Super high-rise large-span transfer truss unloading method

Abstract

The invention relates to the technical field of building construction, in particular to a super high-rise large-span transfer truss unloading method. According to the technical scheme, the method comprises the steps that a structural mode is recognized, finite element unloading simulation is conducted, and a cutting guide line and partitions are pre-designed; laying a multi-source sensor network and building a real-time data platform; gas cutting grading unloading is adopted according to a preset partition sequence, and cutting parameters are dynamically adjusted based on stress, displacement and temperature data monitored in real time; the structure state is evaluated in real time through data fusion analysis, and a graded early warning and dynamic adjustment mechanism is triggered; continuous monitoring is conducted after unloading, and the support is dismantled after stable conditions are met. The system comprises a data acquisition module, a data analysis module, a decision support module and a visual interface. According to the method, active control over smooth transfer and deformation of the internal force of the structure in the unloading process is achieved by constructing a sensing, analyzing, deciding and executing closed loop, the problems that a traditional method is low in synchronization precision and high in stress concentration risk are solved, and the method has the advantages of being high in safety and adaptability and controllable in construction.

Description

Technical Field

[0001] This invention relates to the field of building construction technology, and in particular to a method for unloading a super high-rise, large-span transfer truss. Background Technology

[0002] In the construction of super high-rise buildings, large-span transfer trusses serve as key load-bearing components. After the concrete structure is completed and reaches its design strength, the temporary support system beneath it needs to be removed. This process is called "unloading." Unloading is essentially the process of smoothly and safely transferring the load borne by the truss from its temporary supports to the permanent structure. Its technical implementation is directly related to the safety and forming quality of the main structure.

[0003] Currently, the most common unloading method in engineering practice relies on the operation of hydraulic jack clusters. This method involves arranging multiple hydraulic jacks at the bottom of the truss as temporary support points. Through unified oil supply and control by a pump station, the aim is to synchronize the retraction of all jack pistons, thereby gradually reducing the supporting force and slowly lowering the truss to its permanent support. Its technical principle depends on the synchronization accuracy of the hydraulic system and centralized command control by the operators.

[0004] However, this method faces significant challenges in practical applications. Achieving high-precision synchronization is extremely difficult due to differences in individual jack performance, uneven structural stiffness distribution, and the impact of dynamic load redistribution. Asynchronous unloading can easily lead to abrupt changes in reaction forces at various truss support points, causing localized stress concentrations and overall deformation inconsistencies, posing a safety risk of localized structural damage or even instability. Furthermore, this risk is difficult to effectively prevent and control in the absence of real-time, comprehensive structural status feedback and dynamic control mechanisms. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the background art by proposing a method for unloading super high-rise large-span transfer trusses.

[0006] This application provides a method for unloading a super high-rise, large-span transfer truss, which includes the following steps: S1. Identify the truss structure modes, determine the stress redistribution path during the unloading process based on finite element simulation, and design the corresponding cutting guide line; S2. Deploy a multi-source sensor network at key nodes, support points and cutting areas of the truss to establish a real-time data acquisition and transmission system. S3. According to the pre-designed cutting guide line and partitioning sequence, use gas cutting to perform graded and partitioned unloading, and dynamically adjust the cutting parameters based on real-time monitoring data; S4. Based on the fusion analysis of multi-source sensor data, the structural status is evaluated in real time, and the unloading strategy is dynamically adjusted according to the evaluation results; S5. After unloading, continuously monitor the structure and remove the support system after confirming that the structure is stable.

[0007] Optionally, in step S1: The structural modal identification includes obtaining the first three vertical bending modes of the structure through an environmental excitation method, with a frequency identification range of 0.5-10Hz; The structure is divided into unloading regions with different sensitivity levels based on the modal amplitude, and the region with a modal amplitude greater than 0.7 is defined as the high sensitivity region. The finite element simulation adopts a three-dimensional solid-beam hybrid model, and the constitutive model of the supporting steel plate adopts a bilinear kinematic hardening model with an elastic modulus of 2.06×105MPa and a yield strength of 345MPa.

[0008] Optionally, the cutting guide line designed in step S1 is a continuous smooth curve with its radius of curvature controlled within the range of 500-2000 mm. Based on the thermo-coupling pre-analysis, the target width of the heat-affected zone is determined to be 25-45 mm, and the heat-affected zone is defined as the area with a temperature higher than 250℃.

[0009] Optionally, in step S2: The multi-source sensor network includes strain sensors, displacement sensors, pressure sensors, temperature sensors, and vibration sensors; The strain sensors are arranged at the support of the lower chord of the truss, at the mid-span and at the neutral axis position of the cross section at 1 / 4 span, and the sampling frequency is 1Hz for static and 200Hz for dynamic. The temperature sensor includes a K-type thermocouple arranged around the cutting point at a distance of 10mm, 20mm, and 30mm from the cutting line, and an infrared thermal imager mounted above the cutting area, with a frame rate of 5-10Hz.

[0010] Optionally, in step S3: The gas cutting method uses propane as fuel, and the oxygen purity is not less than 99.5%. Select the cutting nozzle model according to the thickness of the supporting steel plate: use nozzle No. 2 when the steel plate thickness is 20-40mm, and nozzle No. 3 when the thickness is 40-60mm. The initial cutting parameters were set as follows: oxygen pressure 0.5-0.7 MPa, propane pressure 0.05-0.08 MPa, and cutting speed 150-200 mm / min.

[0011] Optionally, the dynamic adjustment of cutting parameters in step S3 includes: The single cutting depth is adjusted according to the real-time monitored load transfer rate: when the load transfer rate is greater than 50kN / step, the single cutting depth is 5mm; when the load transfer rate is less than 20kN / step, the single cutting depth is 10mm. Adjust the cutting speed according to the width of the heat-affected zone monitored by the infrared thermal imager: when the width of the heat-affected zone is greater than 40mm, increase the cutting speed by 20-50mm / min; when it is less than 30mm, decrease the cutting speed by 20-50mm / min. The surface roughness is controlled by adjusting the nozzle height and oxygen flow rate, with a target roughness Ra of 12.5-25 μm.

[0012] Optionally, step S3 may also include melting stage control: When the steel plate is cut to a remaining thickness of 1 / 3 of its total thickness, the melting stage begins. During the melting stage, the cutting nozzle angle is tilted to 70-80 degrees, and the cutting speed is reduced to 100-150 mm / min; Control the melting rate so that the mid-span displacement rise rate does not exceed 0.5 mm / min.

[0013] Optionally, in step S4: The real-time assessment includes calculating the following indicators: load distribution unevenness coefficient at each support point, deviation rate between mid-span displacement and calculated value, and ratio of strain to yield strain at key points. Set warning thresholds: trigger a warning when the load distribution unevenness coefficient is greater than 1.15, the displacement deviation rate is greater than 20%, and the strain ratio is greater than 0.8.

[0014] Optionally, the dynamic adjustment of the unloading strategy in step S4 includes a tiered exception handling mechanism: Level 1 anomaly handling: When a single indicator slightly exceeds the limit, the subsequent cutting order of the partition to which the anomaly point belongs is automatically adjusted; Level 2 anomaly handling: When two or more indicators exceed the standard, suspend all cutting operations adjacent to the anomaly point for 5-10 minutes; Level 3 anomaly handling: When the strain at a critical node reaches more than 80% of the yield strain or the mid-span displacement exceeds 80% of the design allowable value, all cutting operations shall be stopped immediately.

[0015] Optionally, in step S5: The continuous monitoring period shall not be less than 72 hours, and the monitoring frequency shall be: once every 5 minutes in the first 1-2 hours, once every 30 minutes in the 3rd-24th hours, and once every 2 hours on the second day; The conditions for dismantling the support system are: the mid-span displacement change is less than 1 mm within 24 consecutive hours, the stress fluctuation amplitude of all key measuring points is less than ±5% of its final stable value, and the change of the structural fundamental frequency is less than 2% of the test value before unloading.

[0016] In summary, this application includes at least one of the following beneficial technical effects: This invention utilizes a multi-source sensor network for real-time monitoring and data analysis, combined with a tiered early warning and anomaly handling mechanism, to proactively identify and intervene in stress concentration and deformation risks during the unloading process, thereby effectively ensuring structural safety.

[0017] Furthermore, based on structural modal identification and finite element simulation, unloading pre-design was carried out to match the unloading strategy with the structural mechanical properties. By dynamically adjusting the cutting parameters through real-time data, precise adaptive control of trusses with different spans and forms was achieved.

[0018] Finally, the traditional gas cutting process was combined with an intelligent decision-making platform. Data-driven methods provided clear operating instructions and parameter guidance, simplifying human judgment in complex working conditions, making on-site construction more standardized and coordinated, and improving the reliability and efficiency of operations. Attached Figure Description

[0019] Figure 1 A flowchart of an unloading method for a super high-rise large-span transfer truss according to the present invention is provided; Figure 2 A schematic diagram showing the arrangement of deformation observation points; Figure 3 A schematic diagram of the supporting frame. Detailed Implementation

[0020] 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.

[0021] like Figure 1 As shown, the present invention proposes an unloading method for a super high-rise, large-span transfer truss, which includes the following steps: S1. Identify the truss structure modes, determine the stress redistribution path during the unloading process based on finite element simulation, and design the corresponding cutting guide line; S2. Deploy a multi-source sensor network at key nodes, support points and cutting areas of the truss to establish a real-time data acquisition and transmission system. S3. According to the pre-designed cutting guide line and partitioning sequence, use gas cutting to perform graded and partitioned unloading, and dynamically adjust the cutting parameters based on real-time monitoring data; S4. Based on the fusion analysis of multi-source sensor data, the structural status is evaluated in real time, and the unloading strategy is dynamically adjusted according to the evaluation results; S5. After unloading, continuously monitor the structure and remove the support system after confirming that the structure is stable.

[0022] In this embodiment, the pre-design includes: modal identification to determine partitions A, B, and C; finite element analysis to design a cutting guide line with a curvature radius of 1200 mm; and thermal analysis to determine the heat-affected zone control target as 35 ± 5 mm.

[0023] Monitoring deployment: Deploy a network of sensors including strain, displacement, pressure, temperature and vibration sensors, build a real-time data platform, and set a load non-uniformity coefficient threshold of 1.15 and a displacement deviation rate threshold of 20%.

[0024] Unloading execution: Propane gas cutting is used, with initial parameters set at oxygen pressure of 0.55 MPa and cutting speed of 170 mm / min. Cutting is performed cyclically in an ABC sequence, and the single cutting depth and cutting speed are dynamically adjusted based on the real-time monitored load transfer rate and heat-affected zone width.

[0025] Dynamic control: The platform assesses the structural status in real time, triggering two Level 1 warnings (automatic order adjustment) and one Level 2 warning (partial 8-minute pause), but no Level 3 warning is triggered.

[0026] Post-unloading monitoring and dismantling: After unloading, continuous monitoring for 72 hours, and once the data meets the stability standard, the support frame is dismantled in stages and symmetrically.

[0027] The entire unloading process resulted in smooth structural deformation, and the final state matched the design expectations well.

[0028] like Figure 2 and Figure 3 As shown, the unloading method also includes structural modal identification in step S1; as one implementation, the structural modal identification includes obtaining the first three vertical bending modes of the structure through an environmental excitation method, with a frequency identification range of 0.5-10Hz; the structure is divided into unloading regions with different sensitivity levels based on the modal amplitude, wherein the region with a modal amplitude greater than 0.7 is defined as a high-sensitivity region; the finite element simulation adopts a three-dimensional solid-beam hybrid model, and the constitutive model of the supporting steel plate adopts a bilinear kinematic hardening model with an elastic modulus of 2.06×105MPa and a yield strength of 345MPa; In step S1, the cutting guide line is designed as a continuous smooth curve with a radius of curvature controlled within the range of 500-2000 mm. Based on the thermo-coupling pre-analysis, the target width of the heat-affected zone is determined to be 25-45 mm. The heat-affected zone is defined as the area with a temperature higher than 250℃. Step S1 is explained in detail below: In this embodiment, for a steel truss with a span of 45 meters, on-site modal testing was first conducted. Ten accelerometers were evenly arranged on the lower chord of the truss, and 35 minutes of vibration data were collected using the environmental excitation method at a sampling frequency of 200Hz. Analysis revealed that the first three vertical bending frequencies of the structure were 1.2Hz, 3.8Hz, and 7.5Hz. Based on the first mode shape, the mid-span region with a mode shape amplitude greater than 0.7 was designated as the high-sensitivity region A, the region with amplitudes between 0.4 and 0.7 was designated as the medium-sensitivity region B, and the remainder as the low-sensitivity region C. Subsequently, a finite element model was established to simulate the entire unloading process. The supporting steel plate thickness was 30mm, and the elastic modulus of the material model was defined as 2.06 × 10⁻⁶. The yield strength is 345 MPa. Simulation results show that the principal stress traces are arc-shaped near the support point during unloading. Based on this, an arc-shaped cutting guide line with a radius of curvature of 800 mm was designed on the support steel plate. Through thermo-mechanical coupling analysis, it is predicted that the width of the heat-affected zone is approximately 32 mm at a cutting speed of 180 mm / min, which meets the control requirements.

[0029] like Figure 2 As shown, the unloading method also includes the multi-source sensor network mentioned in step S2. In one embodiment, the multi-source sensor network includes strain sensors, displacement sensors, pressure sensors, temperature sensors, and vibration sensors. The strain sensors are arranged at the support of the lower chord of the truss, at the mid-span, and at the neutral axis position of the cross-section at 1 / 4 of the span, with a sampling frequency of 1Hz static and 200Hz dynamic. The temperature sensors include K-type thermocouples arranged around the cutting point at distances of 10mm, 20mm, and 30mm from the cutting line, and an infrared thermal imager mounted above the cutting area, with a frame rate of 5-10Hz. Step S2 is described in detail below: In this embodiment, 20 strain gauges are deployed at key nodes in designated areas A, B, and C, with a static sampling frequency of 1Hz. Prisms are installed directly above the five main support points, and displacement monitoring is performed using a total station at a sampling frequency of 1Hz. A pressure sensor with a range of 500kN is installed on the top of each support frame. K-type thermocouples are implanted around each cutting point at distances of 10mm, 20mm, and 30mm from the preset cutting line. An infrared thermal imager is mounted above the truss, with a monitoring frame rate of 8Hz. All sensors are connected to the field data acquisition station via a wired network, and the data is then uploaded to a cloud analysis platform in real time via fiber optic cable. The platform software performs a data fusion calculation every 10 seconds, outputting indicators such as load non-uniformity coefficient and displacement deviation rate in real time, and dynamically updating and displaying them in a 3D graphical interface.

[0030] like Figure 2 and Figure 3As shown, the unloading method also includes gas cutting in step S3; as one embodiment, the gas cutting method uses propane as fuel gas, and the oxygen purity is not less than 99.5%; the nozzle model is selected according to the thickness of the supporting steel plate: nozzle No. 2 is used when the steel plate thickness is 20-40mm, and nozzle No. 3 is used when the thickness is 40-60mm; the initial cutting parameters are set as follows: oxygen pressure 0.5-0.7MPa, propane pressure 0.05-0.08MPa, cutting speed 150-200mm / min; The dynamic adjustment of cutting parameters in step S3 includes: adjusting the single cutting depth according to the real-time monitored load transfer rate: when the load transfer rate is greater than 50 kN / step, the single cutting depth is 5 mm; when the load transfer rate is less than 20 kN / step, the single cutting depth is 10 mm; adjusting the cutting speed according to the width of the heat-affected zone monitored by the infrared thermal imager: when the width of the heat-affected zone is greater than 40 mm, the cutting speed is increased by 20-50 mm / min; when it is less than 30 mm, the cutting speed is decreased by 20-50 mm / min; the surface roughness is controlled by adjusting the nozzle height and oxygen flow rate, with a target roughness Ra of 12.5-25 μm. Finally, step S3 also includes melting stage control: when the remaining thickness of the steel plate is 1 / 3 of the total thickness, the process transitions to the melting stage; during the melting stage, the cutting nozzle angle is tilted to 70-80 degrees, and the cutting speed is reduced to 100-150 mm / min; the melting speed is controlled so that the mid-span displacement rise rate does not exceed 0.5 mm / min. Step S3 is explained in detail below: In this embodiment, propane gas was used, and the oxygen purity was 99.6%. Based on the 30mm steel plate thickness, a No. 2 cutting nozzle was selected. The initial oxygen pressure was set to 0.6MPa, and the propane pressure to 0.065MPa. After cutting began, the process was repeated cyclically from zones A to C. In the first round of cutting, one support point was selected in each zone, and the cutting depth was set to 8mm. During the cutting process, the infrared thermal imager showed that the width of the heat-affected zone at a certain measuring point in zone A reached 38mm. The data platform automatically issued a command to increase the cutting speed at that point from the initial 180mm / min to 200mm / min. When the system detected a load transfer rate of 55kN / step at another measuring point in zone B, it immediately commanded the cutting depth at that point in the next round to be adjusted to 5mm. When approximately 10mm of steel plate thickness remained, the process transitioned to the melting stage. The operator adjusted the nozzle angle to 75 degrees and reduced the speed to 120mm / min until the steel plate was completely melted and detached.

[0031] like Figure 2 and Figure 3As shown, the unloading method also includes real-time evaluation in step S4; as one implementation, the real-time evaluation includes calculating the following indicators: load distribution unevenness coefficient at each support point, deviation rate between mid-span displacement and calculated value, and ratio of strain to yield strain at key points; setting early warning thresholds: triggering an early warning when the load distribution unevenness coefficient is greater than 1.15, the displacement deviation rate is greater than 20%, and the strain ratio is greater than 0.8; The dynamic adjustment unloading strategy described in step S4 includes a tiered anomaly handling mechanism: Level 1 anomaly handling: When a single indicator slightly exceeds the limit, the subsequent cutting sequence of the partition to which the anomaly point belongs is automatically adjusted; Level 2 anomaly handling: When two or more indicators exceed the limit, all cutting operations adjacent to the anomaly point are suspended for 5-10 minutes; Level 3 anomaly handling: When the strain at a critical node reaches more than 80% of the yield strain or the mid-span displacement exceeds 80% of the design allowable value, all cutting operations are immediately stopped. Step S4 is explained in detail below: In this embodiment, when the unloading reached approximately 50% of the total depth, the data platform showed that the load reduction values ​​of two adjacent measuring points in area A differed by more than 35% of their average value. The platform's decision support module immediately and automatically adjusted the subsequent cutting sequence, advancing the order of measuring points with slower load reduction. Subsequently, while cutting a measuring point in area B, the system simultaneously detected that the displacement deviation rate and the width of the heat-affected zone at that point exceeded the standard, triggering a level-two warning. Based on the platform alarm and the on-site situation, the commander ordered a halt to the cutting operation at that point and the two adjacent points for 8 minutes. During the halt, the data stabilized, and operations resumed after confirmation, without triggering a level-three warning.

[0032] like Figure 2 and Figure 3 As shown, the unloading method also includes continuous monitoring in step S5; as one implementation, the continuous monitoring time is not less than 72 hours, and the monitoring frequency is: once every 5 minutes in the first 1-2 hours, once every 30 minutes in the third-24 hours, and once every 2 hours on the second day; The conditions for dismantling the support system are: the mid-span displacement change is less than 1 mm within 24 consecutive hours, the stress fluctuation amplitude of all key measuring points is less than ±5% of its final stable value, and the change of the structural fundamental frequency is less than 2% of the test value before unloading. The following is a detailed explanation of step S5: In this embodiment, after all cutting and unloading were completed, all monitoring systems were kept running continuously. For the first 2 hours, complete data was recorded every 5 minutes; for the following 22 hours, data was recorded every 30 minutes; and on the second day, data was recorded every 2 hours. By the 60th hour of monitoring, data showed that the mid-span displacement changed by 0.8 mm within 24 hours, stress fluctuations at all key points were within ±4%, and rapid modal testing showed a fundamental frequency change of 1.5%. Once all stability conditions were met, the support frame was dismantled. The dismantling process followed a symmetrical and synchronous principle from the center to the edges. After dismantling each frame, it was left to stand for 2 hours for observation; only after confirming no abnormalities were any observed, the next frame was removed.

[0033] The above specific embodiments are merely several optional embodiments of the present invention. Based on the technical solutions of the present invention and the relevant teachings of the above embodiments, those skilled in the art can make various alternative improvements and combinations to the above specific embodiments.

Claims

1. A method for unloading a super high-rise, large-span transfer truss, characterized in that, The uninstallation method includes the following steps: S1. Identify the truss structure modes, determine the stress redistribution path during the unloading process based on finite element simulation, and design the corresponding cutting guide line; S2. Deploy a multi-source sensor network at key nodes, support points and cutting areas of the truss to establish a real-time data acquisition and transmission system. S3. According to the pre-designed cutting guide line and partitioning sequence, use gas cutting to perform graded and partitioned unloading, and dynamically adjust the cutting parameters based on real-time monitoring data; S4. Based on the fusion analysis of multi-source sensor data, the structural status is evaluated in real time, and the unloading strategy is dynamically adjusted according to the evaluation results; S5. After unloading, continuously monitor the structure and remove the support system after confirming that the structure is stable.

2. The unloading method for a super high-rise, large-span transfer truss according to claim 1, characterized in that, In step S1: The structural modal identification includes obtaining the first three vertical bending modes of the structure through an environmental excitation method, with a frequency identification range of 0.5-10Hz; The structure is divided into unloading regions with different sensitivity levels based on the modal amplitude, and the region with a modal amplitude greater than 0.7 is defined as the high sensitivity region. The finite element simulation adopts a three-dimensional solid-beam hybrid model, and the constitutive model of the supporting steel plate adopts a bilinear kinematic hardening model with an elastic modulus of 2.06×105MPa and a yield strength of 345MPa.

3. The unloading method for a super high-rise, large-span transfer truss according to claim 2, characterized in that, The cutting guide line designed in step S1 is a continuous smooth curve with a radius of curvature controlled within the range of 500-2000 mm; Based on the thermo-coupling pre-analysis, the target width of the heat-affected zone is determined to be 25-45 mm, and the heat-affected zone is defined as the area with a temperature higher than 250℃.

4. The unloading method for a super high-rise, large-span transfer truss according to claim 1, characterized in that, In step S2: The multi-source sensor network includes strain sensors, displacement sensors, pressure sensors, temperature sensors, and vibration sensors; The strain sensors are arranged at the support of the lower chord of the truss, at the mid-span and at the neutral axis position of the cross section at 1 / 4 span, and the sampling frequency is 1Hz for static and 200Hz for dynamic. The temperature sensor includes a K-type thermocouple arranged around the cutting point at a distance of 10mm, 20mm, and 30mm from the cutting line, and an infrared thermal imager mounted above the cutting area, with a frame rate of 5-10Hz.

5. The unloading method for a super high-rise, large-span transfer truss according to claim 1, characterized in that, In step S3: The gas cutting method uses propane as fuel, and the oxygen purity is not less than 99.5%. Select the cutting nozzle model according to the thickness of the supporting steel plate: use nozzle No. 2 when the steel plate thickness is 20-40mm, and nozzle No. 3 when the thickness is 40-60mm. The initial cutting parameters were set as follows: oxygen pressure 0.5-0.7 MPa, propane pressure 0.05-0.08 MPa, and cutting speed 150-200 mm / min.

6. The unloading method for a super high-rise, large-span transfer truss according to claim 1, characterized in that, The dynamic adjustment of cutting parameters in step S3 includes: The single cutting depth is adjusted according to the real-time monitored load transfer rate: when the load transfer rate is greater than 50kN / step, the single cutting depth is 5mm; when the load transfer rate is less than 20kN / step, the single cutting depth is 10mm. Adjust the cutting speed according to the width of the heat-affected zone monitored by the infrared thermal imager: when the width of the heat-affected zone is greater than 40mm, increase the cutting speed by 20-50mm / min; when it is less than 30mm, decrease the cutting speed by 20-50mm / min. The surface roughness is controlled by adjusting the nozzle height and oxygen flow rate, with a target roughness Ra of 12.5-25 μm.

7. The unloading method for a super high-rise, large-span transfer truss according to claim 6, characterized in that, Step S3 also includes melting stage control: When the steel plate is cut to a remaining thickness of 1 / 3 of its total thickness, the melting stage begins. During the melting stage, the cutting nozzle angle is tilted to 70-80 degrees, and the cutting speed is reduced to 100-150 mm / min; Control the melting rate so that the mid-span displacement rise rate does not exceed 0.5 mm / min.

8. The unloading method for a super high-rise, large-span transfer truss according to claim 1, characterized in that, In step S4: The real-time assessment includes calculating the following indicators: load distribution unevenness coefficient at each support point, deviation rate between mid-span displacement and calculated value, and ratio of strain to yield strain at key points. Set warning thresholds: trigger a warning when the load distribution unevenness coefficient is greater than 1.15, the displacement deviation rate is greater than 20%, and the strain ratio is greater than 0.

8.

9. A method for unloading a super high-rise, large-span transfer truss according to claim 8, characterized in that, The dynamic adjustment of the unloading strategy in step S4 includes a tiered exception handling mechanism: Level 1 anomaly handling: When a single indicator slightly exceeds the limit, the subsequent cutting order of the partition to which the anomaly point belongs is automatically adjusted; Level 2 anomaly handling: When two or more indicators exceed the standard, suspend all cutting operations adjacent to the anomaly point for 5-10 minutes; Level 3 anomaly handling: When the strain at a critical node reaches more than 80% of the yield strain or the mid-span displacement exceeds 80% of the design allowable value, all cutting operations shall be stopped immediately.

10. The unloading method for a super high-rise, large-span transfer truss according to claim 1, characterized in that, In step S5: The continuous monitoring period shall not be less than 72 hours, and the monitoring frequency shall be: once every 5 minutes in the first 1-2 hours, once every 30 minutes in the 3rd-24th hours, and once every 2 hours on the second day; The conditions for dismantling the support system are: the mid-span displacement change is less than 1 mm within 24 consecutive hours, the stress fluctuation amplitude of all key measuring points is less than ±5% of its final stable value, and the change of the structural fundamental frequency is less than 2% of the test value before unloading.

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