Concrete filled steel tube interface void detection method based on conjoint analysis of head and tail waves

Abstract

The invention discloses a concrete filled steel tube interface void detection method based on head and tail wave conjoint analysis. A plurality of piezoelectric sensors are uniformly arranged on the inner wall of a steel pipe, modulation pulse or sine wave signals are adopted to cyclically excite the piezoelectric sensors, and response signals of the opposite side and the corresponding adjacent sensors are collected. Under the assumption that both the steel pipe and the concrete are uniform media, the characteristic change of the head wave signal mainly reflects the interface state on the propagation path, and can be used for identifying the interface void of the area where the excitation or receiving sensor is located; as the tail wave signal contains multiple reflection and scattering components, the symmetrical path contrastive analysis is carried out on the tail wave signal, and the medium change of an indirect area between the sensors can be effectively sensed, so that the void condition of a corresponding position is judged. According to the method, quantitative recognition of the head wave on the path defect and high-sensitivity sensing of the tail wave on the change of the adjacent region are combined, so that a completely-covered void detection system is constructed, and the technical problem that global monitoring is difficult to realize by a traditional method is solved.

Description

Technical Field

[0001] This invention belongs to the field of concrete structure health monitoring technology, and specifically relates to a method for detecting voids at the interface of steel-concrete composite structures based on joint analysis of first and last waves. Background Technology

[0002] Concrete-Filled Steel Tube (CFST), as a high-performance composite structure, is widely used in bridges, buildings, high-rise structures, and foundation piles due to its combination of the high strength of steel and the good compressive strength of concrete. Its structural performance largely depends on the good bond and synergistic effect between the steel tube and the internal concrete. However, during construction, curing, or service, the interface between the steel tube and concrete often experiences debonding or voiding due to factors such as formwork separation, concrete shrinkage, insufficient vibration, temperature gradients, or long-term loads—a phenomenon known as "interface debonding." The formation of voids interrupts the stress transfer path between the steel tube and concrete, reducing their synergistic performance. Studies show that when voids exist at the interface, the confinement effect of the concrete weakens, and the axial compressive bearing capacity, ductility, and energy dissipation capacity all decrease significantly, even leading to premature local buckling. Under cyclic loading, the voided areas may also become crack initiation sites, inducing fatigue damage and durability degradation. Furthermore, once a void forms at the interface, its expansion process is often hidden and difficult to detect in time in the response of the external structure. If it is not detected and repaired in time, it will seriously threaten the safety and service life of the structure.

[0003] Currently, the main methods for detecting voids in steel-concrete composite pipes include: Ultrasonic pulse (UPV) method, which determines the location of the void by measuring the arrival time and amplitude difference of the first wave; however, this method mainly reflects changes in the medium along the direct wave path and has weak ability to identify small voids located outside the direct path; Impact elastic wave method, which relies on surface impact to induce wave reflection signals; however, it is greatly affected by the impact energy and the direction of reception, resulting in poor data consistency; Infrared thermography method, which utilizes the difference in thermal conductivity of the air layer to detect the void area; however, it is only applicable to surface defects and is sensitive to ambient temperature; Acoustic emission method and strain monitoring method can be used for long-term health monitoring, but they are difficult to accurately locate early voids. In summary, existing detection technologies often suffer from weak signals, significant interference, and low spatial resolution when dealing with voids embedded inside steel pipes, small in scale, and outside the direct path. A highly sensitive and directional detection method is still lacking.

[0004] In recent years, nondestructive testing methods based on ultrasonic coda wave analysis have gradually attracted attention. A coda wave is a long, continuous signal segment formed by multiple scattering and reflections within a structure, containing rich information about medium inhomogeneity and interface changes. Compared to the initial wave, the coda wave is more sensitive to minute structural changes and can characterize the cumulative multiple reflection effects along the wave's propagation path. Studies in concrete and rock materials have demonstrated that the energy, spectral centroid, and high-frequency energy ratio of the coda wave signal change significantly when microcracks or interface relaxation occur. However, current coda wave detection is mostly applied to damage monitoring within rock masses or single concrete materials, with limited research on interface void detection in steel-concrete composite systems. Due to the high reflectivity and multipath propagation characteristics of the steel pipe wall, the mechanism of the coda wave signal in this system is more complex, and a unified quantitative evaluation method has not yet been established for its directionality, sensitivity, and the comprehensive response of multiple sensing channels. Summary of the Invention To address at least one of the problems existing in current technologies, this invention proposes a method for detecting voids at the interface of steel-concrete composite structures based on joint analysis of the first and last waves. This method utilizes a ring-shaped piezoelectric sensor array deployed on the inner wall of the steel tube, employing alternating excitation and multi-point reception. By combining the waveform differences in the tailwave signal caused by void reflection, it can qualitatively reflect the impact of voids on wave propagation characteristics. Compared to the traditional first-wave method, this method can effectively identify voids along non-direct paths. By analyzing the differences in cross-correlation values ​​of tailwave signals between different channels, it can inversely deduce the direction and location of the void. This method offers advantages such as high detection accuracy, strong resistance to coupling interference, and the ability to achieve early warning and long-term monitoring, providing a new, highly sensitive detection method for the health assessment of steel-concrete composite structures.

[0005] To achieve the objective of this invention, a method for detecting voids at the interface of steel-concrete composite tubes based on joint analysis of first and last waves is provided, comprising the following steps: The piezoelectric sensors circumferentially set on the preset detection section of the steel-concrete composite member are sequentially excited to emit ultrasonic excitation signals in a healthy state, and the health response signals of the corresponding piezoelectric sensors at the receiving end are recorded for each excitation. The ultrasonic excitation signal is repeatedly emitted under the test state, and the corresponding real-time response signal is collected. The health response signal and the real-time response signal are preprocessed separately. The first wave time window is adaptively determined within a preset time range based on the envelope of the health response signal and the real-time response signal; the arrival time and signal amplitude of the first wave are observed within the first wave time window; if the arrival time or amplitude of the first wave reaches the preset value, it is determined that there is interface detachment near the piezoelectric sensor at the corresponding excitation end or the piezoelectric sensor at the receiving end. If the waveform parameters of the first wave signals of the health response signal and the real-time response signal do not change by a preset, a fixed-length sliding window is set in the tail wave time period after the first wave time window, and the sliding cross-correlation sequence of the health response signal and the current real-time response signal is calculated. The global minimum value of the cross-correlation coefficient and its corresponding time are determined from the sliding cross-correlation sequence as the characteristic moment when the corresponding receiving channel is most sensitive to the gap. By comparing the characteristic moments of multiple receiving channels, the receiving channel with the earlier characteristic moment is closer to the gap-off region, thereby realizing the determination of the gap-off position and spatial inversion. Furthermore, at least six to eight piezoelectric sensors are evenly arranged circumferentially on the inner wall of the steel pipe, wherein when any one piezoelectric sensor is used as the excitation end, at least two piezoelectric sensors on its opposite side and adjacent to it are used as the receiving end.

[0006] Furthermore, when stimulating the piezoelectric sensor, a modulated pulse or sine wave signal is used for cyclic excitation.

[0007] Furthermore, the preprocessing includes DC removal, normalization, filtering, and envelope analysis.

[0008] Furthermore, the method for determining the first wave time window is as follows: the envelope is obtained by performing a Hilbert transform on the health signal, and a continuous interval from 20% to 40% of the maximum envelope amplitude is selected within the first wave search time range as the first wave time window.

[0009] Furthermore, the wake window begins after the first wave time window and ends after signal acquisition is completed; Furthermore, the cross-correlation coefficients are normalized.

[0010] Furthermore, the cross-correlation coefficient in the sliding cross-correlation sequence is calculated using the following formula:

[0011] in, For cross-correlation coefficients, For health response signals, To respond to signals in real time, For time, The mean, Standard deviation, The mean of the health response signal. This represents the average of the current health response signals. The standard deviation of the health response signal. The standard deviation of the current health response signal. This is the change in the first wave.

[0012] Furthermore, the minimum cross-correlation value corresponds to the time period in which the propagation paths of multiple reflections and scattering of the wake wave overlap with the void region to the greatest extent.

[0013] Furthermore, by establishing a temporal sequence through the characteristic moments of multiple receiving channels, the propagation path corresponding to the receiving channel with the earliest occurrence of the minimum cross-correlation characteristic moment is closest to the void region, thereby achieving angular or segmental positioning of the void region within the cross-sectional area.

[0014] The present invention also provides a detection system for voids at the interface of steel-concrete composite pipe based on joint analysis of first and last waves.

[0015] The present invention also provides a computer device.

[0016] The present invention also provides a computer-readable storage medium.

[0017] Compared with the prior art, the advantages of the present invention are as follows: 1. High-sensitivity detection: The wake wave contains multiple reflections, making it more sensitive to interface delamination and enabling the detection of early, minute delamination. 2. High scalability: The method is applicable to single-ring, multi-ring, and multi-frequency excitation systems, and can be extended to three-dimensional monitoring; 3. Wide detection range: Compared with the current ultrasonic detection method that only uses the first wave characteristic parameters, the detection method that combines the first and last waves can effectively broaden the detection range under limited piezoelectric sensor tools, thereby improving the detection efficiency. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the detection method provided in an embodiment of the present invention; Figure 2 This is a structural layout plan view in an embodiment of the present invention; Figure 3 This is a perspective view of the structural layout in an embodiment of the present invention; Figure 4 This is a schematic diagram of the target channel during a single excitation in an embodiment of the present invention (where S1 is used for excitation and S4-S6 are used for reception). Figure 5 This is a schematic diagram of the effect of voids in the cross section on the pressure sensor at the receiving end in an embodiment of the present invention (where the solid line segment represents the direct wave between pressure sensors, and the dashed line represents the reflected tail wave generated by the voids). In the diagram: 1. Piezoelectric sensor, 2. Steel pipe, 3. Concrete area, 4. Piezoelectric sensor wire. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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, 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.

[0020] like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves, comprising the following steps: Step 1: When making the steel pipe 2, multiple thin-shell piezoelectric sensors 1 are evenly pasted on the inner wall of the steel pipe 2. When any one of the piezoelectric sensors 1 is used as the excitation end, at least two piezoelectric sensors 1 on its circumferential opposite side and adjacent to the opposite side are used as the receiving end.

[0021] In one embodiment, such as Figure 2 and Figure 3 As shown, for a certain cross-section of a steel-concrete composite member, multiple piezoelectric sensors 1 are uniformly arranged circumferentially on the inner wall of the steel tube 2 at that cross-section, forming a ring-shaped detection cross-section. Each piezoelectric sensor 1 can serve as an excitation end. When a piezoelectric sensor 1 serves as an excitation end, at least two piezoelectric sensors 1 on its opposite circumferential side and adjacent to it serve as receiving ends. Depending on the needs, one or more detection sides or detection cross-sections can be set on the steel-concrete composite member to form a single-ring, multi-ring, or multi-frequency excitation system.

[0022] In one embodiment, such as Figure 2 and Figure 3 As shown, at least six to eight piezoelectric sensors 1 are arranged circumferentially on the inner wall of the steel pipe 2 at the detection section. The six to eight piezoelectric sensors 1 are arranged according to... ~ Arranged at intervals.

[0023] Step 2: After the concrete in the steel pipe concrete has solidified, the piezoelectric sensors 1 arranged in sequence are excited. The pressure sensor 1 at the excitation end emits an ultrasonic excitation signal in a healthy state, and the health response signal of the pressure sensor 1 at each receiving end is recorded.

[0024] Step 3: Repeatedly transmit ultrasonic excitation signals in the test state, that is, sequentially excite each piezoelectric sensor 1 and collect the corresponding real-time response signals.

[0025] Step 4: Preprocess the health response signal and the real-time response signal respectively, including DC removal, normalization, filtering and envelope analysis.

[0026] Step 5: Based on the envelope of the health response signal and the real-time response signal, adaptively determine the first wave time window within a preset time range; observe the arrival time of the first wave and the signal amplitude within the first wave time window. If the arrival time of the first wave in the real-time response signal shows a significant lag or the signal amplitude shows a significant decrease, it is determined that there is an interface gap near the piezoelectric sensor 1 at the excitation end or the piezoelectric sensor 1 at the receiving end.

[0027] In one embodiment, the first wave time window is determined by performing a Hilbert transform on the health response signal and the real-time response signal to obtain the envelope, and selecting a continuous interval within the first wave search time range where the envelope amplitude reaches 20% to 40% of the maximum envelope amplitude as the first wave time window.

[0028] In one embodiment, the significant lag and significant decrease are defined as exceeding a 95% confidence interval of the healthy value, which can be considered a difference from a healthy state, i.e., a gap has occurred on the path. The values ​​of the significant lag and significant decrease are determined based on the experimental materials or treatment methods.

[0029] Step 6: If the waveform parameters of the first wave signal (the model within the first wave time window is the first wave signal) of the health response signal and the real-time response signal do not change significantly, then set a fixed-length sliding window in the tail wave time period after the first wave time window, and calculate the sliding cross-correlation sequence of the health response signal and the real-time response signal.

[0030] In one embodiment, the wake window in step 6 (the wake window refers to the selected fixed-length sliding window in the entire wake band after the first wave reception) starts from the time window after the first wave and ends when the signal acquisition is completed.

[0031] Whether a significant change has occurred is determined based on the materials or treatment methods used in the experiment. In one embodiment, a 95% confidence interval exceeding the health value is defined as a difference from a healthy state, which can be considered a gap in the path.

[0032] In step 6, the cross-correlation coefficients are normalized cross-correlation. The cross-correlation coefficient in a sliding cross-correlation sequence can be calculated using the following formula:

[0033] in, For cross-correlation coefficients, For health response signals, To respond to signals in real time, For time, The mean, To determine the standard deviation, the minimum value of the absolute cross-correlation is chosen as the target value in this example. The mean of the health response signal. This represents the average of the current health response signals. The standard deviation of the health response signal. The standard deviation of the current health response signal. This refers to the change in the first wave. If the first wave is delayed or advanced due to the influence of signal decoupling, then it is necessary to... To align the two waveforms first, then perform cross-correlation. If the arrival time of the first wave remains unchanged under the influence of the gap, then... =0.

[0034] A sliding cross-correlation sequence refers to using a fixed-length sliding window to perform segmented cross-correlation comparisons between the entire tailband and the healthy state. In one embodiment, assuming a fixed-length sliding window of length 2 is used within the range of 1 to 10, five window segments can be obtained, resulting in five cross-correlation values. These five cross-correlation values ​​are then arranged in a sliding cross-correlation sequence, with cross-correlation coefficients C1, C2, ... and the cross-correlation sequence is... Then, the minimum value is extracted from the cross-correlation sequence and used as the target cross-correlation value.

[0035] Step 7: Determine the global minimum value of the cross-correlation coefficient and its corresponding time from the sliding cross-correlation sequence as the characteristic moment when the receiving channel is most sensitive to the slippage.

[0036] One exciter to one receiver constitutes a receiving channel.

[0037] In one embodiment, the global minimum of the cross-correlation coefficient corresponds to the time period in which the propagation path of multiple wake reflections and scatterings overlaps most with the void region. That is, if a minimum cross-correlation coefficient appears, it indicates that the void region has the greatest impact on that time point along that path. By observing the order in which the minimum values ​​appear for each receiving channel, it is possible to determine which receiving channel is affected first and which is affected later, thereby determining the distance between the receiving end and the void region.

[0038] Step 8: Compare the characteristic moments of multiple receiving channels. The receiving channel with the earlier characteristic moment is closer to the de-empty area. Based on this, the de-empty position can be determined and spatially inverted. In one embodiment, step 8 establishes a temporal sequence through the characteristic moments of multiple receiving channels. The propagation path corresponding to the receiving channel with the earliest occurrence of the minimum cross-correlation characteristic moment is closest to the void region, thereby achieving angular (referring to the void direction) or segment (location of the void region) positioning of the void region within the cross-sectional area.

[0039] In one embodiment, a steel-concrete composite interface void detection system based on first and last wave joint analysis is provided to implement the method described in the foregoing embodiments. The system includes the following modules: The health response signal acquisition module is used to sequentially excite the piezoelectric sensors circumferentially set on the preset detection section of the steel tube concrete component to emit ultrasonic excitation signals in a healthy state, and record the health response signal of the corresponding piezoelectric sensor at the receiving end under each excitation. The real-time response signal acquisition module is used to repeatedly transmit ultrasonic excitation signals in the test state and acquire the corresponding real-time response signals. The preprocessing module is used to preprocess the health response signal and the real-time response signal respectively; The interface de-energization judgment module is used to adaptively determine the first wave time window within a preset time range based on the envelope of the health response signal and the real-time response signal; and observe the arrival time and signal amplitude of the first wave within the first wave time window. If the arrival time or amplitude of the first wave reaches the preset value, it is determined that there is interface de-energization near the piezoelectric sensor of the corresponding excitation end or the piezoelectric sensor of the receiving end. The cross-correlation calculation module is used to calculate the sliding cross-correlation sequence between the health response signal and the current real-time response signal by setting a fixed-length sliding window in the tail wave time period after the first wave time window if the waveform parameters of the first wave signals of the health response signal and the real-time response signal have not changed by a preset. The feature time determination module is used to determine the global minimum value of the cross-correlation coefficient and its corresponding time from the sliding cross-correlation sequence as the feature time when the corresponding receiving channel is most sensitive to the gap. The de-empty direction and region positioning module is used to compare the characteristic moments of multiple receiving channels. The receiving channel with the earlier characteristic moment is closer to the de-empty region, thereby realizing the determination of the de-empty position and spatial inversion. In one embodiment, a computer device is provided, including 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 detection method described in the foregoing embodiments.

[0040] In one embodiment, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements the detection method described in the foregoing embodiments.

[0041] The system, computer device, and computer-readable storage medium described above can achieve the same technical effects as the methods provided in the foregoing embodiments.

[0042] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves, characterized in that, Includes the following steps: The piezoelectric sensors circumferentially set on the preset detection section of the steel-concrete composite member are sequentially excited to emit ultrasonic excitation signals in a healthy state, and the health response signals of the corresponding piezoelectric sensors at the receiving end are recorded for each excitation. The ultrasonic excitation signal is repeatedly emitted under the test state, and the corresponding real-time response signal is collected. The health response signal and the real-time response signal are preprocessed separately. The first wave time window is adaptively determined within a preset time range based on the envelope of the health response signal and the real-time response signal; within the first wave time window, the presence of interface delamination is determined based on the arrival time of the first wave and the signal amplitude. If the waveform parameters of the first wave signals of the health response signal and the real-time response signal do not change by a preset, a fixed-length sliding window is set in the tail wave time period after the first wave time window, and the sliding cross-correlation sequence of the health response signal and the current real-time response signal is calculated. The characteristic moment when the receiving channel is most sensitive to missing data is determined based on the cross-correlation coefficient in the sliding cross-correlation sequence. By comparing the characteristic moments of multiple receiving channels, the receiving channel with the earlier characteristic moment is closer to the gap-off region, thereby realizing the determination of the gap-off position and spatial inversion.

2. The method for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves according to claim 1, characterized in that, Multiple piezoelectric sensors are uniformly arranged circumferentially on the inner wall of the steel pipe. When any one piezoelectric sensor is used as the excitation end, at least two piezoelectric sensors on its opposite side and adjacent to it are used as the receiving end.

3. The method for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves according to claim 1, characterized in that, The method for determining the first wave time window is as follows: the envelope is obtained by performing a Hilbert transform on the health response signal, and a continuous interval within the first wave search time range in which the envelope amplitude reaches the preset range of the maximum envelope amplitude is selected as the first wave time window.

4. The method for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves according to claim 1, characterized in that, Within the first wave time window, observe the arrival time and signal amplitude of the first wave. If the arrival time or amplitude of the first wave reaches the preset value, it is determined that there is interface detachment near the piezoelectric sensor at the corresponding excitation end or the piezoelectric sensor at the receiving end.

5. The method for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves according to claim 1, characterized in that, The cross-correlation coefficient in a sliding cross-correlation sequence is calculated using the following formula: in, For cross-correlation coefficients, For health response signals, To respond to signals in real time, For time, The mean, Standard deviation, The mean of the health response signal. This represents the average of the current health response signals. The standard deviation of the health response signal. The standard deviation of the current health response signal. This is the change in the first wave.

6. The method for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves according to claim 1, characterized in that, The global minimum value of the cross-correlation coefficient and its corresponding time are determined from the sliding cross-correlation sequence as the characteristic moment when the corresponding receiving channel is most sensitive to the gap.

7. A method for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves, as described in any one of claims 1-6, characterized in that, When comparing the characteristic moments of multiple receiving channels, a temporal sequence is established using the characteristic moments of multiple receiving channels. The propagation path corresponding to the receiving channel with the earliest occurrence of the minimum cross-correlation characteristic moment is closest to the void region, thereby achieving angular or segmental positioning of the void region within the cross-sectional area.

8. A system for detecting voids at the interface of steel-concrete composite pipes based on joint analysis of first and last waves, characterized in that, For implementing the method of any one of claims 1-7, the system comprises the following modules: The health response signal acquisition module is used to sequentially excite the piezoelectric sensors circumferentially set on the preset detection section of the steel tube concrete component to emit ultrasonic excitation signals in a healthy state, and record the health response signal of the corresponding piezoelectric sensor at the receiving end under each excitation. The real-time response signal acquisition module is used to repeatedly transmit ultrasonic excitation signals in the test state and acquire the corresponding real-time response signals. The preprocessing module is used to preprocess the health response signal and the real-time response signal respectively; The interface de-energization judgment module is used to adaptively determine the first wave time window within a preset time range based on the envelope of the health response signal and the real-time response signal; and observe the arrival time and signal amplitude of the first wave within the first wave time window. If the arrival time or amplitude of the first wave reaches the preset value, it is determined that there is interface de-energization near the piezoelectric sensor of the corresponding excitation end or the piezoelectric sensor of the receiving end. The cross-correlation calculation module is used to calculate the sliding cross-correlation sequence between the health response signal and the current real-time response signal by setting a fixed-length sliding window in the tail wave time period after the first wave time window if the waveform parameters of the first wave signals of the health response signal and the real-time response signal have not changed by a preset. The feature time determination module is used to determine the global minimum value of the cross-correlation coefficient and its corresponding time from the sliding cross-correlation sequence as the feature time when the corresponding receiving channel is most sensitive to the gap. The de-empty direction and region positioning module is used to compare the characteristic moments of multiple receiving channels. The receiving channel with the earlier characteristic moment is closer to the de-empty region, thereby realizing the determination of the de-empty position and spatial inversion.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the detection method according to any one of claims 1-6.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the detection method according to any one of claims 1-6.

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