Intelligent prestress string supporting system for steel trestle

Abstract

The invention discloses an intelligent prestressed string supporting system for a steel trestle. A bailey chord connector is in bolted connection with a bailey beam lower chord through a bolt; a support frame vertical rod is bolted with a lug plate of the Bailey chord connector, a support frame lug plate is arranged at the bottom of the support frame, and a horizontal tension rod prestress intelligent adjusting device is arranged in the middle of the support frame to realize preliminary adjustment of the prestress of the horizontal tension rod; hogging moment generated by prestress of the tensioning chord members can effectively offset external load of the main body structure, and stability and bearing capacity of the main body structure are improved; according to the intelligent prestress optimization mechanism, an intelligent system is introduced, accurate control over prestress of a string supporting system under the complex environment condition can be achieved, the overall stability of the structure is enhanced, a PLC main control platform receives information of a data encoder, iteration optimization is conducted on the prestress through a gradient descent method, an instruction is made, and the intelligent system is optimized. Big data interaction of the string supporting system is achieved, and the system has the advantages of being digitized, intelligent and high in informatization degree.

Description

Technical Field

[0001] The invention belongs to the technical field of prefabricated steel structure bridge construction, and specifically relates to an intelligent prestressed string support system for a steel trestle. Background Art

[0002] As a highway prefabricated steel structure bridge, steel trestle is widely used in water construction, earthquake relief, dangerous bridge reinforcement and road repair. Steel trestle is constructed with Bailey beams and I-beams, which have high strength and rigidity. The components of steel trestle are prefabricated and assembled on site to shorten the construction period. In addition, most of the components of steel trestle are standard parts, which can be disassembled and reused, which has the advantage of saving engineering costs.

[0003] The strength, stability and fatigue resistance of traditional steel trestles have been significantly reduced. Therefore, it is urgent to develop a lightweight and highly intelligent prestressed string support system suitable for various complex environmental conditions to improve the stability of large-span steel trestles. The use of intelligent equipment can greatly shorten the repair time and improve construction efficiency. Summary of the invention

[0004] The present invention provides an intelligent string support system for a steel trestle, which can effectively solve the problems in the background technology.

[0005] The present invention adopts the following technical solutions to achieve the above-mentioned purpose:

[0006] An intelligent prestressed chord support system for a steel trestle, the support system having a Bailey chord connector connected to the lower chord bolt of the Bailey beam, to ensure that the main structure of the steel trestle is connected to the chord support system as a whole, so as to achieve effective transmission of the upper structure load; the Bailey chord connectors are arranged in three groups along the longitudinal direction of the main structure of the steel trestle, and each group of the Bailey chord connectors is arranged in four groups along the transverse direction of the main structure of the steel trestle; wherein the four Bailey chord connectors in the middle group are a pair of two; each pair of Bailey chord connectors is connected by a support frame , and the two pairs of Bailey chord connectors are connected as a whole through a horizontal tension rod; prestressed intelligent adjustment devices are respectively arranged at both ends of the horizontal tension rod to realize automatic loading and unloading of the horizontal tension rod, thereby improving construction efficiency; the support frame comprises two support frame vertical rods arranged symmetrically on the left and right; the two support frame vertical rods are respectively connected to the corresponding Bailey chord connectors; the two support frame vertical rods are connected as a whole through two support frame horizontal rods arranged up and down; the lower end of each support frame vertical rod is respectively connected to the other two groups of Bailey chord connectors through an oblique tension rod;

[0007] The support system is also provided with an intelligent prestressed stress optimization mechanism; the intelligent prestressed stress optimization mechanism includes a prestressed stress intelligent driving device, an intelligent loading and unloading device, a displacement sensor, a fiber grating stress sensor, a data encoder and a PLC main control platform. By introducing the intelligent system, it is possible to achieve precise control of the prestress of the string support system under complex environmental conditions and enhance the overall stability of the structure. The PLC main control platform receives the information of the data encoder, iteratively optimizes the prestress through the gradient descent method, and issues instructions to realize the big data interaction of the string support system.

[0008] The Bailey chord connector includes a connector horizontal bar, a connector ear plate and a connector limiting bolt hole; the connector horizontal bar is arranged along the transverse direction of the steel trestle, and the connector ear plate and the connector limiting bolt hole are arranged between the two connector horizontal bars; the connector ear plate has two limiting holes, and the top is welded to the center position of the connector horizontal bar; the connector limiting bolt holes are arranged at the top of the connector horizontal bar, symmetrically arranged along the longitudinal direction of the connector horizontal bar, and the spacing corresponds to the bolt holes of the lower chord of the Bailey beam, and are connected with pins or bolts.

[0009] The support frame includes a support frame vertical rod, a support frame horizontal rod, a support frame ear plate and a support frame vertical rod bolt hole. The support frame vertical rod is arranged one on each side and welded to the support frame horizontal rod; the support frame horizontal rod is arranged up and down along a certain distance; the support frame ear plate is arranged one on each side symmetrically along the central axis of the support frame vertical rod, and the support frame ear plate is provided with a bolt hole for connecting the oblique tension rod; the support frame vertical rod bolt holes are provided with two at a certain interval on the upper part of the support frame vertical rod, and the interval corresponds to the spacing of the limit holes of the connector ear plate welded to the Bailey chord connector; the external part of the support frame vertical rod is installed with a prestressed intelligent adjustment device to realize the automatic loading and unloading of the horizontal tension rod and the preliminary adjustment of the prestress, so as to improve the construction efficiency.

[0010] The oblique tensioning rod includes a bidirectional screw, a threaded sleeve, and a U-shaped joint; threads are provided at both ends of the bidirectional screw, and the threads at both ends are in opposite directions. The threads are rotatably connected to the threaded sleeve. When the bidirectional screw rotates, it will drive the support frame to move in opposite directions, thereby generating prestress and enhancing the overall stability; a bolt hole is opened in the middle position of the U-shaped joint, and the diameter of the bolt hole is consistent with the diameter of the limiting holes of the ear plate of the support frame and the ear plate of the chord rod connector, ensuring that the support frame and the chord rod connector are firmly connected.

[0011] The horizontal tension rod comprises a bidirectional screw, a threaded sleeve and a toothed joint; the toothed joint is provided with a clamping groove for clamping with the prestressed intelligent adjustment device, so as to realize the rapid connection of the horizontal tension rod and the preliminary adjustment of the prestress of the string support system. The bidirectional screw and threaded sleeve are consistent with the bidirectional screw and threaded sleeve of the oblique tension rod.

[0012] The intelligent prestress optimization mechanism includes an intelligent prestress drive device, an intelligent prestress adjustment device, a displacement sensor, a fiber Bragg grating stress sensor, a data encoder and a PLC main control platform. The intelligent prestress drive device is installed on a bidirectional screw and includes an intelligent drive element, an active bevel gear and a driven bevel gear. The intelligent drive element is fixedly connected to the active bevel gear, and the driven bevel gear is radially fixedly installed inside the bidirectional screw. The gears of the active bevel gear and the driven bevel gear are meshed to ensure that the active bevel gear drives the driven bevel gear to rotate when the active bevel gear rotates, thereby generating prestress in the string support system; after receiving the instruction from the PLC main control platform, the intelligent drive element drives the active bevel gear connected to it to rotate clockwise, and the active bevel gear rotates to drive the driven bevel gear to rotate counterclockwise along the radial direction of the bidirectional screw, thereby driving the bidirectional screw to be tightly fitted with the threaded sleeve to generate prestress; the intelligent drive element can also drive the bidirectional screw to rotate a suitable number of turns according to the instruction of the PLC main control platform to achieve the effect of optimal prestress.

[0013] The prestressed intelligent adjustment device includes an intelligent telescopic element, a first rack, a gear, a second rack, a fixed block and a spring; the intelligent telescopic element is fixedly connected to the first rack and can drive the first rack to move up and down; the first rack, the gear and the second rack are meshed with each other, and a linkage reaction is formed between the three; the top of the fixed block is an inclined surface, which facilitates the horizontal tension rod to be clamped and fixed with the inclined surface of the fixed block when it contacts the fixed block; the spring is installed at the bottom of the fixed block, and the plug-in fit between the clamping groove and the fixed block is achieved under the action of the spring elastic force.

[0014] Specifically, after receiving the instruction from the PLC main control platform, the intelligent telescopic element performs locking and unlocking operations according to different working conditions; when installing the horizontal tension rod, the intelligent telescopic element is unlocked, and the toothed joint of the horizontal tension rod contacts the inclined surface of the fixed block of the prestressed intelligent adjustment device. As the horizontal tension rod is continuously inserted, the fixed block moves downward, and the spring contracts. When the insertion depth of the horizontal tension rod reaches the position of the clamping groove, the fixed block moves upward under the action of the spring elastic force, and the fixed block is clamped and fixed with the clamping groove, and the intelligent telescopic element is locked. When the tension string support system needs to be dismantled, the intelligent telescopic element is started in the unlocked state, the first rack moves upward, and the driving gear rotates clockwise. The gear rotates to drive the second rack to move downward, and the movement of the second rack drives the fixed block to disengage from the fixed groove, so that the horizontal tension rod can be disengaged from the support frame.

[0015] The displacement sensor is installed on the Bailey chord connector of the string support system, and is mainly used to measure the deflection, vibration, strain and other physical parameters of the Bailey chord connector under the application of prestress, external load and environmental effects; the fiber grating stress sensor is installed on the oblique tension rod, horizontal tension rod and support frame, and the stress value of each detection component is obtained according to the basic principles of material mechanics.

[0016] The working principle of the intelligent prestress optimization mechanism is as follows: under the influence of external environment such as external load, deadweight of the main structure and wind temperature, the displacement sensor and the fiber grating stress sensor measure various physical parameters of the measured component and transmit the measurement signal to the data encoder. The data encoder encodes each parameter and optimizes the prestress value by the gradient descent method. The optimized prestress value is received by the PLC main control platform, and instructions are given to the prestress intelligent drive device and the prestress intelligent adjustment device. The intelligent telescopic element realizes the preliminary adjustment of the prestress by controlling the insertion depth of the tension rod, and the intelligent drive element realizes the fine adjustment of the prestress by rotating the bidirectional screw.

[0017] The specific implementation scheme of the gradient descent prestress optimization algorithm in the data encoder is as follows:

[0018] S1: Determine the prestress optimization function model, transmit the influencing parameters of the prestress of the tension support system to the data encoder, and establish m sample optimization function models F (x1, x2, ..., x n )

[0019]

[0020] Among them: a i (i=0,1,2,…,n) are the parameters of the prestress optimization model, x i (i=0, 1, 2, ..., n) is the influencing factor of the prestress optimization function model for each sample.

[0021] S2: Establish the CF loss function. In order to select the optimal solution of the prestressed model from the m sample functions, the MSE mean square error analysis method is used to analyze the sample output value f j The square of the difference between the prestressed stress optimization function and the prestressed stress optimization function is obtained to obtain the CF loss function, and the degree of fitting of the prestressed stress optimization function is measured according to the CF loss function. That is, the minimization of the loss function means the best degree of fitting, and the corresponding prestressed stress optimization model parameters are the optimal parameters.

[0022]

[0023] S3: Determine the gradient of the CF loss function. If you want to find the minimum loss function value as quickly as possible, you need to search in the direction where the derivative value of the CF loss function decreases, that is, the negative gradient direction. By continuously iterating and solving the CF loss function through the gradient descent method, you can get the minimized loss function and the parameter values ​​of the prestressed optimization function model.

[0024] Specifically, for the prestress optimization model parameter a i(i=0,1,2,…,n), in a i The partial derivative of the CF loss function is calculated at the position, and the collection of n negative partial derivatives is called the gradient of the CF loss function, which is expressed as follows:

[0025]

[0026] S4: Determine the gradient descent distance. In order to avoid gradient explosion, gradient disappearance and local optimal solution when the data encoder is looking for the optimal prestress function, the learning efficiency α is introduced to correct the gradient of the loss function, and the distance of the current position descent can be obtained, that is:

[0027]

[0028] S5: Determine whether all prestress optimization model parameters a i (i=0,1,2,…,n), the gradient descent distance is less than ε. If it is less than ε, the algorithm terminates, and all the current prestressed optimization model parameters a i (i=0, 1, 2, ..., n), which is the final result; otherwise, go to step S6 to check a i to update.

[0029] S6: Update all a i (i=0,1,2,…,n), for a i , and its update expression is as follows:

[0030]

[0031] After the update is completed, the algorithm goes to step S2 for recalculation. When all gradient descent distances are less than ε, the algorithm terminates and outputs the prestressed optimal function model F(x1, x2, ..., x n ).

[0032] S7: According to the iterative method, the optimal prestress function model of the tension rod can be obtained. Since the prestress of the tension rod of the string support system is controlled by the toothed joint extension length controlled by the intelligent telescopic element and the intelligent driving element driving the bidirectional screw to rotate, the preliminary and fine adjustments of the prestress of the tension rod are achieved. Therefore, based on the optimal prestress function of the tension rod, the correction functions λ and β are introduced to establish the functional relationship between the toothed joint extension length of the bidirectional screw and the number of rotations of the bidirectional screw and the optimal prestress function of the tension rod:

[0033]

[0034] The gradient descent prestressed stress optimization algorithm uses a CF loss function to search for the global optimal solution in the sample database along the direction of the fastest negative gradient descent. The optimal function model of prestressed stress is found through continuous iteration, which ensures the timeliness of the convergence speed. The introduction of learning efficiency α effectively avoids the occurrence of local optimal solutions in the search process, ensuring the extensiveness and globality of the search.

[0035] Preferably, the prestress optimization algorithm for the intelligent tensioned support system provided by the present invention can run the calculation program on the PLC main control platform processor, store the calculation results, and execute the above method.

[0036] The present invention proposes an intelligent prestressed string support system and optimization method for a steel trestle, which adopts the above technical solution and has the following beneficial effects:

[0037] 1. The intelligent prestressed chord support system and optimization method for steel trestle provided by the present invention can effectively disperse the external load of the main structure through the reverse bending moment generated by the prestress of the tensioned chord rod, improve the stability and bearing capacity of the main structure, have the advantages of strong spanning capacity, light component weight and obvious economic benefits, and are suitable for post-disaster reconstruction and rapid emergency temporary projects under high-cold and high-altitude environmental conditions.

[0038] 2. The intelligent prestressed tensioned brace system and optimization method for steel trestles provided by the present invention introduce an intelligent system. After the sample data detected by the displacement sensor and the fiber grating stress sensor are processed and analyzed by the data encoder, the PLC main control platform issues instructions to the intelligent driving element and the intelligent telescopic element, thereby realizing big data interaction of the tensioned brace system, which has the characteristics of high digitization, intelligence and informatization.

[0039] 3. The intelligent prestressed string support system and optimization method for steel trestles provided by the present invention optimizes the prestress value through a gradient descent prestress optimization algorithm, establishes a multivariate prestress function model according to external load information, performs a global sample function search along the direction of the negative gradient descent of the CF loss function, and obtains the prestress optimal function model through continuous iterative calculation. This method has the advantages of fast convergence speed and wide search range, and can realize precise control of the prestress of the string support system, thereby optimizing the structural characteristics and extending the service life cycle of the structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is the elevation drawing of the intelligent prestressed string support system;

[0041] Figure 2 It is the side view of the intelligent prestressed string support system;

[0042] Figure 3-1 , 3-23-3 is a schematic diagram of the structure of the Bailey chord connector;

[0043] Figure 4-1 , 4-2 is a structural schematic diagram of the support frame;

[0044] Figure 5-1 , 5-2 It is a structural schematic diagram of the oblique tension rod;

[0045] Figure 5-3 , 5-4 It is a structural schematic diagram of the horizontal tension rod;

[0046] Figure 6 It is the working principle diagram of the intelligent prestressing optimization mechanism;

[0047] Figure 7 It is a prestressed intelligent driving device;

[0048] Figure 8 It is an intelligent loading and unloading device;

[0049] Fig. 9 Program diagram for the gradient descent prestress optimization algorithm.

[0050] 1. Bailey chord connector, 11. Connector horizontal rod, 12. Connector ear plate, 13. Connector limit bolt.

[0051] 2. Support frame, 21. Support frame vertical rod, 22. Support frame horizontal rod, 23. Support frame ear plate, 24. Support frame vertical rod bolt hole.

[0052] 3. Oblique tension rod, 31. Bidirectional screw, 32. Threaded casing, 33. U-shaped joint.

[0053] 4. Horizontal tension rod, 41. Toothed joint, 42. Snap-in groove.

[0054] 5. Intelligent prestressed optimization mechanism, 51. Prestressed intelligent driving device, 511. Intelligent driving element, 512. Active bevel gear, 513. Driven bevel gear, 52. Prestressed intelligent adjustment device, 521. Intelligent telescopic element, 522. First rack, 523. Gear, 524. Second rack, 525. Fixed block, 526. Spring, 53. Displacement sensor, 54. Fiber Bragg grating stress sensor, 55. Data encoder, 56. PLC main control platform. DETAILED DESCRIPTION

[0055] The following is a detailed description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] In this embodiment, Figure 1 , Figure 2 As shown: This embodiment proposes an intelligent prestressed tension string support system and optimization method for a steel trestle, including a Bailey chord connector 1, a support frame 2, an oblique tension rod 3, a horizontal tension rod 4 and an intelligent prestressed optimization mechanism 5.

[0057] like Figure 3-1 , 3-2 , 3-3: the Bailey chord connector includes a connector horizontal rod 11, a connector ear plate 12 and a connector limit bolt hole 13;

[0058] Furthermore, the connector horizontal rod 11 is made of channel steel with a specification of [10×1380mm. The connector horizontal rod is arranged in the transverse direction of the steel trestle with a transverse spacing of 90mm. The connector horizontal rod 11 is connected to the Bailey lower chord with a pin or bolt;

[0059] Furthermore, the connector ear plate 12 is set to be two, with a thickness of 25 mm, and two limiting holes are opened in the middle position thereof, and the center distance between the two limiting holes is 100 mm. The top of the connector ear plate 12 is welded at the center position inside the connector horizontal rod 11;

[0060] Furthermore, the connector limiting bolt hole 13 is arranged at the top of the connector horizontal rod 11, the bolt hole diameter is 40 mm, and four connector limiting bolt holes 13 are symmetrically arranged along the longitudinal direction of the connector horizontal rod 11. The bolt hole spacing corresponds to the bolt hole of the lower chord of the Bailey beam, which are 260 mm and 330 mm respectively.

[0061] like Figure 4-1 , 4-2 As shown: the support frame 2 includes a support frame vertical rod 21, a support frame horizontal rod 22, a support frame ear plate 23 and a support frame vertical rod bolt hole 24;

[0062] Furthermore, the support frame vertical rod 21 is made of [10×900mm channel steel, one is arranged on each side, the distance between the two support frame vertical rods 21 is 900mm, and they are welded to the support frame horizontal rod 22; the support frame vertical rod 21 is externally installed with an intelligent loading and unloading device 52 to realize automatic loading and unloading of the horizontal tension rod and preliminary adjustment of the prestress, so as to improve the construction efficiency;

[0063] Furthermore, the support frame horizontal rod 22 is made of [10×920mm channel steel, one is arranged at the upper and lower positions, the spacing is 180mm, and the lower support frame horizontal rod 22 is 250mm away from the bottom of the support frame vertical rod 21;

[0064] Furthermore, the support frame ear plate 23 is arranged symmetrically along the central axis of the support frame vertical rod 21, and the thickness of the support frame ear plate 23 is 25 mm. A bolt hole with a diameter of 50 mm is opened in the middle position of the support frame ear plate 23 to connect the oblique tension rod 3;

[0065] Furthermore, two bolt holes 24 of the support frame vertical rod are provided at a certain interval on the upper part of the support frame vertical rod. In this embodiment, the interval between the bolt holes 24 of the support frame vertical rod is 100 mm.

[0066] like Figure 5-1 , 5-2 As shown, the oblique tension rod 3 includes a bidirectional screw 31, a threaded sleeve 32, and a U-shaped joint 33; threads are provided at both ends of the bidirectional screw 31, and the threads at both ends are in opposite directions. The threads are rotatably connected with the threaded sleeve 32. When the bidirectional screw 31 rotates, it drives the support frame 2 to have a tendency to move in opposite directions, thereby generating prestress and enhancing the overall stability;

[0067] Furthermore, a bolt hole is provided in the middle of the U-shaped joint 33, and the diameter of the bolt hole is consistent with the diameter of the limiting hole of the ear plate of the support frame and the ear plate of the chord rod connector. In this embodiment, it is set to 50 mm to ensure that the support frame and the chord rod connector are firmly connected;

[0068] Furthermore, a guide device is provided in front of the winch platform for adjusting the entry angle of the lifting traction rope to avoid friction and collision when the lifting traction rope enters the winch from the anchor.

[0069] Furthermore, if Figure 5-3 , 5-4 As shown, the horizontal tension rod 4 includes a bidirectional screw 31, a threaded sleeve 32 and a toothed joint 41; the toothed joint 41 is provided with a plurality of snap-in grooves 42, and the snap-in grooves 42 are snap-connected with the prestressed intelligent adjustment device 52 to achieve a quick connection of the horizontal tension rod 4, and also to achieve a preliminary adjustment of the prestress of the string support system.

[0070] It is worth noting that the bidirectional screw 31 and the threaded sleeve 32 are consistent with the bidirectional screw 31 and the threaded sleeve 32 of the oblique tension rod 3;

[0071] like Figure 6-8 As shown, the intelligent prestress optimization mechanism 5 includes a prestress intelligent driving device 51, a prestress intelligent adjusting device 52, a displacement sensor 53, a fiber grating stress sensor 54, a data encoder 55 and a PLC main control platform 56;

[0072] like Figure 7 As shown, the prestressed intelligent driving device 51 is installed on the bidirectional screw 31, including an intelligent driving element 511, a driving bevel gear 512 and a driven bevel gear 513. The intelligent driving element 511 is fixedly connected to the driving bevel gear 512, and the driven bevel gear 513 is radially fixedly installed inside the bidirectional screw 31. The gears of the driving bevel gear 512 and the driven bevel gear 513 are meshed to ensure that the driven bevel gear 513 is driven to rotate when the driving bevel gear 512 rotates, so that the string support system generates prestress;

[0073] Specifically, after receiving the instruction from the PLC main control platform 56, the intelligent driving element 511 drives the active bevel gear 512 connected thereto to rotate clockwise, and the active bevel gear 512 rotates to drive the driven bevel gear 513 to rotate counterclockwise along the radial direction of the bidirectional screw 31, thereby driving the bidirectional screw 31 to be tightly fitted with the threaded sleeve 32 to generate a pre-tightening force;

[0074] Furthermore, the intelligent driving element 511 can also drive the bidirectional screw 31 to rotate a suitable number of turns according to the instructions of the PLC main control platform 56 to achieve the optimal prestressing effect.

[0075] like Figure 8 As shown, the prestressed intelligent adjustment device 52 includes an intelligent telescopic element 521, a first rack 522, a gear 523, a second rack 524, a fixing block 525 and a spring 526; the intelligent telescopic element 521 is fixedly connected to the first rack 522, and can drive the first rack 522 to move up and down; the gear 523 is bolted to the prestressed intelligent adjustment device 52; the first rack 522, the gear 523 and the second rack 523 are meshed with each other, and a linkage reaction is formed between the three;

[0076] Furthermore, the top of the fixing block 525 is an inclined surface, so that when the horizontal tension rod 4 contacts the fixing block 525, the clamping groove 42 is clamped and fixed with the inclined surface of the fixing block 525;

[0077] Furthermore, the spring 526 is installed at the bottom of the fixing block 525, and the plug-in fit between the clamping groove 42 and the fixing block 525 is achieved under the action of the spring force;

[0078] Specifically, after the intelligent telescopic element 521 receives the instruction from the PLC main control platform 56, the intelligent telescopic element 521 performs locking and unlocking operations according to different working conditions;

[0079] When installing the horizontal tension rod 4, the intelligent telescopic element 521 is unlocked, and the toothed joint 41 of the horizontal tension rod 4 contacts the inclined surface of the fixed block 525 of the prestressed intelligent adjustment device 52. As the horizontal tension rod 4 is continuously inserted, the fixed block 525 moves downward and the spring contracts. When the insertion depth of the horizontal tension rod 4 reaches the position of the snap-in groove 42, under the action of the spring elastic force, the fixed block 525 moves upward, and the fixed block 525 is snap-fitted and fixed to the snap-in groove 42, and the intelligent telescopic element 521 is locked.

[0080] When the horizontal tension rod 4 of the string support system needs to be removed, the intelligent telescopic element 521 is started to be in the unlocked state, the first rack 522 moves upward, and the driving gear 523 rotates clockwise. The gear 523 rotates to drive the second rack 524 to move downward. The movement of the second rack 524 drives the fixing block 525 to disengage from the clamping groove 42 of the toothed joint 41, thereby achieving the purpose of the horizontal tension rod 4 being able to disengage from the support frame 2.

[0081] Furthermore, the displacement sensor 53 is installed on the Bailey chord connector 1 of the string support system, and is mainly used to measure the physical parameters such as deflection, vibration, strain, etc. of the Bailey chord connector 1 under the application of prestress, external load and environmental effects.

[0082] The fiber grating stress sensor 54 is installed on the oblique tension rod 3, the horizontal tension rod 4 and the support frame 2, and the stress value of each detection component is obtained according to the basic principle of material mechanics.

[0083] Furthermore, the fiber Bragg grating stress sensor 54 is installed on the oblique tension rod 3, the horizontal tension rod 4 and the support frame 2, and the stress value of each detection component is obtained according to the basic principle of material mechanics.

[0084] like Figure 6 As shown, the working principle of the intelligent prestress optimization mechanism 5 is as follows: under the influence of external loads, the deadweight of the main structure, wind temperature and other external environments, the displacement sensor 53 and the fiber grating stress sensor 54 measure the various physical parameters of the measured component and transmit the measurement signal to the data encoder 55. The data encoder 55 encodes each parameter and optimizes the prestress value by the gradient descent method. The optimized prestress value is received by the PLC main control platform 56, and instructions are given to the prestress intelligent drive device 51 and the prestress intelligent adjustment device 52. The intelligent telescopic element 521 realizes the preliminary adjustment of the prestress by controlling the insertion depth of the horizontal tension rod 4, and the intelligent drive element 511 realizes the fine adjustment of the prestress by rotating the bidirectional screw 31.

[0085] In addition, in this embodiment, the gradient descent prestress optimization algorithm in the data encoder includes the following steps:

[0086] The gradient descent prestressed stress optimization algorithm is to establish m sample functions composed of n influencing factors, use the MSE mean square error analysis method to measure the fitting degree of the prestressed stress optimization function, search for the global sample function along the direction of the fastest gradient descent of the CF loss function, and find the optimal parameters of the prestressed stress optimization model through continuous iterative calculation.

[0087] Specifically, in this embodiment, four influencing factors, namely, the deadweight of the main structure, dynamic load, wind load and temperature, are selected, 50 sample points are randomly selected from the PC main control platform, a quaternion function is established, and the gradient descent prestress optimization algorithm is described in detail:

[0088] S1: Determine the prestress optimization function model

[0089]

[0090] S2: Establishing the CF loss function. The prestress value of the cable-stayed support system will change with the changes of external influencing factors and external loads. In this embodiment, 50 prestress values ​​are randomly selected from the PLC main control platform, and the MSE mean square error analysis method is used to establish the CF loss function. Each prestress optimization function model corresponds to a relative CF loss function value. The smaller the CF loss function value, the higher the degree of fitting of the prestress function model, thereby transforming the problem of searching for the prestress function model into solving the problem of solving the minimum value of the CF loss function.

[0091]

[0092] S3: Determine the gradient of the CF loss function. If you want to find the minimum loss function value as quickly as possible, you need to search along the direction where the derivative value of the CF loss function decreases, that is, the negative gradient direction. By continuously iterating and solving the CF loss function through the gradient descent method, you can get the minimum value of the loss function and the optimal parameter value of the prestressing function model as quickly as possible. Specifically, for the prestressing optimization model parameter a i (i=0, 1, 2, 3, 4), respectively, the partial derivatives of the CF loss function are calculated. The collection of the four negative partial derivatives is called the gradient of the CF loss function, and its expression is as follows:

[0093]

[0094] S4: Determine the gradient descent distance. In order to avoid gradient explosion, gradient disappearance and local optimal solution when the data encoder is looking for the optimal prestress function, the step length α is introduced to correct the gradient of the loss function, and the distance of the current position descent can be obtained, that is:

[0095]

[0096] S5: Determine whether all prestress optimization model parameters ai (i=0,1,2,3,4), the gradient descent distance is less than ε. If it is less than ε, the algorithm terminates. All the current prestress optimization model parameters a i (i=0, 1, 2, 3, 4), which is the final result; otherwise, go to step S6 for a i to update.

[0097] S6: Update all a i (i=0,1,2,3,4), for a i , and its update expression is as follows:

[0098]

[0099] After the update is completed, the algorithm is terminated and the optimal function model F of prestressing is output. j (x1, x2, …, x n ).

[0100] As a preferred embodiment, in this embodiment, from the initial position Perform iterative search. For ease of understanding, the learning efficiency is fixed at α = 0.01. After n iterations, the amplitude of the gradient vector is close to 0.001, that is, parameter a i <ε=0.001, the detailed iteration process is as follows:

[0101] T0: CF loss function initial value:

[0102] At this time: a0i(i=0, 1, 2, 3, 4)>ε=0.001, the amplitude of the gradient vector is large, and the first iteration is performed.

[0103] T1: First iteration: Update the CF loss function parameters a0 i (i = 0, 1, 2, 3, 4). After the update is completed, go to step S2 to recalculate the value of the CF loss function, that is,

[0104]

[0105] At this time: a1 i (i = 0, 1, 2, 3, 4) > ε = 0.001, the amplitude of the gradient vector is relatively large, and the second iteration is performed.

[0106] T2: Second iteration: Update the CF loss function parameters a1 i (i = 0, 1, 2, 3, 4). After the update is completed, go to step S2 to recalculate the value of the CF loss function, that is,

[0107]

[0108] i(i=0, 1, 2, 3, 4)>ε=0.001, the amplitude of the gradient vector is large, and the third iteration is performed.

[0109] …

[0110] Tn: nth iteration: Update the CF loss function parameters an-1i (i=0, 1, 2, 3, 4). After the update is completed, go to step S2 to recalculate the value of the CF loss function, that is,

[0111]

[0112] an i(i=0,1,2,3,4)<ε=0.001, the amplitude of the gradient vector meets the requirements, and the algorithm terminates. The parameters an i(i=0,1,2,3,4) corresponding to the CF loss function are the optimal solutions for the parameters of the prestress optimization function model, that is,

[0113]

[0114] S7: The intelligent string support system realizes precise adjustment of prestress through the combined effect of the length of the toothed joint 41 of the horizontal tension rod 4 extending into the prestressed intelligent adjustment device 52 and the number of rotations of the bidirectional screw 31 driven by the intelligent driving element 511. In this embodiment, correction functions λ and β are introduced to establish a functional relationship between the extension length of the toothed joint 41 of the bidirectional screw 31 and the number of rotations of the bidirectional screw 31 and the optimal prestress function of the tension rod, so that the control of the prestress of the string support system by the PLC main control platform 56 can be transformed into direct control of the extension length of the toothed joint 41 and the number of rotations of the bidirectional screw 31, which greatly improves the prestress adjustment process and adjustment accuracy.

[0115]

[0116] The gradient descent prestressed stress optimization algorithm uses a CF loss function to search for the global optimal solution in the sample database along the direction of the fastest negative gradient descent, and finds the prestressed stress optimal function model through n iterations, thereby ensuring the high efficiency of the convergence speed. After introducing the learning efficiency α, the local optimal solution in the search process is effectively avoided, thereby ensuring the extensiveness and globality of the search.

[0117] The above description is only a preferred specific implementation manner of the present invention, and does not limit the patent scope of the present invention. Although the present invention has been described in detail through the above preferred embodiments, ordinary technicians in the relevant field should understand that various changes, modifications, substitutions and variations can be made to the specific implementation manner of the present invention with reference to the above embodiments, all of which are included in the patent protection scope of the present invention.

Claims

1. An intelligent prestressed string support system for a steel trestle, the support system having a Bailey chord connector connected to the lower chord of the Bailey beam bolt, to ensure that the main structure of the steel trestle is connected to the string support system as a whole, so as to achieve effective transmission of the upper structure load; the Bailey chord connectors are arranged in three groups along the longitudinal direction of the main structure of the steel trestle, and each group of the Bailey chord connectors is arranged in four groups along the transverse direction of the main structure of the steel trestle; wherein the four Bailey chord connectors in the middle group are a pair of two; each pair of Bailey chord connectors is connected by a support frame The two pairs of Bailey chord connectors are connected as a whole through a horizontal tension rod; prestressed intelligent adjustment devices are respectively arranged at both ends of the horizontal tension rod to realize automatic loading and unloading of the horizontal tension rod, thereby improving construction efficiency; the support frame comprises two support frame vertical rods arranged symmetrically on the left and right; the two support frame vertical rods are respectively connected to the corresponding Bailey chord connectors; the two support frame vertical rods are connected as a whole through two support frame horizontal rods arranged up and down; the lower end of each support frame vertical rod is respectively connected to the other two groups of Bailey chord connectors through an oblique tension rod; The support system is also provided with an intelligent prestressed stress optimization mechanism; the intelligent prestressed stress optimization mechanism includes a prestressed stress intelligent driving device, an intelligent loading and unloading device, a displacement sensor, a fiber grating stress sensor, a data encoder and a PLC main control platform. By introducing the intelligent system, it is possible to achieve precise control of the prestress of the string support system under complex environmental conditions and enhance the overall stability of the structure. The PLC main control platform receives the information of the data encoder, iteratively optimizes the prestress through the gradient descent method, and issues instructions to realize the big data interaction of the string support system.

2. The intelligent prestressed string support system for a steel trestle according to claim 1 is characterized in that: The Bailey chord connector includes a connector horizontal bar, a connector ear plate and a connector limiting bolt hole; the connector horizontal bar is arranged along the transverse direction of the steel trestle, and the connector ear plate and the connector limiting bolt hole are arranged between the two connector horizontal bars; the connector ear plate has two limiting holes, and the top is welded to the center position of the connector horizontal bar; the connector limiting bolt holes are arranged at the top of the connector horizontal bar, symmetrically arranged along the longitudinal direction of the connector horizontal bar, and the spacing corresponds to the bolt holes of the lower chord of the Bailey beam, and are connected with pins or bolts.

3. The intelligent prestressed string support system for a steel trestle according to claim 1 is characterized in that: The support frame includes a support frame vertical rod, a support frame horizontal rod, a support frame ear plate and a support frame vertical rod bolt hole; the support frame vertical rod is arranged one on each side and welded to the support frame horizontal rod; the support frame horizontal rod is arranged up and down along a certain distance; the support frame ear plate is arranged one on each side symmetrically along the central axis of the support frame vertical rod, and the support frame ear plate is provided with bolt holes for connecting the oblique tension rod; two support frame vertical rod bolt holes are provided at a certain interval on the upper part of the support frame vertical rod, and the interval between the bolt holes corresponds to the interval between the limit holes of the connector ear plate welded to the Bailey chord connector; a prestressed intelligent adjustment device is installed on the outside of the support frame vertical rod to realize automatic loading and unloading of the horizontal tension rod and preliminary adjustment of the prestress, so as to improve the construction efficiency.

4. The intelligent prestressed string support system for a steel trestle according to claim 1 is characterized in that: The oblique tensioning rod includes a bidirectional screw, a threaded sleeve, and a U-shaped joint; threads are provided at both ends of the bidirectional screw, and the threads at both ends are in opposite directions. The threads are rotatably connected to the threaded sleeve. When the bidirectional screw rotates, it will drive the support frame to move in opposite directions, thereby generating prestress and enhancing the overall stability; a bolt hole is opened in the middle position of the U-shaped joint, and the diameter of the bolt hole is consistent with the diameter of the limiting holes of the ear plate of the support frame and the ear plate of the chord rod connector, ensuring that the support frame and the chord rod connector are firmly connected.

5. The intelligent prestressed string support system for a steel trestle according to claim 1 is characterized in that: The horizontal tension rod includes a bidirectional screw, a threaded sleeve and a toothed joint; the toothed joint is provided with a snap-in groove for snapping into the prestressed intelligent adjustment device to achieve quick connection of the horizontal tension rod and preliminary adjustment of the prestress of the string support system; the bidirectional screw and threaded sleeve are consistent with the bidirectional screw and threaded sleeve of the oblique tension rod.

6. The intelligent prestressed string support system for a steel trestle according to claim 1 is characterized in that: The intelligent prestress optimization mechanism includes a prestress intelligent drive device, a prestress intelligent adjustment device, a displacement sensor, a fiber Bragg grating stress sensor, a data encoder and a PLC main control platform; the prestress intelligent drive device is installed on a bidirectional screw, and includes an intelligent drive element, an active bevel gear and a driven bevel gear; after receiving the instruction of the PLC main control platform, the intelligent drive element drives the active bevel gear connected to it to rotate clockwise, and the active bevel gear rotates to drive the driven bevel gear to rotate counterclockwise along the radial direction of the bidirectional screw, thereby driving the bidirectional screw and the threaded casing to be tightly tightened to generate a prestressing force; the intelligent drive element can also drive the bidirectional screw to rotate an appropriate number of circles according to the instruction of the PLC main control platform to achieve the optimal prestressing effect.

7. The intelligent prestressed string support system for a steel trestle according to claim 6 is characterized in that: The prestressed intelligent adjustment device includes an intelligent telescopic element, a first rack, a gear, a second rack, a fixed block and a spring; after the intelligent telescopic element receives the instruction from the PLC main control platform, the intelligent telescopic element performs locking and unlocking operations according to different working conditions; when installing the horizontal tension rod, the intelligent telescopic element is unlocked, and the toothed joint of the horizontal tension rod contacts the inclined surface of the fixed block of the prestressed intelligent adjustment device. As the horizontal tension rod is continuously inserted, the fixed block moves downward, and the spring contracts. When the insertion depth of the horizontal tension rod reaches the position of the clamping groove, the fixed block moves upward under the action of the spring elastic force, and the fixed block is clamped and fixed with the clamping groove, and the intelligent telescopic element is locked; when the tensioning support system needs to be dismantled, the intelligent telescopic element is started in the unlocked state, the first rack moves upward, and the driving gear rotates clockwise. The rotation of the gear drives the second rack to move downward, and the movement of the second rack drives the fixed block to disengage from the fixed groove, thereby achieving the purpose of disengaging the horizontal tension rod from the support frame.

8. The intelligent prestressed string support system for a steel trestle according to claim 6 is characterized in that: The displacement sensor is installed on the Bailey chord connector of the tensioning support system, and is mainly used to measure the deflection, vibration, strain and other physical parameters of the Bailey chord connector under the application of prestress, external load and environmental effects; the fiber grating stress sensor is installed on the oblique tension rod, the horizontal tension rod and the support frame, and the stress value of each detection component is obtained according to the basic principle of material mechanics; under the influence of external load, the deadweight of the main structure and wind temperature and other external environments, the displacement sensor and the fiber grating stress sensor measure various physical parameters of the measured component and transmit the measurement signal to the data encoder, the data encoder encodes each parameter and optimizes the prestress value by the gradient descent method, the optimized prestress value is received by the PLC main control platform, and instructions are issued to the prestress intelligent drive device and the prestress intelligent adjustment device, the intelligent telescopic element realizes the preliminary adjustment of the prestress by controlling the insertion depth of the tension rod, and the intelligent drive element realizes the fine adjustment of the prestress by rotating the bidirectional screw.

9. The intelligent prestressed string support system for a steel trestle according to claim 8 is characterized in that: The gradient descent prestress optimization algorithm is as follows: S1: Determine the prestress optimization function model, transmit the influencing parameters of the prestress of the tension support system to the data encoder, and establish m sample optimization function models F (x1, x2, ..., x n ) Among them: a i (i=0,1,2,…,n) are the parameters of the prestress optimization model, x i (i=0, 1, 2, ..., n) is the influencing factor of the prestress optimization function model for each sample; S2: Establish the CF loss function. In order to select the optimal solution of the prestressed model from the m sample functions, the MSE mean square error analysis method is used to analyze the sample output value f j The difference between the prestress optimization function and the square is taken to obtain the CF loss function, and the degree of fitting of the prestress optimization function is measured according to the CF loss function. That is, the minimization of the loss function means the best fitting degree, and the corresponding prestress optimization model parameters are the optimal parameters. S3: Determine the gradient of the CF loss function. If the value of the minimized loss function is to be found at the fastest speed, it is necessary to search in the direction where the derivative value of the CF loss function decreases, i.e., the negative gradient direction. The CF loss function is continuously iterated and solved by the gradient descent method to obtain the minimized loss function and the parameter values ​​of the prestress optimization function model. Specifically, for the prestress optimization model parameter a i (i=0,1,2,…,n), in a i The partial derivative of the CF loss function is calculated at the position, and the collection of n negative partial derivatives is called the gradient of the CF loss function, which is expressed as follows: S4: Determine the gradient descent distance. In order to avoid gradient explosion, gradient disappearance and local optimal solution when the data encoder is looking for the optimal prestress function, the learning efficiency α is introduced to correct the gradient of the loss function, and the distance of the current position descent can be obtained, that is: S5: Determine whether all prestress optimization model parameters a i (i=0,1,2,…,n), the gradient descent distance is less than ε. If it is less than ε, the algorithm terminates. All the current prestress optimization model parameters a i (i=0, 1, 2, ..., n), which is the final result; otherwise, go to step S6 to check a i Make updates; S6: Update all a i (i=0,1,2,…,n), for a i , and its update expression is as follows: After the update is completed, the algorithm goes to step S2 for recalculation. When all gradient descent distances are less than ε, the algorithm terminates and outputs the prestressed optimal function model F(x1, x2, ..., x n ); S7: According to the iterative method, the optimal prestress function model of the tension rod can be obtained. Since the prestress of the tension rod of the string support system is controlled by the toothed joint extension length controlled by the intelligent telescopic element and the intelligent driving element driving the bidirectional screw to rotate to achieve the preliminary and fine adjustment of the prestress of the tension rod; therefore, on the basis of the optimal prestress function of the tension rod, the correction functions λ and β are introduced to establish the functional relationship between the toothed joint extension length of the bidirectional screw and the number of rotations of the bidirectional screw and the optimal prestress function of the tension rod: The gradient descent prestressed stress optimization algorithm uses a CF loss function to search for the global optimal solution in the sample database along the direction of the fastest negative gradient descent. The optimal function model of prestressed stress is found through continuous iteration, which ensures the timeliness of the convergence speed. The introduction of learning efficiency α effectively avoids the occurrence of local optimal solutions in the search process, ensuring the extensiveness and globality of the search.

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