Concrete crack deep deformation wireless monitoring system and monitoring method

Abstract

This invention provides a wireless monitoring system for deep deformation of concrete cracks, belonging to the field of civil engineering structural health monitoring technology. It includes a built-in passive sensing unit, an external wireless detection unit, and a cloud-based data analysis and inversion platform. The built-in passive sensing unit comprises a ferromagnetic sensing metal strip and a positioning structure. The external wireless detection unit includes a signal transmitting module. The cloud-based data analysis and inversion platform includes a signal receiving module and a main control processor. The signal transmitting module transmits electromagnetic wave signals to the concrete structure. This invention directly senses deep deformation of cracks through the embedded metal strip, rather than relying on surface inference or passively receiving weak signals. The metal strip and concrete deform in tandem, accurately reflecting the true deformation of cracks at depth, overcoming the limitations of traditional technologies that can only perform surface measurements or depth estimations. This invention also relates to a monitoring method for this wireless monitoring system for deep deformation of concrete cracks.

Description

Technical Field

[0001] This invention relates to the field of structural health monitoring technology in civil engineering, and more specifically, to a wireless monitoring system for deep deformation of concrete cracks based on multi-directional collaborative sensing, adaptable to both new and existing concrete structures. This invention also relates to a monitoring method for this wireless monitoring system for deep deformation of concrete cracks. Background Technology

[0002] Concrete cracks are a key indicator for assessing structural safety and durability. In tunnels, underground caverns, and other engineering projects, deep cracks in the lining concrete are highly concealed and have complex development mechanisms, making them a core source of risk threatening structural safety. In particular, monitoring internal cracks in existing structures is even more difficult.

[0003] Existing monitoring technologies, such as optical observation, ultrasonic methods, and impact echo methods, are mostly limited to surface measurement or depth estimation. They have inherent limitations, such as accuracy being greatly affected by material inhomogeneity, difficulty in achieving long-term automated monitoring, and the inability to capture three-dimensional deformation information deep within cracks. Traditional electromagnetic methods suffer from weak signals and low signal-to-noise ratios due to the dielectric properties of concrete, making it difficult to accurately capture deep crack deformation. Therefore, developing a technology that can accurately, continuously, and automatically monitor the three-dimensional propagation of deep concrete cracks has significant engineering value.

[0004] In recent years, monitoring technologies based on electromagnetic principles have been developed due to their advantages such as non-destructiveness and long-term monitoring capability, but they still have many limitations:

[0005] 1) The Chinese patent "An Automatic Monitoring System for Cracks in Concrete Structures" (application number: 202411849232.4) includes an electromagnetic monitoring module, an image acquisition module, a protection module, and a cleaning module. The system can monitor the maximum or minimum value of crack changes over a long period of time by using the slider of the image acquisition module. However, this patent is essentially still focused on surface monitoring. Its electromagnetic module is mainly used to trigger image acquisition and does not involve the accurate measurement of deep deformation inside the concrete. Its monitoring depth and accuracy are limited, and the system structure is complex. Moving parts are easily damaged in long-term outdoor environments.

[0006] 2) The Chinese patent "An Electromagnetic Monitoring System and Method for Active Cracks in Concrete Dams" (application number: 202211735567.4) monitors and locates active cracks by collecting and identifying the inherent electromagnetic radiation signals generated by active cracks in concrete dams. This patent is a passive receiving monitoring method that relies on the signals generated by the crack activity itself. Its signal strength is weak, the signal-to-noise ratio is low, and it is easily affected by environmental electromagnetic interference. It has poor monitoring effect on inactive cracks or micro-cracks and it is difficult to accurately quantify the depth and three-dimensional morphology of cracks.

[0007] 3) The Chinese patent "A Method and Apparatus for Judging the Trend of the Tip of a Concrete Diagonal Crack" (application number: 202310208701.3) fills the crack to be tested with metal powder, and then uses an electromagnetic wave radar detector to detect it from different angles and measuring lines. The trend of the crack tip is judged by identifying the fluctuation points of the reflected waves of the metal powder. This patent requires intervention on the existing crack, which changes the physical state of the crack itself. Moreover, the uniformity of the powder filling is difficult to guarantee, which affects the accuracy of the measurement. It cannot achieve long-term, continuous automated monitoring and is only suitable for one-time detection.

[0008] In summary, existing electromagnetic-based monitoring technologies for monitoring internal deformation in concrete suffer from limitations such as limited monitoring depth, low signal-to-noise ratio, susceptibility to interference, need for intervention in crack conditions, and difficulty in long-term automated monitoring. Therefore, there is an urgent need for a multi-directional monitoring solution that eliminates the need for drilling in new pre-embedded structures, facilitates operation of existing boreholes, provides long-range and stable wireless transmission, and enables intelligent data application. This solution aims to address the problems of poor scenario adaptability, weak wireless performance, and imbalance between accuracy and practicality in existing technologies. Summary of the Invention

[0009] The primary objective of this invention is to overcome the deficiencies of the aforementioned background technology and to provide a wireless monitoring system for deep deformation of concrete cracks.

[0010] The second objective of this invention is to provide a monitoring method for this wireless monitoring system for deep deformation of concrete cracks.

[0011] To achieve the aforementioned first objective, the technical solution of the present invention is: a wireless monitoring system for deep deformation of concrete cracks, characterized in that: it includes a built-in passive sensing unit, an external wireless detection unit, and a cloud-based data analysis and inversion platform; the built-in passive sensing unit includes a ferromagnetic sensing metal strip and a positioning structure; the ferromagnetic sensing metal strip is embedded inside the concrete structure through the positioning structure, forming a cooperative deformation relationship with the concrete;

[0012] The external wireless detection unit includes a signal transmitting module; the cloud-based data analysis and inversion platform includes a signal receiving module and a main control processor; the signal transmitting module transmits electromagnetic wave signals to the concrete structure; the signal receiving module receives the echo signals reflected by the ferromagnetic sensing metal strip; the main control processor filters, amplifies, and performs analog-to-digital conversion on the echo signals, and transmits the processed data to the cloud-based data analysis and inversion platform.

[0013] In the above technical solution, the built-in passive sensing unit is divided into a new structure pre-embedded type and an existing structure drilled type.

[0014] When the built-in passive sensing unit is a pre-embedded type in the new structure, the positioning structure is a three-dimensional orthogonal positioning bracket; the three-dimensional orthogonal positioning bracket is a cross-shaped frame, and the three-dimensional orthogonal positioning bracket is provided with metal strip positioning slots in the X, Y, and Z axes. The inner wall of the metal strip positioning slots is pasted with a rubber buffer layer; the ferromagnetic sensing metal strip is fixed in the metal strip positioning slots in the X, Y, and Z axes and is pre-embedded synchronously with the concrete pouring;

[0015] When the built-in passive sensing unit is an existing structure drilled type, the positioning structure is a three-dimensional orthogonal channel group; the three-dimensional orthogonal channel group is formed by drilling with a core drill with an angle positioner, and the three-dimensional orthogonal channel group contains 3 channels, arranged along the X, Y and Z axes; after the ferromagnetic sensing metal strip is implanted into the channel of the three-dimensional orthogonal channel group, high-performance non-shrink grout is backfilled using a segmented pressure grouting process.

[0016] In the above technical solution, the ferromagnetic sensing metal strip is made of low-carbon steel, galvanized steel or iron-chromium-aluminum alloy, with a relative magnetic permeability of not less than 500, and the cross-section of the ferromagnetic sensing metal strip is circular, rectangular or irregularly shaped with periodic markings.

[0017] In the above technical solution, the segmented pressure grouting process is as follows: The grouting pipe is inserted from the bottom of the trench, with the pipe opening 100mm from the bottom of the trench; a high-performance non-shrink grouting material is injected at a certain pressure using a grouting pump; the segmented pressure grouting process is adopted, with pauses in stages during grouting to check the filling condition. After checking for voids, the grouting pipe continues to be pushed upwards; after grout overflows from the top of the trench, the pressure is maintained for 30 seconds, the grouting valve is closed, and curing is carried out for 7-14 days.

[0018] In the above technical solution, the signal transmission module transmits electromagnetic wave signals of a specific frequency and supports frequency modulated continuous wave (FMCW) mode and pulse radar mode.

[0019] In the above technical solution, the cloud-based data analysis and inversion platform includes a data storage module, an algorithm operation module, and an early warning module;

[0020] The algorithm operation module has built-in differential calculation algorithm and multi-source signal fusion algorithm. By extracting the arrival time difference, phase shift and amplitude attenuation characteristic parameters of the echo signal, it solves the three-dimensional deformation data of the crack based on the calibration mathematical model.

[0021] The early warning module triggers an early warning when the deformation data exceeds a preset crack deformation threshold.

[0022] To achieve the second objective mentioned above, the technical solution of the present invention is: a monitoring method for a wireless monitoring system for deep deformation of concrete cracks, characterized by comprising the following steps:

[0023] Step 1: Select the built-in passive sensing unit according to the type of concrete structure. For new structures, use the new structure pre-embedded type; for existing structures, use the existing structure drilled type.

[0024] Step 2: After the built-in passive sensing unit is installed, the external wireless detection unit is activated, and the signal transmitting module transmits electromagnetic wave signals to the concrete structure; the signal receiving module receives the echo signals reflected by the ferromagnetic sensing metal strip; a wireless monitoring baseline database is established.

[0025] Step 3: According to the set monitoring cycle, the external wireless detection unit automatically emits electromagnetic waves and receives the reflected echoes. After signal processing, the signals are sent to the cloud data analysis and inversion platform through the wireless transmission module.

[0026] Step 4: The cloud-based data analysis and inversion platform compares the current echo signal with the baseline signal, extracts the changes in characteristic parameters, calculates the deformation of the ferromagnetic sensing metal strip based on the experimentally calibrated mathematical model, and inverts the depth, width, and three-dimensional extension morphology of the crack.

[0027] Step 5: When the crack deformation data exceeds the preset threshold, the system will automatically trigger an early warning.

[0028] In the above technical solution, the mathematical model calibrated in step 4 is as follows:

[0029] Prepare standard specimens with the same mix proportions as the engineering concrete, and pre-embed or drill holes to implant three-dimensional orthogonal ferromagnetic sensing metal strips according to the actual engineering method.

[0030] A universal testing machine was used to apply a three-point bending load to the specimen to simulate multi-directional crack propagation, and a high-precision displacement sensor was used to measure the deformation of the ferromagnetic sensing metal strip simultaneously.

[0031] Multi-directional echo signals under different loads were collected, the correspondence between characteristic parameters and the deformation of ferromagnetic sensing metal strips was fitted, calibration coefficients were determined, and a calibration database was established.

[0032] In the above technical solution, in step 3, the signal processing specifically includes: performing low-pass filtering and high-pass filtering on the echo signal in sequence; amplifying and performing 16-bit analog-to-digital conversion on the filtered signal; packaging the processed data with the synchronously acquired environmental parameters, and encrypting and sending them to the cloud data analysis and inversion platform through the wireless transmission module.

[0033] In the above technical solution, in step 4, after receiving wireless data, the cloud data analysis and inversion platform automatically corrects for environmental influences; compares the current multi-directional echo signals with the baseline signals, and extracts the arrival time difference, phase shift, and amplitude attenuation characteristic parameters of each direction;

[0034] Substituting into the coupled mathematical model, the deformation of the multi-directional ferromagnetic sensing metal strip is calculated using a multi-source signal fusion algorithm; based on the synergistic relationship between the deformation of the ferromagnetic sensing metal strip and the concrete cracks, the depth, width, and three-dimensional propagation trajectory of the cracks are inverted.

[0035] Compared with the prior art, the present invention has the following advantages.

[0036] 1) Precise Depth Measurement: This invention directly senses deep deformation of cracks through an embedded metal strip, rather than relying on surface inference or passively receiving weak signals. The metal strip and concrete deform in tandem, accurately reflecting the true deformation of cracks at depth, overcoming the limitations of traditional technologies that can only perform surface measurements or depth estimations.

[0037] 2) High signal-to-noise ratio and anti-interference capability: The metal strip is a good electromagnetic wave reflector with a relative permeability much greater than 1, which greatly enhances the signal strength. The system adopts a multi-frequency scanning function to distinguish the echo of the preset metal strip from the environmental interference signal by the reflection difference of signals of different frequencies. Combined with the differential calculation algorithm, the static background interference is eliminated, which effectively overcomes the problems of signal attenuation and noise interference in concrete medium.

[0038] 3) Long-term stability and durability: The sensing unit of this invention is embedded in concrete, which is less affected by external environmental interference. The metal material is corrosion resistant and suitable for long-term monitoring.

[0039] 4) Strong adaptability to different scenarios: New structures do not require drilling, and precise positioning is achieved through pre-embedded brackets to avoid structural damage and improve construction efficiency; Existing structures use conventional core drilling machines + angle positioners, which do not require special equipment, and construction personnel can operate them after simple training, with a drilling qualification rate of ≥95%.

[0040] 5) Three-dimensional deformation monitoring capability: This invention can deploy multiple embedded sensing units to form a distributed monitoring network, and the channel direction of each unit can be arranged in multiple dimensions according to the potential crack direction. By analyzing various characteristic parameters of the echo signal, the deformation distribution of the crack along the depth direction can be obtained, clearly depicting its three-dimensional expansion morphology.

[0041] 6) Real-time automated monitoring: This invention supports long-term, continuous, and automated data acquisition and analysis; it can automatically transmit and receive signals according to a set cycle, perform data processing, inversion, and result output, and automatically trigger an early warning signal when the crack deformation exceeds the limit, without the need for manual intervention, thus improving monitoring efficiency and timeliness.

[0042] 7) Structural compatibility and measurement authenticity: This invention ensures that the deformation of the sensing unit and the parent structure is consistent under stress by backfilling the drill holes with materials that match the mechanical properties of the original structure. This fundamentally guarantees the authenticity and reliability of the monitoring data and avoids stress shielding or measurement errors caused by mismatch in the properties of the filling materials.

[0043] 8) Flexible deployment and wide applicability: The channel of this invention is mainly installed after drilling, which causes little damage to the structure. It is particularly suitable for non-destructive monitoring and long-term health diagnosis of existing concrete structures. It can also be used for pre-embedding in the pouring of new structures. The sensing units can be flexibly deployed according to the characteristics of different engineering structures and potential crack patterns. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the present invention.

[0045] Figure 2 This is a structural diagram for a newly constructed structure with a pre-embedded positioning structure.

[0046] Figure 3 Diagram showing the connection relationship between the metal strip positioning slot and the ferromagnetic sensing metal strip.

[0047] Figure 4 This is a detailed cross-sectional view of the built-in passive sensing unit.

[0048] Figure 5 This is a schematic diagram of the electromagnetic reflection measurement principle (comparison of echoes in normal and cracked states).

[0049] Figure 6 This is a flowchart of signal processing and data inversion.

[0050] Figure 7 This is a layout diagram for Example 1.

[0051] Figure 8 This is a flowchart of Example 1.

[0052] Figure 9 This is a layout diagram for Example 2.

[0053] Figure 10 This is a flowchart of Example 2.

[0054] Figure 11 This is a layout diagram for Example 2.

[0055] Figure 12 This is a flowchart of Example 2.

[0056] Among them, 100-built-in passive sensing unit, 110-ferromagnetic sensing metal strip, 120-positioning structure, 121-three-dimensional orthogonal positioning bracket, 122-metal strip positioning slot, 123-rubber buffer layer, 200-external wireless detection unit, 210-signal transmission module, 300-cloud data analysis and inversion platform, 310-signal receiving module, 320-main control processor, 400-concrete structure, 410-concrete reinforced test beam, 420-dam block, 430-tunnel section, 510-jack. Detailed Implementation

[0057] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but these descriptions are not intended to limit the invention and are merely illustrative. The advantages of the present invention will become clearer and easier to understand through this description.

[0058] Referring to the attached drawings, the wireless monitoring system for deep deformation of concrete cracks is characterized by comprising a built-in passive sensing unit 100, an external wireless detection unit 200, and a cloud-based data analysis and inversion platform 300. The built-in passive sensing unit 100 includes a ferromagnetic sensing metal strip 110 and a positioning structure 120. The ferromagnetic sensing metal strip 110 is embedded inside the concrete structure 400 through the positioning structure 120, forming a cooperative deformation relationship with the concrete.

[0059] The external wireless detection unit 200 includes a signal transmitting module 210; the cloud data analysis and inversion platform 300 includes a signal receiving module 310 and a main control processor 320; the signal transmitting module 210 transmits electromagnetic wave signals to the concrete structure 400; the signal receiving module 310 receives the echo signal reflected by the ferromagnetic sensing metal strip 110; the main control processor 320 performs filtering, amplification, and analog-to-digital conversion processing on the echo signal, and simultaneously collects temperature and humidity environmental parameters for data correction; using 5G (high-speed scenario) technology, the processed data is transmitted to the cloud data analysis and inversion platform 300, supporting low-power mode; the cloud data analysis and inversion platform 300 has built-in differential calculation and multi-source signal fusion algorithms, compares the current signal with the baseline signal, extracts arrival time difference, phase shift, and amplitude attenuation characteristic parameters, solves the three-dimensional deformation data of the crack based on the calibration mathematical model, and triggers an over-threshold warning.

[0060] The signal transmitting module 210 is an electromagnetic wave signal generator used to transmit pulse waves or continuous waves with a frequency range between 200MHz and 3GHz to the area where the built-in passive sensing unit 100 is located, using frequency modulated continuous wave (FMCW) or pulse radar system.

[0061] The signal receiving module 310 is a high-sensitivity signal receiving module, used to accurately receive the echo signal reflected back by the ferromagnetic sensing metal strip 110.

[0062] The main control processor 320 can control the timing of signal transmission and reception, and perform amplification, filtering and analog-to-digital conversion on the received echo signal;

[0063] The external wireless detection unit 200 has a multi-frequency scanning function, which can distinguish the echo of the preset metal strip from the environmental interference signal by the difference in reflection of signals of different frequencies.

[0064] The cloud-based data analysis and inversion platform 300 runs dedicated algorithm software, with the main control processor 320 as its core. It incorporates a differential calculation algorithm that compares the current echo signal with the baseline signal acquired when the structure was healthy, eliminating static background interference. Simultaneously, by analyzing one or more characteristic parameters of the echo signal, such as arrival time, phase shift, amplitude attenuation, or frequency spectrum changes, the algorithm interprets the deformation information of the sensing metal strip, thereby inverting the deformation data of the concrete cracks (including depth, width, and three-dimensional expansion morphology).

[0065] The present invention can deploy multiple built-in passive sensing units 100. The channel direction of each built-in passive sensing unit 100 can be arranged in multiple dimensions according to the potential crack direction. The spacing between adjacent sensing units is set according to the monitoring accuracy requirements, and together they form a distributed monitoring network for capturing crack deformation in different directions.

[0066] The built-in passive sensing unit 100 is divided into two types: the type pre-embedded in new structures and the type drilled in existing structures.

[0067] When the built-in passive sensing unit 100 is a pre-embedded type in a newly constructed structure, the positioning structure 120 is a three-dimensional orthogonal positioning bracket 121; the three-dimensional orthogonal positioning bracket 121 is a cross-shaped frame, and the three-dimensional orthogonal positioning bracket 121 is provided with metal strip positioning slots 122 in the X, Y, and Z axes. A rubber buffer layer 123 is pasted on the inner wall of the metal strip positioning slots 122 to prevent the ferromagnetic sensing metal strips 110 from shifting during pouring and vibration; a concrete protective layer control block is provided at the bottom of the three-dimensional orthogonal positioning bracket 121 to ensure... The embedment depth of the ferromagnetic sensing metal strip 110 meets the design requirements; for large-volume concrete structures, connecting bars are provided between the supports to form a distributed pre-embedded array; the ferromagnetic sensing metal strip 110 is fixed in the metal strip positioning slot 122 through the fixing bolt holes 1221 in the three directions of X, Y, and Z axes, and is pre-embedded synchronously with the concrete pouring; before pouring, the position, direction, and quantity of the embedded ferromagnetic sensing metal strip 110 are determined according to the monitoring requirements, and are firmly secured to ensure that the ferromagnetic sensing metal strip 110 does not shift during the pouring process;

[0068] When the built-in passive sensing unit 100 is a pre-existing drilled structure, the positioning structure 120 is a three-dimensional orthogonal channel group. The three-dimensional orthogonal channel group is formed by drilling with a conventional core drilling machine with an angle locator (accuracy ±0.5°). The three-dimensional orthogonal channel group contains 3 channels arranged along the X, Y, and Z axes. The inner wall of the channel is coated with an epoxy-based interface agent. After the ferromagnetic sensing metal strip 110 is inserted into the channel of the three-dimensional orthogonal channel group, high-performance non-shrink grout is backfilled using a segmented pressure grouting process. The drilling diameter is larger than the diameter of the ferromagnetic sensing metal strip 110 (to reserve grouting gaps), and the drilling depth is determined according to the structural thickness. The horizontal and vertical spacing between adjacent channels is determined according to requirements. After drilling, the debris in the channel is cleaned with high-pressure air, and then the interface agent is applied to the inner wall with a brush.

[0069] For areas requiring monitoring of multidimensional deformation, built-in passive sensing units 100 should be arranged in the corresponding directions to form a sensing array, based on the expected crack direction (including horizontal and oblique cracks).

[0070] Insert the ferromagnetic sensing metal strip 110 into the channel, and backfill and compact it with fine stone concrete or high-strength non-shrink grouting material of the same grade as the original structure. During the backfilling process, use a vibrator or pressure grouting to remove voids.

[0071] The ferromagnetic sensing metal strip 110 is made of low-carbon steel, galvanized steel, or iron-chromium-aluminum alloy, with a relative magnetic permeability of not less than 500. The cross-section of the ferromagnetic sensing metal strip 110 is circular, rectangular, or irregularly shaped with periodic markings. The irregular structure can improve the recognition of electromagnetic wave reflection signals. The surface treatment of the ferromagnetic sensing metal strip 110 is as follows: in humid environments, an epoxy resin waterproof coating is applied, and in areas with high groundwater levels, a water-swellable waterproof strip is wrapped around it to ensure durability.

[0072] The segmented pressure grouting process is as follows: Insert the grouting pipe from the bottom of the trench, with the pipe opening 100mm from the bottom; inject high-performance non-shrink grout using a grouting pump at a certain pressure; employ segmented pressure grouting, pausing intermittently during the grouting process to check the filling condition. After confirming there are no voids, continue advancing the grouting pipe upwards; after grout overflows from the top of the trench, maintain pressure for 30 seconds, close the grouting valve, and allow to cure for 7-14 days.

[0073] The signal transmitting module 210 transmits electromagnetic wave signals of a specific frequency. The signal transmitting module 210 supports frequency modulated continuous wave (FMCW) mode and pulse radar mode.

[0074] The cloud-based data analysis and inversion platform 300 includes a data storage module, an algorithm operation module, and an early warning module;

[0075] The algorithm operation module has built-in differential calculation algorithm and multi-source signal fusion algorithm. By extracting the arrival time difference, phase shift and amplitude attenuation characteristic parameters of the echo signal, it solves the three-dimensional deformation data of the crack based on the calibration mathematical model.

[0076] The early warning module triggers an early warning when the deformation data exceeds a preset crack deformation threshold.

[0077] The cloud-based data analysis and inversion platform's 300 functions include:

[0078] Data reception: Real-time reception of multi-directional echo signals and environmental parameters transmitted wirelessly, supporting historical data backtracking;

[0079] Algorithm operation: Built-in weighted average multi-source signal fusion algorithm, eliminating static clutter;

[0080] Visualization output: Supports web access and generates trend curves with deformation.

[0081] Early warning function: Customizable crack deformation threshold, warning when the threshold is exceeded.

[0082] The deployment of this invention must meet the following requirements:

[0083] New structure: 100 built-in passive sensing units are arranged in a distributed array at intervals, and metal strip positioning brackets are tied and fixed to the structural steel bars to avoid displacement during pouring;

[0084] Existing structure: The built-in passive sensing unit 100 avoids the main structural ribs, and the adjacent channel groups are spaced at a certain distance to avoid mutual interference between drilling.

[0085] A monitoring method for a wireless monitoring system for deep deformation of concrete cracks, characterized by comprising the following steps:

[0086] Step 1, Pre-install the built-in passive sensing unit 100:

[0087] Based on the 400 type of concrete structure, the built-in passive sensing unit 100 is selected. For new structures, the new structure pre-embedded type is used, and for existing structures, the existing structure drilled type is used.

[0088] For newly constructed concrete structures: Before pouring, according to the division of the monitoring area, fix the three-dimensional orthogonal positioning bracket 121 inside the formwork and tie the bracket to the structural steel reinforcement; insert the ferromagnetic sensing metal strip 110 into the metal strip positioning slot 122, check the verticality and embedment depth of the ferromagnetic sensing metal strip 110, and temporarily fix it with positioning clamps; if the monitoring area is a thin-walled component, the three-dimensional orthogonal positioning bracket 121 is made of biodegradable polylactic acid plastic to avoid the steel reinforcement bracket occupying too much structural cross section;

[0089] For existing concrete structures: Use a rebar scanner to detect the position of the main reinforcement in the monitoring area, mark the areas to be avoided when drilling, and determine the center point of the channel group; install a core drill with an angle locator (positioning accuracy ±0.5°), drill holes in sequence, and clean the debris in the channel with high-pressure air after drilling. Apply epoxy interface agent evenly to the inner wall of the channel with a brush; insert a ferromagnetic sensing metal strip 110, with thick foam pads wrapped around both ends of the ferromagnetic sensing metal strip 110 to avoid direct contact with the bottom wall of the channel; backfill the grout using a segmented pressure grouting process, and cure for 7 days (14 days in humid environments); when drilling existing structures, if the structure is thick, the channel does not need to penetrate the structure, reducing the drilling difficulty.

[0090] Step 2, establish a baseline database:

[0091] After the built-in passive sensing unit 100 is installed, the external wireless detection unit 200 is activated and the transmission frequency is set to 200MHz-3GHz; the signal transmission module 210 transmits electromagnetic wave signals to the concrete structure 400; the signal receiving module 310 receives the echo signals reflected by the ferromagnetic sensing metal strip 110; the multi-directional echo signals are continuously collected for 24 hours, and the average value is taken after removing outliers as the baseline signal of the structural health status, which is then uploaded to the cloud platform for storage via a wireless link; the collected signal data is stored as the baseline signal in the baseline database of the main control processor 320;

[0092] Step 3, transmitting and receiving electromagnetic signals:

[0093] According to the set monitoring cycle, the external wireless detection unit 200 automatically emits electromagnetic waves and receives reflected echoes. During the reception process, it records parameters such as signal acquisition time, ambient temperature, and humidity in real time for subsequent data correction. After signal processing, the signal is sent to the cloud data analysis and inversion platform 300 through the wireless transmission module. The detection unit enters a low-power mode and restarts acquisition when triggered by the next monitoring cycle.

[0094] Step 4, Signal Processing and Feature Extraction:

[0095] The main control processor 320 preprocesses the received echo signal. First, it filters out high-frequency noise through a low-pass filter, then filters out low-frequency interference through a high-pass filter, and then amplifies and converts the signal from analog to digital. Subsequently, it extracts the time-domain features (time of arrival, amplitude attenuation) and frequency-domain features (phase shift, frequency spectrum change) of the processed signal.

[0096] Step 5, Data Inversion and Result Output:

[0097] The extracted signal feature parameters are compared with the corresponding parameters in the baseline database to calculate the difference value. This difference value is then substituted into a pre-defined mathematical model (which is a database or function model of the correspondence between echo signal feature parameters and the deformation of the ferromagnetic sensing metal strip 110, pre-calibrated through experiments) to calculate the deformation of the ferromagnetic sensing metal strip 110. Based on the cooperative deformation relationship between the ferromagnetic sensing metal strip 110 and concrete, the depth, width, and three-dimensional propagation trend of concrete cracks are derived. The monitoring results are then output as curves, charts, or three-dimensional models using data visualization software.

[0098] Step 6, Early Warning and Emergency Response:

[0099] The system has a preset crack deformation threshold. When the inverted crack deformation data exceeds the preset threshold, the main control processor 320 will automatically trigger an early warning signal. After receiving the warning, relevant personnel can promptly go to the site to verify and take emergency measures such as reinforcement and repair to prevent the crack from expanding further.

[0100] In step 5, the mathematical model calibrated in the experiment is:

[0101] First, in a laboratory environment, standard specimens with the same mix proportions as actual engineering concrete were fabricated. Ferromagnetic sensing metal strips 110 of different sizes were pre-embedded in the specimens. Different levels of load were applied to the specimens using a mechanical loading device to simulate the entire process of crack initiation and propagation. Second, during the loading process, the system was used to collect echo signal characteristic parameters under different loads, and a high-precision displacement sensor was used to measure the actual deformation of the ferromagnetic sensing metal strips 110. Finally, the collected characteristic parameters and the actual deformation were fitted and analyzed to establish a functional relationship between the characteristic parameters and the deformation, forming a calibration database.

[0102] In step 3, the signal processing specifically involves: performing low-pass filtering and high-pass filtering on the echo signal in sequence; amplifying and performing 16-bit analog-to-digital conversion on the filtered signal; and packaging the processed data with the synchronously acquired environmental parameters and transmitting them encrypted to the cloud data analysis and inversion platform 300 via a wireless transmission module.

[0103] In step 5, after receiving wireless data, the cloud data analysis and inversion platform 300 automatically corrects for environmental influences; compares the current multi-directional echo signal with the baseline signal, and extracts the arrival time difference, phase shift, and amplitude attenuation characteristic parameters of each direction; substitutes them into the coupled mathematical model, and combines the multi-source signal fusion algorithm to calculate the deformation of the multi-directional ferromagnetic sensing metal strip 110; based on the synergistic relationship between the deformation of the ferromagnetic sensing metal strip 110 and the concrete crack, inverts the depth, width, and three-dimensional propagation trajectory of the crack.

[0104] Example 1: Monitoring cracks in laboratory concrete beams.

[0105] To verify the system's ability to dynamically monitor the entire process of concrete cracks, from initiation to expansion and penetration, bending tests on reinforced concrete beams were conducted in the laboratory. Figure 7 and Figure 8 As shown, a reinforced concrete test beam 410 is fabricated. In the expected cracking area of ​​the pure bending section at the bottom of the reinforced concrete test beam 410, before the concrete test beam 410 is poured, a low-carbon steel ferromagnetic sensing metal strip 110 is vertically tied to the bottom reinforcing steel with nylon cable ties, ensuring that it is 30mm away from the bottom surface of the beam and perpendicular to the longitudinal axis of the beam.

[0106] After concrete pouring and standard curing, a jack 510 was used to apply three-point bending load to the reinforced concrete test beam 410. During the loading process, the system of this invention continuously emitted electromagnetic waves into the sensing area at a specific sampling frequency and simultaneously acquired echo signals. By processing the echo signals in real time using data analysis software, the entire process of cracks starting from the concrete cover, extending inwards, and finally penetrating the entire cross-section was successfully captured.

[0107] The monitoring system outputs real-time, continuous data on crack depth and width changes, accurately reflecting each stage of crack development. Experimental results show that the system can accurately monitor the entire crack development process: the initial crack load is 25 kN, the load when the crack expands to half the beam height is 45 kN, and the load when the crack penetrates is 68 kN. The crack depth monitoring error is ≤0.5 mm, the width monitoring error is ≤0.05 mm, and the consistency with the dial gauge measured data is ≥98%, verifying the excellent performance of the sensor unit in co-deformation with concrete under the direct pre-embedded scheme and its effectiveness in monitoring cracks in concrete structures.

[0108] Example 2: Long-term monitoring of large-volume concrete dams.

[0109] To verify the long-term monitoring performance of this invention in the actual environment of a large-scale water conservancy project, it was applied in the field on a concrete gravity dam. For example... Figure 9 and Figure 10 As shown, in a dam gallery, a dam block 420 with existing surface cracks was selected, and a core drill was used to drill a hole along the direction of the crack extension as a channel.

[0110] After applying an epoxy interface agent to the inner wall of the channel, a ferromagnetic sensing metal strip with an anti-corrosion coating is inserted into the hole, and a special high-strength non-shrink grout is used to fill the hole tightly through a segmented pressure grouting process, ensuring that the ferromagnetic sensing metal strip 110 forms an integral whole with the surrounding concrete.

[0111] The moisture-proof and explosion-proof signal receiving module 310 was fixedly installed at a suitable location within the corridor for long-term automated monitoring. The system automatically collected data at regular intervals, continuously monitoring for 18 months. By analyzing the changes in characteristic parameters of the echo signal, the system successfully detected the regular opening-closing cycle of the cracks as the reservoir water level changed, with an amplitude of 0.1–0.3 mm; the opening and closing amplitude varied with seasonal temperature changes, ranging from 0.05–0.15 mm. Long-term monitoring data also revealed an extremely slow crack propagation trend, with a propagation rate of approximately 0.2 mm / year. The system demonstrated a signal-to-noise ratio (SNR) ≥25 dB and a data validity rate ≥99.5% under harsh conditions, exhibiting good stability and durability, providing continuous and reliable data support for accurately assessing the structural safety of the dam.

[0112] Example 3: Stability monitoring of tunnel lining cracks.

[0113] To verify the applicability of this invention in the structural health monitoring of operating tunnels, it was applied in an engineering project in an operating tunnel; for example... Figure 11 and Figure 12 As shown, in tunnel section 430 where cracks were found, three sections with typical crack development (arch crown, left and right arch waists) were selected, and several monitoring points were set up.

[0114] At each monitoring point, a monitoring channel was drilled at a 45° angle using a specialized drilling rig. A flat, galvanized steel magnetic metal strip with an anti-corrosion coating and an outer water-swellable sealing strip was inserted into the hole. The hole was then filled tightly with high-strength, non-shrink grout, and the borehole opening was finished.

[0115] The multi-channel external detection unit is fixedly mounted on a bracket on the tunnel sidewall, with its scanning center aligned with the pre-embedded sensing unit area. The system automatically performs scanning monitoring at a set interval, running continuously for 3 months. The signal transmitting module controls the radar antenna to emit electromagnetic wave pulses with specific parameters towards the lining surface, and the receiving module synchronously collects the reflected signals.

[0116] After three months of continuous monitoring, data analysis showed that the monthly variation in stable crack width was <0.05 mm, the propagation rate of developing cracks was 0.1–0.3 mm / month, and the depth propagation trend was 1–3 mm / month. The system's positioning accuracy reached ±10 mm, the crack width identification resolution was 0.02 mm, and the wireless data reporting success rate was ≥97%. Based on this precise monitoring data, the maintenance management department formulated differentiated treatment strategies: stable cracks were primarily observed, while developing cracks were promptly addressed with targeted measures. This decision-making approach based on precise monitoring data avoided over-maintenance, significantly saved maintenance costs, and ensured the safe operation of the tunnel.

[0117] Based on this precise monitoring data, the maintenance management department formulated differentiated treatment strategies: stable cracks were primarily treated through observation, while developing cracks were addressed promptly with targeted measures. This decision-making approach based on accurate monitoring data avoided over-repair, significantly saved maintenance costs, and ensured the safe operation of the tunnel.

[0118] All other unspecified parts belong to the prior art.

Claims

1. A wireless monitoring system for deep deformation of concrete cracks, characterized in that: It includes a built-in passive sensing unit (100), an external wireless detection unit (200), and a cloud-based data analysis and inversion platform (300); the built-in passive sensing unit (100) includes a ferromagnetic sensing metal strip (110) and a positioning structure (120); the ferromagnetic sensing metal strip (110) is embedded in the concrete structure (400) through the positioning structure (120) and forms a cooperative deformation relationship with the concrete; The external wireless detection unit (200) includes a signal transmitting module (210), and the cloud data analysis and inversion platform (300) includes a signal receiving module (310) and a main control processor (320). The signal transmitting module (210) transmits electromagnetic wave signals to the concrete structure (400). The signal receiving module (310) receives the echo signal reflected by the ferromagnetic sensing metal strip (110). The main control processor (320) filters, amplifies, and performs analog-to-digital conversion on the echo signal and transmits the processed data to the cloud data analysis and inversion platform (300).

2. The wireless monitoring system for deep deformation of concrete cracks according to claim 1, characterized in that: The built-in passive sensing unit (100) is divided into two types: pre-embedded type for new structures and drilled type for existing structures. When the built-in passive sensing unit (100) is a pre-embedded type in the new structure, the positioning structure (120) is a three-dimensional orthogonal positioning bracket (121); the three-dimensional orthogonal positioning bracket (121) is a cross-shaped frame, and the three-dimensional orthogonal positioning bracket (121) is provided with metal strip positioning slots (122) in the three directions of X, Y and Z axes. The inner wall of the metal strip positioning slots (122) is pasted with a rubber buffer layer (123); the ferromagnetic sensing metal strip (110) is fixed in the metal strip positioning slots (122) in the three directions of X, Y and Z axes, and is pre-embedded synchronously with the concrete pouring; When the built-in passive sensing unit (100) is a pre-existing drilled structure, the positioning structure (120) is a three-dimensional orthogonal channel group; the three-dimensional orthogonal channel group is formed by drilling with a core drill with an angle locator, and the three-dimensional orthogonal channel group contains 3 channels arranged along the X, Y and Z axes; after the ferromagnetic sensing metal strip (110) is implanted into the channel of the three-dimensional orthogonal channel group, high-performance non-shrink grout is backfilled using a segmented pressure grouting process.

3. The wireless monitoring system for deep deformation of concrete cracks according to claim 2, characterized in that: The ferromagnetic sensing metal strip (110) is made of low-carbon steel, galvanized steel or iron-chromium-aluminum alloy, with a relative permeability of not less than 500. The cross-section of the ferromagnetic sensing metal strip (110) is circular, rectangular or irregular structure with periodic engravings.

4. The wireless monitoring system for deep deformation of concrete cracks according to claim 2, characterized in that: The segmented pressure grouting process is as follows: the grouting pipe is inserted from the bottom of the channel, with the pipe opening 100mm from the bottom of the channel; a grouting pump is used to inject high-performance non-shrink grouting material at a pressure of 0.5-1.0MPa. A segmented pressure grouting process is adopted, with pauses in stages during grouting to check the filling condition. After confirming there are no voids, the grouting pipe continues to advance upwards; after grout overflows from the top of the channel, maintain pressure for 30 seconds, close the grouting valve, and cure for 7-14 days.

5. The wireless monitoring system for deep deformation of concrete cracks according to claim 3, characterized in that: The signal transmitting module (210) transmits electromagnetic wave signals of a specific frequency. The signal transmitting module (210) supports frequency modulated continuous wave (FMCW) mode and pulse radar mode.

6. The wireless monitoring system for deep deformation of concrete cracks according to claim 1, characterized in that: The cloud-based data analysis and inversion platform (300) includes a data storage module, an algorithm operation module, and an early warning module; The algorithm operation module has built-in differential calculation algorithm and multi-source signal fusion algorithm. By extracting the arrival time difference, phase shift and amplitude attenuation characteristic parameters of the echo signal, it solves the three-dimensional deformation data of the crack based on the calibration mathematical model. The early warning module triggers an early warning when the deformation data exceeds a preset crack deformation threshold.

7. A monitoring method for a wireless monitoring system for deep deformation of concrete cracks, characterized in that, Includes the following steps: Step 1: Select the built-in passive sensing unit (100) according to the type of concrete structure (400). For new structures, adopt the new structure pre-embedded type, and for existing structures, adopt the existing structure drilled type. Step 2: After the built-in passive sensing unit (100) is installed, the external wireless detection unit (200) is activated, and the signal transmitting module (210) transmits electromagnetic wave signals to the concrete structure (400); the signal receiving module (310) receives the echo signal reflected by the ferromagnetic sensing metal strip (110); and a wireless monitoring baseline database is established. Step 3: According to the set monitoring cycle, the external wireless detection unit (200) automatically emits electromagnetic waves and receives reflected echoes. After signal processing, the signals are sent to the cloud data analysis and inversion platform (300) through the wireless transmission module. Step 4: The cloud-based data analysis and inversion platform (300) compares the current echo signal with the baseline signal, extracts the changes in characteristic parameters, calculates the deformation of the metal strip based on the experimentally calibrated mathematical model, and inverts the depth, width and three-dimensional extension morphology of the crack. Step 5: When the crack deformation data exceeds the preset threshold, the system will automatically trigger an early warning.

8. The monitoring method of the wireless monitoring system for deep deformation of concrete cracks according to claim 7, characterized in that, In step 4, the mathematical model calibrated in the experiment is as follows: Prepare standard specimens with the same mix proportions as the engineering concrete, and embed or drill three-dimensional orthogonal ferromagnetic sensing metal strips (110) according to the actual engineering method. A universal testing machine was used to apply a three-point bending load to the specimen to simulate multi-directional crack propagation, and a high-precision displacement sensor was used to measure the deformation of the ferromagnetic sensing metal strip (110). Multi-directional echo signals under different loads were collected, the correspondence between characteristic parameters and the deformation of ferromagnetic sensing metal strip (110) was fitted, the calibration coefficients were determined, and a calibration database was established.

9. The monitoring method of the wireless monitoring system for deep deformation of concrete cracks according to claim 8, characterized in that, In step 3, the signal processing specifically involves: performing low-pass filtering and high-pass filtering on the echo signal in sequence; amplifying and performing 16-bit analog-to-digital conversion on the filtered signal; and packaging the processed data with the synchronously acquired environmental parameters and transmitting them encrypted to the cloud data analysis and inversion platform (300) via the wireless transmission module.

10. The monitoring method of the wireless monitoring system for deep deformation of concrete cracks according to claim 9, characterized in that, In step 4, after receiving the wireless data, the cloud data analysis and inversion platform (300) automatically corrects for environmental influences; compares the current multi-directional echo signal with the baseline signal, and extracts the arrival time difference, phase shift, and amplitude attenuation characteristic parameters of each direction; Substitute the coupled mathematical model and combine the multi-source signal fusion algorithm to calculate the deformation of the multi-directional ferromagnetic sensing metal strip (110); based on the synergistic relationship between the deformation of the ferromagnetic sensing metal strip (110) and the concrete crack, the depth, width and three-dimensional extension trajectory of the crack are inverted.

Images