3D imaging algorithm for scanning defects in concrete

Abstract

The invention provides a concrete internal scanning defect 3D imaging algorithm, and belongs to the technical field of concrete detection, and the algorithm comprises the following steps: 1, installing a detection device; an acceleration sensor matrix is pre-laid on a to-be-detected concrete structure, and impact equipment is moved to a to-be-detected area; step 2, data acquisition; according to the method, an impact echo method is adopted, impact equipment is used for impacting a concrete structure, elastic waves are generated, elastic wave signals are received through a pre-laid acceleration sensor matrix, and original data in concrete are obtained; 3, preprocessing the original data; 4, data analysis; calculating and analyzing the preprocessed data; 5, constructing a model; the position, size and shape information of the defect is determined according to the analysis result, a three-dimensional visualization technology is adopted, a three-dimensional model in the concrete is constructed, the structure in the concrete and the defect distribution condition are displayed, and the problem that a traditional detection method lacks visualization is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of concrete detection, and more specifically, particularly relates to a 3D imaging algorithm for scanning defects inside concrete. Background Art

[0002] As one of the most commonly used materials in today's construction projects, the quality and structural integrity of concrete are very important to the safety and durability of buildings. During the long-term use of concrete structures, due to the influence of various natural and human factors, internal defects such as holes and cracks are inevitable. Once these defects develop to a dangerous level, they may seriously affect the bearing capacity and service life of the concrete structure, and even endanger the safety of the building.

[0003] With the continuous advancement of science and technology, the demand for non-destructive testing of concrete structures is growing; however, traditional testing methods are not only destructive, but also the test results are not accurate and comprehensive enough; in recent years, some advanced non-destructive testing technologies, such as ultrasonic testing, radar testing, etc., although they have improved the accuracy and efficiency of testing to a certain extent, there are still deficiencies in the visualization of defects.

[0004] In this context, 3D imaging technology has gradually become a development direction for concrete internal defect detection. By scanning the interior of the concrete and using 3D imaging technology to convert the scanning data into clear 3D images, the internal structure and defect distribution of the concrete can be intuitively displayed. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a 3D imaging algorithm for scanning defects inside concrete to solve the technical problem in the prior art that, although the traditional detection method can detect the situation inside the concrete to a certain extent, it still has insufficient visualization of defects.

[0006] The purpose and effect of the 3D imaging algorithm for scanning defects inside concrete of the present invention are achieved by the following specific technical means:

[0007] A 3D imaging algorithm for scanning defects inside concrete includes the following steps:

[0008] Step 1: Install the testing equipment;

[0009] Pre-lay an acceleration sensor matrix on the concrete structure to be tested, and move the impact device to the area to be tested;

[0010] Step 2: Data acquisition;

[0011] The impact echo method is adopted, the impact device is used to impact the concrete structure to generate elastic waves, and the elastic wave signals are received by the pre-laid acceleration sensor matrix to obtain the original data inside the concrete;

[0012] Step 3: Data preprocessing;

[0013] Preprocess the raw data to remove noise and interference signals and improve data quality;

[0014] Step 4: Data analysis;

[0015] Perform computational analysis on the preprocessed data and identify possible defect areas inside the concrete by analyzing the characteristics of the frequency domain signal;

[0016] Step 5: Model construction;

[0017] The location, size and shape of the defects are determined based on the analysis results, and a three-dimensional model of the interior of the concrete is constructed using three-dimensional visualization technology.

[0018] In a preferred embodiment, in step one, the acceleration sensor matrix includes a plurality of acceleration sensors arranged at equal intervals on the surface of the concrete structure to be detected; the number of acceleration sensors in the acceleration sensor matrix is ​​50 to 80, the spacing between the plurality of groups of acceleration sensors is a uniform spacing of 10 cm to 30 cm, and the plurality of groups of acceleration sensors are installed on the surface of the concrete structure by gluing, bolting or magnetic adsorption.

[0019] In a preferred embodiment, in step three, the preprocessing includes using a Butterworth filter to remove high-frequency noise and low-frequency interference using a digital filtering algorithm, reducing data fluctuations through smoothing, and performing data enhancement operations to improve the signal-to-noise ratio of the signal.

[0020] In a preferred embodiment, the calculation formula of the digital filtering algorithm is:

[0021]

[0022] Where ω represents the angular frequency, ω c represents the cutoff frequency, and n represents the order of the filter.

[0023] In a preferred embodiment, the smoothing process uses a moving average method or a median filtering method to reduce random fluctuations in data, and the data enhancement operation can improve the signal-to-noise ratio by amplifying the amplitude of the signal or increasing the number of repetitions of the signal.

[0024] In a preferred embodiment, in step 4, the calculation formula for calculating and analyzing the preprocessed data is:

[0025]

[0026] In the formula, ω represents the angular frequency, t represents the time, x(t) represents the time domain signal, x(ω) represents the frequency domain signal, and e -iwt represents the complex exponential function.

[0027] In a preferred embodiment, in step five, determining the location, size and shape information of the defect includes:

[0028] Assume that the coordinates of the concrete structure in three-dimensional space are (x, y, z). For each detection point, when there is a defect at the detection point, a specific attribute value is assigned to the point, and D(x, y, z) is used to represent the defect attribute of the point.

[0029] In a preferred embodiment, the defect attributes include defective and non-defective, the defective includes D(x, y, z)=1, and the non-defective includes D(x, y, z)=0. By connecting adjacent points with the same attribute values, the surface of the defective area is formed, thereby constructing a three-dimensional model.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. By pre-laying an acceleration sensor matrix on the surface of the concrete structure, the elastic wave signal generated by the impact echo can be received from multiple positions at the same time, so as to obtain more comprehensive information inside the concrete; by calculating and analyzing the pre-processed data, the possible defect areas inside the concrete can be identified; and, by using 3D visualization technology to build a 3D model inside the concrete, the location, size and shape information of the defects are clearly presented, and the structure and defect distribution inside the concrete are intuitively displayed. For complex large-scale concrete structures, such as bridges and high-rise buildings, the algorithm can locate the specific locations of defects such as cracks and voids, helping engineers to better understand the internal conditions of the structure and provide a strong basis for formulating reasonable repair plans.

[0032] 2. In terms of data processing, Butterworth filter is used for digital filtering to remove high-frequency noise and low-frequency interference to make the data purer. Moving average method or median filtering method is used for smoothing to reduce random fluctuations of data, retain key spectral features, and improve data stability. At the same time, data enhancement operation improves the signal-to-noise ratio by amplifying the signal amplitude or increasing the number of signal repetitions, further enhancing the reliability of the data. These measures work together to enable the algorithm to be more efficient in processing large amounts of scanning data, reduce computing time, improve imaging quality, obtain detection results faster, improve the efficiency of engineering detection, and reduce costs.

[0033] 3. The number of acceleration sensors in the acceleration sensor matrix is ​​50 to 80, and the spacing is a uniform number between 10cm and 30cm. It can be installed in a variety of ways, such as pasting, bolting or magnetic adsorption. It can adapt to concrete structures of different sizes and shapes. Whether it is a small concrete component or a large concrete project, it can be reasonably arranged according to the actual situation. While improving the applicability, it also ensures the accuracy and comprehensiveness of the detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a flow chart of the steps of a 3D imaging algorithm for scanning defects inside concrete according to the present invention. DETAILED DESCRIPTION

[0035] In order to further understand the present invention, preferred embodiments of the present invention are described below in conjunction with the accompanying drawings and examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the present invention.

[0036] Example:

[0037] Please refer to Figure 1 As shown, the present invention provides a 3D imaging algorithm for scanning defects inside concrete, comprising the following steps:

[0038] Step 1: Install the testing equipment;

[0039] First, it is necessary to pre-deploy an acceleration sensor matrix on the surface of the concrete structure to be tested. This acceleration sensor matrix can fully collect the elastic wave signals generated inside the concrete, laying a solid foundation for subsequent data analysis. At the same time, it is also necessary to move the impact device to the area to be tested, and prepare to impact the concrete structure to induce elastic wave signals. Through such preparatory work, the detection equipment can be in place, making full preparations for subsequent data collection and analysis.

[0040] Step 2: Data acquisition;

[0041] After the installation of the testing equipment is completed, the data acquisition phase can begin. Specifically, the impact echo method will be used to impact the concrete structure to be tested. This impact behavior will generate a series of elastic wave vibration signals inside the concrete, which carry the internal structure information of the concrete. The acceleration sensor matrix pre-deployed on the concrete surface can capture these elastic wave signals in real time and convert them into electronic data, providing the original basis for subsequent data analysis. Through this impact echo method, comprehensive information inside the concrete can be obtained non-invasively, avoiding the limitations of traditional destructive tests.

[0042] Step 3: Data preprocessing;

[0043] After obtaining the raw data inside the concrete, it is necessary to pre-process these data and use digital filtering technology to remove noise and interference signals in the raw data to improve data quality;

[0044] Step 4: Data analysis;

[0045] After completing the data preprocessing, the preprocessed data can be calculated and analyzed to identify possible defective areas inside the concrete, and the preprocessed data can be analyzed in the frequency domain. By analyzing the characteristics of the elastic wave signal inside the concrete in different frequency bands, those frequency intervals with obvious abnormalities can be found. These abnormal frequencies usually mean that there may be defects or cracks inside the concrete. The voids and cracks in the concrete will cause the elastic waves to have characteristics such as energy drop or resonant frequency shift in certain frequency bands. Therefore, based on the in-depth analysis of these frequency domain characteristics, the areas inside the concrete that may have problems can be determined, providing an important basis for subsequent 3D reconstruction and visualization.

[0046] Step 5: Model construction;

[0047] After completing the in-depth analysis of the frequency domain characteristics of the elastic wave signal, these analysis results can be further used to construct a three-dimensional model of the interior of the concrete; based on the abnormal frequency range identified previously, the location, size, shape and other information of possible defects in the concrete can be determined. Once these key parameters are determined, they can be intuitively mapped into a three-dimensional space with the help of three-dimensional visualization technology, thereby constructing a three-dimensional model of the interior of the concrete; this three-dimensional model can not only clearly show the specific location of the defects, but also reflect their size and shape characteristics. Through this visualization method, engineering and technical personnel can not only better understand the actual situation inside the concrete, but also provide important basis for subsequent maintenance.

[0048] In the process of preliminary setting up the detection equipment in step 1, the acceleration sensor matrix is ​​arranged. The acceleration sensor matrix includes multiple acceleration sensors installed at equal intervals on the surface of the concrete structure to be detected. This acceleration sensor matrix consists of 50 to 80 acceleration sensors, which are evenly distributed on the surface of the concrete structure to be detected, and maintain a uniform spacing of 10 cm to 30 cm between each other. This dense and orderly sensor array can capture the elastic wave signals generated by impact excitation inside the concrete from multiple positions, so as to obtain more comprehensive information inside the concrete, and lay a solid foundation for subsequent data analysis; in addition, these acceleration sensors can be installed in a variety of ways, such as pasting, bolting or magnetic adsorption, so as to ensure that they can be firmly attached to the surface of concrete structures of various sizes and shapes. Whether it is a small component or a large engineering project, the layout of the sensor matrix can be flexibly adjusted according to the actual situation to improve the applicability and accuracy of the detection.

[0049] In step three after completing the deployment of the acceleration sensor matrix and data acquisition, a series of preprocessing operations are required for the acquired raw data to improve the quality and availability of the data; the digital filtering algorithm such as the Butterworth filter is used to specifically remove high-frequency noise and low-frequency interference, so that the effective elastic wave signal can be highlighted; secondly, smoothing processing techniques such as moving average smoothing or median filtering are applied to reduce random fluctuations in the data and obtain more stable signal characteristics; and data enhancement operations further improve the signal-to-noise ratio of the signal, laying a good foundation for subsequent frequency domain analysis; through this series of preprocessing links, the quality and reliability of the original data have been greatly improved, thus creating favorable conditions for accurately identifying internal defects of concrete.

[0050] When performing digital filtering operations, a digital filtering algorithm will be used, and the calculation formula is:

[0051]

[0052] Where ω represents the angular frequency, ω c Represents the cutoff frequency, n represents the order of the filter, and digital filtering through the Butterworth filter can effectively remove high-frequency noise and low-frequency interference, making the original data purer and more stable; the algorithm has the advantages of flat amplitude characteristics and linear phase characteristics, and can better retain the key features of the signal; therefore, applying this digital filtering algorithm to the preprocessing of elastic wave signals inside concrete can effectively improve the quality of the data.

[0053] In addition to using the Butterworth filter to remove noise interference, other effective measures are taken in the preprocessing stage. On the one hand, smoothing techniques such as moving average or median filtering are applied to successfully reduce random fluctuations in the original data while retaining key spectral features, thereby improving the stability of the data; on the other hand, data enhancement operations such as amplifying the signal amplitude or increasing the number of repetitions are used to significantly improve the signal-to-noise ratio and further enhance the reliability of the data; the comprehensive application of these preprocessing methods enables the subsequent frequency domain analysis and three-dimensional reconstruction stages to run more efficiently, reduces calculation time, improves imaging quality, and enables detection results to be presented faster, making the algorithm more efficient when processing large amounts of scanning data, reducing calculation time, improving imaging quality, improving the efficiency of engineering detection, and reducing costs.

[0054] In step 4, after the preliminary data preprocessing, the data will enter the calculation analysis, and the preprocessed time domain signal will be analyzed in the frequency domain. The calculation formula is:

[0055]

[0056] In the formula, ω represents the angular frequency, t represents the time, x(t) represents the time domain signal, x(ω) represents the frequency domain signal, and e -iwt represents a complex exponential function; through this transformation, the original time domain waveform data can be converted into frequency domain spectrum, thus creating favorable conditions for subsequent signal analysis and feature extraction; frequency domain analysis can effectively reflect the frequency characteristics of elastic waves in the propagation process, and provides an important basis for accurately identifying internal defects of concrete.

[0057] In step five, after the aforementioned data preprocessing and frequency domain analysis, the specific location, size and shape information of the internal defects of the concrete will be determined; it is necessary to establish a coordinate system of the concrete structure in three-dimensional space, in which the coordinates of each detection point can be expressed by (x, y, z). For those detection points with defects, a specific attribute value D(x, y, z) will be assigned to identify the defect characteristics of the point. By analyzing the distribution of these detection points with defect attribute values, the accurate location, size and shape information of the internal defects of the concrete can be further inferred. These results can not only provide valuable reference for the project, but also an important basis for the subsequent repair and maintenance work. In the specific implementation process, the defect attributes will be further refined, that is, for those detection points with defects, D will be assigned to them. The attribute value of (x, y, z) = 1, while the defect-free point corresponds to D(x, y, z) = 0; by connecting adjacent detection points with the same attribute values, the surface contour of the defective area can be clearly outlined, and finally a complete three-dimensional model can be constructed. This model can not only intuitively display the structural characteristics and defect distribution inside the concrete, but also for some complex large-scale concrete structures, such as bridges, high-rise buildings, etc., it can also accurately locate the specific locations of various defects such as cracks and voids; compared with traditional detection methods, the visualization effect of this algorithm is more outstanding, which not only helps engineers better understand the internal conditions of the structure, but also provides a reliable basis for the subsequent formulation of scientific and reasonable repair plans. It not only solves the problem of lack of visualization, but also improves the efficiency and quality of engineering detection.

[0058] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A 3D imaging algorithm for scanning defects inside concrete, characterized by: The following steps are included: Step 1: Install the testing equipment; Pre-lay an acceleration sensor matrix on the concrete structure to be tested, and move the impact device to the area to be tested; Step 2: Data acquisition; The impact echo method is adopted, the impact device is used to impact the concrete structure to generate elastic waves, and the elastic wave signals are received by the pre-laid acceleration sensor matrix to obtain the original data inside the concrete; Step 3: Data preprocessing; Preprocess the raw data to remove noise and interference signals and improve data quality; Step 4: Data analysis; Perform computational analysis on the preprocessed data and identify possible defect areas inside the concrete by analyzing the characteristics of the frequency domain signal; Step 5: Model construction; The location, size and shape of the defects are determined based on the analysis results, and a three-dimensional model of the interior of the concrete is constructed using three-dimensional visualization technology.

2. The 3D imaging algorithm for scanning defects inside concrete according to claim 1 is characterized by: In step one, the acceleration sensor matrix includes a plurality of acceleration sensors arranged at equal intervals on the surface of the concrete structure to be detected; the number of acceleration sensors in the acceleration sensor matrix is ​​50 to 80, the spacing between the plurality of groups of acceleration sensors is a uniform spacing of 10 cm to 30 cm, and the plurality of groups of acceleration sensors are installed on the surface of the concrete structure by pasting, bolting or magnetic adsorption.

3. The 3D imaging algorithm for scanning defects inside concrete according to claim 1 is characterized by: In step three, the preprocessing includes using a Butterworth filter to remove high-frequency noise and low-frequency interference using a digital filtering algorithm, reducing data fluctuations through smoothing, and performing data enhancement operations to improve the signal-to-noise ratio of the signal.

4. The 3D imaging algorithm for scanning defects inside concrete according to claim 3 is characterized by: The calculation formula of the digital filtering algorithm is: Where ω represents the angular frequency, ω c represents the cutoff frequency, and n represents the order of the filter.

5. The 3D imaging algorithm for scanning defects inside concrete according to claim 3 is characterized by: The smoothing process uses a moving average method or a median filtering method to reduce random fluctuations in data, and the data enhancement operation can improve the signal-to-noise ratio by amplifying the amplitude of the signal or increasing the number of repetitions of the signal.

6. The 3D imaging algorithm for scanning defects inside concrete according to claim 1 is characterized by: In step 4, the calculation formula for calculating and analyzing the preprocessed data is: In the formula, ω represents the angular frequency, t represents the time, x(t) represents the time domain signal, x(ω) represents the frequency domain signal, and e -iwt represents the complex exponential function.

7. The 3D imaging algorithm for scanning defects inside concrete according to claim 1, characterized in that: In step five, the location, size and shape information of the defect are determined including; Assume that the coordinates of the concrete structure in three-dimensional space are (x, y, z). For each detection point, when there is a defect at the detection point, a specific attribute value is assigned to the point, and D(x, y, z) is used to represent the defect attribute of the point.

8. The 3D imaging algorithm for scanning defects inside concrete according to claim 7 is characterized by: The defect attributes include defective and non-defective. The defective includes D(x, y, z)=1, and the non-defective includes D(x, y, z)=0. By connecting adjacent points with the same attribute values, the surface of the defective area is formed, thereby constructing a three-dimensional model.

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