Novel damping vibration attenuation intelligent bridge support

Abstract

The invention relates to the technical field of bridge engineering, and discloses a novel damping vibration attenuation intelligent bridge support which comprises a bottom plate, a top plate is arranged at the top of the bottom plate, and the bottom plate is connected with the top plate through a connecting rod; the damping assembly is arranged between the bottom plate and the top plate and used for conducting damping operation when the damping assembly is stressed; the extrusion plate is fixed at the bottom of the top plate and is used for generating a force effect on the damping assembly; the limiting frame is fixed to the top of the bottom plate and used for limiting the force application direction of the extrusion plate; the sensing assemblies are arranged in the limiting frame in an annular array mode and used for monitoring the state of the equipment in a multi-azimuth mode when the equipment is stressed. External impact force is effectively absorbed and dissipated layer by layer, the top plate is buffered for the first time, and then the extrusion plate and the damping assembly are used for buffering for the second time and the third time, so that equipment still keeps stable when bearing large loads and vibration, the overall damping effect of the bridge support is improved, the service life of the structure is prolonged, and the service life of the bridge support is prolonged. And the possibility of fatigue damage is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of bridge engineering, and in particular to a novel damping and vibration reduction intelligent bridge bearing. Background Art

[0002] Bridge bearings are an important component of bridge structures. Their main function is to support the weight of the bridge deck and other superstructures and transfer these loads to the lower structure of the bridge, such as piers and abutments. The bearings play a dual function of connection and load-bearing. At the same time, they also allow the bridge to make necessary movements within a certain range to adapt to the expansion, rotation and displacement of the bridge caused by temperature changes, wind loads, traffic loads or earthquakes. The design and installation of bridge bearings are crucial to the safety, stability and service life of the bridge. They not only require precise calculations to carry huge loads, but also need to take into account environmental factors and material aging. Good bearing design can significantly reduce maintenance requirements and improve the overall performance and economic benefits of the bridge. In short, bridge bearings are an indispensable component of bridge engineering and play a decisive role in ensuring the safety, functionality and durability of bridge structures. Correct design, material selection and maintenance strategies are the key to achieving these goals.

[0003] However, there are still some unavoidable problems in the actual use of existing bridge bearings. First, traditional bridge bearing systems usually use a single material or simple structure. When facing complex dynamic load environments (such as traffic, wind loads, earthquakes, etc.), their vibration reduction performance is often limited. These traditional systems are difficult to adapt to vibrations of various frequencies and amplitudes, which makes the bridge structure prone to fatigue damage after long-term stress, thereby shortening the service life of the bridge and increasing the frequency and cost of maintenance and replacement; Secondly, most bridge bearing systems lack effective real-time monitoring and fault warning mechanisms. Traditional methods rely on regular manual inspections or simple threshold-based monitoring systems. These methods are not only slow to respond and inefficient, but also difficult to provide sufficient warning time to take preventive measures. In addition, this lack of intelligent monitoring system cannot accurately identify impending failures, resulting in the inability to repair or replace damaged parts in a timely manner, which may cause serious safety accidents. Finally, in the existing technology, when a part of the bridge support system or a sensor fails, it often leads to the loss of important data or transmission interruption, because these systems usually lack effective data redundancy and backup measures. In this case, the continuity and reliability of the system are greatly reduced, affecting the overall operation efficiency of the bridge and the accuracy of safety monitoring. In addition, after a node fails, the recovery operation of the traditional bridge support system is complicated and time-consuming, which increases maintenance costs and operational difficulties. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a novel damping and vibration reduction intelligent bridge bearing, which solves the problem that it is difficult to adapt to vibrations of various frequencies and amplitudes, resulting in a shortened service life of the bridge support.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a new type of damping and vibration reduction intelligent bridge bearing, comprising: A bottom plate, a top plate is arranged on the top of which, and the bottom plate and the top plate are connected by a connecting rod; A shock absorbing assembly is arranged between the bottom plate and the top plate and is used for shock absorbing when subjected to force; An extrusion plate, which is fixed to the bottom of the top plate and is used to exert force on the shock absorbing assembly; A limit frame, which is fixed on the top of the bottom plate and is used to limit the force direction of the extrusion plate; The sensor assembly is arranged in a ring array inside the limit frame and is used for multi-directional monitoring of the state of the device when it is subjected to force; The PLC module is arranged in the middle of the bottom wall of the limit frame and is used to control the overall intelligent detection process.

[0006] Preferably, the shock absorbing assembly includes a docking plate, and a plurality of the docking plates are provided. The top docking plate is connected to the extrusion plate, and the bottom docking plate is connected to the limit frame. One side of the docking plate is rotatably connected to a push rod through a swivel.

[0007] Preferably, a docking block is fixed on one side of the docking plate, a fixed frame 1 is arranged between the docking blocks, a fixed frame 2 is fixed on both sides of the fixed frame 1, a slider is slid inside the fixed frame 2, and one end of the push rod is connected to the slider through a rotating shaft.

[0008] Preferably, a damper 2 is arranged inside the second fixing frame, and the output ends of the damper 2 are fixed to the slider, and a damper 1 is arranged on the top of the bottom docking block, and the output end of the damper 1 is connected to the top docking block.

[0009] Preferably, a damping layer 1 is arranged inside the top plate, a damping layer 2 is arranged on the top of the damping layer 1, a damping layer 3 is arranged on the bottom of the damping layer 1, the damping layer 2 is filled with graphene-reinforced carbon fiber composite material, the damping layer 1 is filled with nanoporous polymer foam, and the damping layer 3 is filled with magnetorheological material.

[0010] Preferably, the sensor components are provided in multiple types, including: stress sensor, vibration sensor, temperature sensor and humidity sensor, and the PLC module includes a data acquisition module, a dynamic routing control module, a predictive fault detection and early warning module, a data redundancy and backup module and a load balancing and efficiency improvement module.

[0011] Preferably, the data acquisition module includes a sensor signal acquisition unit and a signal processing and filtering unit; The sensor signal acquisition unit is used to collect the stress, vibration, temperature and other information of the bridge from each sensor node and receive it into the PLC module; The signal processing and filtering is used to filter and process the sensor data received by the PLC module, remove noise and transmit it to the routing module; The dynamic routing control module includes a routing control unit and a receiving unit; The receiving unit is used to receive the status of each module to determine the path; The routing control unit is used to dynamically select the best route according to the real-time update of the path status.

[0012] Preferably, the predictive fault detection and early warning module includes a fault detection unit and an early warning unit; The fault detection module analyzes the health status of the node through a fault prediction algorithm. Once it detects that the battery power of the node is lower than the threshold or the signal strength is gradually weakening, the PLC system will issue an alarm in advance and automatically mark the node as a potential fault node; The fault prediction algorithm predicts the fault probability of the sensor node by combining the real-time status and historical data of the node through a machine learning model. The formula is as follows: in, is the failure probability of node N; is the battery power status of node n; is the signal strength of node n; is the running time of node n; the warning module is used for automatically sending out a warning signal to notify the maintenance personnel when a potential fault is detected, and at the same time notifying the routing control unit to automatically adjust the route to ensure that data transmission continues; The warning content includes the ID, location and expected failure time of the faulty node.

[0013] Preferably, the data redundancy and backup module adopts a fault-tolerant mechanism to continue to operate and maintain data integrity and continuity when a sensor node fails, specifically comprising the following steps: S1. Redundant backup: Distribute data storage among multiple nodes or back it up on a central server; S2, Fault recovery: When a node fails, the system can obtain data from other backup nodes and continue to perform tasks to ensure uninterrupted data transmission; In the step S1, data is backed up to multiple nodes through distributed storage; In step S2, by determining whether the node is invalid, if the failed node n cannot work, then select other backup nodes to restore data, specifically: in, Indicates the result of data recovery, that is, the system selects which node to recover data from by judging the node status; Indicates data obtained from node k. Node k is one of the nodes that back up data. Usually, when node n fails, the system will restore data from node k. Represents the original data from node n. When node n works normally, the system directly obtains data from the node. n represents the sensor node that is currently working or failed. Specific explanation: If node n works normally, the system will directly use its data; if node n fails, the system will restore data from other backup nodes k.

[0014] Preferably, the load balancing and efficiency improvement module includes a real-time load monitoring unit and a load balancing strategy unit; The real-time load monitoring unit is used to continuously monitor the data transmission volume and network bandwidth utilization of each sensor node, and notify the routing control unit to dynamically adjust the transmission volume of different routes according to the real-time load of the node; The load balancing strategy unit is used to assist the routing control unit to automatically distribute data packets to a path with a lower load when a certain path is overloaded; The real-time load monitoring unit and the load balancing strategy unit can be specifically expressed as the following formula: in, Indicates the allocated data path; It represents the data distribution result on the path with lower load; Indicates the data distribution result when load balancing on the current path, indicating that if the current path is the best, the data will still be transmitted through this path; Indicates that the path with the smallest load is selected, which is calculated by the average load of all nodes on each path; represents the set of all possible paths; Indicates the path The total number of nodes on ; Indicates the current data transmission volume of node n; Represents the maximum available bandwidth of node n.

[0015] Working principle: When the equipment is placed under the bridge for support, the corresponding top plate will be subjected to force. At this time, the top plate itself will perform the first buffering through its own material. The buffered impact force will be transmitted to the position of the shock absorbing component through the extrusion plate. At this time, the inclination angle of the connecting rod changes, and there is a certain degree of lateral displacement with the fulcrum position of the top plate. When the shock absorbing component is subjected to force, the top docking plate is first subjected to the force, and then drives the corresponding docking block to sink. At this time, the impact force is buffered for the second time through the action of damper one, and while the docking plate and the docking block sink, the inclination angle of the corresponding push rod will also be cheaper, and then the slider will be pushed through the rotating shaft, so that it exerts force on damper two under the restriction of fixed frame two, so that damper two performs the third buffering.

[0016] The present invention provides a new type of damping and vibration reduction intelligent bridge bearing, which has the following beneficial effects: 1. The present invention effectively absorbs and dissipates external impact force layer by layer. The top plate performs the first buffering, and then the extrusion plate and shock-absorbing components perform the second and third buffering treatments, so that the equipment remains stable when subjected to large loads and vibrations. This improves the overall vibration reduction effect of the bridge bearing, extends the service life of the structure, and reduces the possibility of fatigue damage.

[0017] 2. The present invention integrates the data acquisition, fault detection, dynamic routing control and load balancing modules in the PLC module, collects the stress, vibration, temperature and other information of the bridge in real time through sensors, and intelligently monitors the status of the nodes. Through the fault prediction algorithm, the potential failure risk of the node can be detected in advance, an early warning can be issued and the data transmission path can be adjusted. This function significantly improves the safety and reliability of the system and reduces the equipment maintenance cost.

[0018] 3. The present invention uses data redundancy and backup functions. Even when a sensor node fails, the system can still automatically restore data from other nodes or the central server to ensure uninterrupted data transmission. This mechanism ensures the high reliability of the bridge support system. Even if some nodes fail, it will not affect the normal operation of the overall system, thereby improving the system's fault tolerance and data integrity. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A perspective view of the present invention; Figure 2 It is a structural explosion diagram of the present invention; Figure 3 It is a schematic diagram of the shock absorbing assembly of the present invention; Figure 4 It is the internal structure distribution diagram of the limit frame of the present invention; Figure 5 This is a distribution diagram of the internal structure of the top plate of the present invention; Figure 6 It is the PLC module flow chart of the present invention.

[0020] Among them, 1. bottom plate; 2. connecting rod; 3. top plate; 4. extrusion plate; 5. shock absorbing assembly; 51. docking plate; 52. docking block; 53. push rod; 54. fixed frame one; 55. fixed frame two; 56. slider; 57. damper one; 58. damper two; 6. limit frame; 7. sensor assembly; 8. PLC module; 9. damping layer one; 10. damping layer two; 11. damping layer three. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Embodiment 1

[0022] Please see attached Figure 1 -Attached Figure 4 The embodiment of the present invention provides a novel damping and vibration reduction intelligent bridge bearing, comprising: A bottom plate 1, a top plate 3 is arranged on the top of the bottom plate 1, and the bottom plate 1 and the top plate 3 are connected by a connecting rod 2; A shock absorbing assembly 5, which is arranged between the bottom plate 1 and the top plate 3, and is used for performing shock absorbing operation when subjected to force; An extrusion plate 4, which is fixed to the bottom of the top plate 3 and is used to exert force on the shock absorbing assembly 5; A limit frame 6, which is fixed on the top of the bottom plate 1 and is used to limit the force direction of the extrusion plate 4; The sensor assembly 7 is arranged in a ring array inside the limit frame 6 and is used for multi-directional monitoring of the state of the device when it is subjected to force; A PLC module 8, which is arranged in the middle of the bottom wall of the limit frame 6 and is used to control the overall intelligent detection process; The shock absorbing assembly 5 includes a docking plate 51, and a plurality of docking plates 51 are provided. The top docking plate 51 is connected to the extrusion plate 4, and the bottom docking plate 51 is connected to the limit frame 6. A push rod 53 is rotatably connected to one side of the docking plate 51 through a swivel. A docking block 52 is fixed to one side of the docking plate 51. A fixed frame 1 54 is provided between the docking blocks 52. A fixed frame 2 55 is fixed on both sides of the fixed frame 1 54. A slider 56 is slidably provided inside the fixed frame 2 55. One end of the push rod 53 is connected to the slider 56 through a rotating shaft. A damper 2 58 is provided inside the fixed frame 2 55. The output end of the damper 2 58 is fixed to the slider 56. A damper 1 57 is provided on the top of the bottom docking block 52, and the output end of the damper 1 57 is connected to the top docking block 52.

[0023] Specifically, when the equipment is placed under the bridge as a support, the top plate 3 will first bear the vertical load from the bridge structure and the vibration or impact force applied by the outside world. At this time, the top plate 3 plays the role of initial buffering through its material characteristics. The top plate 3 is usually made of high-strength and elastic materials, which can effectively disperse and absorb part of the impact force, thereby reducing the instantaneous load directly acting on the equipment. The buffering at this stage not only helps to reduce the intensity of the initial impact force, but also can prolong the force conduction time to a certain extent, making the subsequent shock absorption process smoother. The residual impact force after the top plate 3 buffers is transmitted through the extrusion plate 4 fixed under the top plate 3. The force is transmitted to the shock absorbing component 5. The extrusion plate 4 serves as a force transmission device, and its function is to evenly distribute the force on the top plate 3 to the entire shock absorbing component 5. In this process, the connecting rod 2 connecting the top plate 3 and the bottom plate 1 is tilted to a certain extent. The change in its tilt angle depends on the magnitude and direction of the applied force. When the connecting rod 2 is tilted, the fulcrum position of the top plate 3 is laterally offset. This change in the fulcrum position helps the equipment to provide a more flexible support angle when subjected to force, thereby improving the overall stability of the equipment and reducing the risk of concentrated force on the structure. At the same time, as the force is transmitted to the shock absorbing component 5, the component begins to bear the force in the vertical direction. First, the top docking plate 51 in the shock absorbing assembly 5 is directly acted upon by the force. Since the docking plate 51 is one of the key components of the shock absorbing assembly 5, its structural design can bear and effectively disperse the vertical load. After being subjected to the force, the docking plate 51 drives the docking block 52 below it to sink together. The movement in this stage mainly buffers the impact force through the elasticity of the structure and the deformation of the docking block 52, so that the impact force gradually decays and enters the second buffering process of the equipment; in the process of the docking block 52 sinking, the damper 57 begins to play its role and provides the second buffering. As an important shock absorbing element, the damper 57 uses its internal damping material to The material absorbs and dissipates energy, thereby reducing the transmission rate and intensity of the force. At this time, the existence of the damper 1 57 can not only further reduce the impact force transmitted from the top plate 3, but also effectively protect other structural elements of the equipment from the influence of excessive loads; when the docking plate 51 and the docking block 52 sink, the inclination angle of the push rod 53 also changes accordingly. This inclination allows the push rod 53 to interact with the slider 56 through the rotating shaft, pushing the slider 56 to slide inside the fixed frame 2 55. The fixed frame 2 55 serves as a limiting structure to ensure that the slider 56 moves in a reasonable track under the action of force to avoid deviation or excessive deformation.The movement of the slider 56 further drives the damper 2 58 to bear force. At this time, the damper 2 58 enters the working state, providing the third buffer for the equipment. The damper 2 58 can effectively deal with the lateral force brought by the push rod 53 and the pressure formed by the slider 56, further absorb and dissipate the residual vibration energy, and make the shock absorption effect of the whole device more perfect. Through the design of the multi-stage damping structure, the equipment can successively attenuate the force under the impact loads of different intensities and frequencies, thereby ensuring the stability and long-term durability of the support system; in general, the multi-stage buffering mechanism gradually attenuates the impact force applied by the outside through three effective buffering processes, which are layered by the top plate 3, the damper 1 57 and the damper 2 58 in the shock absorbing assembly 5, respectively, to ensure that the equipment has excellent shock absorption effect under strong dynamic loads. This multi-level shock absorption design not only improves the seismic resistance and impact resistance of the equipment, but also reduces structural fatigue and prolongs the service life of the equipment. ; Embodiment 2

[0024] Please see attached Figure 5 A damping layer 1 9 is arranged inside the top plate 3, a damping layer 2 10 is arranged on the top of the damping layer 1 9, a damping layer 3 11 is arranged at the bottom of the damping layer 1 9, the damping layer 2 10 is filled with graphene-reinforced carbon fiber composite material, the damping layer 1 9 is filled with nanoporous polymer foam, and the damping layer 3 11 is filled with magnetorheological material.

[0025] Specifically, the damping layer 9 is specifically composed of 50% to 65% polyurethane, 10% to 25% silicone resin, 5% to 15% nano-silicon dioxide and 2% to 8% foaming agent. The specific porosity after the composition is between 50% and 90%. The more pores, the more the material can absorb vibration energy, and the larger the porosity, the higher the flexibility. In addition, the elastic modulus of the nanoporous foam can be adjusted according to the application scenario, usually between 0.5 MPa and 10 MPa. The higher elastic modulus can withstand a larger load while maintaining sufficient elasticity to prevent permanent deformation. Finally, its density is usually low, at 0.02 g / cm³ to 0.15 g / cm³, which can ensure the overall weight of the structure is reduced while providing a better cushioning effect. The damping layer 2 10 is specifically composed of 50% to 65% carbon fiber, 15% to 25% graphene nanosheets, 7% to 15% epoxy resin matrix and 2% to 7% thermal conductive filler. Its tensile strength can reach more than 5000 MPa, which is much higher than ordinary composite materials, ensuring that the top plate 3 will not break or deform when subjected to severe impact. In addition, its Young's modulus is 200 GPa to 300 GPa, which makes the material have high rigidity and can effectively disperse large stresses. The thermal conductivity is ≥3000 W / m·K, which makes it have excellent thermal management capabilities, can quickly dissipate heat, and reduce heat accumulation caused by long-term vibration. Finally, its density is usually 1.6 g / cm³ to 2.0 g / cm³, ensuring that the material has a light weight and reducing the dead weight of the structure, thereby providing good rigid support for the damping layer 2 10, which can further absorb the impact force and evenly distribute it to the entire top plate area, thereby avoiding local stress concentration, and helping to quickly dissipate the heat generated by the vibration of the top plate 3 to prevent structural degradation caused by heat accumulation; The damping layer three 11 is specifically composed of 65% to 75% silicone oil, 20% to 30% carbon iron particles and 2% to 8% of a reagent composed of a stabilizer and a dispersant. Under non-magnetic field conditions, the initial viscosity of the magnetorheological material is usually 0.1 Pa·s to 1Pa·s. When the magnetic field is applied, the viscosity can be rapidly increased to 50 Pa·s or even higher, providing instant damping enhancement. After the magnetic field is applied, the yield stress of the magnetorheological material can reach 50 kPa to 100 kPa, which makes the material have high damping capacity when impacted. Finally, its density is generally 3 g / cm³ to 4 g / cm³, which is moderate and can adapt to large stress changes. Embodiment 3

[0026] Please see attached Figure 6 , the sensing component 7 is provided with various types, including: a stress sensor, a vibration sensor, a temperature sensor and a humidity sensor; The PLC module 8 includes a data acquisition module, a dynamic routing control module, a predictive fault detection and early warning module, a data redundancy and backup module, and a load balancing and efficiency improvement module; The data acquisition module includes a sensor signal acquisition unit and a signal processing and filtering unit; The sensor acquisition signal unit is used to collect the stress, vibration, temperature and other information of the bridge from each sensor node and receive it into the PLC module; Signal processing and filtering is used to filter and process the sensor data received by the PLC module, remove noise and transmit it to the routing module; The dynamic routing control module includes a routing control unit and a receiving unit; The receiving unit is used to receive information from each module to determine the path status; The routing control unit is used to dynamically select the best route based on the real-time update of the path status; The predictive fault detection and early warning module includes a fault detection unit and an early warning unit; The fault detection module analyzes the health status of the node through a fault prediction algorithm. Once it detects that the battery power of the node is below the threshold or the signal strength is gradually weakening, the PLC system will issue an alarm in advance and automatically mark the node as a potential fault node; The fault prediction algorithm combines the real-time status and historical data of the node through a machine learning model to predict the possibility of failure of the sensor node. The formula is as follows: in, is the failure probability of node n; is the battery power status of node n (ranging from 0 to 1, 1 means the battery is fully charged and 0 means the battery is exhausted); is the signal strength of node n (ranging from 0 to 1, 1 indicates a good signal and 0 indicates a weak signal or no signal); is the running time of node n (the cumulative running time of the node. The longer the time, the closer it may be to failure); The early warning module is used to automatically send out an early warning signal to notify maintenance personnel when a potential fault is detected, and to notify the routing control unit to automatically adjust the route to ensure that data transmission continues; The warning content includes the ID, location and expected failure time of the faulty node; The data redundancy and backup module adopts a fault-tolerant mechanism to continue to operate and maintain data integrity and continuity when a sensor node fails. Specifically, it includes the following steps: S1. Redundant backup: Distribute data storage among multiple nodes or back it up on a central server; S2, Fault recovery: When a node fails, the system can obtain data from other backup nodes and continue to perform tasks to ensure uninterrupted data transmission; In step S1, data is backed up to multiple nodes through distributed storage; In step S2, by determining whether the node is invalid, if the failed node n cannot work, then select other backup nodes to restore data, specifically: in, Indicates the result of data recovery, that is, the system selects which node to recover data from by judging the node status; Indicates data obtained from node k. Node k is one of the nodes that back up data. Usually, when node n fails, the system will restore data from node k. Represents the original data from node n. When node n works normally, the system directly obtains data from the node. n represents the sensor node that is currently working or failed. Specific explanation: If node n works normally, the system will directly use its data; if node n fails, the system will restore data from other backup nodes k. The load balancing and efficiency improvement module includes a real-time load monitoring unit and a load balancing strategy unit; The real-time load monitoring unit is used to continuously monitor the data transmission volume and network bandwidth utilization of each sensor node, and notify the routing control unit to dynamically adjust the transmission volume of different routes according to the real-time load of the node; The load balancing strategy unit is used to automatically distribute data packets to a path with lower load when a certain path is overloaded; The real-time load monitoring unit and the load balancing strategy unit can be specifically expressed as the following formula: in, Indicates the assigned data path (i.e. the path that the data packet will take); It represents the data distribution result on the path with lower load; Indicates the data distribution result when load balancing on the current path, indicating that if the current path is the best, the data will still be transmitted through this path; Indicates that the path with the smallest load is selected, which is calculated by the average load of all nodes on each path; represents the set of all possible paths; Indicates the path The total number of nodes; Indicates the current data transmission volume of node n; Indicates the maximum available bandwidth of the node.

[0027] Specifically, the data acquisition module inputs the data signals of each sensor node into the PLC module 8 through the sensor signal acquisition unit, and performs preliminary processing on these data through the signal processing and filtering unit to eliminate noise and ensure the quality of data for subsequent processing. The processed data is transmitted to the dynamic routing control module, wherein the receiving unit receives the path status information provided by other modules and updates the node status in real time; in the dynamic routing control module, the routing control unit dynamically selects the best route based on the real-time update of the path status and the real-time load conditions of each node. This module also works closely with the load balancing and efficiency improvement module. The real-time load monitoring unit transmits the load information to the routing control unit by monitoring the data transmission volume and bandwidth utilization of each sensor node. When the path load is too high, the load balancing strategy unit automatically distributes the data packet to the path with lower load to ensure the high efficiency of network transmission; at the same time, the predictive fault detection and early warning module calculates the node failure probability by using the fault prediction algorithm through the fault detection unit and combining the battery power status, signal strength, running time and historical data of the sensor node. When it is detected that the battery power of a node is lower than the threshold or the signal strength is gradually weakening, the system will issue an alarm in advance and mark the node as a potential fault node. The early warning module issues a warning to the maintenance personnel through the real-time early warning function, and at the same time notifies the routing control unit to automatically adjust the data transmission path to ensure that data transmission is not interrupted; after the fault node fails, the data redundancy and backup module continues to ensure data integrity and continuity through the fault tolerance mechanism. The redundant backup mechanism of this module stores data in multiple nodes or central servers in a dispersed manner. When a node fails, the system can automatically determine its status and restore data from other backup nodes. The restored data continues to be transmitted to avoid data loss; In this way, the modules in the system work closely together to achieve efficient bridge monitoring and control. In the process of sensor data collection, processing and fault prediction, the data will be reasonably allocated to the path under load balancing to ensure the stability and performance of the system. At the same time, through the data redundancy mechanism, even if some nodes fail, the system can automatically adjust the route and restore the data to ensure the continuous operation of data flow and bridge monitoring.

[0028] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A new type of damping and vibration reduction intelligent bridge bearing, characterized in that: include: A bottom plate (1) having a top plate (3) disposed on its top, wherein the bottom plate (1) and the top plate (3) are connected via a connecting rod (2); A shock absorbing assembly (5), which is arranged between the bottom plate (1) and the top plate (3) and is used to perform shock absorbing operations when subjected to force; An extrusion plate (4) fixed to the bottom of the top plate (3) and used to exert a force on the shock absorbing component (5); A limit frame (6) fixed to the top of the bottom plate (1) and used to limit the force direction of the extrusion plate (4); A sensor assembly (7) is arranged in a ring array inside the limit frame (6) and is used for multi-directional monitoring of the state of the device when it is subjected to force; A PLC module (8) is arranged in the middle of the bottom wall of the limit frame (6) and is used to control the overall intelligent detection process.

2. According to claim 1, the novel damping and vibration reduction intelligent bridge bearing is characterized in that: The shock absorbing assembly (5) comprises a docking plate (51), wherein a plurality of the docking plates (51) are provided, wherein the top docking plate (51) is connected to the extrusion plate (4), and the bottom docking plate (51) is connected to the limit frame (6), and one side of each of the docking plates (51) is rotatably connected to a push rod (53) via a swivel.

3. According to claim 2, the novel damping and vibration reduction intelligent bridge bearing is characterized in that: A docking block (52) is fixed on one side of the docking plate (51), a fixing frame 1 (54) is arranged between the docking blocks (52), a fixing frame 2 (55) is fixed on both sides of the fixing frame 1 (54), a slider (56) is slidably arranged inside the fixing frame 2 (55), one end of the push rod (53) is connected to the slider (56) via a rotating shaft, a damping layer 1 (9) is arranged inside the docking plate (51), a damping layer 2 (10) is arranged on the top of the damping layer 1 (9), a damping layer 3 (11) is arranged on the bottom of the damping layer 1 (9), the damping layer 2 (10) is filled with a graphene-reinforced carbon fiber composite material, the damping layer 1 (9) is filled with a nanoporous polymer foam, and the damping layer 3 (11) is filled with a magnetorheological material.

4. According to claim 3, the novel damping and vibration reduction intelligent bridge bearing is characterized in that: A damper 2 (58) is arranged inside the second fixing frame (55), and the output ends of the damper 2 (58) are fixed to the slider (56). A damper 1 (57) is arranged on the top of the docking block (52) at the bottom, and the output end of the damper 1 (57) is connected to the docking block (52) at the top.

5. According to claim 1, the novel damping and vibration reduction intelligent bridge bearing is characterized in that: A damping layer 1 (9) is arranged inside the top plate (3), a damping layer 2 (10) is arranged on the top of the damping layer 1 (9), and a damping layer 3 (11) is arranged on the bottom of the damping layer 1 (9), the damping layer 2 (10) is filled with a graphene-reinforced carbon fiber composite material, the damping layer 1 (9) is filled with a nanoporous polymer foam, and the damping layer 3 (11) is filled with a magnetorheological material.

6. The novel vibration damping intelligent bridge bearing according to claim 1 is characterized in that: The sensor components (7) are provided in a variety of ways, including: a stress sensor, a vibration sensor, a temperature sensor and a humidity sensor; the PLC module (8) includes a data acquisition module, a dynamic routing control module, a predictive fault detection and early warning module, a data redundancy and backup module and a load balancing and efficiency improvement module.

7. The novel vibration damping intelligent bridge bearing according to claim 6 is characterized in that: The data acquisition module includes a sensor signal acquisition unit and a signal processing and filtering unit; The sensor signal acquisition unit is used to collect the stress, vibration, temperature and other information of the bridge from each sensor node and receive it into the PLC module; The signal processing and filtering is used to filter and process the sensor data received by the PLC module, remove noise and transmit it to the routing module; The dynamic routing control module includes a routing control unit and a receiving unit; The receiving unit is used to receive the status of each module to determine the path; The routing control unit is used to dynamically select the best route according to the real-time update of the path status.

8. The novel vibration damping intelligent bridge bearing according to claim 6 is characterized in that: The predictive fault detection and early warning module includes a fault detection unit and an early warning unit; The fault detection module analyzes the health status of the node through a fault prediction algorithm. Once it detects that the battery power of the node is lower than the threshold or the signal strength is gradually weakening, the PLC system will issue an alarm in advance and automatically mark the node as a potential fault node; The fault prediction algorithm predicts the fault probability of the sensor node by combining the real-time status and historical data of the node through a machine learning model. The formula is as follows: in, is the failure probability of node n; is the battery power status of node n (ranging from 0 to 1, 1 means the battery is fully charged and 0 means the battery is exhausted); is the signal strength of node n (ranging from 0 to 1, 1 indicates a good signal and 0 indicates a weak signal or no signal); is the running time of node n (the cumulative running time of the node. The longer the time, the closer it may be to failure); The warning module is used to automatically send out a warning signal to notify maintenance personnel when a potential fault is detected, and to notify the routing control unit to automatically adjust the route to ensure that data transmission continues; The warning content includes the ID, location and expected failure time of the faulty node.

9. The novel vibration damping intelligent bridge bearing according to claim 6 is characterized in that: The data redundancy and backup module adopts a fault-tolerant mechanism to continue to operate and maintain data integrity and continuity when a sensor node fails, and specifically includes the following steps: S1, Redundant backup: Distribute data storage among multiple nodes or back it up on a central server; S2, Fault recovery: When a node fails, the system can obtain data from other backup nodes and continue to execute tasks to ensure uninterrupted data transmission; In the step S1, data is backed up to multiple nodes through distributed storage; In step S2, by determining whether the node is invalid, if the failed node n cannot work, then select other backup nodes to restore data, specifically: in, Indicates the result of data recovery, that is, the system selects which node to recover data from by judging the node status; Indicates data obtained from node K. Node k is one of the nodes that back up data. Usually, when node n fails, the system will restore data from node k. Represents the original data from node n. When node n works normally, the system directly obtains data from the node. n represents the sensor node that is currently working or failed. Specific explanation: If node n works normally, the system will directly use its data; if node n fails, the system will restore data from other backup nodes k.

10. The novel vibration damping intelligent bridge bearing according to claim 6 is characterized in that: The load balancing and efficiency improvement module includes a real-time load monitoring unit and a load balancing strategy unit; The real-time load monitoring unit is used to continuously monitor the data transmission volume and network bandwidth utilization of each sensor node, and notify the routing control unit to dynamically adjust the transmission volume of different routes according to the real-time load of the node; The load balancing strategy unit is used to assist the routing control unit to automatically distribute data packets to a path with a lower load when a certain path is overloaded; The real-time load monitoring unit and the load balancing strategy unit can be specifically expressed as the following formula: in, Indicates the assigned data path (i.e. the path that the data packet will take); It represents the data distribution result on the path with lower load; Indicates the data distribution result when load balancing on the current path, indicating that if the current path is the best, the data will still be transmitted through this path; Indicates that the path with the smallest load is selected, which is calculated by the average load of all nodes on each path; represents the set of all possible paths; Indicates the path The total number of nodes on ; Indicates the current data transmission volume of node n; Represents the maximum available bandwidth of node n.

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