Method for detecting compactness in concrete pouring construction

Abstract

The invention relates to the technical field of compactness detection, in particular to a compactness detection method in concrete pouring construction. The method comprises the following steps: determining an abnormal section according to the deviation of ultrasonic signal data points between monitoring points on a vertical line, analyzing the matching deviation degree of the abnormal section and other monitoring points to obtain a defect evaluation index, and screening a key section; analyzing signal deviation and aggregation distribution between key sections at the monitoring points, and obtaining defect attention in combination with defect evaluation indexes; and determining the connected sections according to the distribution of the key sections, obtaining a compactness evaluation index through the position distribution and the section proportion of the connected sections and the defect attention in combination with the distribution density and the ground distribution degree of the monitoring points with the key sections, and performing evaluation detection. According to the method, the associated defects are identified and the risk is quantified in the wall thickness direction through multiple monitoring points, and the wall compactness is comprehensively evaluated in combination with the spatial distribution and the quantitative risk of the associated defects, so that the detection result is more accurate and credible.

Description

Technical Field

[0001] The present invention relates to the technical field of density detection, and in particular to a density detection method in concrete pouring construction. Background Art

[0002] In construction projects, hardened concrete must possess sufficient strength and durability to bear loads and resist environmental erosion. A key indicator of concrete durability is its density; the higher the density, the stronger the structure. Because concrete density reflects the uniformity and compactness of the material and is a key indicator of concrete construction quality, it is crucial to monitor the density of concrete walls to prevent cracks and structural damage, ensuring overall building safety.

[0003] During the pouring process, concrete walls typically require vibration to ensure that bubbles and voids within the concrete are effectively expelled. Insufficient vibration may lead to the formation of bubbles and voids, thus affecting the wall's density. Existing technologies often analyze the density of concrete walls using ultrasonic signals from monitoring locations on the concrete wall. However, if defects such as honeycombs, voids, or slag inclusions are present within the concrete wall, the defect locations will exhibit spatial continuity. Single-point detection results only focus on the "presence" or "size" of the defect, making it difficult to identify such cross-regional correlations and easily misjudging systemic defects as scattered local issues. In reality, defects within concrete walls have spatial distribution characteristics. Failure to comprehensively assess the defects based on their spatial distribution within the overall structure can result in high errors in defect assessment, impacting the density assessment of concrete walls. Summary of the Invention

[0004] In order to solve the technical problems in the above-mentioned prior art, the purpose of the present invention is to provide a density detection method in concrete pouring construction, and the technical solution adopted is as follows: The present invention provides a method for detecting density in concrete pouring construction, the method comprising: At each monitoring point of the concrete wall, a direction perpendicular to the wall surface is used as an extension direction; and an ultrasonic signal sequence in the extension direction is obtained; On the same vertical line, the abnormal section of the monitoring point in the extension direction is determined based on the signal value deviation of the data points in the ultrasonic signal sequence between each monitoring point and other monitoring points; the degree of matching deviation between each abnormal section of each monitoring point and the ultrasonic signal sequence of other monitoring points is analyzed to obtain the defect assessment index of the abnormal section; and the key section is screened out from the abnormal section based on the defect assessment index; At each monitoring point, the defect concern level of each monitoring point is determined based on the degree of ultrasonic signal sequence deviation between key sections, the distribution and aggregation of key sections from the center of the wall, and the defect assessment index. On the same vertical line, connected sections are determined based on the distribution of key sections at all monitoring points in the extension direction. The comprehensive risk of the wall is determined based on the distribution and aggregation of connected sections from the ground on each vertical line, the proportion of each connected section, and the defect concern level of the corresponding monitoring point. The impact concentration of the wall is obtained based on the distribution density and distance from the ground of the monitoring points in the key sections of the wall. The density assessment index is obtained by combining the comprehensive risk and impact concentration of the wall. The density is evaluated based on the density evaluation index.

[0005] Furthermore, the method for obtaining the abnormal section includes: For any monitoring point, each other monitoring point on the same vertical line as the monitoring point is taken as the analysis monitoring point; The DTW algorithm is applied to the ultrasonic signal sequence of the monitoring point and the analysis monitoring point to obtain a matching pair of each data point in the ultrasonic signal sequence of the monitoring point; the distance between the data points in each matching pair of data points is calculated and negative correlation mapping is performed to obtain a matching value of each data point to the analysis monitoring point; When the mean of the matching values ​​between the data point of the monitoring point and all other monitoring points on the same vertical line is less than the preset abnormal threshold, the corresponding data point is recorded as an abnormal data point; Two or more consecutive abnormal data points on the ultrasonic signal sequence of the monitoring point are merged to form an abnormal period; the propagation length position in the extension direction corresponding to each abnormal period of the ultrasonic signal sequence is taken as each abnormal segment.

[0006] Furthermore, the method for obtaining the defect assessment index includes: For any abnormal section at any monitoring point, during the time period of the ultrasonic signal sequence corresponding to the abnormal section, the similarity between the ultrasonic signal sequence and the ultrasonic signal sequences of each other monitoring point on the same perpendicular line is calculated as the matching factor between the abnormal section and each other monitoring point; Other monitoring points with matching factors less than the preset matching threshold are regarded as difference monitoring points of the abnormal section; The ratio of the total number of difference monitoring points in the abnormal section to the total number of all other monitoring points on the same perpendicular line is taken as the matching deviation degree of the abnormal section; Perform negative correlation mapping between the abnormal section and the mean of the matching factors of all difference monitoring points to obtain the matching abnormality degree of the abnormal section; The defect assessment index of the abnormal section is obtained by combining the matching deviation and matching abnormality of the abnormal section.

[0007] Furthermore, the method for obtaining the defect attention level includes: For any monitoring point with more than two key sections, the similarity of the ultrasonic signal sequence between every two key sections at the monitoring point is calculated, and the mean of all similarities is negatively correlated and mapped as the defect complexity of the monitoring point; Calculate the interval distance between each two adjacent key sections in the extension direction of the monitoring point, and perform negative correlation mapping on the mean of all interval distances to serve as the aggregation distribution degree of the monitoring point; The ratio of the sum of the lengths of all key segments at the monitoring point to the total propagation length in the extension direction is taken as the segment distribution degree of the monitoring point; The initial attention level of the monitoring point is obtained by combining the defect complexity, cluster distribution and segment distribution of the monitoring point; Calculate the distance between each key section at the monitoring point and the center of the wall and perform negative correlation mapping to obtain the central threat degree of each key section. Combine the central threat degree of each key section with the defect assessment index to obtain the hazard assessment index of each key section. The defect attention level of the monitoring point is obtained by combining the hazard assessment indicators and initial attention levels of all key sections at the monitoring point.

[0008] Furthermore, the method for obtaining the connected segments includes: For any vertical line, between each monitoring point and each adjacent monitoring point on the vertical line, when there is a key segment with overlapping distribution positions in the extension direction, the overlapping key segments are merged into one overlapping segment; After traversing the key segments of all monitoring points on the vertical line, each overlapping segment is regarded as a connected segment.

[0009] Furthermore, the method for obtaining the comprehensive risk includes: For any connected segment on any vertical line, the ratio of the length of the connected segment in the extension direction to the total propagation length in the extension direction is used as the horizontal distribution index of each connected segment; the number of monitoring points contained in the connected segment is used as the vertical distribution index of each connected segment; the average defect attention of the monitoring points contained in each connected segment is used as the defect impact of each connected segment; the horizontal distribution index, vertical distribution index and defect impact of each connected segment are combined to obtain the density impact factor of each connected segment; Calculate the minimum distance between each connected segment and every other connected segment on the vertical line, and use the average of all minimum distances as the distribution spacing value of each connected segment. Perform negative correlation mapping and normalization on the product of the distance of each connected segment from the wall and the ground and the distribution spacing value to obtain the ground distribution aggregation index of each connected segment. Combine the density influencing factor and the ground distribution aggregation index of each connected segment to obtain the risk coefficient of each connected segment. The comprehensive risk of the wall is obtained by combining the risk coefficients of all connected segments on the vertical line.

[0010] Furthermore, the method for obtaining the influence concentration includes: Each monitoring point with a key section is regarded as a key point; the ratio between the total number of key points and the total number of all monitoring points is regarded as the key ratio; The distance between each key point and the wall and the ground is calculated and averaged to obtain the key load-bearing influence. The distance between each key point is calculated and averaged to obtain the key spacing distribution. The product of the key load-bearing influence and the key spacing distribution is negatively correlated to obtain the centralized distribution influence of the key points. The influence concentration of the wall is obtained by combining the centralized distribution influence and the key proportion.

[0011] Furthermore, the method for obtaining the density evaluation index includes: The product of the comprehensive risk and impact concentration of the wall is negatively correlated and normalized to obtain the density assessment index.

[0012] Furthermore, the density assessment based on the density assessment index includes: When the density evaluation index is greater than or equal to the preset first detection threshold, the density evaluation result is recorded as qualified; When the density evaluation index is less than the preset first detection threshold and greater than the preset second detection threshold, the density evaluation result is recorded as good; When the density evaluation index is less than or equal to the preset second detection threshold, the density evaluation result is recorded as unqualified; the preset first detection threshold is greater than the preset second detection threshold.

[0013] Furthermore, the method for obtaining the key section includes: The abnormal section whose defect assessment index is greater than the preset defect threshold is regarded as the key section.

[0014] The present invention has the following beneficial effects: The present invention uses the direction perpendicular to the wall surface as the extension direction at multiple monitoring points on the concrete wall, and captures the internal structural characteristics of the wall thickness direction through ultrasonic signals. On the same vertical line, the abnormal section is determined based on the deviation of the ultrasonic signal data points between the monitoring points, and the degree of matching deviation between the abnormal section and other monitoring points is analyzed to obtain the defect assessment index, identify the potential hidden related defects within the same vertical line, quantify the defect possibility of the abnormal section, and screen the key sections accordingly. The subsequent hazard risk assessment is carried out through the preliminarily screened high-risk sections to improve the comprehensive analysis of hidden defects. At each monitoring point, the signal deviation and cluster distribution between the key sections are analyzed to reflect the complexity of the defects and the influence of the location. The defect attention is obtained in combination with the defect assessment index to measure the defect risk of a single monitoring point.

[0015] Considering the spatial distribution of defect correlation, the connected segments are determined based on the distribution of key segments. The position distribution and segment proportion of the connected segments are used to reflect the impact of the defective part on the position of the load-bearing area and the scale of the defect. Combined with the defect attention of the single-point position, the local risk is reflected to determine the comprehensive risk, and the overall impact of defects in different vertical directions is systematically evaluated. The distribution density and the degree of distribution from the ground of the monitoring points in the key segments are used to reflect the clustering of defects and their impact on the load-bearing area, and the concentration of impact is obtained to further evaluate the spatial clustering risk of defects and avoid ignoring the potential hazards of concentrated defects. The density assessment index is obtained and evaluated in combination with the comprehensive risk and the concentration of impact to more comprehensively and accurately reflect the overall density of the wall. The present invention identifies associated defects and quantifies risks in the direction of the wall thickness through multiple monitoring points. Combined with the spatial distribution of associated defects and the quantified risks, the wall density is comprehensively evaluated to make the detection results more accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 A flow chart of a method for detecting density during concrete pouring construction provided by one embodiment of the present invention; Figure 2 A schematic diagram of monitoring point distribution provided by one embodiment of the present invention; Figure 3 A schematic diagram of ultrasonic wall detection provided by one embodiment of the present invention; Figure 4 A schematic diagram of the distribution of monitoring points on a vertical line provided by one embodiment of the present invention; Figure 5 A flow chart of a method for obtaining defect attention provided by one embodiment of the present invention; Figure 6 A schematic diagram of the distribution of key sections at monitoring points on a perpendicular line provided by one embodiment of the present invention; Figure 7 A flow chart of a method for obtaining comprehensive risk provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0018] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of a method for detecting the density of concrete during pouring construction proposed by the present invention. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0019] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0020] The specific scheme of the density detection method in concrete pouring construction provided by the present invention is described in detail below with reference to the accompanying drawings.

[0021] See also Figure 1 , which shows a flow chart of a density detection method in concrete pouring construction provided by one embodiment of the present invention, the method comprising the following steps: S1: At each monitoring point on the concrete wall, the direction perpendicular to the wall surface is used as the extension direction; an ultrasonic signal sequence in the extension direction is obtained.

[0022] Once a concrete wall is constructed, destructive testing methods (such as cutting and drilling) can compromise the wall's integrity and structural strength. Ultrasonic density testing, however, emits ultrasonic waves and analyzes the reflected waves without damaging the concrete, thereby preserving the wall's integrity and ensuring its structural safety. Therefore, this embodiment uses ultrasonic testing for nondestructive density testing during concrete pouring.

[0023] In the embodiment of the present invention, multiple monitoring points are evenly arranged on the concrete wall to be inspected with uniform thickness. Figure 2, which shows a schematic diagram of the distribution of monitoring points provided by an embodiment of the present invention. Taking the direction perpendicular to the wall as the extension direction, a professional ultrasonic instrument is used to transmit ultrasonic signals to the concrete wall, and the ultrasonic signals propagate along the extension direction. Specifically, a pair of transmitting transducers and receiving transducers are coupled to two surfaces parallel to the measured component, and the axes of the two transducers are on the same straight line. Figure 3 , which shows a schematic diagram of a wall ultrasonic detection provided by an embodiment of the present invention.

[0024] The ultrasonic signal sequence at each monitoring point is obtained. Due to the uniform thickness, the length of the ultrasonic signal sequence is consistent, meaning the total propagation length along the extension direction is consistent and equal to the wall thickness. As can be understood, since the propagation speed of ultrasound in concrete is constant, the ultrasonic signal sequence, plotted on the horizontal axis as time, corresponds to each propagation location within the wall at each moment.

[0025] It should be noted that ultrasonic testing is a well-known technical means well known to those skilled in the art and will not be described in detail here.

[0026] S2: On the same vertical line, determine the abnormal section of the monitoring point in the extension direction according to the signal value deviation of the data points in the ultrasonic signal sequence between each monitoring point and other monitoring points; analyze the degree of matching deviation between each abnormal section of each monitoring point and the ultrasonic signal sequence of other monitoring points to obtain the defect assessment index of the abnormal section; and screen out the key section from the abnormal section based on the defect assessment index.

[0027] Concrete wall pouring is typically carried out in horizontal layers, with vibration moving vertically. Insufficient vibration at a particular layer will result in generally low concrete density within that height range. In a concrete wall structure, the ultrasonic signals at each monitoring point should be essentially identical, reflecting and scattering the ultrasound waves in a consistent manner. This means the ultrasonic signal sequences at each monitoring point should have similar signal values. However, defects such as honeycombs and voids at the monitoring point will alter ultrasonic signal propagation. Therefore, analysis should be conducted along the same vertical line, first comparing the propagation of individual monitoring points within the wall to preliminarily assess the potential presence of lateral defects such as honeycombs and voids within the wall. See [the rest of the text for more information]. Figure 4 , which shows a schematic diagram of the distribution of monitoring points on a vertical line provided by an embodiment of the present invention, wherein the dotted line represents a vertical line.

[0028] Because the overall structure of concrete is typically continuous and relatively homogeneous, while the signals from most monitoring points are highly consistent, a single point with a significant difference in the signal sequence is highly likely to indicate an abnormality in the concrete density at that location, such as honeycombing, voids, slag inclusions, and other quality issues. Therefore, by analyzing the deviations of the data points in the ultrasonic signal sequence, we can preliminarily identify possible abnormal sections.

[0029] Preferably, in an embodiment of the present invention, the method for obtaining an abnormal section includes: First, for any monitoring point, each other monitoring point on the same perpendicular line as that monitoring point is sequentially used as an analysis monitoring point. Similarity analysis is then performed on each of the other monitoring points. A DTW algorithm is applied to the ultrasonic signal sequences of this monitoring point and the analysis monitoring point to obtain matching pairs for each data point in the ultrasonic signal sequence at that monitoring point. The method for obtaining sequence matching pairs using the DTW algorithm is well known to those skilled in the art and will not be detailed here.

[0030] For matching pairs in the DTW algorithm, the distance between data points in each matching pair reflects similarity. Therefore, the distance between data points in each matching pair is calculated and negative correlation mapping is performed to obtain the matching value of each data point to the analysis monitoring point. The smaller the distance, the higher the degree of matching at the data point, that is, the more similar the signals are. It should be noted that negative correlation mapping is a technical means well known to those skilled in the art, such as using inverse proportional values ​​or negative exponential forms with natural constants as the base, and will not be further described here.

[0031] Furthermore, when the mean matching value between the data point of the monitoring point and all other monitoring points on the same vertical line is less than the preset abnormal threshold, the corresponding data point is recorded as an abnormal data point. Through the matching analysis on the same vertical line, the worse the degree of signal matching between the data point and all other monitoring points, that is, the smaller the mean matching value, the more significant the abnormality at the data point. The threshold judgment is used to perform preliminary abnormal point screening. In the embodiment of the present invention, the preset abnormal threshold can be set to 0.6. The specific numerical value is adjusted by the implementer according to the implementation scenario and is not limited here.

[0032] Finally, two or more consecutive abnormal data points on the ultrasonic signal sequence of the monitoring point are merged as an abnormal period. Since the existence of abnormalities usually has a certain range, a single abnormal data point on the ultrasonic signal sequence is very likely to be an error point. Therefore, the local propagation period with possible defects is circled from the signal only by the distribution of consecutive abnormal data points.

[0033] The propagation length position in the extension direction corresponding to each abnormal time period of the ultrasonic signal sequence is then used as each abnormal segment. In one specific embodiment of the present invention, since the ultrasonic velocity is fixed and known, the time in the signal sequence can be converted from the velocity into a horizontal position in the extension direction, that is, the depth from the wall surface. The specific position distance can be obtained using the formula s = v × t, where s represents the position in the extension direction, v is the propagation velocity of the ultrasonic wave in concrete, and t is the time. By obtaining the corresponding first and last positions in the extension direction of each abnormal time period, the length between the first and last positions is the abnormal segment.

[0034] Because abnormal sections may exhibit varying degrees of defect manifestation, there are varying degrees of defect risk. Low-risk sections may be composed of extremely small, localized abnormal data points, where overall signal deviation may not be significant. These areas may represent local interference, potentially introducing interference errors during subsequent defect assessment. Therefore, further quantitative analysis is conducted on the possible abnormal sections to determine the likelihood of actual defects, screening for sections with potentially significant defects for subsequent analysis.

[0035] Preferably, in an embodiment of the present invention, the method for obtaining defect assessment indicators includes: For any abnormal segment at any monitoring point, the similarity between the ultrasonic signal sequence and the ultrasonic signal sequences of all other monitoring points on the same perpendicular line is calculated for the time period corresponding to the abnormal segment. This is used as the matching factor between the abnormal segment and each other monitoring point. A matching test is then performed on the corresponding segment portion of the abnormal segment, and the degree of similarity between the other monitoring points in this segment is analyzed. It should be noted that obtaining inter-sequence similarity is a well-known technique for those skilled in the art, and can employ methods such as the DTW algorithm, the Pearson correlation coefficient, or the Manhattan distance, and is not limited or elaborated upon herein.

[0036] Furthermore, other monitoring points with matching factors less than a preset matching threshold are considered differential monitoring points for the abnormal segment. A smaller matching factor indicates a more significant defect in the abnormal segment relative to other monitoring points. Therefore, the threshold is used to determine differential monitoring points with poor matching. The greater the number of differential monitoring points, the stronger the defect in the abnormal segment. In this embodiment of the present invention, the matching threshold can be set to 0.7. The specific value can be adjusted by the implementer and is not limited here.

[0037] Furthermore, the ratio of the total number of differential monitoring points in the abnormal segment to the total number of all other monitoring points on the same perpendicular line is used as the matching deviation degree of the abnormal segment. The larger the matching deviation degree, the greater the signal difference between the abnormal segment and the more monitoring points, and the more significant the abnormal defect in the abnormal segment. The average value of the matching factor between the abnormal segment and all differential monitoring points is negatively correlated to obtain the matching abnormality degree of the abnormal segment. The smaller the overall matching factor between the abnormal segment and the differential monitoring points, the more significant the difference and the stronger the defect.

[0038] Finally, the defect assessment index of the abnormal segment is obtained by combining the matching deviation and matching abnormality of the abnormal segment. In an embodiment of the present invention, the matching deviation and matching abnormality are both positively correlated with the defect assessment index of the abnormal segment. The product of the matching deviation and matching abnormality of the abnormal segment is normalized as the defect assessment index of the abnormal segment. The larger the defect assessment index, the higher the possibility of defects.

[0039] It should be noted that normalization is a technical means well known to those skilled in the art. The normalization options may be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0040] Defect assessment indicators are used to screen out defective sections that require special attention from abnormal sections. These sections are also known as high-probability defect sections, which have a significant impact on wall density. In this embodiment of the present invention, abnormal sections with defect assessment indicators greater than a preset defect threshold are designated as key sections. The preset defect threshold can be set to 0.7, which can be adjusted by the implementer.

[0041] S3: At each monitoring point, the defect attention level of each monitoring point is obtained based on the degree of ultrasonic signal sequence deviation between key sections, the distribution and aggregation of key sections from the center of the wall, and the defect assessment index. On the same vertical line, the connected sections are determined based on the distribution of key sections of all monitoring points in the extension direction. The comprehensive risk of the wall is obtained based on the distribution and aggregation of connected sections from the ground on each vertical line, the section ratio of each connected section, and the defect attention level of the corresponding monitoring point.

[0042] During concrete pouring, the distribution of defects is related to the construction process. If vibration is uniform, defects should be relatively regular, confined to a small, localized area. However, if vibration is chaotic, such as when the vibrator is moved haphazardly, defects will be randomly distributed, located at varying depths and involving different types of defects. For example, insufficient concrete slump and inadequate vibration during pouring can form continuous horizontal honeycomb bands, or leakage at formwork joints can lead to dense bubbles near horizontal joints. These defects disrupt the continuity of the concrete, causing localized stress concentrations and, in turn, causing cracks to expand in the wall.

[0043] Therefore, the possible defect distribution and quantity in the extension direction are considered at each monitoring point, and a preliminary defect hazard attention level analysis is conducted on the monitoring point. The signal deviation and cluster distribution between key sections are used to reflect the complexity of the defects and the impact of their location. The defect attention level is obtained by combining the defect assessment indicators to measure the defect hazard risk of a single monitoring point.

[0044] Preferably, in the embodiment of the present invention, the method for obtaining defect attention degree can be found in Figure 5 , which shows a flow chart of a method for obtaining defect attention provided by an embodiment of the present invention, the method comprising the following steps: S301: Obtaining the initial attention degree of the monitoring point based on the ultrasound signal sequence difference and distribution spacing between key segments at the monitoring point, as well as the distribution lengths of all key segments.

[0045] Considering that at each monitoring point, the higher the proportion of defects and the more complex their distribution, the greater the impact on structural strength. For example, continuous voids in the thickness direction can weaken shear resistance. Therefore, we focus on analyzing the possible presence of multiple critical sections at the monitoring point. Monitoring points with a single critical section do not require attention analysis.

[0046] For any monitoring point with more than two critical sections, the similarity of the ultrasonic signal sequences between each two key sections at that monitoring point is calculated. The mean of all similarities is negatively correlated and used as the defect complexity for that monitoring point. The degree of defect complexity is quantified by the signal differences between the key sections. Greater defect complexity indicates a more irregular signal distribution between sections, indicating a greater potential for diverse defect types, which could impact the quality and long-term structural stability of the concrete wall and warrants greater attention.

[0047] Furthermore, the spacing between each two adjacent key sections along the extension direction at the monitoring point is calculated, and the mean of all spacing distances is negatively correlated to form the clustered distribution degree of the monitoring point. The clustered distribution degree reflects the distribution concentration of defects. The smaller the spacing distance, the more concentrated the defect distribution, the higher the risk of structural failure in the future, and the higher the level of attention required. It should be noted that the shortest distance between two key sections can be used as the spacing distance to reflect the length of the distribution interval. Distance acquisition is a technical method well known to those skilled in the art and will not be elaborated here.

[0048] Furthermore, the ratio of the length and value of all key sections at the monitoring point to the total propagation length in the extension direction is used as the segment distribution degree of the monitoring point. The degree of hazard is measured by the length distribution ratio of the total defective part at the monitoring point. The higher the overall defect ratio, the greater the risk of hazard at the monitoring point and the higher the level of attention required.

[0049] Finally, the initial attention degree of the monitoring point is obtained by combining the defect complexity, aggregation distribution and segment distribution of the monitoring point. In an embodiment of the present invention, the product of the defect complexity, aggregation distribution and segment distribution is normalized to obtain the initial attention degree of the monitoring point. The risk attention of the extended defense line at the monitoring point is preliminarily measured through the spatial distribution of multiple attention segments.

[0050] S302: Obtain a hazard assessment index for the key section based on the distribution distance between each key section at the monitoring point and the center of the wall and in combination with the defect assessment index.

[0051] The center of a wall is the neutral axis of structural stress and the core area of ​​stress transmission. Defects close to the center can directly weaken the wall's shear and bending resistance. For example, voids in the center can lead to stress concentrations when loaded, easily inducing crack propagation. Therefore, considering the spatial distribution characteristics of critical sections, emphasizing the impact of defects on the wall's strength and bearing capacity, and combining the distance from the center of the wall and the potential significance of defects in critical sections themselves, we prioritize the hazard weight of defects in the central area to accurately assess local risks.

[0052] Furthermore, the distance between each key segment at the monitoring point and the center of the wall is calculated and negatively correlated. This distance is used as the central threat level for each key segment. The closer the distance to the center, the higher the threat level. Combining the central threat level and the defect assessment index for each key segment, a hazard assessment index for each key segment is obtained. In this embodiment of the present invention, the product of the central threat level and the defect assessment index is used as the hazard assessment index for each key segment. The larger the hazard assessment index, the more likely the key segment is to pose a greater hazard.

[0053] S303: Obtain the defect concern level of the monitoring point according to the hazard assessment index and initial concern level of the key section at the monitoring point.

[0054] The attention level is adjusted by the defect risk impact on the spatial distribution, and the defect attention level of the monitoring point is obtained by combining the hazard assessment indicators and initial attention level of all key sections at the monitoring point. In an embodiment of the present invention, the mean value of the hazard assessment indicators of all key sections at the monitoring point is normalized, and the normalized value is multiplied by the initial attention level to obtain the defect attention level of the monitoring point.

[0055] Because defects in concrete walls, such as honeycombs, voids, and slag inclusions, aren't confined to a single area but can extend vertically, for example, when a wall is cast and vibrated in layers (e.g., each layer is approximately 30-50cm high), missing a vibration step (e.g., the vibrator isn't inserted into that layer) can result in low concrete density in that layer. If vibration is omitted in successive layers, defects can become distributed vertically (e.g., honeycombs can be found from 10cm to 30cm).

[0056] Once a connectivity defect is formed, it will pose a threat to the overall structural strength and stability of the entire wall. This vertical connectivity defect will form a weak zone running through the wall. If the vertical connectivity is more serious, the void will cause the upper load to be unable to be transferred to the foundation, causing local collapse.

[0057] Therefore, we analyze the potential connectivity of key segments under the same vertical line and assess the risk impact of connectivity distribution in the vertical direction. First, we determine the connected segments. Since the extension direction is consistent, when the propagation distance of the key segments is consistent, connectivity impact may occur at the same vertical level.

[0058] Therefore, in the embodiment of the present invention, for any vertical line, between each monitoring point and each adjacent monitoring point on the vertical line, when there is a key segment with overlapping distribution positions in the extension direction, the overlapping key segments are merged into one overlapping segment. Figure 6 , which shows a distribution diagram of key sections at monitoring points under the same vertical line provided by an embodiment of the present invention. Monitoring point x, monitoring point x-1 and monitoring point x-2 are adjacent monitoring points under the same vertical line. The dotted line indicates that the adjacent monitoring point x and monitoring point x-1 overlap in position, and key section 1 and key section 2 are an overlapping section.

[0059] After traversing the key sections of all monitoring points on the vertical line, each overlapping section is considered a connected section. Connectivity is used to further analyze the spatial continuity of defects, providing a basis for assessing systemic risk. The location distribution and segment ratio of connected sections reflect the impact of defects on the load-bearing area and the scale of defects. Combined with the defect attention at the location of a single monitoring point, local risks are reflected to determine the overall risk, systematically evaluating the overall impact of defects in different vertical directions.

[0060] Therefore, the scale, location and defect characteristics of the connected sections are comprehensively considered to quantify their impact on density and determine the risk of the wall after comprehensive analysis. Preferably, in the embodiment of the present invention, the method for obtaining the comprehensive risk is described in Figure 7 , which shows a flow chart of a method for obtaining comprehensive risk provided by an embodiment of the present invention, the method comprising the following steps: S311: Obtain a density influencing factor of each connected segment on each vertical line according to the distribution degree of each connected segment in the extension direction and the vertical direction, and the defect attention degree of the monitoring point.

[0061] First, the impact of a single connected section is analyzed, and the proportion of connectivity in the horizontal and vertical directions is used to reflect the expansion range of the defect. Combined with the defect wind direction involving the monitoring point itself, the impact of a single connected section on the overall density is quantified to intuitively reflect the comprehensive risk of the connected section.

[0062] In this embodiment of the present invention, for any connected segment on any vertical line, the ratio of the length of the connected segment in the extension direction to the total propagation length in the extension direction is used as the horizontal distribution index for each connected segment. A larger horizontal distribution index indicates a greater proportion of defects in the wall, resulting in more air voids, honeycomb-like defects, or voids, and a greater impact on the wall's density. The length of the connected segment in the extension direction is the length between the minimum and maximum propagation locations within the connected segment, including the key segment.

[0063] Furthermore, the number of monitoring points contained in the connected segment is used as the vertical distribution index of each connected segment. When the vertical distribution index indicates that the connected segment contains more monitoring points on the vertical line, the greater the expansion of the defect in the vertical space, and the more seriously the internal density of the wall is affected.

[0064] Furthermore, the average defect attention of each connected segment containing monitoring points is taken as the defect impact of each connected segment. The greater the overall defect attention of the connected segment containing monitoring points, the more complex the defects in the connected segment, the wider the impact range, and the greater the impact on the density of the concrete wall.

[0065] Finally, the horizontal distribution index, vertical distribution index and defect impact of each connected segment are combined to obtain the density impact factor of each connected segment. In an embodiment of the present invention, the product of the horizontal distribution index, vertical distribution index and defect impact of each connected segment is used as the density impact factor of each connected segment.

[0066] S312: According to the clustering distribution of the connected segments on each vertical line at a distance from the wall and the ground, combined with the density influencing factor, the risk coefficient of each connected segment is obtained.

[0067] Different connected sections have different locations within the wall and are therefore of varying importance. For example, the base or supporting area of ​​the wall may bear greater external forces. The closer a connected section is to the ground below, the greater its impact on the wall's load-bearing capacity. Therefore, connected sections closer to the load-bearing area and with greater concentration of load require more attention.

[0068] In an embodiment of the present invention, the minimum distance between each connected segment and each other connected segment on the vertical line is calculated, and the average of all minimum distances is used as the distribution spacing value of each connected segment. The distribution spacing value reflects the distribution distance between connected segments. When the distribution spacing value is smaller, it means that the multiple connected segments are more concentrated and the risk is higher.

[0069] Furthermore, the product of the distance of each connected segment from the wall to the ground and the distribution spacing value is negatively correlated and normalized to obtain the ground distribution aggregation index of each connected segment. The larger the ground distribution aggregation index of the connected segment, the closer the connected segment is to the load-bearing area and the more concentrated the distribution is, and the higher the risk of the connected segment.

[0070] Ultimately, the risk coefficient for each connected segment is calculated by combining the density impact factor and the distance-to-ground distribution clustering index for each connected segment. This, combined with the risk impact of the connected segment's own characteristics and the risk impact of its spatial distribution, yields a more comprehensive risk assessment. In this embodiment of the present invention, the product of each connected segment's density impact factor and the distance-to-ground distribution clustering index serves as the risk coefficient for each connected segment.

[0071] S313: Combine the risk coefficients of all connected segments on the vertical line to obtain the comprehensive risk of the wall.

[0072] The risk assessment results of all connected vertical segments are combined to measure the overall risk of the wall. In this embodiment of the present invention, the sum of the risk coefficients of all connected segments on each vertical line is used as the vertical risk of each vertical line, which is then used as the risk assessment result for the vertical line. Finally, the average of the vertical risk scores of all vertical lines is used as the comprehensive risk of the wall.

[0073] At this point, the comprehensive risk of the wall is obtained by combining the spatial distribution characteristics of the defects.

[0074] S4: Based on the distribution density and distance from the ground of monitoring points in key sections of the wall, the impact concentration of the wall is obtained; combined with the comprehensive risk and impact concentration of the wall, a density assessment index is obtained; and density assessment is performed based on the density assessment index.

[0075] For an entire concrete wall, if monitoring points with potential defects are concentrated in a certain local area of ​​the wall, the density within that area will deteriorate, potentially leading to a sharp concentration of stress in that area, directly causing cracks, and thus affecting the safety and durability of the building. Therefore, based on the distribution of monitoring points in a key section, preferably, in an embodiment of the present invention, the method for obtaining the concentration of influence includes: Each monitoring point with a critical section is regarded as a key point, and the ratio between the total number of key points and the total number of all monitoring points is regarded as the key proportion. The higher the proportion, the more extensive the defects of the wall, the higher the universality of the defects, and the worse the density.

[0076] The distance from each key point to the wall floor is then calculated and averaged to obtain the key load-bearing impact, which indicates the proximity of the defect to the ground-bearing area. A smaller key load-bearing impact indicates that the overall key points are closer to the ground area and therefore have a greater load-bearing pressure. The distances between each key point are then calculated and averaged to obtain the key spacing distribution, which indicates the concentration of defects. A smaller key spacing distribution indicates a more concentrated distribution of key points.

[0077] The product of the key load-bearing influence and the key spacing distribution is negatively correlated and mapped to obtain the concentrated distribution influence of the key points. When both the key load-bearing influence and the key spacing distribution are smaller, it means that the key points are more concentrated in the part close to the ground, which is more likely to affect the foundation or structural stability of the wall, and the density is poor.

[0078] Finally, the centralized distribution influence and the critical proportion are combined to obtain the influence concentration of the wall. In an embodiment of the present invention, the product of the centralized distribution influence and the critical proportion is used as the influence concentration of the wall to more comprehensively evaluate the spatial aggregation risk of defects. The greater the influence concentration, the higher the risk.

[0079] Therefore, the density evaluation index is obtained by combining the comprehensive risk and impact concentration of the wall. The smaller the comprehensive risk and impact concentration of the wall, the lower the defect risk faced by the wall and the higher the stability of the wall. Therefore, in an embodiment of the present invention, the product of the comprehensive risk and impact concentration of the wall is negatively correlated and normalized to obtain the density evaluation index. The larger the density evaluation index, the better the density of the wall.

[0080] At this point, the density assessment result of the concrete wall is determined by analyzing the spatial distribution of defects and their harmful effects on the wall density. Based on the density assessment index, a threshold judgment method can be used to perform density assessment detection. In an embodiment of the present invention, a preset first detection threshold of 0.8 and a preset second detection threshold of 0.5 are set. While ensuring that the preset first detection threshold is greater than the preset second detection threshold, the specific numerical value can be adjusted by the implementer.

[0081] When the density assessment index is greater than or equal to the preset first detection threshold, it is considered that the density of the concrete wall meets the design requirements and the defect risk is low, and the density assessment result is recorded as qualified.

[0082] When the density assessment index is less than the preset first detection threshold and greater than the preset second detection threshold, it is considered that the concrete wall has a small amount of defects such as honeycomb and rough surface that do not affect the structural safety. The density assessment result is recorded as good, and more detailed inspection and repair can be carried out later.

[0083] When the density assessment index is less than or equal to the preset second detection threshold, the concrete wall is considered to have significant defects such as through cracks or large-area voids, which makes the strength significantly substandard and affects the structural bearing capacity. The density assessment result is recorded as unqualified, and the wall can be subsequently repaired on a large scale, or demolished and re-cast.

[0084] In summary, the present invention uses the direction perpendicular to the wall surface as the extension direction at multiple monitoring points of the concrete wall, and captures the internal structural characteristics of the wall thickness direction through ultrasonic signals. On the same vertical line, the abnormal section is determined based on the deviation of the ultrasonic signal data points between the monitoring points, and the degree of matching deviation between the abnormal section and other monitoring points is analyzed to obtain the defect assessment index, identify the potential hidden associated defects in the same vertical line, quantify the defect possibility of the abnormal section, and screen the key sections accordingly. The subsequent hazard risk assessment is carried out through the preliminarily screened high-risk sections to improve the comprehensive analysis of hidden defects. At each monitoring point, the signal deviation and cluster distribution between the key sections are analyzed to reflect the complexity of the defects and the influence of the location. The defect attention is obtained in combination with the defect assessment index to measure the defect risk of a single monitoring point. Considering the spatial distribution of defect associations, the connected sections are determined based on the distribution of the key sections. The position distribution and segment proportion of the connected sections reflect the influence of the defect part on the position of the load-bearing area and the scale of the defect. Combined with the defect attention of the single point position, the local risk is reflected to determine the comprehensive risk, and the overall impact of defects in different vertical directions is systematically evaluated. By analyzing the density of monitoring points in key sections and their distance from the ground, we can reflect the clustering of defects and their impact on the load-bearing area, obtain the concentration of impact, and further evaluate the spatial clustering risk of defects to avoid ignoring the potential hazards of concentrated defects. Combining the comprehensive risk and the concentration of impact, we can obtain a density assessment index and conduct an assessment to more comprehensively and accurately reflect the overall density of the wall. The present invention uses multiple monitoring points to identify related defects and quantify risks in the thickness direction of the wall. Combining the spatial distribution of related defects with the quantified risk, we can comprehensively evaluate the wall density, making the detection results more accurate and reliable.

[0085] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0086] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for detecting density in concrete pouring construction, characterized in that: The method comprises: At each monitoring point of the concrete wall, a direction perpendicular to the wall surface is used as an extension direction; and an ultrasonic signal sequence in the extension direction is obtained; On the same vertical line, the abnormal section of the monitoring point in the extension direction is determined based on the signal value deviation of the data points in the ultrasonic signal sequence between each monitoring point and other monitoring points; the degree of matching deviation between each abnormal section of each monitoring point and the ultrasonic signal sequence of other monitoring points is analyzed to obtain the defect assessment index of the abnormal section; and the key section is screened out from the abnormal section based on the defect assessment index; At each monitoring point, the defect concern level of each monitoring point is determined based on the degree of ultrasonic signal sequence deviation between key sections, the distribution and aggregation of key sections from the center of the wall, and the defect assessment index. On the same vertical line, connected sections are determined based on the distribution of key sections at all monitoring points in the extension direction. The comprehensive risk of the wall is determined based on the distribution and aggregation of connected sections from the ground on each vertical line, the proportion of each connected section, and the defect concern level of the corresponding monitoring point. The impact concentration of the wall is obtained based on the distribution density and distance from the ground of the monitoring points in the key sections of the wall. The density assessment index is obtained by combining the comprehensive risk and impact concentration of the wall. The density is evaluated based on the density evaluation index.

2. The method for detecting density during concrete pouring construction according to claim 1, wherein: The method for obtaining the abnormal section includes: For any monitoring point, each other monitoring point on the same vertical line as the monitoring point is taken as the analysis monitoring point; The DTW algorithm is applied to the ultrasonic signal sequence of the monitoring point and the analysis monitoring point to obtain a matching pair of each data point in the ultrasonic signal sequence of the monitoring point; the distance between the data points in each matching pair of data points is calculated and negative correlation mapping is performed to obtain a matching value of each data point to the analysis monitoring point; When the mean of the matching values ​​between the data point of the monitoring point and all other monitoring points on the same vertical line is less than the preset abnormal threshold, the corresponding data point is recorded as an abnormal data point; Two or more consecutive abnormal data points on the ultrasonic signal sequence of the monitoring point are merged to form an abnormal period; the propagation length position in the extension direction corresponding to each abnormal period of the ultrasonic signal sequence is taken as each abnormal segment.

3. The method for detecting density during concrete pouring construction according to claim 1, wherein: The method for obtaining the defect assessment index includes: For any abnormal section at any monitoring point, during the time period of the ultrasonic signal sequence corresponding to the abnormal section, the similarity between the ultrasonic signal sequence and the ultrasonic signal sequences of each other monitoring point on the same perpendicular line is calculated as the matching factor between the abnormal section and each other monitoring point; Other monitoring points with matching factors less than the preset matching threshold are regarded as difference monitoring points of the abnormal section; The ratio of the total number of difference monitoring points in the abnormal section to the total number of all other monitoring points on the same perpendicular line is taken as the matching deviation degree of the abnormal section; Perform negative correlation mapping between the abnormal section and the mean of the matching factors of all difference monitoring points to obtain the matching abnormality degree of the abnormal section; The defect assessment index of the abnormal section is obtained by combining the matching deviation degree and the matching abnormality degree of the abnormal section.

4. The method for detecting density during concrete pouring construction according to claim 1, wherein: The method for obtaining the defect attention level includes: For any monitoring point with more than two key sections, the similarity of the ultrasonic signal sequence between every two key sections at the monitoring point is calculated, and the mean of all similarities is negatively correlated and mapped as the defect complexity of the monitoring point; Calculate the interval distance between each two adjacent key sections in the extension direction of the monitoring point, and perform negative correlation mapping on the mean of all interval distances as the aggregation distribution degree of the monitoring point; The ratio of the sum of the lengths of all key segments at the monitoring point to the total propagation length in the extension direction is taken as the segment distribution degree of the monitoring point; Combine the defect complexity, cluster distribution and segment distribution of the monitoring point to obtain the initial attention of the monitoring point; Calculate the distance between each key section at the monitoring point and the center of the wall and perform negative correlation mapping to obtain the central threat degree of each key section. Combine the central threat degree of each key section with the defect assessment index to obtain the hazard assessment index of each key section. The defect attention level of the monitoring point is obtained by combining the hazard assessment indicators and initial attention levels of all key sections at the monitoring point.

5. The method for detecting density during concrete pouring construction according to claim 1, characterized in that: The method for obtaining the connected segments includes: For any vertical line, between each monitoring point and each adjacent monitoring point on the vertical line, when there is a key segment with overlapping distribution positions in the extension direction, the overlapping key segments are merged into one overlapping segment; After traversing the key segments of all monitoring points on the vertical line, each overlapping segment is regarded as a connected segment.

6. A density detection method in concrete pouring construction according to claim 1, characterized in that: The method for obtaining the comprehensive risk includes: For any connected segment on any vertical line, the ratio of the length of the connected segment in the extension direction to the total propagation length in the extension direction is used as the horizontal distribution index of each connected segment; the number of monitoring points contained in the connected segment is used as the vertical distribution index of each connected segment; the average defect attention of the monitoring points contained in each connected segment is used as the defect impact of each connected segment; the horizontal distribution index, vertical distribution index and defect impact of each connected segment are combined to obtain the density impact factor of each connected segment; Calculate the minimum distance between each connected segment and every other connected segment on the vertical line, and use the average of all minimum distances as the distribution spacing value of each connected segment. Perform negative correlation mapping and normalization on the product of the distance of each connected segment from the wall and the ground and the distribution spacing value to obtain the ground distribution aggregation index of each connected segment. Combine the density influencing factor and the ground distribution aggregation index of each connected segment to obtain the risk coefficient of each connected segment. The comprehensive risk of the wall is obtained by combining the risk coefficients of all connected segments on the vertical line.

7. A density detection method in concrete pouring construction according to claim 1, characterized in that: The method for obtaining the influence concentration includes: Each monitoring point with a key section is regarded as a key point; the ratio between the total number of key points and the total number of all monitoring points is regarded as the key ratio; The distance between each key point and the wall and the ground is calculated and averaged to obtain the key load-bearing influence. The distance between each key point is calculated and averaged to obtain the key spacing distribution. The product of the key load-bearing influence and the key spacing distribution is negatively correlated to obtain the centralized distribution influence of the key points. The influence concentration of the wall is obtained by combining the centralized distribution influence and the key proportion.

8. The method for detecting density during concrete pouring construction according to claim 1, characterized in that: The method for obtaining the density evaluation index includes: The product of the comprehensive risk and impact concentration of the wall is negatively correlated and normalized to obtain the density assessment index.

9. A density detection method in concrete pouring construction according to claim 1, characterized in that: The density assessment based on the density assessment index includes: When the density evaluation index is greater than or equal to the preset first detection threshold, the density evaluation result is recorded as qualified; When the density evaluation index is less than the preset first detection threshold and greater than the preset second detection threshold, the density evaluation result is recorded as good; When the density evaluation index is less than or equal to the preset second detection threshold, the density evaluation result is recorded as unqualified; the preset first detection threshold is greater than the preset second detection threshold.

10. A density detection method in concrete pouring construction according to claim 1, characterized in that: The method for obtaining the key section includes: The abnormal section whose defect assessment index is greater than the preset defect threshold is regarded as the key section.

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