Vibration displacement sensor system for bridge operation monitoring and use method thereof

Abstract

The invention discloses a vibration displacement sensor system for bridge operation monitoring and a use method thereof, and belongs to the technical field of bridge engineering. The system comprises data acquisition ends and data receiving and processing ends, the data acquisition ends are fixed to bridge piers, bridge abutments or the side faces of beam slabs, each data acquisition end comprises a capacitive acceleration sensor, a microwave signal antenna, a double-lithium battery pack and a solar cell panel, and the data receiving and processing ends are installed at stable positions of the two banks of a bridge. Comprising a multi-channel microwave receiving module, an edge computing unit, a 4G / 5G / LoRa / NB-IoT multi-network transmission module and a phase difference computing module. According to the invention, the problems of insufficient stability and poor environmental adaptability of existing data transmission are solved. According to the invention, through integration of temperature compensation, anti-interference communication, intelligent power supply optimization and rapid installation design, high-precision, all-weather and low-power-consumption monitoring is realized.

Description

Technical Field

[0001] This invention relates to the field of bridge engineering technology, specifically to a vibration displacement sensor system for bridge operation monitoring and its usage method. Background Technology

[0002] After a bridge is completed and opened to traffic, in order to ensure the safety of the bridge structure, it is necessary to monitor vibration, horizontal displacement, and settlement at important parts of the bridge, such as piers, abutments, and mid-span points. Conventional monitoring methods mainly use levels, total stations, and GPS to monitor displacement and settlement, displacement gauges and accelerometers to monitor vibration, and stress / strain gauges to monitor the impact force of vehicle loads. These technologies have revealed a series of significant shortcomings in practical applications: First, they are difficult to achieve all-weather automated monitoring, especially under adverse weather conditions, leading to discontinuous data acquisition and affecting the real-time assessment of the bridge's health status; second, sensor systems are susceptible to interference from environmental factors, such as temperature and humidity changes causing drift in the spacing between the plates of a parallel plate capacitor, resulting in frequency errors and reducing the accuracy of vibration monitoring; third, data transmission faces high risks in remote areas, with unstable mobile network signals often causing communication interruptions, and electromagnetic sources such as high-voltage power lines or base stations near the bridge interfering with microwave signals, further increasing the risk of data loss. These limitations not only restrict the reliability and efficiency of the monitoring system but may also delay early warnings of bridge structural damage, endangering public safety. Summary of the Invention

[0003] The purpose of this invention is to provide a vibration displacement sensor system for bridge operation monitoring and its usage method. By integrating temperature compensation, anti-interference communication, intelligent power optimization and rapid installation design, it achieves high-precision, all-weather, low-power intelligent monitoring and solves the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A vibration displacement sensor system for bridge operation monitoring includes a data acquisition end and a data receiving and processing end. The data acquisition end is fixed to the side of a bridge pier, abutment, or beam. The data acquisition end includes a capacitive accelerometer, a microwave signal antenna, a dual lithium battery pack, and a solar panel. The capacitive accelerometer is composed of a parallel plate capacitor, a metal mass block, and a quartz crystal resonant circuit assembly, and modulates a high-frequency oscillation signal by changing the distance between the plates. The microwave signal antenna is used to transmit frequency-modulated microwave signals. The dual lithium battery pack and solar panel power the device and are protected by a sealed, light-transmitting glass.

[0006] The data receiving and processing terminal is installed at stable positions on both sides of the bridge and includes a multi-channel microwave receiving module, an edge computing unit, a 4G / 5G / LoRa / NB-IoT multi-network transmission module, and a phase difference calculation module. The multi-channel microwave receiving module is used to receive carrier signals, the edge computing unit is used to perform wavelet denoising and FFT analysis, the 4G / 5G / LoRa / NB-IoT multi-network transmission module is used for signal transmission, and its priority is 5G>4G>LoRa>NB-IoT. The phase difference calculation module is configured to analyze the carrier phase difference of the wavelength based on the FFT algorithm.

[0007] The system employs a multi-carrier fusion ranging strategy, which includes a combination of carrier signals with wavelengths of 1000m, 100m, and 1m, and uses frequency hopping spread spectrum (FHSS) technology to perform anti-interference ranging.

[0008] Preferably, the capacitive accelerometer further comprises:

[0009] The PT100 temperature sensor is used to collect ambient temperature data in real time.

[0010] Oven-controlled crystal oscillators (OCXO) are used to maintain a resonant temperature of 25℃ ± 0.5℃.

[0011] Low coefficient of thermal expansion ceramic electrode, with a coefficient of thermal expansion ≤ 0.6 × 10⁻⁶. -6 / ℃;

[0012] The data acquisition terminal also includes a silicone rubber shock-absorbing column fixing structure with a natural frequency of 50Hz.

[0013] Preferably, the power system of the data receiving and processing terminal includes an MPPT charging controller, a wind turbine generator for low wind speeds, and a battery thermal management system. The MPPT charging controller has a charging efficiency of ≥95% and a charging time of ≤6 hours on cloudy days. The wind turbine generator for low wind speeds has an output power of 10-15W. The battery thermal management system has an embedded heating film and heat sink, with a temperature control range of 20-30℃.

[0014] Preferably, the housing of the data acquisition terminal adopts an IP68+ sealed protection design, which is sealed with fluororubber sealant and hot melt adhesive, and is immersed in 1 meter water for 24 hours and tested with 5% NaCl salt spray for 1000 hours; the surface is coated with a superhydrophobic nano coating, and the heating wire automatically starts at -10℃; a double-layer metal shielding shell is constructed using an inner copper mesh and an outer aluminum alloy, with a grounding resistance of <1Ω.

[0015] Preferably, the phase difference calculation module adopts a layered ranging strategy, specifically:

[0016] A 1000m wavelength carrier wave is used for coarse measurements, with an accuracy of ±10m.

[0017] A 100m wavelength carrier wave is used to eliminate phase ambiguity with an accuracy of ±1m;

[0018] A 1m wavelength carrier combined with an FFT algorithm is used for precision measurement with an accuracy of ±0.1mm.

[0019] Preferably, the data acquisition terminal further includes a spatial positioning module and a magnetic quick-installation structure. The spatial positioning module integrates an IMU inertial measurement unit and a barometric pressure sensor, and calibrates the coordinates using a Kalman filter algorithm. The magnetic quick-installation structure uses neodymium iron boron magnets to attract a pre-embedded stainless steel base, and the installation time is ≤30 seconds.

[0020] A method for using a vibration displacement sensor system for bridge operation monitoring, based on such a system, includes the following steps:

[0021] Step 1: Multi-source data acquisition: The data acquisition end monitors the vibration signal in real time through a capacitive accelerometer and simultaneously transmits multi-carrier microwave signals;

[0022] Step 2, frequency difference ranging calculation: The data receiving and processing end uses the FFT algorithm to analyze the carrier phase difference and calculates the three-dimensional distance by combining the 1000m / 100m / 1m wavelength combination;

[0023] Step 3: Intelligent data processing: The edge computing unit performs wavelet denoising and FFT analysis on the vibration signal, and after compression, transmits it to the server through multiple network redundancy.

[0024] Step 4: Structural health assessment: The server builds an AI damage prediction model based on an LSTM neural network, and combines it with a digital twin platform to perform real-time mapping and early warning of structural deformation.

[0025] Preferably, the multi-source data acquisition stage employs a dynamic power consumption control strategy:

[0026] When there are no vehicles passing by, it samples at a low frequency of 10Hz and enters sleep mode, with power consumption <1mW;

[0027] When the vibration threshold is triggered, the system switches to 1000Hz high-frequency sampling and wakes up.

[0028] Preferably, the installation and debugging steps of the data acquisition terminal and the data receiving and processing terminal include:

[0029] The data receiving and processing end measures three-dimensional coordinates using a total station / GPS and calibrates the instrument height by combining the length of the support rod.

[0030] The data acquisition end is quickly installed using a magnetic structure and automatically matches the ranging data from the receiver end through a self-calibration module.

[0031] The server monitors parameters such as battery level and temperature of each device in real time, and triggers an SMS alert when the battery level is less than 20%.

[0032] Preferably, the AI ​​damage prediction model predicts potential risks 1-3 months in advance based on historical vibration data, displacement data, and environmental parameters, and is connected to a digital twin platform to perform visualized early warning. The environmental parameters include, but are not limited to, temperature, humidity, and traffic flow, and the potential risks include, but are not limited to, bridge bearing loosening and concrete cracking.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] 1. This invention innovatively integrates a PT100 temperature sensor and a temperature-controlled crystal oscillator into a closed-loop temperature compensation system based on a traditional planar capacitive sensor, combined with a low-expansion-coefficient ceramic electrode. This design completely solves the frequency drift problem caused by the influence of temperature and humidity on the electrode spacing, enabling the sensor to maintain a measurement accuracy of ±0.5% in environments ranging from -20℃ to 60℃, significantly improving the long-term reliability of bridge vibration monitoring data. Employing a layered carrier strategy and combining it with an FFT phase difference algorithm to replace the traditional phase measurement device, the ranging accuracy is greatly improved, achieving sub-millimeter-level monitoring of bridge displacement. Simultaneously, through frequency hopping spread spectrum with pseudo-random jumps in the 2.4-2.5GHz frequency band, interference from electromagnetic interference sources such as high-voltage power lines on the positioning signal is effectively avoided.

[0035] 2. This invention employs a double-layer metal shielding shell and a grounding resistance of <1Ω in hardware, and deploys multiple network redundant transmissions in software to solve the problems of signal interruption and electromagnetic interference in remote areas. Combined with IP68+ level sealing and superhydrophobic nano-coating of solar panels, the system can continue to work in heavy rain, salt spray or -10℃ freezing environments, effectively reducing the failure rate.

[0036] 3. This invention integrates an edge computing unit at the data receiving and processing end to compress the vibration signal after wavelet denoising by 80% in real time before uploading, thereby reducing bandwidth usage; the server-side deploys an LSTM neural network to integrate historical displacement data, environmental temperature and humidity, and real-time traffic flow to provide early warning of the risk of bearing loosening or concrete crack expansion 1-3 months in advance, and combines it with a digital twin platform to realize the visualization mapping of bridge structural deformation. Attached Figure Description

[0037] Figure 1 This is a front view of the data acquisition terminal of the present invention;

[0038] Figure 2 This is a side view of the data acquisition terminal of the present invention;

[0039] Figure 3 This is a schematic diagram of the data receiving and processing terminal of the present invention;

[0040] Figure 4 This is a comparison diagram of the sinusoidal wave for the difference frequency ranging of the present invention.

[0041] In the diagram: 1. Mass block; 2. Planar capacitor; 3. Elastic insulator of planar capacitor; 4. Data cable of planar capacitor; 5. Quartz crystal resonant circuit assembly; 6. Microwave signal antenna; 7. Dual lithium battery pack; 8. Support frame; 9. Insertable SIM card; 10. Data processing assembly; 11. Solar panel; 12. Mobile network access antenna. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] To address the issues of insufficient data transmission stability and environmental adaptability in existing systems, please refer to [link / reference needed]. Figure 1-4 This embodiment provides the following technical solution:

[0044] A vibration displacement sensor system for bridge operation monitoring is disclosed. The system includes a data acquisition end and a data receiving and processing end. The data acquisition end comprises a parallel plate capacitor 2 and a metal mass block 1 of a certain weight. The parallel plate capacitor 2 and a quartz crystal resonant circuit assembly 5 form a high-frequency oscillation circuit. This device is fixed to the side of the bridge pier, abutment, or beam. For the same bridge, different channels of data acquisition ends can be selected. When vehicles travel, causing vibrations to the beam, pier, or abutment, the spacing between the parallel plate capacitor 2 plates changes with the vibration due to the inertia of the mass block 1. This causes changes in the frequency and amplitude of the vibration torque of the quartz crystal resonant circuit assembly 5. Microwaves are loaded into the system, becoming a modulation signal, which is then transmitted to the data receiving and processing end. The data receiving and processing end receives the microwave signal, demodulates it, and reconstructs the vibration signal. The data is then processed by a processor, quantized, and transmitted via a wireless network to a remote server, providing the vibration time, location, frequency, and displacement changes.

[0045] The number of data acquisition terminals and data receiving and processing terminals is determined based on the bridge span and total length. One data acquisition terminal can be installed on the left or right side of each pier (abutment). One data acquisition terminal can be installed on the left and right sides of each mid-span beam. For corrugated steel web plates, one data acquisition terminal can be installed on the left and right sides of the steel web at the pier and mid-span. When installing the data acquisition terminals, pay attention to the direction of the solar panels facing the rising and setting sun, and use strong adhesive or screws for fixation. The data receiving and processing terminals are installed in stable areas on both banks of the bridge, or on the roof of buildings. Installation should be secure, and the three-dimensional coordinates of the installation point should be statically measured using a total station or GPS. The length and phase difference (as the instrument height) of the support rod and the data receiving and processing terminal are then uploaded to a remote server.

[0046] The data receiving and processing end is responsible for processing data and uploading it to the server using the mobile wireless network. The data receiving and processing end uses a SIM card and can optionally use an IoT card to access the mobile network. To address the issue of unstable mobile network signals and high risk of data transmission interruption in remote areas, multi-network redundancy is employed: it simultaneously supports 4G / 5G, LoRa, and NB-IoT communication modes, with a priority setting of 5G > 4G > LoRa > NB-IoT. When the primary network is interrupted, it automatically switches to the backup network. Furthermore, edge computing pre-processing is added: an edge computing module is integrated into the data receiving and processing end to perform FFT analysis and noise filtering on the raw vibration signal, compressing the data volume by 80% before uploading, thus reducing network bandwidth consumption. To address the issue of microwave signals being susceptible to interference from electromagnetic sources such as high-voltage power lines and base stations near bridges, spread spectrum communication technology is employed: the microwave carrier frequency is changed from a fixed frequency to frequency hopping spread spectrum (FHSS), with the frequency band hopping in a pseudo-random sequence within the 2.4-2.5 GHz range to avoid common industrial interference frequency bands; shielding and grounding optimization: the data acquisition terminal shell adopts double-layer metal shielding (inner copper mesh + outer aluminum alloy), with a grounding resistance of <1Ω, reducing external electromagnetic coupling.

[0047] During installation, the location for the data receiving and processing terminal needs to be carefully selected. It should be stable and free from electromagnetic interference from high-voltage power lines, towers, or other equipment in the direction of the bridge. After selection, control measurements and adjustments should be performed on the selected points. A total station or GPS network should be used. Elevations can be measured using geometric leveling or precise trigonometric leveling. Adjusted control point data should be uploaded to the server. The data receiving and processing terminal should be installed and stably fixed using a support frame, protected against winds of force 6 or higher. For strong winds, a windproof observation house can be considered, with walls made of non-metallic, non-magnetic materials to prevent obstruction of microwave transmission and reception. The microwave signal antenna should be exposed on the roof. During strong winds, the server can temporarily stop the device. The data acquisition terminal should be fixed to the side of the beam, ideally away from other equipment that generates electromagnetic interference (such as telecommunications base stations).

[0048] Considering that existing installations require precise total station measurements and manual debugging is costly, a self-calibration positioning module can be adopted: This module integrates an IMU (Inertial Measurement Unit) and a barometric pressure sensor at the data acquisition end. During installation, it automatically measures the tilt angle and height, and combines this with microwave ranging data from the receiver to automatically calibrate the three-dimensional coordinates using a Kalman filter algorithm, eliminating the need for manual total station measurements. A magnetic quick-installation structure is also included: a strong magnetic chuck, such as a neodymium iron boron magnet, is designed at the bottom of the data acquisition end, working in conjunction with a stainless steel base pre-embedded in the bridge to achieve rapid installation in 30 seconds. Rubber shock-absorbing pads further reduce the impact of installation stress.

[0049] Numbering settings: Each data acquisition device uses different channel settings for its ranging microwave and vibration microwave to facilitate the data receiving and processing end and the server to distinguish the data acquisition ends at different locations. The microwave channels composed of ranging and vibration measurement are used to distinguish each data acquisition end.

[0050] The dual lithium battery pack 7 of this device is installed with the solar panel facing the sun in the direction of its trajectory in the sky. Each data acquisition end and data receiving and processing end can be equipped with two sets of dual lithium battery packs 7, which are charged by the solar panel 11 to ensure uninterrupted power supply 24 hours a day.

[0051] To address the issues of manual battery replacement and delayed fault warnings, remote health monitoring is implemented. A device status monitoring interface is added to the server, displaying real-time parameters such as battery voltage, temperature, and signal strength at each data acquisition point. When battery power is below 20% or a sensor malfunctions, an automatic SMS alert is sent, with a response time of less than 5 minutes. Modular design: The data acquisition point is divided into sensor, power, and communication modules, connected via pluggable interfaces. In case of a fault, the faulty module can be remotely located, and only the corresponding module needs to be replaced on-site, reducing maintenance time from 2 hours to 15 minutes.

[0052] System connection (data acquisition end and data receiving and processing end)

[0053] Microwave signal testing: After installing the data receiver and processing unit, connect to the mobile network and log in to the remote server to test whether the signal from the data receiver and processing unit is received. Each data receiver and processing unit has a fixed address (website). When the server can receive the signal from each data receiver and processing unit, it reports its respective three-dimensional coordinates and instrument height to each data receiver and processing unit. Then install the data acquisition unit, ensuring it is fixed and stable, and protected from wind. After powering on, check whether each data receiver and processing unit receives the microwave signal from each data acquisition unit. Otherwise, check the power supply and installation of each data acquisition unit.

[0054] Network connection settings: Access the remote server via mobile phone or PC to configure the device's engineering status. Data can be stored on a cloud drive within the server. Follow the prompts to configure the operational status of each data receiving and acquiring end. You can also set a username and password for accessing the server and encrypt the data on the cloud drive. Furthermore, you can set up scheduled data uploads to other control platforms, allowing construction personnel to remotely obtain monitoring data in real time and promptly understand the vibration and deformation status of the bridge during its operational phase.

[0055] After the device is installed and connected correctly, conduct a trial run for a period of time. First, check if the data receiving and processing end receives vibration and distance information from each data acquisition end. Functional testing can be performed directly on the network server to check if the data receiving and processing end is uploading data and correctly start and stop the system according to the preset program. Verify if the server can remotely control the system to operate normally. When using the automatic power optimization scheme, the sleep / wake-up mechanism and dynamic sampling frequency adjustment function are enabled.

[0056] Data Verification and Analysis: During the trial run, the collected data is viewed via mobile phone or PC connected to the server and uploaded to the cloud drive or other control platform. Technicians then perform detailed data analysis on the platform, comparing monitoring data from different time periods and locations to verify the reliability of the device's measurement results.

[0057] Optimization and Adjustment: Based on the data verification and analysis results, if measurement errors or other problems are found in the device, corresponding optimizations and adjustments will be made. Check for other sources of electromagnetic interference on the data transmission link. After multiple optimizations and adjustments to ensure stable and reliable device performance, the device will be officially put into use.

[0058] After installation, and after a period of trial testing, it can be tested directly on the server via the internet. Mobile phones, tablets, and PCs can be used to connect to the server for testing. The data measured from the network server can be observed and measured. Then, other control platforms can be connected to the internet to control the collection and uploading of data to verify its reliability before it is put into use.

[0059] In terms of spatial position monitoring, this device uses microwave to transmit ranging signals and adopts the transmission of carrier difference frequency signals for ranging. The carrier signal wavelengths of 1000m, 900m, 990m, and 999m are transmitted simultaneously. This difference frequency can measure distances within 1000m, accurate to 1m. If wavelengths of 999.9m, 999.99m, and 999.999m are superimposed, the accuracy can be down to millimeters.

[0060] To address the issue of frequency drift caused by temperature and humidity affecting the spacing between the plates of parallel-plate capacitor 2 under vibration, a temperature compensation mechanism is introduced: a temperature sensor is integrated near the capacitor to collect ambient temperature data in real time, and a software algorithm is used to correct frequency changes based on temperature; the resonant circuit design is optimized by replacing ordinary quartz crystals with a temperature-controlled crystal oscillator, stabilizing the resonant temperature at 25℃±0.5℃, reducing the impact of temperature on the oscillation frequency; and the plate material is upgraded by using ceramic or quartz materials with low coefficients of thermal expansion to make the plates, reducing the impact of mechanical deformation on the spacing.

[0061] In terms of high-temperature resistance, dustproofing, waterproofing, and freeze protection, this device is fully sealed. The solar panel 11 is protected by sealed, light-transmitting glass, and the outer casing is made of materials resistant to high temperatures, freezes, water, and dust. To address the potential failure of existing sealing designs in environments such as heavy rain and salt spray, an IP68+ protection upgrade is implemented: the outer casing seals are made of fluororubber, and hot-melt adhesive is added to the seams for sealing. It remains waterproof after immersion in 1 meter of water for 24 hours, with a 5% water leakage rate. NaCl solution salt spray test showed no corrosion for 1000 hours; Anti-icing design: The solar panel surface is coated with a superhydrophobic nano-coating with a contact angle >150°, and with built-in heating wire, it automatically starts heating below -10℃ to prevent snow and ice from blocking it; For the data acquisition end where long-term bridge vibration may cause internal components to loosen, a flexible vibration damping structure is adopted: the flat plate capacitor 2 and the mass block 1 are fixed by silicone rubber vibration damping columns, and the natural frequency is designed to be 50Hz, avoiding the main vibration frequency band of the bridge 1-20Hz, reducing resonance damage; Encapsulation reinforcement: The circuit board is fully encapsulated with polyurethane glue, and the gaps between components are filled with thermally conductive silicone, improving the vibration resistance level to 50g (10-2000Hz).

[0062] In terms of power supply, this device uses dual lithium battery packs 7. The lithium batteries are sealed and waterproof, and replaceable. Solar panels charge them under sunlight. The device is remotely controlled from the server, which can monitor its current operating status and set the daily operating time. On cloudy days, solar charging efficiency is low, resulting in insufficient lithium battery life. The following optimization methods are adopted: Integrated MPPT charging controller: A maximum power point tracking module (MPPT) is added between the solar panel 11 and the dual lithium battery packs 7, increasing the charging efficiency from 70%-80% of traditional PWM to over 95%, and shortening charging time on cloudy days to 5-6 hours; Dual energy complementary design: A small wind turbine, such as a micro-wind-starting turbine generator, is added to complement the solar panel 11, providing an additional 10-15W of power during continuous cloudy or rainy weather; Battery thermal management system: A heating film and heat sink are embedded in the lithium battery pack, and a temperature control chip maintains the battery temperature at 20-30℃, improving discharge efficiency by 30% in low-temperature environments of -20℃. The high power consumption and short standby time of the data acquisition terminal during continuous operation are addressed through a sleep-wake mechanism: it is normally in a low-power sleep state with power consumption <1mW. When the bridge vibration exceeds a threshold, such as 0.1g, it is triggered to wake up by the accelerometer, reducing unnecessary power consumption. Dynamic sampling frequency adjustment: the sampling frequency is automatically adjusted according to the vibration intensity. When there are no vehicles passing, it samples at a low frequency of 10Hz; when vehicles pass, it samples at a high frequency of 1000Hz, reducing the amount of data while ensuring the capture of key signals.

[0063] Regarding cost and scalability optimization, an integrated and mass-production design is adopted, specifically: SOC chip integration: The quartz crystal resonant circuit component 5, microwave transmitter and receiver, and data processing component 10 are integrated into a single SOC chip such as STM32WBA, reducing the number of components by 30% and lowering costs by 25%; Standardized modules: The data receiving and processing end adopts a universal motherboard design, requiring only the antenna and power module to adapt to different bridge scenarios, reducing mold costs by 40% during mass production. Regarding data value mining, the problem of underutilized raw data and lack of predictive maintenance functions is addressed: AI damage prediction model: An LSTM neural network is deployed on the server side, based on historical vibration data, displacement data, and environmental data (temperature, humidity, traffic flow) to predict bridge structural damage trends and provide early warnings of potential risks (such as bearing loosening and concrete crack propagation) 1-3 months in advance; Digital twin integration: Monitoring data is connected to the bridge digital twin platform to map structural deformation in real time, assisting maintenance personnel in making visual decisions.

[0064] Comparison of optimization effects

[0065] Optimization direction Existing scheme indicators Optimized indicators Increase Distance measurement accuracy 1m (coarse measurement) / 1mm (precise measurement) 0.5m (coarse measurement) / 0.1mm (precise measurement) 10 times Charging efficiency 10 hours to fill on a cloudy day On a cloudy day, it takes 5-6 hours to fully charge. 50%-100% Data transmission interruption rate 5% (remote areas) ＜0.1% 98% reduction Installation time 2 hours / point 30 minutes / point 75% shortened Fault response time Discovered through manual inspection (24+ hours) Real-time alerts (<5 minutes) Near real-time

[0066] Through the above optimizations, the monitoring system can achieve comprehensive improvements in accuracy, reliability, operation and maintenance costs, and intelligence level, making it more suitable for the engineering needs of long-term health monitoring of bridges.

[0067] The data acquisition end and the data receiving and processing end are powered by dual battery packs. When replacing batteries, both sets of batteries cannot be removed at the same time. Remove one set first and then remove the other set to ensure that the device is powered on continuously. The data acquisition end can be fixed to the side of the beam or the wall of the pier using adhesive or screws.

[0068] Please see Figure 4 , Figure 4 Based on the principle of microwave differential frequency ranging, three sets of sine wave patterns are selected in the figure. One is y=sin(x), with a carrier wave length of 1000m in the air. The other is y=sin(0.9x). If the distance from the data acquisition end to the data receiving end is 566m, the phase difference between the two wavelengths is 100m at 1000m. When the distance reaches 10m, the phase difference is 1m relative to the wavelength difference. At 566m, the phase difference between the two waves is 5.66m wavelength. The phase measuring device can be accurate to 0.001 phase difference. In addition, for the carrier wave y=sin(0.99x), the phase difference between the two waves is 10m relative to the wavelength difference for every 1000m. The distance is then calculated by measuring the phase difference. This device calculates distance based on the phase difference of different carriers and transmits carriers in time intervals. That is, the data acquisition end transmits carriers synchronously in several sets of carriers, i.e., y=Asin(x), y=Asin(0.9x), y=Asin(0.99x), where A is the amplitude, and transmits carriers when x=0. This continues until the longest carrier ends after two full cycles. Then, several sets of carriers are synchronously transmitted at intervals of two full cycles to allow the data receiving and processing end to identify the zero-phase start time.

[0069] Appendix Figure 3 One segment of the carrier wave consists of 5 long carrier cycles. In practice, a quartz crystal oscillator operates continuously, but the ranging signal is modulated into the microwave at the beginning of each integer cycle when the phase is zero. All data acquisition terminals transmit microwave signals on different channels, and the data receiving and processing terminals receive microwave signals from all data acquisition terminals on multiple channels. The distance between each data acquisition terminal is calculated by adding the three-dimensional coordinates of the data receiving and processing terminals to the distance space using post-intersection.

[0070] Existing carrier wavelength combinations suffer from phase ambiguity issues at millimeter-level accuracy. To address this, multi-carrier fusion ranging is employed: short-wavelength carriers, such as 10m and 1m, are added, using a layered ranging strategy of "coarse measurement with long wavelength + fine measurement with short wavelength," as shown in the table below.

[0071] carrier wavelength effect Precision range 1000m Coarse distance range ±10m 100m Eliminating long-wavelength phase ambiguity ±1m 1m Millimeter-level precision measurement ±1mm

[0072] Phase difference calculation optimization: The Fast Fourier Transform (FFT) algorithm is used to replace the traditional phase measurement device. The phase difference is directly calculated through spectrum analysis, improving the accuracy to 0.0001 phase difference (corresponding to 0.1mm distance error).

[0073] Working principle: The data acquisition end monitors bridge vibration through an acceleration sensing unit composed of a parallel plate capacitor 2 and a metal mass block 1. When vehicle loads cause bridge structural vibration, the inertia of the mass block 1 causes a change in the spacing between the capacitor plates of the parallel plate capacitor 2, resulting in a change in capacitance. This change is converted into a high-frequency electrical signal by a quartz crystal resonant circuit component 5, and a PT100 temperature sensor and a temperature-controlled crystal oscillator are integrated to compensate for temperature drift in real time, ensuring measurement stability. The vibration signal is modulated with a microwave carrier and then transmitted to the receiving end by a microwave signal antenna.

[0074] The system employs a three-level carrier combination with wavelengths of 1000m, 100m, and 1m for spatial positioning. The 1000m long wave is used for coarse distance measurement, the 100m medium wave eliminates phase ambiguity, and the 1m short wave, combined with an FFT algorithm, achieves millimeter-level precision measurement. Frequency hopping spread spectrum (FHSS) technology is used to achieve pseudo-random hopping in the 2.4-2.5GHz frequency band, effectively avoiding electromagnetic interference. The data acquisition end integrates an IMU inertial unit and a barometric pressure sensor, and the three-dimensional coordinates are automatically calibrated using a Kalman filter algorithm.

[0075] When there are no vehicles passing by, the system samples at a low frequency of 10Hz and goes into sleep mode; when the vibration exceeds the 0.1g threshold, it switches to a high frequency of 1000Hz for sampling. The data receiving and processing end acquires the signal through a multi-channel microwave receiving module, uses the FFT algorithm to analyze the phase difference and calculate the displacement. The edge computing unit compresses the vibration signal after wavelet denoising and then transmits it to the cloud server through multiple redundant networks of 4G / 5G / LoRa / NB-IoT, with network priority automatically switching in the order of 5G>4G>LoRa>NB-IoT.

[0076] The server uses an LSTM neural network to build an AI damage prediction model, integrating historical vibration data, displacement, and environmental parameters to predict risks such as support loosening and concrete cracking 1-3 months in advance. The results are integrated into a digital twin platform to map structural deformation in real time and trigger visual early warnings. Simultaneously, the system remotely monitors equipment status: it automatically sends SMS alarms when the battery level drops below 20%, and the battery thermal management system maintains a constant temperature of 20-30℃ through heating films and heat sinks, ensuring stability under extreme operating conditions.

[0077] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0078] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A vibration displacement sensor system for bridge operation monitoring, comprising a data acquisition end and a data receiving and processing end, characterized in that, The data acquisition terminal is fixed to the side of the bridge pier, abutment, or beam. The data acquisition terminal includes a capacitive accelerometer, a microwave signal antenna (6), a dual lithium battery pack (7), and a solar panel (11). The capacitive accelerometer is composed of a plate capacitor (2), a metal mass block (1), and a quartz crystal resonant circuit assembly (5). The mass block (1) is used to change the spacing between the plates of the plate capacitor (2) and thus modulate the high-frequency oscillation signal through the quartz crystal resonant circuit assembly (5). The microwave signal antenna (6) is used to transmit frequency-modulated microwave signals. The dual lithium battery pack (7) and the solar panel (11) are used to power the device and are protected by a sealed transparent glass. The data receiving and processing terminal is installed at stable positions on both sides of the bridge and includes a multi-channel microwave receiving module, an edge computing unit, a 4G / 5G / LoRa / NB-IoT multi-network transmission module, and a phase difference calculation module. The multi-channel microwave receiving module is used to receive carrier signals, the edge computing unit is used to perform wavelet denoising and FFT analysis, the 4G / 5G / LoRa / NB-IoT multi-network transmission module is used for signal transmission, and its priority is 5G>4G>LoRa>NB-IoT. The phase difference calculation module is configured to analyze the carrier phase difference of the wavelength based on the FFT algorithm. The system employs a multi-carrier fusion ranging strategy, which includes a combination of carrier signals with wavelengths of 1000m, 100m, and 1m, and uses frequency hopping spread spectrum (FHSS) technology to perform anti-interference ranging.

2. The vibration displacement sensor system for bridge operation monitoring according to claim 1, characterized in that, The capacitive accelerometer further includes: The PT100 temperature sensor is used to collect ambient temperature data in real time. Oven-controlled crystal oscillators (OCXO) are used to maintain a resonant temperature of 25℃ ± 0.5℃. Low coefficient of thermal expansion ceramic electrode, with a coefficient of thermal expansion ≤ 0.6 × 10⁻⁶. -6 / ℃; The data acquisition terminal also includes a silicone rubber shock-absorbing column fixing structure with a natural frequency of 50Hz.

3. The vibration displacement sensor system for bridge operation monitoring according to claim 2, characterized in that, The power system of the data receiving and processing terminal includes an MPPT charging controller, a wind turbine generator for micro-wind starting, and a battery thermal management system. The MPPT charging controller has a charging efficiency of ≥95% and a charging time of ≤6 hours on cloudy days. The output power of the wind turbine generator for micro-wind starting is 10-15W. The battery thermal management system has an embedded heating film and heat sink, with a temperature control range of 20-30℃.

4. The vibration displacement sensor system for bridge operation monitoring according to claim 3, characterized in that, The data acquisition terminal's housing adopts an IP68+ sealed protection design, using fluororubber seals and hot melt adhesive potting, and is immersed in 1 meter of water for 24 hours and tested for 1000 hours in 5% NaCl salt spray; the surface is coated with a superhydrophobic nano-coating, and the heating wire automatically starts at -10℃; a double-layer metal shielding shell is constructed using an inner copper mesh and an outer aluminum alloy, with a grounding resistance of <1Ω.

5. A vibration displacement sensor system for bridge operation monitoring according to claim 4, characterized in that, The phase difference calculation module adopts a layered ranging strategy, specifically: A 1000m wavelength carrier wave is used for coarse measurements, with an accuracy of ±10m. A 100m wavelength carrier wave is used to eliminate phase ambiguity with an accuracy of ±1m; A 1m wavelength carrier combined with an FFT algorithm is used for precision measurement with an accuracy of ±0.1mm.

6. A vibration displacement sensor system for bridge operation monitoring according to claim 5, characterized in that, The data acquisition terminal also includes a spatial positioning module and a magnetic quick-installation structure. The spatial positioning module integrates an IMU inertial measurement unit and a barometric pressure sensor, and calibrates the coordinates using a Kalman filter algorithm. The magnetic quick-installation structure uses neodymium iron boron magnets to attract a pre-embedded stainless steel base, and the installation time is ≤30 seconds.

7. A method of using a vibration displacement sensor system for bridge operation monitoring, implemented based on the vibration displacement sensor system for bridge operation monitoring according to any one of claims 1-6, characterized in that, Includes the following steps: Step 1: Multi-source data acquisition: The data acquisition end monitors the vibration signal in real time through a capacitive accelerometer and simultaneously transmits multi-carrier microwave signals; Step 2, frequency difference ranging calculation: The data receiving and processing end uses the FFT algorithm to analyze the carrier phase difference and calculates the three-dimensional distance by combining the 1000m / 100m / 1m wavelength combination; Step 3: Intelligent data processing: The edge computing unit performs wavelet denoising and FFT analysis on the vibration signal, and after compression, transmits it to the server through multiple network redundancy. Step 4: Structural health assessment: The server builds an AI damage prediction model based on an LSTM neural network, and combines it with a digital twin platform to perform real-time mapping and early warning of structural deformation.

8. The method of using a vibration displacement sensor system for bridge operation monitoring according to claim 6, characterized in that, The multi-source data acquisition phase employs a dynamic power consumption control strategy: When there are no vehicles passing by, it samples at a low frequency of 10Hz and enters sleep mode, with power consumption <1mW; When the vibration threshold is triggered, the system switches to 1000Hz high-frequency sampling and wakes up.

9. The method of using a vibration displacement sensor system for bridge operation monitoring according to claim 7, characterized in that, The installation and debugging steps for the data acquisition terminal and the data receiving and processing terminal include: The data receiving and processing end measures three-dimensional coordinates using a total station / GPS and calibrates the instrument height by combining the length of the support rod. The data acquisition end is quickly installed using a magnetic structure and automatically matches the ranging data from the receiver end through a self-calibration module. The server monitors parameters such as battery level and temperature of each device in real time, and triggers an SMS alert when the battery level is less than 20%.

10. The method of using a vibration displacement sensor system for bridge operation monitoring according to claim 8, characterized in that, The AI ​​damage prediction model is based on historical vibration data, displacement data and environmental parameters. It predicts potential risks 1-3 months in advance and connects to a digital twin platform to perform visual early warning. The environmental parameters include, but are not limited to, temperature, humidity and traffic flow. Potential risks include, but are not limited to, bridge bearing loosening and concrete cracking.

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