Distributed optical fiber strain sensing detection system for bridge engineering dynamic and static load test

Abstract

The invention relates to the technical field of bridge engineering detection, in particular to a distributed optical fiber strain sensing detection system for a bridge engineering dynamic and static load test, and the system comprises a distributed optical fiber strain sensing module which is used for obtaining the strain information of different positions of a bridge; the dynamic and static load signal acquisition and conversion module is used for converting the strain signal into a strain electric signal suitable for transmission and processing; the temperature compensation module is used for carrying out temperature compensation on the strain signal according to the change of the collected environment temperature; the data processing and analyzing module is used for processing and analyzing the strain electric signal subjected to temperature compensation so as to obtain the strain distribution condition and related parameters of the bridge structure under the action of dynamic and static loads; and the monitoring and early warning module is used for monitoring the state of the bridge in real time according to the result obtained by the data processing and analyzing module and sending out an early warning signal when the strain of the bridge is abnormal. The problem that in the prior art, comprehensive, high-precision and real-time dynamic and static load strain monitoring cannot be carried out on bridge engineering is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bridge engineering detection, and particularly relates to a distributed optical fiber strain sensing detection system for bridge engineering dynamic and static load test. BACKGROUND

[0002] In the field of bridge engineering, accurately monitoring the strain of the bridge structure under the action of dynamic and static load is crucial for evaluating the structural health condition, bearing capacity and safety of the bridge. Currently, the commonly used strain measurement technologies mainly include electrical measurement and optical fiber sensing measurement.

[0003] Based on traditional electrical measurement methods such as resistance strain gauges and string gauges, only single-point and local measurement of the structure can be achieved, and it is difficult to form a distributed sensing network. This makes it necessary to arrange a large number of sensors when comprehensively monitoring large bridges, which is not only costly but also extremely complex to install and maintain. Moreover, due to the sparseness of the measurement points, the overall strain distribution of the bridge cannot be accurately reflected.

[0004] Currently, long-distance optical fiber sensing technologies mainly include Brillouin optical time domain reflectance / analysis (BOTDR / A) technology and conventional fiber Bragg grating sensing technology. Although the BOTDR / A technology can achieve distributed sensing of the structure, its measurement accuracy is poor, the sampling frequency is extremely low, and it can only be used for static or quasi-static measurement, which cannot meet the real-time monitoring requirements of the strain changes of the bridge under dynamic load (such as vehicle driving, earthquakes, etc.). Moreover, the strain of structures without main reinforcement (such as plain concrete structures, pavement base layers, asphalt layers, etc.) cannot be directly measured by this technology. The conventional fiber Bragg grating sensing technology usually has less than 20 multiplexed sensors per optical fiber, which can only form a small-scale sensing network and cannot achieve comprehensive coverage monitoring of large bridges. Moreover, each fiber Bragg grating sensor needs to be independently packaged and installed, further increasing the construction difficulty and cost.

[0005] In summary, the existing technologies have many deficiencies in the strain monitoring of bridge engineering dynamic and static load test, and cannot meet the requirements of comprehensive, high-precision and real-time dynamic and static load strain monitoring of bridges. Therefore, it is of great practical significance to develop a distributed optical fiber strain sensing detection system that can solve the above problems. SUMMARY

[0006] In order to overcome the above technical defects, the purpose of the present application is to provide a distributed optical fiber strain sensing detection system for bridge engineering dynamic and static load test, so as to solve the problem that the existing technologies cannot comprehensively, accurately and in real time monitor the dynamic and static load strain of bridge engineering.

[0007] The present application discloses a distributed optical fiber strain sensing detection system for bridge engineering dynamic and static load test, comprising:

[0008] The distributed optical fiber strain sensing module comprises a plurality of sensing optical fibers, and a plurality of strain sensing units are arranged on each sensing optical fiber at intervals, for being distributed on the bridge structure and acquiring strain information of different positions of the bridge;

[0009] The dynamic and static load signal acquisition and conversion module is connected with the distributed optical fiber strain sensing module, and is used for acquiring strain signals of the strain sensing units and converting the strain signals into strain electric signals suitable for transmission and processing.

[0010] The temperature compensation module is connected with the distributed optical fiber strain sensing module and the dynamic and static load signal acquisition and conversion module, and is used for monitoring the ambient temperature around the sensing optical fiber in real time and compensating the strain signals according to the change of the acquired ambient temperature.

[0011] The data processing and analysis module is connected with the dynamic and static load signal acquisition and conversion module and the temperature compensation module, and is used for processing and analyzing the strain electric signals after temperature compensation, so as to acquire the strain distribution and related parameters of the bridge structure under the action of dynamic and static loads.

[0012] The monitoring and early warning module is connected with the data processing and analysis module, and is used for monitoring the bridge state in real time according to the result obtained by the data processing and analysis module, and sending an early warning signal when the strain of the bridge is abnormal.

[0013] Preferably, the strain sensing unit is a fiber Bragg grating (FBG), and the change amount of the center wavelength of the fiber Bragg grating is According to the calculation formula The strain amount is calculated , wherein is the initial center wavelength of the fiber Bragg grating, is the effective elasto-optical coefficient.

[0014] Preferably, the sensing optical fiber is a multimode optical fiber, and the core diameter of the multimode optical fiber ranges from 50 ~100 .

[0015] Preferably, the dynamic and static load signal acquisition and conversion module comprises a signal amplifier, which is used for amplifying the strain signals output by the strain sensing units, and the amplification multiple A ranges from 10 to 1000, and the relationship between the signal amplitude after amplification and the signal amplitude before amplification is . .

[0016] Preferably, the dynamic and static load signal acquisition and conversion module further comprises an analog-to-digital converter, and the resolution of the analog-to-digital converter ranges from 12 to 24 bits.

[0017] ​Preferably, the temperature compensation module includes a distributed optical fiber temperature sensor, which is laid parallel to the sensing optical fiber to measure the ambient temperature around the sensing optical fiber in real time.

[0018] Preferably, the temperature compensation module further includes a temperature compensation algorithm unit. This unit performs temperature compensation on the acquired strain signal based on the ambient temperature measured by the distributed fiber optic temperature sensor and a pre-established temperature-strain relationship model. The temperature-strain relationship model is as follows: ,in, The additional strain is caused by temperature, where T is the actual measured temperature. For reference temperature, and This is a coefficient related to the sensing fiber material.

[0019] Preferably, the data processing and analysis module includes a Fast Fourier Transform (FFT) unit for performing spectral analysis on the acquired strain signals to obtain the vibration frequency information of the bridge under dynamic load. Through analysis of the vibration frequency f, the vibration frequency is calculated according to the formula... Estimate the elastic modulus E of the bridge structure, where m is the mass per unit length of the bridge structure, L is the calculated span of the bridge, and I is the moment of inertia of the bridge section.

[0020] Preferably, the data processing and analysis module further includes a finite element analysis unit, which is used to compare and analyze the strain data obtained by the distributed fiber optic strain sensing module, the dynamic and static load signal acquisition and conversion module, and the temperature compensation module with the pre-established bridge finite element model, so as to evaluate the difference between the actual stress state and the theoretical design state of the bridge structure.

[0021] Preferably, the monitoring and early warning module includes an audible and visual alarm unit. When the bridge strain value obtained by the data processing and analysis module exceeds a preset safety threshold, the audible and visual alarm unit emits an audible and visual alarm signal. At the same time, the monitoring and early warning module also includes a remote communication unit for transmitting alarm information and related strain data to the monitoring center.

[0022] Compared with existing technologies, the above technical solution has the following advantages:

[0023] 1. This invention, through a distributed optical fiber strain sensing module, can comprehensively and distributedly acquire strain information on bridge structures, solving the problem that traditional electrical measurement methods have sparse measuring points and cannot fully reflect the strain distribution of bridges. At the same time, compared with conventional fiber Bragg grating sensing technology, it can realize large-scale sensor network deployment and improve the comprehensiveness of monitoring.

[0024] 2. The dynamic and static load signal acquisition and conversion module can effectively acquire and convert the weak signal output by the strain sensing unit, which is convenient for subsequent processing. By setting an appropriate amplification factor and analog-to-digital converter resolution, the accuracy of signal acquisition is guaranteed.

[0025] 3. The temperature compensation module can monitor the ambient temperature in real time and perform temperature compensation on the collected strain signal, eliminating the interference of temperature changes on the measurement results, improving the accuracy of strain measurement, and solving the problem of temperature factors affecting the accuracy of measurement in the existing technology.

[0026] 4. The data processing and analysis module uses various analysis methods, such as the fast Fourier transform unit to perform spectrum analysis to obtain vibration frequency information and estimate elastic modulus, and the finite element analysis unit to compare actual strain data with theoretical models, which can deeply evaluate the stress state and performance of bridge structures and provide a more comprehensive and accurate basis for bridge safety assessment.

[0027] 5. The monitoring and early warning module can monitor the bridge status in real time and issue early warning signals in a timely manner when abnormal situations occur. At the same time, it can remotely transmit alarm information and data, which facilitates timely measures to ensure bridge safety and improves the timeliness and safety of bridge monitoring. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the distributed optical fiber strain sensing detection system for dynamic and static load testing of bridge engineering according to the present invention. Detailed Implementation

[0029] The advantages of the present invention will be further illustrated below with reference to the accompanying drawings and specific embodiments.

[0030] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0031] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0032] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this disclosure, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0033] In the description of this invention, it should be understood that the terms "longitudinal", "lateral", "up", "down", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0034] In the description of this invention, unless otherwise specified and limited, it should be noted that the terms "installation", "connection" and "linking" should be interpreted broadly. For example, they can refer to mechanical or electrical connections, or internal connections between two components. They can be direct connections or indirect connections through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0035] In the following description, suffixes such as "module," "part," or "unit" used to denote elements are used only for the convenience of the description of the invention and have no specific meaning in themselves. Therefore, "module" and "part" can be used interchangeably.

[0036] See Figure 1 As shown in this embodiment, a distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering will be described in detail as follows:

[0037] The distributed fiber optic strain sensing module, serving as the "sensing front end" of a "distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering," primarily functions to directly acquire strain information from the bridge structure. This "strain information" refers to data related to the degree of deformation at different locations of the bridge structure under static loads (such as the bridge's own weight and the weight of the bridge deck pavement) and dynamic loads (such as moving vehicles, wind, and earthquakes), including the magnitude, direction, and distribution range of the strain. This distributed fiber optic strain sensing module comprises multiple sensing fibers, with multiple strain sensing units spaced apart on these fibers being the key components for acquiring strain information. These strain sensing units are closely fitted to the bridge structure. When the bridge deforms, they cause corresponding physical changes in the strain sensing units (such as shifts in the center wavelength of the fiber Bragg grating and changes in fiber length), thereby converting the bridge's mechanical deformation into detectable optical signals to capture strain information at different locations on the bridge. This distributed arrangement allows strain sensing units to cover key stress-bearing parts of the bridge, such as the main beam, the connection between the pier and the main beam, and the supports. It breaks through the limitations of single-point measurement in traditional electrical measurement methods and overcomes the shortcomings of conventional fiber Bragg grating sensing technology in terms of the limited number of multiple sensors. It enables the collection of strain information from a wide range of bridges and multiple measuring points.

[0038] The dynamic and static load signal acquisition and conversion module acts as a "signal processing relay station" in the "Distributed Fiber Optic Strain Sensing Detection System for Dynamic and Static Load Testing of Bridge Engineering." Its core task is to process the signals containing strain information acquired by the distributed fiber optic strain sensing module. Since the strain-carrying signals output by the strain sensing unit are typically very weak (e.g., minute changes in optical signals), they are difficult to transmit directly over long distances and undergo subsequent data processing. This module first acquires these weak signals containing strain information using a dedicated signal acquisition component (e.g., a photodetector), and then converts them into electrical signals suitable for subsequent transmission and processing through a signal conversion circuit. These electrical signals still retain the original strain information; only the signal form has changed from optical to electrical, allowing subsequent modules (such as the temperature compensation module and the data processing and analysis module) to further process the strain information. This process ensures that the original strain signal can be effectively captured and converted into a form recognizable by the "Distributed Fiber Optic Strain Sensing Detection System for Dynamic and Static Load Testing of Bridge Engineering."

[0039] The temperature compensation module is a crucial corrector in the "Distributed Fiber Optic Strain Sensing System for Dynamic and Static Load Testing of Bridge Engineering," ensuring measurement accuracy. Its function is to eliminate the influence of temperature on the accuracy of strain information. Changes in ambient temperature cause thermal expansion and contraction of the sensing fiber, leading to additional physical changes in the strain sensing unit. These changes can be misinterpreted as strain information generated by bridge structural deformation, interfering with the measurement of the true strain of the bridge. This temperature compensation module monitors the ambient temperature distribution around the sensing fiber in real time using distributed fiber optic temperature sensors. Then, the temperature compensation algorithm unit corrects the electrical signal containing strain information transmitted from the dynamic and static load signal acquisition and conversion module based on the temperature distribution information and a pre-established temperature-strain relationship model (i.e., the quantification relationship of the additional strain generated by temperature changes on the strain sensing unit). Specifically, it subtracts the additional strain information caused by temperature changes from the total strain information carried by the electrical signal, thus obtaining the true strain information generated only by the bridge load, ensuring the accuracy of strain measurement.

[0040] The data processing and analysis module, serving as the "data hub" of the "distributed fiber optic strain sensing and detection system for dynamic and static load testing of bridge engineering," is responsible for in-depth processing and analysis of the strain electrical signals, which contain real strain information after temperature compensation. This module uses specialized data processing algorithms (such as filtering algorithms to remove signal noise and signal demodulation algorithms to extract strain characteristics) to accurately extract the strain values ​​(i.e., specific strain magnitude data) of various parts of the bridge from the electrical signals. Furthermore, it presents the strain distribution of the bridge through data visualization techniques (such as plotting strain cloud maps and strain curves). Simultaneously, it performs statistical analysis on the extracted strain information to obtain relevant parameters, such as the maximum and minimum strain values ​​at different locations, the strain variation trend over time, and the strain gradient. These analytical results provide a deeper understanding of the actual stress state of the bridge under dynamic and static loads, allowing for the assessment of whether there are problems such as local stress concentration or excessive deformation in the bridge structure. This provides detailed and accurate strain information to support the evaluation of the bridge structure's load-bearing capacity, health status, and safety.

[0041] The monitoring and early warning module acts as a "safety guardian" in the "Distributed Fiber Optic Strain Sensing System for Dynamic and Static Load Testing of Bridge Engineering." Its operation is based on strain information output from the data processing and analysis module. This module pre-stores safe strain thresholds for various parts of the bridge under different load conditions (these thresholds are determined according to bridge design standards, material properties, and safety specifications) and receives real-time information from the data processing and analysis module, including strain values ​​and strain distribution at various bridge locations. By comparing and analyzing the real-time strain information with the preset strain thresholds, the module tracks the bridge's condition in real time. When the strain value at a certain location exceeds the corresponding strain threshold (i.e., abnormal strain occurs), the monitoring and early warning module immediately activates the audible and visual alarm unit, emitting a loud alarm sound and flashing warning lights to alert on-site personnel to potential safety risks to the bridge. Simultaneously, the remote communication unit transmits the alarm information (such as the location and time of the abnormal strain) and related detailed strain data (such as the real-time strain value at that location and strain change curve) remotely to the monitoring center via a wireless network. This allows the monitoring center staff to promptly grasp the abnormal situation of the bridge and take appropriate measures (such as suspending the test, conducting an emergency inspection of the bridge, and restricting traffic) to ensure the safety of the bridge.

[0042] The relationship and collaborative workflow between the modules are as follows: In "A Distributed Fiber Optic Strain Sensing Detection System for Dynamic and Static Load Testing of Bridge Engineering", the modules are connected through signal transmission lines (such as fiber optic cables, shielded cables, etc.) or data interfaces (such as Ethernet interfaces, USB interfaces, etc.) to form an organic whole. The collaborative workflow is as follows:

[0043] The strain sensing unit of the distributed fiber optic strain sensing module senses the strain changes of the bridge under dynamic and static loads, generates an optical signal containing strain information, and transmits this signal through the sensing fiber to the dynamic and static load signal acquisition and conversion module. The dynamic and static load signal acquisition and conversion module acquires the optical signal, converts it into an electrical signal containing strain information, and then sends the electrical signal to the temperature compensation module and the data processing and analysis module. The temperature compensation module performs temperature compensation processing on the received electrical signal based on real-time monitored temperature information, obtaining an electrical signal that eliminates the influence of temperature and contains true strain information, and feeds it back to the data processing and analysis module. The data processing and analysis module processes and analyzes the received signal, extracting information such as strain values ​​and strain distribution at various parts of the bridge, and transmits the results to the monitoring and early warning module. The monitoring and early warning module compares the received results with preset thresholds and executes corresponding monitoring and early warning operations.

[0044] This embodiment will again describe in detail the strain sensing unit mentioned in the above embodiments. The strain sensing unit is a fiber Bragg grating. A fiber Bragg grating is a structure in which a periodic refractive index modulation is written into the core of an optical fiber through ultraviolet light interference. Its core feature is that "the center wavelength has a linear relationship with strain"—when the bridge structure at the location of the fiber Bragg grating deforms, the fiber Bragg grating will be stretched or compressed along with the structure, causing a change in its internal periodic refractive index structure, which in turn causes a shift in the center wavelength. The greater the strain, the greater the change in the center wavelength. The larger the strain, the more linear this relationship remains within a certain strain range. Based on this characteristic, the formula for calculating the strain is given in this embodiment. ,in The change in the center wavelength of the fiber Bragg grating (unit: nm). The initial center wavelength of the fiber Bragg grating (i.e., the center wavelength under strain, unit: nm); The effective photoelastic coefficient (a dimensionless constant determined by the fiber material); The dependent variable (dimensionless, usually expressed as microstrain) (Unit: ). This formula allows us to calculate the result from a given... , and actual measurement In the case of deriving the dependent variable value , This enables quantitative measurement of bridge strain.

[0045] This embodiment focuses on the core component of the "distributed fiber optic strain sensing module" described in the previous embodiments. In those embodiments, the module's function was to "acquire strain information at different locations on the bridge." This embodiment specifies a concrete solution for achieving this function—sensing strain through wavelength changes in a fiber Bragg grating and calculating the specific strain value using a formula. This concretization transforms "strain information" from an abstract concept into a quantifiable physical quantity, providing a clear input for subsequent modules (such as the dynamic and static load signal acquisition and conversion module, and the data processing and analysis module). For example, the dynamic and static load signal acquisition and conversion module can design an acquisition circuit based on the optical signal characteristics of the fiber Bragg grating (such as center wavelength changes), and the data processing and analysis module can directly perform distribution analysis based on the calculated strain value, thereby improving the measurement accuracy and reliability of the entire "distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering."

[0046] For the calculation formula in this embodiment The physical significance lies in establishing a direct correlation between the optical properties (center wavelength variation) of fiber Bragg gratings and the mechanical properties (strain) of bridge structures:

[0047] It is a physical quantity that can be directly measured by optical detection equipment (such as spectrometers and fiber Bragg grating demodulators). The right side of the equation is an expression related to strain. This calculation formula realizes the conversion of "optical signal → mechanical signal".

[0048] In the calculation formula and All are known constants ( It can be calibrated at the factory. Determined by the optical fiber material, such as quartz optical fiber. (Approximately 0.22), therefore only measurement is needed. This allows for rapid calculation of strain values, simplifying the measurement process.

[0049] The linear relationship ensures that within a certain strain range (typically -2000), +2000 The measurement results are accurate and stable, requiring no complex nonlinear correction, making them suitable for rapid application in engineering fields.

[0050] To facilitate understanding, this embodiment will further explain the application of this calculation formula in detail by way of an example, assuming the initial center wavelength of the fiber Bragg grating. =1550nm, effective elastic coefficient =0.22, measured center wavelength change =0.01nm, then (i.e., 8.3) This example visually demonstrates how stretching a fiber Bragg grating causes a change in its center wavelength. After measuring the change using a regulator, the strain value of the main beam can be quickly obtained using a calculation formula, providing data support for assessing the stress state of a bridge under dynamic loads.

[0051] In this embodiment, the sensing optical fiber described in the above embodiments will be described in more detail again, specifying that it uses multimode optical fiber and the diameter range of the fiber core.

[0052] The above embodiments described in detail that the strain sensing unit is a fiber Bragg grating, and these fiber Bragg gratings need to be integrated into the sensing pipeline for distributed arrangement. This embodiment describes the type and parameters (core diameter) of the sensing pipeline carrying the fiber Bragg gratings to ensure that the signal transmission between the fiber Bragg gratings meets the stability and anti-interference requirements of the detection system.

[0053] The sensing fiber described in the above embodiments is a multimode fiber, and the core diameter of the multimode fiber ranges from 50. ~100 The core difference between multimode fiber and single-mode fiber lies in the larger core diameter, which allows different modes of optical signals to be transmitted within the core. In this detection system, the role of multimode fiber is to carry multiple fiber Bragg grating strain sensing units and to achieve stable transmission of the reflected signals from each fiber Bragg grating.

[0054] The core diameter range is 50. ~100 The reason is that when the core diameter is too small (e.g., less than 50 mm), Optical signals are susceptible to damage during transmission due to factors such as fiber bending and vibration, leading to increased signal attenuation. Furthermore, reflected signals from multiple fiber Bragg gratings may interfere with each other due to mode competition. When the fiber core diameter is too large (e.g., greater than 100 mm), the signal attenuation is further exacerbated. Although the signal capacity has increased, the flexibility of the optical fiber has decreased, making it unsuitable for laying on the complex surfaces of bridge structures. It may also exacerbate optical signal dispersion, affecting signal transmission quality. Therefore, 50 ~100 The fiber core diameter range is the optimal choice that balances signal transmission stability, anti-interference, and ease of construction.

[0055] For ease of understanding, this embodiment will be described and explained again by way of a specific example. In this embodiment, a fiber core diameter of 62.5 mm is selected. Multimode fiber is used as the sensing fiber, and multiple fiber Bragg gratings are etched onto it as strain sensing units. Its advantage lies in its 62.5... At 50 ~100 Within the optimal range, when the bridge is subjected to dynamic loads (such as heavy vehicles passing over it), the wavelength signals reflected by each fiber Bragg grating propagate through the optical fiber without significant crosstalk due to the moderate fiber core diameter. For example, if the center wavelengths of two adjacent fiber Bragg gratings are 1550nm and 1555nm respectively, their reflected signals will be within the range of 62.5nm. After transmission through the fiber core, the signal strength attenuation is only 3%, and there is no wavelength overlap. The dynamic and static load signal acquisition and conversion module can accurately distinguish and acquire these two signals, and calculate the strain values ​​at the corresponding locations. The optical fiber selected in this embodiment has good flexibility and can be laid along the surfaces of complex structures such as the arched supports and stay cables of bridges, ensuring a tight fit between the fiber Bragg grating and the bridge structure, accurately acquiring strain information. Furthermore, the large core (such as 125)... The optical fiber may be too rigid to fit properly, resulting in distorted strain information acquisition.

[0056] It should be noted that the dynamic and static load signal acquisition and conversion module will be described in detail again in this embodiment. This module includes a signal amplifier, which is used to amplify the strain signal output by the strain sensing unit. The amplification factor A ranges from 10 to 1000. Simultaneously, the amplitude of the amplified signal... Compared with the signal amplitude before amplification The relationship is .

[0057] The core function of the dynamic and static load signal acquisition and conversion module described in the above embodiments is to "acquire the strain signal of the strain sensing unit and convert it into an electrical signal suitable for transmission and processing". In this embodiment, the function is to amplify the acquired weak signal.

[0058] The signal amplifier described in this embodiment amplifies the weak strain signal output by the strain sensing unit. The amplification factor A and the relationship between the amplification before and after amplification are described above.

[0059] In this embodiment, the amplification factor A of the signal amplifier is fixed within the range of 10 to 1000 because when the amplification factor is less than 10, the signal amplification effect is insufficient, and the signal may still be distorted due to noise. When the amplification factor is greater than 1000, it may lead to signal saturation (i.e., exceeding the amplifier's output range), resulting in the loss of detailed information from the original signal. The range of 10 to 1000 can be sensitively adjusted according to the output signal strength of different strain sensing units, balancing amplification effect and signal integrity.

[0060] For the amplified signal amplitude Compared with the signal amplitude before amplification The relationship is The significance lies in ensuring minimal linear distortion of the signal. Linear amplification means that the amplified signal maintains the same waveform and trend as the original signal, with only the amplitude being amplified proportionally. This ensures that subsequent modules can accurately reconstruct the original strain information from the amplified signal. It provides a quantitative basis for selecting the amplification factor. Based on the input requirements of subsequent modules and the amplitude of the original signal, the required amplification factor A can be calculated using this formula (if the original signal is known). =10 Target output =1mV, then A=1mV / 10 =100), making parameter settings more targeted.

[0061] This linear amplification characteristic affects the accuracy of the detection system. For example, when the bridge strain value is 10... The corresponding electrical signal amplitude output by the fiber Bragg grating is 5. If an amplification factor of A=200 is chosen, the output signal... The data processing and analysis module can accurately calculate the strain value based on this; if there is nonlinearity in the amplification process, the calculated strain value may be too large or too small, affecting the judgment of the stress state of the bridge.

[0062] For ease of understanding, this embodiment will be described and explained again using a specific example, where the weak signal strain amplitude output by the strain output unit... At that time, the amplification factor of the signal amplifier is set to A=100, based on the above relationship. The amplified signal amplitude =1000=1mV.

[0063] For this example, 10 The original signal is a typical weak signal, highly susceptible to noise interference during transmission (such as environmental electromagnetic noise that can reach several microvolts). Direct processing would lead to significant errors. However, after amplification to 1mV, the signal-to-noise ratio is improved (the noise percentage drops from 50% to 0.5), and the 1mV signal amplitude is within the optimal input range for most data acquisition devices. This allows the data processing and analysis module to extract signal features more accurately and calculate the corresponding strain values. For example, in bridge dynamic load tests, the dynamic strain signal generated when a vehicle passes is typically a microvolt fluctuation. After amplification, the strain-time curve can be clearly presented, providing reliable data for analyzing the dynamic response characteristics of the bridge.

[0064] It should be noted that this embodiment will provide a detailed description of the dynamic and static load signal acquisition and conversion module described in the above embodiments. This module also includes an analog-to-digital converter with a resolution of 12-24 bits.

[0065] In this embodiment, the signal processing flow of the dynamic and static load signal acquisition and conversion module is continued. In the previous embodiment, the weak strain signal was amplified to a suitable amplitude (millivolt or volt level) by a signal amplifier. However, the signal at this time is still an analog signal (an electrical signal that changes continuously with time), which cannot be directly recognized and processed by the data processing and analysis module (usually a digital circuit or computer system). In this embodiment, an analog-to-digital converter will be used to convert the analog signal into a digital signal.

[0066] The core function of an analog-to-digital converter (ADC) is to convert continuously changing analog signals (such as amplified strain gauge signals) into discrete digital signals (binary codes consisting of 0s and 1s).

[0067] The reason for setting the resolution of analog-to-digital converters (ADCs) to 12-24 bits is that resolution refers to the smallest signal change that the ADC can distinguish, usually expressed in binary bits. The higher the number of bits, the higher the resolution. When the resolution is lower than 12 bits, the ability to distinguish small strain signals is insufficient, and signal details may be lost (such as the subtle strain changes of bridges under slight dynamic loads). When the resolution is higher than 24 bits, although the accuracy is further improved, it will lead to a decrease in conversion speed and a significant increase in cost. Moreover, for the routine strain measurement requirements of bridge dynamic and static load tests, 24 bits meets the highest accuracy requirements.

[0068] For ease of understanding, this embodiment will be described and explained again using a specific example. The resolution of the analog-to-digital converter directly determines the accuracy of the digital signal's reproduction of the original analog signal. Taking 16-bit resolution as an example: if the amplitude range of the analog signal is 0~5V, 16-bit resolution means that the entire range is divided into... There are several quantization levels, and the voltage interval for each level is approximately 5V ÷ 65536 ≈ 0.0000763V (about 76.3V). This means the analog signal changes by more than 76.3%. At this time, the digital signal will change accordingly, ensuring that the tiny strain signal (after amplification) can be accurately converted. The higher the resolution, the smaller the quantization error (the difference between the analog signal and the corresponding digital signal). For example, the quantization error of 12-bit resolution is only about 5V ÷ 4096 ≈ 1.22mV, while the quantization error of 24-bit resolution is only about 5V ÷ 16777216 ≈ 0.3mV. This greatly reduces signal loss during the conversion process and provides high-precision data support for the data processing and analysis modules.

[0069] In this embodiment, a 16-bit analog-to-digital converter (ADC) will be used to process the 0-5V analog strain signal. This ADC subdivides the 0-5V signal range into 65,536 quantization levels, each corresponding to approximately 76.3 volts. The voltage change. When the amplified analog strain signal generates 0.1mV (100) due to the strain change of the bridge. When a vehicle experiences a 0.1mV fluctuation, the analog-to-digital converter (ADC) can accurately identify this change and output the corresponding digital signal (with 1-2 quantization units increased compared to the original digital value). For a 12-bit resolution converter (quantization interval 1.22mV), a 0.1mV signal change would result in the loss of strain details. In bridge dynamic load tests, strain fluctuations during vehicle passage may only be in the microvolt to millivolt range. A 16-bit converter can clearly reproduce these fluctuations, providing accurate data for analyzing the bridge's dynamic response (such as vibration frequency and amplitude).

[0070] In summary, this embodiment clarifies the configuration and resolution range of the analog-to-digital converter, achieving high-precision conversion from analog strain signals to digital signals.

[0071] In this embodiment, the temperature compensation module will be described in detail again. The temperature compensation module also includes a distributed optical fiber temperature sensor, which is laid parallel to the sensing optical fiber to measure the ambient temperature around the sensing optical fiber in real time.

[0072] The core function of the temperature compensation module described in the above embodiments is to monitor the ambient temperature in real time and perform temperature compensation on the collected strain signal according to the temperature change. In this embodiment, the temperature monitoring execution component (distributed optical fiber temperature sensor) and its spatial relationship with the sensing optical fiber (parallel laying) are clearly defined to ensure that the temperature monitoring data can accurately reflect the ambient temperature of the sensing optical fiber and provide a reliable basis for subsequent temperature compensation.

[0073] A distributed fiber optic temperature sensor is a sensor based on principles such as optical time-domain reflectometry (OTDR) or Raman scattering, capable of continuously measuring the temperature distribution along the fiber optic cable. Compared to traditional point-type temperature sensors (such as thermocouples and thermistors), its advantage lies in its ability to achieve long-distance, distributed temperature monitoring, acquiring the temperature at every point along the sensing fiber, rather than the temperature value of isolated points.

[0074] The distributed fiber optic temperature sensor is laid parallel to the sensing fiber (meaning the distributed fiber optic temperature sensor must be laid along the direction of the sensing fiber, maintaining a close and parallel spatial relationship), typically with a spacing of no more than 5 cm. This arrangement ensures that the temperature measured by the distributed fiber optic temperature sensor is consistent with the actual ambient temperature of the sensing fiber, avoiding temperature measurement deviations caused by spatial differences.

[0075] The parallel laying arrangement of distributed fiber optic temperature sensors and sensing fibers serves several purposes. Firstly, it ensures that each fiber Bragg grating strain sensing unit on the sensing fiber has a corresponding temperature measurement point. For instance, when a fiber Bragg grating on the sensing fiber is located at the mid-span of the bridge's main beam, the temperature measurement value from the distributed fiber optic temperature sensor at that location can be directly used to compensate for the strain signal of that fiber Bragg grating, avoiding compensation errors caused by temperature-strain mismatch. Secondly, as bridge temperature dynamically changes with the environment (such as day-night cycles and weather variations), the parallel-laid distributed fiber optic temperature sensors can track these dynamic temperature changes along the sensing fiber in real time. For example, under direct sunlight, the bridge deck temperature may rise by 5°C within one hour; the distributed fiber optic temperature sensors can capture this change in real time and simultaneously use it for dynamic compensation of the strain signal. Thirdly, the distributed fiber optic temperature sensor itself is also in fiber optic form and can be laid together with the sensing fiber (e.g., bundled in the same cable tray), without adding excessive construction complexity. Furthermore, its electromagnetic interference resistance and corrosion resistance are consistent with the sensing fiber, making it suitable for the harsh outdoor environment of bridges.

[0076] For ease of understanding, this embodiment will be described and explained again using a specific example. In a monitoring area of ​​the bridge, distributed fiber optic temperature sensors are laid closely parallel to sensing fibers. As the ambient temperature changes over time (15°C in the morning, 30°C at noon), the temperature data measured by the distributed fiber optic temperature sensors along the entire length of the sensing fiber shows a continuously changing curve. For example, the temperature on the sun-facing side of the main beam is 3°C higher than the shaded side, and the temperature sensor can accurately capture this difference. For a fiber Bragg grating on the sensing fiber (located on the sun-facing side), the temperature at the corresponding distributed fiber optic temperature sensor measurement point is 30°C at noon. This temperature value will be directly used by the temperature compensation algorithm unit to compensate for the strain signal of the fiber Bragg grating, eliminating the additional strain (approximately 150°C) caused by the temperature difference between 30°C and 15°C in the morning. ~200 (The specific method depends on the material of the optical fiber), ensuring that the obtained strain value reflects only the bridge load, not the temperature effect. If the distributed optical fiber temperature sensor is not laid parallel to the sensing fiber (e.g., only a point sensor is placed at one end of the bridge), the strain signal at the 30°C location may be compensated by an average temperature of 15°C, resulting in approximately... The compensation error far exceeds the normal strain of the bridge (usually several hundred). This seriously affects the accuracy of measurements.

[0077] In this embodiment, the temperature compensation module will be described in detail again. The temperature compensation module also includes a temperature compensation algorithm unit and its corresponding temperature-strain relationship model, as described in detail below.

[0078] In the above embodiments, it was clearly stated that the temperature distribution around the sensing fiber is obtained by a distributed optical fiber temperature sensor. In this embodiment, the focus is on how to use the obtained temperature data for strain signal compensation. That is, through the temperature compensation algorithm unit and the preset temperature-strain relationship model, the temperature change is converted into the corresponding additional strain and removed from the total strain.

[0079] The main content of this embodiment is that the temperature compensation module includes a temperature compensation algorithm unit. This unit performs temperature compensation on the acquired strain signal based on temperature data measured by distributed fiber optic temperature sensors and a pre-established temperature-strain relationship model. The temperature-strain relationship model is as follows: ,in, The additional strain is caused by temperature, where T is the actual measured temperature. For reference temperature, and This is a coefficient related to the sensing fiber material.

[0080] The temperature compensation algorithm unit is the logical core that performs compensation calculations. It receives two key inputs: the real-time temperature T measured by a distributed fiber optic temperature sensor, and a pre-calibrated temperature-strain relationship model. This model quantifies the additional strain caused by temperature changes in the sensing fiber, where:

[0081] This represents the additional strain caused by temperature (a value that needs to be subtracted from the total strain); T is the actual measured temperature. Reference temperature (usually the calibration temperature, such as 20℃); and The coefficient related to the sensing fiber material ( The coefficients are linear. (These are nonlinear correction coefficients, all calibrated experimentally). A quadratic polynomial form is used in this temperature-strain relationship, considering both the linear relationship between temperature change and additional strain (the main part) and correcting for the nonlinear effects of large-scale temperature changes through quadratic terms. This is more efficient than a purely linear model. It has higher compensation accuracy.

[0082] Regarding the establishment of the temperature-strain relationship model:

[0083] Temperature-strain relationship model Pre-calibration through experiments is required. The specific process is as follows: Place the sensing fiber in a constant temperature chamber, and under no-load conditions (temperature change only), measure the change in the center wavelength of the fiber Bragg grating corresponding to different temperatures T, and then calculate the additional strain. Then, by fitting using the least squares method, we obtain... and .

[0084] Advantages of this temperature-strain relationship model:

[0085] High accuracy: Quadratic term correction ensures the model maintains an error of less than 0.5% over a wide temperature range of -40℃ to 80℃. / ℃, far superior to the linear model (error approximately 2). / ℃); highly adaptable: by adjusting and It can be adapted to sensing optical fibers of different materials (such as the significant difference in coefficients between plastic optical fibers and quartz optical fibers); it is computationally efficient: the computational complexity of the quadratic polynomial is low, and it can run in real time on embedded systems, meeting the requirements for signal processing speed in bridge dynamic load tests (usually requiring the processing of thousands of data points per second).

[0086] For ease of understanding, this embodiment will be described in detail through specific embodiments. If, in a particular embodiment, it is known... , , Real-time temperature T=30℃ (temperature change) =10℃), then substitute it into the temperature-strain relationship model. From the middle (i.e., 110) If the total strain measured by the strain sensing unit is 500 at this time... (Including structural strain and temperature-induced strain), the compensated true structural strain is 500. -110 =390 .

[0087] In the above embodiments, if no compensation is performed or a linear model (ignoring quadratic terms) is used, then 110 will be... The addition of temperature strain to the structural strain leads to a measurement error of up to 22%. By adopting the temperature-strain relationship model in this embodiment, the error can be controlled within 1%, ensuring that the strain value obtained from the data processing and analysis model can truly reflect the stress state of the bridge under load.

[0088] In this embodiment, the data processing and analysis module in the above embodiment will be described in detail again. It is clear that the data processing and analysis module also includes a fast Fourier transform unit and the corresponding elastic modulus estimation formula, as described in detail below.

[0089] The core function of the data processing and analysis module described in the above embodiments is to process and analyze the strain electrical signal after temperature compensation to obtain the distribution and related parameters of the bridge structure under dynamic and static loads. In this embodiment, the focus is on the spectrum analysis of the dynamic load signal. The bridge vibration frequency is extracted by the fast Fourier transform unit, and the elastic modulus is estimated based on the frequency information.

[0090] The Fast Fourier Transform (FFT) is a mathematical algorithm that converts a time-domain signal into a frequency-domain signal. Its function is to extract the vibration frequencies (i.e., the main frequency components) of a bridge from a time-varying strain signal. In bridge dynamic load tests, dynamic loads such as vehicle traffic and wind force cause periodic changes in the bridge. The FFT unit can convert these time-domain periodic changes into peak frequencies in the frequency domain, i.e., the bridge's natural or forced vibration frequencies. Elastic modulus estimation formula. The correlation between the elastic moduli of bridge structures in the vibration frequency domain was established, wherein:

[0091] E is the elastic modulus of the bridge structure (a physical quantity that reflects the material's ability to resist deformation, unit: Pa); The bridge vibration frequency (Hz) is obtained through Fast Fourier Transform analysis; m is the mass per unit length of the bridge structure (kg / m); L is the calculated span of the bridge (m); I is the moment of inertia of the bridge section (a geometric parameter reflecting the section's resistance to bending deformation, unit: ...). This calculation formula is derived based on the vibration theory of simply supported beams and is suitable for estimating the overall elastic modulus of bridges under dynamic loads, providing a quantitative standard for evaluating bridge structural performance.

[0092] The function of the Fast Fourier Transform (FFT) unit and the significance of the elastic modulus calculation formula are as follows: The FFT unit converts the time-domain strain signal (such as a strain curve that varies with time) into a power spectral density map in the frequency domain. The frequencies corresponding to the peaks in the map are the main vibration frequencies of the bridge. For example, when a vehicle passes over a bridge at a certain speed, the strain signal exhibits irregular fluctuations in the time domain. After the FFT conversion, one or more obvious peaks will appear on the power spectrum. These peak frequencies correspond to the vibration frequencies of the bridge under that dynamic load. The elastic modulus calculation formula... The derivation is based on the theory of lateral vibration of simply supported beams. Its physical meaning is that the vibration frequency of a bridge is positively correlated with its elastic modulus and moment of inertia of the cross section, and negatively correlated with the mass per unit length and span. Given m, L, and I (which can be obtained through bridge design drawings or on-site measurements), the vibration frequency f can be obtained through fast Fourier transform, and the elastic modulus E can be quickly calculated to evaluate the overall stiffness of the bridge.

[0093] To facilitate understanding in this embodiment, the formula for calculating the elastic modulus described herein will be explained in detail again. Given that the mass per unit length of the bridge structure is m = 500 kg / m, the span is L = 50 m, and the moment of inertia is I = 0.4... If the vibration frequency under dynamic load is obtained through the Fast Fourier Transform unit, f = 50Hz, then substituting this into the elastic modulus calculation formula yields... Pa (i.e., 190 GPa). This result can be compared with the elastic modulus used in bridge design (e.g., 30~40 GPa for concrete bridges, the example here is an assumed value for steel bridges). If the estimated value deviates significantly from the design value (e.g., less than 20% of the design value), it indicates that the bridge structure has stiffness degradation or damage, and further testing and evaluation are required.

[0094] In this embodiment, the data processing and analysis module described in the above embodiments will be described in detail again. The data processing and analysis module also includes a finite element analysis unit, which is used to analyze and compare the actual strain data with the bridge finite element model. The specific explanation is as follows.

[0095] The above embodiments describe in detail how the Fast Fourier Transform (FFT) unit estimates the elastic modulus through vibration frequency, thereby achieving a quantitative assessment of the bridge's dynamic performance. This embodiment introduces a Finite Element Analysis (FEM) unit to compare the actual strain data collected by the system with the results calculated by the theoretical model, evaluating the actual state of the bridge from the perspective of structural stress matching.

[0096] The main content to be described in this embodiment is that the data processing and analysis module also includes a finite element analysis unit, which is used to compare and analyze the collected strain data with the pre-established bridge finite element model to evaluate the difference between the actual stress state and the theoretical design state of the bridge structure.

[0097] A bridge finite element model is a digital model built based on bridge design drawings using finite element software (such as ANSYS and ABAQUS). It contains information such as the bridge's geometric dimensions, material parameters (such as elastic modulus and Poisson's ratio), and constraint conditions. It can calculate the theoretical strain values ​​of each part under simulated dynamic and static loads.

[0098] The core function of the finite element analysis unit is to receive actual strain data acquired by the distributed fiber optic sensing module and corrected by the temperature compensation module, compare it point-by-point or partition-by-partially with the theoretical strain data output by the finite element model under the same load condition, and calculate the deviation rate (e.g., ...). To assess the degree of matching between the two, and thus determine whether the actual stress on the bridge meets expectations.

[0099] The engineering process of the finite element analysis unit consists of three key steps: The first step is model calibration: Before comparison, the material properties of the finite element model are corrected according to the measured parameters such as the elastic modulus estimated in the above embodiments to ensure that the theoretical calculation is based on the current actual performance of the bridge; The second step is load synchronization: The finite element model is simulated to be subjected to the same load conditions as the actual experiment (such as the loading position and magnitude of static load, and the vehicle speed and weight of dynamic load), and the theoretical strain distribution of the corresponding working conditions is generated; The third step is data matching and deviation analysis: The measured strain data (presented in the form of strain cloud map or measurement point table) is superimposed and compared with the theoretical data. The focus of the analysis includes, but is not limited to, overall trend deviation, local peak deviation, and spatial distribution deviation.

[0100] For overall trend deviations: such as whether the strain distribution pattern of the entire bridge is consistent with the theory (e.g., the strain is theoretically the largest at mid-span, but does the actual measurement show the same pattern); for local peak deviations: such as whether the strain peaks in key parts such as near the supports and cantilever ends exceed the theoretical range; for spatial distribution deviations: such as whether there are abnormal areas where the theoretical strain is small but the measured strain is significant.

[0101] To facilitate understanding, this embodiment will describe the content described in detail through a specific example. For instance, if a finite element model of a bridge calculates a theoretical strain of 5 × 10⁻⁶ at a certain location under specific loading conditions... The actual strain value collected by the system was 5.5 × The deviation rate is then calculated using the formula described above. If the design tolerance for this part is ±15%, then a 10% deviation is within a reasonable range, indicating that the actual stress on this part matches the theoretical stress. If the theoretical strain for another part is 3× The actual value is 6× If the deviation rate reaches 100%, the cause needs to be investigated (such as additional loads not considered in the model, or stiffness reduction caused by structural damage).

[0102] The value of the comparative analysis described in this embodiment lies in the fact that when the deviation rate is generally small (e.g., less than 5%), it indicates that the stress on the bridge meets the design expectations; when the local deviation is significant, targeted structural inspections (e.g., ultrasonic testing, rebound testing) can be carried out to avoid omissions in judgment based solely on a single strain threshold.

[0103] The monitoring and early warning module is described in detail in the above embodiments. It is clarified that the monitoring and early warning module includes an audible and visual alarm unit and a remote communication unit, which are used to issue alarms and transmit information when the bridge strain is abnormal. Its specific contents include.

[0104] The core function of the monitoring and early warning module described in the above embodiments is to monitor the bridge status in real time based on the results obtained by the data processing and analysis module, and issue an early warning signal when the bridge strain is abnormal. In this embodiment, the form of the early warning signal (audio-visual alarm) and the information transmission method (remote communication) are specified to ensure that relevant personnel can be informed in a timely manner and take corresponding measures when the bridge strain is abnormal.

[0105] The aforementioned audible and visual alarm unit is a device that emits alarms through both sound and light. The sound is typically a continuous or intermittent buzzing or alarm, while the light is a flashing warning light (such as a brightly lit red or yellow), quickly attracting the attention of staff on-site. The remote communication unit, on the other hand, is a component that transmits alarm information and related data to a remote monitoring center via wireless networks (such as 4G, 5G, and LoRa) or wired networks, enabling long-distance information transmission.

[0106] The preset safety threshold is a strain limit value determined based on factors such as bridge design standards, material strength, and service life. When the bridge strain value calculated by the data processing and analysis module exceeds this safety threshold, it is determined to be an abnormal strain, triggering the monitoring and early warning module.

[0107] Regarding the functions of the audible and visual alarm unit and the remote communication unit described in this embodiment: The audible and visual alarm unit can quickly create a strong sensory stimulus at the test site when abnormal bridge strain occurs, attracting the attention of on-site personnel and making them immediately aware of the safety risk to the bridge. For example, when the strain value of a certain part of the bridge exceeds the safety threshold, the audible and visual alarm unit will emit a piercing alarm sound, and at the same time, a red warning light will flash rapidly. Upon hearing and seeing this, on-site personnel can immediately stop the current test operation and inspect the abnormal part. The remote communication unit transmits alarm information (such as alarm time and abnormal location) and relevant strain data (such as the real-time strain value of the part, strain change curve, and the difference from the safety threshold) to the monitoring center, enabling remote management personnel to understand the abnormal situation of the bridge in real time. Based on this information, the monitoring center can remotely guide on-site work or dispatch personnel and equipment to the site for handling, realizing remote monitoring and management of bridge safety. Regarding the synergistic effect of the audible and visual alarm unit and the remote communication unit, when the data processing and analysis module determines that the bridge strain is abnormal, it will send a trigger signal to the monitoring and early warning module. After receiving the signal, the monitoring and early warning module will simultaneously activate the audible and visual alarm unit and the remote communication unit. The audible and visual alarm unit will issue an alarm on site, and the remote communication unit will transmit relevant information to the monitoring center. The two work together to ensure that information can be delivered to relevant personnel in different locations in a timely manner.

[0108] To facilitate understanding, this embodiment will describe the above content in more detail through a specific example. For instance, in one specific embodiment, the preset strain safety threshold for a certain critical component of the bridge is 8× When the data processing and analysis module calculates the strain value of this part to be 8.5× If the load exceeds the safety threshold, the audible and visual alarm unit in the monitoring and early warning module is immediately triggered, emitting a loud alarm sound (such as a 110-decibel buzzer), while a red warning light flashes twice per second. Upon hearing and / or seeing this, on-site personnel immediately stop the loading test on the bridge and proceed to inspect the critical area. The remote communication unit transmits the alarm information (including the alarm time of 10:30 AM and the abnormal location being the mid-span of the main beam) and detailed strain data (real-time strain value 8.5 × 10⁻⁶) via the 4G network. The difference between the strain curve and the safety threshold is 0.5× The information is transmitted to the monitoring center. Upon receiving this information, the staff at the monitoring center review the situation via video surveillance and remotely contact the on-site personnel to guide them in further testing, such as using a total station to measure the bridge's deformation to determine if any structural damage exists.

[0109] It should be noted that the embodiments of the present invention have better implementability and are not intended to limit the present invention in any way. Any person skilled in the art may use the above-disclosed technical content to change or modify it into equivalent effective embodiments. However, any modifications or equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering, characterized in that, include: A distributed optical fiber strain sensing module, comprising multiple sensing optical fibers, each of which is provided with multiple strain sensing units at intervals, for distributed arrangement on the bridge structure and acquisition of strain information at different locations on the bridge. The dynamic and static load signal acquisition and conversion module is connected to the distributed optical fiber strain sensing module and is used to acquire the strain signal of the strain sensing unit and convert the strain signal into a strain electrical signal suitable for transmission and processing. A temperature compensation module is connected to the distributed optical fiber strain sensing module and the dynamic and static load signal acquisition and conversion module. It is used to monitor the ambient temperature around the sensing optical fiber in real time and to perform temperature compensation on the strain signal according to the changes in the acquired ambient temperature. The data processing and analysis module is connected to the dynamic and static load signal acquisition and conversion module and the temperature compensation module. It is used to process and analyze the strain electrical signal after temperature compensation in order to obtain the strain distribution and related parameters of the bridge structure under dynamic and static loads. The monitoring and early warning module is connected to the data processing and analysis module and is used to monitor the bridge status in real time based on the results obtained by the data processing and analysis module, and issue an early warning signal when the bridge strain is abnormal.

2. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 1, characterized in that, The strain sensing unit is a fiber Bragg grating (FBG), and the change in the center wavelength of the fiber Bragg grating is... According to the calculation formula Calculate the dependent variable ,in The initial center wavelength of the fiber Bragg grating. The effective elastic coefficient.

3. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 2, characterized in that, The sensing fiber is a multimode fiber, and the core diameter of the multimode fiber ranges from 50. ~100 .

4. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 1, characterized in that, The dynamic and static load signal acquisition and conversion module includes a signal amplifier for amplifying the strain signal output by the strain sensing unit. The amplification factor A ranges from 10 to 1000, and the amplified signal amplitude... Compared with the signal amplitude before amplification The relationship is .

5. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 4, characterized in that, The dynamic and static carrier signal acquisition and conversion module also includes an analog-to-digital converter with a resolution of 12 to 24 bits.

6. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 1, characterized in that, The temperature compensation module includes a distributed optical fiber temperature sensor, which is laid parallel to the sensing optical fiber to measure the ambient temperature around the sensing optical fiber in real time.

7. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 6, characterized in that, The temperature compensation module further includes a temperature compensation algorithm unit. This algorithm unit performs temperature compensation on the acquired strain signal based on the ambient temperature measured by the distributed fiber optic temperature sensor and a pre-established temperature-strain relationship model. The temperature-strain relationship model is... ,in, The additional strain is caused by temperature, where T is the actual measured temperature. For reference temperature, and This is a coefficient related to the sensing fiber material.

8. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 1, characterized in that, The data processing and analysis module includes a Fast Fourier Transform (FFT) unit, used to perform spectral analysis on the acquired strain signals to obtain the vibration frequency information of the bridge under dynamic load. Through analysis of the vibration frequency f, the vibration frequency is calculated according to the formula... Estimate the elastic modulus E of the bridge structure, where m is the mass per unit length of the bridge structure, L is the calculated span of the bridge, and I is the moment of inertia of the bridge section.

9. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 8, characterized in that, The data processing and analysis module also includes a finite element analysis unit, which is used to compare and analyze the strain data obtained by the distributed fiber optic strain sensing module, the dynamic and static load signal acquisition and conversion module, and the temperature compensation module with the pre-established bridge finite element model to evaluate the difference between the actual stress state and the theoretical design state of the bridge structure.

10. The distributed fiber optic strain sensing detection system for dynamic and static load testing of bridge engineering according to claim 1, characterized in that, The monitoring and early warning module includes an audible and visual alarm unit. When the bridge strain value obtained by the data processing and analysis module exceeds a preset safety threshold, the audible and visual alarm unit emits an audible and visual alarm signal. At the same time, the monitoring and early warning module also includes a remote communication unit for transmitting alarm information and related strain data to the monitoring center.

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