A walking-type jacking curved bridge intelligent adjustment method and system

Abstract

The present invention relates to an intelligent adjustment method and system for a walking-type jacking curved bridge. The intelligent adjustment method comprises: obtaining a theoretical reaction matrix of the jack under stress-free conditions [R k ] t and the theoretical elevation displacement matrix [△ k ] t ; Get the real-time reaction matrix of the jack [R k ] c and the elevation displacement matrix [△ k ] c ; Based on the theoretical reaction matrix [R k ] t , Theoretical elevation displacement matrix [△ k ] t , real-time reaction matrix [R k ] c and the elevation displacement matrix [△ k ] c , and the jack support reaction force is corrected and executed. Compared with the existing technology, this invention synchronously controls the reaction force and displacement of the jack during the "jacking and jacking" process in real time, verifies the actual monitoring data with the theoretical calculation data, and further optimizes and adjusts the jack reaction force. The jack stroke is intelligently controlled through the PC terminal throughout the process, which can provide real-time early warning and real-time correction, improving the efficiency and quality of curved bridge construction, and is more in line with the concept of modern, automated, and intelligent bridge construction.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge construction, and in particular to an intelligent adjustment method and system for a walking-type jacking curved bridge. Background Art

[0002] With the rapid development of bridge construction in my country, the technical difficulty and complexity of bridge construction are also increasing. When the span of a bridge is large, it crosses specific obstacles, and temporary piers between spans are not allowed under the bridge, the traditional bridge erection method can no longer meet the needs of the project. To solve this engineering problem, construction methods such as cantilever assembly construction, jacking construction, and rotation construction have emerged, which do not require the establishment of temporary supports under the bridge. Among them, jacking construction is widely used due to its fast and safe technical characteristics. Traditional jacking construction uses the existing roadbed section as a prefabricated platform for jacking beams, and uses jacking equipment to push the prefabricated beams one span at a time in the direction of the bridge span. With the increasing complexity of the environment in which bridge construction occurs, the traditional jacking construction process can no longer meet the needs of engineering construction. The engineering community has developed a new jacking method - walking jacking construction.

[0003] The walking jacking construction process consists of two steps: lifting and advancing. It's applicable to various bridge types, but it's currently used more often on straight bridges than on curved ones. The "bending-torsion coupling" effect of curved bridges complicates the stress state and deformation of curved beams. The jacking process presents challenges with linear control, stress control, and various construction safety risks. Currently, research on these issues is limited and unsystematic, and the risks and controls associated with the walking jacking method for curved bridges remain to be addressed.

[0004] Therefore, in view of the current situation, a walking-type jacking curved bridge intelligent adjustment method is needed to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a walking-type jacking curved bridge intelligent adjustment method and system.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] According to a first aspect of the present invention, there is provided a method for intelligently adjusting a curved bridge by walking-type jacking, comprising:

[0008] Obtain the theoretical reaction matrix of the jack under stress-free conditions [R k ] t and the theoretical elevation displacement matrix [△ k ] t ;

[0009] Get the real-time reaction matrix of the jack k ] c and the elevation displacement matrix [△ k ] c ;

[0010] Based on the theoretical reaction matrix [R k ] t , Theoretical elevation displacement matrix [△ k ] t , real-time reaction matrix [R k ] c and the elevation displacement matrix [△ k ] c , correct and execute the jack support reaction force.

[0011] Furthermore, the jack support reaction force is corrected and executed as follows:

[0012] S1. For any jacking working condition k, randomly generate the optimization coefficient and optimize and adjust to obtain the jack support reaction force [dR]0:

[0013] [dR]0=P{[R k ] t -[R k ] c}

[0014] Where P is the randomly generated optimization coefficient;

[0015] S2, execute the optimized adjustment of the jack support reaction force [dR]0, and obtain the actual monitored lifting amount [d△]1;

[0016] S3, randomly generate an optimization coefficient, optimize and adjust it again to obtain the jack support reaction force [dR]0, execute the optimized and adjusted jack support reaction force [dR]0, and obtain the actual monitored jacking amount [d△]2;

[0017] S4. If the two actual monitored lifting amounts [d△]1 and [d△]2 meet the preset execution conditions, execute step S5; otherwise, go to step S1;

[0018] S5. Calculate and optimize the jack reaction force [dR] e :

[0019]

[0020] S6, based on optimized jack reaction force [dR] e Calculate the precision coefficient λ. If the precision coefficient λ meets the preset termination condition, the optimization of the jack reaction force [dR] is performed. e , complete this round of optimization, otherwise, go to step S1, the calculation formula of the precision coefficient λ is:

[0021] λ={[dR] e +2[dR]0} / {[R k ] t -[R k ] c}.

[0022] Furthermore, the randomly generated optimization coefficient P has a value range of 0.1 to 0.4.

[0023] Furthermore, the preset execution conditions are:

[0024] 0.8≤[d△]2 / [d△]1≤1.2.

[0025] Furthermore, the preset termination conditions are:

[0026] The precision coefficient λ falls within a preset threshold range, which is 0.95 to 1.05.

[0027] According to a second aspect of the present invention, there is provided a walking-type jacking curved bridge intelligent adjustment system, comprising:

[0028] Theoretical data module, used for the theoretical reaction matrix of the jack under stress-free conditions [R k ] t and the theoretical elevation displacement matrix [△ k ] t ;

[0029] Measured data module, used to obtain the real-time reaction matrix of the jack [R k ] c and the elevation displacement matrix [△ k ] c ;

[0030] Optimization adjustment module for the theoretical reaction matrix [R k ] t , Theoretical elevation displacement matrix [△ k ] t , real-time reaction matrix [R k ] c and the elevation displacement matrix [△ k ] c , correct and execute the jack support reaction force.

[0031] Furthermore, the jack support reaction force is corrected and executed as follows:

[0032] S1. For any jacking working condition k, randomly generate the optimization coefficient and optimize and adjust to obtain the jack support reaction force [dR]0:

[0033] [dR]0=P{[R k ]t -[R k ] c}

[0034] Where P is the randomly generated optimization coefficient;

[0035] S2, execute the optimized adjustment of the jack support reaction force [dR]0, and obtain the actual monitored lifting amount [d△]1;

[0036] S3, randomly generate an optimization coefficient, optimize and adjust it again to obtain the jack support reaction force [dR]0, execute the optimized and adjusted jack support reaction force [dR]0, and obtain the actual monitored jacking amount [d△]2;

[0037] S4. If the two actual monitored lifting amounts [d△]1 and [d△]2 meet the preset execution conditions, execute step S5; otherwise, go to step S1;

[0038] S5. Calculate and optimize the jack reaction force [dR] e :

[0039]

[0040] S6, based on optimized jack reaction force [dR] e Calculate the precision coefficient λ. If the precision coefficient λ meets the preset termination condition, the optimization of the jack reaction force [dR] is performed. e , complete this round of optimization, otherwise, go to step S1, the calculation formula of the precision coefficient λ is:

[0041] λ={[dR] e +2[dR]0} / {[R k ] t -[R k ] c}.

[0042] Furthermore, the randomly generated optimization coefficient P has a value range of 0.1 to 0.4.

[0043] Furthermore, the preset execution conditions are:

[0044] 0.8≤[d△]2 / [d△]1≤1.2.

[0045] Furthermore, the preset termination conditions are:

[0046] The precision coefficient λ falls within a preset threshold range, which is 0.95 to 1.05.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The present invention synchronously controls the reaction force and displacement of the jack during the "lifting and pushing" process in real time, verifies the actual monitoring data with the theoretical calculation data, and further optimizes and adjusts the jack's reaction force, and intelligently controls the jack's stroke through a PC terminal throughout the entire process. Compared with the traditional jacking method, the walking-type jacking curved bridge intelligent adjustment method has higher construction accuracy, can provide real-time early warning and real-time correction, improves the efficiency and quality of curved bridge construction, and is more in line with the concept of modern, automated, and intelligent bridge construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a technical roadmap for the intelligent adjustment method of a walking-type jacking curved bridge of the present invention;

[0050] Figure 2 This is a schematic diagram of the reaction force of the jack used for a curved bridge according to the present invention;

[0051] Figure 3 The figure is a schematic diagram of the reaction force and displacement elevation of the jack used for the curved bridge of the present invention. DETAILED DESCRIPTION

[0052] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operating process. Obviously, the described embodiment is only an embodiment of a part of the present invention, not all embodiments, and the protection scope of the present invention is not limited to the following embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention.

[0053] This specification provides method operation steps such as embodiments or flowcharts, but may include more or fewer operation steps based on conventional or non-creative work. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the actual system or server product is executed, it can be executed in sequence or in parallel (for example, in a parallel processor or multi-threaded processing environment) according to the embodiment or the method shown in the accompanying drawings, or the execution order of steps without timing restrictions can be adjusted.

[0054] The present application provides a walking-type jacking-type intelligent adjustment method for a curved bridge, comprising:

[0055] Obtain the theoretical reaction matrix of the jack under stress-free conditions [R k ] t and the theoretical elevation displacement matrix [△ k ] t ;

[0056] Get the real-time reaction matrix of the jackk ] c and the elevation displacement matrix [△ k ] c ;

[0057] Based on the theoretical reaction matrix [R k ] t , Theoretical elevation displacement matrix [△ k ] t , real-time reaction matrix [R k ] c and the elevation displacement matrix [△ k ] c , correct and execute the jack support reaction force.

[0058] Among them, such as Figure 1 As shown, the jack support reaction force is corrected and executed as follows:

[0059] S1. For any jacking working condition k, randomly generate the optimization coefficient and optimize and adjust to obtain the jack support reaction force [dR]0:

[0060] [dR]0=P{[R k ] t -[R k ] c}

[0061] Where P is a randomly generated optimization coefficient, ranging from 0.1 to 0.4.

[0062] S2, execute the optimized adjustment of the jack support reaction force [dR]0, and obtain the actual monitored lifting amount [d△]1;

[0063] S3. Randomly generate the optimization coefficient again, and optimize and adjust again to obtain the jack support reaction force [dR]0 (note that since the optimization coefficient is randomly generated again, the jack support reaction force [dR]0 obtained in step S3 may not be equal to the jack support reaction force [dR]0 obtained in step S1). Execute the optimized and adjusted jack support reaction force [dR]0 to obtain the actual monitored jacking amount [d△]2;

[0064] S4. If the two actual monitored lifting amounts [d△]1 and [d△]2 meet the preset execution conditions, execute step S5; otherwise, go to step S1;

[0065] The default execution conditions are:

[0066] 0.8≤[d△]2 / [d△]1≤1.2.

[0067] S5. Calculate and optimize the jack reaction force [dR] e :

[0068]

[0069] S6, based on optimized jack reaction force [dR] e Calculate the precision coefficient λ. If the precision coefficient λ meets the preset termination condition, the optimization of the jack reaction force [dR] is performed. e , complete this round of optimization, otherwise, go to step S1, and the calculation formula of the precision coefficient λ is:

[0070] λ={[dR] e +2[dR]0} / {[R k ] t -[R k ] c}.

[0071] The default termination conditions are:

[0072] The precision coefficient λ falls within a preset threshold range, which is 0.95 to 1.05.

[0073] Among them, the reaction matrix [R k ] and the displacement matrix [△ k ]The expression is as follows:

[0074]

[0075]

[0076] In the formula: i is the pier number, j is the jack number, and k is the jacking condition number. It can be understood that in the jacking construction, there are multiple construction piers, corresponding to different pier numbers, and several jacks are set on the construction piers. Figure 2 and Figure 3 Staff will calculate an initial jacking plan based on the bridge's gravity, load-bearing requirements, speed, and the number and specifications of the jacks. This plan includes multiple, temporally continuous working conditions, and determines the jacking amount, corresponding jack reaction force, and displacement values ​​for each condition. The intelligent adjustment solution provided in this application will then be applied to optimize and adjust the jacking plan during construction.

[0077] The present invention synchronously controls the reaction force and displacement of the jack during the "lifting and pushing" process in real time, verifies the actual monitoring data with the theoretical calculation data, and further optimizes and adjusts the jack's reaction force, and intelligently controls the jack's stroke through a PC terminal throughout the entire process. Compared with the traditional jacking method, the walking-type jacking curved bridge intelligent adjustment method has higher construction accuracy, can provide real-time early warning and real-time correction, improves the efficiency and quality of curved bridge construction, and is more in line with the concept of modern, automated, and intelligent bridge construction.

[0078] The present invention also provides a walking-type jacking curved bridge intelligent adjustment system, comprising:

[0079] Theoretical data module, used for the theoretical reaction matrix of the jack under stress-free conditions [R k ] t and the theoretical elevation displacement matrix [△ k ] t ;

[0080] Measured data module, used to obtain the real-time reaction matrix of the jack [R k ] c and the elevation displacement matrix [△ k ] c ;

[0081] Optimization adjustment module for the theoretical reaction matrix [R k ] t , Theoretical elevation displacement matrix [△ k ] t , real-time reaction matrix [R k ] c and the elevation displacement matrix [△ k ] c , correct and execute the jack support reaction force.

[0082] Correct the jack support reaction force and perform the following steps:

[0083] S1. For any jacking working condition k, randomly generate the optimization coefficient and optimize and adjust to obtain the jack support reaction force [dR]0:

[0084] [dR]0=P{[R k ] t -[R k ] c}

[0085] Where P is a randomly generated optimization coefficient, ranging from 0.1 to 0.4.

[0086] S2, execute the optimized adjustment of the jack support reaction force [dR]0, and obtain the actual monitored lifting amount [d△]1;

[0087] S3. Randomly generate the optimization coefficient again, and optimize and adjust again to obtain the jack support reaction force [dR]0 (note that since the optimization coefficient is randomly generated again, the jack support reaction force [dR]0 obtained in step S3 may not be equal to the jack support reaction force [dR]0 obtained in step S1). Execute the optimized and adjusted jack support reaction force [dR]0 to obtain the actual monitored jacking amount [d△]2;

[0088] S4. If the two actual monitored lifting amounts [d△]1 and [d△]2 meet the preset execution conditions, execute step S5; otherwise, go to step S1;

[0089] The default execution conditions are:

[0090] 0.8≤[d△]2 / [d△]1≤1.2.

[0091] S5. Calculate and optimize the jack reaction force [dR] e :

[0092]

[0093] S6, based on optimized jack reaction force [dR] e Calculate the precision coefficient λ. If the precision coefficient λ meets the preset termination condition, the optimization of the jack reaction force [dR] is performed. e , complete this round of optimization, otherwise, go to step S1, and the calculation formula of the precision coefficient λ is:

[0094] λ={[dR] e +2[dR]0} / {[R k ] t -[R k ] c}.

[0095] The default termination conditions are:

[0096] The precision coefficient λ falls within a preset threshold range, which is 0.95 to 1.05.

[0097] Of course, further, it is also possible to set up a measured data module M1, a theoretical calculation and analysis module M2, an execution control module M3 and a real-time feedback module M4; in fact, the measured data module M1 and the real-time feedback module M4 are all used to collect real-time data. The entire process is carried out through the PC terminal to carry out intelligent control of the jack's "lifting and pushing";

[0098] The measured data module is mainly used for real-time acquisition, storage and analysis of actual monitoring data, that is, real-time acquisition, storage and analysis of the actual monitoring jack reaction matrix [R k ] c and the elevation displacement matrix [△ k ] c ;

[0099] The theoretical calculation and analysis module is mainly used to calculate and output theoretical data under stress-free conditions, verify the actual monitoring data with the theoretical calculation data, and perform real-time early warning and real-time correction. Specifically, it calculates and outputs the theoretical reaction matrix under stress-free conditions [R k ] t and the theoretical elevation displacement matrix [△ k ] t, verifying the actual monitoring data with the theoretical calculation data, further revealing the changes in stress and displacement during the bridge pushing process, and performing real-time data early warning and real-time data correction;

[0100] The execution control module is responsible for executing and controlling the jack pushing situation at each position, and for real-time monitoring, calculation, optimization and adjustment of the pushing process. Specifically, it is responsible for executing and controlling the jack pushing reaction force at each position. k ] and displacement [△ k ] size, and monitor, calculate, optimize and execute the pushing process in real time;

[0101] The real-time feedback module is responsible for feeding back the real-time monitoring data, giving warnings for data that exceeds the warning value and affects the safety of the jacking, making further optimization and adjustments to the jacking plan, accurately grasping the problems that arise during the jacking process, and ensuring the safety of the jacking. Specifically, it is responsible for feeding back the real-time monitored reaction force [R k ] and elevation displacement [△ k ] is fed back to the theoretical calculation and analysis module M2, which issues warnings for data that exceeds the warning value and affects the safety of jacking, makes further optimization and adjustment of the jacking plan, accurately grasps and solves problems that arise during the jacking process, and ensures the safety of jacking.

[0102] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0103] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A walking-type jacking curve bridge intelligent adjustment method, characterized in that: include: Obtain the theoretical reaction matrix of the jack under stress-free conditions [R k ] t and the theoretical elevation displacement matrix [△ k ] t ; Get the real-time reaction matrix of the jack k ] c and the elevation displacement matrix [△ k ] c ; Based on the theoretical reaction matrix [R k ] t , Theoretical elevation displacement matrix [△ k ] t , real-time reaction matrix [R k ] c and the elevation displacement matrix [△ k ] c , correct and execute the reaction force of the jack support; Correct the jack support reaction force and perform the following steps: S1. For any jacking working condition k, randomly generate the optimization coefficient and optimize and adjust to obtain the jack support reaction force [dR]0: [dR]0=P{[R k ] t -[R k ] c } Where P is the randomly generated optimization coefficient; S2, execute the optimized adjustment of the jack support reaction force [dR]0, and obtain the actual monitored lifting amount [d△]1; S3, randomly generate an optimization coefficient, optimize and adjust it again to obtain the jack support reaction force [dR]0, execute the optimized and adjusted jack support reaction force [dR]0, and obtain the actual monitored jacking amount [d△]2; S4. If the two actual monitored lifting amounts [d△]1 and [d△]2 meet the preset execution conditions, execute step S5; otherwise, go to step S1; S5. Calculate and optimize the jack reaction force [dR] e : S6, based on optimized jack reaction force [dR] e Calculate the precision coefficient λ. If the precision coefficient λ meets the preset termination condition, the optimization of the jack reaction force [dR] is performed. e , complete this round of optimization, otherwise, go to step S1, the calculation formula of the precision coefficient λ is: λ={[dR] e +2[dR]0} / {[R k ] t -[R k ] c }。 2. The intelligent adjustment method for a walking-type jacking curved bridge according to claim 1 is characterized in that: The value range of the randomly generated optimization coefficient P is 0.1 to 0.

4.

3. The intelligent adjustment method for a walking-type jacking curved bridge according to claim 1 is characterized in that: The default execution conditions are: 0.8≤[d△]2 / [d△]1≤1.

2.

4. The intelligent adjustment method for a walking-type jacking curved bridge according to claim 1 is characterized in that: The default termination conditions are: The precision coefficient λ falls within a preset threshold range, which is 0.95 to 1.

05.

5. A walking-type jacking curved bridge intelligent adjustment system, characterized in that: include: Theoretical data module, used for the theoretical reaction matrix of the jack under stress-free conditions [R k ] t and the theoretical elevation displacement matrix [△ k ] t ; Measured data module, used to obtain the real-time reaction matrix of the jack [R k ] c and the elevation displacement matrix [△ k ] c ; Optimization adjustment module for the theoretical reaction matrix [R k ] t , Theoretical elevation displacement matrix [△ k ] t , real-time reaction matrix [R k ] c and the elevation displacement matrix [△ k ] c , correct and execute the reaction force of the jack support; Correct the jack support reaction force and perform the following steps: S1. For any jacking working condition k, randomly generate the optimization coefficient and optimize and adjust to obtain the jack support reaction force [dR]0: [dR]0=P{[R k ] t -[R k ] c } Where P is the randomly generated optimization coefficient; S2, execute the optimized adjustment of the jack support reaction force [dR]0, and obtain the actual monitored lifting amount [d△]1; S3, randomly generate an optimization coefficient, optimize and adjust it again to obtain the jack support reaction force [dR]0, execute the optimized and adjusted jack support reaction force [dR]0, and obtain the actual monitored jacking amount [d△]2; S4. If the two actual monitored lifting amounts [d△]1 and [d△]2 meet the preset execution conditions, execute step S5; otherwise, go to step S1; S5. Calculate and optimize the jack reaction force [dR] e : S6, based on optimized jack reaction force [dR] e Calculate the precision coefficient λ. If the precision coefficient λ meets the preset termination condition, the optimization of the jack reaction force [dR] is performed. e , complete this round of optimization, otherwise, go to step S1, the calculation formula of the precision coefficient λ is: λ={[dR] e +2[dR]0} / {[R k ] t -[R k ] c }。 6. The intelligent adjustment system for a walking-type jacking curved bridge according to claim 5 is characterized in that: The value range of the randomly generated optimization coefficient P is 0.1 to 0.

4.

7. The intelligent adjustment system for a walking-type jacking curved bridge according to claim 5 is characterized in that: The default execution conditions are: 0.8≤[d△]2 / [d△]1≤1.

2.

8. The intelligent adjustment system for a walking-type jacking curved bridge according to claim 5 is characterized in that: The default termination conditions are: The precision coefficient λ falls within a preset threshold range, which is 0.95 to 1.05.

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