A device and method for testing the quality of concrete used in water conservancy projects

Abstract

This invention discloses a concrete quality testing device and method for hydraulic engineering projects, belonging to the field of quality testing technology. The invention accurately identifies areas of insufficient vibration through the construction of a three-dimensional vibration time field and gradient analysis, overcoming the uncertainty of traditional experience-based judgment of defect areas. Subsequently, a rate distribution map is constructed using the crack length change rate and spatial interpolation to achieve a quantitative characterization of early crack evolution. Based on this, the sampling and analysis of sound source energy fluctuations using acoustic emission sensors further improves the sensitivity for identifying latent structural defects. Finally, the invention establishes a correlation between defects and monitoring units through a multi-parameter joint judgment mechanism, scientifically classifying the structural quality level.

Description

Technical Field

[0001] This invention relates to the field of quality testing technology, and in particular to a device and method for testing the quality of concrete used in water conservancy projects. Background Technology

[0002] With the rapid advancement of infrastructure construction, water conservancy projects are playing an increasingly important role in flood control, irrigation, and water resource allocation. Concrete structures are the most widely used foundation components in water conservancy projects, and their quality directly affects the safety and service life of the project. Traditional concrete construction quality management relies heavily on manual inspections, spot checks, and post-construction crack observation. These methods suffer from problems such as delayed response, incomplete coverage, and a high risk of misjudgment. In recent years, with the introduction of non-destructive testing (NDT) technology, dynamic monitoring of internal defects in concrete using acoustic emission (AE), ultrasound, and infrared imaging has become a research hotspot. Simultaneously, structural health monitoring systems (SHM) are gradually being deployed in major projects to collect data on deformation, cracks, and stress in real time, enabling long-term assessment and early warning of structural performance. However, most existing concrete quality inspection systems focus on monitoring the entire life cycle of the structure, lacking targeted tracking analysis and dynamic feedback mechanisms for the early stages of construction quality formation (such as pouring and vibration quality).

[0003] Especially during the construction of large-volume concrete components, insufficient vibration often leads to hidden defects such as honeycomb-like surfaces, voids, or insufficient density within the concrete. These problems can easily develop into cracks or even structural deterioration later on. While some systems attempt to use temperature and strain fields for quality inference, they struggle to accurately pinpoint the location and evolution rate of defects and lack a coupled judgment mechanism for multi-source parameters. Furthermore, although acoustic emission technology offers high sensitivity and real-time performance, its application in identifying concrete pouring quality defects is still limited by the placement of sampling points and analytical algorithms, resulting in a lack of systematic integration. In summary, current technologies have not yet achieved a closed-loop management system encompassing the entire process from construction activity recording to early defect identification and structural quality grading, leaving significant room for improvement. Summary of the Invention

[0004] In view of the problems existing in the current concrete quality testing technology, this invention is proposed.

[0005] Therefore, the problem to be solved by this invention is how to construct a defect location and level determination mechanism based on construction data, which has higher pertinence, real-time performance and evaluation accuracy.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a concrete quality testing device for hydraulic engineering, comprising: a vibration identification module, used to extract spatial locations with insufficient vibration time based on the concrete pouring area marked in the component drawings, combined with vibration time and location recording data, and divide them into defect unit sets according to an equal volume grid method; a crack monitoring module, used to divide the spatial range corresponding to the defect unit set into monitoring unit sets according to monitoring accuracy requirements, extract length change sequences and calculate corresponding rate values, and generate a rate spatial distribution envelope map; an acoustic emission acquisition module, used to select rate change regions in the rate spatial distribution envelope map, deploy multiple acoustic emission sensing nodes in the monitoring unit set, perform time-series sampling of sound source signal intensity, and extract acoustic emission energy fluctuation indicators; and a quality grading module, used to map the rate spatial distribution envelope map and acoustic emission indicators to the defect unit-monitoring unit correlation matrix through coordinate matching, classify the quality level according to the joint judgment criteria, and output a defect unit quality grading list.

[0008] As a preferred embodiment of the concrete quality testing device for water conservancy projects described in this invention, the extraction of spatial locations with insufficient vibration time includes: extracting each concrete pouring area according to the construction area number using the boundary line coordinates in the component drawings, extending the boundary into a construction enclosure, which serves as the spatial limitation range for the vibration data of the corresponding concrete pouring area; performing three-dimensional interpolation on the vibration records collected within the construction enclosure according to time sequence and position to construct a vibration time field; and extracting the spatial change rate by differentiating the vibration time field to identify locations with obvious local abrupt changes and interrupted gradient continuity, which constitute vibration defect areas, characterizing the restricted vibration process or the existence of concrete dead zones.

[0009] As a preferred embodiment of the concrete quality testing device for water conservancy projects described in this invention, the following steps are included: dividing the area into a set of defect units using an equal-volume grid method includes: dividing each vibration defect area into cubes with fixed side lengths to generate a set of defect units, wherein each defect unit has a center coordinate; extending the boundary into a construction enclosure includes: reading the two-dimensional boundary frame data of the concrete pouring area, extracting the component outline set according to the construction area number; combining the construction thickness record corresponding to each construction area number, extending the corresponding boundary vertically to the construction thickness to construct a construction enclosure.

[0010] As a preferred embodiment of the concrete quality testing device for water conservancy projects described in this invention, the step of extracting the length change sequence and calculating the corresponding rate value includes: periodically acquiring images of the surface of the monitoring unit from a fixed perspective to form a surface image sequence; using a region tracking calibration method, taking the crack endpoint appearing in the first image as a reference, extracting the corresponding positional changes in subsequent images to form a crack length change sequence; and using the least squares method to perform linear fitting on each period of the crack length change sequence, calculating the crack growth rate value corresponding to each period, and generating a crack growth rate sequence.

[0011] As a preferred embodiment of the concrete quality testing device for water conservancy projects described in this invention, the generation of the rate spatial distribution envelope map includes: extracting the center coordinates of all monitoring units in the monitoring unit set; calling the reference corner coordinates of the construction enclosure, converting the center coordinates of the monitoring units into three-dimensional offsets relative to the reference corner coordinates of the construction enclosure, and using them as mapping coordinates in the local coordinate system of the construction enclosure; associating the crack growth rate with the mapping coordinates to construct a discrete rate field in the coordinate system of the construction enclosure; and performing trilinear interpolation on the discrete rate field to generate a rate spatial distribution envelope map covering the entire area of ​​the construction enclosure.

[0012] As a preferred embodiment of the concrete quality testing device for water conservancy projects described in this invention, the deployment of multi-point acoustic emission sensing nodes includes: constructing a difference tensor based on the difference in crack growth rate between each monitoring unit in the velocity spatial distribution envelope diagram; selecting the monitoring unit with the largest average velocity difference from the difference tensor as the central monitoring unit; defining a three-dimensional detection area containing N spatially adjacent monitoring units, where N is a constant; and deploying at least four acoustic emission sensors in a tetrahedral topology based on the coordinates of the central monitoring unit.

[0013] As a preferred embodiment of the concrete quality testing device for water conservancy projects described in this invention, the step of performing time-series sampling of the sound source signal intensity and extracting the acoustic emission energy fluctuation index includes: performing cross-correlation calculation on the collected sound wave time-series data, and extracting the sound wave path difference and energy change as the acoustic emission fluctuation index of the corresponding monitoring unit.

[0014] As a preferred embodiment of the concrete quality testing device for water conservancy projects described in this invention, the construction of the defect unit-monitoring unit association matrix includes: mapping the coordinates of the central monitoring unit to the defect unit space through the nearest neighbor algorithm to generate parameter pairs indexed by the defect unit; and arranging the parameter pairs in an orderly manner to form the defect unit-monitoring unit association matrix.

[0015] As a preferred embodiment of the concrete quality testing device for water conservancy projects described in this invention, the step of classifying quality grades according to the joint judgment criteria includes: performing minimum-maximum normalization on the parameter pairs to obtain standardized parameter pairs; and calculating the difference vector for the standardized parameter pairs. And construct dominant labels: if the difference vector If it is, then it is marked as rate-dominant; when the difference vector If the condition is positive, it is marked as wave-dominant; otherwise, it is marked as cooperative-dominant. and The dominant distinguishing factor is used; the monitoring unit number is mapped to the corresponding dominant label, and multiple judgment intervals are defined according to the category to which the dominant label belongs. The parameter combinations under different dominant categories are assigned quality levels respectively.

[0016] Secondly, this invention provides a method for quality inspection of concrete used in water conservancy projects, comprising: extracting spatial locations with insufficient vibration time based on the concrete pouring area marked in the component drawings, combined with vibration time and location recording data, and dividing them into defect unit sets according to an equal volume grid method; dividing the spatial range corresponding to the defect unit set into monitoring unit sets according to monitoring accuracy requirements, extracting length change sequences and calculating corresponding rate values, and generating a rate spatial distribution envelope map; selecting rate abrupt change regions in the rate spatial distribution envelope map, deploying multiple acoustic emission sensing nodes in the monitoring unit set, performing time-series sampling of the sound source signal intensity, and extracting acoustic emission energy fluctuation indicators; mapping the rate spatial distribution envelope map and acoustic emission indicators to the defect unit-monitoring unit correlation matrix through coordinate matching, classifying the quality level according to the joint judgment criteria, and outputting a defect unit quality classification list.

[0017] Thirdly, the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, wherein the computer program instructions, when executed by the processor, implement the steps of the concrete quality testing device for water conservancy projects as described in the first aspect of the present invention.

[0018] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, they implement the steps of the concrete quality testing device for water conservancy projects as described in the first aspect of the present invention.

[0019] The beneficial effects of this invention are as follows: By constructing a three-dimensional vibration time field and performing gradient analysis, this invention accurately identifies areas of insufficient vibration, overcoming the uncertainty of traditional experience-based judgment of defect areas. Subsequently, a rate distribution map is constructed using the crack length change rate and spatial interpolation, achieving a quantitative characterization of early crack evolution. Based on this, the sampling and analysis of sound source energy fluctuations using acoustic emission sensors further improves the sensitivity of identifying latent structural defects. Finally, through a multi-parameter joint judgment mechanism, the correlation between defects and monitoring units is established, scientifically classifying the structural quality level. The overall device of this invention achieves an organic combination of defect visualization during the construction phase, quantification of the evolution process, and structured evaluation results. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a structural diagram of a concrete quality testing device used in water conservancy projects.

[0022] Figure 2 This is a flowchart of a method for testing the quality of concrete used in water conservancy projects. Detailed Implementation

[0023] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0024] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0025] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0026] Figure 1 This is a structural diagram of a concrete quality testing device for hydraulic engineering according to an embodiment of the present invention. Figure 1 As shown, the concrete quality testing device for water conservancy projects includes:

[0027] The vibration identification module is used to extract the spatial locations where the vibration time is insufficient based on the concrete pouring area marked in the component drawings, combined with vibration time and location data, and divide them into a set of defective units using an equal volume grid method.

[0028] In this embodiment of the invention, the vibration identification module specifically includes the following:

[0029] Spatial locations where insufficient vibration time was extracted include:

[0030] a. Extract each concrete pouring area by using the boundary line coordinates in the component drawings and the construction area number. Extend the boundary into a closed construction body, which serves as the spatial limit for the vibration data of the corresponding concrete pouring area.

[0031] The process of expanding the boundary into a construction enclosure includes the following steps:

[0032] Step 1.1: Read the two-dimensional boundary frame data of the concrete pouring area and extract the component outline set according to the construction area number.

[0033] Specifically, the first step is to extract boundary line data from the construction drawings. Boundary line data consists of a set of line segments describing the outer contour of concrete components. Each set of boundary lines includes start and end coordinates and has a clearly defined construction area number. In existing two-dimensional drawings, these boundary lines only describe the horizontal projected outline and cannot be used to describe the actual three-dimensional construction space; therefore, they need to be expanded.

[0034] Step 1.2: Based on the construction thickness record corresponding to each construction area number, extend the corresponding boundary vertically to the construction thickness to construct the construction enclosure.

[0035] The expansion method involves extending the two-dimensional boundary vertically based on the thickness records of construction areas with the same number. The extended thickness is the actual concrete pouring thickness recorded by the construction unit in the construction log, and the thickness value is entered into the system in meters. After extension, a closed three-dimensional space is formed, namely the construction enclosure, and each enclosure can be uniquely mapped to the corresponding construction area number.

[0036] It should be noted that the purpose of extending the two-dimensional boundary into a three-dimensional construction enclosure is to provide strict boundary constraints for the spatial analysis of vibration data.

[0037] Existing methods for identifying vibration processes typically monitor operation time by deploying sensors on the surface, but they lack assessment of the vibration quality of the entire spatial volume, resulting in significant blind spots in the detection results.

[0038] This invention limits the sensing data to the area of ​​the construction enclosure, thereby eliminating invalid data points and improving the accuracy of subsequent interpolation analysis.

[0039] The completed construction enclosure is represented in the form of a cube or prism, with its boundary consisting of the drawing outline and vertical thickness, and its spatial coordinates being the boundary envelope within a three-dimensional Cartesian coordinate system.

[0040] After the enclosure is constructed, the vibration data collected during construction will be confined to this volume. The vibration data includes: timestamps, geographic coordinates, and vibration duration of the vibration equipment operating on the surface and inside the component.

[0041] Data sources typically come from handheld vibratory recorders, embedded sensor modules, or mobile trajectory tracking systems, and all recorded data includes precise time and three-dimensional coordinates.

[0042] b. Perform three-dimensional interpolation on the vibration records collected within the construction enclosure according to time sequence and location to construct a vibration time field.

[0043] Traditional methods often employ simple time averaging or two-dimensional interpolation, which are insufficient to reflect the complex vibration process within concrete. This invention uses three-dimensional spline interpolation or Kriging interpolation methods, weighted according to the distance between interpolation nodes, vibration time difference, and spatial distribution density, to construct a vibration time field with spatial continuity.

[0044] Each spatial point can be interpolated to obtain a vibration duration value, in seconds. The vibration time field is essentially a three-dimensional scalar field, where the value at each point represents the duration of vibration experienced by the concrete at that location.

[0045] c. Differentiating the vibration time field yields the spatial rate of change. Locations with significant local abrupt changes and interrupted gradient continuity constitute vibration defect areas, characterizing restricted vibration processes or the presence of concrete dead zones.

[0046] In practice, based on the constructed vibration time field, the spatial gradient field is further calculated. The gradient calculation is achieved by differentiating adjacent voxels in space, performing first-order differences in the X, Y, and Z directions respectively, to obtain the vibration time change rate of each voxel in the three directions.

[0047] Based on the analysis of the continuity of gradient magnitude and direction, spatial regions with significant abrupt changes in vibration time and breaks in gradient direction are identified as candidate areas where problems exist in the vibration process. Specifically, neighborhood difference thresholds and directional consistency indicators are set to assist in the judgment.

[0048] Unlike existing solutions that rely solely on extreme or low values ​​for judgment, this invention designs a method that determines whether there is a spatial continuity break in the rate of change, which can more accurately characterize the vibration dead zones or missed vibration areas caused by construction operations.

[0049] Furthermore, the defect element set, divided according to the equal-volume mesh method, includes:

[0050] Each of the aforementioned vibration defect areas is divided into cubes with fixed side lengths to generate a set of defect units, wherein each defect unit has center coordinates.

[0051] Specifically, for each defective unit, the center coordinates (three-dimensional coordinates), volume side length, construction area number, and average vibration time are recorded.

[0052] The side length value in the division criteria can be selected based on the minimum crack monitoring accuracy and acoustic positioning accuracy of the component. In this invention, it is set as the minimum unit that ensures crack monitoring coverage without redundancy. After the division is completed, the set of small cubes within all vibration defect areas constitutes the defect unit set.

[0053] It should be noted that, compared with existing solutions that rely on simplified statistical analysis or only monitor surface data, this invention can achieve high-resolution spatial reconstruction of vibration quality by constructing a three-dimensional time field and gradient field, and realize the transformation from extensive construction records to fine component units.

[0054] The crack monitoring module is used to divide the monitoring unit set according to the monitoring accuracy requirements within the spatial range corresponding to the defect unit set, extract the length change sequence and calculate the corresponding rate value, and generate a rate spatial distribution envelope map.

[0055] It should be noted that the crack monitoring module is used to periodically observe the evolution of cracks on the structural surface through image acquisition technology during operation or the operational phase. After the monitoring data is generated, it is combined with the defect unit set output by the early vibration identification module to perform spatial correspondence analysis, extract the crack growth trajectory within the defect area, calculate the propagation rate value, and generate a rate spatial distribution envelope map. The image acquisition task of this module can be performed independently of the vibration identification process and can be carried out long-term according to the set monitoring cycle after the structure hardens and during the operational phase.

[0056] Unlike existing solutions that rely solely on extreme or low values ​​for judgment, this invention designs a method that determines whether there is a spatial continuity break in the rate of change, which can more accurately characterize the vibration dead zones or missed vibration areas caused by construction operations.

[0057] Furthermore, the defect element set, divided according to the equal-volume mesh method, includes:

[0058] Each of the aforementioned vibration defect areas is divided into cubes with fixed side lengths to generate a set of defect units, wherein each defect unit has center coordinates.

[0059] Specifically, for each defective unit, the center coordinates (three-dimensional coordinates), volume side length, construction area number, and average vibration time are recorded.

[0060] The side length value in the division criteria can be selected based on the minimum crack monitoring accuracy and acoustic positioning accuracy of the component. In this invention, it is set as the minimum unit that ensures crack monitoring coverage without redundancy. After the division is completed, the set of small cubes within all vibration defect areas constitutes the defect unit set.

[0061] It should be noted that, compared with existing solutions that rely on simplified statistical analysis or only monitor surface data, this invention can achieve high-resolution spatial reconstruction of vibration quality by constructing a three-dimensional time field and gradient field, and realize the transformation from extensive construction records to fine component units.

[0062] The crack monitoring module is used to divide the monitoring unit set according to the monitoring accuracy requirements within the spatial range corresponding to the defect unit set, extract the length change sequence and calculate the corresponding rate value, and generate a rate spatial distribution envelope map.

[0063] It should be noted that the crack monitoring module is used to periodically observe the evolution of cracks on the structural surface through image acquisition technology during operation or the operational phase. After the monitoring data is generated, it is combined with the defect unit set output by the early vibration identification module to perform spatial correspondence analysis, extract the crack growth trajectory within the defect area, calculate the propagation rate value, and generate a rate spatial distribution envelope map. The image acquisition task of this module can be performed independently of the vibration identification process and can be carried out long-term according to the set monitoring cycle after the structure hardens and during the operational phase.

[0064] Although crack monitoring and vibration identification differ significantly in implementation time, in the subsequent data fusion stage, by unifying the coordinate system and spatial mapping methods, the trend of crack changes can be traced back to the early vibration defect area, enabling the attribution and assessment of quality status across time.

[0065] In this embodiment of the invention, the crack monitoring module specifically includes the following:

[0066] Extracting the length variation sequence and calculating the corresponding rate value includes:

[0067] First, periodic image acquisition is performed on the surface of the monitoring unit using a fixed viewing angle to form a surface image sequence.

[0068] Specifically, because the internal defects of concrete materials are time-varying and hidden, a single observation result is difficult to reflect the true failure trend. Therefore, it is necessary to use a periodic image sequence for continuous observation to form the trajectory of crack length change.

[0069] This invention first refines the space within each defect area according to monitoring accuracy requirements, dividing it into multiple monitoring units. The side length of each monitoring unit is set to the spatial scale corresponding to image recognition accuracy (e.g., 1 cm). This ensures a unique mapping relationship between subsequent crack length changes and three-dimensional spatial coordinates, guaranteeing coordinate consistency across multi-source data.

[0070] For the aforementioned set of monitoring units, crack monitoring operations employ a fixed-viewpoint approach to perform image acquisition. Image acquisition utilizes industrial-grade cameras, mobile arms, or track systems equipped with repeatable positioning devices to ensure consistent parameters such as illumination, angle, and distance for each acquired image.

[0071] The image acquisition cycle is set according to the structural monitoring plan. The fixed cycle ensures that the data has temporal continuity and trend analysis value. The image data obtained from each image acquisition constitutes a surface image sequence, and each image records the acquisition timestamp, shooting pose information, image resolution, and monitoring unit number.

[0072] By periodically acquiring images of the surface of the monitoring unit, the actual length change trajectory of the crack at different time points is obtained, forming a visual basis for the aging or damage evolution of the structure.

[0073] Among them, the region tracking calibration method is adopted, taking the crack endpoints that appear in the first image as the benchmark, and extracting the corresponding position changes in subsequent images to form a crack length change sequence.

[0074] Specifically, using the crack endpoints identified in the initial image as a benchmark, algorithms based on grayscale gradients, edge tracking, or convolutional neural networks (the specific implementation of this invention is not limited to these algorithms and can be set according to actual conditions) are employed to automatically identify the corresponding endpoint positions in subsequent images. The specific operations are as follows: edge detection is performed on the crack region, the skeleton path is extracted, and the length of the crack endpoints and the path are matched and calibrated; by matching the spatial positions of the crack start and end points at different times, a crack length variation sequence is formed.

[0075] Crack lengths are measured in millimeters, and the sequence is plotted with timestamps on the horizontal axis and crack length on the vertical axis, forming a discrete time series for subsequent rate calculations. Compared to traditional image comparison methods, this method can adapt to changes in illumination and surface disturbances, improving monitoring robustness.

[0076] Finally, the least squares method was used to perform linear fitting on each period of the crack length variation sequence, and the crack growth rate value corresponding to each period was calculated to generate the crack growth rate sequence.

[0077] For example, a linear fit is performed on the crack length sequence within a time period (such as the time difference between two consecutive images).

[0078] The least squares fitting formula is as follows:

[0079] ;

[0080] in, For the first Crack growth rate per cycle, For the first The time point corresponding to the acquisition of each image frame. For the corresponding crack length, and For the first The arithmetic mean of all time points and crack lengths within each period, where n is the number of image frames acquired in each monitoring period.

[0081] The rates described above represent the average propagation rate of cracks within one cycle, reflecting the activity of internal defects in the material. The crack growth rate sequence is indexed by monitoring unit number and bound to spatial coordinates to form the basic data that can be used for three-dimensional spatial analysis.

[0082] The spatial distribution envelope of the generation rate includes:

[0083] The center coordinates of all monitoring units in the monitoring unit set are extracted and represented as Cartesian coordinates in three-dimensional space. Each center coordinate point corresponds one-to-one with the crack growth rate, forming a discrete set of three-dimensional scalar points.

[0084] To ensure that the velocity field can be spatially interpolated and analyzed within the coordinate system of the construction enclosure, the reference corner coordinates of the construction enclosure need to be called, and the center coordinates of the monitoring unit need to be converted into a three-dimensional offset relative to the reference corner coordinates of the construction enclosure, which will then be used as the mapped coordinates in the local coordinate system of the construction enclosure.

[0085] The reference corner coordinates are the starting angle marked on the construction drawings, i.e., the three-dimensional coordinates of the lowest layer corner. The center coordinates of all monitoring units are vector-subtracted relative to this reference corner to generate a three-dimensional offset. This three-dimensional offset represents the position of the monitoring unit in the local coordinate system, which can be used for mesh interpolation and shares the same coordinate reference with other parameters (such as acoustic emission nodes and vibration defect units).

[0086] Furthermore, the crack growth rate is correlated with the mapped coordinates to construct a discrete velocity field in the coordinate system of the construction enclosure. The discrete velocity field is then subjected to trilinear interpolation to generate a velocity spatial distribution envelope map covering the entire construction enclosure.

[0087] Specifically, to transform the discrete velocity field into a continuous spatial distribution map, a trilinear interpolation algorithm is employed. In the trilinear interpolation process, a voxel grid is established based on the construction enclosure and a fixed voxel size. Velocity-weighted interpolation is then performed on points within each voxel. The interpolation function is as follows:

[0088] ;

[0089] in, For interpolation point rate, The weights of the eight vertices, This represents the growth rate of the crack at the apex. It ensures that a rate estimate can be obtained at any point in space, generating a continuous three-dimensional rate distribution field, i.e., a rate spatial distribution envelope map.

[0090] In this invention, the image acquisition and processing of the crack monitoring module does not depend on whether the vibration recognition module is executed. It can be deployed and started independently after the concrete structure enters the operation period, and then a mapping relationship is formed with the defect units during the construction period through a three-dimensional coordinate system.

[0091] The velocity spatial distribution envelope map of this invention has the following advantages: First, it can realize the location of crack risks in the entire structure space, no longer limited to surface observation; second, the data source has periodicity and can be used for time-series risk assessment; third, image acquisition and coordinate consistency processing ensure the accuracy of data fusion.

[0092] Compared to the traditional method of identifying cracks using image difference in a single frame, this module improves the accuracy and controllability of the results through triple fusion of spatial coordinates, time series, and rate values.

[0093] The acoustic emission acquisition module is used to select regions of rapid rate change in the velocity spatial distribution envelope map, deploy multiple acoustic emission sensing nodes in the monitoring unit set, perform time-series sampling of the sound source signal intensity, and extract acoustic emission energy fluctuation indicators.

[0094] In this embodiment of the invention, the acoustic emission acquisition module specifically includes the following:

[0095] Step 3.1: Construct a difference tensor based on the difference in crack growth rate between each monitoring unit in the velocity spatial distribution envelope diagram. Select the monitoring unit with the largest average velocity difference from the difference tensor as the central monitoring unit. Define a three-dimensional detection zone containing N spatially adjacent monitoring units, where N is a constant.

[0096] It should be noted that the spatial distribution of crack growth rate in the velocity spatial distribution envelope map is highly non-uniform. The rate differences between different monitoring units reflect changes in the local stress state of the structure, as well as changes in crack propagation direction and intensity. Therefore, in order to select the deployment area for acoustic emission sensors, it is necessary to construct a set of difference tensors reflecting the gradient of crack growth rate changes among monitoring units, starting from the velocity spatial distribution envelope map.

[0097] The difference tensor uses the monitoring cells of the three-dimensional mesh index as nodes, calculates the rate difference between the monitoring cells and all spatially adjacent cells, and stores it in the form of a three-dimensional matrix.

[0098] For example, the formula for calculating tensors is as follows:

[0099] ;

[0100] in, Indicates that the index is The difference in average crack growth rate between the monitoring unit and m adjacent units, This indicates the crack growth rate of the current monitoring unit. This represents the crack growth rate of adjacent monitoring units.

[0101] By performing a global scan of the values ​​in the difference tensor, the monitoring unit with the largest difference in crack growth rate is identified as the location where the crack evolution rate change is most significant in this region. The corresponding monitoring unit is defined as the central monitoring unit, and a three-dimensional detection zone is constructed using spatial coordinates as the geometric reference.

[0102] Step 3.2: Based on the coordinates of the central monitoring unit, deploy at least 4 acoustic emission sensors in a tetrahedral topology.

[0103] The three-dimensional detection area is a spatial region containing a central monitoring unit and adjacent monitoring units. To ensure that the spatial detection results have three-dimensional resolution, the detection area must meet the requirements of three-dimensional multipath coverage in the direction of sound wave propagation.

[0104] In this invention, the three-dimensional detection zone consists of a central monitoring unit and multiple spatially adjacent monitoring units, typically 6 to 12. This zone must satisfy the following condition: the spatial distance between adjacent monitoring units does not exceed twice the side length of the monitoring unit, to ensure that the sound source response has localized characteristics.

[0105] The acoustic emission sensors are deployed in the three-dimensional detection area, using a regular tetrahedral topology.

[0106] The tetrahedral topology is characterized by its simplicity, strong spatial resolution, and minimal 3D positioning error. Using the 3D coordinates of the central monitoring unit as a reference, at least four acoustic emission sensors are deployed according to the following rules: sensor nodes are distributed diagonally around the central monitoring unit (the actual deployment can be scaled up based on the central coordinates of the monitoring unit), forming a non-coplanar layout among the nodes. Each node's coordinates are described using the same local coordinate system as the enclosed structure, ensuring that the four points are not coplanar or collinear during deployment. This deployment enables the acoustic emission acquisition system to spatially locate any sound source within the structure and monitor multi-path sound wave propagation.

[0107] Step 3.3: Perform cross-correlation calculation on the collected acoustic wave time series data, and extract the acoustic wave path difference and energy change as the acoustic emission fluctuation index of the corresponding monitoring unit.

[0108] Each acoustic emission sensor has a sampling accuracy of 1 MHz or higher and a dynamic range greater than 60 dB. The sensors are synchronized using the same clock signal source, ensuring a unified reference time for all sampling moments. During acquisition, the sensors record signals using a constant period, dividing the period into multiple time points with equal time resolution, recording three elements: amplitude, frequency, and time-varying energy.

[0109] Each acoustic signal sample is accompanied by a node number, timestamp, and three-dimensional location coordinates. When a structural vibration or acoustic emission event occurs, multiple nodes simultaneously record the acoustic excitation signal and generate acoustic arrival responses with different time delays.

[0110] Ideally, the sound wave propagates from the sound source to each sound emission node with different propagation paths and medium impedances. Therefore, the sound wave signals received by different nodes exhibit time delays and waveform differences. By performing cross-correlation analysis on the sound wave time-series data collected from multiple nodes, the sound wave path difference can be accurately extracted. The cross-correlation analysis uses the following calculation method:

[0111] ;

[0112] in, and The first The and the first Each acoustic emission sensing node in time The signal was collected at the location; This is a time delay.

[0113] Cross-correlation function The maximum value corresponding to This refers to the difference in sound wave propagation paths between two nodes. Multiple cross-correlated path differences can be used to construct a sound wave propagation path map, which, when combined with the three-dimensional geometric layout, can further pinpoint the spatial coordinates of the sound source.

[0114] Furthermore, the amplitude attenuation and frequency variation of the signal during sound wave propagation also change due to the inhomogeneity of the medium. Therefore, based on cross-correlation analysis, it is also necessary to extract the total energy change of each sound wave signal. The energy change index is calculated as follows:

[0115] ;

[0116] This energy index represents the total amount of acoustic energy received by a node per unit time, reflecting the level of acoustic emission activity within the current structural location. By statistically analyzing the energy variation amplitude over multiple periods in a time series, an energy fluctuation sequence can be formed, serving as an indirect quantitative indicator of the structural activity level of this monitoring unit.

[0117] The acoustic emission fluctuation index is a quantitative parameter that reflects the abrupt changes in stress and dynamic changes in cracks within a structure, calculated based on the acoustic energy sequence. This index is defined as the coefficient of variation of the energy sequence over multiple consecutive periods. Specifically, it is calculated by dividing the standard deviation of the energy sequence by the mean of the energy sequence, yielding the energy fluctuation coefficient of the monitoring unit. A larger coefficient indicates greater fluctuation in the activity level of the sound source and a more unstable structural state.

[0118] The energy fluctuation indicators extracted from all acoustic emission nodes are uniformly mapped to the coordinates of the monitoring unit center, forming a data structure paired with the velocity space distribution envelope diagram. Each monitoring unit ultimately possesses two parameters: crack growth rate and acoustic emission energy fluctuation coefficient.

[0119] The quality grading module is used to map the velocity spatial distribution envelope map and acoustic emission index to the defect unit-monitoring unit correlation matrix through coordinate matching, classify the quality level according to the joint judgment criteria, and output a list of defect unit quality grades.

[0120] In this embodiment of the invention, the quality grading module specifically includes the following:

[0121] The construction of the defect unit-monitoring unit correlation matrix includes:

[0122] The coordinates of the central monitoring unit are mapped to the defect unit space using the nearest neighbor algorithm (where the side length of the defect unit is less than or equal to an integer multiple of the side length of the monitoring unit), generating parameter pairs indexed by the defect unit, and then arranging the parameter pairs in order to form a defect unit-monitoring unit correlation matrix.

[0123] Specifically, the prerequisite for quality classification is to map two types of data located in different spatial locations—crack rate parameters and acoustic emission wave parameters—to the same structural unit.

[0124] Since crack rate data originates from surface image monitoring grids, while acoustic emission wave data originates from three-dimensional spatial sound source perception, their initial coordinate systems differ spatially. Therefore, it is necessary to use the defect element set as the primary index for mapping and unify parameter pairing sources. The center coordinates of the defect elements come from the three-dimensional mesh constructed by the vibration identification module within the construction enclosure. Each element is a cubic structure with fixed side lengths and a spatial reference system, denoted as […]. .

[0125] The center coordinates of the monitoring unit set are The number of units must be no less than the size of the defect unit set. A nearest neighbor matching method is used to find the nearest monitoring unit coordinate point in three-dimensional Euclidean space for each defect unit's spatial center point, forming a one-to-one match. The specific formula is as follows:

[0126] ;

[0127] in, Represents Euclidean distance. In order to be with the first Each defective element is indexed by the nearest monitoring element. Using this method, each defective element is assigned a matching vector containing two types of parameter values: the crack growth rate and acoustic emission energy fluctuation index corresponding to the monitoring element. Finally, a defective element-monitoring element correlation matrix is ​​constructed, indexed by the defective element and containing the two parameters.

[0128] It is important to note here that the core of constructing the defect element-monitoring element correlation matrix lies in achieving spatial fusion and information attribution between parameters from different time stages. The defect element set reflects the potential hazard areas caused by insufficient vibration time in the early construction stage. Its construction is based on a three-dimensional grid structure within the closed construction body, representing the spatial projection of the historical construction intervention effect. The crack rate parameter and acoustic emission fluctuation parameter are derived from the structural response monitoring of the current time period, reflecting time-varying information such as strain energy concentration and microcrack evolution on the structural surface and inside.

[0129] Therefore, by constructing a spatial mapping relationship to accurately match the current state parameters to the historical defect area, it is possible to achieve operational response tracking and risk level quantification for potential construction defects.

[0130] This invention utilizes the crack growth rate and acoustic emission wave intensity of the current cycle to infer the structural risk level of areas with insufficient early vibration quality, thereby providing a quality level classification based on spatiotemporal composite indicators. This invention establishes a stable three-stage judgment chain of historical defect location → current monitoring response → quality level evaluation, providing data channels and judgment rules to support defect evolution trend identification and risk warning.

[0131] The quality grade classification based on the joint judgment criteria includes:

[0132] First, the parameter pairs are subjected to min-max normalization to obtain standardized parameter pairs.

[0133] Secondly, the difference vector is calculated for the standardized parameter pairs. And construct a dominant label. In actual crack development, there are three typical development states: rate-dominated (crack extension is significantly faster than energy response), wave-dominated (strong acoustic energy release but slow cracking), and synergistic-dominated (both have similar intensity). If the difference vector If it is, then it is marked as rate-dominant; when the difference vector If the condition is positive, it is marked as wave-dominant; otherwise, it is marked as cooperative-dominant. and The dominant distinguishing factor.

[0134] Finally, the monitoring unit number is mapped to the corresponding dominant label, and multiple judgment intervals are defined according to the category to which the dominant label belongs. The parameter combinations under different dominant categories are assigned quality levels.

[0135] The quality grading list is output in a two-dimensional table format. Each column contains the following fields: number, three-dimensional coordinates, dominant label, quality grade, etc. The list can be output in standard data formats such as JSON and CSV for downstream systems to use for visualization, defect area reinforcement assessment, and construction feedback adjustments.

[0136] Furthermore, such as Figure 2 As shown, this embodiment also provides a method for testing the quality of concrete used in water conservancy projects, including:

[0137] S1: Based on the concrete pouring area marked in the component drawings, combined with the vibration time and location data, extract the spatial locations where the vibration time is insufficient, and divide them into defect unit sets according to the equal volume grid method.

[0138] S2: Within the spatial range corresponding to the defect unit set, divide the monitoring unit set according to the monitoring accuracy requirements, extract the length change sequence and calculate the corresponding rate value, and generate a rate spatial distribution envelope map.

[0139] S3: Select the region of rapid rate change in the velocity spatial distribution envelope map, deploy multiple acoustic emission sensing nodes in the monitoring unit set, perform time-series sampling of the sound source signal intensity, and extract the acoustic emission energy fluctuation index.

[0140] S4: Map the velocity spatial distribution envelope and acoustic emission index to the defect unit-monitoring unit correlation matrix through coordinate matching, classify the quality level according to the joint judgment criteria, and output the defect unit quality classification list.

[0141] This embodiment also provides a computer device suitable for concrete quality testing devices for water conservancy projects, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the concrete quality testing device for water conservancy projects as proposed in the above embodiment.

[0142] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0143] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the concrete quality testing device for water conservancy projects as proposed in the above embodiments.

[0144] In summary, this invention accurately identifies areas of insufficient vibration through the construction of a three-dimensional vibration time field and gradient analysis, overcoming the uncertainty of traditional experience-based judgment of defect areas. Subsequently, a rate distribution map is constructed using the crack length change rate and spatial interpolation to achieve a quantitative characterization of early crack evolution. Based on this, the sampling and analysis of sound source energy fluctuations using acoustic emission sensors further enhances the sensitivity for identifying latent structural defects. Finally, a multi-parameter joint judgment mechanism establishes the correlation between defects and monitoring units, scientifically classifying structural quality levels. The overall device of this invention achieves an organic combination of defect visualization during construction, quantification of the evolution process, and structured evaluation results.

[0145] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A concrete quality testing device for water conservancy projects, characterized in that: include: The vibration identification module is used to extract the spatial locations where the vibration time is insufficient based on the concrete pouring area marked in the component drawings, combined with vibration time and location data, and divide them into a set of defective units in an equal volume grid manner. The crack monitoring module is used to divide the monitoring unit set according to the monitoring accuracy requirements within the spatial range corresponding to the defect unit set, extract the length change sequence and calculate the corresponding rate value, and generate a rate spatial distribution envelope map. The acoustic emission acquisition module is used to select regions of rapid rate change in the velocity spatial distribution envelope map, deploy multiple acoustic emission sensing nodes in the monitoring unit set, perform time-series sampling of the sound source signal intensity, and extract acoustic emission energy fluctuation indicators. The quality grading module maps the velocity spatial distribution envelope and acoustic emission indicators to the defect unit-monitoring unit correlation matrix through coordinate matching, classifies the quality level according to the joint judgment criteria, and outputs a list of defect unit quality grades; the extraction of spatial locations with insufficient vibration time includes: By using the boundary line coordinates in the component drawings, each concrete pouring area is extracted according to the construction area number. The boundary is then extended into a construction enclosure, which serves as the spatial limit for the vibration data of the corresponding concrete pouring area. The vibration records collected within the construction enclosure are interpolated in three dimensions according to time sequence and location to construct a vibration time field. The spatial rate of change obtained by differentiating the vibration time field is used to extract the locations where there are obvious local abrupt changes and interruptions in gradient continuity, which constitute the vibration defect area, indicating that the vibration process is restricted or there are dead corners in the concrete.

2. The concrete quality testing device for water conservancy projects as described in claim 1, characterized in that: The defect element set divided according to the equal-volume mesh method includes: Each of the aforementioned vibration defect areas is divided into cubes with fixed side lengths to generate a set of defect units, wherein each defect unit has center coordinates; The process of extending the boundary into a construction enclosure includes: Read the two-dimensional boundary wireframe data of the concrete pouring area and extract the component outline set according to the construction area number; By combining the construction thickness records corresponding to each construction area number, the corresponding boundary is extended vertically to form the construction thickness, thus constructing a closed construction body.

3. The concrete quality testing device for water conservancy projects as described in claim 2, characterized in that: The step of extracting the length variation sequence and calculating the corresponding rate value includes: Periodic image acquisition of the surface of the monitoring unit is performed from a fixed viewing angle to form a surface image sequence; A region tracking calibration method is used to extract the corresponding positional changes in subsequent images based on the crack endpoints that appear in the first image, forming a crack length change sequence. The crack length variation sequence is linearly fitted to each period using the least squares method, and the crack growth rate value corresponding to each period is calculated to generate a crack growth rate sequence.

4. The concrete quality testing device for water conservancy projects as described in claim 3, characterized in that: The spatial distribution envelope of the generation rate includes: Extract the center coordinates of all monitoring units in the monitoring unit set; The reference corner coordinates of the construction enclosure are called, and the center coordinates of the monitoring unit are converted into a three-dimensional offset relative to the reference corner coordinates of the construction enclosure, which is used as the mapped coordinates in the local coordinate system of the construction enclosure. By associating the crack growth rate with the mapped coordinates, a discrete rate field is constructed in the coordinate system of the construction closed body. The discrete velocity field is subjected to trilinear interpolation to generate a velocity spatial distribution envelope map covering the entire construction enclosure.

5. The concrete quality testing device for water conservancy projects as described in claim 1, characterized in that: The deployment of the multi-point acoustic emission sensing nodes includes: Based on the difference in crack growth rate between each monitoring unit in the velocity spatial distribution envelope diagram, a difference tensor is constructed. The monitoring unit with the largest average velocity difference is selected from the difference tensor as the central monitoring unit. A three-dimensional detection zone is defined, which contains N spatially adjacent monitoring units, where N is a constant. Based on the coordinates of the central monitoring unit, at least four acoustic emission sensors are deployed in a tetrahedral topology.

6. The concrete quality testing device for water conservancy projects as described in claim 5, characterized in that: The step of performing time-series sampling of the sound source signal intensity and extracting acoustic emission energy fluctuation indicators includes: Cross-correlation calculations are performed on the collected acoustic wave time series data to extract the acoustic wave path difference and energy change, which are used as the acoustic emission fluctuation index of the corresponding monitoring unit.

7. The concrete quality testing device for water conservancy projects as described in claim 1, characterized in that: The construction of the defect unit-monitoring unit correlation matrix includes: The coordinates of the central monitoring unit are mapped to the defect unit space using the nearest neighbor algorithm, generating parameter pairs indexed by the defect unit. The parameters are arranged in an ordered manner to form a defect unit-monitoring unit correlation matrix.

8. The concrete quality testing device for water conservancy projects as described in claim 7, characterized in that: The quality grade classification based on the joint judgment criteria includes: The parameter pairs are subjected to min-max normalization to obtain standardized parameter pairs. Calculate the difference vector for the standardized parameter pair. And construct dominant labels: if the difference vector If it is, then it is marked as rate-dominant; when the difference vector If the condition is positive, it is marked as wave-dominant; otherwise, it is marked as cooperative-dominant. and The dominant distinguishing factor; The monitoring unit number is mapped to the corresponding dominant label, and multiple judgment intervals are defined according to the category to which the dominant label belongs. The parameter combinations under different dominant categories are assigned quality levels respectively.

9. A concrete quality testing device system for water conservancy projects, based on the concrete quality testing device for water conservancy projects according to any one of claims 1 to 8, characterized in that: Also includes: Based on the concrete pouring area marked in the component drawings, combined with the vibration time and location data, the spatial locations with insufficient vibration time are extracted and divided into defect unit sets according to the equal volume grid method. Within the spatial range corresponding to the defect unit set, the monitoring unit set is divided according to the monitoring accuracy requirements, the length change sequence is extracted and the corresponding rate value is calculated to generate a rate spatial distribution envelope map. In the velocity spatial distribution envelope map, a velocity change region is selected, and multiple acoustic emission sensing nodes are deployed in the monitoring unit set to perform time-series sampling of the sound source signal intensity and extract the acoustic emission energy fluctuation index. The velocity spatial distribution envelope map and acoustic emission index are mapped to the defect unit-monitoring unit correlation matrix through coordinate matching. The quality level is classified according to the joint judgment criteria, and a list of defect unit quality grades is output.

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