Steel bridge tower intelligent tension deviation early warning system and method

Abstract

The application discloses a steel bridge tower intelligent pull deviation early warning system and method, and belongs to the technical field of bridge construction, which comprises the following steps: determining the steel bridge tower pull deviation based on the cable saddle pre-deviation and the longitudinal space of the steel bridge tower top; determining the steel bridge tower pull deviation information; determining the steel bridge tower pull deviation threshold set; obtaining the steel bridge tower pull deviation early warning information based on each early warning module; determining the early warning coefficient of each early warning module based on the steel bridge tower pull deviation early warning information and the steel bridge tower pull deviation threshold set; determining the early warning contribution degree of each early warning module; determining the information entropy of each early warning module; determining the weight coefficient of each early warning module; determining the comprehensive early warning index based on the early warning contribution degree of the early warning module and the weight coefficient of each early warning module; and determining the pull deviation early warning information of at least one time point based on the comprehensive early warning index and the comprehensive early warning threshold. The application solves the technical problems of lacking pull deviation feedback mechanism and existing safety hazards, reduces the false positive rate and the false negative rate, and improves the technical effect of the pull deviation early warning.

Description

Technical Field

[0001] This invention relates to the field of bridge construction technology, specifically to a smart anti-deviation system and method for steel bridge towers. Background Technology

[0002] The principle of pre-offset cable saddles in suspension bridges is to offset the main cable saddles a certain distance towards the side spans before the main cables are erected. This ensures that the horizontal components of the cable force are balanced during the main cable erection process, preventing the cable strands from slipping within the saddle grooves, thereby controlling the main cable alignment. For suspension bridges with a large side-to-middle span ratio (the ratio of the side span to the middle span), a large pre-offset cable saddle amount is often required to balance the horizontal forces on both sides of the main cable saddle. However, compared to concrete bridge towers, steel bridge towers have a smaller longitudinal space at the top, making it unsuitable for such large pre-offset amounts.

[0003] To address the technical problem that the space at the top of the steel bridge tower of a suspension bridge cannot meet the pre-deflection of the cable saddle, a bridge tower tensioning system is used to adjust the bridge tower to replace part of the pre-deflection of the cable saddle, taking advantage of the flexibility of the steel bridge tower. However, the bridge tower tensioning system lacks a tensioning feedback mechanism, which makes the tensioning system prone to accidents during the tensioning process, posing a safety hazard. Summary of the Invention

[0004] To address the above problems, the first aspect of this invention provides a smart anti-balance method for steel bridge towers, comprising the following steps:

[0005] The steel bridge tower tension deflection is determined based on the cable saddle pre-deflection and the maximum longitudinal space at the top of the tower.

[0006] Determine the steel bridge tower tension information based on the steel bridge tower tension deviation;

[0007] Determine the set of steel bridge tower deflection thresholds based on steel bridge tower deflection information;

[0008] Early warning information on steel bridge tower misalignment is obtained based on each early warning module;

[0009] The warning coefficients of each warning module are determined based on the steel bridge tower pull-off warning information and the steel bridge tower pull-off threshold set.

[0010] The early warning contribution of each early warning module is determined based on its early warning coefficient.

[0011] The information entropy of each early warning module is determined based on its early warning contribution.

[0012] The weight coefficients of each early warning module are determined based on the information entropy of each module.

[0013] The comprehensive early warning index is determined based on the early warning contribution of each early warning module and the weighting coefficient of each early warning module.

[0014] Based on the comprehensive early warning index and comprehensive early warning threshold, determine the pull-off early warning information at least at one time point.

[0015] In some embodiments, the steel bridge tower deflection information includes: the final tension of the pre-deflection cable, the number of stages of tensioning, the bridge tower deflection after each stage of tensioning, the cable force of the pre-deflection cable after each stage of tensioning, the tower base stress after each stage of tensioning, and the tension of the tower base connecting bolt after each stage of tensioning.

[0016] In some embodiments, the steel bridge tower deflection threshold set refers to a set of thresholds used to determine whether the motion state or stress state of the steel bridge tower is normal during the deflection process.

[0017] The set of threshold values ​​for steel bridge tower pull-off includes:

[0018] The threshold sets for bridge tower deviation, pre-tensioned cable force, tower base stress, and connecting screw tension.

[0019] In some embodiments, the steel bridge tower deflection information includes: real-time tower deflection, real-time tension of the pre-deflection cable, real-time stress at the tower base, and real-time tension of the connecting bolt at the tower base.

[0020] In some embodiments, the warning coefficients include: bridge tower deviation warning coefficient, pre-tensioned cable force warning coefficient, tower base stress warning coefficient, and tower base bolt tension warning coefficient;

[0021] The calculation method for the bridge tower deviation early warning coefficient is as follows:

[0022]

[0023] Where y1(t) is the bridge tower offset early warning coefficient, X ms (t) represents the real-time displacement of the bridge tower during the m-th stage of tensioning, X m The threshold value for the bridge tower offset during the m-th level of tensioning;

[0024] The calculation method for the pre-tension cable force warning coefficient is as follows:

[0025]

[0026] Where y2(t) is the pre-tension cable force warning coefficient, N ms (t) represents the real-time cable force (N) of the pre-tensioned cable during the m-th stage tensioning process. m The threshold force of the pre-tensioned cable at the m-th tension level;

[0027] The calculation method for the tower bottom stress early warning coefficient is as follows:

[0028]

[0029] Where y3(t) is the tower bottom stress warning coefficient, σ ms (t) represents the real-time stress at the bottom of the tower during the m-th stage of tensioning, σ m The stress threshold at the bottom of the tower during the m-th stage of tensioning;

[0030] The calculation method for the tower bottom screw tension warning coefficient is as follows:

[0031]

[0032] Where y4(t) is the tension warning coefficient of the connecting screw at the bottom of the tower, F ms (t) represents the real-time tension of the tower base connecting screw during the m-th stage of tensioning, F m This is the screw tension threshold.

[0033] In some embodiments, the early warning contribution is calculated as follows:

[0034]

[0035] Where, p i (t) represents the early warning contribution of the i-th early warning module, y i (t) represents the warning coefficient of the i-th warning module, and n represents the number of warning modules.

[0036] In some embodiments, the information entropy of each early warning module is calculated as follows:

[0037]

[0038] Among them, E i Let i be the information entropy of the i-th early warning module. Let be the normalization factor, i be the number of early warning modules, t0 and t1 be the upper and lower limits of the integral, and p be the normalization factor. i (t) represents the early warning contribution of the i-th early warning module, and dt is the integral variable.

[0039] In some embodiments, the comprehensive early warning index is calculated as follows:

[0040]

[0041] Where n is the number of early warning modules, w i Let y be the weight of the i-th early warning module. i (t) represents the warning coefficient of the i-th warning module.

[0042] In some embodiments, the comprehensive warning threshold refers to the threshold used to determine whether it is necessary to stop the pull-off;

[0043] The deviation warning information is confirmed by comparing the comprehensive warning index and the comprehensive warning threshold.

[0044] A second aspect of the present invention provides a smart tension-biasing early warning system for steel bridge towers, used to execute a smart tension-biasing early warning method for steel bridge towers as described in the above-mentioned scheme, comprising:

[0045] The first determining module is used to determine the deflection of the steel bridge tower;

[0046] The second determining module is used to determine the steel bridge tower deflection information;

[0047] The third determining module is used to determine the set of threshold values ​​for steel bridge tower deflection;

[0048] The acquisition module is used to acquire early warning information about the steel bridge tower misalignment.

[0049] The fourth determining module is used to determine the warning coefficient of each warning module;

[0050] The fifth determination module is used to determine the early warning contribution of each early warning module;

[0051] The sixth determining module is used to determine the information entropy of each early warning module;

[0052] The seventh module is used to determine the weighting coefficients of each early warning module;

[0053] The eighth module is used to determine the comprehensive early warning index;

[0054] The ninth determination module is used to determine the pull-off warning information at least at one point in time.

[0055] By adopting the above technical solution, the present invention mainly has the following technical effects:

[0056] By adopting a dynamic weight allocation mechanism based on information entropy, risks can be assessed more accurately. This solves the technical problem of the lack of a bias feedback mechanism, which makes the bias system prone to accidents and poses safety hazards during the bias process. It effectively reduces the false alarm rate and the false alarm rate, and improves the bias early warning effect. Attached Figure Description

[0057] Figure 1 This is a flowchart of a smart anti-skewing method for steel bridge towers according to the present invention;

[0058] Figure 2 This is a schematic diagram of the steel bridge tower being pulled off course. Detailed Implementation

[0059] To enable those skilled in the art to better understand the present invention, the technical solutions in 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 a part of the embodiments of the present invention, and not all of them. 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.

[0060] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0061] Please see Figure 1 The first aspect of this invention provides a smart anti-eccentricity warning method for steel bridge towers, comprising the following steps:

[0062] (a) Determine the steel bridge tower tension based on the cable saddle pre-deflection and the maximum longitudinal space at the top of the tower;

[0063] In some embodiments, the cable saddle pre-offset refers to the horizontal offset of the main cable saddle (or main cable) that is pre-set during bridge construction to balance the difference in horizontal forces on both sides of the main cable.

[0064] In some embodiments, the cable saddle pre-deflection can be calculated based on the bridge design structure. In some embodiments, the cable saddle pre-deflection is calculated as follows:

[0065]

[0066] Where L1 is the cable saddle pre-offset, H m For the horizontal force of the main cable in the middle span, H b For the horizontal force of the main cable in the side span; K T For the lateral stiffness of the bridge tower;

[0067] In some embodiments, the maximum longitudinal space at the top of the tower is the maximum horizontal offset of the main cable saddle (or main cable) when the steel bridge tower is not pulled off course.

[0068] In some embodiments, the steel bridge tower deflection refers to the horizontal offset of the steel bridge tower top to meet the cable saddle pre-deflection when the maximum longitudinal space at the top of the tower cannot meet the cable saddle pre-deflection.

[0069] In some embodiments, the steel bridge tower deflection can be calculated based on the cable saddle pre-deflection and the maximum longitudinal space at the top of the tower.

[0070] In some embodiments, the calculation method for the steel bridge tower deflection is as follows:

[0071] L = L1 - L2

[0072] Where L is the steel bridge tower tension deviation, L1 is the cable saddle pre-deflection, and L2 is the maximum longitudinal space at the top of the tower.

[0073] Please see Figure 2 , Figure 2 The diagram illustrates the deflection of a steel bridge tower. In some embodiments, the maximum longitudinal space at the top of the tower can be the distance between the pre-deflection point of the cable saddle and the centerline of the steel bridge tower. For example, the pre-deflection of the cable saddle is 3.65m, and the distance between the pre-deflection point of the cable saddle and the centerline of the steel bridge tower is 2.4m. Therefore, the deflection of the steel bridge tower is 3.65 - 2.4 = 1.25m, indicating that the top of the steel bridge tower needs to be offset by 1.25m in the horizontal direction along the pre-deflection direction of the cable saddle.

[0074] (b) Determine the steel bridge tower tension information based on the steel bridge tower tension deviation;

[0075] In some embodiments, the steel bridge tower deflection information may include the mechanical parameters of the steel bridge tower deflection. In some embodiments, the mechanical parameters of the steel bridge tower deflection may include the motion state and stress state of the steel bridge tower during the deflection process.

[0076] In some embodiments, the steel bridge tower deflection information can be calculated using finite element software. An exemplary finite element software could be MIDAS, a widely used finite element analysis software in civil engineering and building structures, primarily for the analysis and design of bridges, building structures, etc. MIDAS software has several product series, such as MIDAS Civil (for civil engineering structural analysis) and MIDAS Gen (for building structural analysis), all of which have nonlinear analysis capabilities.

[0077] In some embodiments, the steel bridge tower deflection information includes:

[0078] The final tension of the pre-deflection cable refers to the tension required to shift the top of the steel bridge tower horizontally to a predetermined position along the pre-deflection direction of the cable saddle.

[0079] In some embodiments, the deflection process of the steel bridge tower can be achieved by tensioning the cables connected to the top of the steel bridge tower. Through certain equipment and methods, tension is applied to the steel strands or cables to cause the top of the steel bridge tower to shift horizontally.

[0080] The number of stages of tensioning refers to the number of steps in which the total tension is divided during construction. The purpose is to control the structural response and avoid abrupt changes.

[0081] In some embodiments, the deflection process can be achieved by connecting one end of the pre-deflection cable to the top of the steel bridge tower and the other end to a jack, and tensioning the pre-deflection cable connected to the jack.

[0082] In some embodiments, the steel bridge tower deflection information further includes:

[0083] The bridge tower deflection after each tensioning stage represents the horizontal displacement of the top of the bridge tower after each tensioning stage is completed.

[0084] The tension of the pre-tensioned cable after each tensioning stage represents the tension borne by the pre-tensioned cable after each tensioning stage.

[0085] The tower base stress after each tensioning stage represents the stress borne by the bottom of the bridge tower after each tensioning stage.

[0086] The tension of the connecting screw at the bottom of the tower after each stage of tensioning represents the axial tension borne by the connecting screw after each stage of tensioning.

[0087] (c) Determine the set of steel bridge tower deflection thresholds based on steel bridge tower deflection information;

[0088] In some embodiments, the steel bridge tower deflection threshold set refers to a set of thresholds used to determine whether the motion state or stress state of the steel bridge tower during the deflection process is normal. In some embodiments, the steel bridge tower deflection threshold set includes:

[0089] The bridge tower deviation threshold set refers to the set of thresholds used to determine whether the horizontal displacement of the top of the bridge tower is normal during the staged tensioning process. For example, if the bridge tower deviation exceeds the bridge tower deviation threshold for that stage of tensioning, it indicates that the bridge tower deviation is too large and there is a safety hazard. In some embodiments, each stage of tensioning can correspond to a separate bridge tower deviation threshold. In some embodiments, the bridge tower deviation threshold can be set based on the bridge tower deviation after each stage of tensioning.

[0090] The pre-tensioning cable force threshold set refers to a set of thresholds used to determine whether the tension borne by the pre-tensioning cable during the staged tensioning process is normal. For example, if the pre-tensioning cable force exceeds the pre-tensioning cable force threshold for that stage of tensioning, it indicates that the tension borne by the pre-tensioning cable is too large, which may pose a safety hazard of pre-tensioning cable breakage. In some embodiments, each stage of tensioning may correspond to a separate pre-tensioning cable force threshold. In some embodiments, the pre-tensioning cable force threshold can be set based on the pre-tensioning cable force after each stage of tensioning.

[0091] A set of tower base stress thresholds refers to a set of thresholds used to determine whether the stress at the bottom of the tower during the staged tensioning process is normal. For example, if the tower base stress exceeds the tower base stress threshold for that stage of tensioning, it indicates that the stress at the bottom of the steel bridge tower is too high, which may pose a safety hazard of structural fracture. In some embodiments, each stage of tensioning may correspond to a separate tower base stress threshold. In some embodiments, the tower base stress threshold can be set based on the tower base stress after each stage of tensioning.

[0092] A set of connecting screw tension thresholds is used to determine whether the tension borne by the connecting screws during the staged tensioning process is normal. For example, if the connecting screw tension exceeds the connecting screw tension threshold for that stage of tensioning, it indicates that the tension borne by the bolts and screws at the bottom of the steel bridge tower is too high, which may pose a safety hazard of bolt breakage. In some embodiments, each stage of tensioning may correspond to a separate screw tension threshold. In some embodiments, the screw tension threshold can be set based on the axial tension borne by the connecting screws at the bottom of the tower after each stage of tensioning.

[0093] (d) Obtain early warning information on steel bridge tower misalignment based on each early warning module;

[0094] In some embodiments, the steel bridge tower pull-off warning information can be real-time parameters reflecting the motion and stress state of the steel bridge tower during the pull-off process; in some embodiments, the steel bridge tower pull-off warning information can be obtained through various warning modules.

[0095] In some embodiments, the steel bridge tower deflection information may include:

[0096] Real-time bridge tower misalignment refers to the horizontal displacement of the top of the bridge tower during tensioning. In some embodiments, the real-time bridge tower misalignment can be obtained through a bridge tower misalignment early warning module. An exemplary bridge tower misalignment early warning module can be a GNSS coordinate acquisition system at the top of the tower.

[0097] The real-time cable force of the pre-biased cable is the actual cable force during tensioning. In some embodiments, the real-time cable force of the pre-biased cable can be obtained through a pre-biased cable force early warning module. For example, the pre-biased cable force early warning module can be collected in real time by the jack of the tensioning system.

[0098] Real-time stress at the bottom of the tower, the real-time stress state at the bottom of the bridge tower. In some embodiments, the real-time stress at the bottom of the tower can be obtained by a tower stress early warning module. An exemplary tower stress early warning module can be a stress monitoring system.

[0099] The real-time tension of the connecting screw at the bottom of the tower and the axial pressure borne by the connecting screw are measured. In some embodiments, the real-time stress at the bottom of the tower can be obtained through a tower bottom screw pressure early warning module. An exemplary tower bottom stress early warning module can be a bolt early warning force monitoring system.

[0100] (e) Determine the warning coefficient of each warning module based on the steel bridge tower pull-off warning information and the steel bridge tower pull-off threshold set;

[0101] In some embodiments, the warning coefficients include: bridge tower deviation warning coefficient, pre-tensioned cable force warning coefficient, tower base stress warning coefficient, and tower base bolt tension warning coefficient;

[0102] In some embodiments, the bridge tower deviation early warning coefficient is calculated as follows:

[0103]

[0104] Where y1(t) is the bridge tower offset early warning coefficient, X ms (t) represents the real-time displacement of the bridge tower during the m-th stage of tensioning, X m The threshold value for the bridge tower offset during the m-th level of tensioning;

[0105] The calculation method for the pre-tension cable force warning coefficient is as follows:

[0106]

[0107] Where y2(t) is the pre-tension cable force warning coefficient, N ms (t) represents the real-time cable force (N) of the pre-tensioned cable during the m-th stage tensioning process. m The threshold force of the pre-tensioned cable at the m-th tension level;

[0108] The calculation method for the tower bottom stress early warning coefficient is as follows:

[0109]

[0110] Where y3(t) is the tower bottom stress warning coefficient, σ ms (t) represents the real-time stress at the bottom of the tower during the m-th stage of tensioning, σ m The stress threshold at the bottom of the tower during the m-th stage of tensioning;

[0111] The calculation method for the tower bottom screw tension warning coefficient is as follows:

[0112]

[0113] Where y4(t) is the tension warning coefficient of the connecting screw at the bottom of the tower, F ms (t) represents the real-time tension of the tower base connecting screw during the m-th stage of tensioning, F mThe screw tension threshold;

[0114] (f) Determine the early warning contribution of each early warning module based on the early warning coefficient of each early warning module;

[0115] In some embodiments, the early warning contribution rate is used to reflect the degree of contribution of each early warning module to the overall risk at the current moment.

[0116] In some embodiments, the early warning contribution is calculated as follows:

[0117]

[0118] Where, p i (t) represents the early warning contribution of the i-th early warning module, y i (t) represents the warning coefficient of the i-th warning module, and n represents the number of warning modules;

[0119] For example: Let y1(t) = 0.8, y2(t) = 1.2, y3(t) = 0.6, and y4(t) = 0.9;

[0120] The contribution of the bridge tower offset early warning module is:

[0121] p1(t)=0.8 / (0.8+1.2+0.6+0.9)=0.229.

[0122] (g) Determine the information entropy of each early warning module based on its early warning contribution;

[0123] In some embodiments, the information entropy is an indicator used to measure the uncertainty of each early warning module. The smaller the information entropy value, the more deterministic the early warning information of the early warning module is.

[0124] In some embodiments, the information entropy of each early warning module is calculated as follows:

[0125]

[0126] Among them, E i Let i be the information entropy of the i-th early warning module. Let be the normalization factor, i be the number of early warning modules, t0 and t1 be the upper and lower limits of the integral, and p be the normalization factor. i (t) represents the early warning contribution of the i-th early warning module, and dt is the integral variable;

[0127] (h) Determine the weight coefficient of each early warning module based on the information entropy of each early warning module;

[0128] In some embodiments, the weighting coefficients of each early warning module are calculated as follows:

[0129]

[0130] Among them, w i Let E be the weight of the i-th early warning module. i Let be the information entropy of the i-th early warning module, and n be the number of early warning modules.

[0131] (i) Determine the comprehensive early warning index based on the early warning contribution of each early warning module and the weight coefficient of each early warning module;

[0132] In some embodiments, the comprehensive early warning index is calculated as follows:

[0133]

[0134] Where n is the number of early warning modules, w i Let y be the weight of the i-th early warning module. i (t) represents the warning coefficient of the i-th warning module;

[0135] In some embodiments, by adopting a dynamic weight allocation mechanism based on information entropy, the intelligent deviation early warning system can achieve more accurate risk assessment. Compared with the traditional fixed weight method, it can effectively reduce the false alarm rate and false negative rate, improve the early warning effect, and effectively solve the technical problem that the lack of a deviation feedback mechanism makes the deviation system prone to accidents and safety hazards during the deviation process.

[0136] (j) Based on the comprehensive early warning index and comprehensive early warning threshold, determine the pull-off early warning information at least one time point;

[0137] In some embodiments, the comprehensive warning threshold refers to the threshold used to determine whether it is necessary to stop the pull.

[0138] In some embodiments, deviation warning information can be confirmed by comparing a comprehensive warning index and a comprehensive warning threshold. For example, when comparing the comprehensive warning index with the comprehensive warning threshold, a deviation warning information is generated if the comprehensive warning index is greater than the comprehensive warning threshold. An exemplary comprehensive warning threshold can be 1.

[0139] In some embodiments, when the comprehensive early warning index is greater than the comprehensive early warning threshold, after issuing a tensioning warning, the tensioning system stops working, and after finding the cause and handling it, tensioning can continue; if the comprehensive early warning index is less than the comprehensive early warning threshold during the tensioning process, tensioning continues until the bridge tower deviation is equal to the bridge tower deviation after each level of tensioning, thus completing the current level of tensioning. Through multiple levels of tensioning, the tensioning process is completed until the bridge tower deviation is equal to the steel bridge tower tensioning amount.

[0140] A second aspect of the present invention provides a smart tension-biasing early warning system for steel bridge towers, used to execute a smart tension-biasing early warning method for steel bridge towers as described in the above-mentioned scheme, comprising:

[0141] The first determining module is used to determine the deflection of the steel bridge tower;

[0142] The second determining module is used to determine the steel bridge tower deflection information;

[0143] The third determining module is used to determine the set of threshold values ​​for steel bridge tower deflection;

[0144] The acquisition module is used to acquire early warning information about the steel bridge tower misalignment.

[0145] The fourth determining module is used to determine the warning coefficient of each warning module;

[0146] The fifth determination module is used to determine the early warning contribution of each early warning module;

[0147] The sixth determining module is used to determine the information entropy of each early warning module;

[0148] The seventh module is used to determine the weighting coefficients of each early warning module;

[0149] The eighth module is used to determine the comprehensive early warning index;

[0150] The ninth determination module is used to determine the pull-off warning information at least at one point in time.

[0151] Finally, it should be noted that the embodiments disclosed in this invention are merely preferred embodiments of this invention and are only used to illustrate the technical solutions of this invention, not to limit it. Although this invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this invention.

Claims

1. A smart anti-balance method for steel bridge towers, characterized in that, Includes the following steps: The steel bridge tower tension deflection is determined based on the cable saddle pre-deflection and the maximum longitudinal space at the top of the tower. Determining the steel bridge tower tension deflection information based on the steel bridge tower tension deflection. The steel bridge tower deflection information includes: the final tension of the pre-deflection cable, the number of stages of tensioning, the bridge tower deflection after each stage of tensioning, the cable force of the pre-deflection cable after each stage of tensioning, the tower base stress after each stage of tensioning, and the tension of the tower base connecting bolt after each stage of tensioning. The steel bridge tower deflection information also includes: real-time tower deflection, real-time cable force of the pre-deflection cable, real-time stress at the tower base, and real-time tension of the connecting bolt at the tower base; Determine the steel bridge tower tension deflection threshold set based on steel bridge tower tension deflection information. The steel bridge tower deflection threshold set refers to the set of thresholds used to determine whether the motion state or stress state of the steel bridge tower is normal during the deflection process. The set of threshold values ​​for steel bridge tower pull-off includes: The threshold sets for bridge tower deviation, pre-tensioned cable force, tower base stress, and connecting bolt tension. Early warning information on steel bridge tower misalignment is obtained based on each early warning module; The warning coefficients of each warning module are determined based on the steel bridge tower pull-off warning information and the steel bridge tower pull-off threshold set. The early warning contribution of each early warning module is determined based on its early warning coefficient. The information entropy of each early warning module is determined based on its early warning contribution. The weight coefficients of each early warning module are determined based on the information entropy of each module. The comprehensive early warning index is determined based on the early warning contribution of each early warning module and the weighting coefficient of each early warning module. Based on the comprehensive early warning index and comprehensive early warning threshold, determine the deviation early warning information at least one time point; The early warning modules include: a bridge tower deviation early warning module, a pre-deflection cable force early warning module, a tower base stress early warning module, and a tower base screw pressure early warning module.

2. The intelligent anti-deviation method for steel bridge towers according to claim 1, characterized in that, The warning coefficients include: bridge tower deviation warning coefficient, pre-deflection cable force warning coefficient, tower base stress warning coefficient, and tower base bolt tension warning coefficient; The calculation method for the bridge tower deviation early warning coefficient is as follows: ， in, This is the early warning coefficient for bridge tower deviation. For the first Real-time displacement of bridge towers during the tensioning process For the first The threshold for bridge tower misalignment under tensioning; The calculation method for the pre-tension cable force warning coefficient is as follows: ， in, The pre-tension cable tension warning coefficient is used. For the first Real-time cable force of the pre-tensioned cable during the tensioning process. For the first The pre-tensioned cable force threshold of the tensioned cable; The calculation method for the tower bottom stress early warning coefficient is as follows: ， in, This is the early warning coefficient for the stress at the bottom of the tower. For the first Real-time stress at the bottom of the tower during the tensioning process. For the first The stress threshold at the bottom of the tower under tension; The calculation method for the tower bottom screw tension warning coefficient is as follows: ， in, The tension warning coefficient for the connecting screw at the bottom of the tower. For the first Real-time tension of the tower base connecting bolts during the tensioning process. This is the screw tension threshold.

3. The intelligent anti-eccentricity warning method for steel bridge towers according to claim 2, characterized in that, The calculation method for the early warning contribution is as follows: ， in, For the first The early warning contribution of each early warning module. For the first The warning coefficient of each warning module, This refers to the number of early warning modules.

4. The intelligent anti-eccentricity warning method for steel bridge towers according to claim 3, characterized in that, The information entropy of each early warning module is calculated as follows: ， in, For the first Information entropy of each early warning module As the normalization factor, The number of early warning modules, , Let be the upper and lower limits of the integral. For the first The early warning contribution of each early warning module. It is the integral variable.

5. The intelligent anti-eccentricity warning method for steel bridge towers according to claim 4, characterized in that, The comprehensive early warning index is calculated as follows: ， in, The number of early warning modules, For the first The weight of each early warning module, For the first The warning coefficient of each warning module.

6. The intelligent anti-eccentricity warning method for steel bridge towers according to claim 5, characterized in that, The comprehensive early warning threshold refers to the threshold used to determine whether it is necessary to stop the pull-off. The deviation warning information is confirmed by comparing the comprehensive warning index and the comprehensive warning threshold.

7. A smart anti-deviation early warning system for steel bridge towers, characterized in that, A method for implementing a smart anti-balance warning system for steel bridge towers according to any one of claims 1-6 includes: The first determining module is used to determine the deflection of the steel bridge tower; The second determining module is used to determine the steel bridge tower deflection information; The third determining module is used to determine the set of steel bridge tower deflection thresholds; The acquisition module is used to acquire early warning information about the steel bridge tower misalignment. The fourth determining module is used to determine the warning coefficient of each warning module; The fifth determination module is used to determine the early warning contribution of each early warning module; The sixth determining module is used to determine the information entropy of each early warning module; The seventh module is used to determine the weighting coefficients of each early warning module; The eighth module is used to determine the comprehensive early warning index; The ninth determination module is used to determine the pull-off warning information at least at one point in time.

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