Primary and secondary double-control grading unloading device and method suitable for large-span suspended heavy-load open-web truss

Abstract

The invention belongs to the technical field of open-web truss unloading, and particularly relates to a primary-secondary double-control grading unloading device and method suitable for a large-span suspended heavy-load open-web truss. The primary-secondary double-control grading unloading device comprises a grading control device, and the grading control device is integrated with a real-time monitoring system and a remote control platform; the real-time monitoring system is used for collecting monitoring data of the open-web truss in the unloading process in real time, and the remote control platform is used for receiving the monitoring data; the main and secondary double-control unloading device comprises a hydraulic jack and a sand box, and the hydraulic jack serves as a main control unloading component and is used for actively controlling step-by-step unloading force; the sand box serves as a secondary control unloading component and is used for auxiliary control of step-by-step unloading displacement. The hydraulic jack actively controls step-by-step unloading force, and the sand box assists in controlling step-by-step unloading displacement, so that double index control of load and displacement is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of unloading of open-web trusses, and particularly relates to a primary-secondary dual-control hierarchical unloading device and method applicable to large-span suspended heavy open-web trusses. Background Art

[0002] In the structural design of large-span buildings, reinforced concrete laminated open-web trusses are usually used as design carriers with both structural functions and aesthetic effects. During the construction process of layer-by-layer loading, the open-web truss relies on the support frame as a temporary support means until it finally forms a self-bearing system. During the construction stage of gradually unloading the support frame, the stress mode of the open-web truss gradually changes from temporary support to self-bearing until the overall self-bearing stress state is fully realized. Therefore, the index control during the unloading process is crucial and directly related to the overall quality and safety of the main structure.

[0003] The existing structural unloading methods mainly include the screw unloading method, the sand box unloading method, and the jack unloading method, but each has its limitations: The screw unloading method has simple equipment, convenient operation, controllable unloading rate, and can achieve hierarchical unloading. However, due to the low bearing capacity of the screw and the dependence on manual operation, the synchronous controllability is poor, and it is difficult to meet the high-precision unloading requirements.

[0004] The sand box unloading method has simple equipment structure, convenient operation, can achieve controllable unloading rate and hierarchical unloading, and has the advantages of less later maintenance and environmental friendliness. However, the sand box is greatly affected by humidity changes. If not properly protected, the sand is prone to getting damp and caking. In addition, the operation of the sand box depends on manual labor, which is restricted by human factors, and the actual use effect may not be ideal.

[0005] The jack unloading method has a large bearing capacity and a controllable unloading rate, and realizes synchronous control through an integrated control system of liquid, machine, electricity, and computer, with good synchronism. However, when the number of unloading points is large, this method requires a large number of equipment, resulting in a high one-time equipment investment cost.

[0006] In summary, these traditional methods have their own advantages and disadvantages at the technical level, but in the unloading construction application of large-span suspended heavy open-web trusses, there are certain technical difficulties and they cannot fully meet the actual construction requirements. Therefore, there is an urgent need for an innovative unloading scheme that can take into account the requirements of high precision, safety, and economy and effectively cope with the challenges of complex construction environments. Summary of the Invention

[0007] Object of the Invention: The object of the present invention is to provide a primary-secondary dual-control hierarchical unloading device and method applicable to large-span suspended heavy open-web trusses in view of the deficiencies of the prior art, which can effectively control the deformation and load during the truss unloading process and achieve remote real-time control of the unloading.

[0008] Technical solution: The primary and secondary dual-control hierarchical unloading device applicable to large-span suspended heavy-duty open-web trusses of the present invention includes:

[0009] A hierarchical control device, which integrates a real-time monitoring system and a remote control platform. The real-time monitoring system is used to collect monitoring data of the open-web truss during the unloading process, and the remote control platform is used to receive the monitoring data; and

[0010] A primary and secondary dual-control unloading device, which includes hydraulic jacks and sand boxes. The hydraulic jacks serve as the main control unloading components for actively controlling the step-by-step unloading force; the sand boxes serve as the secondary control unloading components for assisting in controlling the step-by-step unloading displacement;

[0011] Among them, the remote control platform processes the monitoring data collected by the real-time monitoring system using a data fusion algorithm to obtain hierarchical unloading parameters, and generates corresponding control instructions based on the hierarchical unloading parameters to dynamically adjust the unloading force of the hydraulic jacks and / or the sand discharge volume of the sand boxes, so as to achieve dual-index control of the load and displacement during the unloading process of the open-web truss.

[0012] To further improve the above technical solution, the real-time monitoring system includes a sensing system and a monitoring cloud platform; the sensing system is used to collect real-time monitoring data of key parts of the open-web truss, including reinforcing bar strain gauges, differential pressure static level gauges, and vibrating wire surface crack gauges; the reinforcing bar strain gauges are configured to measure the stress changes of key parts of the open-web truss, the differential pressure static level gauges are configured to monitor the deformation of the open-web truss, and the vibrating wire surface crack gauges are configured to monitor the surface crack width of the open-web truss; the monitoring cloud platform is used to receive and integrate the data collected by the sensing system and generate a visual data panel.

[0013] Furthermore, the hydraulic jacks include a hydraulic pump source, an oil cylinder, standard oil pipes, hydraulic sensors, and a hydraulic controller. Among them, the hydraulic pump source is used to provide hydraulic oil power, the standard oil pipes connect the hydraulic pump source and the oil cylinder to deliver hydraulic oil to the oil cylinder to drive the telescopic movement of the oil cylinder to apply the unloading force; the hydraulic sensors include a pressure sensor and a stroke sensor. The pressure sensor is installed in the hydraulic oil pipeline to collect the hydraulic pressure data in the hydraulic oil pipeline, and the stroke sensor is installed on the oil cylinder to collect the stroke displacement data of the piston rod of the oil cylinder; the hydraulic sensors transmit the collected pressure and stroke data to the hydraulic controller, and the hydraulic controller receives and responds to the control instructions of the remote control platform to adjust the unloading load by controlling the unloading force of the hydraulic pump source.

[0014] Furthermore, the sand box includes: a bottom plate, a waist plate, and a top plate distributed in sequence from bottom to top, an outer cylinder arranged between the bottom plate and the waist plate, and an inner cylinder arranged between the waist plate and the top plate; the outer cylinder is provided with a plurality of sand unloading ports along the circumference, and each sand unloading port is provided with an intelligent sand unloading component, which is configured to respond to the control instructions of the remote control platform, intelligently control the opening and closing of the sand unloading port, realize automatic sand unloading, and assist in controlling the unloading displacement.

[0015] Furthermore, the inner cylinder is provided with a pressure differential static level for monitoring the real-time changes in the height of the sand box, and feeding back the data to the remote control platform for graded unloading parameter regulation to achieve closed-loop control of displacement; the intelligent sand unloading component is an intelligent bolt-driven mechanical arm or a motor-driven piston rotary sand dredging component.

[0016] Furthermore, the remote control platform is configured with a monitoring and early warning mode and a monitoring and alarm mode, which are triggered and executed based on a preset total number of unloading levels and the design value, early warning value and alarm value corresponding to each level of unloading parameters; when the real-time monitoring data does not reach the early warning value, the remote control platform maintains the current hierarchical unloading parameters unchanged and continues to execute the unloading process; when the real-time monitoring data exceeds the early warning value but is less than the alarm value, the remote control platform enters the monitoring and early warning mode, adjusts the hierarchical unloading parameters through the data fusion algorithm, and continues to execute the unloading process based on the adjusted hierarchical unloading parameters; when the real-time monitoring data exceeds the alarm value, the remote control platform immediately enters the monitoring and early warning mode, and performs the following operations: increase the monitoring frequency, stop the unloading process, start the bearing capacity verification and safety assessment procedures, perform bearing capacity verification and safety assessment on the hollow truss according to the structural design document, and decide whether to continue the next stage of unloading construction according to the bearing capacity verification and safety assessment results and the requirements of the structural design document.

[0017] The method for unloading a hollow truss by using the primary and secondary double-control graded unloading device suitable for a large-span suspended heavy-load hollow truss comprises the following steps:

[0018] S1: After the pre-unloading conditions are met, the hydraulic jack is hoisted to the top surface of the supporting frame beam and located on both sides of the sand box, and the oil cylinder is started to tighten the supporting bottom plate to establish the initial supporting state;

[0019] S2: Conduct unloading simulation drills, perform simulations of the operation flow of each process, and optimize unloading parameters and operation flow based on the simulation results;

[0020] S3: According to the jacking force requirements for each stage of unloading, start each hydraulic jack to gradually lift the open-web truss to a stable state, and then control the sand box to unload sand to the predetermined value; during the sand unloading process, monitor the deformation of the open-web truss in real time. If the deformation reaches the warning value and the top of the sand box has not yet separated from the bottom surface of the open-web truss, stop the sand unloading operation, control the hydraulic jacks to fall synchronously, and support the open-web truss with the sand box to complete the unloading of the current stage;

[0021] S4: Monitor and collect various monitoring data during the unloading process of the open-web truss in real time, let the open-web truss stand still until it reaches a stable state, use a data fusion algorithm to process the monitoring data and evaluate the condition of the open-web truss, and dynamically adjust and determine the next-stage unloading parameters based on the evaluation results;

[0022] S5: Repeat steps S3 and S4 to complete the unloading construction stage by stage until the open-web truss forms a self-bearing force system; after the last stage of unloading is completed, remove the sand box and hydraulic jacks to complete the unloading construction.

[0023] Further, in step S4, use a data fusion algorithm to process the collected monitoring data to obtain a measured value after excluding environmental factor interference, compare the measured value with the designed value in the current-stage unloading parameters, and judge whether it is necessary to adjust the next-stage unloading parameters according to the comparison result. If it exceeds the warning value, based on the data fusion result and the mechanical calculation of the open-web truss, correct the subsequent stage-by-stage unloading parameters.

[0024] Further, the data fusion algorithm includes the following sub-steps:

[0025] S401: Perform time-domain segmentation processing on the monitoring data in the stable state and divide it into multiple data sets;

[0026] S402: Calculate the mean square error of each data set;

[0027] S403: Exhaustively group the data sets and perform data fusion processing according to the groups;

[0028] S404: Take two data sets as an example and use the minimum variance unbiased estimation method to perform data fusion calculation to obtain the minimum variance estimated value;

[0029] S405: Calculate the mean value according to the minimum variance estimated value at all times of each group combination to obtain the final minimum variance estimated value of each group combination;

[0030] S406: Calculate the overall mean value of the final minimum variance estimated values of all combinations as the measured value after excluding environmental factor interference;

[0031] S407: Compare the measured value with the designed value in the current stage unloading parameter. Determine whether it is necessary to adjust the next-stage unloading parameter according to the comparison result. If it exceeds the warning value, correct the subsequent stage-by-stage unloading parameters based on the data fusion result and the mechanical calculation of the vierendeel truss.

[0032] Further, the correcting the subsequent stage-by-stage unloading parameters based on the data fusion result and the mechanical calculation of the vierendeel truss includes: substituting the stress data in the monitoring data into the data fusion algorithm for processing, and calculating the current top column support force to quantify the actual load-bearing situation of the structure; based on the current top column support force, calculating the percentage of the total remaining support force of the structure after the current stage-by-stage unloading to evaluate the current unloading degree; calculating the deviation between the actual remaining support force percentage and the target value in the design document to evaluate the gap between the actual unloading effect and the predetermined target; judging whether the actual unloading support force is too large or too small according to the positive or negative of the deviation value; based on the evaluation result, making an intelligent decision on the unloading parameter adjustment strategy, including: when the actual unloading support force is too small and there is a deformation warning, increasing the unloading amount of the new unloading level and correspondingly correcting the subsequent unloading parameters; when the actual unloading support force meets the standard or is too large, keeping the next-stage unloading parameter unchanged, and recalculating and updating the warning value and the alarm value to adapt to the new structural state.

[0033] Beneficial effects: Compared with the prior art, the advantages of the present invention are as follows: 1. The primary and secondary dual-control stage-by-stage unloading device provided by the present invention can effectively control the load and deformation during the unloading process, ensuring the safety and stability of the structure. The hydraulic jack, as the active control device, provides the stage-by-stage unloading force for stage-by-stage unloading as the main control index; the sand box assists in controlling the unloading displacement as the secondary control index. The two devices work together, not only providing double guarantees for the unloading process of the construction structure, making the unloading process more accurate and controllable, but also saving costs through reasonable division of labor.

[0034] 2. The stage-by-stage control device provided by the present invention supports remote real-time control, which can provide a basis for high-precision unloading operations and effectively avoid the uncertainty and errors caused by human factors. In addition, by reducing manual operations, the potential safety hazards during the construction process are greatly reduced. The unloading parameter control algorithm in the device adopts a data fusion method to replace the traditional average value solving method. While maximizing the utilization of monitoring data, it can effectively cope with the time-varying complexity of the construction environment (such as factors like temperature, humidity, wind direction, environmental vibration, etc.), thereby significantly improving the accuracy of data collection and fully mining the effective information in the monitoring data.

[0035] 3. The device and method of the present invention cooperate with each other. Through the monitored data with remote real-time feedback, the algorithm dynamically predicts and adjusts the unloading parameters of the hydraulic jacks and sand boxes according to the current stress and deformation conditions of the truss, forming a closed-loop control. During the entire unloading process, no manual intervention is required, ensuring the accuracy and reliability of the key steps until the unloading task is successfully completed. Description of the Drawings

[0036] Figure 1 It is a flowchart of the data fusion algorithm for eliminating the influence of environmental factors of the present invention;

[0037] Figure 2 It is a measured time history diagram generated by simulation in Embodiment 1 of the present invention;

[0038] Figure 3 It is a sectional view of the support where the primary and secondary dual-control hierarchical unloading device of the present invention is installed;

[0039] Figure 3 In the figure: 10. Sand box; 20. Hydraulic jack; 30. Conversion ring beam; 40. Support frame beam; 50. Support column; 6. Intelligent robotic arm; 8. Differential static level;

[0040] Figure 4 It is a general layout plan of the hierarchical unloading device of the open-web truss in Embodiment 2 of the present invention;

[0041] Figure 5 It is a schematic diagram of automatic sand unloading of the sand box in Embodiment 2 of the present invention;

[0042] Figure 5 In the figure: 1. Inner cylinder; 2. Outer cylinder; 3. Bolt for sand unloading hole; 4. Load-bearing plate; 5. Bottom plate of sand unloading cylinder; 6. Intelligent robotic arm; 7. Waist plate; 8. Differential static level;

[0043] Figure 6 It is a plan layout diagram of the monitoring points at the top of the conversion column and support column in Embodiment 2 of the present invention;

[0044] Figure 7 It is a schematic diagram of the monitoring point arrangement of the support column in Embodiment 2 of the present invention;

[0045] Figure 8 It is a plan layout diagram of the monitoring points of the conversion ring beam in Embodiment 2 of the present invention;

[0046] Figure 9 It is a schematic diagram of the monitoring point arrangement of the conversion ring beam in Embodiment 2 of the present invention;

[0047] Figure 10 It is a change curve of the mean square error of the monitoring data in Embodiment 2 of the present invention;

[0048] Figure 11This is the time history diagram of the mid-span deformation monitoring data of the conversion ring beam in Embodiment 2 of the present invention. Detailed implementation manners

[0049] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings, but the protection scope of the present invention is not limited to the described embodiments.

[0050] Embodiment 1: This embodiment illustrates the specific calculation steps of the data fusion algorithm provided by the present invention through numerical simulation, and its algorithm flow is as Figure 1 shown.

[0051] S1. First, perform the acquisition response simulation. Set the sampling frequency f = 1 Hz and the simulation duration to 600 seconds. Assume that the measured time history follows a normal distribution N(5, 0.25), and assume that the measured values are affected by harmonic interference caused by environmental factors. The harmonic satisfies the formula:

[0052]

[0053] That is, the amplitude is 0.05 mm and the period is 120 seconds. Then the final simulated response Z(t) = M(t) + H(t). The simulated time history is shown in Figure 2 .

[0054] According to the above measurement simulation formula, it can be calculated that the entire time history contains 600 data points. Set the length of the moving window to 30 data points and the step length to 15 data points. According to this setting, the time history data is divided into 39 segments, numbered from 1 to 39 in ascending order along the time axis.

[0055] S2. Substitute the data in each time window into the following variance calculation formula for processing:

[0056]

[0057] Where:

[0058]

[0059] A total of 39 groups of variances are calculated and denoted as where j = 1, 2,..., 39.

[0060] S3. Perform an exhaustive combination of the 39 segments of data to obtain groups of data combinations.

[0061] S4. Select the i-th and j-th groups of data from the combinations, where i, j = 1, 2,..., 39, and i ≠ j, i < j. Substitute the k-th data of each group into the following formula, k = 1, 2,..., 30

[0062]

[0063] Where, respectively represent the k-th data point corresponding to the i-th and j-th time windows, where K is a weight coefficient, and the calculation formula is as follows:

[0064]

[0065] According to the above two formulas, the minimum variance unbiased estimate value at the k-th moment is obtained

[0066] S5. Substitute the minimum variance unbiased estimate values at all moments under the i-j combination into the following formula for calculation to solve the average value of this combination

[0067]

[0068] S6. Repeat S4 and S5 to calculate the average minimum variance unbiased estimate values for each of the 741 groups of data combinations where i, j = 1, 2, …, 39, and i ≠ j, i < j. Substitute the of all combinations into the following formula to calculate the overall average minimum variance unbiased estimate value

[0069]

[0070] where i, j = 1, 2, …, 39, and i ≠ j, i < j.

[0071] Finally, the calculated is the measured value after excluding the interference of environmental factors.

[0072] The present invention provides a data fusion algorithm based on minimum variance unbiased estimation. By segmenting time windows, stationary data is regarded as independent sensor measurement values. The data fusion algorithm is used to comprehensively process each segment of data and then take its average value, minimizing the influence of the time-varying complexity of the construction environment (including factors such as environmental vibration, temperature, humidity, wind direction, etc.) on the measurement data, thereby significantly improving the accuracy and reliability of the measurement results.

[0073] Next, through a more detailed engineering application example, it will be illustrated how the data fusion algorithm of the present invention assists in the dynamic correction of unloading parameters and effectively excludes the interference caused by changes in the construction environment during actual staged unloading tasks.

[0074] Example 2: As Figure 3 shown, the primary-secondary dual-control staged unloading device provided by the present invention is composed of a sand box and a hydraulic jack, and is placed between the transfer beam of the open-web truss structure and the lower support structure (i.e., at the unloading support) to achieve precise control of the load and displacement during the unloading process. The overall layout is referred toFigure 4 According to the design of the support structure and truss structure in this embodiment, in order to fully meet the requirements of staged unloading, the number of sand boxes is set to eight, and they are precisely arranged at specific positions of support columns A, B, C, D, E, F, G, and H respectively.

[0075] The main equipment of the hydraulic jack automatic control unloading system is as shown in the following table:

[0076] Table 1 Hydraulic Jack Equipment Parameters

[0077]

[0078]

[0079] As Figure 5 shown, the sand box is designed to support the open-web truss transfer beam and is arranged in the middle position at the top of the temporary support frame column. A total of 8 sand boxes are set. The sand box consists of an inner cylinder 1 and an outer cylinder 2. The cylinder is designed to be circular, while the cylinder top plate 4, bottom plate 5, and waist plate 7 are all designed to be square. The sand discharge hole bolt 3 is used to control the sand discharge operation of the sand box. The specific structural parameters are calculated according to relevant structural design specifications. In the above technical solution, in order to ensure the automatic control of the sand box, the traditional method of manually screwing bolts is replaced by an intelligent bolt driving robotic arm 6. This robotic arm realizes the automatic opening and closing of the sand discharge port bolt through the sand box controller. In addition, a piston rotary sand dredging assembly driven by a motor can also be selected to further achieve automatic control. The differential static level 8 is used to monitor the sand discharge height of the sand box in real time and remotely transmit the sand box height data. This improvement supports the efficient automatic operation of the sand box sand discharge process, not only significantly improving the construction efficiency, but also effectively reducing the errors and potential safety hazards that may be caused by manual operations.

[0080] In this embodiment, according to the force characteristics of the open-web truss in the project, the actual site conditions, and the requirements of loading and unloading, following the principles of safety, economy, and reasonableness, the monitoring content and the number of measuring points are determined as follows: (1) 2 stress monitoring points and 2 deformation monitoring points at the top of the support frame column; (2) 2 stress monitoring points and 2 deformation monitoring points at the top of the transfer columns from the 8th floor to the 8Mth floor; (3) 2 deformation monitoring points, 2 stress monitoring points, and 2 crack monitoring points on the 9th floor transfer ring beam. Since the specific positions of the cracks cannot be determined through simulation calculations, the positions of the crack monitoring points can be adjusted according to the positions where cracks appear during unloading.

[0081] Figures 6 to 9 Shows the specific layout scheme of three types of monitoring points (stress monitoring points, deformation monitoring points, and crack monitoring points) in this embodiment. The names of the monitoring points in the figure are as follows: The triangular mark is the deformation (including deflection) monitoring point, the circular mark is the stress monitoring point, and the pentagram mark is the crack monitoring point.

[0082] Taking the support column A as an example, the deformation monitoring index at the bottom of the transfer beam is used for illustration, and the specific unloading parameters and indexes are shown in Table 2:

[0083] Table 2 Deformation monitoring index at the bottom of the transfer beam

[0084]

[0085]

[0086] The unloading process of the embodiment is as follows:

[0087] S1. After meeting the pre-unloading conditions, hoist the hydraulic jack to the top surface of the support frame beam (stiffened area) on both sides of the sand box at the top of the support frame column by an electric hoist. Ensure that the centroid of the jack is consistent with the centroids of the support frame beam and the transfer beam on the 9th floor, and get as close to the sand box as possible while ensuring the convenience of construction operations. Set a process gasket (polytetrafluoroethylene plate) on the top surface of the oil cylinder, start the oil cylinder, and tighten the support bottom plate. At the same time, arrange monitoring facilities according to the monitoring plan.

[0088] S101. Conduct acquisition tests one day in advance, and the test duration is 3 hours. When collecting data, set the time window length to 120 measurement points and the step length to 60 measurement points, and calculate the mean square error change curve of the sensor. It should be particularly noted that in order to avoid the interference of environmental vibration on the measured data, other construction processes should be suspended during the unloading construction.

[0089] In this embodiment, taking the measured value of the differential static level as an example to illustrate the specific application of the data fusion algorithm, and the processing flow of other types of monitoring data is the same as it. The parameters of the measuring equipment are as follows: the measuring range is 500mm, the sampling accuracy of the sensor during factory test is 0.05% FS, the sampling frequency is 1Hz, and the test results are as Figure 10 shown.

[0090] According to the design value, warning value and alarm value of the deformation at the bottom of the transfer beam in the design book of this embodiment, the numerical ranges of the above three types of indexes are 0.5 - 3mm. The test results show that the change of environmental factors can cause an error of up to 5% in the measured data. To ensure the safety of staged unloading, it is necessary to perform data fusion processing on the measured data to eliminate the interference of environmental factors and improve the measurement accuracy.

[0091] S2. Before the formal unloading construction, unloading simulation is required to practice each process to improve the operation proficiency. After confirming that each link is correct, the unloading construction can start.

[0092] S201. After the above preparations are completed, simulated unloading should be carried out, and the following main inspection contents should be clarified first:

[0093] (1) Whether the information transmission and feedback between the general commander and the operation groups, inspection groups, and monitoring groups at each unloading point are smooth and clear;

[0094] (2) Whether the monitoring equipment is operating normally;

[0095] (3) Whether the standby power supply is reliable;

[0096] (4) Whether the models and performances of each unloading device are consistent with the requirements of the plan;

[0097] (5) Whether the unloading operation meets the requirements of symmetry, step-by-step, and overall synchronization;

[0098] (6) Whether the unloading personnel at each post are proficient in relevant operation skills.

[0099] S202. Complete the simulated unloading according to the following steps:

[0100] (1) Determine the unloading position and the model of the jack: Confirm the unloading area and the model of the required hydraulic jack;

[0101] (2) Install the hydraulic pump source system and place the jack: Install the equipment according to the design requirements and adjust the position of the jack;

[0102] (3) Joint commissioning of the computer control system: Start and commission the computer control system to ensure the normal joint operation with the hydraulic pump source system and sensors;

[0103] (4) Input the jack lifting force: Input the designed jack lifting force value into the computer control system;

[0104] (5) Load and unload: Operate the jack to lift the load according to the predetermined force value;

[0105] (6) Discharge sand from the sand box: Discharge sand until the top of the sand box reaches the design target;

[0106] (7) Synchronous lowering of the jack: Slowly lower the jack to make the sand box bear the load again;

[0107] (8) Real-time monitoring: Real-time monitor the operating status and relevant data of each device, and input the data into the algorithm described in the technical plan to eliminate the interference of environmental factors;

[0108] (9) Step-by-step judgment: Judge whether the conditions for entering the next level of unloading are met according to the data analysis results;

[0109] (10) Complete the simulation: Complete all unloading processes in sequence according to the step-by-step unloading mode.

[0110] S203. After all simulation work is completed and confirmed to be correct, clear the irrelevant personnel from the site. After turning off the power supplies unrelated to the unloading equipment and monitoring equipment (to reduce interference to sensors), the unloading construction can begin.

[0111] S3. According to the jacking force requirements corresponding to the first-level unloading, synchronously start all jack cylinders. After jacking the transfer beam on the 9th floor to a stable state, synchronously unload the sand in each sand box to the predetermined target value, ensuring that the gap between the top of the sand box and the bottom of the transfer beam on the 9th floor remains within the range of 0.1 - 0.5 mm. If the deformation (downward stroke of the top of the sand box) of the bottom of the transfer beam on the 9th floor corresponding to the support column reaches the warning value and the top of the sand box still cannot be separated from the bottom of the transfer beam on the 9th floor, the sand unloading operation should be immediately stopped, and the top of the sand box should be maintained at the current elevation state. Subsequently, synchronously control the slow descent of the jack cylinders to make the sand box support the open-web truss again, thus completing the unloading at this level.

[0112] S4. Monitor and collect various data in real time, and let the open-web truss stand still to redistribute the internal forces of the main structure. After the open-web truss reaches a stable state, analyze the collected data, evaluate the stress and deformation conditions of the open-web truss, and accordingly adjust and determine the next-level unloading parameters. The next-stage unloading construction can only be carried out under the condition that the monitoring data is stable for 6 hours continuously and the standing time of the open-web truss is not less than 9 hours.

[0113] S401. Perform time-domain segmentation processing on the two-hour monitoring data of the collected stable open-web truss using a moving window. Taking the measured value of the differential pressure type hydrostatic level as an example, the processing flow of other types of monitoring data is the same. The current unloading level is the first level, and the measured value at support column A is taken. Its data time history is as Figure 11 shown. Set the number of sampling points X m in the time window = 120, and the number of step points X s between adjacent time windows = 60. Therefore, a total of 119 data segments are divided. The data segment of the i-th time window is represented by the subscript i and is named Di, i = 1, 2,..., 119.

[0114] S402. Using the data fusion method, first calculate the mean square error of each data set to obtain 119 sets of variance values, which are respectively denoted as Assume that the noise of each data segment follows a Gaussian distribution and the mean value is the true value Then each segment of observed data satisfies

[0115] S403. Exhaustively combine different two sets of data from the 119 data sets in sequence and perform data fusion according to the grouping. A total of sets of combined fusion calculations are required.

[0116] S404. Taking the combination D1 + D2 as an example, perform data fusion processing using unbiased estimation. Take the k-th data point and in two time windows respectively, k = 1, 2,..., 120, and substitute them into the following formula to calculate the estimated value after data fusion

[0117]

[0118] The above formula gives an unbiased estimate of the measured value. At this time, the mean square error of the estimated value is:

[0119]

[0120] The calculation formula for the weight coefficient K is:

[0121]

[0122] In this example, the variances corresponding to the two time windows are

[0123] For the 120 sampling points within the time window, it is necessary to calculate 120 times to obtain the minimum variance estimation time history of the combination D1+D2. The minimum variance estimated value of the combination is solved according to the following formula:

[0124]

[0125] S405. Repeat the steps of S404, and 7021 groups of minimum variance estimated values are calculated, which are respectively represented by , where and i≠j and i<j

[0126] S406. Substitute the calculation results of S405 into the following formula to solve the overall minimum variance estimated value:

[0127]

[0128] Finally, the minimum variance estimated value of the beam bottom deformation at this measuring point under the two-hour steady state is calculated as

[0129]

[0130] S407. The current unloading level is the first level. Taking support column A as an example, according to Table 2, the design parameters are the design value of the beam bottom deformation warning value alarm value

[0131] Compare the calculation results of S406 with the design parameter values: The obtained estimated value is less than the design value. Therefore, this staged unloading meets the safety conditions and the second staged unloading process can be directly carried out.

[0132] During the unloading process of this embodiment, no situation exceeding the warning value occurred; to fully illustrate the calculation method for updating the unloading parameters, assume that it is now in the stage of completing the first-level unloading, and the minimum variance estimated value of the deformation at the bottom of the transfer beam calculated in S407 is greater than the warning value and less than the alarm value. At this time, the stress data collected is substituted into the data fusion process of S401 - S406, and the minimum variance estimated value of the current column top support force after eliminating the interference of environmental factors is calculated through formulas (6) and (7)

[0133]

[0134] In the formula: Nc: current column top support force (kN); Average stress monitored by the steel bar meter (kN / mm 2 ); k j : Calibration coefficient of the j-th steel bar meter (kN / Hz 2 ); f ji : Monitoring frequency of the j-th steel bar meter (Hz); f j0 : Initial frequency after installation of the j-th steel bar meter (Hz); A js : Cross-sectional area of the j-th steel bar meter (mm 2 ); E C : Elastic modulus of concrete (kN / mm 2 ); E s : Elastic modulus of steel bar (kN / mm 2 ); A C : Cross-sectional area of concrete (mm 2 ); A S : Total cross-sectional area of steel bars (mm 2 ).

[0135] Substitute into formula (8) to obtain the percentage α1 of the column top support force after the current stage of unloading is completed,

[0136]

[0137] Substitute α1 into formula (9) to obtain the difference Δα1 between the column top support force after the current unloading is completed and the designed support force,

[0138]

[0139] Similar to the above, hypothetical working conditions are used to illustrate two different parameter correction situations. In the first working condition, let α1 = 85%. At this time, Δα1 = 0.85 - 0.8 = 5% > 0. According to the technical solution, a new unloading level needs to be added. The newly added percentage of stepwise unloading is equal to the remaining percentage of the supporting force at this level plus 50% of the unloading percentage of the next level. The total percentage of the column top supporting force β unloaded under the newly added i + 1th stepwise working condition is calculated by Equation (10).

[0140]

[0141] Therefore, the design value of the remaining column top supporting force after the completion of the newly added i + 1th stepwise unloading is substituted into Equation (11) for calculation.

[0142]

[0143] According to the relevant structural design specifications, calculate the beam bottom deformation and crack indexes of the newly added step, and update the stepwise unloading parameters and detection indexes of support A. See Table 3 for details.

[0144] Table 3 Stepwise unloading parameters and deformation monitoring indexes of support column A after updating in working condition 1

[0145]

[0146] In the second working condition, assume that after the completion of the current stepwise unloading, the percentage of the column top supporting force of support column A is α1 = 75%. At this time, Δα1 = 0.75 - 0.8 = -5%, that is, Δα1 < 0. According to the technical solution, this situation indicates that the current unloading supporting force percentage is less than the design requirement, and there is no need to update the unloading parameters. In this case, only the deformation monitoring indexes of the next level need to be calculated. Refer to the relevant structural design specifications, recalculate the conversion beam bottom deformation and crack indexes, and obtain the updated stepwise unloading parameters and deformation detection indexes of support column A. See Table 4 for details.

[0147] Table 4 Stepwise unloading parameters and deformation monitoring indexes of support column A after updating in working condition 2

[0148]

[0149] S5. Repeat steps S3 and S4 to complete the unloading construction step by step, and finally make the open-web truss form a self-bearing system. During the last step, monitor and collect various data in real time. After the open-web truss is stable (that is, the mean value change range of the monitoring data within 24 hours does not exceed 5%), conduct data analysis and condition assessment with reference to the design book and structural design specifications. After completion, remove the sand box and hydraulic jacks, indicating that the entire unloading construction is successfully completed.

[0150] As described above, although the present invention has been shown and described with reference to specific preferred embodiments, it should not be construed as a limitation on the present invention itself. Various changes in form and detail may be made thereto without departing from the spirit and scope of the present invention as defined by the appended claims.

Claims

1. The primary and secondary double-control graded unloading device is suitable for large-span suspended heavy-loaded hollow trusses, which is characterized by: include: A hierarchical control device, wherein the hierarchical control device is integrated with a real-time monitoring system and a remote control platform, wherein the real-time monitoring system is used to collect monitoring data of the open-web truss during unloading in real time, and the remote control platform is used to receive the monitoring data; and a primary and secondary dual-control unloading device, the primary and secondary dual-control unloading device comprising a hydraulic jack and a sand box, the hydraulic jack being a primary control unloading component for actively controlling the step-by-step unloading force; the sand box being a secondary control unloading component for assisting in controlling the step-by-step unloading displacement; Among them, the remote control platform adopts a data fusion algorithm to process the monitoring data collected by the real-time monitoring system to obtain the graded unloading parameters, and generates corresponding control instructions based on the graded unloading parameters to dynamically adjust the unloading force of the hydraulic jack and / or the sand unloading amount of the sand box, so as to achieve dual indicator control of load and displacement during the unloading process of the hollow truss.

2. The primary and secondary double-control graded unloading device suitable for large-span suspended heavy-loaded hollow trusses according to claim 1 is characterized in that: The real-time monitoring system includes a sensor system and a monitoring cloud platform; The sensing system is used to collect real-time monitoring data of key parts of the hollow truss, including a steel bar strain gauge, a pressure differential static level and a vibrating wire surface crack gauge; the steel bar strain gauge is configured to measure the stress change of the key parts of the hollow truss, the pressure differential static level is configured to monitor the deformation of the hollow truss, and the vibrating wire surface crack gauge is configured to monitor the width of the surface crack of the hollow truss; The monitoring cloud platform is used to receive and integrate the data collected by the sensor system and generate a visual data panel.

3. The primary and secondary double-control graded unloading device suitable for large-span suspended heavy-loaded hollow trusses according to claim 1 is characterized in that: The hydraulic jack includes a hydraulic pump source, a cylinder, a standard oil pipe, a hydraulic sensor and a hydraulic controller, wherein the hydraulic pump source is used to provide hydraulic oil power, the standard oil pipe connects the hydraulic pump source and the cylinder, and delivers hydraulic oil to the cylinder to drive the cylinder to extend and retract to apply an unloading force; the hydraulic sensor includes a pressure sensor and a stroke sensor, the pressure sensor is installed in the hydraulic oil pipeline, and is used to collect hydraulic pressure data in the hydraulic oil pipeline, and the stroke sensor is installed on the cylinder, and is used to collect stroke displacement data of the cylinder piston rod; the hydraulic sensor transmits the collected pressure and stroke data to the hydraulic controller, and the hydraulic controller receives and responds to the control instructions of the remote control platform, and realizes unloading load adjustment by controlling the unloading force of the hydraulic pump source.

4. The primary and secondary double-control graded unloading device suitable for large-span suspended heavy-loaded hollow trusses according to claim 1 is characterized in that: The sand box includes: a bottom plate, a waist plate, and a top plate which are sequentially distributed from bottom to top, an outer cylinder arranged between the bottom plate and the waist plate, and an inner cylinder arranged between the waist plate and the top plate; the outer cylinder is provided with a plurality of sand unloading ports along the circumference, and each sand unloading port is provided with an intelligent sand unloading component, which is configured to respond to the control command of the remote control platform, intelligently control the opening and closing of the sand unloading port, realize automatic sand unloading, and assist in controlling the unloading displacement.

5. The primary and secondary double-control graded unloading device applicable to large-span suspended heavy-loaded hollow trusses according to claim 4 is characterized in that: The inner cylinder is provided with a pressure differential static level for monitoring the real-time changes in the height of the sand box, and feeding back the data to the remote control platform for graded unloading parameter regulation to achieve closed-loop control of displacement; the intelligent sand unloading component is an intelligent bolt-driven mechanical arm or a motor-driven piston rotary sand dredging component.

6. The primary and secondary double-control graded unloading device applicable to large-span suspended heavy-loaded hollow trusses according to claim 4 is characterized in that: The remote control platform is configured with a monitoring and early warning mode and a monitoring and alarm mode, which are triggered and executed based on the total number of pre-set unloading levels and the design value, early warning value and alarm value corresponding to each level of unloading parameters; When the real-time monitoring data does not reach the warning value, the remote control platform maintains the current graded unloading parameters unchanged and continues to execute the unloading process; When the real-time monitoring data exceeds the warning value but is less than the alarm value, the remote control platform enters the monitoring and warning mode, adjusts the graded unloading parameters through the data fusion algorithm, and continues to execute the unloading process based on the adjusted graded unloading parameters; When the real-time monitoring data exceeds the alarm value, the remote control platform immediately enters the monitoring and early warning mode and performs the following operations: increase the monitoring frequency, stop the unloading process, start the bearing capacity verification and safety assessment program, perform bearing capacity verification and safety assessment on the hollow truss according to the structural design document, and decide whether to continue with the next stage of unloading construction based on the bearing capacity verification and safety assessment results and the requirements of the structural design document.

7. A method for unloading a hollow truss using the primary and secondary double-control graded unloading device for a large-span suspended heavy-loaded hollow truss according to any one of claims 1 to 6, characterized in that: The following steps are involved: S1: After the pre-unloading conditions are met, the hydraulic jack is hoisted to the top surface of the supporting frame beam and located on both sides of the sand box, and the oil cylinder is started to tighten the supporting bottom plate to establish the initial supporting state; S2: Conduct unloading simulation drills, perform simulations of the operation flow of each process, and optimize unloading parameters and operation flow based on the simulation results; S3: According to the jacking force requirements of each level of unloading, start each hydraulic jack to lift the hollow truss step by step to a stable state, and then control the sand box to unload sand to a predetermined value; during the sand unloading process, monitor the deformation of the hollow truss in real time. If the deformation reaches the warning value and the top of the sand box is still not separated from the bottom of the hollow truss, stop the sand unloading operation, control the hydraulic jacks to fall synchronously, and the hollow truss is supported by the sand box to complete the current level of unloading; S4: Real-time monitoring and collection of various monitoring data during the unloading process of the hollow truss, static hollow truss to a stable state, use data fusion algorithm to process the monitoring data and evaluate the hollow truss status, and dynamically adjust and determine the next level of unloading parameters based on the evaluation results; S5: Repeat steps S3 and S4 to complete the unloading construction step by step until the hollow truss forms a self-bearing system; after the last level of unloading is completed, remove the sand box and the hydraulic jack to complete the unloading construction.

8. The primary and secondary double-control graded unloading device applicable to large-span suspended heavy-loaded hollow trusses according to claim 7 is characterized in that: In step S4, the collected monitoring data are processed by a data fusion algorithm to obtain a measurement value after eliminating the interference of environmental factors. The measurement value is compared with the design value in the current stage unloading parameter. According to the comparison result, it is determined whether the next stage unloading parameter needs to be adjusted. If it exceeds the warning value, the subsequent stage unloading parameters are corrected based on the data fusion result and the mechanical calculation of the hollow truss.

9. The primary and secondary double-control graded unloading device applicable to large-span suspended heavy-loaded hollow trusses according to claim 8 is characterized in that: The data fusion algorithm includes the following sub-steps: S401: performing time domain segmentation processing on the monitoring data in a stable state to divide it into multiple data sets; S402: Calculate the mean square error of each data set; S403: exhaustively grouping the data set, and performing data fusion processing according to the groups; S404: Taking two sets of data sets as an example, a minimum variance unbiased estimation method is used to perform data fusion calculation to obtain a minimum variance estimation value; S405: Calculate the mean value according to the minimum variance estimation values ​​of each combination at all times to obtain the final minimum variance estimation value of each combination; S406: Calculate the overall mean of the final minimum variance estimation values ​​of all combinations as the measurement value after eliminating the interference of environmental factors; S407: Compare the measured value with the design value in the current stage unloading parameter, and determine whether the next stage unloading parameter needs to be adjusted based on the comparison result. If it exceeds the warning value, correct the subsequent stage unloading parameters based on the data fusion result and the mechanics calculation of the hollow truss.

10. The primary and secondary double-control graded unloading device applicable to large-span suspended heavy-loaded hollow trusses according to claim 9 is characterized in that: The correction of subsequent graded unloading parameters based on the data fusion results and the mechanical calculation of the hollow truss includes: Substituting the stress data in the monitoring data into the data fusion algorithm for processing, the current column top support force is calculated to quantify the actual load bearing situation of the structure; Based on the current column top support force, calculate the percentage of the total support force remaining in the structure after the current graded unloading and evaluate the current unloading degree; Calculate the deviation between the actual remaining support force percentage and the target value in the design document, and evaluate the gap between the actual unloading effect and the predetermined target; According to the positive or negative value of the deviation, it is judged whether the actual unloading support force is too large or too small; Based on the evaluation results, intelligent decision-making on the unloading parameter adjustment strategy includes: when the actual unloading support force is too small and deformation warning is issued, the unloading amount of the new unloading level is added, and the subsequent unloading parameters are corrected accordingly; when the actual unloading support force meets the standard or is too large, the unloading parameters of the next level are kept unchanged, and the warning value and alarm value are recalculated and updated to adapt to the new structural state.

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