Density data processing method of steel tube concrete based on wavelet analysis technology

Abstract

The present invention discloses a steel tube concrete density data processing method based on wavelet analysis technology. The method collects ultrasonic signal data of on-site steel tube concrete density detection; applies wavelet analysis technology to perform wavelet transform on the collected ultrasonic signal data; selects the wavelet coefficient layer to be processed, initializes the cycle counters i and j of wavelet decomposition, and threshold T; respectively judges the cycle counters i and j, and threshold T, and performs inverse wavelet transform until the cycle counter i≥the length of the wavelet coefficient, obtains the denoised ultrasonic signal data and outputs it. The method applies wavelet analysis technology to smoothly reduce the noise of the collected signal, covers a wide frequency range, so that defects of various sizes and types can be detected, the detection accuracy is improved, and the quantitative analysis of the density defects of steel-concrete composite structures is realized.

Description

Technical Field

[0001] The invention relates to the technical field of nondestructive testing of composite structures, and in particular to a density data processing method of steel tube concrete based on wavelet analysis technology. Background Art

[0002] Traditional reinforced concrete structures have problems such as large consumption of building resources and energy, relatively serious environmental pollution during construction, and insufficient earthquake resistance. Pure steel structures have shortcomings such as no second line of defense and low damping. Therefore, most super high-rise buildings currently generally adopt the "steel-concrete composite structure system". The second line of defense is relative to the frame-shear structure. When designing the earthquake resistance of the frame-shear structure, the first line of defense is the shear wall and the second line of defense is the frame.

[0003] During the concrete pouring process of steel tube concrete composite structure, due to the presence of stiffening ribs and steel bars inside the steel tube, the internal space of the structure is narrow. In addition, factors such as uneven vibration and radial shrinkage of concrete can easily lead to defects such as voids and debonding between the steel tube and concrete interface, thereby weakening the bearing capacity and other mechanical properties of the composite structure, causing safety hazards. Therefore, it is of great significance to conduct active health non-destructive testing to evaluate the safety of its main structure.

[0004] The density of steel tube concrete is mostly measured by percussion method, ultrasonic first wave sound time method, impact echo method, etc. The percussion method is based on the loudness, pitch and timbre of the sound. The ultrasonic first wave sound time method uses a non-metallic ultrasonic detector to measure the first wave sound time value of the component, which is input into the tomography (CT) software to obtain the sound velocity distribution map of the component, and then obtain the density status information of the component through the sound velocity distribution map. The impact echo method uses the collected acceleration signal to perform WVD and spectrum transformation to obtain the WVD time domain distribution comparison of components with different densities.

[0005] The tapping method relies on the experience of engineers and has low accuracy. The first wave of the ultrasonic first wave acoustic time method is difficult to measure accurately. For hollow components, the first wave will be diffracted along the steel pipe wall. It can only qualitatively determine the location of internal defects, but it is difficult to quantitatively determine the depth and size of the defects. The impact echo method detection results are greatly affected by the shape and size of the component. It is only suitable for large-volume and long-distance components, and it is difficult to quantitatively analyze defects.

[0006] When using steel tube concrete composite structures to test the density of steel tube concrete composite structures, there are two main interferences in the collected signals. On the one hand, there are noise signals brought by the detection environment, which is difficult to avoid in the on-site detection environment. It is necessary to analyze and minimize the impact of noise signals on the detection results. On the other hand, when exciting sound waves, the waveforms generated in the object being tested are not unique. In addition to surface waves, other forms of waves will also be generated. These waves may be body waves, scattered waves, multiple reflection waves, or other forms of waves. Different methods and equipment for exciting sound waves will also produce different additional waves. Therefore, the signal processing collected by steel tube concrete composite structure detection is particularly important. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide a steel tube concrete density data processing method based on wavelet analysis technology. The method uses wavelet analysis technology to smoothly reduce the noise of the collected signals, covering a wide frequency range, so that defects of various sizes and types can be detected, the detection accuracy can be improved, and the quantitative analysis of the density defects of steel-concrete composite structures can be realized.

[0008] In order to solve the above technical problems, the density data processing method of steel tube concrete based on wavelet analysis technology of the present invention comprises the following steps:

[0009] Step 1: Collect ultrasonic signal data for density detection of on-site steel tube concrete;

[0010] Step 2: Apply wavelet analysis technology to perform wavelet transform on the collected ultrasonic signal data;

[0011] Step 3: Select the wavelet coefficient layer to be processed, initialize the loop counters i and j of wavelet decomposition, and the threshold T;

[0012] Step 4: If the loop counter i ≥ the length of the wavelet coefficient, perform inverse wavelet transform to obtain the denoised ultrasonic signal data and output it;

[0013] Step 5: If the loop counter i is less than the length of the wavelet coefficient, determine whether the loop counter j is greater than or equal to the width of the wavelet coefficient layer. If so, add 1 to the loop counter i and set the loop counter j to 0, and repeat step 4.

[0014] Step 6: If not, determine whether the absolute value of the wavelet coefficient is less than T. If so, set the wavelet coefficient to 0. If not, retain the wavelet coefficient. Then, after the loop counter j is increased by 1, re-determine whether the loop counter j is ≥ the width of the wavelet coefficient layer.

[0015] Furthermore, in the step 1, the ultrasonic signal for on-site steel tube concrete density detection is a sinusoidal signal or a swept frequency signal.

[0016] Since the steel tube concrete density data processing method based on wavelet analysis technology of the present invention adopts the above-mentioned technical scheme, that is, the method collects ultrasonic signal data of on-site steel tube concrete density detection; uses wavelet analysis technology to perform wavelet transform on the collected ultrasonic signal data; selects the wavelet coefficient layer to be processed, initializes the loop counters i and j of wavelet decomposition, and threshold T; respectively judges the loop counters i and j, and threshold T, until the loop counter i ≥ the length of the wavelet coefficient, then performs inverse wavelet transform, obtains the denoised ultrasonic signal data and outputs it. The method uses wavelet analysis technology to smoothly reduce the noise of the collected signal, covering a wide frequency range, so that defects of various sizes and types can be detected, the detection accuracy is improved, and the quantitative analysis of the density defects of the steel-concrete composite structure is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments:

[0018] Figure 1 It is a flowchart of the density data processing method of steel tube concrete based on wavelet analysis technology of the present invention;

[0019] Figure 2 It is a schematic diagram comparing the original ultrasonic signal data and the ultrasonic signal data after denoising by the method;

[0020] Figure 3 It is the time-frequency diagram of noisy ultrasonic signal analyzed by wavelet analysis;

[0021] Figure 4 This is the effect diagram of the time domain analysis of the sinusoidal signal based on the amplitude and the first wave sound. DETAILED DESCRIPTION

[0022] Implementation example Figure 1 As shown, the steel tube concrete density data processing method based on wavelet analysis technology of the present invention includes the following steps:

[0023] Step 1: Collect ultrasonic signal data for density detection of on-site steel tube concrete;

[0024] Step 2: Apply wavelet analysis technology to perform wavelet transform on the collected ultrasonic signal data;

[0025] Step 3: Select the wavelet coefficient layer to be processed, initialize the loop counters i and j of wavelet decomposition, and the threshold T;

[0026] Step 4: If the loop counter i ≥ the length of the wavelet coefficient, perform inverse wavelet transform to obtain the denoised ultrasonic signal data and output it;

[0027] Step 5: If the loop counter i is less than the length of the wavelet coefficient, determine whether the loop counter j is greater than or equal to the width of the wavelet coefficient layer. If so, add 1 to the loop counter i and set the loop counter j to 0, and repeat step 4.

[0028] Step 6: If not, determine whether the absolute value of the wavelet coefficient is less than T. If so, set the wavelet coefficient to 0. If not, retain the wavelet coefficient. Then, after the loop counter j is increased by 1, re-determine whether the loop counter j is ≥ the width of the wavelet coefficient layer.

[0029] Preferably, in step 1, the ultrasonic signal for on-site steel tube concrete density detection is a sinusoidal signal or a swept frequency signal.

[0030] like Figure 2 As shown in the figure, the sine signal is a typical simple periodic signal. The advantage of using the sine signal as an active monitoring signal is that its wave form is simple and easy to compile and analyze later. Time domain analysis is the most intuitive analysis method in defect signal analysis. The compactness of the component can be directly judged by the amplitude of the received signal. Figure 2 This is the effect diagram of the time domain analysis of a sinusoidal signal based on amplitude.

[0031] Depend on Figure 3 and Figure 4 It can be seen that the swept frequency signal can cover a wide frequency range, so that defects of various sizes and types can be detected with high accuracy and a wide range of applications. Figure 3 It shows that the frequency of the signal being analyzed is 100 Hz, the duration is 0.1 s, and the energy is between 2.5-3; Figure 4 BX1-BX4 correspond to different degrees of defects, BX4 represents the maximum degree of defect, and BX1 represents the defect-free state. The signal can be decomposed into a set of wavelet packet basis functions through wavelet packet decomposition, and the energy of each wavelet packet basis function is calculated to describe the local characteristics of the signal. By analyzing the wavelet packet energy of the decomposed sweep signal, the defect quantitative analysis of the steel-concrete composite structure is realized.

[0032] This method uses wavelet analysis to decompose the signal into wavelet sub-bands of different frequencies, so as to better understand and analyze the characteristics of the signal. Unlike traditional Fourier transform, wavelet analysis can not only provide frequency domain information, but also time domain and space domain information. The noise signal and the energy of the additional wave are filtered out through wavelet filtering, leaving the required sound wave signal, thereby improving the quality of the signal and laying the foundation for subsequent data analysis. That is, this method uses wavelet analysis technology to filter the ultrasonic signal data, and then analyzes the processed signal to obtain the density of the component.

Claims

1. A method for processing density data of steel tube concrete based on wavelet analysis technology, characterized in that This method comprises the following steps: Step 1: Collect ultrasonic signal data for density detection of on-site steel tube concrete; Step 2: Apply wavelet analysis technology to perform wavelet transform on the collected ultrasonic signal data; Step 3: Select the wavelet coefficient layer to be processed, initialize the loop counters i and j of wavelet decomposition, and the threshold T; Step 4: If the loop counter i ≥ the length of the wavelet coefficient, perform inverse wavelet transform to obtain the denoised ultrasonic signal data and output it; Step 5: If the loop counter i is less than the length of the wavelet coefficient, determine whether the loop counter j is greater than or equal to the width of the wavelet coefficient layer. If so, add 1 to the loop counter i and set the loop counter j to 0, and repeat step 4. Step 6: If not, determine whether the absolute value of the wavelet coefficient is less than T. If so, set the wavelet coefficient to 0. If not, retain the wavelet coefficient. Then, after the loop counter j is increased by 1, re-determine whether the loop counter j is ≥ the width of the wavelet coefficient layer.

2. The method for processing density data of steel tube concrete based on wavelet analysis technology according to claim 1 is characterized in that: In the step 1, the ultrasonic signal for on-site steel tube concrete density detection is a sinusoidal signal or a swept frequency signal.

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