Crack resistance evaluation method and system based on concrete shrinkage rate

Abstract

The invention provides an anti-cracking performance evaluation method and system based on a concrete shrinkage rate. The method comprises the following steps: firstly, collecting shrinkage rate real-time sequence data and an acoustic emission signal flow of a concrete sample in a curing process, separating a high-frequency elastic wave energy attenuation characteristic value from the acoustic emission signal flow, and carrying out space-time coupling on the high-frequency elastic wave energy attenuation characteristic value and a shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index; then obtaining a calibrated crack initiation tendency index based on an ambient temperature hysteresis effect and a temperature drift error of the calibrated crack initiation tendency index, and then outputting an anti-crack performance grade according to a grading deviation degree between a pre-designed grading parameter and a fluctuation range of the calibrated crack initiation tendency index; according to the technical scheme provided by the invention, the essential defect that a traditional method cannot correlate material characteristics with environmental response is overcome, direct quantitative mapping of material structure performance and damage evolution is also realized, and a traceable material-level basis is provided for engineering anti-crack design.

Description

Technical Field

[0001] The present application relates to the technical field of material testing, and in particular to a method and system for evaluating the anti-cracking performance of concrete based on its shrinkage rate. Background Art

[0002] In concrete structure engineering practice, especially in scenarios such as large-span bridges and high-rise building foundations that are subject to complex environmental temperature and humidity changes, such engineering structures are affected by the day and night temperature difference and seasonal climate cycles, and the coupling effect of concrete shrinkage strain and temperature stress is significantly enhanced. Traditional static evaluation methods are difficult to accurately reflect the dynamic initiation trend of internal microcracks.

[0003] A representative approach currently involves non-contact surface displacement monitoring based on digital image correlation technology. This involves applying an artificial speckle pattern to the concrete surface, capturing the surface displacement field during the curing process with a high-frame-rate camera, and then employing a 3D reconstruction algorithm to determine local strain concentrations, thereby inferring crack development trends. This approach utilizes computer vision technology to avoid the interference of contact sensor installation and enables visualization of global strain distribution.

[0004] While this solution enables surface displacement monitoring, it is limited by the principle of external image acquisition and cannot capture microcrack initiation at the aggregate-paste interface within concrete. Furthermore, it is difficult to distinguish between bulk thermal deformation caused by sudden temperature changes and true shrinkage cracks. When strong ambient light interferes or water vapor obscures surface texture, the signal-to-noise ratio of the image data drops sharply, rendering the strain solution ineffective. Ultimately, only the apparent strain distribution can be output, and it is unable to correlate with material gradation characteristics to achieve closed-loop evaluation of crack resistance. Summary of the Invention

[0005] The present application provides a method and system for evaluating the crack resistance of concrete based on its shrinkage rate, which is used to solve the problems in the prior art such as the inability to capture the behavior of internal microcracks, data failure caused by environmental interference, and the implementation of crack resistance evaluation without considering the material properties.

[0006] In a first aspect, the present application provides a method for evaluating crack resistance based on concrete shrinkage, comprising: Collect real-time serial data and acoustic emission signal streams of shrinkage during the curing process of concrete samples prepared with passive responsive materials based on pre-designed gradation parameters; Separating high-frequency elastic wave energy attenuation characteristic values ​​that are strongly associated with shrinkage microcrack propagation from the aggregate-paste interface waveguide effect capture region in the acoustic emission signal stream; The high-frequency elastic wave energy attenuation characteristic value is temporally and spatially coupled with the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index; Dynamically calibrating the temperature drift error of the crack initiation tendency indicator based on the ambient temperature hysteresis effect of the passive responsive material to obtain a calibrated crack initiation tendency indicator; The crack resistance performance grade is outputted according to the gradation deviation between the pre-designed gradation parameter and the fluctuation range of the calibrated crack initiation tendency index.

[0007] Optionally, collecting real-time serial data of shrinkage rate and acoustic emission signal stream of concrete samples prepared with passive responsive materials based on pre-designed gradation parameters during the curing process includes: The array acoustic wave guided sensor is pre-embedded in the aggregate-rich area of ​​the concrete sample; When the passive responsive material undergoes a volume phase change during the solidification process, the stress wave generated by the microstructural deformation of the passive responsive material itself drives the displacement of adjacent aggregates, forming a contraction displacement pulse; The array-type acoustic wave guided sensor continuously receives elastic wave signals excited by the contraction displacement pulse and reflected by the aggregate slurry interface to form an acoustic emission signal stream; According to the sequence distribution and intensity value of the contraction displacement pulse on the solidification time axis, the real-time sequence data of the contraction rate is constructed.

[0008] Optionally, separating high-frequency elastic wave energy attenuation characteristic values ​​that are strongly associated with shrinkage microcrack propagation from the aggregate-paste interface waveguide effect capture region in the acoustic emission signal flow includes: In a single contraction displacement pulse cycle, the elastic wave signal segment reflected by the aggregate slurry interface in the acoustic emission signal stream is intercepted as a basic wave energy group; Identifying a signal attenuation blind zone boundary point formed by the shortest distance position between adjacent aggregate particles in the basic fluctuation energy group; When the signal strength between the boundary points of the signal attenuation blind zone is in a continuously decreasing distribution, locking the node with continuous loss of fluctuation energy within the shortest distance position; According to the density of adjacent nodes with continuous wave energy loss in the time series, the high-frequency elastic wave energy attenuation characteristic values ​​are separated.

[0009] Optionally, the high-frequency elastic wave energy attenuation characteristic value is temporally and spatially coupled with the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index, including: Locate the waveform top event where the high-frequency elastic wave energy attenuation characteristic value reaches a peak value within a single contraction displacement pulse cycle; At the time when the waveform top event occurs, the fluctuation range of the preset time span before and after the time when the waveform top event occurs in the real-time series data of the contraction rate is intercepted; Converting the aggregate average particle size data in the pre-designed gradation parameters into a displacement constraint rate of a single displacement pulse in the concrete medium, and marking an effective shrinkage jump point when the shrinkage change amplitude within the fluctuation range exceeds the displacement constraint rate; The deviations between the occurrence time of all waveform top events and the corresponding effective shrinkage rate jump points during the solidification process are statistically analyzed to generate a crack initiation tendency index.

[0010] Optionally, converting the average aggregate particle size data in the pre-designed gradation parameters into a displacement constraint rate of a single displacement pulse in the concrete medium comprises: Determine the standard span value of the theoretical gap between aggregates in the concrete sample according to the average aggregate particle size data; A single displacement pulse conduction path is established by using the standard span value and the phase change gauge coefficient of the passive responsive material; defining a reference value of a displacement constraint rate according to a critical instability inflection point of the displacement pulse conduction path; The standard span value of the theoretical gap between the aggregates is used to correct the reference value of the displacement constraint rate to generate the displacement constraint rate of a single displacement pulse in the concrete medium.

[0011] Optionally, dynamically calibrating the temperature drift error of the crack initiation tendency indicator based on the ambient temperature hysteresis effect of the passive responsive material to obtain a calibrated crack initiation tendency indicator includes: At each temperature collection node during the curing process, record the instantaneous value of the ambient temperature and simultaneously detect the internal temperature response value of the passive responsive material; When the rate of change of the instantaneous value of the ambient temperature exceeds a preset value, a hysteresis interval identification window is triggered; In the hysteresis interval identification window, a temperature hysteresis compensation factor is constructed according to a deviation trend between the internal temperature response value and the instantaneous value of the ambient temperature; The value of the crack initiation tendency index on the corresponding time axis is multiplied by the temperature hysteresis compensation factor to generate a calibrated crack initiation tendency index.

[0012] Optionally, outputting a crack resistance performance grade according to a gradation deviation between the pre-designed gradation parameter and a fluctuation range of the calibrated crack initiation tendency index includes: Extracting the maximum critical value of the acceptable fluctuation range of gradation from the pre-designed gradation parameters; Dividing the time axis of the solidification process into equal-length detection time frames, and counting the numerical interval span of the calibrated crack initiation tendency index within each detection time frame; When the span of the numerical interval continuously exceeds the maximum critical value and the ratio reaches the phase change sensitivity coefficient of the passive responsive material, it is marked as an abnormal time frame; The crack resistance performance level is output according to the distribution density of the abnormal time frames on the time axis of the solidification process.

[0013] In a second aspect, the present application provides a system for evaluating crack resistance based on concrete shrinkage, comprising: An acquisition module is used to collect real-time serial data of shrinkage rate and acoustic emission signal stream of concrete samples prepared with passive responsive materials based on pre-designed gradation parameters during the curing process; a separation module for separating high-frequency elastic wave energy attenuation characteristic values ​​strongly associated with shrinkage microcrack propagation from the aggregate slurry interface waveguide effect capture region in the acoustic emission signal stream; A generation module is used to perform spatiotemporal coupling between the high-frequency elastic wave energy attenuation characteristic value and the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index; a calibration module for dynamically calibrating a temperature drift error of the crack initiation tendency indicator based on an ambient temperature hysteresis effect of the passive responsive material to obtain a calibrated crack initiation tendency indicator; The output module is used to output the crack resistance performance grade according to the gradation deviation between the pre-designed gradation parameter and the fluctuation range of the calibrated crack initiation tendency index.

[0014] In a third aspect, the present application provides a computing device comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for evaluating crack resistance based on concrete shrinkage rate as described in the first aspect above.

[0015] In a fourth aspect, the present application provides a computer storage medium storing a computer program. When the computer program is executed by a computer, it implements a method for evaluating crack resistance based on concrete shrinkage rate as described in the first aspect.

[0016] This application uses the synergistic effect of passive responsive materials and concrete grading parameters to simultaneously collect dual physical signal streams of shrinkage rate and acoustic emission during the curing process, directly separate the high-frequency energy attenuation characteristic values ​​related to microcracks from the aggregate interface characteristic area of ​​the acoustic emission signal, and combine with the shrinkage rate jump point to achieve accurate quantification of crack initiation tendency; further utilize the material's own temperature hysteresis effect to dynamically calibrate temperature interference, and finally perform deviation analysis on the fluctuation range of the grading parameters and the calibrated indicators, constructing a full-chain closed-loop evaluation system from the microcrack response inside the material to the structural crack resistance performance grade, solving the essential defect of traditional methods that cannot associate material properties with environmental response.

[0017] Furthermore, by dividing the solidification time axis into equal-length detection frames and counting the index interval spans, the phase change sensitivity coefficient of the passive responsive material is used as the dynamic threshold to determine the abnormal time frame, and finally the crack resistance performance grade is output according to the distribution density of the abnormal frame. This method is the first to dynamically match the concrete grading tolerance, the phase change characteristics of the smart material and the fluctuation range of the crack index in time and space, realizing the direct quantitative mapping of the material structural performance and the damage evolution, and providing a traceable material-level basis for engineering crack resistance design.

[0018] These and other aspects of the present application will become more readily apparent from the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 A flowchart of a method for evaluating crack resistance based on concrete shrinkage provided by the present application is shown; Figure 2 The present invention provides a structural schematic diagram of a system for evaluating crack resistance based on concrete shrinkage rate; Figure 3 A schematic structural diagram of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0021] In order to enable people skilled in the art to better understand the solution of this application, the technical solution of this application will be clearly and completely described below in conjunction with the drawings in this application.

[0022] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to being different types.

[0023] The following will be combined with the accompanying drawings to clearly and completely describe the technical solutions in this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of this application.

[0024] Figure 1 A flowchart of a method for evaluating the crack resistance of concrete based on its shrinkage rate is provided for this application. Figure 1 As shown, the method includes: Step 101 : collecting real-time serial data of shrinkage rate and acoustic emission signal stream of concrete sample during curing process after passive responsive material is prepared based on pre-designed gradation parameters.

[0025] In this step, the pre-designed grading parameters refer to the material structure ratio data pre-set before concrete preparation based on the aggregate particle size distribution, mineral admixture ratio and cementitious material dosage, which are used to limit the aggregate gap characteristics and material homogeneity; passive responsive materials refer to microcapsule phase change materials or shape memory alloy particles added to concrete, which are intelligent additives that can autonomously expand / contract in volume with changes in ambient temperature and humidity, and their phase change behavior directly drives internal stress changes; the real-time sequence data of shrinkage rate refers to the continuous quantitative record of the micro-deformation inside the concrete captured by the displacement sensor on the curing time axis, which directly reflects the cumulative effect of the displacement pulse triggered by the phase change of the passive responsive material; the acoustic emission signal stream refers to the time-series fluctuation signal group composed of elastic waves reflected from the aggregate slurry interface, and its energy attenuation characteristics are related to the dynamic physical process of microcrack expansion.

[0026] In this embodiment, during the pouring of concrete samples, array acoustic waveguide sensors are pre-embedded in the area of ​​highest aggregate volume concentration based on a pre-designed aggregate distribution map with pre-designed grading parameters. Once the curing process begins, the temperature gradient triggers a microscopic phase change in the passively responsive material (e.g., the melting and expansion of paraffin microcapsules). The resulting volume change generates stress waves that mechanically vibrate and drive the instantaneous displacement of adjacent aggregates, generating a quantifiable contraction displacement pulse. When this pulse reaches the sensor, the electromechanical conversion properties of the piezoelectric ceramic are utilized to capture the aggregate interface reflection wave excited by the displacement pulse, synchronously generating an acoustic emission signal stream. Simultaneously, a laser interferometer records the temporal distribution and amplitude intensity of the displacement pulse along the curing timeline and maps this information into real-time shrinkage rate sequence data, thereby achieving homologous acquisition of dual-path physical signals and synchronous binding of timestamps.

[0027] Step 102 : Separate high-frequency elastic wave energy attenuation characteristic values ​​that are strongly associated with shrinkage microcrack propagation from the aggregate-paste interface waveguide effect capture region in the acoustic emission signal stream.

[0028] In this step, the aggregate-paste interface waveguide effect capture area refers to the acoustic wave reflection path interval formed by the interface between aggregate particles and cement paste inside the concrete. This area produces a specific acoustic wave guiding effect due to the heterogeneous structure of the material. The high-frequency elastic wave energy attenuation characteristic value specifically refers to the characteristic value of the acoustic wave energy loss caused by microcrack expansion in the frequency band above 20kHz, which is used to characterize the dynamic evolution intensity of shrinkage cracks. In this embodiment, the acoustic emission signal stream is first intercepted according to a single contraction displacement pulse cycle, and the elastic wave signal segment reflected by the aggregate interface is obtained as the basic wave energy group. Then, the signal attenuation blind zone boundary points formed by the shortest spacing between adjacent aggregates in the energy group are identified. The blind zone boundary causes sound wave scattering due to the physical barrier effect of the aggregate gap. Then, the continuous downward trend of the acoustic wave signal intensity between the blind zone boundary points is detected, and the wave energy continuous loss node corresponding to the downward trend is locked. Finally, the density distribution degree of adjacent energy loss nodes on the time axis is counted, and the high-frequency elastic wave energy attenuation characteristic values ​​strongly associated with the expansion of shrinkage microcracks are separated through time series aggregation operation. This process uses the natural structure of aggregate gaps to screen acoustic wave attenuation signals, replacing artificial feature extraction algorithms with physical mechanisms to achieve high-precision capture of microcrack features.

[0029] Step 103 : performing spatiotemporal coupling between the high-frequency elastic wave energy attenuation characteristic value and the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index.

[0030] In this step, the shrinkage rate jump point refers to the mutation position in the real-time shrinkage rate series data where the change amplitude exceeds the displacement constraint rate within a specific time interval, which is used to characterize the critical behavior of local failure of the material; the crack initiation tendency index is a quantitative value constructed by the coordinated time deviation of the acoustic wave physical response and the shrinkage displacement behavior, which directly reflects the dynamic process trend of microcracks from initiation to expansion, providing an early warning for solidification risks.

[0031] In this embodiment, the peak moment of the high-frequency elastic wave energy attenuation characteristic value within a single shrinkage displacement pulse cycle is first located, and this moment is defined as the waveform top event as the time reference point. Then, with the waveform top event as the center, the fluctuation interval in the real-time series data of the shrinkage rate is intercepted by extending forward and backward for a fixed time length. Subsequently, the average aggregate particle size data in the pre-designed grading parameters is called, and the displacement constraint rate is generated by the particle size-displacement conversion rule. When the shrinkage rate change amplitude within the intercepted fluctuation interval exceeds the constraint rate, it is marked as an effective shrinkage rate jump point. Finally, the deviation of the occurrence time of all waveform top events and the corresponding jump points in the entire solidification process is counted, and the time difference sequence is aggregated into a crack initiation tendency indicator.

[0032] Step 104 : dynamically calibrating the temperature drift error of the crack initiation tendency indicator based on the ambient temperature hysteresis effect of the passive responsive material to obtain a calibrated crack initiation tendency indicator.

[0033] In this step, the ambient temperature hysteresis effect refers to the asynchronous deviation characteristics between the internal temperature response value of the passive responsive material and the instantaneous value of the ambient temperature, which is the time delay effect formed by the hysteresis of the material's thermal conduction; the temperature drift error refers to the non-crack false fluctuation of the crack initiation tendency indicator caused by the sudden change of ambient temperature. Its essence is the signal interference of thermal expansion deformation on the actual contraction behavior, which needs to be eliminated through a physical compensation mechanism.

[0034] In this embodiment, the instantaneous value of the ambient temperature and the internal temperature response value of the passively responsive material are first synchronously acquired at each acquisition node on the curing timeline to construct a dual-temperature monitoring data stream; when the rate of change of the monitored ambient temperature exceeds a preset critical value, the hysteresis interval identification window is immediately triggered; within this window, the continuous hysteresis deviation trend of the internal temperature response value relative to the instantaneous value of the ambient temperature is extracted, and a dynamic temperature hysteresis compensation factor is constructed based on the slope direction and amplitude of the trend; finally, the original value of the crack initiation tendency index at the corresponding time point is multiplied by the compensation factor to generate a calibrated crack initiation tendency index in real time after the temperature drift is eliminated.

[0035] Step 105 : outputting a crack resistance performance grade according to a gradation deviation between the pre-designed gradation parameter and a fluctuation range of the calibrated crack initiation tendency index.

[0036] In this step, gradation deviation refers to the cumulative degree of deviation of the actual fluctuation range of the calibrated crack initiation tendency index beyond the allowable critical value of the pre-designed gradation parameter, which is used to quantify the physical deviation of the material structural behavior from the design benchmark; the crack resistance performance grade is a comprehensive assessment result based on the clustering density of crack risks in the time dimension, which directly corresponds to the durability safety threshold of the engineering structure and provides a grading basis for maintenance decisions.

[0037] In this embodiment, the maximum fluctuation critical value allowed by the aggregate gradation tolerance is first extracted from the pre-designed gradation parameters as a baseline; then, the detection time frame is equally spaced on the curing process time axis, and the numerical interval span statistics of the calibrated crack initiation tendency index within each time frame are performed, and this span reflects the local fluctuation intensity; when the span within a single time frame continuously exceeds the critical value at a ratio that reaches the phase change sensitivity coefficient of the passive responsive material, it is determined to be an abnormal time frame to mark a high-risk period; finally, the distribution density of all abnormal time frames on the entire time axis is calculated, and the crack resistance performance level is directly output through the density segment mapping rule.

[0038] The following is a specific embodiment of steps 101 to 105: For example, during the curing process of the concrete foundation of a cross-sea bridge after pouring, facing the high salt fog and large temperature difference environment, the acoustic emission signal stream and real-time series data of shrinkage rate of concrete samples doped with microcapsule phase change materials are synchronously collected through a pre-embedded sensor array; the acoustic emission signal stream captures the elastic wave reflection at the aggregate-paste interface, and the shrinkage rate data is generated by accumulating displacement pulses triggered by the phase change material. The two together constitute the physical data basis for monitoring curing microcracks, providing dual-channel signal input for subsequent analysis.

[0039] Relying on the above-mentioned acoustic emission signal stream, the aggregate interface reflection wave signal segment within a single contraction displacement pulse cycle is intercepted to identify the boundary points of the acoustic wave attenuation blind zone formed by the minimum spacing between adjacent aggregates; after detecting the continuous downward trend of the signal intensity between the boundaries, the fluctuation energy loss node is locked, and finally the high-frequency elastic wave energy attenuation characteristic value is separated according to the time density of the node, accurately capturing the acoustic characteristics of the micro-crack expansion inside the concrete under sea breeze load, and avoiding the interference of surface corrosion on monitoring.

[0040] The peak moment of the high-frequency elastic wave energy attenuation characteristic value is further taken as the waveform top event, and the shrinkage rate fluctuation range is intercepted before and after the occurrence time point; the aggregate particle size data in the grading parameters is converted into displacement constraint rate, and the effective shrinkage rate jump points exceeding the threshold in the fluctuation range are screened; the time difference series between the waveform top event and the jump point in the full curing cycle are statistically analyzed to generate a crack initiation tendency index reflecting the microcrack initiation efficiency in the cross-sea environment, thereby eliminating the false signal coupling caused by tidal cycles.

[0041] Based on the harsh environment of the bridge where the temperature difference between day and night can reach 20°C, the temperature hysteresis characteristics of the microcapsule phase change material are utilized: when a sudden change in the instantaneous value of the ambient temperature is monitored, the hysteresis window is triggered and the temperature response deviation trend inside the material is compared to construct a dynamic compensation factor; the crack initiation tendency index is multiplied point by point on the time axis with the compensation factor to eliminate false fluctuations caused by changes in the heat capacity of seawater, and the true crack index after temperature drift calibration is output to ensure data reliability during typhoon passage.

[0042] Finally, based on the gradation design standard for cap concrete, the critical value of allowable fluctuation in aggregate gradation was extracted. The calibrated crack index was divided into equally spaced detection frames on the 30-day curing timeline, and the index span within each frame was counted. When the proportion of spans continuously exceeding the critical value reached the sensitivity coefficient of the phase change material, an abnormal frame was marked. Finally, based on the spatiotemporal clustering density of abnormal frames within the tidal cycle, a crack resistance performance grade of "Grade A (low risk)" to "Grade D (urgent maintenance)" was output, directly guiding maintenance decisions for cross-sea bridges.

[0043] As an practicable embodiment, according to step 101, collecting real-time serial data of shrinkage rate and acoustic emission signal stream of a concrete sample after preparing a passive responsive material based on pre-designed gradation parameters during the curing process includes: In step 201 , an array of acoustic wave guidance sensors is pre-embedded in an aggregate-rich area of ​​a concrete sample.

[0044] In this step, the aggregate-enriched area refers to the local high-density aggregation area of ​​aggregate particles determined according to the pre-designed grading parameters during the preparation of the concrete sample. This area forms an acoustic wave reflection hotspot due to the interface effect between the aggregate and the paste; the array-type acoustic wave guide sensor is a grid-shaped detection component composed of multiple piezoelectric ceramic units. Its pre-buried position strictly matches the aggregate spatial distribution map and is used to directionally capture the interface elastic wave signal.

[0045] In this embodiment, the spatial coordinate cluster with the highest aggregate volume ratio within the concrete sample is first located based on the aggregate spatial distribution model with pre-designed grading parameters. Then, during the pouring phase, the array of acoustic wave guidance sensors is fixed to the core intersection of this coordinate cluster, ensuring that the sensor detection surface is facing the direction of the gap between adjacent aggregates. After the concrete solidifies and forms, this deployment method enables the sensor array to be directly embedded in the acoustic wave conduction path at the interface of the aggregate-pasture, establishing a physical channel foundation for the subsequent capture of reflected signals related to shrinkage microcracks.

[0046] Step 202 : When the passive responsive material undergoes a volume phase change during the solidification process, the stress wave generated by the microstructure deformation of the passive responsive material itself drives the displacement of adjacent aggregates, thereby forming a contraction displacement pulse.

[0047] In this step, volume phase change refers to the microscopic lattice expansion or contraction behavior of passive responsive materials under changes in concrete curing temperature and humidity, and the strain energy generated is transmitted through intermolecular forces; stress wave drive refers to the elastic stress wave released when the phase change material deforms, which propagates in the concrete medium, causing the instantaneous movement effect of adjacent aggregates to overcome static friction; the contraction displacement pulse is a discrete record in the time domain of the mechanical displacement event formed after the adjacent aggregates are driven, which is used to characterize the dynamic accumulation process of microscopic contraction inside the material.

[0048] In this embodiment, when a passively responsive material's lattice reorganizes due to ambient temperature changes, its microstructural deformation releases elastic stress waves that propagate through the concrete medium as spherical waves. When these stress waves reach the contact points of aggregate particles, they force the aggregate to overcome interfacial static friction and produce instantaneous displacement. This displacement is transmitted through the slurry bond, forming a continuous displacement sequence that is ultimately recorded as a pulse signal as a contraction displacement pulse. This entire process utilizes the natural conversion of material phase change energy into mechanical energy, achieving physical quantification of contraction behavior without external excitation.

[0049] Step 203 : continuously receiving elastic wave signals excited by the contraction displacement pulse and reflected by the aggregate slurry interface through the arrayed acoustic wave guided sensor to form an acoustic emission signal stream.

[0050] In this step, contraction displacement pulse excitation refers to the process in which the kinetic energy of aggregate particles is converted into elastic vibration energy and released in the concrete medium when the aggregate particles are driven by stress waves to produce instantaneous displacement; aggregate-paste interface reflection refers to the signal scattering and reflection phenomenon caused by the sudden change of acoustic impedance when the elastic wave propagates to the interface between aggregate and cement paste.

[0051] In this embodiment, when a contraction displacement pulse triggers instantaneous displacement of the aggregate, the released elastic vibration energy propagates along the concrete medium to the aggregate-paste interface, forming a reflected wave due to the difference in material acoustic impedance. The arrayed acoustic wave guide sensor continuously captures the original analog signal of the reflected wave at the embedded position, and generates a time-amplitude sequence stream after analog-to-digital conversion. This signal stream fully records the attenuation morphology of the reflected wave within each displacement pulse cycle, forming the acoustic emission data foundation required for microcrack analysis.

[0052] Step 204 : constructing real-time sequence data of shrinkage rate according to the sequence distribution and intensity value of the shrinkage displacement pulse on the solidification time axis.

[0053] In this step, the curing time axis is a continuous sequence of time coordinates from the initial setting to the final setting of the concrete sample, which is used to mark the absolute timing of physical events; the sequence distribution of the contraction displacement pulse refers to the combination pattern of the occurrence interval and duration of the pulse event on the time axis, and the intensity value represents the cumulative scalar of the displacement amplitude of a single pulse. The two together define the spatiotemporal intensity characteristics of the contraction behavior.

[0054] In this embodiment, the precise occurrence time and duration of all shrinkage displacement pulses on the solidification time axis are first extracted to establish a pulse time series distribution map; the integral value of the aggregate displacement amplitude corresponding to each pulse is synchronously collected as the intensity value; then the intensity values ​​of the discrete pulses are arranged continuously according to the time series distribution, and a time-displacement curve is generated by pulse accumulation; finally, the curve is normalized to the shrinkage rate per unit time according to the solidification process, and continuous shrinkage rate real-time series data is constructed.

[0055] As another embodiment, according to step 102, separating high-frequency elastic wave energy attenuation characteristic values ​​strongly associated with shrinkage microcrack propagation from the aggregate-paste interface waveguide effect capture region in the acoustic emission signal stream includes: Step 301 : within a single contraction displacement pulse cycle, intercepting the elastic wave signal segment reflected by the aggregate slurry interface in the acoustic emission signal stream as a basic wave energy group.

[0056] In this step, a single contraction displacement pulse cycle refers to the complete time interval corresponding to the completion of a volume phase change of the passive responsive material. The material stress release and aggregate displacement behavior within this cycle constitute a discrete event unit; the elastic wave signal segment reflected at the aggregate-slurry interface refers to a continuous waveform slice in the time domain of the reflected wave formed by the difference in acoustic impedance of the aggregate-slurry in the acoustic emission signal stream; the basic wave energy group is the set of all original amplitude values ​​contained in this signal segment, which is used to characterize the original distribution state of the acoustic wave energy in a single physical event.

[0057] In this embodiment, the start and end time marks of a single contraction displacement pulse are first determined, and the corresponding segment of the acoustic emission signal stream is intercepted within this time window. Then, the elastic wave signals reflected from all aggregate-paste interfaces within this segment are extracted, and the waveform envelope of their original amplitude varying with time is retained. This signal envelope completely records the interfacial reflection energy distribution excited by a single material phase change, forming a basic wave energy group that is not contaminated by environmental noise.

[0058] Step 302: Identify the signal attenuation blind zone boundary point formed by the shortest distance position between adjacent aggregate particles in the basic fluctuation energy group.

[0059] In this step, the shortest spacing position between adjacent aggregate particles is the adjacent area of ​​the aggregate space determined by the grading parameters. This position forms the minimum path in the sound wave propagation path due to the physical gap between the aggregates; the signal attenuation blind zone boundary point specifically refers to the energy drop inflection point caused by sound wave scattering at both ends of the shortest spacing position, and its spatial coordinates are uniquely determined by the aggregate arrangement configuration.

[0060] In this embodiment, based on the spatial coordinates of the embedded sensor array and the aggregate gradation distribution model, the spatial coordinates of the shortest spacing between adjacent aggregate pairs corresponding to the basic wave energy group are located; by comparing the amplitude attenuation slopes of the elastic wave on both sides of the coordinates, the starting point of the sudden drop and the ending point of the rebound of the acoustic wave energy from normal propagation into the aggregate gap area are identified; these two points are the boundary points of the attenuation blind zone.

[0061] Step 303: When the signal strength between the boundary points of the signal attenuation blind zone is in a continuously decreasing distribution, the node where the fluctuation energy is continuously lost within the shortest distance position is locked.

[0062] In this step, the continuous decline distribution of signal intensity refers to the non-fluctuating attenuation form of the sound wave amplitude between the boundary points of the attenuation blind zone showing a unidirectional decreasing trend over time, which represents the physical process of continuous absorption of sound wave energy; the node of continuous loss of fluctuating energy is the discrete time position where the energy dissipation rate suddenly changes in this continuous decline section, corresponding to the characteristic moment when the microcracks stably expand and penetrate the gaps in the aggregate.

[0063] In this embodiment, by real-time monitoring of the changes in the sound wave amplitude within the attenuation blind zone boundary point interval, a continuous decreasing sequence is detected in which the amplitude at all subsequent moments is strictly smaller than that at the previous moment; when the decreasing sequence continues to exceed the sound wave conduction time corresponding to the distance from the blind zone boundary point, it is determined to be a state of continuous energy loss; in the locked state, the slope change points of the amplitude-time curve of the interval are scanned to capture the instantaneous inflection point where the energy dissipation rate increases sharply, and the time position of the inflection point is defined as the node of continuous loss of fluctuating energy.

[0064] Step 304 : Separate the high-frequency elastic wave energy attenuation characteristic values ​​based on the density of adjacent nodes with continuous wave energy loss in the time series.

[0065] In this step, the density of nodes with continuous loss of fluctuating energy refers to the degree of spatiotemporal aggregation of multiple loss nodes on the solidified time axis, which is quantified by the inverse of the time interval between adjacent nodes.

[0066] In this embodiment, the occurrence times of all nodes with continuous wave energy loss within a single contraction displacement pulse cycle are first counted, and a discrete node sequence is constructed in chronological order; the time intervals between nodes are calculated and an interval distribution histogram is generated; the node cluster corresponding to the area with the smallest interval value in the histogram is identified, and the integral amount of acoustic wave energy loss of the nodes in the cluster is extracted; finally, the energy spectra of the high-loss nodes in all pulse cycles in the full curing process are aggregated into high-frequency elastic wave energy attenuation characteristic values.

[0067] As another embodiment, according to step 103, the high-frequency elastic wave energy attenuation characteristic value is spatiotemporally coupled with the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index, including: Step 401: locate the waveform top event where the high-frequency elastic wave energy attenuation characteristic value reaches a peak value within a single contraction displacement pulse period.

[0068] In this step, the waveform top event refers to the physical event moment when the characteristic value of the high-frequency elastic wave energy attenuation reaches the highest energy amplitude within a single contraction displacement pulse cycle. This moment corresponds to the peak release state of the acoustic wave energy during the reflection process at the aggregate interface, and represents the extreme point of the acoustic response of microcrack expansion; its positioning result is used as the time reference anchor point for spatiotemporal coupling to synchronize the associated shrinkage rate jump behavior.

[0069] In this embodiment, the energy amplitude change curve of the high-frequency elastic wave energy attenuation characteristic value within a single contraction displacement pulse cycle is monitored in real time, and the amplitude increment signs of adjacent time points are continuously recorded; when a sudden inflection point where the increment sign changes from positive to negative is detected, the time point before the inflection point is determined to be the global highest position of the energy amplitude; the moment corresponding to this position is defined as the moment when the waveform top event occurs.

[0070] Step 402 : At the time of occurrence of the waveform top event, a fluctuation range of a preset time span before and after the time of occurrence in the real-time series data of the contraction rate is intercepted.

[0071] In this step, the preset time span is a physical time window determined by the acoustic wave conduction velocity of concrete and the average particle size of aggregate. Its width ensures that the complete path length of the acoustic wave from excitation to reflection is covered; the fluctuation range is the data segment in the real-time sequence data of shrinkage rate, centered on the waveform top event moment and extending back and forth by the time span, which is used to capture the sudden change behavior of shrinkage displacement that is strongly associated with acoustic events.

[0072] In this embodiment, the theoretical propagation time of the sound wave in the aggregate gap is first calculated based on the aggregate particle size data and the concrete elastic modulus in the pre-designed grading parameters; this propagation time is expanded to a fixed time span as a capture window; then, with the time when the waveform top event output in step 401 occurs as the center point of the time axis, the time span is extended forward and backward to capture the corresponding segment of the shrinkage rate real-time sequence data; this segment completely contains the shrinkage displacement response that may be triggered by the sound wave event, forming the data basis for subsequent jump point identification.

[0073] Step 403 : Convert the aggregate average particle size data in the pre-designed gradation parameters into a displacement constraint rate of a single displacement pulse in the concrete medium. When the shrinkage rate variation within the fluctuation range exceeds the displacement constraint rate, it is marked as an effective shrinkage rate jump point.

[0074] In this step, the displacement constraint rate refers to the maximum allowable displacement change of a single displacement pulse in the concrete medium. It is the upper limit of physical displacement conduction determined by the average particle size of the aggregate and is used to distinguish real shrinkage cracks from thermal expansion false signals. The effective shrinkage rate jump point is a mutation event marked when the shrinkage rate change within the fluctuation range exceeds the constraint rate, representing the critical state of local instability of the material.

[0075] In this embodiment, the average aggregate particle size data in the pre-designed grading parameters is first called, and the maximum transmissible displacement of a single displacement pulse in the aggregate gap is calculated in combination with the elastic modulus of concrete, which is defined as the displacement constraint rate. Subsequently, the shrinkage rate fluctuation interval intercepted in step 402 is scanned to identify the cumulative value of the shrinkage rate changes at consecutive time points in the interval. When the cumulative value exceeds the displacement constraint rate, it is determined that local material yield behavior exists in the interval and is marked as an effective shrinkage rate jump point.

[0076] Step 404 , the deviations between the occurrence times of all waveform top events and corresponding effective shrinkage rate jump points during the solidification process are counted to generate a crack initiation tendency index.

[0077] In this step, the deviation at the time of occurrence refers to the absolute time difference between the waveform top event and the corresponding effective shrinkage rate jump point, reflecting the conduction delay of the acoustic energy release and the shrinkage displacement response; the crack initiation tendency index is the statistical distribution value of all deviations in the full solidification process aggregated in time series, and the evolution trend intensity of microcracks from initiation to expansion is mapped through the time difference concentration.

[0078] In this embodiment, the occurrence time of each waveform top event and its corresponding effective shrinkage rate jump point are extracted, and the absolute time difference between the two is calculated; all time differences within the entire curing cycle are arranged in chronological order to generate a discrete time difference sequence; a time axis alignment aggregation operation is performed on the sequence, and the main peak area is identified through the time difference density distribution histogram; finally, the time difference concentration in the main peak area is quantified as a crack initiation tendency indicator.

[0079] As another embodiment, according to step 403, converting the aggregate average particle size data in the pre-designed gradation parameters into a displacement constraint rate of a single displacement pulse in the concrete medium includes: Step 501: determining a standard span value of a theoretical gap between aggregates in a concrete sample according to the average aggregate particle size data.

[0080] In this step, the standard span value of the theoretical aggregate gap refers to the theoretical expected value of the minimum clear distance between adjacent aggregate particles calculated by the geometric topological rules based on the aggregate particle size distribution model in the pre-designed gradation parameters. This value reflects the physical path limit of the aggregate stacking structure inside the concrete and is used to define the spatial constraint boundary of displacement conduction.

[0081] In this embodiment, the aggregate particle size distribution histogram of the pre-designed gradation parameters is first analyzed to identify the median value of the dominant particle size range. Based on the spatial geometric relationship of the sphere close packing theory, the minimum gap distance of the median aggregate in the hexagonal closest packing model is calculated. This distance is corrected by combining the cement paste shrinkage compensation coefficient, and finally the standard span value of the theoretical gap between aggregates in the concrete sample is output.

[0082] Step 502 : establishing a single displacement pulse conduction path by using the standard span value and the phase change gauge coefficient of the passive responsive material.

[0083] In this step, the phase change strain coefficient is an inherent property parameter that characterizes the microscopic lattice deformation ability of the passive responsive material under unit temperature change, and its value is uniquely determined by the chemical composition of the material; the single displacement pulse conduction path refers to the energy transfer trajectory constrained by the gap span and material strain characteristics when the stress wave released by the phase change material propagates in the aggregate gap network. The integrity of this path determines the effective conduction range of the displacement pulse.

[0084] In this embodiment, based on the theoretical standard span value of the aggregate gap output in step 501 and combined with the phase change strain coefficient of the passive responsive material, the maximum transmissible strain energy of the stress wave when passing through the minimum gap is calculated. Based on the spatial attenuation gradient of this strain energy threshold in the concrete medium, the optimal energy transfer trajectory from the phase change material excitation point to the aggregate displacement point is plotted. Ultimately, this trajectory is defined as the single displacement pulse conduction path, and its spatial coordinates are integrated to form the physical basis for the subsequent calculation of the displacement constraint rate.

[0085] Step 503 : defining a reference value of the displacement constraint rate according to the critical instability inflection point of the displacement pulse conduction path.

[0086] In this step, the critical instability inflection point refers to the spatial position where the strain energy transfer efficiency in the displacement pulse conduction path suddenly drops, and the stress wave conduction path is locally interrupted at this position due to a geometric mutation of the aggregate gap or a slurry defect; the benchmark value of the displacement constraint rate is the initial displacement upper limit defined according to the maximum conductive strain energy loss ratio at this inflection point, which represents the physical conduction limit of a single displacement pulse under ideal material conditions.

[0087] In this embodiment, a strain energy spatial attenuation gradient analysis is first performed on the displacement pulse conduction path established in step 502 to detect geometric discontinuities where the slope suddenly increases on the path curve. By calculating the jump amplitude of the strain energy attenuation rate before and after this point, the location where the path conduction efficiency drops sharply is determined to be the critical instability inflection point. Subsequently, the maximum allowable strain energy loss ratio at the inflection point is extracted and mapped to the initial reference value of the displacement constraint rate.

[0088] Step 504 : Using the standard span value of the theoretical gap between aggregates, the reference value of the displacement constraint rate is corrected to generate the displacement constraint rate of a single displacement pulse in the concrete medium.

[0089] In this step, the standard span value of the theoretical aggregate gap is the physical quantity of the minimum net distance between aggregates output in step 501, and its value is determined by the grading parameters and the rigidity of the geometric topology rules. The displacement constraint rate is the final displacement conduction upper limit after geometric correction of the reference value by the standard span value, reflecting the actual constraint ability of the aggregate gap on the displacement pulse in the real concrete medium.

[0090] In this embodiment, based on the standard span value of the theoretical aggregate gap in step 501, a negative correlation mapping function is established between the span value and the displacement constraint rate correction coefficient; the displacement constraint rate reference value defined in step 503 is called and input into the mapping function to generate a geometric correction factor; finally, the reference value is multiplied by the correction factor to output the displacement constraint rate of a single displacement pulse in the concrete medium.

[0091] As another embodiment, according to step 104, dynamically calibrating the temperature drift error of the crack initiation tendency indicator based on the ambient temperature hysteresis effect of the passive responsive material to obtain the calibrated crack initiation tendency indicator includes: Step 601 : At each temperature collection node during the curing process, the instantaneous value of the ambient temperature is recorded, and the internal temperature response value of the passive responsive material is detected simultaneously.

[0092] In this step, the temperature collection node refers to the temperature recording position point divided at fixed time intervals on the concrete curing time axis, and its density is determined by the thermal conductivity rate of the passive responsive material; the instantaneous value of the ambient temperature is the real-time temperature sampling value in the microenvironment of the concrete sample surface, reflecting the external thermal disturbance input; the internal temperature response value is the lagged temperature feedback generated when the internal lattice structure of the passive responsive material is deformed by heat, which characterizes the thermal inertia characteristics of the material itself.

[0093] In this embodiment, at each fixed time interval node during the curing process, the instantaneous value of the ambient temperature is synchronously collected by a surface contact thermocouple, and at the same time, a micro-temperature sensor embedded in the passive responsive material is used to detect the internal temperature response value caused by the lattice deformation hysteresis. This dual temperature data stream records the response hysteresis characteristics of the material to external temperature changes in real time, providing a physical comparison basis for subsequent hysteresis compensation. The acquisition frequency is dynamically adjusted by the thermal conductivity coefficient of the material.

[0094] Step 602: When the rate of change of the instantaneous value of the ambient temperature exceeds a preset value, a hysteresis interval identification window is triggered.

[0095] In this step, the hysteresis interval identification window is an analysis interval defined on the time axis to focus on the temperature hysteresis effect when the rate of change exceeds a threshold. Its width is proportional to the material's thermal inertia constant. In this embodiment, the differential change in the instantaneous ambient temperature between adjacent acquisition nodes is calculated in real time. When the absolute value of this differential change exceeds a preset thermal disturbance critical threshold, the hysteresis interval identification window is immediately extended backward from the current moment by the time corresponding to the material's thermal inertia constant to define the hysteresis interval identification window. This window dynamically identifies the maximum delayed impact period of external temperature changes on the material's internal response, providing a time boundary for the precise construction of compensation factors.

[0096] Step 603 : constructing a temperature hysteresis compensation factor according to a deviation trend between the internal temperature response value and the instantaneous value of the ambient temperature within the hysteresis interval identification window.

[0097] In this step, the deviation trend refers to the monotonic trend of the difference between the internal temperature response value and the instantaneous value of the ambient temperature within the hysteresis window over time, which includes two typical modes: linear hysteresis and exponential convergence. The temperature hysteresis compensation factor is a dynamic scaling coefficient generated according to the sign and amplitude of the trend slope, which is used to reversely correct the signal distortion caused by thermal expansion.

[0098] In this embodiment, the difference between the internal temperature response value and the corresponding instantaneous value of the ambient temperature is calculated in a time series within the hysteresis window, and a first-order change trend line of the difference sequence is fitted; when the trend line is monotonically increasing, a negative compensation factor less than 1 is generated, and when it is decreasing, a positive compensation factor greater than 1 is generated, and the factor amplitude is determined by the product of the absolute value of the trend line slope and the latent heat of the material phase change.

[0099] Step 604 : multiply the value of the crack initiation tendency index on the corresponding time axis by the temperature hysteresis compensation factor to generate a calibrated crack initiation tendency index.

[0100] In this step, the time axis correspondence refers to the mapping relationship between each data point of the crack initiation tendency index and the temperature acquisition node, which is strictly time-aligned; the calibrated crack initiation tendency index is the output sequence after the original index value and the compensation factor are multiplied point by point at the same time point. Its physical essence is the real crack evolution signal after the stripping temperature drift.

[0101] In this embodiment, the original crack initiation tendency index data points for the time period covered by the hysteresis window are extracted, and their timestamps are precisely matched with the temperature acquisition nodes; the temperature hysteresis compensation factors generated in step 603 are synchronously mapped to each data point according to the timestamp; a point-to-point multiplication operation is performed, and a calibrated crack initiation tendency index after thermal noise elimination is output.

[0102] As another embodiment, according to step 105, outputting a crack resistance performance grade according to a gradation deviation between the pre-designed gradation parameter and a fluctuation range of the calibrated crack initiation tendency index includes: Step 701: extracting the maximum critical value of the acceptable fluctuation range of gradation from the pre-designed gradation parameters.

[0103] In this step, the maximum critical value of the acceptable gradation fluctuation range refers to the upper limit threshold of the displacement fluctuation allowed by the aggregate particle size distribution tolerance in the pre-designed gradation parameters. This value is determined by the safety factor in the concrete structure design code and the extreme point of the aggregate gradation curve, and is used to define the physical safety boundary of the material shrinkage behavior.

[0104] In this embodiment, the aggregate gradation cumulative distribution curve of the pre-designed gradation parameters is analyzed to locate the particle size extreme value interval corresponding to the sudden change position of the inflection point slope in the curve; the maximum allowable displacement fluctuation corresponding to this particle size interval is calculated in combination with the displacement tolerance coefficient in the durability design standard of concrete structures; and finally, this fluctuation is output as the maximum critical value of the acceptable fluctuation range of the gradation. The extraction process strictly follows the rigid mapping relationship between material mechanics and structural design specifications.

[0105] Step 702 : dividing the time axis of the solidification process into detection time frames of equal length, and counting the numerical interval span of the calibrated crack initiation tendency index within each detection time frame.

[0106] In this step, the detection time frame is an analysis unit divided into equal time periods on the time axis of the solidification process, and its division density is determined by the phase change response period of the passive responsive material; the span of the numerical interval is the difference between the maximum and minimum values ​​of the calibrated crack initiation tendency index within a single detection time frame, reflecting the absolute fluctuation range of the crack evolution intensity within this time period.

[0107] In this embodiment, the curing process time axis is first divided into several equal-length time periods as detection time frames based on the typical phase change cycle length of the passive responsive material. For each time frame, all calibrated crack initiation tendency indicator data points within the frame are extracted, and their global maximum and minimum values ​​are identified. The difference between the two is calculated as the numerical interval span of the time frame, and a span value sequence is generated for subsequent anomaly detection.

[0108] Step 703: When the span of the numerical interval continuously exceeds the maximum critical value at a ratio reaching the phase change sensitivity coefficient of the passive responsive material, it is marked as an abnormal time frame.

[0109] In this step, the phase change sensitivity coefficient is an inherent property parameter that characterizes the sensitivity of passive responsive materials to crack extension energy fluctuations, and its value is determined by the material microstructure; the abnormal time frame refers to the time marker unit that is judged as a high-risk crack evolution period when the proportion of the numerical interval span within the detection time frame continuously exceeds the maximum critical value and reaches this coefficient.

[0110] In this embodiment, the proportion of the duration in which the span of the numerical interval of each detection time frame exceeds the maximum critical value is calculated; the proportion is compared with the phase change sensitivity coefficient of the passive responsive material, and when the proportion value is greater than or equal to the phase change sensitivity coefficient, the time frame is determined to be in an abnormal state; finally, the abnormal state time frame is marked as a red warning interval on the time axis, forming a thermal map of the spatiotemporal distribution of crack risk.

[0111] Step 704: outputting a crack resistance performance level according to the distribution density of the abnormal time frames on the time axis of the solidification process.

[0112] In this step, the distribution density of abnormal time frames refers to the ratio of the number of time frames marked as abnormal to the total number of detected time frames. This density value directly reflects the overall crack risk level of the concrete structure.

[0113] In this embodiment, the number of all marked abnormal time frames is counted, and its percentage of the total number of detected time frames is calculated as the distribution density value; the density value is mapped to the corresponding crack resistance performance grade according to the density grading threshold interval preset in the project acceptance standard (such as 0-20% for Grade A, 20-40% for Grade B, etc.); and the grade is finally output as the final evaluation conclusion of the crack resistance performance of the concrete sample.

[0114] Figure 2 This application provides a structural diagram of a crack resistance evaluation system based on concrete shrinkage rate, such as Figure 2 As shown, the system includes: The acquisition module 21 is used to collect the real-time serial data of shrinkage rate and acoustic emission signal stream of the concrete sample after the passive responsive material is prepared based on the pre-designed gradation parameters during the curing process; A separation module 22 is configured to separate high-frequency elastic wave energy attenuation characteristic values ​​that are strongly associated with shrinkage microcrack propagation from the aggregate slurry interface waveguide effect capture region in the acoustic emission signal stream; A generating module 23 is configured to perform spatiotemporal coupling between the high-frequency elastic wave energy attenuation characteristic value and the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index; A calibration module 24 is configured to dynamically calibrate a temperature drift error of the crack initiation tendency indicator based on an ambient temperature hysteresis effect of the passive responsive material to obtain a calibrated crack initiation tendency indicator; The output module 25 is configured to output a crack resistance performance grade according to a gradation deviation between the pre-designed gradation parameter and a fluctuation range of the calibrated crack initiation tendency index.

[0115] Figure 2 The anti-cracking performance evaluation system based on concrete shrinkage rate can be performed Figure 1 The implementation principle and technical effects of the method for evaluating crack resistance based on concrete shrinkage described in the illustrated embodiment are not further elaborated. The specific manner in which each module and unit performs operations in the aforementioned method for evaluating crack resistance based on concrete shrinkage has been described in detail in the related embodiments and will not be further elaborated here.

[0116] In one possible design, Figure 2 The crack resistance evaluation system based on concrete shrinkage rate of the embodiment shown can be implemented as a computing device, such as Figure 3As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0117] The processing component 32 is used for the above Figure 1 The embodiment provides a method for evaluating crack resistance based on concrete shrinkage.

[0118] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0119] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0120] Of course, a computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0121] The input / output interface provides an interface between the processing component and the peripheral interface module, which can be an output device, an input device, etc.

[0122] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0123] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0124] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The embodiment shown is a method for evaluating the crack resistance of concrete based on its shrinkage rate.

[0125] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0126] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0127] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for evaluating crack resistance based on concrete shrinkage, characterized in that: include: Collect real-time serial data and acoustic emission signal streams of shrinkage during the curing process of concrete samples prepared with passive responsive materials based on pre-designed gradation parameters; Separating high-frequency elastic wave energy attenuation characteristic values ​​that are strongly associated with shrinkage microcrack propagation from the aggregate-paste interface waveguide effect capture region in the acoustic emission signal stream; The high-frequency elastic wave energy attenuation characteristic value is temporally and spatially coupled with the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index; Dynamically calibrating the temperature drift error of the crack initiation tendency indicator based on the ambient temperature hysteresis effect of the passive responsive material to obtain a calibrated crack initiation tendency indicator; The crack resistance performance grade is outputted according to the gradation deviation between the pre-designed gradation parameter and the fluctuation range of the calibrated crack initiation tendency index.

2. The method according to claim 1, characterized in that Collect real-time shrinkage data and acoustic emission signal streams during the curing process of concrete samples prepared with passive responsive materials based on pre-designed gradation parameters, including: The array acoustic wave guided sensor is pre-embedded in the aggregate-rich area of ​​the concrete sample; When the passive responsive material undergoes a volume phase change during the solidification process, the stress wave generated by the microstructural deformation of the passive responsive material itself drives the displacement of adjacent aggregates, forming a contraction displacement pulse; The array-type acoustic wave guided sensor continuously receives elastic wave signals excited by the contraction displacement pulse and reflected by the aggregate slurry interface to form an acoustic emission signal stream; According to the sequence distribution and intensity value of the contraction displacement pulse on the solidification time axis, the real-time sequence data of the contraction rate is constructed.

3. The method according to claim 1, characterized in that The high-frequency elastic wave energy attenuation characteristic value strongly associated with the expansion of shrinkage microcracks is separated from the aggregate paste interface waveguide effect capture area in the acoustic emission signal flow, including: In a single contraction displacement pulse cycle, the elastic wave signal segment reflected by the aggregate slurry interface in the acoustic emission signal stream is intercepted as a basic wave energy group; Identifying a signal attenuation blind zone boundary point formed by the shortest distance position between adjacent aggregate particles in the basic fluctuation energy group; When the signal strength between the boundary points of the signal attenuation blind zone is in a continuously decreasing distribution, locking the node with continuous loss of fluctuation energy within the shortest distance position; According to the density of adjacent nodes with continuous wave energy loss in the time series, the high-frequency elastic wave energy attenuation characteristic values ​​are separated.

4. The method according to claim 1, wherein The high-frequency elastic wave energy attenuation characteristic value is temporally and spatially coupled with the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index, including: Locate the waveform top event where the high-frequency elastic wave energy attenuation characteristic value reaches a peak value within a single contraction displacement pulse cycle; At the time when the waveform top event occurs, the fluctuation range of the preset time span before and after the time when the waveform top event occurs in the real-time series data of the contraction rate is intercepted; Converting the aggregate average particle size data in the pre-designed gradation parameters into a displacement constraint rate of a single displacement pulse in the concrete medium, and marking an effective shrinkage jump point when the shrinkage change amplitude within the fluctuation range exceeds the displacement constraint rate; The deviations between the occurrence time of all waveform top events and the corresponding effective shrinkage rate jump points during the solidification process are statistically analyzed to generate a crack initiation tendency index.

5. The method according to claim 4, characterized in that Converting the average aggregate particle size data in the pre-designed gradation parameters into a displacement constraint rate of a single displacement pulse in the concrete medium includes: Determine the standard span value of the theoretical gap between aggregates in the concrete sample according to the average aggregate particle size data; A single displacement pulse conduction path is established by using the standard span value and the phase change gauge coefficient of the passive responsive material; defining a reference value of a displacement constraint rate according to a critical instability inflection point of the displacement pulse conduction path; The standard span value of the theoretical gap between the aggregates is used to correct the reference value of the displacement constraint rate to generate the displacement constraint rate of a single displacement pulse in the concrete medium.

6. The method according to claim 1, characterized in that Dynamically calibrating the temperature drift error of the crack initiation tendency indicator based on the ambient temperature hysteresis effect of the passive responsive material to obtain a calibrated crack initiation tendency indicator includes: At each temperature collection node during the curing process, record the instantaneous value of the ambient temperature and simultaneously detect the internal temperature response value of the passive responsive material; When the rate of change of the instantaneous value of the ambient temperature exceeds a preset value, a hysteresis interval identification window is triggered; In the hysteresis interval identification window, a temperature hysteresis compensation factor is constructed according to a deviation trend between the internal temperature response value and the instantaneous value of the ambient temperature; The value of the crack initiation tendency index on the corresponding time axis is multiplied by the temperature hysteresis compensation factor to generate a calibrated crack initiation tendency index.

7. The method according to claim 1, characterized in that Outputting a crack resistance performance grade based on the gradation deviation between the pre-designed gradation parameters and the fluctuation range of the calibrated crack initiation tendency index includes: Extracting the maximum critical value of the acceptable fluctuation range of gradation from the pre-designed gradation parameters; Dividing the time axis of the solidification process into equal-length detection time frames, and counting the numerical interval span of the calibrated crack initiation tendency index within each detection time frame; When the span of the numerical interval continuously exceeds the maximum critical value and the ratio reaches the phase change sensitivity coefficient of the passive responsive material, it is marked as an abnormal time frame; The crack resistance performance level is output according to the distribution density of the abnormal time frames on the time axis of the solidification process.

8. A crack resistance evaluation system based on concrete shrinkage, characterized in that: include: An acquisition module is used to collect real-time serial data of shrinkage rate and acoustic emission signal stream of concrete samples prepared with passive responsive materials based on pre-designed gradation parameters during the curing process; a separation module for separating high-frequency elastic wave energy attenuation characteristic values ​​strongly associated with shrinkage microcrack propagation from the aggregate slurry interface waveguide effect capture region in the acoustic emission signal stream; A generation module is used to perform spatiotemporal coupling between the high-frequency elastic wave energy attenuation characteristic value and the shrinkage rate jump point in the shrinkage rate real-time sequence data to generate a crack initiation tendency index; a calibration module for dynamically calibrating a temperature drift error of the crack initiation tendency indicator based on an ambient temperature hysteresis effect of the passive responsive material to obtain a calibrated crack initiation tendency indicator; The output module is used to output the crack resistance performance grade according to the gradation deviation between the pre-designed gradation parameter and the fluctuation range of the calibrated crack initiation tendency index.

9. A computing device, characterized in that The method comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for evaluating crack resistance based on concrete shrinkage rate as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the method for evaluating the anti-cracking performance based on concrete shrinkage rate according to any one of claims 1 to 7 is implemented.

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