Wading rigid bridge cofferdam stability real-time monitoring method based on multi-source sensing

Abstract

The invention discloses a wading rigid bridge cofferdam stability real-time monitoring method based on multi-source sensing, and belongs to the technical field of bridge construction safety monitoring. According to the method, a structure-hydrological multi-source sensor is arranged, and displacement, strain, scouring and water flow data are collected in real time through a cofferdam top receiver, a main rib fiber grating sensor, a base osmometer, a multi-beam depth finder and a current meter; and reversely correcting cofferdam material parameters based on a digital twinborn model, dynamically calculating an anti-sliding coefficient and an anti-overturning coefficient, predicting a deformation trend in combination with an LSTM neural network, and setting first-level early warning and second-level early warning. According to the method, the problems of lagging of traditional monitoring data, limitation of single-dimensional analysis and high false alarm rate of an empirical threshold are solved, short-time instability risk identification is realized, and the false alarm rate is reduced at the flow velocity gt; accurate monitoring is kept in a 3m / s torrent environment, and the safety of deepwater construction is remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bridge construction safety monitoring, in particular to a water-involved rigid-frame bridge cofferdam stability real-time monitoring method based on multi-source sensing. BACKGROUND

[0002] Traditional cofferdam monitoring relies on periodic measurement by manual total station, which has data lag and cannot capture instantaneous instability risk; a single sensor (such as a strain gauge) cannot comprehensively reflect the stability of the cofferdam under the coupling action of multiple factors such as water flow scouring and base seepage; there is a lack of a collaborative analysis model for hydrological environment and structural response, and the early warning threshold is set empirically; GPS displacement monitoring is used without integrating stress data, and optical fiber monitoring of cofferdam strain is proposed, but the real-time correlation problem of base scouring has not been solved. SUMMARY

[0003] The purpose of the present application is to provide a water-involved rigid-frame bridge cofferdam stability real-time monitoring method based on multi-source sensing, which realizes real-time synchronous acquisition of cofferdam "structure-hydrology" parameters for the first time, shortens the lag of traditional manual monitoring from several hours to a few minutes, establishes a cofferdam finite element digital twin model that integrates real-time data, breaks through the limitations of traditional empirical threshold setting, reduces the stability evaluation error, and solves the problems raised in the background technology.

[0004] To achieve the above purpose, the present application provides the following technical scheme:

[0005] A water-involved rigid-frame bridge cofferdam stability real-time monitoring method based on multi-source sensing, comprising:

[0006] Step one, real-time acquisition of displacement, strain and inclination data of the cofferdam by the structure monitoring unit, and real-time acquisition of cofferdam base pore water pressure, three-dimensional water flow field and base topography change data by the hydrological monitoring unit;

[0007] Step two, parallel transmission of encrypted data by 4G / Beidou dual-mode edge gateway, built-in lightweight Docker container supports remote algorithm update, multi-sensor time synchronization is realized through PTP protocol, and local cache mechanism is adopted to deal with network interruption;

[0008] Step three, pre-processing and timestamp alignment of heterogeneous sensor data, inverse correction of cofferdam material parameters based on real-time strain data, calculation of anti-slide stability coefficient Ks and anti-overturning stability coefficient Kt, and prediction of future deformation;

[0009] Step four, triggering of graded early warning and linkage control measures according to the threshold values of displacement, stress, base scouring depth or stability coefficient.

[0010] Preferably, the structure monitoring unit is configured as:

[0011] High-precision GNSS receivers with IP68 waterproof housing are installed at the four corners of the cofferdam top, with a sampling frequency of 10 Hz, and are fixed with magnetic bases and waterproof quick-release brackets;

[0012] Fiber Bragg grating sensors are spirally wrapped at the main ribs of the cofferdam, with a spacing of 0.5 m ± 0.05 m, connected to a wavelength demodulator to monitor micro-strain, and the sensor surface is coated with a 0.2 mm polyurethane waterproof layer;

[0013] A tiltmeter with a range of ±10° and an accuracy of 0.01° is installed at the center of the cofferdam top to compensate for GNSS displacement data.

[0014] Preferably, the hydrological monitoring unit is configured to:

[0015] A piezometer with a water-permeable stone protective sleeve is buried 0.5 m ± 0.1 m below the cofferdam foundation soil layer to monitor pore water pressure;

[0016] A 4-beam Janus configuration acoustic Doppler current profiler (ADCP) is deployed on the water-facing surface with a range of 0.01-5 m / s, outputting three-dimensional flow field data every 5 minutes;

[0017] A multi-beam depth sounder is fixed in the underwater area of the cofferdam outer edge to establish a three-dimensional model of the foundation with a scanning frequency of 200 kHz, generating a scour thermodynamic map automatically every 2 hours with an accuracy of ±2 cm.

[0018] Preferably, in the dynamic stability calculation:

[0019] The formula for calculating the anti-slide stability coefficient Ks is:

[0020]

[0021] Where μ is the foundation friction coefficient, ΣN i is the total vertical force, F 水流 is the flow thrust monitored by ADCP, P 土压力 is the soil pressure monitored by the piezometer;

[0022]

[0023] Where Σ(W i × d i ) is the total anti-overturning moment, h is the flow thrust action height, h p is the soil pressure action height.

[0024] Preferably, the data preprocessing includes:

[0025] Sensor failure data is removed using the 3σ criterion;

[0026] The heterogeneous data of GNSS, FBG and ADCP are unified and aligned to the same timestamp.

[0027] Preferably, the 4G / Beidou dual-mode edge gateway of the transmission layer automatically switches the transmission mode when the network is interrupted, and encrypts the transmission data through the MQTT protocol.

[0028] Preferably, the dynamic stability calculation further comprises:

[0029] Based on real-time strain data, the elastic modulus E and Poisson's ratio mu of the cofferdam material are inversely corrected.

[0030] Input displacement / stress time series data, and output 15-minute deformation prediction.

[0031] Preferably, the trigger condition and measure of the hierarchical early warning response comprise:

[0032] First-level warning: when the displacement exceeds 50% of the design value or the stress exceeds 70% of the allowable value, trigger the LED screen warning, APP push log and start the standby water pump group.

[0033] Second-level warning: when the base scouring depth reaches 1 / 3 of the cofferdam depth or Ks<1.5, the BIM system is suspended and the cofferdam support system is started.

[0034] Compared with the prior art, the beneficial effects of the present application are:

[0035] 1、The present application captures the local strain of the main rib of the steel cofferdam by spirally winding the fiber Bragg grating sensor, realizes millimeter-level displacement monitoring in combination with the waterproof GNSS receiver and the inclinometer at the four corners of the cofferdam, embeds the osmometer in the base and deploys the multi-beam depth finder and the acoustic Doppler current profiler, forms a full-dimensional sensing system covering structural deformation, base scouring and water flow impact force, realizes real-time synchronous acquisition of "structure-hydrology" parameters of the cofferdam, shortens the hysteresis of traditional manual monitoring from several hours to 5 minutes, and especially solves the defect that a single sensor cannot reflect the multi-factor coupling effect in a rapid flow environment.

[0036] 2、The present application adapts to the actual state of the structure by inversely correcting the material parameters, and innovates a double-coefficient dynamic calculation method: the anti-sliding coefficient comprehensively considers the base friction resistance, water flow thrust and soil pressure, the anti-overturning coefficient considers the self-weight restoring moment and overturning moment, and the future 15-minute deformation trend is predicted in combination with the LSTM neural network, which breaks through the limitation of traditional empirical threshold setting and reduces the stability evaluation error.

[0037] 3、The early warning information in the application is directly pushed to the LED screen and mobile terminal APP at the construction site, and is automatically associated with the construction equipment, so that the risk disposal time is compressed to the construction process gap, and the instability accident rate of the deep water cofferdam is significantly reduced; and the data continuity and timeliness can still be ensured in the deep water area with unstable network. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 It is a system architecture diagram of the application;

[0039] Figure 2 It is a cofferdam stability fusion calculation flowchart of the application;

[0040] Figure 3 It is a cofferdam sensor layout profile view of the application;

[0041] Figure 4 It is a cofferdam sensor layout plan view of the application.

[0042] In the figure: 111, GNSS receiver; 112, inclinometer; 121, FBG sensor chain; 122, flowmeter; 123, multi-beam echo sounder; 124, scour monitoring line; 125, osmometer; 21, edge gateway; 22, time synchronization module; 31, cloud platform; 32, early warning terminal. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0044] To solve the problems of inaccurate data and not timely and not comprehensive monitoring feedback in the existing traditional cofferdam construction, please refer to Figures 1-4 The embodiment provides the following technical solutions:

[0045] A real-time monitoring method for cofferdam stability of a wading rigid frame bridge based on multi-source sensing, comprising:

[0046] Step one, real-time acquisition of displacement, strain and inclination data of the cofferdam through the structure monitoring unit, and real-time acquisition of cofferdam base pore water pressure, three-dimensional water flow field and base topography change data through the hydrological monitoring unit;

[0047] Step two, parallel transmission of encrypted data by using the 4G / Beidou dual-mode edge gateway 21, built-in lightweight Docker container supports remote algorithm update, multi-sensor time synchronization is realized through PTP protocol, and a local cache mechanism is adopted to deal with network interruption;

[0048] Step three, pre-processing and timestamp alignment of heterogeneous sensor data, inverse correction of cofferdam material parameters based on real-time strain data, calculation of anti-sliding stability coefficient Ks and anti-overturning stability coefficient Kt, and prediction of future deformation;

[0049] Step four, triggering of graded early warning and linkage control measures according to the threshold values of displacement, stress, base scour depth or stability coefficient.

[0050] The sensing layer includes a structure monitoring unit and a hydrological monitoring unit.

[0051] The structure monitoring unit is configured as:

[0052] A high-precision GNSS receiver 111 is installed at the top of the cofferdam, which has an IP68 waterproof shell, a sampling frequency of 10 Hz, and real-time monitoring of millimeter-level displacement; a high-strength magnetic base and a waterproof quick-release bracket are used to ensure stable installation of the equipment in an environment with a flow rate of >3 m / s, and the GNSS receiver 111 is configured with a main power supply and a solar backup dual-battery hot standby system to ensure continuous monitoring;

[0053] Optical fiber Bragg sensors FBG are welded at the main ribs of the cofferdam and are arranged in a spiral along the main ribs of the steel cofferdam with a spacing of 0.5 m±0.05 m, connected to a wavelength demodulator to capture local strain, and the sensor surface is coated with a 0.2 mm polyurethane waterproof layer, and the wavelength demodulator monitors micro-strain in real time;

[0054] An inclinometer 112 is added at the center of the top of the cofferdam to monitor changes in inclination, with a range of ±10° and an accuracy of 0.01°, and is used to compensate for GNSS displacement data.

[0055] The hydrological monitoring unit is configured as:

[0056] A piezometer 125 is buried in the cofferdam foundation soil layer at a depth of 0.5 m±0.1 m below the foundation to monitor pore water pressure, and a water-permeable stone protection sleeve is used to prevent sediment from clogging, and a layered backfill compaction process is used to ensure measurement accuracy;

[0057] An acoustic Doppler current profiler (ADCP) is deployed on the water-facing surface, which uses a 4-beam Janus configuration with a range of 0.01-5 m / s and outputs three-dimensional flow field data every 5 minutes;

[0058] A multi-beam depth sounder 123 is fixed to the underwater area outside the cofferdam, which scans the foundation terrain with a scanning frequency of 200 kHz, establishes a three-dimensional model of the foundation, and establishes a scour monitoring line 124, which automatically compares the terrain changes every 2 hours to generate a scour heat map with an accuracy of ±2 cm.

[0059] The transmission layer is configured as:

[0060] Adopting 4G / Beidou dual-mode edge gateway 21 for parallel transmission, automatically switching to Beidou to send key data when 4G is interrupted, supporting MQTT protocol transmission of encrypted data; The gateway has a built-in lightweight Docker container, which can remotely update the analysis algorithm without on-site maintenance;

[0061] Built-in local cache mechanism to cope with network interruption, multi-sensor time synchronization through PTP protocol.

[0062] The dynamic stability calculation process includes:

[0063] I. Data preprocessing

[0064] Using 3σ criterion to eliminate invalid sensor data;

[0065] Aligning heterogeneous data such as GNSS, FBG, and ADCP to the same timestamp.

[0066] II. Core model operation

[0067] Updating the digital twin model, inversely correcting the cofferdam material parameters according to real-time strain data, including elastic modulus E and Poisson's ratio μ;

[0068] Calculate the stability coefficient:

[0069]

[0070] Where, K S Evaluate the cofferdam's ability to resist sliding instability;

[0071] μ is the friction coefficient, representing the friction characteristics of the cofferdam foundation material, determined by laboratory tests or field data, the larger the value, the stronger the anti-sliding ability;

[0072] ΣN i is the total vertical force, including the total weight of the cofferdam, construction load, etc., monitored in real time by GNSS displacement terminal and inclinometer 112;

[0073] F 水流 is the water flow thrust, referring to the impact force of water flow on the cofferdam water surface, monitored by acoustic Doppler current profiler, the value is affected by flow rate, water depth and cofferdam shape;

[0074] P 土压力 refers to the horizontal pressure exerted by the surrounding soil on the cofferdam, measured in real time by the array of osmotic pressure meters 125 to more comprehensively reflect the stability of the foundation.

[0075]

[0076] Where, K t Evaluate the cofferdam's ability to resist overturning instability; Σ(W i×d i ) is the total sum of anti-overturning moment, i.e. the product of the weight of the cofferdam W i and its lever d i , the weight is monitored by structural sensors, and the lever is the distance from the center of gravity to the overturning point; h is the height of the water flow thrust action point from the base, calculated from ADCP data combined with the cofferdam geometric model; P is the earth pressure, h p is the height of the earth pressure action point from the base, determined by the location of the piezometer 125 and the cofferdam profile.

[0077] Input displacement / stress time series data, output deformation in the next 15 minutes.

[0078] Hierarchical early warning response mechanism:

[0079] The triggering condition for the first level of early warning (yellow) is that the displacement exceeds 50% of the design value or the stress exceeds 70% of the allowable value, and the response measures include but are not limited to LED screen flashing warning and APP push log, and automatically starting the standby water pump set;

[0080] The triggering condition for the second level of early warning (red) is that the base scouring depth reaches 1 / 3 of the cofferdam burial depth or Ks<1.5, and the response measures include but are not limited to suspending construction through the linkage BIM system, starting reinforcement, and increasing pressure through the linkage cofferdam support system.

[0081] Working principle: First, deploy a multi-source sensor network at key positions of the cofferdam: real-time monitoring of millimeter-level displacement through waterproof GNSS receivers 111 at the four corners of the cofferdam top, capture local micro-strain through spiral-wound fiber Bragg grating sensors at the main ribs, measure pore water pressure through the base piezometer 125, and obtain three-dimensional water flow field data using acoustic Doppler current profiler. The multi-beam depth sounder 123 generates a base scouring thermal map every 2 hours. These heterogeneous sensor data are transmitted through a 4G / Beidou dual-mode edge gateway 21, millisecond-level time synchronization is achieved through PTP protocol, and local caching is enabled in case of network interruption to ensure continuity.

[0082] After transmission to the analysis layer, the system performs dynamic stability evaluation: first, clean up abnormal data using the 3σ rule, align displacement, strain, hydrological and other heterogeneous information to a unified time axis. Based on real-time strain data, the elastic modulus E and Poisson's ratio μ of the cofferdam material are corrected in reverse, and the finite element digital twin model is updated. The stability is evaluated through double coefficient fusion calculation - the anti-sliding coefficient integrates the base friction coefficient μ, the total vertical load ΣNi and the water flow thrust Fwater and the earth pressure P, and the anti-overturning coefficient is the ratio of the weight restoring moment Σ(Wi×di) to the overturning moment. At the same time, the time series data are input into the LSTM neural network to predict the deformation trend in the next 15 minutes.

[0083] The hierarchical response is triggered when the calculated indicators exceed the threshold value: if the displacement exceeds the design value by 50% or the stress exceeds 70%, the first level of early warning is activated, the LED screen flashes and the APP alarm is pushed, and the standby water pump group is activated synchronously; if the base scouring depth reaches 1 / 3 of the buried depth or Ks<1.5 is detected, the second level of early warning is upgraded, the construction plan in the BIM system is automatically suspended, and the cofferdam support structure is pressurized.

[0084] It should be noted that the relational terms herein such as first and second and the like are used solely to distinguish one entity or action from another, without necessarily requiring or implying any such actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0085] While embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, changes, and variations can be made in such embodiments without departing from the spirit and scope of the present application, which is defined by the appended claims.

Claims

1. A method for real-time monitoring of the stability of cofferdams for wading rigid frame bridges based on multi-source sensing, characterized in that, include: Step 1: Real-time data on displacement, strain, and tilt of the cofferdam are obtained through the structural monitoring unit, and real-time data on pore water pressure, three-dimensional flow field, and base topography changes of the cofferdam are obtained through the hydrological monitoring unit. Step 2: Use the 4G / BeiDou dual-mode edge gateway (21) to transmit encrypted data in parallel, build a lightweight Docker container to support remote algorithm updates, realize multi-sensor time synchronization through the PTP protocol, and adopt a local caching mechanism to deal with network interruptions; Step 3: Preprocess and timestamp-align the heterogeneous sensor data, reverse correct the cofferdam material parameters based on real-time strain data, calculate the anti-sliding stability coefficient Ks and the anti-overturning stability coefficient Kt, and predict the future deformation. Step 4: Trigger graded early warning and linkage control measures based on thresholds for displacement, stress, base scour depth, or stability coefficient.

2. The method for real-time monitoring of the stability of a cofferdam for a water-crossing rigid frame bridge based on multi-source sensing, as described in claim 1, is characterized in that... The structural monitoring unit is configured as follows: High-precision GNSS receivers (111) with IP68 waterproof housings are installed at the four corners of the top of the cofferdam. The sampling frequency is 10Hz, and they are fixed with magnetic bases and waterproof quick-release brackets. Fiber optic grating sensors are spirally wound and installed at the main ribs of the cofferdam, with a spacing of 0.5m ± 0.05m. They are connected to a wavelength demodulator to monitor micro-strain. The sensor surface is coated with a 0.2mm polyurethane waterproof layer. An inclinometer (112) with a range of ±10° and an accuracy of 0.01° is installed at the center of the top of the cofferdam to compensate for GNSS displacement data.

3. The method for real-time monitoring of the stability of a cofferdam for a water-crossing rigid frame bridge based on multi-source sensing according to claim 2, characterized in that, The hydrological monitoring unit is configured as follows: A piezometer (125) with a permeable stone protective sleeve was installed 0.5m±0.1m below the foundation soil layer of the cofferdam to monitor the pore water pressure; A 4-beam Janus acoustic Doppler current profiler (ADCP) with a range of 0.01–5 m / s was deployed on the water-facing side, outputting three-dimensional water flow field data every 5 minutes. A multibeam echo sounder (123) was fixed in the underwater area at the outer edge of the cofferdam. A three-dimensional model of the base was established with a scanning frequency of 200kHz. A scour thermal map was automatically generated every 2 hours with an accuracy of ±2cm.

4. The method for real-time monitoring of the stability of a cofferdam for a water-crossing rigid frame bridge based on multi-source sensing according to claim 3, characterized in that, In the dynamic stability calculation: The formula for calculating the anti-skid stability coefficient Ks is: Where μ is the base friction coefficient, ∑N i For the total vertical force, F 水流 For the water flow thrust monitored by ADCP, P 土压力 Earth pressure monitored by piezometer (125); Among them, Σ(W i ×d i ) represents the total anti-overturning moment, and h represents the height of the water flow thrust. p The height at which earth pressure acts.

5. The method for real-time monitoring of the stability of a cofferdam for a water-crossing rigid frame bridge based on multi-source sensing according to claim 4, characterized in that, The data preprocessing includes: Sensor failure data were removed using the 3σ criterion. Align heterogeneous data from GNSS, FBG, and ADCP to the same timestamp.

6. The method for real-time monitoring of the stability of a cofferdam for a water-crossing rigid frame bridge based on multi-source sensing, as described in claim 5, is characterized in that... The 4G / BeiDou dual-mode edge gateway (21) of the transmission layer automatically switches the transmission mode when the network is interrupted and transmits data in encrypted form via the MQTT protocol.

7. The method for real-time monitoring of the stability of a cofferdam for a water-crossing rigid frame bridge based on multi-source sensing according to claim 6, characterized in that, The dynamic stability calculation also includes: The elastic modulus E and Poisson's ratio μ of the cofferdam material are corrected in reverse based on real-time strain data. Input displacement / stress time series data, and output the predicted deformation amount for the next 15 minutes.

8. The method for real-time monitoring of the stability of a cofferdam for a water-crossing rigid frame bridge based on multi-source sensing, as described in claim 7, is characterized in that... The triggering conditions and measures for the tiered early warning response include: Level 1 warning: When the displacement exceeds the design value by 50% or the stress exceeds the allowable value by 70%, the LED screen warning will be triggered, the APP will push the log, and the backup water pump group will be started. Level 2 warning: When the scour depth of the foundation reaches 1 / 3 of the cofferdam's burial depth or Ks < 1.5, the BIM system will suspend construction and start the cofferdam support system for pressure reinforcement.

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