Intelligent concrete crack identification and measurement system

Abstract

The application discloses a kind of concrete crack intelligent identification and measurement system, it is related to concrete structure health monitoring technical field, comprising: data acquisition module: in the position of concrete structure surface excitation mechanical wave, make mechanical wave spread to concrete interior, several piezoelectric film sensors are laid out on the surface of concrete, receive the waveform signal of mechanical wave after passing through concrete, obtain mechanical wave arrival time data set, several infrared imaging units are laid out on the surface of concrete, obtain the transient infrared radiation distribution data of concrete structure surface in the process of mechanical wave propagation, form heat field disturbance data set.The crack target area determined after spatial matching of mechanical anomaly and thermal anomaly has the abnormal characteristics of two physical fields, effectively avoids the misjudgment caused by environmental interference of single detection means, reduces the false positive rate of detection result.

Description

Technical Field

[0001] This invention relates to the field of concrete structure health monitoring technology, specifically to an intelligent identification and measurement system for concrete cracks. Background Technology

[0002] Concrete structures, as the main load-bearing components of modern civil engineering, are widely used in bridges, tunnels, dams, industrial and civil buildings, etc. During long-term service, concrete structures are affected by multiple factors such as load, temperature changes, shrinkage and creep, and environmental erosion, making them prone to cracking. The appearance of cracks not only affects the appearance quality of the structure, but more importantly, it reduces the load-bearing capacity, durability and service life of the structure, and may even cause major safety accidents. Therefore, timely and accurate identification and measurement of concrete cracks are of great significance for structural health monitoring and safety assessment.

[0003] Currently, concrete crack detection technology is mainly divided into two categories: traditional manual inspection methods and instrument-assisted detection methods. Traditional manual inspection methods rely on visual observation by inspectors combined with simple tools such as feeler gauges and crack cards for measurement. Although this method is intuitive and flexible, it is inefficient, the results are greatly affected by the personnel's experience, and it is highly subjective. Furthermore, it is difficult to detect cracks in high-altitude or hidden areas, resulting in blind spots in the detection.

[0004] To address the limitations of manual inspection, various instrument-assisted detection technologies have been developed. The ultrasonic pulse method utilizes the characteristics of ultrasonic waves that reflect, attenuate, and change wave velocity when they encounter cracks in concrete to infer the presence of cracks. However, this method requires the use of a coupling agent and has poor sensitivity to shallow and micro-cracks. Infrared thermal imaging detects abnormal surface temperature distributions caused by differences in thermal conductivity between cracked and intact concrete areas. However, it is easily affected by external factors such as changes in ambient temperature and solar radiation, and the stability and repeatability of the detection results need to be improved. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent concrete crack identification and measurement system.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent identification and measurement system for concrete cracks, specifically comprising:

[0007] Data acquisition module: Mechanical waves are excited at the surface of the concrete structure, causing them to propagate into the concrete. Several piezoelectric thin film sensors are deployed on the concrete surface to receive the waveform signals of the mechanical waves after they pass through the concrete, thus acquiring the arrival time history dataset of the mechanical waves. Several infrared imaging units are deployed on the concrete surface to acquire the transient infrared radiation distribution data of the concrete structure surface during the propagation of the mechanical waves, forming a thermal field disturbance dataset.

[0008] Crack location module: It is connected to the data acquisition module by telecommunications. Based on the waveform distortion characteristics in the mechanical wave arrival time history dataset, it determines the location of the discontinuous interface and the heat dissipation anomaly area based on the thermal anomaly area in the thermal field disturbance dataset. It spatially matches the location of the discontinuous interface with the heat dissipation anomaly area to determine several crack target areas.

[0009] Crack Measurement Module: Telecommunicationally connected to the crack location module, it determines the crack opening width and extension width based on the wavefront diffraction delay and thermal anomaly gradient corresponding to the crack target area.

[0010] Preferably, the data acquisition module includes a controllable impact generator, several piezoelectric thin film sensors, and several infrared imaging units. The controllable impact generator is attached to the concrete surface and generates mechanical waves according to the trigger signal. The mechanical waves propagate into the concrete in the form of spherical waves.

[0011] Several piezoelectric thin film sensors are attached to the concrete surface in an array to sense the surface micro-vibrations generated when mechanical waves arrive and record the first moment when each piezoelectric thin film sensor receives the mechanical wave front, forming a mechanical wave front arrival time history dataset. The mechanical wave front arrival time history data includes the position coordinates of each piezoelectric thin film sensor and the first moment corresponding to each piezoelectric thin film sensor.

[0012] Several infrared thermal imaging units are aligned with the concrete surface to continuously acquire the infrared radiation intensity of the concrete surface, generating a time-series thermal image sequence. The thermal field perturbation dataset contains the radiation intensity change curve of each pixel in the thermal image sequence over time.

[0013] Preferably, the crack positioning module acquires the excitation point coordinates of the controllable impact generator on the concrete structure surface, as well as the sensor position coordinates of each piezoelectric thin film sensor on the concrete structure surface, and acquires the pre-set wave velocity value of the concrete material.

[0014] Based on the straight-line distance between the excitation point location coordinates and the location coordinates of each sensor, and the preset wave velocity value, the first theoretical arrival time of the mechanical wave front to each sensor location is calculated, and the first moment actually recorded by each piezoelectric thin film sensor is extracted from the mechanical wave front arrival time history dataset.

[0015] For any pair of adjacent piezoelectric thin film sensors, the difference between the first theoretical arrival times of the pair of adjacent sensors is taken as the theoretical difference, and the difference between the first moments of the pair of adjacent sensors is taken as the actual difference. The deviation of the actual difference from the theoretical difference is determined. If the deviation exceeds a preset first threshold, the area covered by the line connecting the pair of adjacent piezoelectric thin film sensors is marked as a discontinuous interface position.

[0016] The time-series thermal image sequence contained in the thermal field disturbance dataset is obtained. The thermal image sequence consists of multiple frames of thermal images arranged in chronological order. For each pixel in the thermal image sequence, the radiation intensity value of the pixel in each frame of the thermal image is extracted. All the read radiation intensity values ​​are arranged according to the corresponding frame order to form the radiation intensity of the pixel over time arranged in chronological order.

[0017] Based on the curve of radiation intensity changing with time, for each pair of adjacent sampling times, the difference between the radiation intensity value at the next time moment and the radiation intensity value at the previous time moment is calculated, and this difference is taken as the rate of change of radiation intensity.

[0018] Traverse all adjacent time pairs on the curve of radiation intensity changing with time. Pixels whose rate of change of radiation intensity exceeds the preset second threshold are marked as abnormal pixels. Connected regions formed by multiple abnormal pixels that are continuously distributed in space are marked as heat dissipation abnormal regions. Establish a unified spatial coordinate system and transform the discontinuous interface position and heat dissipation abnormal region into this spatial coordinate system respectively.

[0019] In the spatial coordinate system, the minimum spatial distance between the discontinuous interface location and the heat dissipation anomaly area is calculated, and it is determined whether there is spatial overlap between the two. If the minimum spatial distance is less than a preset third threshold, or if there is spatial overlap, the union area of ​​the discontinuous interface location and the heat dissipation anomaly area is determined as the crack target area.

[0020] Preferably, the crack measurement module selects several piezoelectric thin film sensors located around the crack target area from the stored mechanical wavefront arrival time history dataset based on the spatial range of the crack target area. According to the spatial position of each piezoelectric thin film sensor relative to the crack target area, the selected piezoelectric thin film sensors are divided into a first sensor group located on the first side of the crack and a second sensor group located on the second side of the crack.

[0021] The arrival time of the first diffracted wave generated by the diffraction at the crack tip is extracted from the waveform signals recorded by each sensor in the first sensor group, and the arrival time of the second diffracted wave generated by the diffraction at the crack tip is extracted from the waveform signals recorded by each sensor in the second sensor group.

[0022] Calculate the time difference between the arrival time of the second diffracted wave and the arrival time of the first diffracted wave, obtain the pre-set wave velocity value of the concrete material, and calculate the actual path increment generated by the diffracted wave around the crack tip based on the time difference and the pre-set wave velocity value.

[0023] The position coordinates of each sensor in the first sensor group, the position coordinates of each sensor in the second sensor group, and the position coordinates of the excitation point of the controllable impact generator on the concrete surface are obtained. Based on the position coordinates of each sensor in the first sensor group, the position coordinates of each sensor in the second sensor group, the position coordinates of the excitation point, and the actual path increment, the opening width of the crack on the concrete surface is determined by solving the geometric relationship of the diffraction wave propagation path.

[0024] Extract the thermal image sequence data corresponding to the crack target area from the thermal field disturbance dataset. For each pixel in the crack target area, obtain the radiation intensity change curve of that pixel over time. Calculate the thermal anomaly gradient value of that pixel based on the radiation intensity change curve over time.

[0025] Extract the thermal anomaly gradient values ​​of multiple pixels in the target area of ​​the crack along the direction perpendicular to the crack direction, form a thermal anomaly gradient profile according to the spatial arrangement order, determine the spatial distance corresponding to the thermal anomaly gradient value in the thermal anomaly gradient profile decaying from the maximum value to a preset ratio, obtain the pre-set thermal diffusivity of the concrete material, and determine the depth of the crack extending into the concrete based on the spatial distance and the thermal diffusivity.

[0026] This invention provides an intelligent identification and measurement system for concrete cracks, which has the following advantages:

[0027] This invention excites a controllable mechanical wave on a concrete surface, receives the waveform signal after it passes through the concrete, obtains the mechanical wavefront propagation information, and simultaneously collects transient infrared radiation changes during the mechanical wave propagation process to obtain surface thermal disturbance field information. Based on the waveform distortion characteristics in the mechanical wavefront arrival time history dataset, the location of the discontinuous interface is determined. The location of the discontinuous interface indicates the presence of mechanical anomalies on the stress wave propagation path. At the same time, based on the thermal anomaly region in the thermal field disturbance dataset, a heat dissipation anomaly region is determined. The heat dissipation anomaly region indicates the thermal conduction anomaly in the crack region. The crack target region determined by spatially matching the mechanical anomaly and the thermal anomaly possesses the anomaly characteristics of both physical fields, effectively avoiding misjudgments caused by environmental interference due to a single detection method and reducing the false alarm rate of the detection results. Attached Figure Description

[0028] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Please see Figure 1 This invention provides an intelligent identification and measurement system for concrete cracks, comprising:

[0031] Data acquisition module: Mechanical waves are excited at the surface of the concrete structure, causing them to propagate into the concrete. Several piezoelectric thin film sensors are deployed on the concrete surface to receive the waveform signals of the mechanical waves after they pass through the concrete, thus acquiring the arrival time history dataset of the mechanical waves. Several infrared imaging units are deployed on the concrete surface to acquire the transient infrared radiation distribution data of the concrete structure surface during the propagation of the mechanical waves, forming a thermal field disturbance dataset.

[0032] In this embodiment of the invention, the data acquisition module needs to be specifically described. The data acquisition module includes a controllable impact generating device, several piezoelectric thin film sensors, and several infrared imaging units. The controllable impact generating device is attached to the concrete surface and generates mechanical waves according to the trigger signal. The mechanical waves propagate into the concrete in the form of spherical waves.

[0033] Several piezoelectric thin film sensors are attached to the concrete surface in an array to sense the surface micro-vibrations generated when mechanical waves arrive and record the first moment when each piezoelectric thin film sensor receives the mechanical wave front, forming a mechanical wave front arrival time history dataset. The mechanical wave front arrival time history data includes the position coordinates of each piezoelectric thin film sensor and the first moment corresponding to each piezoelectric thin film sensor.

[0034] Several infrared thermal imaging units are aligned with the concrete surface to continuously acquire the infrared radiation intensity of the concrete surface, generating a time-series thermal image sequence. The thermal field perturbation dataset contains the radiation intensity change curve of each pixel in the thermal image sequence over time.

[0035] It should be noted that after receiving an external trigger signal, the controllable impact generator generates a first mechanical wave according to the preset excitation parameters. Since the controllable impact generator is in close contact with the concrete surface, the generated mechanical wave can enter the interior of the concrete medium and propagate to the surrounding space in the form of a spherical wave. The spherical wave follows the propagation law of elastic waves in solid media during propagation. When it encounters material discontinuities such as cracks, voids or foreign objects, it will undergo reflection, refraction, diffraction and mode conversion. By controlling the frequency band range of the mechanical wave, its penetration depth in the concrete and its sensitivity to defects of different sizes can be controlled.

[0036] When the first mechanical wave propagates inside the concrete and reaches the sensor location, it causes a small vibration on the concrete surface. The piezoelectric thin film sensor converts the mechanical vibration into an electrical signal based on the piezoelectric effect. Each sensor independently records the first moment when it first detects a valid vibration signal. The first moment precisely corresponds to the time when the wavefront of the mechanical wave arrives at the sensor location. The system synchronously collects the position coordinates of all sensors and their corresponding first moments to form a mechanical wavefront arrival time history dataset. The mechanical wavefront arrival time history dataset records the time information of the stress wave generated by the same excitation event propagating to different spatial points, reflecting the actual propagation path and velocity distribution of the wave in the concrete medium. Any time anomalies that deviate from the expected propagation law of a uniform medium imply the existence of discontinuous interfaces on the path.

[0037] When mechanical waves propagate through concrete, the medium in the area through which the mechanical wave passes undergoes instantaneous compression and expansion. This volume change leads to a small adiabatic change in local temperature. At the same time, the air gaps inside defects such as cracks have significantly different thermophysical properties from the concrete body, which hinders heat conduction and causes an abnormal surface temperature field distribution. The infrared thermal imaging unit records the infrared radiation intensity of the concrete surface at a high frame rate, generating a time-series thermal image sequence. Each frame corresponds to the surface temperature distribution at a sampling time. By extracting the change in radiation intensity of each pixel in the thermal image sequence over time, a thermal field perturbation dataset is formed. The thermal field perturbation dataset captures the dynamic response characteristics of the surface thermal field during mechanical wave propagation, especially the abnormal heating or cooling rate exhibited by the crack area due to the obstruction of heat conduction.

[0038] It should be noted that the mechanical wavefront is the leading edge section of the mechanical wave propagating inside the concrete. It is the dynamic boundary formed at the instant when the vibration energy just arrives at a certain point in the concrete. When the wavefront of the mechanical wave propagates to the piezoelectric thin film sensor deployed on the concrete surface, the piezoelectric thin film sensor senses the surface micro-vibration and records the corresponding first moment. The first moment reflects the actual time taken for the mechanical wave to propagate from the excitation point to the location of the piezoelectric thin film sensor. Due to the presence of cracks, the mechanical wave will diffract or be blocked on the propagation path, causing the actual arrival time to deviate from the theoretical arrival time in uniform concrete. This deviation is the wavefront distortion feature. By analyzing the distortion features presented by the first moment recorded by several sensors, the location of the discontinuous interface where the crack is located can be deduced.

[0039] Crack location module: It is connected to the data acquisition module by telecommunications. Based on the waveform distortion characteristics in the mechanical wave arrival time history dataset, it determines the location of the discontinuous interface and the heat dissipation anomaly area based on the thermal anomaly area in the thermal field disturbance dataset. It spatially matches the location of the discontinuous interface with the heat dissipation anomaly area to determine several crack target areas.

[0040] In this embodiment of the invention, the crack location module needs to be specifically described. The crack location module obtains the position coordinates of the excitation point of the controllable impact generator on the surface of the concrete structure, as well as the sensor position coordinates of each piezoelectric thin film sensor on the surface of the concrete structure, and obtains the wave velocity value preset by the concrete material.

[0041] Based on the straight-line distance between the excitation point location coordinates and the location coordinates of each sensor, and the preset wave velocity value, the first theoretical arrival time of the mechanical wave front to each sensor location is calculated, and the first moment actually recorded by each piezoelectric thin film sensor is extracted from the mechanical wave front arrival time history dataset.

[0042] For any pair of adjacent piezoelectric thin film sensors, the difference between the first theoretical arrival times of the pair of adjacent sensors is taken as the theoretical difference, and the difference between the first moments of the pair of adjacent sensors is taken as the actual difference. The deviation of the actual difference from the theoretical difference is determined. If the deviation exceeds a preset first threshold, the area covered by the line connecting the pair of adjacent piezoelectric thin film sensors is marked as a discontinuous interface position.

[0043] The time-series thermal image sequence contained in the thermal field disturbance dataset is obtained. The thermal image sequence consists of multiple frames of thermal images arranged in chronological order. For each pixel in the thermal image sequence, the radiation intensity value of the pixel in each frame of the thermal image is extracted. All the read radiation intensity values ​​are arranged according to the corresponding frame order to form the radiation intensity of the pixel over time arranged in chronological order.

[0044] Based on the curve of radiation intensity changing with time, for each pair of adjacent sampling times, the difference between the radiation intensity value at the next time moment and the radiation intensity value at the previous time moment is calculated, and this difference is taken as the rate of change of radiation intensity.

[0045] Traverse all adjacent time pairs on the curve of radiation intensity changing with time. Pixels whose rate of change of radiation intensity exceeds the preset second threshold are marked as abnormal pixels. Connected regions formed by multiple abnormal pixels that are continuously distributed in space are marked as heat dissipation abnormal regions. Establish a unified spatial coordinate system and transform the discontinuous interface position and heat dissipation abnormal region into this spatial coordinate system respectively.

[0046] In the spatial coordinate system, the minimum spatial distance between the discontinuous interface location and the heat dissipation anomaly area is calculated, and it is determined whether there is spatial overlap between the two. If the minimum spatial distance is less than a preset third threshold, or if there is spatial overlap, the union area of ​​the discontinuous interface location and the heat dissipation anomaly area is determined as the crack target area.

[0047] Calculate the minimum spatial distance between the discontinuous interface location and the heat dissipation anomaly zone, and determine whether there is spatial overlap between the two. This includes the following steps:

[0048] The discontinuous interface is formed by the line region between a set of adjacent piezoelectric thin film sensor pairs. In the spatial coordinate system, it is represented by one or more line segments or sets of line segments with a specific orientation. Each line segment corresponds to the line between a pair of adjacent piezoelectric thin film sensors marked as abnormal. Each point on the line segment has a unique three-dimensional spatial coordinate. The heat dissipation abnormal area is formed by a number of continuously distributed abnormal pixels. In the spatial coordinate system, it is represented by a point set region composed of discrete pixels. Each abnormal pixel in the point set region has a unique three-dimensional spatial coordinate.

[0049] For each line segment that constitutes the discontinuous interface position, the line segment is divided into several equally spaced sampling points according to the preset sampling interval. Each sampling point has a unique three-dimensional spatial coordinate. Discretization processing is performed on all line segments to convert the discontinuous interface position into a first point set composed of several discrete sampling points.

[0050] Extract all abnormal pixels that constitute the heat dissipation anomaly region, and use the three-dimensional spatial coordinates of these abnormal pixels as the second point set. The second point set is the discrete representation of the heat dissipation anomaly region in the spatial coordinate system.

[0051] Traverse each discrete sampling point in the first point set. For each discrete sampling point, calculate the spatial straight-line distance between the discrete sampling point and each abnormal pixel in the second point set. For each pair of points consisting of a discrete sampling point and an abnormal pixel, substitute their three-dimensional coordinates into the spatial distance calculation formula to obtain the distance value between the pair of points. Record the minimum value among all the distance values ​​of the pair of points and use the minimum value as the minimum spatial distance between the discontinuous interface location and the heat dissipation abnormal area.

[0052] For each discrete sampling point in the first point set, check whether the three-dimensional spatial coordinates of the discrete sampling point are exactly the same as the three-dimensional spatial coordinates of any abnormal pixel in the second point set. If at least one discrete sampling point has the same coordinates as an abnormal pixel, it is determined that the discontinuous interface position and the heat dissipation abnormal area have spatial overlap. If the discrete sampling point in the first point set is located in the closed area enclosed by the line connecting adjacent abnormal pixels, it is also considered to have spatial overlap.

[0053] It should be noted that the preset sampling interval is used to convert the continuously distributed discontinuous interface positions into a set of points composed of discrete sampling points. Since the discontinuous interface positions are represented as continuous line segments between adjacent piezoelectric film sensor pairs, while the heat dissipation anomaly area is represented as a discrete set of pixels, the two do not match in terms of data form and cannot be directly calculated in terms of point-to-point distance. By introducing the sampling interval to take points at equal intervals on the continuous line segments, the line segments can be discretized into a series of sampling points with definite spatial coordinates, so that the discontinuous interface positions and the heat dissipation anomaly area can be calculated in terms of spatial distance and overlap judgment under the same data form.

[0054] The preset sampling interval represents the spatial interval between two adjacent sampling points when discretizing the continuous line segments corresponding to the discontinuous interface positions. The magnitude of the sampling interval determines the sampling point density in the first point set after discretization. The smaller the sampling interval, the more sampling points are generated on a unit length line segment, the higher the approximation of the first point set to the original continuous line segment, and the higher the accuracy of the subsequent minimum spatial distance calculation. The larger the sampling interval, the fewer sampling points are generated on a unit length line segment, and the computational load is reduced accordingly. The sampling interval is measured in length units and is consistent with the spatial reference coordinate system.

[0055] The preset sampling interval is obtained by selecting any two adjacent abnormal pixels in the heat dissipation anomaly area, calculating the spatial distance between them, taking the average of the distance values ​​of several adjacent pixel pairs, obtaining the average distribution density of the abnormal pixels, and using the average value as the sampling interval to ensure that the sampling point density after discretization of the discontinuous interface position is on the same order of magnitude as the pixel density of the heat dissipation anomaly area.

[0056] It should be noted that before performing the crack location module analysis, a unified spatial reference coordinate system is first established in the physical space where the concrete structure is located. The spatial reference coordinate system can be an absolute coordinate system based on the global navigation satellite system, or a relative coordinate system set for a specific detection area. For example, a three-dimensional rectangular coordinate system is established with a specific corner point of the concrete structure as the origin and the length, width and height directions of the structure as coordinate axes. When several piezoelectric thin film sensors are attached to the concrete surface in an array, the unique identifier of each piezoelectric thin film sensor and its corresponding sensor position coordinates in the spatial reference coordinate system are obtained by reading the sensor layout configuration information. When the controllable impact generator determines its current position in the spatial reference coordinate system through the built-in position sensing unit and uses the current position as the excitation point position, the first theoretical arrival time of the mechanical wavefront to each sensor position is calculated based on the straight-line distance between the excitation point position coordinates and the position coordinates of each sensor and the preset wave velocity in the concrete.

[0057] The preset wave velocity value represents the standard speed at which a mechanical wave propagates in a defect-free, intact concrete medium. The preset wave velocity value serves as a reference parameter for theoretical calculations, used to calculate the first theoretical arrival time of the mechanical wave to each piezoelectric thin film sensor based on the straight-line distance. The preset wave velocity value is obtained by selecting a representative area of ​​the concrete structure that is known to be defect-free before the detection begins, and by receiving the waveform signal through the piezoelectric thin film sensor using the excited mechanical wave. Based on the known distance between the excitation point and the waveform signal receiving point, as well as the actual recorded propagation time, the actual wave velocity of the concrete material in the current state is calculated in reverse.

[0058] The pre-set first threshold represents the maximum allowable deviation of the mechanical wavefront arrival time. The pre-set first threshold is used to determine whether the degree of deviation of the actual difference from the theoretical difference is sufficient to constitute an anomaly. That is, it is used to distinguish between small deviations caused by measurement noise and micro-inhomogeneity of materials and significant deviations caused by defects such as cracks. The pre-set first threshold is obtained by conducting multiple excitation tests in a known defect-free area of ​​the concrete structure before the start of the test, collecting multiple sets of mechanical wavefront arrival time history data, calculating the deviation between the actual difference and the theoretical difference of each adjacent piezoelectric thin film sensor pair, statistically analyzing the distribution range of these deviation values, and using the maximum value obtained from the statistics or the upper limit corresponding to a certain confidence interval as the pre-set first threshold. Alternatively, based on the timing accuracy of the piezoelectric thin film sensor and the distance between adjacent sensors, the maximum deviation that may be introduced by timing error and positioning error is calculated, and the maximum deviation is multiplied by a safety factor as the pre-set first threshold.

[0059] The pre-set second threshold represents the abnormal judgment boundary of the radiation intensity change rate. The pre-set second threshold is used to filter out pixels with abnormal thermal response behavior from all pixels. It is used to distinguish between abnormal heat conduction caused by cracks and normal radiation intensity changes caused by environmental temperature fluctuations and surface emissivity differences. The pre-set second threshold is obtained by acquiring thermal image sequences in known defect-free areas of the concrete structure, extracting the radiation intensity change curves of all pixels in the defect-free areas, calculating the radiation intensity change rate of each pixel, and statistically calculating the average and standard deviation of the radiation intensity change rate. The average value plus three times the standard deviation is used as the pre-set second threshold. Alternatively, before the mechanical wave is excited, multiple frames of background thermal images are continuously acquired, the radiation intensity fluctuation range of each pixel in the background state is calculated, and the maximum value of the background fluctuation is multiplied by a coefficient greater than 1 as the pre-set second threshold to ensure that only significant thermal anomalies caused by mechanical waves can be identified.

[0060] The pre-set third threshold represents the maximum allowable distance during spatial matching. It is used to determine whether the location of the discontinuous interface and the heat dissipation area belong to the same crack origin. That is, it is used to associate mechanical anomalies with thermal anomalies. When the two are close enough, they are considered to be pointing to the same crack target. The pre-set third threshold is obtained based on the spatial positioning accuracy of the discontinuous interface location and the edge positioning accuracy of the heat dissipation anomaly area. The comprehensive positioning error of the two is calculated and used as the pre-set third threshold.

[0061] It should be noted that the straight-line distance between the first position and each second position is calculated, and the straight-line distance is divided by the preset wave speed to obtain the first theoretical arrival time of the mechanical wave front to each second position. For any pair of adjacent sensors, the difference between the first theoretical arrival times of the two sensors is calculated as the theoretical difference value. At the same time, the difference between the first recorded moments of the two sensors is obtained as the actual difference value. The actual difference value is compared with the theoretical difference value. When the deviation of the actual difference value from the theoretical difference value exceeds the first threshold, it is determined that there is an abnormal stress wave propagation in the connecting area between the pair of adjacent sensors. The abnormal stress propagation indicates that the stress wave does not propagate in a straight line in the connecting area but detours. Therefore, the connecting area is marked as a discontinuous interface position. The discontinuous interface position indicates that there is an obstacle in the stress wave propagation path.

[0062] For each pixel in the thermal image sequence, the curve of its radiation intensity change over time is extracted, and the rate of change of radiation intensity for each pixel is calculated. The rate of change of radiation intensity for each pixel is compared with a preset second threshold, and pixels with a rate of change of radiation intensity exceeding the second threshold are selected. Spatial connectivity analysis is performed on the selected pixels, and adjacent and continuously distributed pixels are grouped into the same region. This region is marked as a heat dissipation anomaly region. The formation of the heat dissipation anomaly region is that the air gaps inside the crack have different thermal conductivity characteristics than the concrete body, which causes the temperature change rate of the crack region to be significantly different from that of the intact concrete region during the propagation of mechanical waves.

[0063] The marked discontinuous interface locations and heat dissipation anomaly areas are superimposed in the coordinate system. For each discontinuous interface location, the spatial distance between it and each heat dissipation anomaly area is calculated. When a discontinuous interface location and a heat dissipation anomaly area have spatial overlap, or the minimum distance between them is less than the preset third threshold, it is determined that the location and the anomaly area have spatial correlation. The union area of ​​the discontinuous interface locations and heat dissipation anomaly areas that meet the spatial correlation conditions is determined as the crack target area. The crack target area has both stress wave propagation anomaly characteristics and heat conduction anomaly characteristics, thus verifying the existence of cracks from two independent dimensions: mechanics and thermodynamics.

[0064] Crack Measurement Module: Telecommunicationally connected to the crack location module, it determines the crack opening width and extension width based on the wavefront diffraction delay and thermal anomaly gradient corresponding to the crack target area.

[0065] In this embodiment of the invention, the crack measurement module needs to be specifically described. Based on the spatial range of the crack target area, the crack measurement module selects several piezoelectric thin film sensors located around the crack target area from the stored mechanical wavefront arrival time history dataset. According to the spatial position of each piezoelectric thin film sensor relative to the crack target area, the selected piezoelectric thin film sensors are divided into a first sensor group located on the first side of the crack and a second sensor group located on the second side of the crack.

[0066] The arrival time of the first diffracted wave generated by the diffraction at the crack tip is extracted from the waveform signals recorded by each sensor in the first sensor group, and the arrival time of the second diffracted wave generated by the diffraction at the crack tip is extracted from the waveform signals recorded by each sensor in the second sensor group.

[0067] Calculate the time difference between the arrival time of the second diffracted wave and the arrival time of the first diffracted wave, obtain the pre-set wave velocity value of the concrete material, and calculate the actual path increment generated by the diffracted wave around the crack tip based on the time difference and the pre-set wave velocity value.

[0068] The position coordinates of each sensor in the first sensor group, the position coordinates of each sensor in the second sensor group, and the position coordinates of the excitation point of the controllable impact generator on the concrete surface are obtained. Based on the position coordinates of each sensor in the first sensor group, the position coordinates of each sensor in the second sensor group, the position coordinates of the excitation point, and the actual path increment, the opening width of the crack on the concrete surface is determined by solving the geometric relationship of the diffraction wave propagation path.

[0069] Extract the thermal image sequence data corresponding to the crack target area from the thermal field disturbance dataset. For each pixel in the crack target area, obtain the radiation intensity change curve of that pixel over time. Calculate the thermal anomaly gradient value of that pixel based on the radiation intensity change curve over time.

[0070] Extract the thermal anomaly gradient values ​​of multiple pixels in the target area of ​​the crack along the direction perpendicular to the crack direction, form a thermal anomaly gradient profile according to the spatial arrangement order, determine the spatial distance corresponding to the thermal anomaly gradient value in the thermal anomaly gradient profile decaying from the maximum value to a preset ratio, obtain the pre-set thermal diffusivity of the concrete material, and determine the depth of the crack extending into the concrete based on the spatial distance and the thermal diffusivity.

[0071] It should be noted that obtaining the arrival time of the first diffracted wave includes the following steps:

[0072] For each sensor in the first sensor group, since the first sensor group is located on the first side of the crack, after the mechanical wave starts from the excitation point, part of it directly reaches the sensor on that side along a straight path to form a direct wave, and the other part goes around the tip of the crack to form a diffracted wave. The moment corresponding to the first peak in the waveform signal whose amplitude exceeds the preset noise line is identified and taken as the arrival time of the direct wave. After the arrival time of the direct wave, the second peak in the waveform signal whose amplitude exceeds the preset noise line is searched and the moment corresponding to the peak is taken as the arrival time of the diffracted wave. For multiple sensors in the first sensor group, the arrival time of their respective diffracted waves is extracted. All the extracted arrival times of diffracted waves are averaged to obtain the first arrival time of the diffracted wave.

[0073] Obtaining the arrival time of the second diffracted wave includes the following steps:

[0074] After the active wave field excitation, the complete waveform signals recorded by each sensor in the second sensor group are obtained. Since the second sensor group is located on the second side of the crack, the crack acts as a discontinuous interface and blocks the straight propagation path of the mechanical wave. Therefore, the direct wave cannot reach the sensor on this side. The first valid signal received by the sensor on this side must be a diffracted wave that arrives after bypassing the crack tip. For each sensor in the second sensor group, the amplitude of the waveform signal recorded by the sensor changes with time. The first peak in the waveform signal with an amplitude exceeding the preset noise line is searched. The time corresponding to the peak is taken as the arrival time of the diffracted wave. For multiple sensors in the second sensor group, the arrival time of their respective diffracted waves is extracted. All the extracted arrival times of diffracted waves are averaged to obtain the arrival time of the second diffracted wave.

[0075] The specific steps for obtaining the opening width of the concrete surface and the depth of the crack extending into the concrete are as follows:

[0076] Based on the spatial range of the crack target area, several piezoelectric thin film sensors located around the crack target area are selected from the stored mechanical wavefront arrival time history dataset. According to the spatial position of each piezoelectric thin film sensor relative to the crack target area, the selected piezoelectric thin film sensors are divided into a first sensor group located on the first side of the crack and a second sensor group located on the second side of the crack.

[0077] The arrival time of the first diffracted wave generated by the diffraction at the crack tip is extracted from the waveform signals recorded by each sensor in the first sensor group, and the arrival time of the second diffracted wave generated by the diffraction at the crack tip is extracted from the waveform signals recorded by each sensor in the second sensor group.

[0078] Calculate the time difference between the arrival time of the second diffracted wave and the arrival time of the first diffracted wave;

[0079] Obtain the pre-set wave velocity value of the concrete material. Based on the time difference and the pre-set wave velocity value, calculate the actual path increment generated by the diffracted wave around the crack tip. The specific calculation steps for the actual path increment are as follows:

[0080] Calculate the time difference between the arrival time of the second diffracted wave and the arrival time of the first diffracted wave. The time difference represents the extra time it takes for the diffracted wave to propagate from the first side of the crack to the second side of the crack compared to the time it takes to propagate directly from the mechanical wave excitation point to the first side of the crack. Multiply the time difference by a preset wave velocity value to obtain the actual propagation distance increased by the diffracted wave around the crack tip. Use the actual propagation distance as the actual path increment.

[0081] The coordinates of the excitation point of the controllable impact generator on the concrete surface, the coordinates of each sensor in the first sensor group, and the coordinates of each sensor in the second sensor group are obtained.

[0082] Based on the coordinates of the excitation point, the coordinates of each sensor in the first sensor group, the coordinates of each sensor in the second sensor group, and the actual path increment, the spatial position of the crack tip inside the concrete is determined by solving the geometric relationship of the diffraction wave propagation path.

[0083] Based on the spatial location of the crack tip, calculate the horizontal distance between the projection point of the crack tip on the concrete surface and the two sides of the crack, and take twice the horizontal distance as the opening width of the crack on the concrete surface.

[0084] Extract the thermal image sequence data corresponding to the crack target area from the thermal field disturbance dataset. For each pixel in the crack target area, obtain the radiation intensity change curve of that pixel over time. Calculate the thermal anomaly gradient value of that pixel based on the radiation intensity change curve over time.

[0085] Extract the thermal anomaly gradient values ​​of multiple pixels within the target area of ​​the crack along the direction perpendicular to the crack direction, and form a thermal anomaly gradient profile according to the spatial arrangement order.

[0086] Identify the maximum value of the thermal anomaly gradient in the thermal anomaly gradient profile, and determine the spatial location corresponding to the maximum value of the thermal anomaly gradient as the location of the crack edge.

[0087] Starting from the edge of the crack, extend outward in a direction perpendicular to the crack direction, and read the thermal anomaly gradient value of each pixel in sequence to determine the pixel position when the thermal anomaly gradient value decays from the maximum value of the thermal anomaly gradient to a preset ratio.

[0088] Calculate the spatial distance between the pixel position corresponding to the thermal anomaly gradient value decaying to a preset ratio and the crack edge position, and use this spatial distance as the thermal anomaly feature decay distance;

[0089] After obtaining the thermal anomaly characteristic attenuation distance, the pre-set thermal diffusivity of the concrete material and the total acquisition time of the thermal image sequence after the first mechanical wave excitation are first obtained. This total acquisition time is taken as the characteristic time of heat conduction inside the concrete. Then, according to the proportional principle describing the relationship between the heat diffusion distance in the medium and the diffusion coefficient and time in the heat conduction theory, that is, the lateral diffusion distance of heat along the direction perpendicular to the crack direction in a given time is proportional to the square root of the thermal diffusivity multiplied by the square root of the characteristic time, the thermal anomaly characteristic attenuation distance is taken as the lateral influence range formed on the surface during the heat conduction from the crack tip along the crack wall to the concrete surface. The lateral influence range is geometrically related to the position of the crack tip in the depth direction. The deeper the crack tip is from the surface, the longer it takes for heat to conduct from the tip to the surface, and the larger the lateral diffusion range formed on the surface. Therefore, the thermal anomaly characteristic attenuation distance is divided by the product of the square root of the thermal diffusivity and the square root of the characteristic time to obtain a dimensionless proportionality coefficient. Then, this proportionality coefficient is multiplied by the thermal anomaly characteristic attenuation distance to obtain the depth value of the crack extending into the concrete. This depth value is the distance from the concrete surface to the crack tip in the vertical direction.

[0090] It should be noted that the pre-set thermal diffusivity coefficient plays the role of a quantitative conversion benchmark in the crack geometry measurement module. By analyzing the thermal image sequence, the thermal anomaly gradient profile of the crack target area is obtained, and then the thermal anomaly characteristic attenuation distance is extracted. This attenuation distance characterizes the lateral influence range formed on the surface during the heat conduction from the crack tip along the crack wall to the surface. To convert the measurable lateral influence range on the surface into the depth value of the crack extending into the concrete, it is necessary to use physical parameters that characterize the thermal conductivity of the concrete material itself as the conversion basis. The thermal diffusivity coefficient is the core parameter in this conversion process, which establishes a quantitative relationship between the heat conduction distance and conduction time inside the concrete.

[0091] A higher thermal diffusivity indicates faster heat conduction within concrete, allowing temperature changes to spread more rapidly over greater distances. Conversely, a lower thermal diffusivity indicates slower heat conduction, with temperature changes primarily concentrated near the heat source. In the specific scenario of crack depth measurement, the thermal diffusivity determines the attenuation distance of the thermal anomaly characteristics formed on the surface of cracks of the same depth: for concrete with a higher thermal diffusivity, heat diffuses laterally over a wider range after being conducted from the crack tip to the surface, resulting in a larger attenuation distance for the thermal anomaly characteristics; for concrete with a lower thermal diffusivity, heat conduction is slow, and the lateral diffusion range is limited, resulting in a smaller attenuation distance for the thermal anomaly characteristics.

[0092] The thermal diffusivity can be obtained by consulting the design data of the concrete structure being tested. For example, concrete mix design documents usually contain the thermophysical property parameters of the materials. For concrete prepared according to national standards or industry specifications, the reference value of the thermal diffusivity for that grade of concrete can also be directly found in the relevant standards and specifications. The advantage of this method is its simplicity and speed, making it suitable for routine applications where the accuracy requirements for testing are generally not high.

[0093] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0094] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0096] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0097] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of protection of the described technical solution.

Claims

1. A smart system for identifying and measuring concrete cracks, characterized in that, include: Data acquisition module: Mechanical waves are excited at the surface of the concrete structure, causing them to propagate into the concrete. Several piezoelectric thin film sensors are deployed on the concrete surface to receive the waveform signals of the mechanical waves after they pass through the concrete, thus acquiring the arrival time history dataset of the mechanical waves. Several infrared imaging units are deployed on the concrete surface to acquire the transient infrared radiation distribution data of the concrete structure surface during the propagation of the mechanical waves, forming a thermal field disturbance dataset. The data acquisition module includes a controllable impact generator, several piezoelectric thin film sensors, and several infrared imaging units. The controllable impact generator is attached to the concrete surface and generates mechanical waves according to the trigger signal. The mechanical waves propagate into the concrete in the form of spherical waves. Several piezoelectric thin film sensors are attached to the concrete surface in an array to sense the surface micro-vibrations generated when mechanical waves arrive and record the first moment when each piezoelectric thin film sensor receives the mechanical wave front, forming a mechanical wave front arrival time history dataset. The mechanical wave front arrival time history data includes the position coordinates of each piezoelectric thin film sensor and the first moment corresponding to each piezoelectric thin film sensor. Several infrared thermal imaging units are aligned with the concrete surface to continuously acquire the infrared radiation intensity of the concrete surface, generating a time-series thermal image sequence. The thermal field perturbation dataset contains the radiation intensity change curve of each pixel in the thermal image sequence over time. Crack location module: It is connected to the data acquisition module by telecommunications. Based on the waveform distortion characteristics in the mechanical wave arrival time history dataset, it determines the location of the discontinuous interface and the heat dissipation anomaly area based on the thermal anomaly area in the thermal field disturbance dataset. It spatially matches the location of the discontinuous interface with the heat dissipation anomaly area to determine several crack target areas. Establish a unified spatial coordinate system and transform the location of the discontinuous interface and the heat dissipation anomaly area into this spatial coordinate system. In the spatial coordinate system, calculate the minimum spatial distance between the location of the discontinuous interface and the heat dissipation anomaly area, and determine whether there is spatial overlap between the two. If the minimum spatial distance is less than a preset third threshold, or if there is spatial overlap, then the union area of ​​the location of the discontinuous interface and the heat dissipation anomaly area is determined as the crack target area. Crack Measurement Module: Telecommunicationally connected to the crack location module, it determines the crack opening width and extension width based on the wavefront diffraction delay and thermal anomaly gradient corresponding to the crack target area.

2. The intelligent concrete crack identification and measurement system according to claim 1, characterized in that, The crack location module obtains the excitation point coordinates of the controllable impact generator on the concrete structure surface, as well as the sensor position coordinates of each piezoelectric thin film sensor on the concrete structure surface, and obtains the pre-set wave velocity value of the concrete material. Based on the straight-line distance between the excitation point location coordinates and the location coordinates of each sensor, and the preset wave velocity value, the first theoretical arrival time of the mechanical wave front to each sensor location is calculated, and the first moment actually recorded by each piezoelectric thin film sensor is extracted from the mechanical wave front arrival time history dataset. For any pair of adjacent piezoelectric thin film sensors, the difference between the first theoretical arrival times of the pair of adjacent sensors is taken as the theoretical difference, and the difference between the first time points of the pair of adjacent sensors is taken as the actual difference. The deviation of the actual difference from the theoretical difference is determined. If the deviation exceeds a preset first threshold, the area covered by the line connecting the pair of adjacent piezoelectric thin film sensors is marked as a discontinuous interface position.

3. The intelligent concrete crack identification and measurement system according to claim 2, characterized in that, The time-series thermal image sequence contained in the thermal field disturbance dataset is obtained. The thermal image sequence consists of multiple frames of thermal images arranged in chronological order. For each pixel in the thermal image sequence, the radiation intensity value of the pixel in each frame of the thermal image is extracted. All the read radiation intensity values ​​are arranged according to the corresponding frame order to form the radiation intensity of the pixel over time arranged in chronological order. Based on the radiation intensity change curve over time, for each pair of adjacent sampling times, the difference between the radiation intensity value at the next time moment and the radiation intensity value at the previous time moment is calculated, and this difference is taken as the radiation intensity change rate.

4. The intelligent concrete crack identification and measurement system according to claim 3, characterized in that, Traverse all adjacent time pairs on the curve of radiation intensity changing with time, mark the pixels whose rate of change of radiation intensity exceeds the preset second threshold as abnormal pixels, and mark the connected region formed by multiple abnormal pixels that are continuously distributed in space as heat dissipation abnormal region.

5. The intelligent identification and measurement system for concrete cracks according to claim 1, characterized in that, The crack measurement module selects several piezoelectric thin film sensors located around the crack target area from the stored mechanical wavefront arrival time history dataset based on the spatial range of the crack target area. According to the spatial position of each piezoelectric thin film sensor relative to the crack target area, the selected piezoelectric thin film sensors are divided into a first sensor group located on the first side of the crack and a second sensor group located on the second side of the crack. The arrival time of the first diffracted wave generated by the diffraction at the crack tip is extracted from the waveform signals recorded by each sensor in the first sensor group, and the arrival time of the second diffracted wave generated by the diffraction at the crack tip is extracted from the waveform signals recorded by each sensor in the second sensor group.

6. The intelligent identification and measurement system for concrete cracks according to claim 5, characterized in that, Calculate the time difference between the arrival time of the second diffracted wave and the arrival time of the first diffracted wave, obtain the pre-set wave velocity value of the concrete material, and calculate the actual path increment generated by the diffracted wave around the crack tip based on the time difference and the pre-set wave velocity value. The position coordinates of each sensor in the first sensor group, the position coordinates of each sensor in the second sensor group, and the position coordinates of the excitation point of the controllable impact generator on the concrete surface are obtained. Based on the position coordinates of each sensor in the first sensor group, the position coordinates of each sensor in the second sensor group, the position coordinates of the excitation point, and the actual path increment, the opening width of the crack on the concrete surface is determined by solving the geometric relationship of the diffraction wave propagation path.

7. The intelligent concrete crack identification and measurement system according to claim 5, characterized in that, Extract the thermal image sequence data corresponding to the crack target area from the thermal field disturbance dataset. For each pixel in the crack target area, obtain the radiation intensity change curve of that pixel over time. Calculate the thermal anomaly gradient value of that pixel based on the radiation intensity change curve over time. Extract the thermal anomaly gradient values ​​of multiple pixels in the target area of ​​the crack along the direction perpendicular to the crack direction, form a thermal anomaly gradient profile according to the spatial arrangement order, determine the spatial distance corresponding to the thermal anomaly gradient value in the thermal anomaly gradient profile decaying from the maximum value to a preset ratio, obtain the pre-set thermal diffusivity of the concrete material, and determine the depth of the crack extending into the concrete based on the spatial distance and the thermal diffusivity.

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