Method for detecting integrity of pile body of concrete micropile based on ultrasonic technology
By constructing a reflection extremum chain and matching optimization degree, the problem of low accuracy in identifying defects in concrete micropiles during ultrasonic testing was solved, enabling accurate location of defects and improving the reliability of testing.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA ANENG GRP FIRST ENG BUREAU CO LTD
- Filing Date
- 2025-12-04
- Publication Date
- 2026-04-28
AI Technical Summary
Existing ultrasonic testing methods for concrete micropiles suffer from reduced accuracy in defect identification due to multipath propagation and local reflection, making it difficult to accurately identify the first wave and thus affecting the accuracy of defect identification.
By constructing a reflection extremum chain, based on the smoothness, continuity, and matching optimization of the reflection extremum points, suspected first-wave extremum points are identified, and the waveform maxima that best match the characteristics of the first wave are selected, thereby improving the accuracy of first-wave identification.
It improves the accuracy of defect identification in concrete micropiles, ensures accurate location of defects, and reduces engineering risks.
Smart Images
Figure CN121933633A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of defect detection technology, and specifically to a method for detecting the integrity of concrete micropiles based on ultrasonic technology. Background Technology
[0002] Concrete micropiles are a type of small-diameter load-bearing pile that relies on high-strength grouting materials and steel bars or steel strands to work together. They are suitable for environments with large site restrictions, adjacent buildings, or foundation reinforcement and repair. Due to the small diameter, large number of piles, and limited construction space, any local voids, segregation, necking, broken piles, or steel bar misalignment will significantly weaken the load-bearing capacity of the pile. Therefore, in order to detect quality defects in a timely manner after construction and ensure that the single pile bearing capacity meets the standards, it is necessary to conduct pile integrity testing on concrete micropiles to effectively reduce engineering risks.
[0003] Currently, the main method used for detecting the integrity of concrete micropiles is the ultrasonic transmission method. The propagation speed and energy of ultrasonic waves within the pile are extremely sensitive to material uniformity and defects. By arranging transmitting and receiving probes in pre-embedded sleeves, waveform, signal arrival time, and attenuation information can be obtained to evaluate the internal quality of the micropiles. In the ultrasonic testing of concrete micropiles, the sound waves encounter non-uniform media such as aggregates, reinforcing bars, and duct interfaces within the pile, resulting in multipath propagation and local reflections. These interference components often arrive at the receiving end almost simultaneously with the true first wave of the bulk wave, blurring the originally clear first arrival time boundary. This weakens and disperses the main wave energy, resulting in multiple wavelets with similar energy appearing in the received waveform, making it difficult to accurately distinguish the true first wave and thus reducing the accuracy of defect identification. Summary of the Invention
[0004] To address the technical problem in related technologies where sound waves encounter inhomogeneous media such as aggregates, reinforcing bars, and guide pipe interfaces within the pile body, resulting in multipath propagation and local reflection, thus reducing the accuracy of defect identification, this invention provides a method for detecting the integrity of concrete micropiles based on ultrasonic technology.
[0005] The specific technical solution adopted is as follows: Obtain raw waveform data at multiple depths in a concrete micropile; Based on the smooth continuity of reflection extrema points at different depths in the original waveform data, a reflection extrema chain is constructed, where the reflection extrema points are the waveform maxima in the original waveform data. Based on the degree of matching optimization and the abruptness of matching of different reflection extreme points on the reflection extreme point chain, the suspected first wave extreme points among the reflection extreme points at different depths are identified. Based on the matching and optimization degree of suspected first-wave extreme points at different depths, the probability of defect existence at different depths is calculated; When the probability of the defect exists meets the preset conditions, the depth and location of the defect in the concrete micropile are determined.
[0006] In one possible implementation of this application, a reflection extremum chain is constructed based on the smooth continuity of reflection extremum points at different depths in the original waveform data, including: For any depth in the original waveform data, the reflection extreme points at the current depth are continuously matched with the reflection extreme points at the next depth to obtain multiple matching reflection extreme points. The depths in the original waveform data are arranged sequentially from bottom to top of the pile. By connecting the reflection extrema points in series with each matching reflection extrema point, a reflection extrema chain corresponding to each reflection extrema point is obtained. Any reflection extrema point exists in at least one reflection extrema chain.
[0007] In one possible implementation of this application, after concatenating the reflection extrema points with each matching reflection extrema point to obtain the reflection extrema chain corresponding to each reflection extrema point, the method further includes: If any reflection extremum point at the current depth does not exist in the reflection extremum chain, then the current reflection extremum point is taken as the starting point; The starting point is continuously matched with the reflection extremum point at the next depth, and the reflection extremum chain corresponding to the current starting point is reconstructed.
[0008] In one possible implementation of this application, the reflection extrema at the current depth are continuously matched with the reflection extrema at the next depth to obtain multiple matched reflection extrema, including: Determine the signal time difference and amplitude difference between each reflection extremum point at the current depth and the reflection extremum point at the next depth; Based on the signal time difference and amplitude difference, the normal continuity matching degree between each reflection extremum point at the current depth and the reflection extremum point at the next depth is calculated. The signal time difference and amplitude difference are negatively correlated with the normal continuity matching degree. For any reflection extremum point, the reflection extremum point with the highest normal continuous matching degree in the next depth corresponding to the current reflection extremum point is taken as the matching reflection extremum point of the current reflection extremum point.
[0009] In one possible implementation of this application, based on the degree of matching preference and the abrupt change in matching of different reflection extrema points on the reflection extrema chain, the suspected first-wave extrema points among reflection extrema points at different depths are determined, including: For any reflection extremum point in any reflection extremum chain, based on the normal continuity matching degree of each first reflection extremum point before the current reflection extremum point, and the depth difference between the current reflection extremum point and each first reflection extremum point, the previous matching level value of the current reflection extremum point is calculated. The previous matching level value is used to characterize the degree of matching continuity between each first reflection extremum point at the depth before the current reflection extremum point. Based on the normal continuous matching degree and the previous matching level value, the degree of matching mutation at each reflection extreme point is calculated; Based on the degree of matching mutation and the degree of normal continuous matching, the degree of matching optimization of each reflection extreme point is calculated; For any depth, the reflection extreme point corresponding to the maximum matching preference at the current depth is taken as the suspected first wave extreme point.
[0010] In one possible implementation of this application, the degree of optimal matching for each reflection extremum point is calculated based on the degree of matching mutation and the degree of normal continuous matching, including: The reliability of the current reflection extreme point is calculated based on the degree of matching abrupt change of each first reflection extreme point before any reflection extreme point in the current reflection extreme point chain. Based on the degree of confidence and the degree of normal continuous matching, the degree of matching optimization of each reflection extreme point is calculated.
[0011] In one possible implementation of this application, the reliability of the current reflection extremum is calculated based on the degree of matching abrupt change of each first reflection extremum before any reflection extremum in the current reflection extremum chain, including: Determine the first maximum value among the matching mutation degrees of each first reflection extremum point before any reflection extremum point in the current reflection extremum chain; The reliability of the current reflection extreme point is calculated based on the difference between the preset value and the first maximum value.
[0012] In one possible implementation of this application, the matching preference degree of each reflection extremum point is calculated based on the degree of confidence and the degree of normal continuous matching, including: For any reflection extremum chain existing at the current reflection extremum point, calculate the first average of the product between the confidence level of each reflection extremum point in the current reflection extremum chain and the normal continuous matching degree; The maximum value among the first average values corresponding to each reflection extremum chain where different reflection extremum points exist is taken as the matching preference degree of each reflection extremum point.
[0013] In one possible implementation of this application, the probability of defect existence at different depths is calculated based on the matching preference of suspected first-wave extreme points at different depths, including: For any depth, determine the normal continuity matching degree and matching optimization degree of the suspected first wave extreme point in the current depth; Based on the product of the inverse proportional value of the matching preference degree and the normal continuous matching degree, the probability of defect existence at different depths is calculated. The probability of defect existence is negatively correlated with the normal continuous matching degree and the matching preference degree.
[0014] In one possible implementation of this application, determining the depth location of a defect in a concrete micropile when the probability of defect presence meets a preset condition includes: Compare the probability of defect existence with a preset probability threshold; If the probability of a defect exists is greater than a preset probability threshold, then a defect is determined to exist at the depth corresponding to the probability of a defect in the concrete micropile; otherwise, no defect exists.
[0015] The present invention has, but is not limited to, the following technical effects: By acquiring raw waveform data at multiple depths in concrete micropiles, a reflection extremum chain is constructed based on the smoothness and continuity of reflection extremum points at different depths in the raw waveform data. Then, based on the matching optimization degree and matching mutation of different reflection extremum points on the reflection extremum chain, suspected first wave extremum points among the reflection extremum points at different depths are determined. The waveform maxima that best match the characteristics of the first wave at different depths are screened out, making the main wave energy affected by other inhomogeneous media clearly visible, thus improving the accuracy of the extracted first wave at different depths. Furthermore, based on the matching optimization degree of the suspected first wave extremum points, the probability of defect existence at different depths is determined. When the probability of defect existence meets the preset conditions, the depth location of the defect in the concrete micropiles is determined, thus improving the accuracy of defect identification. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating the first embodiment of the method for detecting the integrity of concrete micropiles based on ultrasonic technology according to this application. Figure 2 This is a schematic diagram of the overall implementation process of the ultrasonic technology-based concrete micropile integrity detection method of this application. Figure 3 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application. Detailed Implementation
[0017] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.
[0018] This application provides a method for detecting the integrity of concrete micropiles based on ultrasonic technology. In the first embodiment of this method, refer to... Figure 1 The methods include: Step S10: Obtain raw waveform data at multiple depths in the concrete micropile.
[0019] As an example, the method for detecting the integrity of concrete micropiles based on ultrasonic technology can be applied to a device for detecting the integrity of concrete micropiles based on ultrasonic technology. This device belongs to a system for detecting the integrity of concrete micropiles based on ultrasonic technology, which in turn belongs to a device for detecting the integrity of concrete micropiles based on ultrasonic technology.
[0020] As an example, the original waveform data can be the ultrasonic data obtained after ultrasonic testing of the concrete micropile. Before ultrasonic testing of the pile, four parallel sonic logging tubes are arranged in the pile body at equal intervals along the circumference of the pile. The sonic logging tubes are fixed on the reinforcing cage at the designed positions. The sonic logging tubes are sealed to prevent mud from entering the tubes. The end of the sonic logging tube should be connected to the bottom of the pile so that the probe can be inserted from the top to the bottom and pulled back before the concrete micropile is constructed.
[0021] When performing integrity testing on concrete micropiles, prepare a CSL main unit, transceiver probes, and a synchronous lifting mechanism, with the probe frequency being 50kHz; it is also necessary to check whether the acoustic logging tube is unobstructed.
[0022] When performing ultrasonic testing on concrete micropiles, the end cap is opened and the sonic logging tube is filled with water. The transmitting probe and receiving probe are placed into two adjacent or diagonally opposite sonic logging tubes, respectively. The probes are lowered to the bottom of the pile simultaneously, and the signal is recorded at a constant rising rate. The specific content of the recorded signal is the original waveform of each depth of each group of sonic logging tubes (any two sonic logging tubes constitute a group). The horizontal axis of the original waveform is time (in µs), and the vertical axis is voltage amplitude (in mV). The voltage amplitude represents the vibration intensity received by the receiving probe.
[0023] Step S20: Based on the smooth continuity of reflection extremum points at different depths in the original waveform data, construct a reflection extremum chain, where the reflection extremum points are the waveform maxima in the original waveform data.
[0024] As an example, in the acquired raw waveform data, the first wave is the initial energy of the ultrasound propagating through the pile body and reaching the receiving end. Its arrival time is directly calculated from the sound velocity, which is a core parameter for judging the density, uniformity, and defect location of the pile body. If the first wave is misidentified, the sound velocity along the entire propagation path will be deviated, affecting the reliability of the pile integrity evaluation. Therefore, accurate identification of the first wave is necessary. In actual pile bodies, sound wave propagation is affected by complex effects such as multipath diffraction, reflection from the guide wall, and local reflection from the reinforcing steel. These interference signals superimposed on the main wave can blur the true boundary of the first wave. At the same time, when there are honeycombing or mud inclusions in the pile body, the energy of the main wave decreases, making the initial arrival time less prominent. Therefore, the first wave often exhibits characteristics such as weak energy, unclear boundaries, and susceptibility to being replaced by interference wave artifacts, making it difficult to accurately identify in the raw waveform.
[0025] The first wave is the signal that truly comes from the main propagation path, and its arrival time will show a smooth and continuous change with the test depth position. However, false signals from local reflectors, such as steel bar reflection, local void boundaries, and honeycomb point defects, can only be excited at a few locations close to the reflector. Therefore, in terms of spatial continuity, they only show the property of sudden local appearance and discontinuous position. Therefore, the reflection extreme value chain composed of reflection extreme value points at different depths is first constructed based on the smooth continuity of reflection extreme value points at different depths.
[0026] As an example, for each depth of ultrasound detection data, there are multiple waveform maxima. These waveform maxima are used as the reflection extreme points of the current depth to reflect the sound wave reflection at the current depth.
[0027] As an example, a reflection extremum chain includes multiple chains, specifically a data chain formed by connecting reflection extremum points at different depths with strong continuity. For any reflection extremum point, there is at least one existing reflection extremum chain. For example, if depth 1 includes reflection extremum points A / B / C and depth 2 includes D / E / F, then the reflection extremum chain can be AD or BD. Thus, the reflection extremum point D will exist in two reflection extremum chains, and so on.
[0028] The step S20 of the concrete micropile integrity detection based on ultrasonic technology also includes steps S21-S22, including: Step S21: For any depth in the original waveform data, continuously match each reflection extreme point at the current depth with the reflection extreme point at the next depth to obtain multiple matching reflection extreme points. The depths in the original waveform data are arranged sequentially from bottom to top of the pile. As an example, since the probe first descends to the bottom of the pile and then rises at a constant rate to record the signal, the extreme reflection points at each depth are obtained sequentially from the bottom of the pile. Then, the continuity is matched with each extreme reflection point at the next depth (shallower depth or higher depth). The normal continuity matching degree between extreme reflection points at different depths is calculated. Based on the normal continuity matching degree, the matching extreme reflection point is selected from the extreme reflection points at the next depth. The extreme reflection point with the strongest continuity with the extreme reflection point at the current depth is selected from the extreme reflection points at the next depth.
[0029] Step S21 includes: Determine the signal time difference and amplitude difference between each reflection extremum point at the current depth and the reflection extremum point at the next depth.
[0030] Based on the signal time difference and amplitude difference, the normal continuity matching degree between each reflection extremum point at the current depth and the reflection extremum point at the next depth is calculated. The signal time difference and amplitude difference are negatively correlated with the normal continuity matching degree.
[0031] As an example, the original waveform data is obtained by measuring the acoustic probe in the acoustic tube. For any set of acoustic tubes, at the [missing information]... The first depth The reflection extreme point and the next depth of the first reflection extreme point Normal continuous matching degree of each reflection extreme point The calculation method is as follows: In the formula, For the first The first depth The first reflection extreme value and the next depth of the first The signal time difference of each reflection extremum (i.e., the absolute value of the difference on the horizontal axis); For the first The first depth The first reflection extreme value and the next depth of the first The absolute value of the amplitude difference between the three reflection extrema, where norm() represents the normalization function, for example, maximum-minimum normalization; where... and The similarity of the two reflection extrema in terms of transmission time (the time it takes for the ultrasonic wave to travel from the transmitter to the receiver) and amplitude is respectively indicated. If they are similar, it means that the two reflection extrema can represent the smooth and continuous characteristics of the first wave during its position rise.
[0032] For any reflection extremum point, the reflection extremum point with the highest normal continuous matching degree in the next depth corresponding to the current reflection extremum point is taken as the matching reflection extremum point of the current reflection extremum point.
[0033] As an example, for any set of sonic logging tubes, at the first... The first depth For each reflection extreme point, the reflection extreme point with the highest normal continuous matching degree at the next depth is recorded as the matching reflection extreme point of that reflection extreme point.
[0034] Step S22: Connect the reflection extremum points with each matching reflection extremum point to obtain the reflection extremum chain corresponding to each reflection extremum point. Any reflection extremum point exists in at least one reflection extremum chain.
[0035] As an example, since the first wave in ultrasonic testing necessarily exists at each depth with only one true first wave position, and assuming no defects, it exhibits continuous trend, gradually changing amplitude without abrupt changes, and smooth spatial extension as it ascends in depth, it is possible to start from the bottom of the pile and continuously match all reflection extrema points at each depth with the reflection extrema points at the next depth to obtain a reflection extrema chain that runs through the entire depth. This reflection extrema chain conforms to the physical characteristics of the true first wave. Starting from the deepest depth, for any reflection extrema, the matching reflection extrema obtained by iteratively following the above method are obtained, and the reflection extrema points are connected in series with their corresponding matching reflection extrema points. Series connection is a data connection method, mainly used to form a data sequence, thereby obtaining a reflection extrema chain, denoted as the reflection extrema chain of that reflection extrema (for example, B is the matching reflection extrema of A, and C is the matching reflection extrema of B, then A, B, and C constitute a reflection extrema chain).
[0036] After step S22, the following steps are also included: If any reflection extremum point at the current depth does not exist in the reflection extremum chain, then the current reflection extremum point is taken as the starting point.
[0037] The starting point is continuously matched with the reflection extremum point at the next depth, and the reflection extremum chain corresponding to the current starting point is reconstructed.
[0038] As an example, if a reflection extremum in the upper or next depth does not exist in any reflection extremum chain, except for the first depth position, the current reflection extremum point is taken as the starting point of the reflection extremum chain, and the reflection extremum points of other depths are continuously matched to form a new reflection extremum chain, ensuring that all reflection extremum points are in the reflection extremum chain.
[0039] Step S30: Based on the degree of matching optimization and the abrupt change of different reflection extreme points on the reflection extreme point chain, determine the suspected first wave extreme point among the reflection extreme points at different depths.
[0040] As an example, the presence of defects in the pile body can disrupt the continuity of the first wave, causing the above matching method to fail after the local defect area. This is because when defects such as cavities or mud inclusions appear in the pile body, the real first wave will exhibit phenomena such as a jump in travel time and a sudden decrease in amplitude due to a decrease in sound velocity, energy attenuation, or path diffraction, thus failing to maintain normal continuity characteristics. Therefore, it is necessary to judge the possibility of defects at each depth based on the abruptness of the matching.
[0041] As an example, the matching preference degree is used to reflect the probability that the reflection extremum at any depth is the first wave extremum. The greater the matching preference degree, the greater the probability that the corresponding reflection extremum is the first wave extremum.
[0042] Step S30 includes steps S31 to S34: Step S31: For any reflection extremum point in any reflection extremum chain, based on the normal continuous matching degree of each first reflection extremum point before the current reflection extremum point and the depth difference between the current reflection extremum point and each first reflection extremum point, calculate the previous matching level value of the current reflection extremum point. The previous matching level value is used to characterize the matching continuity between each first reflection extremum point at the depth before the current reflection extremum point.
[0043] As an example, the first reflection extreme point is any of the reflection extreme points in the depth before the current reflection extreme point, and the first reflection extreme point and the current reflection extreme point are in the same reflection extreme value chain. When a defect occurs in the pile, a sudden change often occurs at a certain reflection extreme point. The previous matching level value of each point before this reflection extreme point is generally normal. By comparing the previous matching level value with the normal continuous matching degree of the reflection extreme point, the possibility of a sudden change at this point can be determined.
[0044] As an example, the depth difference can be the difference between the depth of the current reflection extremum and the depth of the previous first reflection extremum. For example, if the depth of the current reflection extremum is 4 and the depth of the first reflection extremum is 3, then the depth difference is 1.
[0045] As an example, taking the d-th reflection extremum point as an example, the pre-matching level value The calculation method can be: In the formula, For the first The nth reflection extremum point is the nth reflection extremum point in its respective reflection extremum chain. The number of depths before each reflection extremum point; For the first Normal continuous matching degree of the first reflection extreme point; For the first The first reflection extreme point and the first The depth difference between two extreme reflection points is denoted as the normal continuous matching degree between the two extreme reflection points. For example, the normal continuous matching degree between A and B is denoted as the normal continuous matching degree of A.
[0046] Expressed in the first The depth before the first reflection extremum point generally corresponds to the matching level / matching continuity. If a defect occurs, this could lead to abrupt changes, so the previous matching level value needs to be compared with the first... The normal continuous matching degree of each reflection extremum point is compared. is the distance weight, and softmax is the normalization function.
[0047] Step S32: Based on the normal continuous matching degree and the previous matching level value, calculate the degree of matching mutation at each reflection extreme point.
[0048] As an example, taking the d-th reflection extremum point as an example, the degree of abrupt change in the matching... The calculation method can be: In the formula, For the first The pre-matching level value of each reflection extremum point; For the first The normal continuous matching degree of each reflection extreme point, max() represents taking ( ) The maximum value between.
[0049] Step S33: Based on the degree of matching mutation and the degree of normal continuous matching, calculate the degree of matching optimization for each reflection extreme point.
[0050] As an example, the credibility of each reflection extreme point is calculated by matching the degree of mutation. Then, based on the credibility and the normal continuous matching degree, the matching optimization degree of each reflection extreme point is calculated.
[0051] Step S33 includes: The reliability of the current reflection extreme point is calculated based on the degree of matching abrupt change of each first reflection extreme point before any reflection extreme point in the current reflection extreme point chain.
[0052] As an example, if a defect occurs during the matching process, it will cause a delay in the time taken, leading to a sudden drop in the normal continuous matching degree. Furthermore, the matched position may not be the true first wave position. Therefore, it is necessary to determine the reliability of the reflection extrema on the reflection extrema chain. Since the matching is done sequentially from bottom to top, if there is a reflection extrema with a high degree of abrupt change in matching in the path from bottom to top, then subsequent matching is unreliable. Based on this, the reliability of the current reflection extrema point is calculated.
[0053] The step of calculating the confidence level of the current reflection extremum point based on the matching mutation degree of each first reflection extremum point before any reflection extremum point in the current reflection extremum chain includes: Determine the first maximum value among the matching mutation degrees of each first reflection extremum point before any reflection extremum point in the current reflection extremum chain.
[0054] The reliability of the current reflection extreme point is calculated based on the difference between the preset value and the first maximum value.
[0055] As an example, the preset value can be 1. Taking the d-th reflection extremum point as an example, the reliability level is... The calculation method can be: In the formula, For the reflection extremum chain, from the first reflection extremum point to the... The maximum value of the degree of abrupt change in the matching between the extreme reflection points, which is also the first maximum value, This indicates the degree of abrupt change in the matching of each first reflection extremum point before any reflection extremum point.
[0056] Based on the degree of confidence and the degree of normal continuous matching, the degree of matching optimization of each reflection extreme point is calculated.
[0057] As an example, at any depth, since there is one and only one first wave, when there are no defects, the reflection extremum point corresponding to the first wave will have the highest continuous smoothness in the depth change. Based on this, the matching optimization degree of each reflection extremum point is calculated.
[0058] The step of calculating the matching optimization degree of each reflection extreme point based on the degree of confidence and normal continuous matching includes: For any reflection extremum chain existing at the current reflection extremum point, calculate the first average of the product between the confidence level of each reflection extremum point in the current reflection extremum chain and the normal continuous matching degree.
[0059] The maximum value among the first average values corresponding to each reflection extremum chain where different reflection extremum points exist is taken as the matching preference degree of each reflection extremum point.
[0060] As an example, for any reflection extremum point x in any reflection extremum chain, its matching preference can be calculated as follows: In the formula, The degree of matching preference for the extreme reflection point x; This represents the total number of reflection extrema in the reflection extrema chain containing the reflection extrema point x. The x-th point in the reflection extremum chain containing the reflection extremum point x. The reliability of the reflection extreme points; The x-th point in the reflection extremum chain containing the reflection extremum point x. Normal continuous matching degree of each reflection extremum point This represents the first average value. The reason is that the reflection extremum x may exist in multiple reflection extremum chains, so the calculated maximum value is selected as the matching preference degree of the current reflection extremum point.
[0061] Step S34: For any depth, the reflection extreme point corresponding to the maximum matching preference at the current depth is taken as the suspected first wave extreme point.
[0062] As an example, for any depth, the reflection extreme point corresponding to the maximum matching preference among all reflection extreme points at that depth is recorded as the suspected first-wave extreme point.
[0063] Step S40: Based on the matching optimization degree of suspected first wave extreme points at different depths, calculate the probability of defect existence at different depths.
[0064] As an example, after determining the possible first wave location / suspected first wave extreme point at each depth, the location of the defect is reflected by the abrupt change in sound velocity at the defect location, the break in the reflection extreme value chain matching, and the fact that the defect exists in a local area. Therefore, the matching preference of the suspected first wave extreme point at the depth where the defect is located is relatively small. At the same time, the normal continuous matching degree between the suspected first wave extreme point and its matching reflection extreme point is relatively small. Based on this, the probability of the existence of the defect at different depths is calculated.
[0065] Step S40 includes: For any given depth, determine the normal continuity matching degree and matching optimization degree of the suspected first wave extreme point in the current depth.
[0066] Based on the product of the inverse proportional value of the matching preference degree and the normal continuous matching degree, the probability of defect existence at different depths is calculated. The probability of defect existence is negatively correlated with the normal continuous matching degree and the matching preference degree.
[0067] As an example, with the first Taking a depth as an example, the probability of defect existence The calculation method is as follows: In the formula, For the first The normal continuous matching degree of the suspected first wave extreme points corresponding to each depth; For the first The matching optimization degree of the suspected first wave extreme point corresponding to each depth, norm() represents the normalization function, for example, the maximum and minimum value normalization.
[0068] Step S50: When the probability of the defect exists meets the preset conditions, determine the depth and location of the defect in the concrete micropile.
[0069] As an example, the preset condition could be that the probability of a defect exists is greater than a preset probability threshold. When the probability of a defect exists is greater than the preset probability threshold, the preset condition is satisfied, that is, the depth and location of the defect in the concrete micropile can be determined.
[0070] Step S50 includes: The probability of the defect being present is compared with a preset probability threshold.
[0071] If the probability of a defect exists is greater than a preset probability threshold, then a defect is determined to exist at the depth corresponding to the probability of a defect in the concrete micropile; otherwise, no defect exists.
[0072] As an example, the preset probability threshold can be 0.6, 0.7, etc., and there is no specific limitation.
[0073] As an example, since the above method only judges the data between any two sonic logging tubes, in order to comprehensively judge the integrity of the concrete micropiles, all adjacent sonic logging tubes and diagonal sonic logging tubes are measured and analyzed separately to obtain the probability of defects at each depth in accordance with the above method.
[0074] Taking a preset probability threshold of 0.6 as an example, when the probability of a defect is greater than 0.6, the concrete micropile is determined to be incomplete, and the depth and location of the defect are displayed, requiring treatment of the concrete micropile. Conversely, if the probability is less than 0.6, the pile body is considered to be free of defects. Specifically, the overall implementation flowchart of this application is as follows: Figure 2 As shown.
[0075] This application provides a method for detecting the integrity of concrete micropiles based on ultrasonic technology. It acquires original waveform data at multiple depths within the concrete micropiles. Based on the smoothness and continuity of reflection extrema points at different depths in the original waveform data, a reflection extrema chain is constructed. Then, based on the matching optimization degree and matching abruptness of different reflection extrema points on the reflection extrema chain, suspected first-wave extrema points at different depths are identified. The waveform maxima at different depths that best match the characteristics of the first wave are selected, making the main wave energy affected by other inhomogeneous media clearly visible, thus improving the accuracy of the extracted first wave at different depths. Furthermore, based on the matching optimization degree of the suspected first-wave extrema points, the probability of defects at different depths is determined. When the probability of defects meets preset conditions, the depth and location of defects in the concrete micropiles are determined, improving the accuracy of defect identification.
[0076] Reference Figure 3 , Figure 3 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application.
[0077] like Figure 3 As shown, the ultrasonic-based concrete micropile integrity testing device may include: a processor 1001, a memory 1003, and a communication bus 1002. The communication bus 1002 is used to realize the connection and communication between the processor 1001 and the memory 1003.
[0078] Optionally, the ultrasonic-based concrete micropile integrity testing device may also include a user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, a WiFi module, etc. The user interface may include a display screen and an input submodule such as a keyboard; optional user interfaces may also include standard wired or wireless interfaces. The network interface may include standard wired or wireless interfaces (such as a Wi-Fi interface).
[0079] Those skilled in the art will understand that Figure 3 The structure of the ultrasonic-based concrete micropile integrity testing device shown in the figure does not constitute a limitation on the ultrasonic-based concrete micropile integrity testing device. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.
[0080] like Figure 3As shown, the memory 1003, serving as a storage medium, may include an operating system, a network communication module, and a concrete micropile integrity testing program based on ultrasonic technology. The operating system is a program that manages and controls the hardware and software resources of the ultrasonic-based concrete micropile integrity testing equipment, supporting the operation of the ultrasonic-based concrete micropile integrity testing program and other software and / or programs. The network communication module is used to enable communication between the various components within the memory 1003, as well as communication with other hardware and software in the ultrasonic-based concrete micropile integrity testing system.
[0081] exist Figure 3 In the ultrasonic-based concrete micropile integrity testing device shown, the processor 1001 is used to execute the ultrasonic-based concrete micropile integrity testing program stored in the memory 1003 to implement the steps of the ultrasonic-based concrete micropile integrity testing method described above.
[0082] The specific implementation of the concrete micropile integrity testing device based on ultrasonic technology in this application is basically the same as the embodiments of the concrete micropile integrity testing method based on ultrasonic technology described above, and will not be repeated here.
[0083] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.
[0084] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.
[0085] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.
[0086] The above are merely preferred embodiments of this application and do not limit the scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the scope of protection of this application.
[0087] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0088] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
Claims
1. A method for detecting the integrity of concrete micropiles based on ultrasonic technology, characterized in that, The method includes: Obtain raw waveform data at multiple depths in a concrete micropile; Based on the smooth continuity of reflection extremum points at different depths in the original waveform data, a reflection extremum chain is constructed, wherein the reflection extremum points are the waveform maxima in the original waveform data; Based on the degree of matching preference and the abruptness of matching of different reflection extreme points on the reflection extreme point chain, the suspected first wave extreme point among the reflection extreme points at different depths is determined. Based on the matching optimization degree of the suspected first wave extreme points at different depths, the probability of defect existence at different depths is calculated; When the probability of the defect exists meets a preset condition, the depth and location of the defect in the concrete micropile are determined.
2. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 1, characterized in that, The step of constructing a reflection extremum chain based on the smooth continuity of reflection extremum points at different depths in the original waveform data includes: For any depth in the original waveform data, the reflection extreme points at the current depth are continuously matched with the reflection extreme points at the next depth to obtain multiple matching reflection extreme points. The depths in the original waveform data are arranged sequentially from bottom to top of the pile. The reflection extrema points are connected in series with each of the matching reflection extrema points to obtain the reflection extrema chain corresponding to each reflection extrema point, and any one of the reflection extrema points exists in at least one reflection extrema chain.
3. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 2, characterized in that, After concatenating the reflection extrema points with each of the matching reflection extrema points to obtain the reflection extrema chain corresponding to each of the reflection extrema points, the method further includes: If any reflection extremum point at the current depth does not exist in the reflection extremum chain, then the current reflection extremum point is taken as the starting point; The starting point is continuously matched with the reflection extremum point at the next depth, and the reflection extremum chain corresponding to the current starting point is reconstructed.
4. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 2, characterized in that, The step of continuously matching each reflection extremum point at the current depth with the reflection extremum point at the next depth to obtain multiple matching reflection extremum points includes: Determine the signal time difference and amplitude difference between each reflection extremum point at the current depth and the reflection extremum point at the next depth; Based on the signal time difference and the amplitude difference, the normal continuity matching degree between each reflection extremum point at the current depth and the reflection extremum point at the next depth is calculated. The signal time difference and the amplitude difference are negatively correlated with the normal continuity matching degree. For any reflection extremum point, the reflection extremum point with the highest normal continuous matching degree in the next depth corresponding to the current reflection extremum point is taken as the matching reflection extremum point of the current reflection extremum point.
5. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 1, characterized in that, The determination of suspected first-wave extreme points among reflection extreme points at different depths, based on the degree of matching preference and the abruptness of matching at different reflection extreme points on the reflection extreme point chain, includes: For any reflection extremum point in any of the aforementioned reflection extremum chains, based on the normal continuous matching degree of each first reflection extremum point before the current reflection extremum point and the depth difference between the current reflection extremum point and each of the first reflection extremum points, the previous matching level value of the current reflection extremum point is calculated. The previous matching level value is used to characterize the degree of matching continuity between each of the first reflection extremum points at the depth before the current reflection extremum point. Based on the normal continuous matching degree and the previous matching level value, the degree of matching mutation at each reflection extreme point is calculated; Based on the degree of matching mutation and the degree of normal continuous matching, the degree of matching preference of each of the reflection extreme points is calculated; For any depth, the reflection extreme point corresponding to the maximum value of the matching preference at the current depth is taken as the suspected first wave extreme point.
6. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 5, characterized in that, The calculation of the optimal matching degree for each of the reflection extrema points based on the degree of matching mutation and the degree of normal continuous matching includes: The credibility of the current reflection extreme point is calculated based on the degree of matching abrupt change of each of the first reflection extreme points before any reflection extreme point in the current reflection extreme value chain. Based on the degree of confidence and the degree of normal continuous matching, the degree of matching preference of each of the reflection extreme points is calculated.
7. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 6, characterized in that, The calculation of the reliability of the current reflection extremum point based on the degree of matching abrupt change of each of the first reflection extremum points before any reflection extremum point in the current reflection extremum chain includes: Determine the first maximum value among the matching mutation degrees of each of the first reflection extrema points before any reflection extrema point in the current reflection extrema chain; The reliability of the current reflection extreme point is calculated based on the difference between the preset value and the first maximum value.
8. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 6, characterized in that, The calculation of the matching preference degree of each of the reflection extrema points based on the credibility level and the normal continuous matching degree includes: For any reflection extremum chain existing at the current reflection extremum point, calculate the first average value of the product between the confidence level of each reflection extremum point in the current reflection extremum chain and the normal continuous matching degree; The maximum value among the first average values corresponding to each reflection extremum chain where different reflection extremum points exist is taken as the matching preference degree of each reflection extremum point.
9. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 5, characterized in that, The probability of defect existence at different depths is calculated based on the matching optimization degree of the suspected first-wave extreme points at different depths, including: For any depth, determine the normal continuity matching degree and matching optimization degree of the suspected first wave extreme point in the current depth; The probability of defects at different depths is calculated based on the product of the inverse proportional value of the matching preference degree and the normal continuous matching degree. The probability of defects is negatively correlated with the normal continuous matching degree and the matching preference degree.
10. The method for detecting the integrity of concrete micropiles based on ultrasonic technology as described in claim 1, characterized in that, The step of determining the depth location of the defect in the concrete micropile when the probability of the defect's existence meets a preset condition includes: The probability of the defect's existence is compared with a preset probability threshold; If the probability of the defect is greater than a preset probability threshold, then the concrete micropile is determined to have a defect at the depth corresponding to the probability of the defect; otherwise, there is no defect.