Bridge pile foundation detection system based on internet of things

Abstract

The present application relates to the technical field of bridge pile foundation detection, and particularly relates to a bridge pile foundation detection system based on the Internet of Things. The present application realizes multi-source monitoring data fusion analysis and collaborative diagnosis, and improves the accuracy and consistency of defect identification. By combining acoustic signals and geometric monitoring data for joint criterion, the present application effectively overcomes the misjudgment problem caused by the traditional method relying on a single wave speed index, realizes accurate differentiation and identification of structural defects and geometric size defects, and provides a reliable basis for subsequent targeted maintenance.

Description

Technical Field

[0001] This invention relates to the field of bridge pile foundation testing technology, and specifically to a bridge pile foundation testing system based on the Internet of Things. Background Technology

[0002] As a critical load-bearing and force-transmitting component of bridge structures, the integrity, bearing capacity, and long-term stability of bridge pile foundations directly determine the safety and durability of the entire bridge. However, during the pile construction process, pile foundations are prone to structural defects such as cracks, mud inclusions, and segregation due to uncontrolled processes. During the bridge's operational period, they are also affected by traffic loads, geological changes, and material degradation, leading to geometric defects such as slow settlement and horizontal displacement. These defects severely weaken the load-bearing capacity and durability of the pile foundations. Therefore, comprehensive and accurate detection and monitoring of the condition of bridge pile foundations is a crucial step in ensuring their safe operation and maintenance.

[0003] In existing technologies, conventional acoustic wave transmission detection systems typically rely solely on a single indicator of wave velocity reduction to identify defects. This method is prone to misclassifying non-structural factors such as bent acoustic tubes and uneven coupling agents as concrete defects, and it cannot effectively distinguish defect types, leading to misjudgment or confusion of defect types, which affects the targeted nature of subsequent maintenance measures.

[0004] Meanwhile, existing assessment methods only focus on the local condition identification of the pile foundation itself, failing to combine the position and stress relationship of the pile foundation in the pile group to effectively quantify the load redistribution impact on adjacent pile foundations. Consequently, they cannot provide early warning of potential cascading failure risks, leaving subsequent maintenance decisions without a systematic basis. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art. Based on the fusion of multi-source monitoring data such as acoustics and geometry, it collaboratively analyzes multiple acoustic parameters such as concrete wave velocity, signal reflection time, and spectral characteristics. Through directionally independent deformation criteria and quantification of pile group influence, it significantly improves the accuracy of bridge pile foundation defect location and type identification, and achieves a leap from local diagnosis to overall early warning.

[0006] The technical solution adopted by the present invention to solve its technical problem is: a bridge pile foundation detection system based on the Internet of Things, including the following steps: an acoustic diagnostic module, which collects the time-domain waveform of the ultrasonic signal of the bridge pile foundation according to a preset cycle through an ultrasonic device, identifies the concrete wave velocity, signal reflection time and spectral characteristics, and determines whether there are structural defects in the pile foundation. If so, it analyzes the type of defect in the pile foundation.

[0007] The process for determining whether there are structural defects in the pile foundation is as follows: if the concrete wave velocity collected at the current acoustic wave measuring point is lower than the preset wave velocity threshold, and the deviation between the signal reflection time and the reflection time of defect-free concrete exceeds the preset deviation threshold, then the pile foundation is determined to have structural defects; otherwise, the current acoustic wave measuring point of the pile foundation is determined to have no structural defects, and the next acoustic wave measuring point is tested.

[0008] The process of analyzing the defect types of pile foundations is as follows: For pile foundations with structural defects, calculate the main frequency offset and high-frequency energy ratio of their ultrasonic signal spectrum characteristics; when the main frequency offset is less than the preset offset threshold and the high-frequency energy ratio is greater than the preset ratio, it is determined to be a surface structural defect; when the main frequency offset is greater than or equal to the preset offset threshold and the high-frequency energy ratio is less than or equal to the preset ratio, it is determined to be an internal structural defect.

[0009] The geometric monitoring module acquires the horizontal displacement, settlement, uplift, and vertical deviation of the pile foundation, and quantifies the geometric dimensional anomalies of the pile foundation accordingly.

[0010] The comprehensive evaluation module quantifies the degree of defects in the pile foundation based on the defect type and location; it also identifies abnormal pile foundations based on the degree of geometric anomaly and the degree of defects, and analyzes the impact of abnormal pile foundations on the pile group.

[0011] The process of analyzing the degree of defects in the pile foundation is as follows: A continuity analysis is performed on the acoustic measurement points corresponding to surface and internal structural defects along the axial direction of the pile foundation. Acoustic measurement points that are adjacent in the axial direction of the pile foundation and have no normal measurement point interval are grouped into the same defect area. The absolute value of the coordinate difference between the first and last acoustic measurement points of the defect area in the axial direction of the pile foundation is taken as the axial continuous length of the defect. The ratio of the axial continuous length to the total length of the pile foundation is taken as the axial expansion coefficient. The ratio of the number of abnormal acoustic measurement lines within the axial continuous length to the total number of acoustic measurement lines is taken as the lateral expansion coefficient. The product of the axial expansion coefficient and the lateral expansion coefficient is taken as the spatial expansion degree.

[0012] For surface structural defects and internal structural defects, corresponding defect type weighting coefficients are assigned respectively; the pile foundation is divided into multiple functional areas along the axial direction, and each functional area is assigned a corresponding position influence coefficient according to its role in structural stress; the functional area where the defect area is located is determined according to the axial center position of the defect area, and the corresponding position influence coefficient is obtained; the product of the defect type weighting coefficient and the position influence coefficient is used as the comprehensive defect factor; the product of the spatial expansion degree and the comprehensive defect factor is used as the defect degree of the pile foundation.

[0013] The safety early warning module provides graded early warnings for pile foundations based on the degree of geometric anomaly, the degree of defect, and the impact of the pile group.

[0014] Compared with existing technologies, this invention has the following advantages: 1. This invention realizes the fusion analysis and collaborative diagnosis of multi-source monitoring data, improving the accuracy and consistency of defect identification. By combining acoustic signals and geometric monitoring data for joint judgment, it effectively overcomes the misjudgment problem caused by the reliance on a single wave velocity index in traditional methods, and achieves accurate differentiation and identification of structural defects and geometric defects, providing a reliable basis for subsequent targeted maintenance.

[0015] 2. This invention achieves a leap from defect identification to precise defect type determination, improving the targeted nature of maintenance measures. By deeply analyzing the ultrasonic signal spectrum characteristics at the defect location, it effectively distinguishes between surface structural defects and internal structural defects, solving the problem of defect type confusion in existing technologies.

[0016] 3. This invention upgrades the assessment from single pile foundation evaluation to pile group system impact assessment. By introducing pile group impact degree, it comprehensively analyzes the spatial distribution pattern, relative distance, and degree of defects of abnormal pile foundations, assesses their impact on adjacent pile foundations, and achieves early warning of potential cascading risks, enabling operation and maintenance management to shift from passively responding to local damage to proactively preventing and controlling system risks. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the system module connections of the present invention;

[0019] Figure 2 This is a schematic diagram of the process for determining whether there are structural defects in the pile foundation in this invention;

[0020] Figure 3 This is a flowchart illustrating the process of analyzing the defect types of pile foundations in this invention;

[0021] Figure 4 This is a schematic diagram of the process for determining abnormal pile foundations in this invention. Detailed Implementation

[0022] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. Furthermore, it should be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale.

[0023] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification.

[0024] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0025] This invention proposes a bridge pile foundation detection system based on the Internet of Things, including an acoustic diagnostic module, a geometric monitoring module, a comprehensive evaluation module, and a safety early warning module; and the comprehensive evaluation module is connected to the acoustic diagnostic module, the geometric monitoring module, and the safety early warning module respectively.

[0026] Please see Figures 1 to 4 As shown, the data flow sequence in the above modules is as follows: the acoustic diagnostic module and the geometric monitoring module work in parallel, and their output data are synchronously input to the comprehensive evaluation module. The comprehensive evaluation module outputs the decision results to the safety early warning module.

[0027] The acoustic diagnostic module acquires the time-domain waveform of the ultrasonic signal of the bridge pile foundation through ultrasonic equipment at a preset cycle, and identifies the concrete wave velocity, signal reflection time and spectral characteristics from it. Based on this, it determines whether there are structural defects in the pile foundation. If so, it analyzes the type of defect in the pile foundation.

[0028] In the implementation of the above scheme, the ultrasonic signal time-domain waveform of the bridge pile foundation is collected by ultrasonic equipment according to a preset cycle, and the concrete wave velocity, signal reflection time and spectral characteristics are identified from it. See the following process: The ratio of the center distance between the ultrasonic transmitter and receiver in the acoustic tube to the propagation time of the ultrasonic signal in the concrete is taken as the concrete wave velocity at each acoustic measurement point.

[0029] It's important to understand that internal defects can disrupt the continuity of concrete, leading to a decrease in wave velocity. Calculating wave velocity using the center-to-center spacing of the sonic logging tubes can eliminate errors related to the tube wall and installation, ensuring accurate and consistent results.

[0030] The absolute value of the difference between the arrival time of the first wave and the appearance time of the subsequent reflected wave in the time-domain waveform of the received ultrasonic signal is taken as the signal reflection time.

[0031] Ultrasonic signals propagate at a constant wave speed in concrete. When they encounter a defect interface (such as a crack or void), they are reflected and a reflected wave is generated. The signal reflection time is essentially the round-trip time difference of the ultrasonic wave from the emission point to the defect interface and back to the receiving point.

[0032] The received ultrasonic signal time-domain waveform data is transformed in the frequency domain to extract spectral features. In this invention, the time-domain signal can be converted into a frequency-domain signal through Fourier transform to analyze its frequency component distribution.

[0033] In the implementation of the above scheme, the specific process of determining whether the pile foundation has structural defects based on concrete wave velocity, signal reflection time and spectral characteristics is as follows: if the concrete wave velocity collected at the current acoustic wave measuring point is lower than the preset wave velocity threshold, and the deviation between the signal reflection time and the reflection time of defect-free concrete exceeds the preset deviation threshold, then the pile foundation is determined to have structural defects; otherwise, the current acoustic wave measuring point of the pile foundation is determined to have no structural defects, and the next acoustic wave measuring point is tested.

[0034] In concrete without structural defects, the ultrasonic signal propagates smoothly, and the wave velocity is stable and in a high range. When there are structural defects in the concrete, the density of the defect area is significantly reduced, and the ultrasonic signal needs to diffract or penetrate the defect. The propagation path becomes longer and the energy attenuation is aggravated, resulting in the measured wave velocity being lower than the normal range, that is, lower than the preset wave velocity threshold.

[0035] Therefore, the fact that the collected concrete wave velocity is lower than the preset wave velocity threshold is the basic basis for judging whether there may be structural defects in the concrete, and directly reflects the macroscopic characteristics of the disruption of material continuity.

[0036] If there are structural defects in the concrete, the defect interface will generate additional reflected waves, causing the difference between the time from signal transmission to the first reception and the time of subsequent reflected waves to deviate significantly from the reflection time of defect-free concrete. That is, the deviation between the signal reflection time and the reflection time of defect-free concrete exceeds the preset deviation threshold.

[0037] Existing technologies rely solely on the single criterion that the collected concrete wave velocity is below a preset wave velocity threshold. This can easily lead to misjudging non-structural factors such as bent acoustic logging tubes or uneven application of coupling agent as structural defects. In contrast, this invention employs a dual-condition approach to determine concrete structural defects, ensuring that structural defects can be accurately identified.

[0038] In a specific implementation of this invention, for example, the preset wave velocity threshold is 3600 m / s, and the preset deviation threshold is determined based on the normal fluctuation range of the ultrasonic signal reflection time of pile foundations without structural defects. It is determined by statistically analyzing the average and standard deviation of the reflection time of pile foundations without structural defects, combined with the engineering safety factor, to ensure that normal reflection fluctuations and abnormal reflections caused by structural defects can be effectively distinguished. For high-stress pile foundations, the sensitivity to structural defects is high, and the preset deviation threshold can be set to a range of 0.0008-0.001 seconds to identify minor structural defects earlier. In this invention, 0.0008 seconds can be used. For minor pile foundations, the threshold can be appropriately relaxed, and the preset deviation threshold can be set to a range of 0.0012-0.0015 seconds. In this invention, 0.0012 seconds can be used.

[0039] For pile foundations with structural defects, the dominant frequency offset and high-frequency energy ratio of their ultrasonic signal spectrum characteristics are calculated to determine the defect type. The dominant frequency offset refers to the difference between the dominant frequency of the ultrasonic signal from the defective concrete and the dominant frequency of the signal from normal concrete, reflecting the homogeneity of the concrete. The high-frequency energy ratio is the ratio of the high-frequency energy in the ultrasonic signal to the total frequency band energy, reflecting the material's attenuation characteristics. Both calculations can be based on mature signal processing and vibration spectrum analysis theories.

[0040] When the main frequency offset is less than a preset offset threshold and the high-frequency energy ratio is greater than a preset ratio, it is determined to be a surface structural defect. When the main frequency offset is greater than or equal to a preset offset threshold and the high-frequency energy ratio is less than or equal to a preset ratio, it is determined to be an internal structural defect.

[0041] Surface structural defects mainly include cracking, spalling, pitting, shallow cracks, and surface inclusions in the concrete protective layer of the pile body. Internal structural defects mainly include segregation, voids, deep cracks, broken piles, and internal mud inclusions in the deep or central areas of the pile body.

[0042] The dominant frequency of an ultrasonic signal is the frequency component with the most concentrated energy in the time-domain waveform. In defect-free concrete, the signal propagation path is smooth and the scattering is weak, resulting in a stable dominant frequency. When defects are present, the signal propagation path changes, causing the dominant frequency to shift. The amount of dominant frequency shift is directly related to the depth of the structural defect (surface / internal).

[0043] Surface structural defects: The defects are located on the concrete surface and close to the acoustic logging pipe. The ultrasonic signal only needs to diffract or penetrate the defect over a short distance. The propagation path changes little and the interference to the main frequency is weak. Only a small amount of unevenness in the surface medium causes a slight shift in the main frequency. Therefore, the main frequency shift is less than the preset shift threshold.

[0044] Internal structural defects: The defects are located inside the concrete and far from the acoustic logging pipe. The signal needs to diffract over a long distance through the defect area. The propagation path is complex and the scattering is severe. The main frequency with concentrated energy is significantly interfered with, causing the main frequency to shift significantly to the low frequency direction. Therefore, the main frequency shift is greater than or equal to the preset shift threshold.

[0045] The high-frequency energy ratio of an ultrasonic signal is the proportion of high-frequency energy in the frequency domain signal to the total frequency band energy. It reflects the degree of high-frequency attenuation of the ultrasonic signal during propagation. The degree of attenuation is related to the number of defect interfaces and the porosity of the medium. Moreover, the attenuation effects of surface and internal defects are quite different: Surface structural defects: There is only a single defect interface, which has a weak scattering effect on the ultrasonic signal and only a small amount of high-frequency components are lost. Therefore, the high-frequency energy ratio is greater than the preset ratio.

[0046] Internal structural defects: Defective areas are usually accompanied by multiple interfaces and have low internal medium density. Signals need to pass through the interfaces multiple times during propagation, and high-frequency components are scattered and absorbed in large quantities, resulting in a significant decrease in the proportion of high-frequency energy. Therefore, the high-frequency energy ratio is less than or equal to the preset ratio.

[0047] A single indicator cannot accurately distinguish the type of defect. For example, a small main frequency offset may be a surface defect or a small internal defect; a low high-frequency energy ratio may be an internal defect or a signal attenuation caused by uneven coupling agent. By using a dual-indicator collaborative judgment logic, we can follow the physical laws of ultrasonic signal propagation in different defects and form a dual verification against interference factors in engineering inspection. This ensures that the defect type judgment results are consistent with the actual situation and provides a reliable basis for configuring defect type weight coefficients (internal defects have a higher weight than surface defects) in the subsequent comprehensive evaluation module.

[0048] It should be understood that the aforementioned preset offset threshold and preset ratio can be obtained through experimental calibration using standard concrete test blocks with known defects. In a specific implementation of this invention, for example, the preset offset threshold typically ranges from 3kHz to 5kHz, and in this invention, 3kHz can be used; the preset ratio typically ranges from 0.3 to 0.4, and in this invention, 0.3 can be used.

[0049] The geometric monitoring module acquires the horizontal displacement, settlement, uplift, and vertical deviation of the pile foundation, and quantifies the geometric dimensional anomalies of the pile foundation accordingly.

[0050] Horizontal displacement: directly reflects the pile foundation's ability to resist lateral loads; an abnormal increase indicates the risk of pile bending or overall instability.

[0051] Settlement and uplift: These represent the vertical bearing capacity of pile foundations. Excessive settlement may be due to foundation consolidation or loss of pile end bearing capacity; uplift may be caused by frost heave, expansive soil, or slope slippage. Both are direct indicators of vertical safety.

[0052] Vertical deviation: Used to comprehensively quantify the overall tilt of the pile body, it is a global indicator for judging whether the pile foundation has deflected or bent.

[0053] During the operation of bridge pile foundations, they are affected by traffic loads, geological changes, and material deterioration, resulting in geometric defects such as slow settlement and horizontal displacement. However, instability often manifests as complex spatial deformation, and a single indicator (such as monitoring only settlement) is insufficient to fully capture the trend of structural deterioration. For example, slight settlement at the top of the pile foundation may be accompanied by significant lateral tilting. If only vertical displacement is considered, the structural risk will be seriously underestimated.

[0054] This invention introduces horizontal displacement, settlement, uplift, and vertical deviation, corresponding to lateral displacement, compression settlement, upward floating and voiding, and overall tilting, respectively, forming a comprehensive system for characterizing the spatial attitude of pile foundations, effectively avoiding misjudgments caused by the one-sidedness of indicators. Multi-parameter coordination can comprehensively capture such complex deformations and accurately trigger early warnings.

[0055] In the implementation of the above scheme, the specific process of obtaining the horizontal displacement, settlement, uplift and vertical deviation of the pile foundation is as follows: sensor nodes are set up at key locations of the pile foundation, such as the top, middle and bottom of the pile foundation, and incorporated into a unified engineering measurement coordinate system.

[0056] The sensor nodes are all based on a unified engineering measurement coordinate system to ensure that the spatial position of all nodes can be accurately expressed.

[0057] The spatial coordinate data of each sensor node at different monitoring times are obtained. Based on the changes in spatial coordinates between adjacent times, the displacement components in the horizontal direction, the vertical downward direction, and the vertical upward direction are calculated respectively to obtain the horizontal displacement, settlement, and uplift.

[0058] The maximum angle between the spatial axis of the pile foundation and the vertical reference direction, generated by a curve fitting algorithm, is used as the vertical deviation of the pile foundation. The spatial axis of the pile foundation is obtained by fitting the planar coordinates of sensor nodes at different depths along the pile foundation axis into a three-dimensional curve using the least squares method. The vertical reference direction refers to the initial design direction of the pile foundation or the direction of gravity, and is directly determined by measuring instruments.

[0059] In the implementation of the above scheme, the specific process of quantitatively analyzing the geometric dimensional anomalies of the pile foundation based on the horizontal displacement, settlement, uplift and vertical deviation of the pile foundation is as follows.

[0060] Calculate the total horizontal displacement, total settlement, and total uplift from the first monitoring time to the current monitoring time.

[0061] It is important to understand that the total amount mentioned above refers to the cumulative net change in the pile foundation in the corresponding direction from the first monitoring to the current moment. The cumulative net change is calculated based on the coordinate difference between the first monitoring moment and the current monitoring moment.

[0062] Since the pile top is the critical connection point for load transfer, the total settlement and total uplift are usually based on the vertical displacement of the pile top node. The total horizontal displacement is taken from the sensor node with the largest horizontal deformation at the pile top or in the pile body to capture the maximum offset of the pile body under lateral load. The vertical deviation is obtained by fitting the coordinates of all nodes to ensure representativeness.

[0063] The total horizontal displacement, total settlement, total uplift, and vertical deviation were normalized to obtain their corresponding normalized outliers. The maximum value among all normalized outliers was taken as the maximum single-item anomaly response value, and the weighted average of all normalized outliers was taken as the comprehensive anomaly index. The product of the maximum single-item anomaly response value and the comprehensive anomaly index was taken as the geometric dimensional anomaly degree of the pile foundation.

[0064] When the total settlement of the pile foundation is within the normal range, but the total horizontal displacement significantly exceeds the limit, although the overall deformation may seem controllable, there is actually a significant hidden danger of shear failure or overall instability. If such localized abrupt deformations are not identified in time, they can easily trigger a chain reaction of structural failures.

[0065] When a pile foundation exhibits a gradual degradation trend with multiple indicators such as long-term cumulative settlement, slow tilting, and periodic uplift, each individual indicator may not exceed the limit, but the long-term synergistic effect has led to the degradation of the pile foundation structure's stiffness, changes in the force path, and a significant decrease in overall stability, constituting a potential systemic risk.

[0066] Traditional assessment methods, such as the single-indicator threshold method, are difficult to identify systemic degradation caused by the synergistic deterioration of multiple indicators; the linear weighted average method is prone to causing severe single anomalies to be dragged down by a large number of normal values, thus masking high risks.

[0067] The maximum single-item anomaly response value can be used to capture extreme risk items, preventing severe single-item deformation from being diluted by other normal parameters, ensuring that the system remains highly sensitive to the most prominent single risk, and achieving rapid response to high-risk states. The comprehensive anomaly index, on the other hand, reflects the overall degradation level and identifies the gradual degradation trend of multiple indicators developing in tandem. Using the product of these two as the geometric anomaly degree ensures both high sensitivity to sudden, localized severe deformations and an effective response to the gradual degradation trend of multiple indicators developing in tandem.

[0068] The comprehensive evaluation module quantifies the degree of defect in the pile foundation based on the defect type and location; identifies abnormal pile foundations based on the degree of geometric anomaly and the degree of defect; and analyzes the impact of abnormal pile foundations on the pile group.

[0069] It is important to understand that different types of defects weaken the bearing capacity of pile foundation structures to vastly different degrees. For example, internal voids (internal structural defects) may appear in ultrasonic testing as a decrease in concrete wave velocity, a prolonged signal reflection time, a large dominant frequency offset, and a decrease in high-frequency energy ratio, but their harm lies in directly reducing the effective cross-sectional area, thus having a direct impact on bearing capacity. On the other hand, surface cracks (surface structural defects) may appear in ultrasonic testing as a smaller decrease in concrete wave velocity, a slight prolongation in signal reflection time, a smaller dominant frequency offset, and a lower high-frequency energy ratio, but their harm lies in causing steel corrosion and concrete spalling, with a more long-term impact.

[0070] Furthermore, the severity of the same defect can vary drastically depending on its location. For example, a defect located in the critical stress zone of a pile foundation, even if its concrete wave velocity, signal reflection time, dominant frequency offset, and high-frequency energy ratio are similar to those of a similar defect located in the load transmission zone of the pile body, is more likely to cause stress concentration and structural instability because it is located on a critical stress path. Defects located at the edge of the pile foundation are more likely to cause overall cross-sectional failure and pose a higher risk than similar defects located in the center.

[0071] This invention combines defect type and defect location for collaborative analysis, enabling a scientific assessment of the actual hazard of defects and providing a reliable basis for the quantitative evaluation of defect severity.

[0072] In the implementation of the above scheme, the specific process of quantitatively analyzing the degree of defect in the pile foundation according to the defect type and defect location is as follows: the continuity analysis of the acoustic measurement points corresponding to surface structural defects and internal structural defects along the axial direction of the pile foundation is carried out, and the acoustic measurement points that are adjacent in the axial direction of the pile foundation and have no normal measurement point interval are classified into the same defect area.

[0073] The absolute value of the coordinate difference between the first and last acoustic measurement points in the defect area along the axial direction of the pile foundation is taken as the axial continuous length of the defect. The ratio of the axial continuous length to the total length of the pile foundation is taken as the axial expansion coefficient; the ratio of the number of abnormal acoustic measurement lines within the axial continuous length to the total number of acoustic measurement lines is taken as the lateral expansion coefficient; and the product of the axial expansion coefficient and the lateral expansion coefficient is taken as the spatial expansion degree.

[0074] It's important to understand that a sonic logging line is the sound wave propagation path formed between a pair of ultrasonic transmitters and receivers. The total number of sonic logging lines is determined by the combination of the number of sonic logging tubes pre-embedded in the pile. For example, when two sonic logging tubes are embedded in the pile foundation, the total number of sonic logging lines is 1; when three sonic logging tubes are embedded in the pile foundation, the total number of sonic logging lines is 3. The number of abnormal sonic logging lines is the number of sonic logging lines determined to have structural defects within the continuous axial length of the defect.

[0075] The axial and lateral expansion coefficients quantify the relative size of the defect in the axial direction and cross section, respectively. The spatial expansion obtained by multiplying them can comprehensively evaluate the three-dimensional distribution range of the defect.

[0076] Specific defect type weighting coefficients are assigned to surface structural defects and internal structural defects respectively; the pile foundation is divided into multiple functional areas along the axial direction, and each functional area is assigned a corresponding position influence coefficient according to its role in structural stress.

[0077] Generally, the weighting coefficient for internal structural defects is higher than that for surface structural defects. In this invention, for example, the value range of the defect type weighting coefficient can be 0-1, with severe defects approaching 1 and minor defects approaching 0. For instance, internal defects, because they directly reduce the effective cross-sectional area of ​​the pile, are assigned a higher weighting coefficient, which can be set to 0.8; surface defects, because they have a smaller impact on bearing capacity, are assigned a lower weighting coefficient, which can be set to 0.3.

[0078] Configuring defect type weighting coefficients enables differentiated evaluation of different types of defects, avoiding treating them all the same, thereby improving the scientific rigor and accuracy of defect severity assessment.

[0079] It should be noted that the functional areas are divided according to their mechanical importance, and can be categorized as the high-stress zone at the pile top, the force transmission zone in the pile body, the load-bearing zone at the pile end, the variable cross-section zone in the pile body, and other secondary stress zones, providing a basis for accurate analysis of the degree of defects. Among them, other secondary stress zones include, but are not limited to: protective or structural sections, and pile body sections located between two critical stress zones.

[0080] The arithmetic mean of the axial coordinates of the first and last acoustic measurement points in the defect area is taken as the axial center position. Based on the axial center position of the defect area, its functional region is determined, and the corresponding positional influence coefficient is obtained.

[0081] It should be noted that the location influence coefficient can be configured according to the degree of stress criticality of each functional area in the overall structure.

[0082] For example, the high-stress zone at the pile top and the bearing zone at the pile end are directly involved in load transfer, so the highest position influence coefficient is configured, with a value range of 1.2-1.3, and 1.2 is used in this invention; the variable cross-section zone of the pile body is prone to stress concentration, so a relatively high position influence coefficient is configured, with a value range of 0.9-1.1, and 1 is used in this invention; the position influence coefficient of the force transmission zone of the pile body is lower than that of the variable cross-section zone of the pile body, but higher than that of the secondary stress zone, with a value range of 0.7-0.9, and 0.8 is used in this invention.

[0083] The purpose of configuring the location influence coefficient is to quantify the weight of the impact of the location of the defect on the overall safety of the pile foundation, so that the assessment results of the degree of pile foundation defects are closer to the actual mechanical response.

[0084] The product of the defect type weighting coefficient and the location influence coefficient is used as the comprehensive defect factor.

[0085] The product of spatial expansion and comprehensive defect factor is used as the degree of defect of the pile foundation.

[0086] The product of spatial expansion and comprehensive defect factor is used as the defect degree of pile foundation, which reflects the physical scale, inherent hazard and structural importance of the defect.

[0087] In the implementation of the above scheme, the specific process of determining abnormal pile foundations based on geometric dimension anomaly and defect degree is as follows: the geometric dimension anomaly of each pile foundation is compared with the preset anomaly judgment threshold, and its defect degree is compared with the preset defect judgment threshold.

[0088] If the degree of geometric dimensional anomaly is greater than or equal to the preset anomaly judgment threshold, or the degree of defect is greater than or equal to the preset defect judgment threshold, then the pile foundation is determined to be an abnormal pile foundation. If neither of the above two conditions is met, then the pile foundation is determined to be a normal pile foundation.

[0089] Relying solely on geometric anomalies or the degree of defects to identify abnormal pile foundations may lead to missed risks. For example, a pile foundation may have serious internal structural defects but no change in its external shape, or the pile foundation may be severely tilted but the concrete may be intact. In such cases, both geometric anomalies and the degree of defects must be considered simultaneously to achieve dual control over both external morphology and internal quality, and to comprehensively identify abnormal pile foundations.

[0090] It should be added that the preset anomaly detection threshold mentioned above can be determined based on the allowable values ​​in industry design specifications. For example, if the specification stipulates that the allowable horizontal displacement at the top of the pile foundation is 10mm, then a certain percentage, such as 80%, can be taken as the preset anomaly detection threshold. The preset anomaly detection threshold can accurately screen abnormal pile foundations that have the risk of instability.

[0091] The preset defect judgment threshold can be determined by combining the axial continuous length of the defect and its functional area, and the value range can be 0.7-1.0. For example, when the axial continuous length of the defect is large and it is located in the pile end bearing zone, the preset defect judgment threshold can be 0.8. The preset defect judgment threshold can effectively identify abnormal pile foundations with potential internal quality problems.

[0092] In the implementation of the above scheme, the specific process of analyzing the impact of abnormal pile foundations on the pile group is as follows: determine the pile cap number to which the abnormal pile foundation belongs, and obtain the coordinates of all pile foundations under that pile cap.

[0093] It should be added that the pile cap is used as the basic analysis unit because it is the core component that coordinates the synergistic force distribution of the pile foundations in the same group, ensuring the mechanical rationality and effectiveness of the pile group influence assessment.

[0094] Based on the obtained pile foundation coordinates, calculate the relative distance between the abnormal pile foundation and other pile foundations under the same pile cap: ;in, Indicates the first The abscissa of the abnormal pile foundation in the pile cap plane coordinate system. Indicates the first The ordinate of the abnormal pile foundation in the pile cap plane coordinate system. This indicates the number of the abnormal pile foundation, with a value range of [value range missing]. =1, 2, ..., , This represents the total number of all identified abnormal piles under the foundation. Indicates the first The x-coordinate of the pile foundation in the plane coordinate system of the pile cap Indicates the first The ordinate of the pile foundation in the plane coordinate system of the pile cap. This indicates the pile foundation number, with a value range of [value range missing]. =1, 2, ..., , This represents the total number of piles under the foundation cap. Based on this, the local influence of the abnormal pile foundation on each pile is calculated using a predefined distance-influence attenuation function.

[0095] It should be added that the distance-influence decay function describes how the intensity of the influence of an abnormal pile foundation on adjacent pile foundations decreases as the spatial distance between them increases. It can be expressed as an exponential decrease in influence with distance, in the form of: ,in, This is the planar distance between the abnormal pile foundation and its adjacent pile foundation. The attenuation coefficient can range from 0.5 to 1.0, and in this invention, it can be 0.7.

[0096] The ratio of the total number of abnormal piles under the same pile cap to the total number of piles is taken as the percentage of abnormal piles. The total number of piles refers to all piles connected to the same pile cap, including normal piles and abnormal piles.

[0097] Identify the spatial distribution pattern of abnormal pile foundations within the pile cap plane, and configure corresponding distribution pattern weight coefficients accordingly; the spatial distribution patterns include concentrated distribution, edge distribution, and dispersed distribution.

[0098] It should be added that concentrated distribution refers to multiple abnormal piles clustered on one side, which is prone to eccentric instability or overall tilting; edge distribution refers to abnormal piles located on the periphery of the pile cap, which is prone to reducing overturning resistance and weakening bending stiffness; and dispersed distribution refers to abnormal piles evenly distributed, with relatively uniform redistribution of internal forces and the overall integrity can still be maintained. Combining spatial distribution patterns can accurately reflect the degree of influence of abnormal pile foundations on the pile group.

[0099] The weighting coefficients for distribution patterns can be assigned based on the degree of harm that each type of distribution poses to the overall stability of the foundation. For example, the weight for a concentrated distribution can range from 1.3 to 1.5; in this invention, it can be 1.3; the weight for a marginal distribution can range from 1.1 to 1.3; in this invention, it can be 1.1; and the weight for a dispersed distribution can be 1.

[0100] The proportion of abnormal numbers Distribution pattern weight coefficient Degree of defects in all abnormal pile foundations and geometrical anomalies The overall influence of the pile cap group is obtained by combining the average values ​​of the data: ,in, and To adjust the weighting coefficients, satisfying It can be set according to the project priorities. For example, if the focus is on material integrity, it can be set to... , If the focus is on structural geometric stability, then... , .

[0101] The maximum value between the local and overall impact is selected as the impact degree of the abnormal pile foundation on the pile group. Selecting the maximum value is to avoid masking local high risks when only taking the average or weighted sum, thus balancing local abrupt changes and overall deterioration trends, improving the reliability of early warnings, and avoiding missing key hidden dangers.

[0102] The safety early warning module provides graded early warnings for pile foundations based on geometric anomalies, defect severity, and the impact of pile groups.

[0103] The specific implementation process of the above scheme is as follows: The geometric dimensional anomalies, defect levels, and their impact on the pile group of the current pile foundation are normalized to obtain geometric risk values, defect risk values, and pile group risk values, respectively. The geometric risk values, defect risk values, and pile group risk values ​​are then weighted and summed to obtain a comprehensive risk index.

[0104] Geometric risk value and defect risk value reflect the local health status of a single pile and are the fundamental sources of risk in bridge pile foundations; pile group risk value reflects the systemic impact of anomalies in a single pile on the surrounding pile foundations and the overall pile cap, representing the diffusion effect of risk in bridge pile foundations. By weighted summation, local risks and systemic risks can be integrated.

[0105] The weighting of geometric risk value, defect risk value, and pile group risk value can be set according to the project focus. For example, for bridge pile foundations with strict requirements for geometric deformation and internal quality control, the geometric risk weight can be set to 0.4, the defect risk weight can be set to 0.4, and the pile group risk weight can be set to 0.2.

[0106] Risk levels are classified according to the following rules: Normal: The comprehensive risk index is less than the first warning threshold. Mild risk: The comprehensive risk index is between the first and second warning thresholds. High risk: The comprehensive risk index is greater than or equal to the second warning threshold.

[0107] It should be noted that the first and second warning thresholds can be determined based on historical data statistics, with the first warning threshold being less than the second warning threshold. In this invention, the first warning threshold can be set to 0.6, and the second warning threshold to 0.8.

[0108] Based on the determined risk level, the corresponding early warning instruction will be triggered; if no warning level is triggered, monitoring will continue.

[0109] It should be added that a mild risk can trigger a yellow alert and generate a monitoring report, prompting increased patrols and data tracking; a high risk can trigger a red alert, automatically pushing alarm information to the management platform, activating the emergency plan, and recommending the suspension of construction or the conduct of special testing; the warning information should include: station number, risk type, main causes, and recommended measures.

[0110] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0111] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0112] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0113] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0114] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0115] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A bridge pile foundation detection system based on the Internet of Things, characterized in that, include: The acoustic diagnostic module uses ultrasonic equipment to collect the time-domain waveform of the ultrasonic signal of the bridge pile foundation according to a preset cycle, and identifies the concrete wave velocity, signal reflection time and spectral characteristics from it. Based on this, it determines whether there are structural defects in the pile foundation, and if so, it analyzes the type of defect in the pile foundation. The process of determining whether there are structural defects in the pile foundation is as follows: if the concrete wave velocity collected at the current acoustic wave measuring point is lower than the preset wave velocity threshold, and the deviation between the signal reflection time and the reflection time of defect-free concrete exceeds the preset deviation threshold, then it is determined that there are structural defects in the pile foundation; otherwise, it is determined that there are no structural defects at the current acoustic wave measuring point of the pile foundation, and the next acoustic wave measuring point is tested. The process of analyzing the defect types of pile foundations is as follows: For pile foundations with structural defects, calculate the main frequency offset and high-frequency energy ratio of their ultrasonic signal spectrum characteristics; when the main frequency offset is less than a preset offset threshold and the high-frequency energy ratio is greater than a preset ratio, it is determined to be a surface structural defect; when the main frequency offset is greater than or equal to the preset offset threshold and the high-frequency energy ratio is less than or equal to the preset ratio, it is determined to be an internal structural defect. The geometric monitoring module acquires the horizontal displacement, settlement, uplift, and vertical deviation of the pile foundation, and quantifies the geometric dimensional anomalies of the pile foundation accordingly. The comprehensive evaluation module quantifies the degree of defects in the pile foundation based on the defect type and location; it also identifies abnormal pile foundations based on the degree of geometric anomaly and the degree of defects, and analyzes the impact of abnormal pile foundations on the pile group. The process of analyzing the degree of defects in the pile foundation is as follows: A continuity analysis is performed on the acoustic measurement points corresponding to surface and internal structural defects along the axial direction of the pile foundation. Acoustic measurement points that are adjacent in the axial direction without normal measurement point intervals are grouped into the same defect area. The absolute value of the coordinate difference between the first and last acoustic measurement points of the defect area in the axial direction is taken as the axial continuity length of the defect. The ratio of the axial continuity length to the total length of the pile foundation is taken as the axial expansion coefficient. The ratio of the number of abnormal acoustic measurement lines within the axial continuity length to the total number of acoustic measurement lines is taken as the lateral expansion coefficient. The product of the axial expansion coefficient and the lateral expansion coefficient is taken as the spatial expansion degree. For surface structural defects and internal structural defects, corresponding defect type weighting coefficients are assigned respectively; the pile foundation is divided into multiple functional areas along the axial direction, and each functional area is assigned a corresponding position influence coefficient according to its role in structural stress; the functional area of ​​the defect area is determined according to the axial center position of the defect area, and the corresponding position influence coefficient is obtained; the product of the defect type weighting coefficient and the position influence coefficient is used as the comprehensive defect factor; the product of the spatial expansion degree and the comprehensive defect factor is used as the defect degree of the pile foundation. The safety early warning module provides graded early warnings for pile foundations based on the degree of geometric anomaly, the degree of defect, and the impact of the pile group.

2. The bridge pile foundation detection system based on the Internet of Things according to claim 1, characterized in that, The process involves acquiring the time-domain waveforms of ultrasonic signals from bridge pile foundations using ultrasonic equipment at preset intervals, and identifying concrete wave velocity, signal reflection time, and spectral characteristics from these waveforms. Specifically: The ratio of the center-to-center distance between the ultrasonic transmitter and receiver in the acoustic logging tube to the propagation time of the ultrasonic signal in the concrete is taken as the concrete wave velocity at each acoustic measurement point. The absolute value of the difference between the arrival time of the first wave and the appearance time of the subsequent reflected wave in the time-domain waveform of the received ultrasonic signal is taken as the signal reflection time. The received ultrasonic signal time-domain waveform data is transformed in the frequency domain to extract spectral features.

3. The bridge pile foundation detection system based on the Internet of Things according to claim 1, characterized in that, Quantitative analysis of geometric anomalies in pile foundations includes: Calculate the total horizontal displacement, total settlement, and total uplift from the first monitoring time to the current monitoring time; use the maximum angle between the spatial axis of the pile foundation generated by the curve fitting algorithm and the vertical reference direction as the vertical deviation of the pile foundation; The total horizontal displacement, total settlement, total uplift, and vertical deviation were normalized to obtain their corresponding normalized outliers. The maximum value among all normalized outliers was taken as the maximum single outlier response value, and the weighted average of all normalized outliers was taken as the comprehensive outlier index. The product of the maximum single abnormal response value and the comprehensive abnormal index is used as the geometric dimensional anomaly degree of the pile foundation.

4. The bridge pile foundation detection system based on the Internet of Things according to claim 1, characterized in that, The process of determining abnormal pile foundations based on geometric anomalies and defect levels is as follows: The geometric dimensional anomaly of each pile foundation is compared with a preset anomaly judgment threshold, and its defect degree is also compared with a preset defect judgment threshold. If the degree of geometric anomaly is greater than or equal to the preset anomaly judgment threshold, or the degree of defect is greater than or equal to the preset defect judgment threshold, then the pile foundation is judged to be an abnormal pile foundation. If neither of the above two conditions is met, the pile foundation is determined to be a normal pile foundation.

5. The bridge pile foundation detection system based on the Internet of Things according to claim 1, characterized in that, The analysis process for the impact of abnormal pile foundations on pile groups includes: Determine the pile cap number to which the abnormal pile foundation belongs, and obtain the coordinates of all pile foundations under that pile cap; Calculate the relative distance between the abnormal pile foundation and other pile foundations under the same pile cap, and then calculate the local influence of the abnormal pile foundation on each pile foundation using a predefined distance-influence attenuation function. The ratio of the total number of abnormal piles under the same pile cap to the total number of piles is taken as the percentage of abnormality. Identify the spatial distribution pattern of abnormal pile foundations within the pile cap plane, and configure corresponding distribution pattern weight coefficients accordingly; the spatial distribution patterns include concentrated distribution, edge distribution, and dispersed distribution. The overall influence of the pile cap pile group is obtained by integrating the proportion of abnormal numbers, the weighting coefficient of distribution pattern, the degree of defects of all abnormal pile foundations, and the average value of geometric anomalies. The maximum value between the local impact degree and the overall impact degree is selected as the impact degree of the abnormal pile foundation on the pile group.

6. The bridge pile foundation detection system based on the Internet of Things according to claim 1, characterized in that, The process of classifying and issuing early warnings for pile foundations based on geometric dimensional anomalies, defect severity, and pile group impact is as follows: The geometric dimensional anomaly, defect degree, and their impact on the pile group of the current pile foundation are normalized to obtain geometric risk value, defect risk value, and pile group risk value, respectively. The comprehensive risk index is obtained by weighted summation of geometric risk value, defect risk value and pile group risk value. Risk levels are classified according to the following rules: Normal state: The overall risk index is less than the first warning threshold; Mild risk: The comprehensive risk index is between the first and second warning thresholds; High risk: The comprehensive risk index is greater than or equal to the second warning threshold; Based on the determined risk level, the corresponding early warning instruction will be triggered; if no warning level is triggered, monitoring will continue.

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