Deformation monitoring method and device for concrete tower drum

Abstract

The invention discloses a deformation monitoring method and a deformation monitoring device for a concrete tower drum. The deformation monitoring method comprises the following steps: synchronously acquiring wavelength drift and accompanying temperature of a pre-embedded fiber grating sensor and calibration point coordinates of external visual equipment; carrying out temperature compensation on the wavelength drift to calculate the total mechanical strain; accumulated creep is calculated based on concrete rheological characteristics and stripped from total mechanical strain, and effective elastic strain is obtained; fitting the curvature by using the effective elastic strain and reconstructing the theoretical reference displacement of the tower drum; and inputting the theoretical reference displacement and the calibration point coordinates into a Kalman filter, and outputting a final real deformation amount. According to the method, the creep component is accurately stripped, so that false deformation and false alarm in long-term monitoring are eliminated; and meanwhile, the absolute coordinates of the external visual data and the all-weather characteristics of the internal optical fiber data are combined for fusion correction, so that the problems that a traditional integration method is large in accumulative error and visual monitoring is easily interfered by the environment are solved, and high-precision and high-robustness structural deformation monitoring is realized.

Description

Technical Field

[0001] This invention relates to the field of structural deformation monitoring, and specifically to a method and apparatus for monitoring the deformation of a concrete tower. Background Technology

[0002] In the field of structural health monitoring (SHM) technology for civil engineering, especially deformation monitoring of tall concrete structures such as wind turbines, chimneys, and television towers, it has always been a crucial link in ensuring the safe and stable operation of structures. Concrete towers, with their excellent corrosion resistance and cost advantages, have been widely used in modern large-scale wind power projects, providing a solid foundation for the efficient and stable development of wind power. With continuous technological advancements, the demand for deformation monitoring of these tall concrete structures is increasing, and the monitoring results are of paramount importance for the timely detection of potential structural risks and the assurance of structural safety.

[0003] In previous tower deformation monitoring, two main technical approaches have been used. The first is strain-based indirect monitoring, such as fiber optic gratings and resistance strain gauges. This typically involves directly acquiring strain readings from sensors and then calculating displacement using beam element theory integration. This method can reflect the tower's strain condition to some extent, providing data support for deformation monitoring. The second approach is vision- or GPS-based direct monitoring. GPS can directly measure displacement, providing relatively intuitive displacement data; while machine vision obtains relevant displacement information by observing specific parts of the tower. However, in these existing solutions, internal strain monitoring and external visual monitoring are often two independent systems, lacking deep algorithmic integration.

[0004] Existing technologies have significant drawbacks. Indirect strain-based monitoring methods suffer from several limitations. The "total strain" measured by sensors includes elastic strain, thermal strain, and creep strain. Creep, a slowly increasing plastic flow, causes displacement through a mechanism incompatible with elastic equations. Directly substituting the total strain, including creep, into the elastic integral formula results in a significant positive drift error in the calculated tower top displacement as service time increases, leading to false "deformation" alarms. Direct monitoring methods based on vision or GPS also have problems. GPS has a low sampling frequency, making it unable to capture high-frequency vibrations; machine vision is highly susceptible to rain, fog, and lighting conditions, causing data interruptions. Furthermore, the lack of integration between internal strain monitoring and external visual monitoring systems prevents the online calibration of accumulated errors in the internal integral model using external data. Summary of the Invention

[0005] The purpose of this invention is to overcome the above-mentioned technical deficiencies and to propose a method and device for monitoring the deformation of concrete towers.

[0006] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution: This invention provides a method for monitoring the deformation of a concrete tower, comprising: S1 data synchronous acquisition: In At any given moment, the center wavelength drift of the fiber optic grating sensor embedded in the tower wall is simultaneously acquired. Accompanying temperature data and the actual coordinates of the verification points obtained by the external visual monitoring equipment of the tower. ; S2 Mechanical Strain Demodulation: This modulates the center wavelength shift. Temperature compensation was performed to calculate the total mechanical strain including the creep component. ; S3 Creep Stripping and Effective Strain Acquisition: Calculation Based on the Rheological Properties of Concrete Materials Cumulative creep strain over time and the total mechanical strain Subtracting the accumulated creep strain yields the effective elastic strain that causes the instantaneous deformation of the structure. ; S4 reference deformation field reconstruction: utilizing the effective elastic strain The curvature distribution function along the axial direction of the tower is fitted, and the tower height along the axial direction is calculated using a double integral based on this curvature distribution function. theoretical reference displacement of the distribution ; S5 Multi-Source Data Fusion Correction: The theoretical benchmark displacement is then... The actual coordinates of the verification point Input the Kalman filter, calculate the optimal estimated gain, and output the final true deformation of the tower. .

[0007] In some embodiments, in step S2, the total mechanical strain The calculation formula is: in, The initial center wavelength, The effective elastic-optical coefficient of the optical fiber. The coefficient of thermal expansion of optical fiber. Thermo-optic coefficient, The temperature change is measured by a parallel temperature sensor; This is passed as an input parameter to step S3.

[0008] In some embodiments, in step S3, the effective elastic strain The calculation method is as follows: The generalized Kelvin model was used to calculate the cumulative creep strain. : in, For the tower prestress level, and For the model number The elastic modulus and hysteresis time of the element; The effective elastic strain is obtained by performing a stripping operation: The This is passed to step S4 as the sole input source for calculating curvature.

[0009] In some embodiments, in step S4, the theoretical reference displacement The calculation formula is: in, For the tower at height The curvature at that point is determined by the effective elastic strain output in step S3. Sure: in, and The effective elastic strains are calculated for the optical fibers on both sides of the symmetrical tower. For height Lateral spacing of sensors at the location; The The predicted state value is passed to step S5.

[0010] In some embodiments, in step S5, the final true deformation amount The calculation formula is: in: At the height of the verification point The observations obtained by the vision device; It is the predicted value at that height output by step S4; The observation matrix; This is the Kalman gain matrix, used to balance model prediction error with visual observation error.

[0011] In some embodiments, the Kalman gain matrix The update depends on the visual signal-to-noise ratio. ,when When it is below the preset threshold, Automatically reset to zero, at this time .

[0012] This application also provides a deformation monitoring device for a concrete tower, used to perform the method, including: Data acquisition module: used for... At any given moment, the center wavelength drift of the fiber optic grating sensor embedded in the tower wall is simultaneously acquired. Accompanying temperature data and the actual coordinates of the verification points obtained by the external visual monitoring equipment of the tower. ; Preprocessing module: used for processing the center wavelength shift. Temperature compensation was performed to calculate the total mechanical strain including the creep component. ; Creep stripping module: used for calculating the rheological properties of concrete materials. Cumulative creep strain over time and the total mechanical strain Subtracting the accumulated creep strain yields the effective elastic strain that causes the instantaneous deformation of the structure. ; Reference deformation field reconstruction module: used to utilize the effective elastic strain The curvature distribution function along the axial direction of the tower is fitted, and the tower height along the axial direction is calculated using a double integral based on this curvature distribution function. theoretical reference displacement of the distribution ; Multi-source data fusion correction module: used to adjust the theoretical reference displacement The actual coordinates of the verification point Input the Kalman filter, calculate the optimal estimated gain, and output the final true deformation of the tower. .

[0013] In some embodiments, the fiber optic grating sensor is arranged in a double-helix symmetrical structure inside the tower wall, with a spatial phase difference of 180 degrees between the two helical optical fibers, to form the symmetrical two-sided optical fiber layout as described in claim 4.

[0014] This application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the method when running the computer program.

[0015] This application also provides a computer-readable storage medium having computer instructions stored thereon, which, when executed, implement the steps of the method described.

[0016] Compared with the prior art, the beneficial effects of the deformation monitoring method and device for concrete tower cylinders provided by the present invention include: 1. The generalized Kelvin model is used to calculate the cumulative creep strain based on the rheological properties of concrete, and a stripping operation is performed from the total mechanical strain, retaining only the effective elastic strain that causes instantaneous deformation of the structure as the integration input source. This approach fundamentally corrects the logical error of traditional monitoring methods that directly substitute the total strain including creep into the elastic equation for integration, eliminates the huge positive drift error caused by creep plastic flow with increasing service time, and improves the accuracy of long-term deformation monitoring. 2. The theoretical reference displacement derived from fiber optic gratings is used as the state prediction, and the absolute coordinates obtained from external vision devices are used as the observation values. The Kalman filter is used for fusion. At the same time, the Kalman gain matrix is ​​adaptively adjusted according to the visual signal-to-noise ratio, and the gain is automatically set to zero when the SNR is low. This overcomes the limitations of a single monitoring method. The cumulative error of the fiber optic integral model is calibrated online using visual data. At the same time, the fiber optic model is used to fill data gaps under visual failure conditions such as rain and fog. This solves the problems of low GPS sampling and the large environmental limitations of machine vision, and ensures the continuity and reliability of monitoring data. 3. The fiber optic grating sensor is pre-embedded in the tower wall in a double-helix symmetrical structure, and the spatial phase difference between the two helical fibers is set to 180 degrees to form a symmetrical measurement layout. This arrangement can directly cancel the common-mode interference signal caused by the axial compression or uniform thermal expansion of the tower at the physical level, and only retain the differential-mode signal caused by bending. This purifies the data used for curvature fitting at the hardware source and reduces the complexity and error of subsequent algorithm processing. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the deformation monitoring device for a concrete tower provided in an embodiment of the present invention; Figure 2 This is a schematic flowchart of a method for monitoring the deformation of a concrete tower according to an embodiment of the present invention. Explanation of reference numerals in the attached drawings: 100, concrete tower; 110, spiral optical fiber; 120, fiber optic grating sensor; 210, calibration point; 220, external visual monitoring equipment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] This application mainly adopts a scheme of constructing a heterogeneous sensing network and fusing data, which achieves a high-precision deformation monitoring effect by accurately separating creep components and cross-verifying internal and external data. The following is a further detailed description of this application.

[0020] Example 1 Please refer to Figure 1 and Figure 2The deformation monitoring method for concrete tower cylinders provided in this application includes synchronous data acquisition, mechanical strain demodulation, creep stripping and effective strain acquisition, benchmark deformation field reconstruction, and multi-source data fusion correction. By sequentially executing these five steps, the deformation of the concrete tower cylinder can be accurately monitored, eliminating errors caused by creep and improving the accuracy and reliability of monitoring. This is because each step addresses specific problems existing in the prior art, ensuring data comprehensiveness from the beginning of data acquisition, removing interference factors through demodulation and stripping steps, and finally obtaining accurate deformation data through fusion correction.

[0021] Specifically, the synchronous data acquisition includes a fiber optic grating sensor 120, a parallel temperature sensor, and an external visual monitoring device 220. The fiber optic grating sensor 120 generally consists of an optical fiber 110 and a grating. The grating is etched inside the optical fiber 110, and its center wavelength drifts with changes in external strain and temperature. It can be made using single-mode fiber to improve measurement accuracy. During installation, it should be tightly embedded in the tower wall to ensure accurate sensing of the tower's strain. To facilitate subsequent curvature calculations, the fiber optic grating sensor 120 is arranged in a double-helix symmetrical structure within the concrete tower wall 100, with a spatial phase difference of 180 degrees between the two helical fibers. The parallel temperature sensor can be a thermocouple, a thermistor, or other similar sensor; its function is to measure accompanying temperature data. For example, a thermocouple is made of two different metal materials connected together. It determines temperature by measuring thermoelectric potential and has the characteristics of fast response and wide measurement range. The external visual monitoring device 220 can be a high-resolution industrial camera, installed at a ground station at a certain distance from the tower base. Highly reflective targets are set at the top and middle of the concrete tower 100 as calibration points 210. The camera obtains the actual coordinates of the calibration points by capturing changes in the position of the targets. During this process, all sensors and devices need to collect data simultaneously to ensure data synchronization.

[0022] The working process and technical effects of the above structure: The double-helix symmetrical layout ensures that a set of geometrically symmetrical strain data can be obtained at any height of the cross-section. This layout physically cancels out the common-mode interference caused by axial compression or uniform thermal expansion of the tower, retaining only the differential-mode signal caused by bending, thereby significantly improving the signal-to-noise ratio of subsequent curvature calculation.

[0023] The purpose of synchronous data acquisition is to comprehensively obtain information related to tower deformation, providing a foundation for subsequent data analysis and processing. By simultaneously acquiring data from fiber optic grating sensors, parallel temperature sensors, and external visual monitoring equipment, multiple factors such as strain, temperature, and displacement can be comprehensively considered, avoiding the limitations that may arise from a single data source.

[0024] Specifically, mechanical strain demodulation includes fiber optic parameters and temperature compensation formulas.

[0025] The main optical fiber parameters include the initial center wavelength. Fiber effective elastic coefficient Fiber thermal expansion coefficient and thermo-optic coefficient Initial center wavelength This is the center wavelength of the fiber Bragg grating in its initial state; it is a fixed parameter determined during sensor manufacturing. The effective elastic-optical coefficient of the fiber. This reflects the degree of change in the optical properties of an optical fiber when subjected to stress. (Optical fiber thermal expansion coefficient) The thermo-optic coefficient represents the degree of expansion of optical fiber when the temperature changes. This indicates the effect of temperature changes on the optical properties of optical fibers. The temperature compensation formula is: This formula can be used to calculate the center wavelength shift measured by the fiber Bragg grating sensor. Temperature compensation is performed to calculate the total mechanical strain including the creep component. .

[0026] The purpose of mechanical strain demodulation is to eliminate the influence of temperature on the measurement results of fiber Bragg grating sensors and obtain accurate total mechanical strain. Since temperature changes cause fiber stretching and changes in optical properties, resulting in center wavelength drift, temperature compensation is needed to eliminate this interference and provide reliable data for subsequent creep stripping.

[0027] Specifically, creep stripping and effective strain acquisition include the generalized Kelvin model and stripping calculation.

[0028] The generalized Kelvin model is used to calculate cumulative creep strain. Its formula is ,in For the tower prestress level, and For the model number The model considers the rheological properties of concrete and can accurately calculate the elastic modulus and hysteresis time of the elements. The cumulative creep strain over time. The stripping operation calculates the total mechanical strain. Subtract cumulative creep strain ,Right now Thus, the effective elastic strain that causes instantaneous deformation of the structure is obtained. .

[0029] The working process and technical effects of the above steps are as follows: The system first uses stored rheological parameters to extrapolate the current creep value in real time, and then performs a subtraction operation. This step, in principle, corrects the logical error in traditional monitoring methods of "mistaking total strain for elastic strain." Because concrete creep is a plastic flow that occurs over time and does not directly reflect the current stress and bending state of the structure, if it is not separated, the monitored deformation will produce huge spurious drifts over time.

[0030] Creep stripping and effective strain acquisition are key steps in this method. They can eliminate non-structural strain caused by concrete creep, allowing subsequent calculations to be based on the effective elastic strain that truly causes structural deformation, thus greatly improving the accuracy of deformation monitoring.

[0031] Specifically, the reconstruction of the reference deformation field includes the curvature calculation formula and the theoretical reference displacement calculation formula.

[0032] The formula for calculating curvature is: ,in and The effective elastic strains are calculated for the optical fibers on both sides of the symmetrical tower. For height The lateral spacing of the sensors at the location. This formula can be used to calculate the curvature of the tower at different heights based on the effective elastic strain. The theoretical reference displacement calculation formula is as follows: By performing a double integral of the curvature along the height of the tower, the height of the tower section can be calculated. theoretical reference displacement of the distribution .

[0033] The baseline deformation field reconstruction can reconstruct the theoretical baseline displacement of the tower based on the effective elastic strain, providing a foundation for subsequent multi-source data fusion and correction. By calculating curvature and performing integration operations, the effective elastic strain can be converted into displacement information, thereby obtaining the theoretical deformation of the tower.

[0034] Specifically, the multi-source data fusion correction includes a Kalman filter, a formula for calculating the final true deformation, and an adaptive gain control strategy.

[0035] The Kalman filter is an optimal estimation algorithm that calculates the optimal estimation gain based on the system's predicted and observed states, thereby correcting the system state. In this method, the theoretical reference displacement is used... actual coordinates of the verification point Input to the Kalman filter. The final formula for calculating the true deformation is as follows: ,in At the height of the verification point The observations obtained by the vision device, It is the predicted value at that altitude. For the observation matrix, This is the Kalman gain matrix, used to balance model prediction error with visual observation error.

[0036] Furthermore, the Kalman gain matrix The update depends on the visual signal-to-noise ratio. The system will evaluate the imaging quality of external visual monitoring equipment in real time (e.g., calculate image sharpness or contrast). When When the temperature drops below a preset threshold (e.g., in severe weather conditions such as rain, fog, or strong sunlight), the system will automatically... Set to zero, at this time .

[0037] This step implements an "all-weather robust monitoring" mechanism. In clear weather, the high-precision absolute coordinates of the visual data are used to eliminate the accumulated error caused by fiber optic integration. In extreme weather conditions, when visual data fails, the system smoothly switches to a deduction mode that relies solely on the internal model of the fiber. This dynamic weight adjustment strategy solves the dual problems of traditional machine vision monitoring being greatly limited by the environment and traditional fiber optic monitoring having large accumulated errors.

[0038] The implementation principle of this embodiment is as follows: This method effectively solves the problems of creep interference, low data accuracy, and lack of data fusion in existing technologies by constructing a complete system from data acquisition to final result output. Starting from synchronous data acquisition, it comprehensively acquires information related to tower deformation, then removes temperature interference through mechanical strain demodulation, then eliminates the influence of concrete creep through a creep stripping step, then obtains the theoretical reference displacement through reference deformation field reconstruction, and finally optimizes the results using multi-source data fusion correction.

[0039] Example 2 The deformation monitoring device for concrete tower cylinders provided in this application includes an acquisition module, a preprocessing module, a creep stripping module, a reference deformation field reconstruction module, and a multi-source data fusion correction module. The modules cooperate with each other to complete tasks such as data acquisition, preprocessing, creep stripping, reference deformation field reconstruction, and multi-source data fusion correction in sequence, which can efficiently complete the deformation monitoring of concrete tower cylinders.

[0040] Specifically, the acquisition module includes a fiber Bragg grating demodulator, a parallel temperature sensor, and an industrial camera interface.

[0041] The fiber optic grating demodulator is used to acquire the center wavelength drift of the fiber optic grating sensor 120 embedded in the concrete tower wall 100. It typically consists of a light source, a spectrum analyzer, and a data processing unit. The light emitted from the light source undergoes a spectrum change after passing through the fiber optic grating sensor 120. The spectrum analyzer analyzes the changed spectrum to obtain the center wavelength shift, and the data processing unit records and transmits this data. Specifically, the fiber optic grating sensor 120 is arranged in a double-helix symmetrical structure within the concrete tower wall 100, with a spatial phase difference of 180 degrees between the two helical optical fibers 110 to form a symmetrical fiber layout on both sides. A parallel temperature sensor is used to measure accompanying temperature data. These can be thermocouples, thermistors, etc., as mentioned earlier. The industrial camera interface is used to connect an external industrial camera to obtain the actual coordinates of the external calibration point 210 on the tower. The collection.

[0042] The data acquisition module is responsible for acquiring various data related to tower deformation, providing input for subsequent processing modules. Only by acquiring comprehensive and accurate data can the accuracy and reliability of subsequent processing be guaranteed.

[0043] Specifically, the preprocessing module includes an embedded FPGA chip and a temperature compensation algorithm.

[0044] The embedded FPGA chip has high-speed data processing capabilities, enabling it to process the center wavelength shift acquired by the fiber Bragg grating demodulator. Rapid processing is performed. The temperature compensation algorithm is based on the formula mentioned earlier. Temperature compensation is applied to the center wavelength drift to calculate the total mechanical strain including the creep component. .

[0045] The purpose of the preprocessing module is to perform preliminary processing on the collected data, removing interference factors such as temperature, and providing clean data for subsequent creep stripping. The high-speed processing capability of the FPGA chip can improve data processing efficiency and ensure the real-time performance of the entire monitoring system.

[0046] Specifically, the creep stripping module includes a memory and an MCU.

[0047] The memory contains a pre-set table of rheological parameters corresponding to the concrete mix design of the tower section. These parameters are used for calculations based on the generalized Kelvin model. The MCU (microcontroller) calculates the rheological parameters according to the generalized Kelvin model formula. calculate Cumulative creep strain over time And through subtraction Effective elastic strain is obtained.

[0048] The working process and technical effects of the above modules: The creep stripping module is equivalent to a "digital filter". It uses a physical model to filter out creep signals that are useless or even harmful to structural safety assessment, ensuring that the signal output to the next level module is a pure signal that reflects the actual stress state of the structure.

[0049] Specifically, the benchmark deformation field reconstruction module includes a high-performance industrial control computer, curvature fitting, and integral algorithm.

[0050] The high-performance industrial computer serves as the core computing device, running curvature fitting and integration algorithms. The curvature fitting algorithm, based on the effective elastic strain, follows the formula... Calculate the curvature distribution function along the axial direction of the tower. The integration algorithm uses the double integral formula. Calculate the height of the tower. theoretical reference displacement of the distribution .

[0051] The benchmark deformation field reconstruction module can convert effective elastic strain into displacement information, providing a theoretical basis for subsequent multi-source data fusion and correction.

[0052] Specifically, the multi-source data fusion correction module includes a Kalman filter algorithm and a data output unit.

[0053] The Kalman filter algorithm uses the theoretical reference displacement actual coordinates of the verification point The data is collected. As input, the optimal estimated gain is calculated. And according to the formula The final actual deformation of the output tower. Simultaneously, this module is also configured to monitor the visual signal-to-noise ratio (SNR). When the SNR is too low, it automatically sets the gain to zero to prevent low-quality visual data from contaminating accurate model predictions. The data output unit organizes and outputs the final results, which can be displayed in the form of reports, graphs, etc., for easy viewing and analysis by users.

[0054] The multi-source data fusion correction module can comprehensively utilize theoretical models and actual observation data to optimize the final deformation, thereby improving the accuracy and reliability of monitoring.

[0055] Example 3 The electronic device provided in this application includes a memory, a processor, and a computer program. When the processor runs the computer program stored in the memory, it can execute a deformation monitoring method for concrete towers, achieving accurate monitoring of the deformation of the concrete towers. This is because the computer program contains the various steps and algorithms of the aforementioned deformation monitoring method. The processor executes these steps sequentially according to the program's instructions, thus completing the entire process from data acquisition to final result output.

[0056] Specifically, storage media can be solid-state drives (SSDs) or random access memory (RAM). SSDs are characterized by high read and write speeds and high reliability, making them suitable for long-term storage of computer programs and related data. Random access memory is used to temporarily store data and intermediate results during program execution, facilitating fast access by the processor.

[0057] The processor can be a high-performance processor such as an Intel Core series processor or an AMD Ryzen series processor. These processors have multi-core processing capabilities and high clock frequencies, enabling them to quickly execute various algorithms and calculations in computer programs, ensuring the real-time performance and accuracy of the monitoring process.

[0058] The computer program consists of a series of codes that implement steps such as synchronous data acquisition, mechanical strain demodulation, creep stripping and effective strain acquisition, baseline deformation field reconstruction, and multi-source data fusion correction. For example, in the synchronous data acquisition section, the program controls the corresponding sensors and equipment to collect data simultaneously; in the mechanical strain demodulation section, it performs calculations according to the temperature compensation formula; and in the creep stripping section, it calls the generalized Kelvin model for calculations, etc.

[0059] The implementation principle of this embodiment is as follows: the electronic device stores a computer program in its memory, and the processor runs the program, combining hardware and software to automate the monitoring of concrete tower deformation. Compared with traditional manual monitoring or manual calculation, the electronic device has higher efficiency and accuracy, and can reflect the deformation of the tower in real time and accurately, providing a convenient and reliable solution for the safety monitoring of civil engineering structures.

[0060] Example 4 The computer-readable storage medium provided in this application embodiment stores computer instructions thereon, which, when executed, enable the implementation of each step of the concrete tower deformation monitoring method. The computer-readable storage medium can be an optical disc, USB flash drive, portable hard drive, etc.

[0061] Optical discs are a common storage medium that uses lasers to record data onto the disc, offering advantages such as large storage capacity and portability. USB flash drives and portable hard drives, on the other hand, use flash memory chips for data storage, offering advantages such as small size and fast read / write speeds.

[0062] The computer instructions are written according to the deformation monitoring method described above. When these instructions are read and executed by the computer's processor, they sequentially complete operations such as synchronous data acquisition, mechanical strain demodulation, creep stripping and effective strain acquisition, reference deformation field reconstruction, and multi-source data fusion correction. For example, in the synchronous data acquisition stage, the instructions control the sensors and equipment to acquire data; in the mechanical strain demodulation stage, calculations are performed based on the temperature compensation formula, etc.

[0063] The implementation principle of this embodiment is as follows: a computer-readable storage medium provides a storable and disseminated carrier for the concrete tower deformation monitoring method. Users can insert the medium storing computer instructions into a computer or other device, allowing the processor to execute these instructions, thereby achieving the monitoring of the concrete tower deformation. This approach enables the monitoring method to be conveniently used in different devices and environments, improving its versatility and scalability.

[0064] The specific embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made in accordance with the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method of monitoring deformation of a concrete tower section, characterized by, Comprising: S1 data synchronous acquisition: In At any given moment, the center wavelength drift of the fiber optic grating sensor (120) embedded in the wall of the tower (100) is simultaneously acquired. Accompanying temperature data The actual coordinates of the verification point (210) obtained by the external visual monitoring equipment (220) of the tower (100) ; S2 mechanical strain demodulation: the center wavelength shift amount carries out temperature compensation processing, and calculates total mechanical strain containing a creep component ; S3 creep debonding and effective strain retrieval: based on rheological properties of concrete material calculations cumulative creep strain at time t and subtracting the cumulative creep strain to obtain the effective elastic strain causing instantaneous deformation of the structure ; S4 reference deformation field reconstruction: using the effective elastic strain fitting a curvature distribution function to the tower (100) axis and calculating the theoretical reference displacement of the tower (100) along the height distribution based on the curvature distribution function by double integration ; S5 multi-source data fusion correction: the theoretical reference displacement with the actual coordinates of the check point (210) input kalman filter, calculate the optimal estimation gain, output the final real deformation of the tower drum (100) .

2. The method of claim 1, wherein, In step S2, the total mechanical strain is calculated according to the formula: wherein is the initial central wavelength, is the effective photoelastic coefficient of the optical fiber (110), is the thermal expansion coefficient of the optical fiber (110), is the thermo-optic coefficient, is the temperature variation measured by the parallel temperature sensor; said is passed as an input parameter to step S3.

3. The method of claim 1, wherein, In step S3, the effective elastic strain The calculation method is as follows: Cumulative creep strain is calculated using the generalized Kelvin model : where, is the tower (100) prestress level, and is the elastic modulus and the hysteresis time of the model's first element; Performing the peeling operation gives the effective elastic strain: Passing the As the only source of input for the calculation of the curvature, it is passed to step S4.

4. The method of claim 1, wherein, In step S4, the theoretical reference displacement is calculated by the formula: wherein is the curvature of the tower drum (100) at the height , which is determined by the effective elastic strain calculated for the two symmetric sides of the tower drum (100) in step S3: wherein and are the effective elastic strains calculated for the two symmetric sides of the tower drum (100), is the sensor transverse spacing at the height . The are passed as state predictions to step S5.

5. The method of claim 1, wherein, In step S5, the final actual deformation amount The calculation formula is: in: At the height of the verification point (210) The observations acquired by the vision device (220); It is the predicted value at that height output by step S4; The observation matrix; This is the Kalman gain matrix, used to balance model prediction error with visual observation error.

6. The method of monitoring deformation of a concrete tower section of claim 5, wherein, The Kalman gain matrix is updated depending on the visual signal-to-noise ratio , when is below a preset threshold, is automatically set to zero, in which case .

7. A deformation monitoring device for a concrete tower section for carrying out the method according to any one of claims 1 to 6, characterized by The fiber grating sensor (120) is arranged in a double helix symmetric structure in the tower drum (100) wall, and the spatial phase difference of the two helix optical fibers (110) is 180 degrees to form the symmetric two-side optical fiber (110) layout of claim 4. The collection module is used for collecting the center wavelength drift amount of the fiber grating sensor (120) embedded in the wall of the tower drum (100) , the temperature data accompanying the temperature data , and the actual coordinates of the check point (210) obtained by the visual monitoring device (220) outside the tower drum (100) at the moment; Preprocessing module: for processing the center wavelength shift amount carries out temperature compensation processing to calculate total mechanical strain including a creep component ; creep debonding module for calculating based on rheological properties of concrete material cumulative creep strain at time t and subtracting the cumulative creep strain to obtain the effective elastic strain causing instantaneous deformation of the structure ;​ reference deformation field reconstruction module: for reconstructing a reference deformation field using the effective elastic strain fitting a curvature distribution function to the tower (100) in axial direction and calculating the theoretical reference displacement of the tower (100) along the height distribution based on the curvature distribution function by double integration ; Multi-source data fusion correction module: for correcting the theoretical reference displacement with the actual coordinates of the check point (210) Input Kalman filter, calculate the optimal estimation gain, output the final real deformation of the tower (100) .

8. The apparatus for monitoring deformation of a concrete tower section of claim 7, wherein, The processor executes the computer program to perform the method of any one of claims 1 to 6.

9. An electronic device comprising a memory and a processor, said memory having stored thereon a computer program, characterized in that, 10. A computer readable storage medium having stored thereon computer instructions that, when executed, implement the method steps of any one of claims 1 to 6. ​

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