Segmental beam cement joint curing degree monitoring and construction method, equipment and storage medium

Abstract

The segmental beam glue joint curing degree monitoring and construction method, equipment and storage medium belong to the technical field of bridge intelligent construction. The method comprises the following steps: embedding a flexible piezoelectric sensing array on a matching surface of a segmental beam and collecting a no-load baseline; transmitting an excitation signal at a preset time interval after gluing, and extracting acoustic characteristic parameters; through a mapping model of the curing degree of epoxy resin glue and the acoustic characteristics established in advance, the curing degree of each measuring point, the average curing degree of the glue joint and the spatial distribution uniformity are calculated inversely; based on the curing degree and the change rate, combined with the three-level decision logic, the control instructions of the subsequent construction process are output. The present application realizes real-time in-situ nondestructive monitoring of the curing degree of the glue joint and automatic decision of the construction process, and is suitable for glue splicing construction of segmental precast assembled bridges.

Description

Technical Field

[0001] This invention relates to the field of intelligent bridge construction and construction monitoring technology, specifically to methods, equipment, and storage media for monitoring and constructing the curing degree of adhesive joints in segmental beams. Background Technology

[0002] Segmental prefabrication and assembly technology is one of the core technologies for achieving rapid and green bridge construction. This technology involves prefabricating bridge beams into segments at the beam yard, and then transporting each segment to a bridge erecting machine for assembly. The high-performance epoxy resin adhesive (such as K-801) applied between the segments is crucial for ensuring tight joints, transferring shear force, and forming a cohesive structural structure. The degree of curing of the adhesive joints directly determines the safety of subsequent temporary prestressing tensioning, permanent prestressing construction, and system conversion, as well as the overall quality of the completed bridge's alignment.

[0003] Currently, the judgment of the curing status of adhesive joints during on-site construction mainly relies on experience (such as finger touch and estimation of curing time) or post-construction sampling inspection, which has the following technical defects: Information lag and blind spots: It is impossible to know the actual curing process of the adhesive layer inside the joint in real time, especially the uneven curing in multi-layer or complex environments, which leads to the lack of accurate judgment of the curing status of the adhesive layer by the construction personnel.

[0004] High decision-making risks: Conducting large-scale tensioning or moving the bridge erecting machine before the adhesive reaches the designed strength (e.g., ≥20MPa compressive strength in 12 hours, ≥60MPa in 24 hours) can lead to structural slippage, deformation, or even instability. Due to the lack of real-time monitoring data, construction decisions often rely on experience-based judgment, posing significant safety hazards.

[0005] Lack of data closed loop: The data of the curing process is not linked with the subsequent grouting and tensioning processes, making it impossible to achieve dynamic optimization of construction parameters. Construction quality control is still stuck in the extensive mode of "result detection". Summary of the Invention

[0006] This invention aims to address the problems of insufficient monitoring methods for the curing state of epoxy resin adhesive joints in the existing segmental beam gluing construction, delayed information acquisition, and reliance on experience for construction decisions. It provides a method, equipment, and storage medium for monitoring and constructing segmental beam gluing joint curing.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: The following steps are performed using computer equipment to monitor the curing degree of adhesive joints in segmental beams and to guide construction. S1. A flexible piezoelectric sensor array is pre-embedded on the matching surface of the segmental beam, and an unloaded test is performed before applying adhesive. The unloaded baseline waveform and phase spectrum are established through the data acquisition unit. The flexible piezoelectric sensor array is configured as either "one excitation and one reception" or "one excitation and multiple reception". S2. After applying adhesive and temporary prestress, an excitation signal is sent to the flexible piezoelectric sensing array at a preset time interval, and the processor processes and extracts acoustic feature parameters in real time. The excitation signal is a sinusoidal sweep frequency signal with a sweep frequency range of 20kHz to 200kHz, a center frequency of 150kHz, and a signal cycle of 5 to 10 cycles. S3. Based on acoustic characteristic parameters, the curing degree of each measuring point is calculated by inverting the mapping relationship between the curing degree of epoxy resin adhesive and acoustic characteristics, and the average curing degree of the adhesive joint and its spatial distribution uniformity are calculated based on the curing degree of each measuring point. S4. Based on the degree of curing and the rate of change, combined with the preset three-level decision logic, output control instructions for subsequent construction procedures.

[0008] Further preferred embodiment: the flexible piezoelectric sensing array is packaged from multiple flexible piezoelectric ceramic sensors and piezoelectric detectors, prefabricated into a thin sheet with a thickness of ≤1mm, and each set of the flexible piezoelectric sensing array is configured with 2 transmitting chips and 4 receiving chips; The segmental beam matching surface is provided with preset positions, including the four corners and the mid-span position of the segmental beam matching surface.

[0009] Further preferred description, in S2: The preset time interval is 5 minutes; The acoustic characteristic parameters include at least one or more of the following: amplitude attenuation rate, longitudinal wave velocity, dominant frequency offset, and phase change.

[0010] Specifically, the longitudinal wave velocity is calculated according to the following formula:

[0011] in, for The longitudinal wave velocity at time t, The propagation distance between the transmitting and receiving sensors. It is the difference between the arrival time of the first wave of the received signal and the transmission time of the excitation signal.

[0012] The amplitude attenuation rate is calculated according to the following formula:

[0013] in, for The amplitude decay rate at time t, for Peak-to-peak value of the received signal at any given time. This is the reference peak-to-peak value of the received signal under baseline acquisition conditions.

[0014] The frequency offset is calculated using the following formula:

[0015] in, for The frequency offset at any given time. The frequency corresponding to the maximum amplitude of the spectrum of the currently received signal after Fast Fourier Transform. The center frequency of the excitation signal.

[0016] Phase change is calculated using the following formula:

[0017] in, for Phase change at time, The center frequency of the excitation signal, This represents the time delay corresponding to the peak value of the cross-correlation function between the currently received signal and the baseline signal.

[0018] Further preferred description, in S3: The mapping relationship is established in advance in the following way: for the epoxy resin adhesive used in construction, acoustic characteristic parameters and corresponding true values ​​of curing degree are collected at different curing times under laboratory conditions, and a mapping model between the curing degree of the epoxy resin adhesive and the acoustic characteristic parameters is established. The true value of curing degree is determined by differential scanning calorimetry. The mapping model is a weighted fusion model, which is established in the following way: The various acoustic feature parameters are normalized according to the following formula:

[0019] in, For the first The sub-solidification degree is obtained after normalizing the acoustic feature parameters. For the first Each acoustic characteristic parameter in The measured value at time [time]. and These are the calibration values ​​for the corresponding acoustic characteristic parameters in the fully uncured and fully cured states of the epoxy resin adhesive, respectively. The current degree of curing is obtained by weighted fusion according to the following formula. :

[0020] in, This represents the total number of acoustic characteristic parameters. For the first The weight coefficients of each feature parameter, and .

[0021] Further preferred embodiment: the spatial distribution uniformity is determined by a uniformity coefficient. Characterization:

[0022]

[0023]

[0024] in, This represents the average degree of curing at each measuring point. The uniformity coefficient of curing degree at each measuring point. For the first Each measuring point is at The degree of solidification at any given moment This represents the total number of measurement points.

[0025] Further, the three-level decision-making logic includes: Level 1 decision: When the average value of the current degree of solidification is greater than or equal to the first preset threshold, the uniformity coefficient is greater than or equal to the first uniformity threshold, and the rate of change is less than the first rate of change threshold, an instruction is generated to allow the removal of the temporary hangers and the transfer of the beam's self-weight to the temporary support sandbox. Secondary decision: When the average value of the current degree of curing is greater than or equal to the second preset threshold, the uniformity coefficient is greater than or equal to the second uniformity threshold, and the calculated compressive strength is greater than or equal to the design strength value, an instruction to authorize the start of the intelligent tensioning system to perform tensioning of the simply supported steel strand is generated; Level 3 decision: When the average value of the current degree of curing is greater than or equal to the third preset threshold, the uniformity coefficient is greater than or equal to the third uniformity threshold, and the calculated compressive strength is greater than or equal to the design strength value, the command for tensioning the entire steel bundle and grouting the duct is generated. Wherein, the first preset threshold is less than the second preset threshold, and the second preset threshold is less than the third preset threshold.

[0026] The specific formula for calculating compressive strength is as follows:

[0027] in, The curing degree-compressive strength mapping function calibrated in the laboratory (usually a polynomial fit or piecewise linear interpolation).

[0028] Further preferred embodiment: the first preset threshold is 60%, the second preset threshold is 85%, and the third preset threshold is 95%. The first uniformity threshold is 0.85, the second uniformity threshold is 0.88, and the third uniformity threshold is 0.92; The first change rate threshold is 2% / hour, and the change rate is less than the first change rate threshold in three consecutive monitoring tests.

[0029] Further optimization instructions also include: All monitoring data, decision logs, and construction execution results are uploaded to the cloud to generate a full-cycle quality archive for each adhesive joint, covering the curing, tensioning, and grouting processes.

[0030] In another aspect, the present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0031] In another aspect, the present invention also discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method described above.

[0032] As can be seen from the above technical solution, the beneficial effects are as follows: (1) This invention applies a flexible piezoelectric sensor array to the construction of adhesive joints in bridge segment beams, realizing in-situ, real-time, and non-destructive monitoring of the curing degree of the adhesive layer in narrow and irregular spaces. The sensor adopts a flexible and ultra-thin design, which can be directly deployed in the shear keyway of the existing segment beam without changing the original construction process or affecting the force transmission performance of the adhesive layer; (2) This invention forms an automatic closed loop of “monitoring-evaluation-decision-execution”, directly controlling the start time of subsequent tensioning and grouting processes, completely changing the extensive mode that relies on manual experience judgment, and significantly reducing the risk of construction decision-making; (3) This invention abandons single-parameter monitoring and adopts multi-dimensional acoustic characteristics such as wave velocity, amplitude, frequency, and phase to fuse and invert the curing degree, which greatly improves the robustness and accuracy of monitoring in complex construction environments. Through the layout of multiple measuring points and the calculation of uniformity coefficient, the quantitative evaluation of the spatial distribution uniformity of curing degree of the entire cross section of the adhesive joint is realized. Attached Figure Description

[0033] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0035] Example 1 like Figure 1As shown in the figure, the method for monitoring and constructing the curing degree of the adhesive joint of the segmental beam described in this embodiment is implemented by computer equipment in the following steps. S1. A flexible piezoelectric sensor array is pre-embedded on the matching surface of the segmental beam, and an unloaded test is conducted before applying adhesive. The unloaded baseline waveform and phase spectrum are established through the data acquisition and processing unit. S2. After applying adhesive and temporary prestress, excitation signals are sent to the flexible piezoelectric sensing array at preset time intervals, and acoustic feature parameters are extracted in real time by the data acquisition and processing unit. S3. Based on acoustic characteristic parameters, the curing degree of each measuring point is calculated by inverting the mapping relationship between the curing degree of epoxy resin adhesive and acoustic characteristics, and the average curing degree of the adhesive joint and its spatial distribution uniformity are calculated based on the curing degree of each measuring point. S4. Based on the degree of curing and the rate of change, combined with the preset three-level decision logic, output control instructions for subsequent construction procedures.

[0036] It should be noted that the data acquisition and processing unit includes a signal generator, a signal acquisition instrument, and a processor, which are used to send excitation signals to the flexible piezoelectric sensing array at preset time intervals, receive and process response signals, and extract acoustic feature parameters.

[0037] The following provides a detailed explanation of each step: Step 1: Pre-embedding and integration of sensor array.

[0038] During segmental prefabrication at the beam yard, shallow grooves (1.5mm deep, 20mm wide, and 50mm long) are pre-drilled on the matching surfaces at six locations: the four corners of each segment and the top and bottom of the mid-span. A customized flexible piezoelectric sensor array is embedded in the groove and secured with temporary sealant to ensure a flush surface. Each flexible piezoelectric sensor array consists of two transmitting wafers and four receiving wafers, prefabricated into a thin sheet with a thickness ≤1mm. The correspondence between the ID of each sensor and the beam segment number and spatial coordinates is recorded to establish a three-dimensional sensor network topology.

[0039] Step 2: Baseline data acquisition and real-time monitoring.

[0040] After the beam transport vehicle feeds the beam into position, the bridge erecting machine lifts the beam segment to the assembly position. Before the adhesive application process, the sensor data line is connected to perform an "air baseline" scan, which collects the air baseline signal of the matching surface of the two segments in the air state before adhesive application and the dry contact baseline signal in the dry contact state before the application of temporary prestress, and establishes the no-load baseline waveform and phase spectrum.

[0041] Then, apply K-801 epoxy resin adhesive (A:B=3:1) according to the construction method requirements and apply temporary prestress. At this time, immediately start the real-time monitoring system. The data acquisition unit automatically transmits a sinusoidal sweep signal with a center frequency of 150kHz every 5 minutes (sweep range from 20kHz to 200kHz, signal cycle number from 5 to 10 cycles), and receives the response signal after penetrating the adhesive layer from the receiving sensor. The processor extracts key acoustic characteristic parameters in real time, including but not limited to amplitude attenuation rate, longitudinal wave velocity, and dominant frequency offset.

[0042] Specifically, the longitudinal wave velocity is calculated according to the following formula:

[0043] in, for The longitudinal wave velocity at time t, The propagation distance between the transmitting and receiving sensors. It is the difference between the arrival time of the first wave of the received signal and the transmission time of the excitation signal.

[0044] The amplitude attenuation rate is calculated according to the following formula:

[0045] in, for The amplitude decay rate at time t, for Peak-to-peak value of the received signal at any given time. This is the reference peak-to-peak value of the received signal under baseline acquisition conditions.

[0046] The frequency offset is calculated using the following formula:

[0047] in, for The frequency offset at any given time. The frequency corresponding to the maximum amplitude of the spectrum of the currently received signal after Fast Fourier Transform. The center frequency of the excitation signal.

[0048] Phase change is calculated using the following formula:

[0049] in, for Phase change at time, The center frequency of the excitation signal, This represents the time delay corresponding to the peak value of the cross-correlation function between the currently received signal and the baseline signal.

[0050] Step 3: Dynamic inversion calculation of curing degree.

[0051] (I) Model Establishment Before construction, take K-801 epoxy resin adhesive (A:B=3:1) from the construction site and prepare standard test specimens under standard laboratory curing conditions (temperature 23±2℃, humidity 50±5%). Simultaneously conduct the following two tests: Acoustic testing: Using a flexible piezoelectric sensor array of the same specifications as on-site, and a sinusoidal sweep signal with a center frequency of 150kHz as excitation, acoustic response signals were collected at different curing times (every 5 minutes from the time of adhesive application), and longitudinal wave velocity was extracted. Amplitude attenuation rate , frequency offset Phase change Four characteristic parameters.

[0052] Curing degree test: The true value of the curing degree of the specimens at the same time was determined by differential scanning calorimetry. .

[0053] A mapping model is established using four acoustic feature parameters as input and DSC solidification degree as output. In this embodiment, a weighted fusion model is adopted: Normalization of each feature parameter:

[0054]

[0055]

[0056]

[0057] in, , , , These are the calibration values ​​for each acoustic characteristic parameter in the completely uncured state of the epoxy resin adhesive; , , , These are the calibration values ​​for each acoustic characteristic parameter under the fully cured state of the epoxy resin adhesive. Each calibration value was obtained by testing standard specimens of the same batch of epoxy resin adhesive under standard laboratory curing conditions—the calibration value for the completely uncured state was obtained immediately after application of the adhesive, and the calibration value for the fully cured state was obtained after sufficient curing until the degree of cure no longer changed. The completely uncured state and the fully cured state were confirmed as 0% and 100% curing degree, respectively, by differential scanning calorimetry.

[0058] Weighted fusion: The current degree of curing is obtained by fusing the four normalized sub-degrees of curing using the following formula:

[0059] in, Each weighting coefficient is minimized. Sure.

[0060] Taking K-801 epoxy resin adhesive as an example, after laboratory calibration, the following weighting coefficients can be used as a reference value: , , , In actual use, the calibration results of the actual adhesive sample on site shall prevail.

[0061] (II) On-site inversion calculation After real-time monitoring is initiated, the system collects the acoustic response signals of each measuring point every 5 minutes and extracts four acoustic feature parameters. Taking 6 measuring points as an example, the acoustic feature parameters of each measuring point at the current moment are input into the mapping model, and the solidification degree of each measuring point is output: , , , , ,

[0062] Assuming that the degree of curing at 6 measuring points is measured 4 hours after construction, and the results are 68%, 72%, 71%, 73%, 69%, and 70%, calculate the average degree of curing using the following formula:

[0063] The uniformity coefficient is calculated using the following formula:

[0064]

[0065] In this embodiment, The curing degree was judged to have excellent spatial uniformity, and the adhesive layer was in good curing condition.

[0066] Step 4: Intelligent decision execution.

[0067] The intelligent decision-making unit executes a three-level decision-making logic based on the inverted degree of solidification and rate of change: Level 1 Decision (Temporary Tension Lock): When , and rate of change When the condition is met for three consecutive monitoring cycles per hour, it is determined that the temporary suspension rods can be removed, and the weight of the beam can be transferred to the temporary support sandbox. In this embodiment, 4 hours after construction, , If the first-level decision-making conditions are met, the system issues an instruction allowing the removal of the suspension rods in this span and the lowering of the beam into the sand box.

[0068] Secondary decision (simply supported steel strand tensioning): When , And calculate the compressive strength When the load holding time is ≥10 hours (design value × 1.1 safety factor), the system automatically authorizes and starts the intelligent tensioning system to tension the simply supported steel strands in this span. After 12 hours, the system monitors three times consecutively. When the strength reaches 88%-90% and the calculated compressive strength is >25MPa (design value 20MPa×1.1=22MPa), the system automatically authorizes the intelligent tensioning equipment and sends the "side span first span steel strand tensioning order" to start tensioning F2, F4 and other steel strands.

[0069] Level 3 Decision-Making (Integrated Permanent Tensioning and Grouting): When , And calculate the compressive strength (Design value 60MPa × 1.1 = 66MPa for 24 hours), when the load holding time is ≥20 hours, and the concrete strength of the wet joint at the pier top meets the standard, the system automatically generates instructions for tensioning the entire steel strand and grouting the ducts, and transmits them to the intelligent grouting trolley and tensioning equipment. After the entire connection is completed and the strength of the wet joint at the pier top meets the standard, the system monitors the joint. The system automatically generates and issues tensioning and grouting instructions for the entire steel strand T4-1 to the intelligent grouting trolley.

[0070] Step 5: Data feedback and quality traceability.

[0071] All monitoring data, decision logs, and construction execution results are uploaded to the cloud in real time, generating a full-cycle quality file for each adhesive joint, covering the entire process from curing to tensioning to grouting. This file is used for subsequent alignment adjustments and quality traceability. After construction is completed, the curing history curve of the joint, the decision time for each stage, and the tensioning and grouting parameters are automatically generated into a QR code, which is affixed to the side of the beam for scanning and viewing during the operation and maintenance period.

[0072] Example 2 The difference between this embodiment and Embodiment 1 is that the mapping model uses a neural network model instead of a weighted fusion model.

[0073] Using four acoustic characteristic parameters (longitudinal wave velocity) Amplitude attenuation rate , frequency offset Phase change () is the input, degree of curing To output the model, a backpropagation (BP) neural network is constructed. The network structure is as follows: 4 neurons in the input layer, several neurons in the hidden layer (the optimal number is determined through trial and error or grid search), and 1 neuron in the output layer. The hidden layer uses the ReLU activation function. .

[0074] True value of curing degree measured by laboratory DSC To train the labels, the backpropagation algorithm is used to minimize the loss function:

[0075] in, The total number of training samples, For the neural network to the first The predicted output for each sample, For the first The true values ​​of DSC measured solidification degree for each sample. The weights of each layer are iteratively updated using gradient descent until the loss function converges.

[0076] in, The value of the loss function. For the number of iterations, This is the preset convergence accuracy threshold.

[0077] After each segment is assembled, the network weights are fine-tuned (incremental learning) using the complete monitoring data of that segment, achieving iterative optimization through "learning while constructing". The remaining steps are the same as in Example 1.

[0078] Example 3 The difference between this embodiment and Embodiment 1 lies in the number of sensors deployed.

[0079] For construction scenarios with small spans or low monitoring accuracy requirements, four measuring points can be set at the four corners of the segmental beam matching surface, thus reducing the number of points at the top and bottom of the mid-span. The calculation formulas for average degree of cure and uniformity coefficient remain unchanged, but the uniformity judgment criteria are adjusted accordingly: For excellent uniformity, The uniformity is generally good. It has poor uniformity.

[0080] For construction scenarios with large spans or higher monitoring accuracy requirements, additional measuring points can be added at different orientations, such as the bottom and walls of the shear key groove, in addition to the six existing measuring points at the four corners, the top of the mid-span, and the bottom. This is to obtain more comprehensive spatial distribution data of the degree of curing. The remaining steps are the same as in Example 1.

[0081] And the Each measuring point at time [time] Validity determination:

[0082] Total number of valid measuring points:

[0083] When a measuring point receives three consecutive invalid signal acquisitions ( When a data point is not found, the system automatically removes the data from that measurement point and makes a decision based on the remaining valid measurement points.

[0084] Example 4 The difference between this embodiment and Embodiment 1 lies in the parameter configuration of the excitation signal.

[0085] For epoxy resin adhesive layers of different thicknesses or types, the excitation signal parameters can be adjusted adaptively. When the adhesive layer thickness is large (e.g., ≥3mm), a low-frequency mode (20kHz—80kHz) is used to excite the Lamb wave symmetric mode, which is sensitive to the overall curing degree of the adhesive layer; when the adhesive layer thickness is small (e.g., <3mm), a high-frequency mode (80kHz—200kHz) is used to excite the antisymmetric mode, which is sensitive to the curing state of the adhesive layer surface and interface.

[0086] Meanwhile, the system has an adaptive frequency adjustment function: it automatically adjusts the excitation frequency according to the real-time signal-to-noise ratio to avoid interference frequency bands caused by environmental noise such as construction machinery vibration. The number of signal cycles is set to 5-10 cycles to achieve a balance between frequency resolution and time domain resolution. The remaining steps are the same as in Example 1.

[0087] In another aspect, the present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method described above.

[0088] In another aspect, the present invention also discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method described above.

[0089] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the above-described methods for monitoring and constructing the curing degree of adhesive joints in segmental beams.

[0090] It is understood that the systems, devices, and storage media provided in the embodiments of the present invention correspond to the methods provided in the embodiments of the present invention, and the explanations, examples, and beneficial effects of the relevant content can be referred to the corresponding parts of the above methods.

[0091] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0092] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0093] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0094] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring and constructing the curing degree of adhesive joints in segmental beams, characterized in that, Perform the following steps using a computer device. S1. A flexible piezoelectric sensor array is pre-embedded on the matching surface of the segmental beam, and an unloaded test is conducted before applying adhesive. The unloaded baseline waveform and phase spectrum are established through the data acquisition unit. S2. After applying adhesive and temporary prestress, excitation signals are sent to the flexible piezoelectric sensing array at preset time intervals, and the processor processes and extracts acoustic feature parameters in real time. S3. Based on acoustic characteristic parameters, the curing degree of each measuring point is calculated by inverting the mapping relationship between the curing degree of epoxy resin adhesive and acoustic characteristics, and the average curing degree of the adhesive joint and its spatial distribution uniformity are calculated based on the curing degree of each measuring point. S4. Based on the degree of curing and the rate of change, combined with the preset three-level decision logic, output control instructions for subsequent construction procedures.

2. The method for monitoring and constructing the curing degree of adhesive joints in segmental beams according to claim 1, characterized in that: The flexible piezoelectric sensing array is packaged from multiple flexible piezoelectric ceramic sensors and piezoelectric detectors, prefabricated into a thin sheet with a thickness of ≤1mm, and each set of the flexible piezoelectric sensing array is configured with 2 transmitting chips and 4 receiving chips. The segmental beam matching surface is provided with preset positions, including the four corners and the mid-span position of the segmental beam matching surface.

3. The method for monitoring and constructing the curing degree of adhesive joints in segmental beams according to claim 2, characterized in that, In S2: The preset time interval is 5 minutes; The acoustic characteristic parameters include at least one or more of the following: amplitude attenuation rate, longitudinal wave velocity, dominant frequency offset, and phase change.

4. The method for monitoring and constructing the curing degree of adhesive joints in segmental beams according to claim 3, characterized in that, In S3: The mapping relationship is established in advance in the following way: for the epoxy resin adhesive used in construction, acoustic characteristic parameters and corresponding true values ​​of curing degree are collected at different curing times under laboratory conditions, and a mapping model between the curing degree of the epoxy resin adhesive and the acoustic characteristic parameters is established. The true value of curing degree is determined by differential scanning calorimetry. The mapping model is a weighted fusion model, which is established in the following way: The various acoustic feature parameters are normalized according to the following formula: in, For the first The sub-solidification degree is obtained after normalizing the acoustic feature parameters. For the first Each acoustic characteristic parameter in The measured value at time [time]. and These are the calibration values ​​for the corresponding acoustic characteristic parameters in the fully uncured and fully cured states of the epoxy resin adhesive, respectively. The current degree of curing is obtained by weighted fusion according to the following formula. : in, This represents the total number of acoustic characteristic parameters. For the first The weight coefficients of each feature parameter, and .

5. The method for monitoring and constructing the curing degree of adhesive joints in segmental beams according to claim 4, characterized in that, The spatial distribution uniformity is measured by the uniformity coefficient. Characterization: in, This represents the average degree of curing at each measuring point. This represents the standard deviation of the curing degree at each measuring point.

6. The method for monitoring and constructing the curing degree of adhesive joints in segmental beams according to claim 5, characterized in that, The three-level decision-making logic includes: Level 1 decision: When the average value of the current degree of solidification is greater than or equal to the first preset threshold, the uniformity coefficient is greater than or equal to the first uniformity threshold, and the rate of change is less than the first rate of change threshold, an instruction is generated to allow the removal of the temporary hangers and the transfer of the beam's self-weight to the temporary support sandbox. Secondary decision: When the average value of the current degree of curing is greater than or equal to the second preset threshold, the uniformity coefficient is greater than or equal to the second uniformity threshold, and the calculated compressive strength is greater than or equal to the design strength value, an instruction to authorize the start of the intelligent tensioning system to perform tensioning of the simply supported steel strand is generated; Level 3 decision: When the average value of the current degree of curing is greater than or equal to the third preset threshold, the uniformity coefficient is greater than or equal to the third uniformity threshold, and the calculated compressive strength is greater than or equal to the design strength value, the command for tensioning the entire steel bundle and grouting the duct is generated. Wherein, the first preset threshold is less than the second preset threshold, and the second preset threshold is less than the third preset threshold.

7. The method for monitoring and constructing the curing degree of adhesive joints in segmental beams according to claim 6, characterized in that: The first preset threshold is 60%, the second preset threshold is 85%, and the third preset threshold is 95%. The first uniformity threshold is 0.85, the second uniformity threshold is 0.88, and the third uniformity threshold is 0.92; The first change rate threshold is 2% / hour, and the change rate is less than the first change rate threshold in three consecutive monitoring tests.

8. The method for monitoring and constructing the curing degree of adhesive joints in segmental beams according to claim 7, characterized in that, Also includes: All monitoring data, decision logs, and construction execution results are uploaded to the cloud to generate a full-cycle quality archive for each adhesive joint, covering the curing, tensioning, and grouting processes.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it causes the processor to perform the steps of the method as described in any one of claims 1 to 8.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the computer program is executed by the processor, it causes the processor to perform the steps of the method as described in any one of claims 1 to 8.

Images