Reinforcing and supporting construction method for one-time pouring of swivel bridge lower bearing platform

Abstract

The invention relates to the technical field of bridge engineering construction, and discloses a swivel bridge lower bearing platform one-time pouring reinforcing and supporting construction method which comprises the following steps: S1, surveying and setting out: calibrating a lower bearing platform side line and a pile position center line by adopting a total station, and marking a stay wire; s2, mounting a bottom support: cutting I-shaped steel into the bottom support, placing the bottom support in the center of the top surface of the pile head, and fixing the bottom support with a fifth-layer reinforcing steel bar of the lower bearing platform by spot welding; through welding connection of the bottom support, the stand columns, the cooling pipe supporting steel bars, the crossed inclined struts and the top I-shaped steel, a space three-dimensional supporting framework tightly combined with the steel bars in the bearing platform and the cooling pipes is formed, and the framework serves as a stiff structure and can effectively share impact load and lateral pressure during concrete pouring; the overall rigidity and stability of a supporting system are greatly improved, the risks of displacement, deformation and even instability which are likely to happen to a traditional scattered assembly support are fundamentally avoided, and the construction safety is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of bridge engineering construction technology, specifically to a reinforcement and support construction method for the one-time casting of the abutment of a rotating bridge. Background Technology

[0002] In the construction of a swing bridge, the lower abutment serves as a crucial load-bearing and rotational foundation. It is massive in volume, requires a huge volume of concrete to be poured at once, and has numerous layers of internal reinforcement and densely packed cooling water pipes. To ensure the accurate spatial positioning of the reinforcement cage and cooling pipes during pouring and to prevent deformation, a reliable internal support system is essential. Currently, traditional construction methods often use loosely assembled steel pipe supports or structural steel supports as temporary supports. These methods have the following significant drawbacks:

[0003] 1. Poor integration between the support system and the main structure: Traditional supports are often set up independently and have weak connections with the main structural components such as steel bars and cooling pipes, making it difficult to form an overall structure to share the load. Under the impact of concrete pouring and lateral pressure, displacement or deformation is likely to occur.

[0004] 2. Low installation efficiency and long construction period: The installation process of the modular bracket is complicated, requiring a lot of on-site measurement, cutting and fixing work, resulting in a long construction period and affecting the overall project progress.

[0005] 3. High safety risks: Due to the insufficient overall rigidity and stability of the support system, there is a risk of local instability or even overall collapse when bearing the load of large volume concrete, which poses a threat to construction safety.

[0006] 4. Difficulty in quality control: The lack of effective means of monitoring the construction process makes it impossible to monitor the stress state of the supporting structure in real time, making it difficult to provide timely warnings and interventions before safety hazards occur. At the same time, the flatness control of the top surface of the support relies heavily on manual experience, and the accuracy is difficult to guarantee, which may affect the construction quality of the superstructure. Summary of the Invention

[0007] The purpose of this invention is to provide a method for reinforcing and supporting the abutment of a rotating bridge by one-time casting, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for reinforcing and supporting abutments of a rotating bridge in a single pour, comprising the following steps:

[0009] S1. Surveying and setting out: Use a total station to mark the lower foundation edge line and the center line of the pile position, and mark the line.

[0010] S2. Bottom support installation: After cutting the I-beam into a bottom support, place it in the center of the top surface of the pile head and spot weld it to the fifth layer of steel reinforcement of the lower bearing platform;

[0011] S3. Erection of I-beam columns: Hoist the I-beam columns into position and install them on the fifth layer of steel mesh according to the marked position. Multiple steel bars are used to spot weld the perimeter. The bottom of the I-beam columns is fully welded to the base support, and temporary support steel bars are set on both sides.

[0012] S4. Cooling pipe support steel reinforcement installation: Cooling pipe support steel reinforcement is arranged horizontally along the cooling pipe layer and welded to the column I-beams to form a grid. One layer is set every 1m in height, for a total of 5 layers. The horizontal and vertical directions are fully welded to the column I-beams and staggered with the cooling pipe interface positions.

[0013] S5. Cross bracing installation: Cross bracing is installed at the bottom and top 1m of the I-beam of the column. The angle between the bracing and the I-beam of the column is 45-60°. In the north-south direction, the bracing is installed every other one, and in the east-west direction, the bracing is fully installed. The bracing joints are welded on both sides, and the weld length is ≥100mm.

[0014] S6. Horizontal connection of top I-beam: Set up I-beams at the top and connect them horizontally in the east-west direction. Weld steel bars to the inside of the I-beams to form a closed frame. The connection is fully welded and the weld height is ≥6mm.

[0015] As a preferred embodiment of the present invention, the base support, the upright I-beam, and the top I-beam are all made of I14 I-beams. The base support is cut from scrap I-beams and has dimensions of 300×88×140mm.

[0016] As a preferred technical solution of the present invention, the step S1 and step S2 further include pile head leveling and base surface treatment. The specific steps are as follows: the elevation of the pile head of the completed engineering pile is re-measured. When the pile top elevation is higher than the design foundation bottom elevation, a handheld hydraulic splitter or a small static blasting device is used to remove it. After removal, a high-pressure water gun is used to clean the pile top slag and debris.

[0017] As a preferred technical solution of the present invention, after the cross bracing is set in step S5, a vibration sensor or strain gauge is used to monitor the stress of the bracing node in real time during the construction period. The monitoring data is wirelessly transmitted to the monitoring platform. If the node stress is abnormal, the subsequent pouring operation is suspended and reinforcement treatment is carried out.

[0018] As a preferred embodiment of the present invention, the specific steps of the reinforcement treatment are as follows:

[0019] S51. Suspend all subsequent construction activities and set up a safety warning zone around the supporting structure;

[0020] S52. Use a portable digital strain gauge to re-measure the stress of the alarm node and its adjacent nodes to confirm the accuracy of the abnormal data. Use the monitoring platform to backtrack the data, analyze the occurrence time and trend of the stress anomaly, and accurately locate the problem node.

[0021] S53. Temporary support frames are erected on the steel mesh of the foundation near the abnormal node to provide temporary unloading support for the top I-beam.

[0022] S54. Use an angle grinder to clean the surface of the original weld at the abnormal node, remove welding slag and rust, and repair the weld using E50 series welding rods. The length of the repair weld should be ≥150mm and the height of the weld should be ≥ the height of the original weld. After the repair weld is completed, perform heat preservation and slow cooling treatment. If there are cracks in the original weld or obvious node deformation, reinforce it with a reinforcing plate. The reinforcing plate is a 10mm thick Q235B steel plate, cut into a rectangle with a specification of 200mm×100mm. Place the reinforcing plate tightly on both sides of the node between the diagonal brace and the column I-beam, and fix it by surrounding welding on all four sides. The weld height is 8mm.

[0023] S55. After the reinforcement is completed, use an ultrasonic flaw detector to perform non-destructive testing on the repair weld and the reinforcement plate weld.

[0024] S56. Restart the monitoring system and observe the stress change of the reinforced node under static load for ≥30 minutes.

[0025] As a preferred embodiment of the present invention, the specific steps of the data backtracking are as follows:

[0026] S61. Data Extraction and Time Alignment: Retrieve stress monitoring data of the abnormal node and its neighboring nodes throughout the entire construction cycle from the blockchain distributed storage platform, including stress values, temperature, vibration frequency, timestamps and other multi-dimensional data. Through time series alignment algorithms, the sensor data is associated and integrated with external data such as construction logs, weather records, and equipment operating status to construct a complete digital twin fragment of the construction process.

[0027] S62. Big Data Trend Analysis and Anomaly Identification: The sliding window and discrete wavelet transform are used to decompose historical stress data at multiple scales to identify the frequency bands and amplitudes of stress abrupt changes. Based on unsupervised learning algorithms, the existence of hidden anomaly patterns is detected. Combined with a gradient boosting decision tree model, the causal relationship between stress anomalies and construction activities is analyzed.

[0028] S63. Visual backtracking and root cause localization: Enable dynamic time-series visualization dashboards in the monitoring platform, use heat maps, trend curves, and 3D models to highlight the development path of stress anomalies, model the node connection relationship of the support structure through graph neural networks, identify whether there are abnormal transmission paths, output a root cause analysis report, determine whether the anomaly is a transient impact, continuous overload or welding defect, and give a confidence score.

[0029] S64. Prediction and Decision Support: Utilize a deep reinforcement learning model to predict the evolution trend of nodal stress over the next 30 minutes without intervention. Combined with structural mechanics simulation, recommend the optimal reinforcement strategy and estimate the time it takes for the stress to recover to the safe threshold after treatment.

[0030] As a preferred embodiment of the present invention, the specific steps of the multi-scale decomposition are as follows:

[0031] S71. Data cleaning and imputation: Imput missing values ​​in the original stress time series and remove obvious abnormal jump points. Use the Z-score standardization method to convert the stress data into a distribution with a mean of 0 and a standard deviation of 1.

[0032] S72. Set the sliding window parameters: Set the window length to W=60 seconds and the sliding step to S=10 seconds.

[0033] S73. Calculate statistical characteristics within the window: Calculate the mean, variance, peak factor, and mean absolute value of the first difference for the data within each window;

[0034] S74. Discrete wavelet transform multiscale decomposition: Wavelet is selected as the basis function, and the stress data in each sliding window is decomposed into 5 levels of wavelet decomposition to obtain approximation coefficients and detail coefficients.

[0035] S75. Reconstructing signals in each frequency band: Reconstruct the components separately using inverse wavelet transform, extract scale feature vectors, and then combine the multi-scale features of each window into a feature vector to form a time series feature matrix.

[0036] S76. Abrupt Change Detection and Frequency Band Location: Identify the starting point and amplitude of stress abrupt changes on each detail coefficient sequence, calculate the proportion of energy in each frequency band to the total energy, and if the energy ratio of a certain frequency band suddenly increases, identify the starting point and amplitude of the stress abrupt change.

[0037] As a preferred embodiment of the present invention, the specific steps of the heat preservation and slow cooling treatment are as follows:

[0038] S81. Select ceramic fiber blankets or asbestos cloth with high temperature resistance and good thermal insulation performance as thermal insulation materials.

[0039] S82. When the welding operation is completed and the weld area is still red-hot, wrap and cover the entire weld area tightly with the prepared insulation material.

[0040] S83. Use high-temperature resistant iron wire or stainless steel cable ties to securely bind the insulation material to the I-beam or reinforcing plate.

[0041] S84. The welded joints are allowed to cool naturally to ambient temperature under the insulation layer. When the temperature drops below 5°C, a windproof cover is added outside the insulation layer.

[0042] S85. After the node has completely cooled to ambient temperature, remove the insulation material and visually inspect the weld surface for uniform color and any abnormal cracks or other defects.

[0043] As a preferred embodiment of the present invention, after the top I-beams are horizontally connected in step S6, a flatness verification and adjustment step is added, as follows:

[0044] S91. Layout of measuring points and establishment of benchmarks: On the welded top I-beam frame, a calibration measuring point is set up every 3 meters along the east-west and north-south directions to form a grid-like array of measuring points. An automatic leveling laser scanner is set up at a stable position outside the construction area to establish a horizontal laser benchmark plane covering the entire top frame.

[0045] S92. Data Acquisition and Deviation Identification: The operator holds a precision leveling rod and places it at each measuring point in sequence, records the actual height reading of each measuring point relative to the laser reference plane, and calculates the deviation value between it and the design elevation.

[0046] S93. Analysis and Adjustment Decision: When the flatness deviation of any measuring point exceeds the allowable value, identify the local high or low point areas. For local high points, use an angle grinder to grind them; for local low points, use a pad to fill the gaps. The pad is fixed to the top I-beam by intermittent welding.

[0047] S94. Re-testing and Confirmation: After the adjustment is completed, re-test the adjusted area and surrounding measuring points, verify the data, and record and archive it.

[0048] As a preferred embodiment of the present invention, the specific steps for verifying the data are as follows:

[0049] S101. Data verification and logical judgment: The embedded data verification algorithm is used to automatically compare the retest data. If there are any deviations, the system will automatically trigger an early warning and generate a deviation distribution heat map.

[0050] S102. Blockchain-based evidence storage and tamper-proof archiving: All verification data is uploaded in real time to the blockchain-based construction quality management platform to generate a unique hash value;

[0051] S103. The data packet of each measuring point is automatically associated with the image data and operation log of the previous process to generate a complete quality traceability chain;

[0052] S104. Deep Learning-Assisted Decision Archiving: Train a deep learning model in the historical construction database to predict and analyze the current trend of flatness deviation. After identifying potential systematic errors, the model outputs a deviation cause analysis report and generates recommended optimization suggestions.

[0053] S105. Intelligent archiving and access control: All verification data, image data, and analysis reports are stored in a cloud-based digital archive according to a three-level directory structure of project-process-date, and multi-level access control is set.

[0054] Compared with the prior art, the beneficial effects of the present invention are:

[0055] 1. By welding the bottom support, columns, cooling pipe support steel bars, cross braces and top I-beams together, a spatial three-dimensional support frame is formed that is closely integrated with the internal steel bars and cooling pipes of the foundation. As a stiff structure, this frame can effectively share the impact load and lateral pressure during concrete pouring, greatly improving the overall stiffness and stability of the support system. It fundamentally avoids the risks of displacement, deformation or even instability that are prone to occur in traditional scattered supports, and significantly improves construction safety.

[0056] 2. Standardized and modular I-beams and steel reinforcement components are used for on-site assembly and welding. The construction process is clear and the operation is simple, avoiding a large amount of on-site cutting, adjustment and complex connection work in traditional methods. The support device has the dual functions of steel reinforcement skeleton and cooling pipe support, realizing the merging of processes, thereby greatly improving installation efficiency, shortening the construction cycle of the support system, and saving valuable time for subsequent concrete pouring.

[0057] 3. Comprehensive quality control measures were introduced. Precise leveling of the pile heads provided a stable base for the support. Real-time stress monitoring of the cross-bracing nodes enabled dynamic perception and proactive intervention of the structural safety status. A laser leveling instrument was used to perform grid-based verification and adjustment of the flatness of the top frame, ensuring the accuracy of the construction benchmark for the superstructure. These measures together guaranteed the installation quality of the support system, thereby ensuring the casting and forming effect of large-volume concrete, resulting in a smooth surface and effective crack control.

[0058] 4. Making full use of scrap I-beams to make the base supports reflects the concept of green construction. At the same time, it adds an intelligent monitoring link. Due to the resulting improvement in safety, shortening of construction period and quality assurance, it effectively avoids the rework or accident handling costs that may be caused by support problems, thereby reducing the overall project cost and achieving significant economic benefits. Attached Figure Description

[0059] Figure 1 This is an overall flowchart of a construction method for reinforcing and supporting the abutment of a rotating bridge in one-time casting, according to the present invention.

[0060] Figure 2 This is a schematic diagram of the construction process of a reinforcement and support construction method for a rotating bridge abutment that is cast in one go according to the present invention. Detailed Implementation

[0061] 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 only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Example 1

[0063] Please see Figure 1 and Figure 2 This invention provides a method for reinforcing and supporting the abutment of a rotating bridge in a single pour, comprising the following steps:

[0064] S1. Surveying and setting out: Use a total station to mark the lower foundation edge line and the center line of the pile position, and mark the line.

[0065] S2. Bottom support installation: After cutting the I-beam into a bottom support, place it in the center of the top surface of the pile head and spot weld it to the fifth layer of steel reinforcement of the lower bearing platform;

[0066] S3. Erection of I-beam columns: Hoist the I-beam columns into position and install them on the fifth layer of steel mesh according to the marked position. Multiple steel bars are used to spot weld the perimeter. The bottom of the I-beam columns is fully welded to the base support, and temporary support steel bars are set on both sides.

[0067] S4. Cooling pipe support steel reinforcement installation: Cooling pipe support steel reinforcement is arranged horizontally along the cooling pipe layer and welded to the column I-beams to form a grid. One layer is set every 1m in height, for a total of 5 layers. The horizontal and vertical directions are fully welded to the column I-beams and staggered with the cooling pipe interface positions.

[0068] S5. Cross bracing installation: Cross bracing is installed at the bottom and top 1m of the I-beam of the column. The angle between the bracing and the I-beam of the column is 45-60°. In the north-south direction, the bracing is installed every other one, and in the east-west direction, the bracing is fully installed. The bracing joints are welded on both sides, and the weld length is ≥100mm.

[0069] S6. Horizontal connection of top I-beam: Set up I-beams at the top and connect them horizontally in the east-west direction. Weld steel bars to the inside of the I-beams to form a closed frame. The connection is fully welded and the weld height is ≥6mm.

[0070] Furthermore, the base, column I-beams, and top I-beams are all made of I14 I-beams, and the base is cut from scrap I-beams, with dimensions of 300×88×140mm.

[0071] Furthermore, between steps S1 and S2, there is also pile head leveling and base surface treatment. The specific steps are as follows: the elevation of the pile head of the completed engineering pile is re-measured. When the pile top elevation is higher than the design foundation bottom elevation, a handheld hydraulic splitter or a small static blasting device is used to remove it. After removal, a high-pressure water gun is used to clean the pile top slag and debris.

[0072] Furthermore, after the cross bracing is set up in step S5, vibration sensors or strain gauges are used to monitor the stress of the bracing nodes in real time during the construction period. The monitoring data is wirelessly transmitted to the monitoring platform. If the node stress is abnormal, the subsequent pouring operation is suspended and reinforcement is carried out.

[0073] Furthermore, the specific steps for reinforcement are as follows:

[0074] S51. Suspend all subsequent construction activities and set up a safety warning zone around the supporting structure;

[0075] S52. Use a portable digital strain gauge to re-measure the stress of the alarm node and its adjacent nodes to confirm the accuracy of the abnormal data. Use the monitoring platform to backtrack the data, analyze the occurrence time and trend of the stress anomaly, and accurately locate the problem node.

[0076] S53. Temporary support frames are erected on the steel mesh of the foundation near the abnormal node to provide temporary unloading support for the top I-beam.

[0077] S54. Use an angle grinder to clean the surface of the original weld at the abnormal node, remove welding slag and rust, and repair the weld using E50 series welding rods. The length of the repair weld should be ≥150mm and the height of the weld should be ≥ the height of the original weld. After the repair weld is completed, perform heat preservation and slow cooling treatment. If there are cracks in the original weld or obvious node deformation, reinforce it with a reinforcing plate. The reinforcing plate is a 10mm thick Q235B steel plate, cut into a rectangle with a specification of 200mm×100mm. Place the reinforcing plate tightly on both sides of the node between the diagonal brace and the column I-beam, and fix it by surrounding welding on all four sides. The weld height is 8mm.

[0078] S55. After the reinforcement is completed, use an ultrasonic flaw detector to perform non-destructive testing on the repair weld and the reinforcement plate weld.

[0079] S56. Restart the monitoring system and observe the stress change of the reinforced node under static load for ≥30 minutes.

[0080] Furthermore, the specific steps for data backtracking are as follows:

[0081] S61. Data Extraction and Time Alignment: Retrieve stress monitoring data of the abnormal node and its neighboring nodes throughout the entire construction cycle from the blockchain distributed storage platform, including stress values, temperature, vibration frequency, timestamps and other multi-dimensional data. Through time series alignment algorithms, the sensor data is associated and integrated with external data such as construction logs, weather records, and equipment operating status to construct a complete digital twin fragment of the construction process.

[0082] S62. Big Data Trend Analysis and Anomaly Identification: The sliding window and discrete wavelet transform are used to decompose historical stress data at multiple scales to identify the frequency bands and amplitudes of stress abrupt changes. Based on unsupervised learning algorithms, the existence of hidden anomaly patterns is detected. Combined with a gradient boosting decision tree model, the causal relationship between stress anomalies and construction activities is analyzed.

[0083] S63. Visual backtracking and root cause localization: Enable dynamic time-series visualization dashboards in the monitoring platform, use heat maps, trend curves, and 3D models to highlight the development path of stress anomalies, model the node connection relationship of the support structure through graph neural networks, identify whether there are abnormal transmission paths, output a root cause analysis report, determine whether the anomaly is a transient impact, continuous overload or welding defect, and give a confidence score.

[0084] S64. Prediction and Decision Support: Utilize a deep reinforcement learning model to predict the evolution trend of nodal stress over the next 30 minutes without intervention. Combined with structural mechanics simulation, recommend the optimal reinforcement strategy and estimate the time it takes for the stress to recover to the safe threshold after treatment.

[0085] Furthermore, the specific steps of multi-scale decomposition are as follows:

[0086] S71. Data cleaning and imputation: Imput missing values ​​in the original stress time series and remove obvious abnormal jump points. Use the Z-score standardization method to convert the stress data into a distribution with a mean of 0 and a standard deviation of 1.

[0087] S72. Set the sliding window parameters: Set the window length to W=60 seconds and the sliding step to S=10 seconds.

[0088] S73. Calculate statistical characteristics within the window: Calculate the mean, variance, peak factor, and mean absolute value of the first difference for the data within each window;

[0089] S74. Discrete wavelet transform multiscale decomposition: Wavelet is selected as the basis function, and the stress data in each sliding window is decomposed into 5 levels of wavelet decomposition to obtain approximation coefficients and detail coefficients.

[0090] S75. Reconstructing signals in each frequency band: Reconstruct the components separately using inverse wavelet transform, extract scale feature vectors, and then combine the multi-scale features of each window into a feature vector to form a time series feature matrix.

[0091] S76. Abrupt Change Detection and Frequency Band Location: Identify the starting point and amplitude of stress abrupt changes on each detail coefficient sequence, calculate the proportion of energy in each frequency band to the total energy, and if the energy ratio of a certain frequency band suddenly increases, identify the starting point and amplitude of the stress abrupt change.

[0092] Furthermore, the specific steps for the heat preservation and slow cooling treatment are as follows:

[0093] S81. Select ceramic fiber blankets or asbestos cloth with high temperature resistance and good thermal insulation performance as thermal insulation materials.

[0094] S82. When the welding operation is completed and the weld area is still red-hot, wrap and cover the entire weld area tightly with the prepared insulation material.

[0095] S83. Use high-temperature resistant iron wire or stainless steel cable ties to securely bind the insulation material to the I-beam or reinforcing plate.

[0096] S84. The welded joints are allowed to cool naturally to ambient temperature under the insulation layer. When the temperature drops below 5°C, a windproof cover is added outside the insulation layer.

[0097] S85. After the node has completely cooled to ambient temperature, remove the insulation material and visually inspect the weld surface for uniform color and any abnormal cracks or other defects.

[0098] Furthermore, after the horizontal connection of the top I-beams in step S6, a flatness verification and adjustment step is added, as follows:

[0099] S91. Layout of measuring points and establishment of benchmarks: On the welded top I-beam frame, a calibration measuring point is set up every 3 meters along the east-west and north-south directions to form a grid-like array of measuring points. An automatic leveling laser scanner is set up at a stable position outside the construction area to establish a horizontal laser benchmark plane covering the entire top frame.

[0100] S92. Data Acquisition and Deviation Identification: The operator holds a precision leveling rod and places it at each measuring point in sequence, records the actual height reading of each measuring point relative to the laser reference plane, and calculates the deviation value between it and the design elevation.

[0101] S93. Analysis and Adjustment Decision: When the flatness deviation of any measuring point exceeds the allowable value, identify the local high or low point areas. For local high points, use an angle grinder to grind them; for local low points, use a pad to fill the gaps. The pad is fixed to the top I-beam by intermittent welding.

[0102] S94. Re-testing and Confirmation: After the adjustment is completed, re-test the adjusted area and surrounding measuring points, verify the data, and record and archive it.

[0103] Furthermore, the specific steps for verifying the data are as follows:

[0104] S101. Data verification and logical judgment: The embedded data verification algorithm is used to automatically compare the retest data. If there are any deviations, the system will automatically trigger an early warning and generate a deviation distribution heat map.

[0105] S102. Blockchain-based evidence storage and tamper-proof archiving: All verification data is uploaded in real time to the blockchain-based construction quality management platform to generate a unique hash value;

[0106] S103. The data packet of each measuring point is automatically associated with the image data and operation log of the previous process to generate a complete quality traceability chain;

[0107] S104. Deep Learning-Assisted Decision Archiving: Train a deep learning model in the historical construction database to predict and analyze the current trend of flatness deviation. After identifying potential systematic errors, the model outputs a deviation cause analysis report and generates recommended optimization suggestions.

[0108] S105. Intelligent archiving and access control: All verification data, image data, and analysis reports are stored in a cloud-based digital archive according to a three-level directory structure of project-process-date, and multi-level access control is set.

[0109] Example 2 (Method of the Invention)

[0110] In a bridge pier construction project, the construction method described in this invention was used for reinforcement and support. The pier dimensions are 20m × 15m × 6m, and the designed volume of concrete to be poured in one go is approximately 1800m³. 3 During the construction process, all steps were strictly carried out according to the procedure described in Example 1, and the specific implementation is as follows:

[0111] Surveying and setting out and base surface treatment: A total station is used for precise setting out. After the pile heads are leveled, the height difference of the base surface is controlled within ±3mm.

[0112] Support system installation: I14 I-beams are used as the main components, and the base is made from scrap materials.

[0113] Intelligent monitoring and control: Strain gauges are installed at the diagonal brace nodes, and the data is uploaded to the cloud platform in real time. When a stress anomaly occurs (peak value reaches 198MPa), the system automatically alarms and triggers the reinforcement process. After welding and reinforcement with reinforcing plates, the stress recovers to 125MPa.

[0114] Flatness control: The top I-beam frame was checked by a laser leveling instrument, and the maximum deviation was -4mm. After local adjustment with wedge shims, the deviation was met to meet the ±5mm requirement.

[0115] Pouring process: Concrete is poured in layers, with the pouring volume controlled at 120m³ per hour. 3 No visible deformation or settlement was observed in the support system.

[0116] Comparative example (traditional method)

[0117] For comparison, another project with basically the same geological conditions, foundation size, and concrete volume was selected as a control using a traditional construction method. The traditional method uses a loosely assembled steel pipe scaffold as the main support system, with the scaffold separated from the reinforcing bars and cooling pipes, and lacking systematic monitoring and verification measures. The specific implementation is as follows:

[0118] Support installation: Steel pipes are cut on site to build a support frame, which is then tied to the steel mesh with wire without welding.

[0119] Monitoring method: Relies solely on manual inspections, without stress monitoring equipment.

[0120] Flatness control: Spot checks were conducted using a level instrument; no full-section verification was performed.

[0121] Pouring process: During the pouring process, some supports tilted slightly. After manual reinforcement, construction continued, but the overall settlement control was poor.

[0122] Comparison of experimental data and results

[0123] Testing items Method of the present invention (Example 2) Traditional method (comparative example) Testing standards / methods Support system installation period 5 days 8 days From surveying and setting out to support acceptance completion Flatness of the top frame before concrete pouring Average deviation +2mm, maximum deviation -4mm (meets ±5mm requirement) Average deviation +15mm, maximum deviation -28mm Laser leveling instrument grid measurement Maximum stress at the diagonal brace node during pouring 198MPa (restored to 125MPa after reinforcement following alarm) Monitoring was lacking, and localized bending was visible to the naked eye after pouring. Wireless strain monitoring system / manual observation Maximum settlement of the support system after pouring 7mm 25mm Leveling instrument to measure the elevation of the top surface of the foundation Surface appearance of the concrete foundation after molding Smooth, with no visible cracks The area is uneven, with three surface shrinkage cracks. Visual inspection and feeler gauge check Comprehensive construction cost Save 18% Benchmark (100%) Project cost accounting

[0124] Experimental Description and Analysis

[0125] 1. This invention, through standardized components and welding forming process, supports a 37.5% reduction in installation time. Traditional methods suffer from low installation efficiency and poor accuracy due to frequent on-site adjustments, unstable connections, and poor installation accuracy.

[0126] 2. This invention successfully provided an early warning of an abnormal stress during the pouring process. After intelligent backtracking and reinforcement, the stress returned to normal, avoiding potential structural damage. In contrast, the control case lacked monitoring, and the support deformation was not detected in time, posing a safety hazard.

[0127] 3. The support system of this invention has high rigidity and strong integrity. The maximum settlement during the pouring process is only 7mm, and the surface of the foundation is flat and without cracks. Traditional methods have insufficient support rigidity, settlement reaches 25mm, and surface cracks appear, requiring subsequent repairs.

[0128] 4. Although this invention introduces an intelligent monitoring process, it reduces overall costs by 18% through shorter construction periods, improved quality, and reduced rework, resulting in significant economic benefits.

[0129] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for reinforcing and supporting abutments of a rotating bridge with one-time casting, characterized in that, Includes the following steps: S1. Surveying and setting out: Use a total station to mark the lower foundation edge line and the center line of the pile position, and mark the line. S2. Bottom support installation: After cutting the I-beam into a bottom support, place it in the center of the top surface of the pile head and spot weld it to the fifth layer of steel reinforcement of the lower bearing platform; S3. Erection of I-beam columns: Hoist the I-beam columns into position and install them on the fifth layer of steel mesh according to the marked position. Multiple steel bars are used to spot weld the perimeter. The bottom of the I-beam columns is fully welded to the base support, and temporary support steel bars are set on both sides. S4. Cooling pipe support steel reinforcement installation: Cooling pipe support steel reinforcement is arranged horizontally along the cooling pipe layer and welded to the column I-beams to form a grid. One layer is set every 1m in height, for a total of 5 layers. The horizontal and vertical directions are fully welded to the column I-beams and staggered with the cooling pipe interface positions. S5. Cross bracing installation: Cross bracing is installed at the bottom and top 1m of the I-beam of the column. The angle between the bracing and the I-beam of the column is 45-60°. In the north-south direction, the bracing is installed every other one, and in the east-west direction, the bracing is fully installed. The bracing joints are welded on both sides, and the weld length is ≥100mm. S6. Horizontal connection of top I-beam: Set up I-beams at the top and connect them horizontally in the east-west direction. Weld steel bars to the inside of the I-beams to form a closed frame. The connection is fully welded and the weld height is ≥6mm.

2. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 1, characterized in that, The base, column I-beams, and top I-beams are all made of I14 I-beams. The base is cut from scrap I-beams and measures 300×88×140mm.

3. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 1, characterized in that, Between steps S1 and S2, there is also pile head leveling and base surface treatment. The specific steps are as follows: the elevation of the pile head of the completed engineering pile is re-measured. When the pile top elevation is higher than the design foundation bottom elevation, a handheld hydraulic splitter or a small static blasting device is used to remove it. After removal, a high-pressure water gun is used to clean the pile top slag and debris.

4. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 1, characterized in that, After the cross bracing is set in step S5, vibration sensors or strain gauges are used to monitor the stress of the bracing nodes in real time during the construction period. The monitoring data is wirelessly transmitted to the monitoring platform. If the node stress is abnormal, the subsequent pouring operation is suspended and reinforcement is carried out.

5. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 1, characterized in that, The specific steps of the reinforcement treatment are as follows: S51. Suspend all subsequent construction activities and set up a safety warning zone around the supporting structure; S52. Use a portable digital strain gauge to re-measure the stress of the alarm node and its adjacent nodes to confirm the accuracy of the abnormal data. Use the monitoring platform to backtrack the data, analyze the occurrence time and trend of the stress anomaly, and accurately locate the problem node. S53. Temporary support frames are erected on the steel mesh of the foundation near the abnormal node to provide temporary unloading support for the top I-beam. S54. Use an angle grinder to clean the surface of the original weld at the abnormal node, remove welding slag and rust, and repair the weld using E50 series welding rods. The length of the repair weld should be ≥150mm and the height of the weld should be ≥ the height of the original weld. After the repair weld is completed, perform heat preservation and slow cooling treatment. If there are cracks in the original weld or obvious node deformation, reinforce it with a reinforcing plate. The reinforcing plate is a 10mm thick Q235B steel plate, cut into a rectangle with a specification of 200mm×100mm. Place the reinforcing plate tightly on both sides of the node between the diagonal brace and the column I-beam, and fix it by surrounding welding on all four sides. The weld height is 8mm. S55. After the reinforcement is completed, use an ultrasonic flaw detector to perform non-destructive testing on the repair weld and the reinforcement plate weld. S56. Restart the monitoring system and observe the stress change of the reinforced node under static load for ≥30 minutes.

6. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 5, characterized in that, The specific steps for data backtracking are as follows: S61. Data Extraction and Time Alignment: Retrieve stress monitoring data of the abnormal node and its neighboring nodes throughout the entire construction cycle from the blockchain distributed storage platform, including stress values, temperature, vibration frequency, timestamps and other multi-dimensional data. Through time series alignment algorithms, the sensor data is associated and integrated with external data such as construction logs, weather records, and equipment operating status to construct a complete digital twin fragment of the construction process. S62. Big Data Trend Analysis and Anomaly Identification: The sliding window and discrete wavelet transform are used to decompose historical stress data at multiple scales to identify the frequency bands and amplitudes of stress abrupt changes. Based on unsupervised learning algorithms, the existence of hidden anomaly patterns is detected. Combined with a gradient boosting decision tree model, the causal relationship between stress anomalies and construction activities is analyzed. S63. Visual backtracking and root cause localization: Enable dynamic time-series visualization dashboards in the monitoring platform, use heat maps, trend curves, and 3D models to highlight the development path of stress anomalies, model the node connection relationship of the support structure through graph neural networks, identify whether there are abnormal transmission paths, output a root cause analysis report, determine whether the anomaly is a transient impact, continuous overload or welding defect, and give a confidence score. S64. Prediction and Decision Support: Utilize a deep reinforcement learning model to predict the evolution trend of nodal stress over the next 30 minutes without intervention. Combined with structural mechanics simulation, recommend the optimal reinforcement strategy and estimate the time it takes for the stress to recover to the safe threshold after treatment.

7. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 6, characterized in that, The specific steps of the multi-scale decomposition are as follows: S71. Data cleaning and imputation: Imput missing values ​​in the original stress time series and remove obvious abnormal jump points. Use the Z-score standardization method to convert the stress data into a distribution with a mean of 0 and a standard deviation of 1. S72. Set the sliding window parameters: Set the window length to W=60 seconds and the sliding step to S=10 seconds. S73. Calculate statistical characteristics within the window: Calculate the mean, variance, peak factor, and mean absolute value of the first difference for the data within each window; S74. Discrete wavelet transform multiscale decomposition: Wavelet is selected as the basis function, and the stress data in each sliding window is decomposed into 5 levels of wavelet decomposition to obtain approximation coefficients and detail coefficients. S75. Reconstructing signals in each frequency band: Reconstruct the components separately using inverse wavelet transform, extract scale feature vectors, and then combine the multi-scale features of each window into a feature vector to form a time series feature matrix. S76. Abrupt Change Detection and Frequency Band Location: Identify the starting point and amplitude of stress abrupt changes on each detail coefficient sequence, calculate the proportion of energy in each frequency band to the total energy, and if the energy ratio of a certain frequency band suddenly increases, identify the starting point and amplitude of the stress abrupt change.

8. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 5, characterized in that, The specific steps of the heat preservation and slow cooling treatment are as follows: S81. Select ceramic fiber blankets or asbestos cloth with high temperature resistance and good thermal insulation performance as thermal insulation materials. S82. When the welding operation is completed and the weld area is still red-hot, wrap and cover the entire weld area tightly with the prepared insulation material. S83. Use high-temperature resistant iron wire or stainless steel cable ties to securely bind the insulation material to the I-beam or reinforcing plate. S84. The welded joints are allowed to cool naturally to ambient temperature under the insulation layer. When the temperature drops below 5°C, a windproof cover is added outside the insulation layer. S85. After the node has completely cooled to ambient temperature, remove the insulation material and visually inspect the weld surface for uniform color and any abnormal cracks or other defects.

9. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 1, characterized in that, After the horizontal connection of the top I-beam in step S6, a flatness verification and adjustment step is added, as follows: S91. Layout of measuring points and establishment of benchmarks: On the welded top I-beam frame, a calibration measuring point is set up every 3 meters along the east-west and north-south directions to form a grid-like array of measuring points. An automatic leveling laser scanner is set up at a stable position outside the construction area to establish a horizontal laser benchmark plane covering the entire top frame. S92. Data Acquisition and Deviation Identification: The operator holds a precision leveling rod and places it at each measuring point in sequence, records the actual height reading of each measuring point relative to the laser reference plane, and calculates the deviation value between it and the design elevation. S93. Analysis and Adjustment Decision: When the flatness deviation of any measuring point exceeds the allowable value, identify the local high or low point areas. For local high points, use an angle grinder to grind them; for local low points, use a pad to fill the gaps. The pad is fixed to the top I-beam by intermittent welding. S94. Re-testing and Confirmation: After the adjustment is completed, re-test the adjusted area and surrounding measuring points, verify the data, and record and archive it.

10. The reinforcement and support construction method for one-time casting of the abutment under a rotating bridge according to claim 9, characterized in that, The specific steps for verifying the data are as follows: S101. Data verification and logical judgment: The embedded data verification algorithm is used to automatically compare the retest data. If there are any deviations, the system will automatically trigger an early warning and generate a deviation distribution heat map. S102. Blockchain-based evidence storage and tamper-proof archiving: All verification data is uploaded in real time to the blockchain-based construction quality management platform to generate a unique hash value; S103. The data packet of each measuring point is automatically associated with the image data and operation log of the previous process to generate a complete quality traceability chain; S104. Deep Learning-Assisted Decision Archiving: Train a deep learning model in the historical construction database to predict and analyze the current trend of flatness deviation. After identifying potential systematic errors, the model outputs a deviation cause analysis report and generates recommended optimization suggestions. S105. Intelligent archiving and access control: All verification data, image data, and analysis reports are stored in a cloud-based digital archive according to a three-level directory structure of project-process-date, and multi-level access control is set.

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