Concrete filled steel tube void detection method, equipment and device based on fluctuation analysis

Abstract

The invention discloses a concrete filled steel tube void detection method, equipment and device based on fluctuation analysis, and relates to the field of building structure detection.The method comprises the steps that a time domain signal set is obtained, a normalized judgment index corresponding to a target concrete filled steel tube member is calculated, and then a finite element model is optimized to obtain a standby finite element model; one time domain signal set is obtained by detecting a plurality of target concrete filled steel tube members by adopting one measurement method; different time domain signal sets correspond to different measurement methods; performing wavelet packet numerical simulation fitting on the basis of the to-be-used finite element model and the time domain signal set to obtain a fitting function formula of a wavelet packet energy value and the void defect; and according to the actual time domain signal corresponding to the actual concrete filled steel tube member, extracting to obtain an actual wavelet packet energy value, and inputting the actual wavelet packet energy value into the corresponding fitting function formula to obtain the void defect. According to the invention, nondestructive testing of the concrete filled steel tube can be rapidly realized.

Description

Technical Field

[0001] This application relates to the field of building structure testing, and in particular to a method, equipment and apparatus for detecting voids in steel-concrete composite structures based on wave analysis. Background Technology

[0002] Steel-concrete composite structures are widely used in civil engineering. Because the steel tubes encase the concrete, placing the concrete in a triaxial stress state with the strongest load-bearing capacity, they exhibit a "hoop effect," resulting in high load-bearing capacity, strong seismic performance, and convenient construction. Therefore, they are widely used in various projects such as high-rise buildings, bridges, tunnels, and marine engineering. However, due to various factors such as construction quality, material aging, and natural disasters, debonding may occur between the steel tubes and the concrete surface in steel-concrete composite structures. If not detected and repaired in time, this can lead to a decrease in the strength and stability of the structure, and may even cause the entire structure to collapse, resulting in significant losses of life and property. Therefore, the rapid and accurate detection and assessment of debonding defects in steel-concrete composite structures is particularly important.

[0003] Currently, there are three methods for detecting void defects in steel-concrete composite pipes: percussion inspection, drilling verification, and ultrasonic testing. However, percussion inspection has significant limitations due to its heavy reliance on the experience of the person performing the percussion; drilling verification is prone to damaging the integrity of the building structure and is therefore not considered non-destructive testing; and ultrasonic testing is not suitable for large-area testing due to its low efficiency and complex equipment operation. Summary of the Invention

[0004] The purpose of this application is to provide a method, equipment, and apparatus for detecting voids in steel-concrete composite tubes based on wave analysis, which can quickly achieve non-destructive testing of steel-concrete composite tubes.

[0005] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a method for detecting voids in steel-concrete composite structures based on wave analysis, including: Multiple time-domain signal sets are acquired; one of the time-domain signal sets is obtained by using a measurement method to detect multiple target steel-concrete composite members; different time-domain signal sets correspond to different measurement methods; different target steel-concrete composite members have different void defects; For any of the time-domain signal sets, calculate the normalized judgment index corresponding to each of the target steel-concrete composite components; A finite element model for detecting the target steel-concrete composite member is constructed, and the finite element model is optimized using the time-domain signal set and the normalized judgment index corresponding to the target steel-concrete composite member to obtain the finite element model to be used. Numerical simulation and wavelet packet analysis are performed based on the finite element model to be used and the time domain signal set to obtain the fitting function formula of wavelet packet energy value and void defect. The actual wavelet packet energy value is extracted from the actual time-domain signal corresponding to the actual steel-concrete composite member, and then the actual wavelet packet energy value is input into the corresponding fitting function formula to obtain the void defect.

[0006] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a method for detecting voids in steel-concrete composite pipes based on wave analysis.

[0007] Thirdly, this application provides a device for detecting void defects in steel-concrete composite based on wave analysis. The device includes a function signal generator, a first piezoelectric ceramic sensor, a second piezoelectric ceramic sensor, an oscilloscope, and a computer device. The computer device is used to receive the time-domain signal collected by the oscilloscope.

[0008] According to the specific embodiments provided in this application, this application has the following technical effects: A normalized judgment index is introduced to quantify the correlation between interface features and the amplitude of the detection signal. A linear model is established based on the finite element model and wavelet packet energy analysis, revealing the linear relationship between wavelet packet energy values ​​and void defects, thus providing a foundation for quantitative detection of interface defects and a comprehensive and accurate new detection method for health monitoring of steel-concrete composite structures. Combining the above methods can improve detection accuracy and achieve qualitative and quantitative defect analysis. Furthermore, based on the above methods, in practical applications, the actual wavelet packet energy value can be extracted from the actual time-domain signal corresponding to the actual steel-concrete composite component, and then the actual wavelet packet energy value can be input into the corresponding fitting function formula to obtain the void defect, thereby realizing rapid and non-destructive testing of steel-concrete composite structures. In summary, this application, by integrating multiple measurement methods and employing wavelet packet energy analysis technology, can accurately and rapidly detect and quantify void defects in steel-concrete composite structures, and has significant engineering application value. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1This is an application environment diagram of a method for detecting voids in steel-concrete composite tubular structures based on wave analysis, as described in one embodiment of this application.

[0011] Figure 2 This is a flowchart illustrating a method for detecting voids in steel-concrete composite structures based on wave analysis, provided as an embodiment of this application.

[0012] Figure 3 This is a diagram illustrating the pasting process of acrylic sheets.

[0013] Figure 4 This is a schematic diagram of the horizontal measurement method.

[0014] Figure 5 This is a schematic diagram of the oblique measurement method.

[0015] Figure 6 This is a schematic diagram of the void detection experiment.

[0016] Figure 7 A linear diagram showing the relationship between the normalized judgment index DI for different size information and void defects.

[0017] Figure 8 This is a linear diagram showing the relationship between the normalized judgment index DI and void defects for different measurement methods.

[0018] Figure 9 This is a schematic diagram of the mesh for the finite element model.

[0019] Figure 10 This is a stress contour plot of the finite element model.

[0020] Figure 11 This is a schematic diagram of the fitted function curve obtained from PC20.

[0021] Figure 12 This is a schematic diagram of the fitted function curve obtained from PC30.

[0022] Figure 13 This is a schematic diagram of the fitted function curve obtained for XC.

[0023] Figure 14 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application.

[0024] Figure labels: 1-Steel pipe; 2-Acrylic sheet; 3-Concrete; 4-First piezoelectric ceramic sensor; 5-Second piezoelectric ceramic sensor; 6-Spacing 20cm; 7-Spacing 30cm; 8-Function signal generator; 9-Oscilloscope; 10-Wavelet packet analysis. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] This application focuses on the assessment of void defects in completed concrete-filled steel tubular (CFST) structures, enabling a systematic study of the propagation mechanism of stress waves in CFST structures. Based on the propagation characteristics of stress waves, it reveals the influence of different void lengths and heights on stress wave propagation characteristics, optimizes existing testing methods, and proposes new testing methods for comprehensive assessment. It establishes a feature extraction and quantification method for void defects, proposes new evaluation indicators for void defects, and verifies the effectiveness and practicality of the proposed methods through indoor experiments. Numerical simulation reveals the mechanism, and wavelet packet energy analysis reveals the influence of different void lengths and heights on wavelet packet energy values. It quantitatively detects the void length and height in CFST structures, providing a scientific basis and experimental data for the health monitoring and maintenance of CFST structures.

[0027] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0028] The method for detecting voids in steel-concrete composite tubular structures based on wave analysis provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on another server. Terminal 102 can send a set of time-domain signals to server 104. After receiving the signal, server 104 calculates the normalized judgment index corresponding to the target steel-concrete composite member, constructs a finite element model for detecting the target steel-concrete composite member, and optimizes the finite element model using the normalized judgment index corresponding to the target steel-concrete composite member to obtain a usable finite element model. Finally, based on the usable finite element model and the set of time-domain signals, wavelet packet numerical simulation fitting is performed to obtain the fitting function formula between the wavelet packet energy value and the void defect. Alternatively, when terminal 102 sends actual time-domain signals to server 104, server 104 first calculates the actual wavelet packet energy value, and then calls the stored fitting function formula to calculate the void defect.

[0029] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers, or it can be a cloud server.

[0030] In one exemplary embodiment, such as Figure 2 As shown, a method for detecting voids in steel-concrete composite tubular structures based on wave analysis is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps 201 to 205.

[0031] Step 201: Obtain multiple time-domain signal sets; each time-domain signal set is obtained by using a measurement method to detect multiple target steel-concrete composite components; different time-domain signal sets correspond to different measurement methods; different target steel-concrete composite components have different void defects; different measurement methods include oblique measurement methods and various horizontal measurement methods; different horizontal measurement methods correspond to different transmit and receive intervals.

[0032] In a specific application, the selected measurement methods include three types: horizontal measurement with a transmit / receive distance of 20cm, horizontal measurement with a transmit / receive distance of 30cm, and oblique measurement. When using one of these methods, such as the horizontal measurement with a transmit / receive distance of 20cm, the transceiver components (such as two piezoelectric ceramic sensors) are set up according to the 20cm transmit / receive distance and the requirements of the horizontal measurement. Then, the voltage change curve within a certain period, i.e., the time domain signal, is obtained by receiving the data with an oscilloscope. For a target steel-concrete composite member with a void defect, based on the above-mentioned horizontal measurement with a transmit / receive distance of 20cm, one time domain signal can be obtained; for multiple target steel-concrete composite members with different void defects, multiple time domain signals can be obtained, i.e., a set of time domain signals.

[0033] In a specific application example, the multiple target steel-tube concrete components include one healthy steel-tube concrete component and at least one voided steel-tube concrete component, such as six voided steel-tube concrete components; different voided steel-tube concrete components have different voiding defects, and the voiding defect corresponding to the healthy steel-tube concrete component can be regarded as empty. In addition, the voiding defect is characterized by voiding length and voiding height. Specifically, the preparation steps of the target steel-tube concrete component include the following steps (11)-(12).

[0034] (11) Pour self-compacting concrete 3 into the top of the steel pipe 1 and vibrate it. After the pouring is completed, outdoor curing is carried out. Generally, it needs to be placed outdoors and watered regularly for 28 days to prepare healthy steel pipe concrete components.

[0035] (12) Acrylic sheet 2 is bonded to the inner surface of steel pipe 1 with epoxy resin. Then, self-compacting concrete 3 is poured from the top of steel pipe 1 and vibrated. After pouring, outdoor curing is carried out. Generally, it needs to be placed outdoors and watered regularly for 28 days to prepare hollow steel pipe concrete components. The bonding position of the acrylic sheet is the hollow defect. Acrylic sheets 2 of different lengths and heights correspond to hollow defects of different hollow lengths and hollow heights. By cutting acrylic sheets of different lengths and heights, six hollow steel pipe concrete components with different hollow lengths and hollow heights can be prepared. For example, the hollow length of the hollow defect is 50mm, 100mm, and 150mm, the width is 25mm, and the hollow height is 5mm, 10mm, 15mm, and 20mm. Figure 3 As shown.

[0036] The dimensions of the steel pipes used in the above preparation process are generally as follows: cross-sectional dimensions of 400×400×50mm³, steel pipe wall thickness of 10mm, filled with C50 self-compacting concrete, and steel strength grade of Q235.

[0037] In the actual fabrication of hollow steel-concrete composite members, defect markings need to be made at the locations where acrylic plates 2 are pasted, and stress wave excitation measurement points need to be prefabricated. Furthermore, healthy and hollow steel-concrete composite members are sequentially labeled according to the different hollow heights and lengths of the pasted acrylic plates 2, and different testing methods are used, as shown in Table 1 below. PC indicates the use of the horizontal measurement method, PC20 indicates the use of the horizontal measurement method with a transmit / receive interval of 20cm, PC30 indicates the use of the horizontal measurement method with a transmit / receive interval of 30cm, and XC indicates the use of the oblique measurement method. By arranging sensors horizontally along the surface of the steel pipe using the horizontal measurement method, the influence of the hollow height on the stress wave signal can be analyzed; by arranging sensors at specific angles using the oblique measurement method, the influence of the hollow length can be studied.

[0038] Table 1

[0039] In another specific application example, such as Figure 4 , Figure 5 and Figure 6 As shown, the steps for inspecting any target steel-concrete composite member include the following steps (1)-(2).

[0040] (1) Use function signal generator 8 as excitation source to excite the first piezoelectric ceramic sensor 4 to emit a detection signal; specifically, the function signal generator 8 is model RIGOL DG1022, which can excite a continuous sine signal with a frequency of 20kHz and an amplitude of 10V.

[0041] (2) The second piezoelectric ceramic sensor 5 is used to receive the time-domain signal and transmit it to the oscilloscope 9 for display and collection. The first piezoelectric ceramic sensor 4 and the second piezoelectric ceramic sensor 5 are both set on the steel pipe 1 of the target steel-concrete composite member according to the measurement method adopted. The first piezoelectric ceramic sensor 4 and the second piezoelectric ceramic sensor 5 are model PXR03RMH, with external magnetic rings, which can be tightly connected to the steel pipe 1. The oscilloscope 9 is model YOKOGAWA DLM2054, with a sampling rate of 1.25GS / s. The oscilloscope 9 is connected to a USB flash drive to collect time-domain signals in CSV format, thereby recording the time-domain signals detected each time, which becomes the data basis for subsequent wavelet packet analysis 10. In other words, the oscilloscope 9 collects time-domain signal files in CSV format and stores them in the USB flash drive, thereby obtaining a time-domain signal set.

[0042] Specifically, such as Figure 4 As shown, when using the horizontal measurement method, the first piezoelectric ceramic sensor 4 and the second piezoelectric ceramic sensor 5 are horizontally positioned along the surface of the steel pipe of the same target steel-concrete composite member according to a preset transmit / receive distance. The preset transmit / receive distance between the two piezoelectric ceramic sensors can be 20cm. Figure 4 The number 6 in the text can be a spacing of 30cm, corresponding to... Figure 4 The number 7 in the example. Figure 5 As shown, when the oblique measurement method is used, the first piezoelectric ceramic sensor 4 and the second piezoelectric ceramic sensor 5 are set on the steel pipe surface of the same target steel pipe concrete component according to a preset angle.

[0043] Step 202: For any of the time-domain signal sets, calculate the normalized judgment index corresponding to each of the target steel-concrete composite components; wherein the calculation process of the normalized judgment index includes the following steps (21)-(23) to perform qualitative analysis on the extraction of the time-domain amplitude signal data of the continuous sine function.

[0044] (21) For any target steel-concrete composite member in the time domain signal set, extract the amplitude of the sinusoidal signal.

[0045] (22) Calculate the first using the following formula. i Normalized judgment index for individual target concrete-filled steel tube components DI : .

[0046] in, D i For the first i The sinusoidal signal amplitude of a target concrete-filled steel tube component. D P The amplitude of the sinusoidal signal for a healthy steel-concrete composite member.

[0047] (23) Using the void height in the void defect as the abscissa and the normalized judgment index of the target steel-concrete composite member as the ordinate, a point-line graph is plotted for display, such as... Figure 7 and Figure 8 As shown in the figure, the plotted dot-line graph reveals the impact of different degrees of vacancy on the normalized judgment index (DI), i.e., the higher the degree of vacancy, the larger the value of the normalized judgment index (DI).

[0048] Step 203: Construct a finite element model for detecting the target steel-concrete composite member, and optimize the finite element model using the time-domain signal set and the normalized judgment index corresponding to the target steel-concrete composite member to obtain the finite element model to be used. In a specific application, step 203 includes the following steps (31)-(34).

[0049] (31) Based on the parameters of various materials such as steel pipe, concrete and two piezoelectric ceramic sensors involved in the indoor void detection test, an initial finite element model was established using ABAQUS software.

[0050] (32) Calculate the mesh size of the established numerical simulation model. The mesh size should not exceed one-tenth of the wavelength. The formula for calculating the mesh size is: ; .

[0051] in, v Indicates wave speed. E ρ represents the elastic modulus of the material, and ρ represents the density of the material. denoted by wavelength, f represents the transmission frequency.

[0052] (33) Adjust the initial finite element model according to the mesh size obtained in the previous step to obtain the final finite element model, such as... Figure 9 As shown.

[0053] (34) Based on the final finite element model obtained in the previous step, numerical simulation analysis is performed to obtain the corresponding simulation time-domain signal and stress cloud diagram, such as Figure 10 As shown, the simulation normalization judgment index is calculated based on the simulation time-domain signal. Then, the finite element model is optimized by combining the time-domain signal set and the normalization judgment index corresponding to the target steel-concrete composite member, resulting in the finite element model to be used.

[0054] Step 204: Based on the finite element model to be used and the time-domain signal set, numerical simulation and wavelet packet analysis are performed to obtain the fitting function formula between the wavelet packet energy value and the void defect. Specifically, numerical simulation is first performed based on the finite element model to be used and the time-domain signal set to obtain simulated time-domain data; then, wavelet packet analysis is performed on the simulated time-domain data to obtain the simulated wavelet packet energy value, and then the simulated wavelet packet energy value is used to construct a simulation function. In practical applications, the indoor experimental energy can also be substituted into the simulation function to calculate the goodness of fit R. 2 This allows us to determine the degree of fit between the regression line and the observed values, thus obtaining the accuracy of the simulation function.

[0055] In one application example, this application uses MATLAB software to perform wavelet packet energy decomposition of a time-domain signal with a layer of 3. The formula for calculating the wavelet packet energy value is as follows: .

[0056] in, E j,k For the first j Level of layer decomposition k Wavelet packet energy values ​​in each sub-band w j,k ( n ) is the first j Level of layer decomposition k Each frequency band at time n The wavelet packet transform coefficients.

[0057] After obtaining the wavelet packet energy value through the above calculations, the wavelet packet energy values ​​obtained from finite element models using different testing methods are fitted to the data, and the fitting function curve is plotted. The fitting function formula between the wavelet packet energy value and the void defect is as follows: y pcM =0.1175-3 10 -4 x l +6.2 10 -3 x h -2 10 -4 x h 2 .

[0058] y pcN =0.1052-6 10 -4 x l +7.9 10 -3 x h -3 10 -4 xh 2 .

[0059] y xc =0.1026-4 10 -4 x l +1.2 10 -3 x h -1 10 -4 x h 2 .

[0060] Where, x l x is the length of the empty space. h y is the height of the freefall; pcM The energy value of the wavelet packet using the planar survey method with a transmit / receive spacing of M; y pcN The energy value of a wavelet packet using the planar measurement method with a transmit / receive spacing of N; y xc The wavelet packet energy value is obtained using the oblique measurement method. Corresponding to the above description, M is taken as 20 cm, and N as 30 cm. Different voiding defects correspond to different voiding lengths and heights. Furthermore, after establishing the quantitative relationship model between the voiding defects and wavelet packet energy values, experimental results demonstrate that the horizontal measurement method is more sensitive to voiding height, with a goodness of fit R... 2 The highest value can reach 0.9432, while the oblique measurement method has higher accuracy for the gap length, and the goodness of fit R is higher. 2 It reached 0.9775. For example... Figures 11-13 As shown, where Figure 11 This is a schematic diagram of the fitted function curve obtained from PC20. Figure 12 This is a schematic diagram of the fitted function curve obtained from PC30. Figure 13 This is a schematic diagram of the fitted function curve obtained for XC.

[0061] Steps 201-204 above are simulation and fitting preparations required before actual detection of voids in concrete-filled steel tubular structures. Based on the linear relationship between void length and void height, quantitative and accurate detection of void defects in concrete-filled steel tubular structures can be achieved.

[0062] Step 205: Extract the actual wavelet packet energy value from the actual time-domain signal corresponding to the actual steel-concrete composite member, and input the actual wavelet packet energy value into the corresponding fitting function formula to obtain the void defect. Furthermore, in practical applications, to achieve comprehensive detection of different types of void defects, both horizontal and oblique measurement methods can be used for the same actual steel-concrete composite structure.

[0063] In summary, this application employs externally mounted piezoelectric ceramic sensors for stress wave propagation analysis. Stress wave signals are excited and received using both horizontal and oblique measurement methods. Combined with indoor experiments, numerical simulations, and wavelet packet analysis, qualitative identification and quantitative assessment of void defects in steel-concrete composite structures are performed. The horizontal measurement method excels in detecting debonding height, while the oblique measurement method more effectively detects debonding length, thus ensuring sensitivity and accuracy when detecting void defects of different lengths and heights. Furthermore, a normalized judgment index (DI) is introduced to quantify the correlation between interface features and the amplitude of the detection signal, revealing the significant impact of sensor spacing on detection accuracy. A linear model based on wavelet packet energy analysis is established, revealing the linear relationship between wavelet packet energy values ​​and void defects, thus providing a foundation for quantitative detection of interface defects and offering a comprehensive and accurate new method for health monitoring of steel-concrete composite structures. Combining these multiple methods improves detection accuracy and enables both qualitative and quantitative defect analysis. Experiments demonstrate that the goodness of fit of the method in this application can reach up to 0.9775.

[0064] The comprehensive testing method proposed in this application can significantly improve the detection accuracy of debonding defects in concrete-tube steel structures, providing scientific guidance for the maintenance and repair of concrete-tube steel structures, thereby effectively ensuring structural safety and extending service life. The testing equipment used in this application is simple and efficient, with low testing costs and high testing efficiency, thus it has broad application prospects in the health monitoring and maintenance of concrete-tube steel structures.

[0065] Based on the same inventive concept, this application also provides an apparatus. The solution provided by this apparatus is similar to the solution described in the above method. Therefore, the specific limitations of one or more apparatus embodiments provided below can be found in the limitations of the method above, and will not be repeated here.

[0066] In one specific example, the device includes a function signal generator, a first piezoelectric ceramic sensor, a second piezoelectric ceramic sensor, an oscilloscope, and a computer device. The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the method described above. The computer device is used to receive the time-domain signal collected by the oscilloscope. The functions and settings of the function signal generator, the first piezoelectric ceramic sensor, the second piezoelectric ceramic sensor, and the oscilloscope are described in step 201 above. This device can be applied to the detection of voids in steel-concrete composite structures.

[0067] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 14As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media to run. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for detecting voids in steel-concrete composite pipes based on wave analysis.

[0068] Those skilled in the art will understand that Figure 14 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0069] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0070] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0071] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0072] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0073] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0074] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0075] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for detecting voids in concrete-filled steel tubing based on wave analysis, characterized in that, The method includes: Multiple time-domain signal sets are acquired; one of the time-domain signal sets is obtained by using a measurement method to detect multiple target steel-concrete composite members; different time-domain signal sets correspond to different measurement methods; different target steel-concrete composite members have different void defects; Different measurement methods include oblique measurement and various horizontal measurement methods; different horizontal measurement methods correspond to different send / receive intervals; the steps for inspecting any target steel-concrete composite member include: A function signal generator is used as the excitation source to excite the first piezoelectric ceramic sensor to emit a detection signal; a second piezoelectric ceramic sensor is used to receive the time-domain signal and transmit it to an oscilloscope for display and collection; both the first and second piezoelectric ceramic sensors are installed on the target steel-concrete composite member according to the measurement method adopted. For any of the time-domain signal sets, calculate the normalized judgment index corresponding to each of the target steel-concrete composite components; A finite element model for detecting the target steel-concrete composite member is constructed, and the finite element model is optimized using the time-domain signal set and the normalized judgment index corresponding to the target steel-concrete composite member to obtain the finite element model to be used. Numerical simulation and wavelet packet analysis are performed based on the finite element model to be used and the time domain signal set to obtain the fitting function formula of wavelet packet energy value and void defect. The actual wavelet packet energy value is extracted from the actual time-domain signal corresponding to the actual steel-concrete composite member, and then the actual wavelet packet energy value is input into the corresponding fitting function formula to obtain the void defect.

2. The method for detecting voids in steel-concrete composite tubular structures based on wave analysis according to claim 1, characterized in that, The plurality of said target steel-tube concrete members include a healthy steel-tube concrete member and at least one vacant steel-tube concrete member; Different types of hollowed-out steel-concrete composite members have different hollowing defects; The preparation steps of the target steel-concrete composite member include: Self-compacting concrete is poured into the top of the steel pipe and vibrated. After pouring, outdoor curing is carried out to prepare healthy steel pipe concrete components. An acrylic sheet is pasted onto the inner surface of a steel pipe, and then self-compacting concrete is poured from the top of the steel pipe and vibrated. After pouring, outdoor curing is carried out to prepare a hollow steel pipe concrete component; the acrylic sheet is pasted at the location of the hollow defect.

3. The method for detecting voids in steel-concrete composite tubing based on wave analysis according to claim 1, characterized in that, The calculation process of the normalized judgment index includes: For any target steel-concrete composite member in the time-domain signal set, extract the amplitude of the sinusoidal signal; The following formula is used to calculate the first... i Normalized judgment index for individual target concrete-filled steel tube components DI : ； in, D i For the first i The sinusoidal signal amplitude of a target concrete-filled steel tube component. D P The amplitude of the sinusoidal signal for a healthy steel-concrete composite member.

4. The method for detecting voids in steel-concrete composite tubular structures based on wave analysis according to claim 1, characterized in that, The formula for calculating the energy value of a wavelet packet is: ； in, E j,k For the first j Level of layer decomposition k Wavelet packet energy values ​​in each sub-band w j,k ( n ) is the first j Level of layer decomposition k Each frequency band at time n The wavelet packet transform coefficients.

5. The method for detecting voids in steel-concrete composite tubing based on wave analysis according to claim 1, characterized in that, The steps for inspecting any target steel-concrete composite member also include: When the horizontal measurement method is selected, the first piezoelectric ceramic sensor and the second piezoelectric ceramic sensor are horizontally set along the surface of the steel pipe of the same target steel pipe concrete component according to the preset transmit and receive distance. When the oblique measurement method is selected, the first piezoelectric ceramic sensor and the second piezoelectric ceramic sensor are set on the steel pipe surface of the same target steel pipe concrete component according to a preset angle. The oscilloscope was connected to a USB flash drive to collect time-domain signals in CSV format.

6. The method for detecting voids in steel-concrete composite tubing based on wave analysis according to claim 1, characterized in that, Different voiding defects correspond to different voiding lengths and voiding heights; when M is 20cm and N is 30cm, the fitting function formula between the wavelet packet energy value and the voiding defect is: y pcM =0.1175-3 10 -4 x l +6.2 10 -3 x h -2 10 -4 x h 2 ; y pcN =0.1052-6 10 -4 x l +7.9 10 -3 x h -3 10 -4 x h 2 ; y xc =0.1026-4 10 -4 x l +1.2 10 -3 x h -1 10 -4 x h 2 ; Where, x l x is the length of the empty space. h y is the height of the freefall; pcM The energy value of the wavelet packet using the planar survey method with a transmit / receive spacing of M; y pcN The energy value of a wavelet packet using the planar measurement method with a transmit / receive spacing of N; y xc This represents the wavelet packet energy value using the oblique measurement method.

7. The method for detecting voids in steel-concrete composite tubular structures based on wave analysis according to claim 3, characterized in that, The calculation process of the normalized judgment index also includes: using the void height in the void defect as the abscissa and the normalized judgment index of the target steel tube concrete component as the ordinate, drawing a point-line graph for display.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method for detecting voids in steel-concrete composite based on wave analysis as described in any one of claims 1-7.

9. A device for detecting void defects in concrete-filled steel pipes based on wave analysis, characterized in that, The device includes a function signal generator, a first piezoelectric ceramic sensor, a second piezoelectric ceramic sensor, an oscilloscope, and the computer equipment as described in claim 8; The computer device is used to receive the time-domain signal collected by the oscilloscope.

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