Self-powered device and vibration monitoring mechanism simulation system
By combining vibration power generation and solar power generation into a self-powered device, the problem of insufficient power supply for traditional bridge power supply equipment in rainy weather is solved, enabling all-weather bridge safety monitoring, ensuring the normal operation of sensors and providing real-time health assessment.
Patent Information
- Application Number
- CN202511698729.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-19
- Publication Date
- 2026-02-13
AI Technical Summary
In traditional bridge power supply equipment, solar panel power generation is severely affected by weather conditions and sunlight levels. It cannot effectively supply power during continuous rainy weather, which affects the normal operation of sensors.
By combining vibration power generation components and solar power supply components, the vibration power generation components generate electricity through vibration, and the solar power supply components generate electricity through sunlight. The inverter combines the two and stores the electricity in the battery to ensure continuous power supply. At the same time, the monitoring mechanism simulation system includes modules for data preprocessing, early warning threshold setting, simulation calculation, and comprehensive evaluation index to achieve real-time monitoring of the bridge structure.
It achieves continuous power supply throughout the entire time period, ensuring the normal operation of the sensors, and improves the reliability and stability of bridge safety monitoring by conducting real-time health assessments and early warnings of the bridge structure through multi-level monitoring modules.
Smart Images
Figure CN121530280A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of bridges, specifically to a self-powered device and a vibration monitoring mechanism simulation system. Background Technology
[0002] Bridge safety has always held a paramount position for us. Bridge construction projects involve long construction periods, large investments, and complex technical requirements. Especially in recent years, the continuous increase in bridge spans and the use of new materials and processes have amplified bridge safety risks. Statistics show that on average, a bridge collapse occurs every two months, and the number of bridge accidents is increasing year by year, with serious consequences. Road traffic and bridge construction are developing rapidly, and as vital lifeline projects, bridge safety monitoring plays a crucial role in transportation and economic development. Given the rapid development of bridge engineering, safety monitoring is of utmost importance. Bridge construction is a vital national infrastructure project, and bridge engineering is a lifeline project related to the coordinated development of society and the economy. The rapid development of bridge facilities, the huge financial investment, and the prominent role in the economy and society are self-evident. In recent years, urban bridge collapse accidents have occurred repeatedly. How to take effective measures to fundamentally curb these accidents has become extremely urgent. A review of the factors contributing to several collapse accidents reveals that the main causes include human factors, inadequate design standards and specifications, design quality problems, and construction quality defects.
[0003] However, traditional bridge power supply equipment has the following drawbacks: Currently, some cities have used solar panel power generation devices on elevated bridges, but the single method of solar power generation is severely affected by weather conditions and the degree of sunlight. In continuous rainy weather, it affects the power supply to the sensors. Summary of the Invention
[0004] The purpose of this invention is to provide a self-powered device and a vibration monitoring mechanism simulation system to solve the problem mentioned in the background art that some urban overpasses have used solar panel power generation devices, but the single solar power generation method is seriously affected by weather conditions and the degree of sunlight, and the power supply capacity to the sensors is affected in continuous rainy weather.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a self-powered device, comprising a vibration power generation component, an inverter on one side of the vibration power generation component, a solar power supply component on one side of the inverter, a battery at the bottom of the inverter, the vibration power generation component comprising a fixed base and two height shells, the top two sides of the fixed base being fixedly connected to the bottom ends of the two height shells respectively, a pull rod shell at the top of the fixed base, a voltage transformer block installed inside the pull rod shell, an indicator light fixedly installed on one side of the voltage transformer block, a vibration generator installed at the connection between the voltage transformer block and the pull rod shell, the solar power supply component comprising a mounting plate and a length rod, the top of the mounting plate being fixedly connected to the bottom end of the length rod, a power supply platform fixedly installed at the top of the length rod, and a solar panel at the top of the power supply platform.
[0006] As a preferred embodiment of the present invention, the vibration generator includes a soft iron frame and a coil. One side of the inner wall of the soft iron frame is connected to one end of the coil. A fixing frame is fixedly installed on one side of the soft iron frame. A moving iron plate is installed at the other end of the coil. A permanent magnet is installed at the top of the moving iron plate. A return spring is fixedly installed at the top of the fixing frame. The top of the return spring is fixedly connected to the side of the moving iron plate facing away from it. One end of the soft iron frame is connected to a voltage transformer block. When in a static state, the magnetic force generated by the permanent magnet causes the moving iron plate to contact the soft iron frame, forming a closed magnetic circuit, and the magnetic flux in the coil is at its maximum. When subjected to an external force transmitted from the pull rod shell, the moving iron plate separates from the soft iron frame, and the magnetic circuit is broken. At this time, the magnetic flux is very small. When the external force disappears, the moving iron plate forms a closed magnetic circuit with the soft iron frame again. This repeatedly opening and closing magnetic circuit generates a positive and negative alternating voltage on the coil.
[0007] As a preferred embodiment of the present invention, telescopic rods are fixedly installed at the top of both height shells, and the movable ends of the two telescopic rods are fixedly connected to both sides of the bottom end of the pull rod shell, respectively. Connecting springs are fixedly installed on the surface of both height shells, and the top ends of the two connecting springs are fixedly connected to the side of the pull rod shell facing each other. Rigid springs are fixedly installed on both sides of the bottom end of the pressure transformer block, and the bottom ends of the two rigid springs are fixedly connected to the fixed base. Both the connecting springs and the rigid springs are elastic, and the connecting springs and the rigid springs weaken the vibration force received, ensuring the subsequent reset of the pressure transformer block.
[0008] As a preferred embodiment of the present invention, a vertical plate is fixedly installed on one side of the top of the power supply platform, and an angle seat is fixedly installed on the other side of the top of the power supply platform. An angle plate is rotatably connected inside the angle seat. The top of the angle plate is fixedly connected to the bottom of the solar panel. A lead screw is rotatably connected between the vertical plate and the angle seat. A movable block that is slidably connected to the power supply platform is threaded to the middle of the lead screw. A support plate is rotatably connected to the top of the movable block. The top of the support plate is rotatably connected to the middle of the bottom of the angle plate. During the sliding process of the movable block, it drives the support plate to move synchronously. The support plate pushes the angle plate from the bottom, and the angle plate deflects along the angle seat, adjusting the angle at which the solar panel absorbs solar energy. The solar panel converts solar energy into electrical energy.
[0009] As a preferred embodiment of the present invention, a servo motor for driving the lead screw to rotate is fixedly installed on the surface of the upright plate. After the servo motor is powered on, it starts and drives the lead screw to rotate. The thread on the surface of the lead screw matches the thread on the inner wall of the movable block. The movable block is limited by a power supply platform that matches its shape and size, so the movable block slides along the lead screw.
[0010] As a preferred embodiment of the present invention, a first connecting wire is fixedly connected to one side of the vibration power generation component, and a second connecting wire is fixedly connected to one side of the solar power supply component. One end of the first connecting wire and one end of the second connecting wire are both fixedly connected to the input terminal of the inverter. The electrical energy generated by the vibration power generation component and the electrical energy generated by the solar power supply component are transmitted to the inverter.
[0011] As a preferred embodiment of the present invention, the output terminal of the inverter is fixedly connected to a third connecting wire, and the inverter is connected to the battery through the third connecting wire. The electrical energy processed by the inverter is centrally stored in the battery.
[0012] The present invention provides a vibration monitoring mechanism simulation system for a self-powered device, comprising a monitoring mechanism simulation system, wherein the monitoring mechanism simulation system includes a data preprocessing module, an early warning threshold setting module, a simulation calculation module, and a comprehensive evaluation index module; The data preprocessing module collects and preprocesses bridge vibration data, the early warning threshold setting module sets early warning thresholds for the data, the simulation calculation module performs calculations and analyses using several typical bridge structures as analysis objects, and the comprehensive evaluation index module is used for data comparison during the regular maintenance of bridges.
[0013] As a preferred technical solution of the present invention, the data preprocessing module includes a preprocessing submodule and an anomaly removal submodule, and the early warning threshold setting module includes an early warning index selection principle submodule, an environmental load effect submodule, a human influence factor submodule, and a bridge structure early warning threshold submodule. There are many abnormal data and noise data in the acquisition of bridge vibration data by the preprocessing sub-module. These data will have a certain impact on the assessment of bridge health and subsequent maintenance, repair and reinforcement. Therefore, we need to preprocess the data. Data preprocessing includes the elimination of abnormal data, the supplementation of missing data, and noise reduction processing. Usually, the abnormal situations and processing methods of data are as follows: When data mutation occurs, the data should be eliminated through statistics and then interpolation should be carried out; for data exceeding a certain amount, a threshold should be set first, and the exceeding data should be eliminated and then replaced with interpolated data; noise and interfered data are filtered and the noise is eliminated through filtering methods; the trend term caused by instrument zero drift is removed through software and hardware; the change of the sensor preset value is solved through the method of reference value offset. The difference between the test value and the reference value is the obtained actual value. And the abnormal sub-module is eliminated. The data abnormality of the abnormal sub-module is usually the situation where a small part of the data is lost or the data does not conform to the actual situation due to environmental or human factors during the data acquisition and reception process. In order to make the data more conform to the actual situation and provide more accurate parameters for subsequent data processing, it is necessary to eliminate the abnormal values. There are many methods for eliminating abnormal values. The basic idea is to set a threshold, and the data exceeding this threshold is the abnormal value and needs to be eliminated. Usually, there are the Rutherford criterion, the prediction comparison method, the Chauvenet method, and the Grubbs criterion for eliminating abnormal values. The early warning index selection principle sub-module is selected according to the characteristics of bridge load action, key components and the overall structure, and has relative stability, wide applicability and strong operability. When there are conflicts between different indicators, the indicator reflecting the most unfavorable condition of the bridge should be taken as the standard. At the same time, the different degrees of the indicators should be reasonably reflected, and it should preferably include four levels: level, relatively heavy, severe, and especially severe, which are represented by blue, yellow, orange, and red respectively. The wind speed early warning threshold of the environmental load action sub-module: the average wind speed within 10 minutes, level I is greater than or equal to 25.0 m / s; level II is 25.0 m / s; level III is 20.8 m / s; level IV is 17.2 m / s; the bridge deck temperature early warning threshold: level I is -5 °C; level II is -3 °C; level IV is 0 °C. Low temperature causes icing on the bridge deck, affecting driving safety, and vehicle broadcasting prompts are carried out; humidity effect: level I is 70%; level II is 60%; level III is 50%; level IV is 40%. The vehicle load of the human influence factor sub-module: level I, vehicle total weight / axle weight > 2 times the designed vehicle load; level II, the ratio of vehicle total weight / axle weight to the designed vehicle load is between 1.5 - 2.0; level III, the ratio of vehicle total weight / axle weight to the designed vehicle load is between 1.0 - 1.5; level IV, the vehicle total weight / axle weight exceeds the limit specified in "Limits of Dimensions, Loads and Masses for Road Vehicles". The impact of vehicles or ships on bridge piers or towers: bearing capacity assessment method - PF = R / P, level I, 0 < PF ≤ 0.1; level II, 0.1 < PF ≤ 0.5; level III, 0.5 < PF ≤ 0.7; level IV, 0.7 < PF ≤ 1.The bridge structure early warning threshold submodule includes early warning thresholds for tower tilt, absolute cable force, and abnormal cable force changes. The natural frequency of the main girder should preferably be the frequency at 25℃. Natural frequencies at different temperatures should be converted based on the correlation between natural frequencies and temperature obtained from the first year's monitoring data. The early warning threshold for support reaction force is also specified.
[0014] As a preferred technical solution of the present invention, the simulation calculation module includes a bridge model submodule, a load value submodule and a simulation analysis submodule, and the comprehensive evaluation index module includes a comprehensive analysis submodule and a data evaluation submodule. The bridge model submodule provides models for beam bridges, arch bridges, and cable-stayed bridges. The load value submodule specifies the first-stage load as the concrete box girder and lower piers serving as the bridge's load-bearing structure, with a concrete unit weight of 25 kN / m³. The second-stage dead load includes a 90mm thick asphalt concrete pavement, an 80mm thick C30 reinforced concrete pavement, two crash barriers, and a central median strip. Both the C30 concrete and asphalt concrete unit weights are set to 24 kN / m³. The simulation analysis submodule analyzes the beam bridge's vibration modes and stress under no-load conditions. Taking a beam bridge as an example, the software COMSOL is used to analyze the bridge's operation under load, simulating the data acquisition process. Vehicle loads are set as trucks, with each 60-meter convoy consisting of six trucks, each weighing 15 tons. The comprehensive analysis submodule determines the standard values for the bridge's structural condition and selects... Monitoring data from a period during the initial operation phase of the bridge structure is used as the initial value for the bridge structure's health status. Then, correlation analysis is used to calculate the correlation between two monitoring indicators as the standard value to determine the four-level early warning threshold for the bridge structure. The monitoring indicators are analyzed based on correlation analysis and compared with the four-level early warning threshold for the bridge structure to issue an early warning for its health status. The data evaluation submodule, Support Vector Machine (SVM), is a data mining method based on statistical learning theory. It successfully handles regression problems. SVM has a rigorous theoretical foundation and is based on the principle of minimizing structural risk. Its algorithm is a convex quadratic optimization problem, guaranteeing that the found solution is the globally optimal solution. It solves practical problems involving small samples, nonlinearity, and high dimensionality. The complexity of the problem does not depend on the dimension of the features and it has good generalization ability.
[0015] Compared with the prior art, the beneficial effects of the present invention are: the device is used to collect the conventional vibration energy of the bridge body and the local wind energy generated by the high-speed passage of vehicles to generate electricity, realizing continuous power generation at all times. The vibration power generation component works in conjunction with the solar power generation device to ensure the normal use of the entire set of sensing and monitoring equipment. Attached Figure Description
[0016] Figure 1 This is a side view of the present invention; Figure 2 This is a side view of the vibration power generation component of the present invention; Figure 3 This is a partial schematic diagram of the vibration generator of the present invention; Figure 4 This is a side view of the solar power supply component of the present invention; Figure 5 This is a schematic diagram of the architecture of the monitoring mechanism simulation system of the present invention; Figure 6 This is a schematic diagram of the architecture of the data preprocessing module of the present invention; Figure 7 This is a schematic diagram of the architecture of the early warning threshold setting module of the present invention; Figure 8 This is a schematic diagram of the architecture of the simulation computing module of the present invention; Figure 9 This is a schematic diagram of the architecture of the comprehensive evaluation index module of the present invention; Figure 10 This is a model diagram of the beam bridge of the present invention; Figure 11 This is a model diagram of the cable-stayed bridge of the present invention.
[0017] In the diagram: 1. Vibration generator assembly; 101. Fixed base; 102. Height shell; 103. Telescopic rod; 104. Pull rod shell; 105. Voltage transformer block; 106. Indicator light; 107. Vibration generator; 1071. Coil; 1072. Soft iron frame; 1073. Return spring; 1074. Moving iron plate; 1075. Permanent magnet; 1076. Fixing frame; 108. Connecting spring; 109. Rigid spring; 2. Battery; 3. Inverter; 4. Solar power supply assembly; 401. Mounting plate; 402. Length rod; 403. Power supply platform; 404. Angle seat; 405. Solar panel; 406. Angle plate; 407. Support plate; 408. Movable block; 409. Lead screw; 410. Vertical plate; 411. Servo motor; 5. First connecting wire; 6. Second connecting wire; 7. Third connecting wire. Detailed Implementation
[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.
[0019] Please see Figure 1-11This invention provides a self-powered device and a vibration monitoring mechanism simulation system, including a vibration power generation component 1, an inverter 3 on one side of the vibration power generation component 1, a solar power supply component 4 on one side of the inverter 3, and a battery 2 at the bottom of the inverter 3. The vibration power generation component 1 includes a fixed base 101 and two height shells 102. The top two sides of the fixed base 101 are fixedly connected to the bottom ends of the two height shells 102 respectively. The top of the fixed base 101 is provided with a pull rod shell 104. A voltage transformer block 105 is installed inside the pull rod shell 104. An indicator light 106 is fixedly installed on one side of the voltage transformer block 105. A vibration generator 107 is installed at the connection between the voltage transformer block 105 and the pull rod shell 104. The solar power supply component 4 includes a mounting plate 401 and a length rod 402. The top of the mounting plate 401 is fixedly connected to the bottom end of the length rod 402. A power supply platform 403 is fixedly installed on the top of the length rod 402. A solar panel 405 is provided on the top of the power supply platform 403.
[0020] The vibration generator 107 includes a soft iron frame 1072 and a coil 1071. One side of the inner wall of the soft iron frame 1072 is connected to one end of the coil 1071. A fixing bracket 1076 is fixedly installed on one side of the soft iron frame 1072. A moving iron piece 1074 is installed on the other end of the coil 1071. A permanent magnet 1075 is installed on the top of the moving iron piece 1074. A return spring 1073 is fixedly installed on the top of the fixing bracket 1076. The top of the return spring 1073 is fixedly connected to the side of the moving iron piece 1074 opposite to it. The soft iron frame 1072... One end is connected to the voltage transformer 105. When in a static state, the magnetic force generated by the permanent magnet 1075 causes the moving iron piece 1074 to contact the soft iron frame 1072, forming a closed magnetic circuit, and the magnetic flux in the coil 1071 is at its maximum. When subjected to an external force transmitted from the pull rod shell 104, the moving iron piece 1074 separates from the soft iron frame 1072, and the magnetic circuit is broken. At this time, the magnetic flux is very small. When the external force disappears, the moving iron piece 1074 forms a closed magnetic circuit with the soft iron frame 1072 again. This repeatedly opening and closing magnetic circuit generates a positive and negative alternating voltage on the coil 1071.
[0021] Telescopic rods 103 are fixedly installed at the top of each of the two height shells 102. The movable ends of the two telescopic rods 103 are fixedly connected to the two sides of the bottom of the pull rod shell 104, respectively. Connecting springs 108 are fixedly installed on the surface of each of the two height shells 102. The top of each of the two connecting springs 108 is fixedly connected to the side of the pull rod shell 104 facing each other. Rigid springs 109 are fixedly installed on both sides of the bottom of the pressure block 105. The bottom ends of each of the two rigid springs 109 are fixedly connected to the fixed base 101. Both the connecting springs 108 and the rigid springs 109 are elastic. The connecting springs 108 and the rigid springs 109 weaken the vibration force received, ensuring the subsequent reset of the pressure block 105.
[0022] A vertical plate 410 is fixedly installed on one side of the top of the power supply platform 403, and an angle seat 404 is fixedly installed on the other side of the top of the power supply platform 403. An angle plate 406 is rotatably connected inside the angle seat 404. The top of the angle plate 406 is fixedly connected to the bottom of the solar panel 405. A lead screw 409 is rotatably connected between the vertical plate 410 and the angle seat 404. A movable block 408 that is slidably connected to the power supply platform 403 is threadedly connected to the middle of the lead screw 409. A support plate 407 is rotatably connected to the top of the movable block 408. The top of the support plate 407 is rotatably connected to the middle of the bottom of the angle plate 406. During the sliding process of the movable block 408, it drives the support plate 407 to move synchronously. The support plate 407 pushes the angle plate 406 from the bottom. The angle plate 406 deflects along the angle seat 404, adjusting the angle of solar energy absorption by the solar panel 405. The solar panel 405 converts solar energy into electrical energy.
[0023] A servo motor 411 that drives the lead screw 409 to rotate is fixedly installed on the surface of the upright plate 410. After the servo motor 411 is powered on, it starts and drives the lead screw 409 to rotate. The thread on the surface of the lead screw 409 matches the thread on the inner wall of the movable block 408. The movable block 408 is limited by the power supply platform 403 that matches its shape and size, so the movable block 408 slides along the lead screw 409.
[0024] A first connecting wire 5 is fixedly connected to one side of the vibration power generation component 1, and a second connecting wire 6 is fixedly connected to one side of the solar power supply component 4. One end of the first connecting wire 5 and one end of the second connecting wire 6 are both fixedly connected to the input terminal of the inverter 3. The electrical energy generated by the vibration power generation component 1 and the electrical energy generated by the solar power supply component 4 are transmitted to the inverter 3.
[0025] The output terminal of inverter 3 is fixedly connected to a third connecting wire 7. Inverter 3 is connected to battery 2 through the third connecting wire 7. The electrical energy processed by inverter 3 is stored in battery 2.
[0026] The present invention provides a vibration monitoring mechanism simulation system for a self-powered device, comprising a monitoring mechanism simulation system, which includes a data preprocessing module, an early warning threshold setting module, a simulation calculation module, and a comprehensive evaluation index module; The data preprocessing module collects and preprocesses bridge vibration data, the early warning threshold setting module sets early warning thresholds for the data, the simulation calculation module performs calculations and analyses using several typical bridge structures as analysis objects, and the comprehensive evaluation index module is used for data comparison during the regular maintenance of bridges.
[0027] The data preprocessing module includes a preprocessing submodule and an anomaly removal submodule; the early warning threshold setting module includes a early warning indicator selection principle submodule, an environmental load effect submodule, a human influence factor submodule, and a bridge structure early warning threshold submodule. There are many abnormal data and noise data in the acquisition of bridge vibration data by the preprocessing submodule. These data will have a certain impact on the assessment of bridge health and subsequent maintenance, repair and reinforcement. Therefore, we need to preprocess the data. Data preprocessing includes the elimination of abnormal data, the supplementation of missing data, and noise reduction. Usually, the abnormal situations and processing methods of data are as follows: When data mutation occurs, the data should be eliminated through statistics and then interpolated; for data exceeding a certain amount, a threshold should be set first, the exceeding data should be eliminated and then replaced with interpolated data; noise and interfered data are filtered and the noise is eliminated through filtering; the trend term caused by instrument zero drift is removed through software and hardware; the change of sensor preset value is solved through the method of reference value offset. The difference between the test value and the reference value is the obtained actual value. The abnormal submodule is eliminated. The data abnormality of the abnormal submodule usually occurs when a small part of data is lost or the data does not conform to the actual situation due to environmental or human factors during data acquisition and reception. In order to make the data more conform to the actual situation and provide more accurate parameters for subsequent data processing, it is necessary to eliminate abnormal values. There are many methods for eliminating abnormal values. The basic idea is to set a threshold, and the data exceeding this threshold is an abnormal value and needs to be eliminated. Usually, there are the Rutherford criterion, the prediction comparison method, the Chauvenet method, and the Grubbs criterion for eliminating abnormal values. The early warning index selection principle submodule is selected according to the characteristics of bridge load action, key components and the overall structure, and has relative stability, wide applicability and strong operability. When different indicators conflict with each other, the indicator reflecting the most unfavorable condition of the bridge should be used as the standard. At the same time, the different levels of the indicators should be reasonably reflected, and it should include four levels: level, relatively heavy, serious, and particularly serious, which are represented by blue, yellow, orange, and red respectively. The wind speed early warning threshold of the environmental load action submodule: the average wind speed within 10 minutes, level I is greater than or equal to 25.0 m / s; level II is 25.0 m / s; level III is 20.8 m / s; level IV is 17.2 m / s; the bridge deck temperature early warning threshold: level I is -5°C; level II is -3°C; level IV is 0°C. Low temperature causes the bridge deck to freeze, affecting driving safety, and vehicle broadcasting prompts are carried out; humidity effect: level I is 70%; level II is 60%; level III is 50%; level IV is 40%. The vehicle load of the human influence factor submodule: level I, vehicle total weight / axle weight > 2 times the designed vehicle load; level II, the ratio of vehicle total weight / axle weight to the designed vehicle load is between 1.5 - 2.0; level III, the ratio of vehicle total weight / axle weight to the designed vehicle load is between 1.0 - 1.5; level IV, the vehicle total weight / axle weight exceeds the limit specified in "Limits for the Dimensions, Loads and Masses of Road Vehicles". The impact of vehicles or ships on bridge piers or towers: Bearing capacity assessment method - PF = R / P, level I, 0 < PF ≤ 0.1; level II, 0.1 < PF ≤ 0.5; level III, 0.5 < PF ≤ 0.7; level IV, 0.7 < PF ≤ 1.The bridge structure early warning threshold submodule includes early warning thresholds for tower tilt, absolute cable force, and abnormal cable force changes. The natural frequency of the main girder should preferably be the frequency at 25℃. Natural frequencies at different temperatures should be converted based on the correlation between natural frequencies and temperature obtained from the first year's monitoring data. The early warning threshold for support reaction force is also specified.
[0028] The simulation calculation module includes a bridge model submodule, a load value acquisition submodule, and a simulation analysis submodule; the comprehensive evaluation index module includes a comprehensive analysis submodule and a data evaluation submodule. The bridge model submodule provides models for beam bridges, arch bridges, and cable-stayed bridges. The load value submodule specifies that the first-phase load consists of the concrete box girder and the substructure piers, which serve as the load-bearing structure of the bridge. The concrete unit weight is taken as 25 kN / m³. 3 The second phase of the dead load includes a 90mm thick asphalt concrete pavement, an 80mm thick C30 reinforced concrete pavement, two crash barriers, and a central median strip. The unit weight of both the C30 concrete and the asphalt concrete is taken as 24kN / m³. 3 The simulation analysis submodule analyzes the vibration modes and stress conditions of a beam bridge under no-load conditions. Taking a beam bridge as an example, the software COMSOL is used to analyze the bridge's operation under load, simulating the data acquisition process. The vehicle load is set as trucks, with each 60-meter convoy consisting of six trucks, each weighing 15 tons. The comprehensive analysis submodule determines the standard value of the bridge structure's health status, selecting monitoring data from a period during the initial stage of bridge operation as the initial value for the bridge structure's health status. Then, based on the correlation analysis method, the correlation between two monitoring indicators is calculated as the standard value, determining the four-level early warning threshold for the bridge structure's health status. The monitoring indicators are analyzed based on the correlation analysis method and compared with the four-level early warning threshold for the bridge structure to issue an early warning for the bridge structure's health status. The data evaluation submodule uses Support Vector Machine (SVM), a data mining method based on statistical learning theory, to successfully handle regression problems. SVM has a rigorous theoretical foundation and is based on the principle of minimizing structural risk. Its algorithm is a convex quadratic optimization problem, ensuring that the solution found is the globally optimal solution. It solves practical problems with small samples, nonlinearity, and high dimensionality. The complexity of the problem does not depend on the dimension of the features and has good generalization ability.
[0029] In this invention, when in a static state, the magnetic force generated by the permanent magnet 1075 causes the moving iron piece 1074 to contact the soft iron frame 1072, creating a closed magnetic circuit, and the magnetic flux within the coil 1071 is at its maximum. When subjected to an external force transmitted from the pull rod housing 104, the moving iron piece 1074 separates from the soft iron frame 1072, breaking the magnetic circuit, and the magnetic flux is very small at this time. When the external force disappears, the moving iron piece 1074 again forms a closed magnetic circuit with the soft iron frame 1072. This repeatedly opening and closing magnetic circuit generates a changing AC voltage on the coil 1071, which starts the servo motor 411 after it is energized. The machine 411 drives the lead screw 409 to rotate. The threads on the surface of the lead screw 409 match the threads on the inner wall of the movable block 408. The movable block 408 is limited by the power supply platform 403, which matches its shape and size. Therefore, the movable block 408 slides along the lead screw 409. During the sliding process, the movable block 408 drives the support plate 407 to move synchronously. The support plate 407 pushes the angle plate 406 from the bottom. The angle plate 406 deflects along the angle seat 404, adjusting the angle at which the solar panel 405 absorbs solar energy. The solar panel 405 converts solar energy into electrical energy. Assuming the wind speed remains constant, under quasi-static conditions, the expression for the aerodynamic force Fr(t) acting on the system is:
[0030] In the formula, ρ is the air density, A is the area of the blunt body perpendicular to the wind direction, U is the wind speed, and U represents the aerodynamic coefficient. The theoretical model of the variable triangular cross section galloping piezoelectric energy harvester is as follows:
[0031] Before the bluff body begins to vibrate, the nonlinear term of the aerodynamics is relatively small. When i=1, the system damping term is... At this point, the damping term is linear. When i>1, the damping term exists in a nonlinear form. The influence of the external load on the natural frequency of the energy harvester, the system damping, and the critical wind speed in the circuit is determined through linear analysis of electromechanical coupling problems. Based on this, the following state variables are introduced: Table 1 shows the system aerodynamic parameters and the values of n1 and n3.
[0032] During the experimental testing, the resistance was set to 100kΩ-10MΩ, the electromechanical coupling coefficient of the system was ψ=1.15×10-5N / V, the piezoelectric element was MFC, the capacitor was Cp=15.7nF, and a 200mm×200mm×0.1mm aluminum sheet was used as the cantilever beam. A 30mm×10mm×0.3mm MFC piezoelectric element was installed at the middle position of the top of the cantilever beam. The apex angle of the blunt body was set to 30°, 60°, and 90°, controlling the mass of the blunt body at different apex angles while maintaining a consistent height parameter. A wire was used to connect the resistor to the circuit. The honeycomb-shaped area at the end of the circular wind tunnel served as a wind stabilization device. The vibration signal generated by the blunt body vibration was acquired using a digital oscilloscope, and the amplitude was measured by a laser displacement sensor. The energy harvesting power of a single vibration energy harvesting device was limited due to its size and the power of the wind tunnel equipment, with a maximum of only 10mW. (Refer to the instruction manual for details.) Figure 10 The Melk Bridge in Austria has spans of 53+53+79+53+36 (m) and a total length of 274m; the Porr Bridge in Vienna, Austria has a single span of 44m; the Warth Bridge in Austria has 7 spans of 62+5×67+62 (m) and a total length of 459m. The continuous beam bridge deck has a 14m wide driving lane, a beam section height of 5m, and a box girder bottom width of 6.2m, increasing to 8m near the driving lane. The bridge has 9 spans of 25.1+34.7+31.5+30.2+32.6+30.1+30.2+30.4+29.2, a two-way four-lane bridge with a single-direction bridge deck width of 14m. (Refer to the attached instruction manual.) Figure 11 The RAMA2X Bridge in Bangkok, Thailand has a main span of 450m and side spans of 61.2+57.6+46.8(m); the Ting Kau Bridge in Hong Kong SAR, China has four spans of 127+475+448+127(m). Using these as a reference, the bridge length parameters, materials, weight, and standard values for the bridge structural health of the simulated bridge should be determined according to the following formula to establish the functional relationship between the two monitoring data: , X is the sample; b is the threshold; f(x) is another monitoring item's data; K(xi,x) is the kernel function; It is a Lagrange multiplier.
[0033] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A self-powered device, comprising a vibration-generating component (1), characterized in that: An inverter (3) is provided on one side of the vibration power generation component (1), and a solar power supply component (4) is provided on one side of the inverter (3). A battery (2) is provided at the bottom of the inverter (3). The vibration power generation component (1) includes a fixed base (101) and two height shells (102). The top two sides of the fixed base (101) are fixedly connected to the bottom ends of the two height shells (102). A tie rod shell (104) is provided at the top of the fixed base (101). A voltage transformer block is installed inside the tie rod shell (104). 105), an indicator light (106) is fixedly installed on one side of the pressure transformer (105), a vibration generator (107) is installed at the connection between the pressure transformer (105) and the pull rod shell (104), the solar power supply component (4) includes a mounting plate (401) and a length rod (402), the top end of the mounting plate (401) is fixedly connected to the bottom end of the length rod (402), a power supply platform (403) is fixedly installed on the top end of the length rod (402), and a solar panel (405) is provided on the top end of the power supply platform (403).
2. The self-powered device according to claim 1, characterized in that: The vibration generator (107) includes a soft iron frame (1072) and a coil (1071). One side of the inner wall of the soft iron frame (1072) is connected to one end of the coil (1071). A fixing bracket (1076) is fixedly installed on one side of the soft iron frame (1072). A moving iron piece (1074) is installed on the other end of the coil (1071). A permanent magnet (1075) is installed on the top of the moving iron piece (1074). A return spring (1073) is fixedly installed on the top of the fixing bracket (1076). The top of the return spring (1073) is fixedly connected to the side of the moving iron piece (1074) facing it. One end of the soft iron frame (1072) is connected to the pressure transformer block (105).
3. The self-powered device according to claim 1, characterized in that: Telescopic rods (103) are fixedly installed on the top of both height shells (102). The movable ends of the two telescopic rods (103) are fixedly connected to the two sides of the bottom of the pull rod shell (104). Connecting springs (108) are fixedly installed on the surface of both height shells (102). The top of the two connecting springs (108) is fixedly connected to the side of the pull rod shell (104) facing each other. Rigid springs (109) are fixedly installed on both sides of the bottom of the pressure block (105). The bottom ends of the two rigid springs (109) are fixedly connected to the fixed base (101).
4. A self-powered device according to claim 1, characterized in that: A vertical plate (410) is fixedly installed on one side of the top of the power supply platform (403), and an angle seat (404) is fixedly installed on the other side of the top of the power supply platform (403). An angle plate (406) is rotatably connected inside the angle seat (404). The top of the angle plate (406) is fixedly connected to the bottom of the solar panel (405). A lead screw (409) is rotatably connected between the vertical plate (410) and the angle seat (404). A movable block (408) that is slidably connected to the power supply platform (403) is threaded in the middle of the lead screw (409). A support plate (407) is rotatably connected to the top of the movable block (408). The top of the support plate (407) is rotatably connected to the middle of the bottom of the angle plate (406).
5. A self-powered device according to claim 4, characterized in that: A servo motor (411) that drives the lead screw (409) to rotate is fixedly installed on the surface of the upright plate (410).
6. A self-powered device according to claim 1, characterized in that: The vibration power generation component (1) is fixedly connected to one side of a first connecting wire (5), and the solar power supply component (4) is fixedly connected to one side of a second connecting wire (6). One end of the first connecting wire (5) and one end of the second connecting wire (6) are both fixedly connected to the input end of the inverter (3).
7. A self-powered device according to claim 1, characterized in that: The inverter (3) is fixedly connected to a third connecting wire (7) at its output end, and the inverter (3) is connected to the battery (2) through the third connecting wire (7).
8. A vibration monitoring mechanism simulation system for a self-powered device according to any one of claims 1-7, comprising a monitoring mechanism simulation system, characterized in that: The monitoring mechanism simulation system includes a data preprocessing module, an early warning threshold setting module, a simulation calculation module, and a comprehensive evaluation index module; The data preprocessing module collects and preprocesses bridge vibration data, the early warning threshold setting module sets early warning thresholds for the data, the simulation calculation module performs calculations and analyses using several typical bridge structures as analysis objects, and the comprehensive evaluation index module is used for data comparison during the regular maintenance of bridges.
9. The vibration monitoring mechanism simulation system for a self-powered device according to claim 8, characterized in that: The data preprocessing module includes a preprocessing submodule and an anomaly removal submodule, and the early warning threshold setting module includes an early warning index selection principle submodule, an environmental load effect submodule, a human influence factor submodule, and a bridge structure early warning threshold submodule. The preprocessing submodule collects a lot of abnormal and noisy data from bridge vibration data. This data will have a certain impact on the assessment of bridge health and subsequent maintenance, repair and reinforcement. Therefore, we need to preprocess the data. Data preprocessing includes removing abnormal data, filling in missing data, and noise reduction. The following are the usual methods for handling abnormal data: When encountering data abrupt changes, the data should be statistically removed before interpolation; for data exceeding a certain amount, a threshold should be set first, and the excess data should be removed before replacing it with interpolated data; noisy and interfered data are filtered and noise is eliminated. Trend terms caused by instrument drift are removed through software and hardware. The change of the sensor preset value is solved by the method of reference value offset. The difference between the test value and the reference value is the obtained actual value, and the abnormal sub-module is eliminated. The data abnormality of the abnormal sub-module is usually caused by environmental or human factors during data acquisition and reception, resulting in the loss of a small part of data or data that does not conform to the actual situation. To make the data more conform to the actual situation and provide more accurate parameters for subsequent data processing, it is necessary to eliminate the abnormal values. There are many methods for eliminating abnormal values. The basic idea is to set a threshold, and the data exceeding this threshold is an abnormal value and needs to be eliminated. The common methods for eliminating abnormal values include the Lagrange criterion, the prediction comparison method, the Chauvenet method, and the Grubbs criterion. The principle for selecting warning indicators is that the sub-module is selected according to the characteristics of the bridge load, key components, and overall structure, and has relative stability, wide applicability, and strong operability. When different indicators conflict with each other, the indicator reflecting the most unfavorable condition of the bridge shall prevail. At the same time, the different degrees of the indicators should be reasonably reflected, and it should include four levels: level, relatively heavy, severe, and especially severe, which are represented by blue, yellow, orange, and red respectively. The warning threshold of the environmental load action sub-module: average wind speed within 10 minutes, for level I, it is greater than or equal to 25.0 m / s; for level II, it is 25.0 m / s; for level III, it is 20.8 m / s; for level IV, it is 17.2 m / s; the warning threshold of the bridge deck temperature: for level I, it is -5°C; for level II, it is -3°C; for level IV, it is 0°C. Low temperature causes icing on the bridge deck, affecting driving safety, and vehicle broadcasting prompts are carried out; humidity effect: for level I, it is 70%; for level II, it is 60%; for level III, it is 50%; for level IV, it is 40%. The human influence factor sub-module vehicle load: for level I, the total vehicle weight / axle weight > 2 times the designed vehicle load; for level II, the ratio of the total vehicle weight / axle weight to the designed vehicle load is between 1.5 - 2.0; for level III, the ratio of the total vehicle weight / axle weight to the designed vehicle load is between 1.0 - 1.5; for level IV, the total vehicle weight / axle weight exceeds the limit specified in "Limits for Dimensions, Loads and Masses of Road Vehicles". When a vehicle or ship impacts a bridge pier or tower column, the bearing capacity evaluation method - PF = R / P, for level I, 0 < PF ≤ 0.1; for level II, 0.1 < PF ≤ 0.5; for level III, 0.5 < PF ≤ 0.7; for level IV, 0.7 < PF ≤ 1.
0. The bridge structure warning threshold sub-module respectively conducts warning thresholds for bridge tower inclination, absolute cable force warning of cables, and abnormal warning of cable force change. The natural vibration frequency of the main girder should preferably use the frequency at 25°C. The natural vibration frequencies at different temperatures should be converted according to the corresponding relationship between the natural vibration frequency and temperature obtained from the first-year monitoring data. The warning threshold of the bearing reaction force.
10. A vibration monitoring mechanism simulation system for a self-powered device according to claim 8, characterized in that: The simulation calculation module includes a bridge model sub-module, a load value-taking sub-module, and a simulation analysis sub-module. The comprehensive evaluation index module includes a comprehensive analysis sub-module and a data evaluation sub-module; The bridge model submodule provides models for beam bridges, arch bridges, and cable-stayed bridges. The load value submodule specifies that the first-phase load consists of the concrete box girder and the substructure piers, which serve as the load-bearing structure of the bridge. The concrete unit weight is taken as 25 kN / m³. 3 The second phase of the dead load includes a 90mm thick asphalt concrete pavement, an 80mm thick C30 reinforced concrete pavement, two crash barriers, and a central median strip. The unit weight of both the C30 concrete and the asphalt concrete is taken as 24kN / m³. 3 The simulation analysis submodule analyzes the vibration modes and stress conditions of a beam bridge under no-load conditions. Taking a beam bridge as an example, the software COMSOL is used to analyze the bridge's operation under load, simulating the data acquisition process. The vehicle load is set as trucks, with each 60-meter convoy consisting of six trucks, each weighing 15 tons. The comprehensive analysis submodule determines the standard value of the bridge structure's health status, selecting monitoring data from a period during the initial stage of bridge operation as the initial value for the bridge structure's health status. Then, based on the correlation analysis method, the correlation between two monitoring indicators is calculated as the standard value, determining the four-level early warning threshold for the bridge structure's health status. The monitoring indicators are analyzed based on the correlation analysis method and compared with the four-level early warning threshold for the bridge structure to issue an early warning for the bridge structure's health status. The data evaluation submodule uses Support Vector Machine (SVM), a data mining method based on statistical learning theory, to successfully handle regression problems. SVM has a rigorous theoretical foundation and is based on the principle of minimizing structural risk. Its algorithm is a convex quadratic optimization problem, ensuring that the solution found is the globally optimal solution. It solves practical problems with small samples, nonlinearity, and high dimensionality. The complexity of the problem does not depend on the dimension of the features and has good generalization ability.