth of cracks.

[0032] Furthermore, the control module combines the finite element model to simulate the stress distribution of the bridge deck and predict the crack expansion trend.

[0033] In one embodiment, the control module connects to external devices via a wireless communication interface (such as Wi-Fi or 4G) to support remote monitoring and data logging. Alternatively, a field programmable gate array (FPGA) can be used as the control module to improve real-time processing speed.

[0034] Pumping module: Specifically, the pumping module uses a two-component syringe pump system, with each syringe storing the bacterial suspension and nutrient solution, respectively, with a capacity of 500 ml. Preferably, the pumping module is a peristaltic pump that can provide a flow rate of 0.1 to 10 ml / min, and the grouting pressure is controlled at 2-5 bar.

[0035] Furthermore, the pumping module is equipped with an in-line mixer to ensure that the bacteria and nutrient solution are fully mixed before injection, thereby improving the remediation efficiency.

[0036] As an implementation, the pumping system monitors the grouting pressure in real time via a pressure sensor to prevent overpressure from causing crack expansion. Alternatively, a single-component pumping system can be used, which is suitable for fast-curing polymer materials.

[0037] Storage Module: Specifically, the storage module includes two 10-liter refrigerated tanks, one for storing a bacterial suspension and the other for storing a nutrient solution. The temperature is maintained at 4°C to maintain bacterial activity. Preferably, the bacterial suspension contains Bacillus subtilis spores at a concentration of 10^9 spores / mL suspended in phosphate buffered saline (PBS). The nutrient solution contains 20 g / L yeast extract, 50 g / L urea, and 100 g / L calcium chloride, with a viscosity controlled to 5-10 centipoise (cP).

[0038] Furthermore, the tanks are equipped with level sensors and automatic replenishment systems, connected to external bulk storage to ensure a continuous supply of materials.

[0039] As an implementation method, a single tank can be used to store pre-mixed self-healing materials, simplifying system design.

[0040] System integration and operation: Specifically, before concrete pouring, the vascular network and sensors are embedded in the formwork. After pouring, the system is calibrated and the initial strain data is recorded.

[0041] When running, the system operates as follows: Crack Detection: Embedded sensors continuously monitor the strain distribution in the concrete structure with a sampling frequency of 1 Hz. When cracks larger than 0.2 mm are detected, the data is transmitted to the control module.

[0042] Data analysis: The control module uses a support vector machine algorithm to analyze sensor data to determine the location, width, and depth of cracks and predict crack growth trends.

[0043] Grouting parameter determination: Based on the crack characteristics, the control module calculates the grouting volume (formula: V = L × W × D × k, where k is 1.2) and pressure (2-4 bar).

[0044] Material injection: The pumping module injects self-healing materials into the cracks through the vascular network. Bacteria metabolize in the cracks to produce calcium carbonate, which seals the cracks.

[0045] Repair monitoring: Sensors continuously monitor strain changes in the repair area to verify the repair effect and trigger secondary grouting when necessary.

[0046] Preferably, the system supports multiple repairs, allowing for the reuse of the vascular network. Furthermore, ultrasonic testing can be combined to verify the integrity of the repair. The advantages of this embodiment lie in its high degree of integration and automation, making it suitable for the construction of large structures such as new bridges and tunnels, significantly extending their service life and reducing maintenance costs.

[0047] Example 2 This embodiment provides an intelligent penetration grouting process and device for concrete crack self-repairing material, specifically, an intelligent penetration grouting process flow.

[0048] In this embodiment, the process of the intelligent penetration grouting process is described, which is suitable for crack repair of embedded device systems.

[0049] Step 1: Crack Detection Specifically, embedded fiber optic strain sensors continuously monitor the strain distribution in the concrete structure at a sampling frequency of 1 Hz. Preferably, a sliding average filter is used to process the data to reduce noise. Furthermore, an anomaly detection algorithm based on statistical process control identifies strain readings exceeding three standard deviations from the mean, indicating potential crack formation.

[0050] As an implementation method, sensor data is transmitted to a control module via a wireless network to record strain anomalies in real time. Alternatively, an acoustic emission sensor can be used to detect acoustic wave signals generated by crack formation to enhance detection sensitivity.

[0051] Step 2: Data Analysis Specifically, when an anomaly is detected, the control module activates a support vector machine-based classifier to confirm the presence of cracks and estimate their characteristics. Preferably, the classifier uses features such as peak strain amplitude, strain gradient, and spatial correlation to output the probability of crack presence, width, and location. Furthermore, the control module incorporates a regression model to estimate crack depth and propagation trends, ensuring the accuracy of grouting parameters. As an implementation, data analysis can utilize a convolutional neural network (CNN) to process multidimensional sensor data to improve crack identification accuracy.

[0052] Step 3: Determination of grouting parameters Specifically, based on the crack analysis results, the control module calculates the grouting volume and pressure. Preferably, the grouting volume is calculated using the formula: V = L × W × D × k, where V is the grouting volume, L is the crack length, W is the crack width, D is the crack depth, and k is the safety factor (typically 1.2). Furthermore, for cracks wider than 0.5 mm, the grouting pressure is set at 2-4 bar, and the water-cement ratio of the bacterial suspension is 0.4-0.5. As an embodiment, the pressure can be adjusted based on the crack depth, increasing to 5 bar for depths greater than 50 mm.

[0053] Step 4: Material Injection Specifically, the control module selects an injection point in the vascular network near the crack location and activates the pumping module to inject the self-healing material according to calculated parameters. Preferably, a two-component pump mixes the bacterial suspension and nutrient solution using a static mixer before injection. Furthermore, the injection process continues until the crack is filled or the repair agent overflows from adjacent channels. Pressure sensors monitor the process in real time to prevent overpressure. As an implementation, a phased injection strategy can be employed to enhance material permeability.

[0054] Step 5: Repair monitoring Specifically, after the injection is complete, sensors continuously monitor strain changes in the crack area to verify the repair's effectiveness. Preferably, monitoring continues for 14 days after the repair to ensure complete calcium carbonate deposition. Furthermore, if the strain data does not return to normal, the system can trigger a second injection. As an implementation option, ultrasonic testing or X-ray tomography can be performed periodically to verify the integrity of the repair.

[0055] This embodiment achieves efficient and accurate crack repair through an automated process, reduces manual intervention, and improves repair quality.

[0056] Example 3 This embodiment provides an application of an intelligent penetration grouting process and device for concrete crack self-repairing materials in bridge engineering.

[0057] In this embodiment, the specific application of the intelligent permeation grouting system in a new bridge project is described. Specifically, the bridge is a prestressed concrete T-beam bridge with a total length of 200 meters, a span of 30 meters, and a bridge deck width of 10 meters.

[0058] System Installation: Before the bridge concrete is poured, the vascular network and sensor modules are laid out on the formwork. Specifically, the vascular network consists of 3D-printed PLA tetrahedral units, each with a 50 mm side, a 5 mm channel diameter, and a 1 mm wall thickness. The units are connected at nodes to form a grid-like structure that covers the entire bridge deck. The optimal density of the vascular network is 100 units per cubic meter of concrete to ensure coverage of all potential crack locations.

[0059] The sensor modules use distributed fiber optic strain sensors, arranged along the length of the bridge deck, with one measurement point every three meters, for a total of 60 points. The fiber optic sensors are buried to a depth of 50 mm to ensure detection of both surface and internal cracks.

[0060] The control module, installed in the bridge's management center, utilizes an industrial-grade computer with redundant power supplies and backup systems to ensure 24 / 7 operation. The pumping and storage modules are located in an equipment room near the bridge. The storage module holds 50 liters of bacterial suspension and nutrient solution, sufficient for multiple repairs.

[0061] Operational Process: After the bridge was commissioned, the system began real-time monitoring. It detected a crack in the bridge deck mid-span. Strain data indicated a crack width of approximately 0.3 mm and a depth of 10 mm. The control module analyzed the data and determined a grouting volume of 5 ml at a pressure of 3 bar.

[0062] The pumping module activates, injecting the bacterial suspension into the vascular network. The material flows through the channels to the fracture location. After the grouting is completed, the system monitors the strain changes in the fracture area through sensors to confirm that the fracture has been sealed.

[0063] Furthermore, 14 days after the repair, ultrasonic testing confirmed that the cracks had completely healed and the concrete's strength had recovered to 95% of its original strength. Furthermore, compared to traditional manual grouting methods, this system shortened repair time by 50% and reduced material usage by 30%, significantly improving efficiency and cost-effectiveness.

[0064] The present invention realizes real-time detection and precise repair of concrete cracks through an embedded intelligent penetration grouting system and an automated process flow. Example 1 describes in detail the hardware composition of the system and its integration method, and realizes fully automatic repair through an embedded vascular network and sensors, which is suitable for large structures such as newly built bridges and tunnels. Example 2 explains each step of the process flow, emphasizing the coordinated work of automated detection, analysis and grouting to ensure repair efficiency and quality. Example 3 demonstrates the successful application of the present invention in actual bridge engineering, provides specific data and comparisons, and verifies its reliability and superiority.

[0065] This invention significantly improves repair efficiency and precision by combining 3D printing technology, embedded sensors, and automated control. The use of bacteria-based self-healing materials further enhances the sustainability of repairs, reduces environmental impact, and provides an innovative maintenance solution for the construction industry.

[0066] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A device for self-repairing concrete cracks, characterized by: include a network of blood vessels embedded in the concrete structure, configured to deliver self-healing materials to the crack location; a plurality of sensors embedded in the concrete structure, configured to detect the presence, location, and size of cracks; a control module in communication with the plurality of sensors, configured to receive crack detection data, analyze crack characteristics, and determine grouting parameters; a pumping module connected to the vascular network, configured to inject the self-repairing material into the vascular network according to grouting parameters; A storage module for storing self-repairing materials, wherein the self-repairing materials include a bacterial suspension and nutrients thereof.

2. The device of concrete crack self-repairing material according to claim 1, characterized in that: The vascular network includes hollow tetrahedral units made of 3D-printed polylactic acid (PLA), which form a three-dimensional mesh structure with channel diameters of 3-5 mm, supporting multiple repairs.

3. The device of concrete crack self-repairing material according to claim 1, characterized in that: The multiple sensors are distributed optical fiber strain sensors with a spatial resolution of 5-10 cm and a strain measurement accuracy of ±1 microstrain. They are preferably coated with polyimide to resist the alkaline environment of concrete.

4. The device of concrete crack self-repairing material according to claim 1, characterized in that: The self-repairing material is a bacterial suspension containing Bacillus subtilis spores with a concentration of 10^8-10^9 spores / ml. The nutrient solution includes yeast extract, urea and calcium chloride with a viscosity of 5-10 centipoise.

5. The device of concrete crack self-repairing material according to claim 1, characterized in that: The control module includes a microcontroller that runs a machine learning algorithm and uses a classifier based on a support vector machine to analyze sensor data and predict crack growth trends.

6. The device of concrete crack self-repairing material according to claim 1, characterized in that: The pumping module is a two-component injection pump equipped with an online mixer. The grouting pressure is controlled at 2-5 bar and the flow rate range is 0.1-10 ml / min.

7. The intelligent penetration grouting process of the concrete crack self-repairing material according to any one of claims 1 to 6, characterized in that: The steps include: Detect cracks in concrete structures using embedded sensors; Analyze crack detection data to determine the location, width and depth of cracks; Determine grouting parameters based on crack analysis results, including the volume of self-repairing material and grouting pressure; The self-healing material is injected into the vascular network embedded in the concrete structure according to the grouting parameters; Use embedded sensors to monitor the repair process and verify crack sealing effectiveness.

8. The intelligent penetration grouting process of the concrete crack self-repairing material according to claim 7, characterized in that: Detecting cracks involves monitoring strain changes using fiber-optic strain sensors and identifying anomalies exceeding three standard deviations from the mean using statistical process control algorithms.

9. The intelligent penetration grouting process of the concrete crack self-repairing material according to claim 7, characterized in that: Analyzing the crack detection data involves classifying the crack type using a support vector machine algorithm, estimating crack width and depth, and predicting crack growth in conjunction with a finite element model.

10. The device of concrete crack self-repairing material according to claim 1, characterized in that: Also included is a monitoring module configured to verify the effectiveness of the repair using ultrasonic testing.

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