A support frame monitoring system based on vibration analysis

Abstract

The present invention discloses a support frame monitoring system based on vibration analysis, which relates to the technical field of structural health monitoring. Multiple sensors are used to synchronously collect the vibration wave signals and geometric deformation signals of the support frame under dynamic loads; a local vibration wave and geometric deformation coupling propagation modeling module is utilized to simulate the propagation of the vibration wave in the support frame and its interaction with local deformation; through a non-linear wave effect analysis module, the distortion effect of minute geometric deformation on the vibration wave is identified, and a quantitative relationship between the vibration wave propagation and minute geometric deformation is established; an adaptive correction algorithm module generates design parameters for adjusting the geometric shape or material properties; a time-frequency and space decoupling analysis module captures the interaction between the vibration wave propagation mode and geometric deformation in each region. The monitoring system of the present invention can monitor and precisely correct the vibration characteristics of the support frame in real time, significantly improving the safety and reliability of the structure, and is applicable to the health management of various engineering structures.

Description

Technical Field

[0001] The present invention relates to the technical field of structural health monitoring, and particularly to a support frame monitoring system based on vibration analysis. Background Art

[0002] Under dynamic loads and periodic vibrations, the local deformation and overall vibration of the support frame exhibit complex wave propagation characteristics. Especially at the contact points, joints, or deformed parts of the structure, the propagation and feedback mechanisms of vibration waves present complex non-linear characteristics. Existing vibration monitoring and analysis methods often fail to accurately capture the wave characteristics of these local deformations, especially in high-frequency or multi-dimensional vibration responses. Since the small deformations and fluctuations of the support frame usually propagate in different forms in different regions, the responses of existing methods to these fluctuations are mostly limited to traditional time-domain and frequency-domain analyses, and it is difficult to delve into the spatial characteristics of vibration wave propagation and the interaction between them and geometric deformations. Summary of the Invention

[0003] The purpose of the present invention is to solve the problems in the background art, and to propose a support frame monitoring system based on vibration analysis.

[0004] To achieve the above purpose, the present invention adopts the following technical solutions:

[0005] A support frame monitoring system based on vibration analysis, comprising:

[0006] A data acquisition module that synchronously acquires vibration wave signals and geometric deformation signals of the support frame under dynamic loads through multiple sensors. The vibration wave signals are time-domain waveforms, and the geometric deformation signals are strain and displacement data of each part of the support frame. All signals are marked with time stamps and form a first data set;

[0007] A local vibration wave and geometric deformation coupled propagation modeling module that establishes a local vibration wave propagation and geometric deformation coupling model based on the first data set, simulates the influence of the local deformation area of the support frame on the vibration wave propagation, and forms a second data set with the attenuation, reflection, non-linear effects, sub-harmonic and sub-harmonic generation effects of the vibration wave under high-frequency conditions;

[0008] A non-linear wave effect analysis module that performs non-linear wave analysis based on the second data set, identifies the distortion effect of small geometric deformations on vibration waves, and establishes a quantitative relationship between vibration wave propagation and small geometric deformations, revealing the fatigue and stress concentration of the support frame, thereby generating a third data set;

[0009] An adaptive correction algorithm module predicts the vibration characteristics of the support frame according to the third data set through an adaptive correction algorithm, generates design parameters for adjusting the geometric shape or material properties of the support frame, and reduces vibration resonance and distortion effects;

[0010] A time-frequency and space decoupling analysis module independently analyzes the spatial modes of vibration waves in sub-regions based on the design parameters by combining time-frequency analysis and space decoupling methods, captures the interaction between the propagation modes of vibration waves and geometric deformations in each region, establishes a quantitative model between vibration waves and geometric deformations, and further reveals the coupling effect between vibration modes and geometric deformations in different regions, providing data support for subsequent optimization of the support frame and vibration correction.

[0011] Preferably, the local vibration wave and geometric deformation coupling model is established through the following steps: According to the first data set, an influence model of the local deformation region of the support frame on the propagation of vibration waves is established through finite element analysis (FEA); the propagation of vibration waves under dynamic loads of the support frame is simulated, considering the influence of the local deformation region on the attenuation, reflection, and nonlinear effects of vibration waves; the local vibration wave and geometric deformation coupling model is represented by the following formula: Where: represents the displacement field of the support frame at position and time ; represents the strain field of the local region, reflecting the influence of geometric deformation; represents the vibration wave propagation speed, which is affected by local geometric deformation; represents the initial condition.

[0012] Preferably, the nonlinear wave effect analysis module includes: identifying the nonlinear components in the vibration wave through time-frequency analysis methods; identifying the harmonic, sub-harmonic, and sub-sub-harmonic components caused by minute geometric deformations through high-order Fourier analysis; establishing a quantitative relationship between minute geometric deformations and vibration wave propagation based on the analysis results obtained through time-frequency analysis and high-order Fourier analysis to form a third data set; the simulation of the nonlinear wave effect is carried out based on the second data set through the following formula: Where: represents the nonlinear amplitude at frequency ; is the nonlinear wave coefficient, representing the intensity of the th harmonic; is the th harmonic phase.

[0013] Preferably, the adaptive correction algorithm module includes: based on the third data set, training a model through machine learning methods to optimize the prediction of the vibration characteristics of the support frame; generating design parameters for adjusting the geometric shape or material properties of the support frame according to the prediction results to reduce vibration resonance and distortion effects and optimize the dynamic response of the support frame; and performing according to the following formula: Where: represents the geometric shape adjustment amount; and are the predicted and actual vibration frequency changes respectively; and are the predicted and actual strain data respectively; is the weight coefficient.

[0014] Preferably, the time-frequency and spatial decoupling analysis module includes: using time-frequency analysis methods to extract the frequency-domain characteristics of vibration waves; dividing the spatial propagation mode of vibration waves into regions, and using spatial decoupling techniques to independently analyze local regions to identify the interaction between the vibration wave propagation mode and geometric deformation in different regions; combining the time-frequency analysis and spatial decoupling through the following formula: Wherein, is the frequency-domain vibration mode, is the frequency, is the spatial coordinate.

[0015] Preferably, the nonlinear effects of vibration waves caused by minute geometric deformations include the generation of sub-harmonics and sub-harmonics, and the generation effects are corrected by parameter adjustment in the nonlinear wave effect analysis module. The minute geometric deformations include minute displacements of the structure and strains in local regions.

[0016] Preferably, the spatial decoupling analysis of the vibration wave propagation is carried out through the region independent analysis module, and a multi-region decoupling model is used to independently model the vibration wave to optimize the vibration analysis effect of the local and global regions.

[0017] Preferably, the data acquisition module synchronously acquires vibration signals and geometric deformation signals through a multi-sensor cluster. Among them, the vibration signals include acceleration signals and displacement signals, and the geometric deformation signals include strain signals and displacement field data.

[0018] Preferably, the time-frequency and spatial decoupling analysis module performs multi-scale decomposition on the vibration wave signal by using Wavelet Transform and Short-Time Fourier Transform, so as to extract the vibration wave propagation mode and geometric deformation information at different scales respectively, and optimize the monitoring of the support frame.

[0019] Preferably, the adaptive correction algorithm module generates design parameters for adjusting the geometric shape or material properties of the support frame by real-time analysis of the changing trends of the vibration data and the geometric deformation data, specifically including: collecting vibration data through sensors, analyzing the vibration mode and geometric deformation of the support frame, and identifying stress concentration areas in various parts; based on vibration and strain analysis, generating design parameters for adjusting the physical properties of existing materials to optimize the dynamic performance of the system.

[0020] The present invention has the following beneficial effects:

[0021] 1. In the present invention, the coupled propagation modeling of local vibration waves and geometric deformations is combined with the nonlinear wave effect analysis module to identify and quantify the influence of small geometric deformations on vibration wave propagation, thereby revealing the fatigue and stress concentration of the support frame. The adaptive correction algorithm module analyzes the monitoring data through machine learning technology and provides design parameters for automatically adjusting the geometric shape or material properties of the support frame to optimize its dynamic response and reduce vibration resonance and distortion effects. The time-frequency and spatial decoupling analysis module further provides an in-depth understanding of the vibration wave propagation mode, allowing the monitoring system to accurately capture the interaction between the vibration wave propagation mode and geometric deformation in each area.

[0022] 2. The present invention significantly improves the accuracy and efficiency of monitoring, allowing engineers to understand the health status of the support frame in real time. Secondly, by identifying potential structural problems at an early stage, the system significantly reduces the risk of unexpected failures and enhances the safety of the structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a system architecture diagram of a support frame monitoring system based on vibration analysis proposed by the present invention;

[0024] Figure 2 is the first axial pressure monitoring diagram in the present invention;

[0025] Figure 3 This is the second axial pressure monitoring diagram in the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] This implementation plan aims to achieve real-time monitoring and data collection of key areas in the high-formwork support system by precisely arranging sensors, so as to comprehensively evaluate the deformation, settlement, stress, and vibration conditions of the formwork. Through the sensors arranged at the key parts of the structure, combined with time-frequency analysis and spatial decoupling technology, the coupled analysis of vibration wave propagation and geometric deformation is optimized, thereby improving the safety, stability, and construction accuracy of the overall structure. Through this plan, the stress condition and deformation of the support system can be monitored in real time, potential safety hazards can be prevented, the stability of the formwork and support frame during the high-formwork construction process can be ensured, and the construction risks caused by excessive formwork settlement or deformation can be reduced.

[0028] As Figures 1 - 3 shown, a support frame monitoring system based on vibration analysis proposed by the present invention.

[0029] 1. In one embodiment, the data acquisition module: sensors at the key parts of the support frame. Monitoring layout principle: Real-time monitoring should be carried out on parameters such as formwork settlement, vertical rod axial force, member inclination angle, acceleration, strain, and overall horizontal displacement of the support frame at key parts or weak parts of the high-formwork, mainly including:

[0030] Overall horizontal displacement of the support frame: Horizontal displacement sensors are arranged at key nodes (support points and bearing points).

[0031] Settlement sensors, strain gauges, stress sensors. In the middle of the large-span cast-in-place concrete slab: at the middle and mid-span positions of the slab.

[0032] Settlement sensors, displacement sensors. Layout of beam span measurement points: When the beam span is less than 9 meters, at 1 / 2 span; when it exceeds 9 meters, at 1 / 4, 1 / 2, and 3 / 4 positions.

[0033] Support settlement sensors, vertical rod axial force sensors, inclination sensors. Layout of inclination sensors: At 2 / 3 to 3 / 4 of the height of the vertical rods of the support frame.

[0034] Electronic inclination sensors. Layout of axial force sensors: At the key positions between the top bracket and the formwork.

[0035] Pressure sensors or force sensors. Layout of settlement monitoring: Below the key support points at the bottom of the formwork.

[0036] Among them, the data acquisition frequency: the acquisition frequency of vibration signals (acceleration signals and displacement signals) is from 1000 Hz to 5000 Hz to ensure that high-frequency vibration modes are captured. The acquisition frequency of geometric deformation signals (strain and displacement field data) is from 500 Hz to 2000 Hz, which is adapted according to the deformation rate. All acquired signals will be marked with timestamps to ensure that the data can be synchronously associated with factors such as actual load changes and external interferences. Denoising processing is performed on the acquired original signals, and technologies such as Kalman filtering are used to remove measurement errors and external noises to ensure the accuracy of the data.

[0037] 2. In one embodiment, the local vibration wave and geometric deformation coupled propagation modeling module: obtains a first data set from the data acquisition module, including vibration wave signals (such as time-domain waveform signals like acceleration and displacement) and geometric deformation signals (such as strain and displacement field data of each part of the support frame). According to the first data set, an influence model of the local deformation area of the support frame on the vibration wave propagation is established by the finite element analysis method. The specific operations are as follows: Geometric modeling is performed on the support frame to construct a support frame model including the local deformation area; dynamic loads (such as vibrations, external impacts, etc.) are applied to simulate the deformation response of the support frame under different load conditions; the support frame model is discretized and divided into several small units for numerical solution.

[0038] Simulate the propagation of vibration waves in the support frame, considering the influence of local deformation on the vibration wave propagation. The specific operations are as follows: In the finite element model, a vibration source (such as an external vibration source or mechanical impact) is applied and the propagation of the generated vibration wave is simulated; consider the influence of the local deformation area of the support frame on the vibration wave, such as effects like attenuation, reflection, and refraction of the vibration wave; use the wave equation to simulate the propagation process of the vibration wave in the support frame, and incorporate the nonlinear effects caused by deformation, and the generation effects of sub-harmonics and sub-harmonics into the model.

[0039] Couple the propagation of the vibration wave and the influence of geometric deformation to form a coupled propagation model of local vibration wave and geometric deformation. The specific steps include: Define the interaction relationship between the vibration wave and geometric deformation. This relationship is described by the stress-strain equation, combined with the strain data and displacement field data of each part of the support frame. During the modeling process, consider the influence of deformation on the vibration wave propagation, such as the influence of strain changes in the local deformation area on the vibration wave speed and propagation direction. Convert the model into a computable mathematical formula, and the specific formula is as follows: Where: represents the displacement field of the support frame at position and time . represents the strain field of the local area, reflecting the influence of geometric deformation. represents the vibration wave propagation speed, which is affected by local geometric deformation. Represents the initial condition, i.e., the action of the vibration source.

[0040] In the process of establishing the coupled model, consider the nonlinear wave effect, especially the nonlinear distortion effect of tiny geometric deformation on the vibration wave. The operations include: identifying the nonlinear waves generated due to local geometric deformation, such as the generation of subharmonics and sub-harmonics. Modeling these wave effects through the nonlinear wave equation and adding the nonlinear terms caused by deformation during the simulation process.

[0041] Through the iterative optimization process, adjust the model parameters to ensure that the influence of local deformation can be accurately reflected in the propagation process of the vibration wave. The optimization methods include: using the least squares method to adjust the model parameters to minimize the deviation between the simulation results and the actual observed data. Using sensitivity analysis to evaluate the influence of each parameter on the propagation of the vibration wave and adjusting the influence parameters in the local deformation area.

[0042] Output the calculation results of the coupled propagation model, including the time and space characteristics of the vibration wave propagation, the vibration wave attenuation, reflection, etc. in each region. According to the results of the coupled propagation model, generate the second data set, which includes the propagation mode of the vibration wave, attenuation information, nonlinear effects, etc.

[0043] Through the above operation steps, the local vibration wave and geometric deformation coupled propagation modeling module can establish an accurate model of the influence of the local deformation of the support frame on the vibration wave propagation, and provide data support for subsequent nonlinear wave effect analysis, adaptive correction, and time-frequency and space decoupling analysis.

[0044] 3. In one embodiment, the nonlinear wave effect analysis module: Based on the second data set (generated by the local vibration wave and geometric deformation coupled propagation modeling module), conduct a detailed analysis of the nonlinear wave effect of the support frame vibration wave, identify the distortion effect of tiny geometric deformation on the vibration wave, and establish a quantitative relationship between the vibration wave propagation and geometric deformation.

[0045] Receive the second data set from the local vibration wave and geometric deformation coupled propagation modeling module, which includes information such as the simulated vibration wave propagation characteristics, the influence of local deformation, and nonlinear effects. The data content includes the time-domain signal of the vibration wave, deformation strain data, wave propagation speed, etc.

[0046] Time-frequency analysis: Through time-frequency analysis methods, decompose the frequency components in the vibration signal and identify the nonlinear components. The specific operations include: conducting multi-scale time-frequency analysis on the vibration wave signal, extracting the time-frequency characteristics of the vibration wave, and identifying the nonlinear changes during the wave process. Using time-frequency diagrams to analyze the spectral components in each time period, especially paying attention to the influence of tiny geometric deformation on the vibration wave, and identifying the time periods when nonlinear frequencies (such as subharmonics and sub-harmonics) are generated.

[0047] Decompose the vibration wave signal through high-order Fourier transform to further identify the harmonics, sub-harmonics, and super-harmonics caused by minute geometric deformations. The specific operations are as follows: Conduct high-order Fourier analysis on the vibration wave signal, extract the spectral components of different orders, and identify the non-linear fluctuations caused by minute geometric deformations. Calculate and analyze the non-linear fluctuation coefficient to evaluate the influence of harmonics, sub-harmonics, and super-harmonics on the propagation characteristics of the vibration wave.

[0048] Based on the results of time-frequency analysis and high-order Fourier analysis, calculate the non-linear fluctuation coefficient to quantitatively describe the wave distortion effect caused by minute geometric deformations. The formula is: Where: represents the non-linear amplitude at frequency . is the non-linear fluctuation coefficient, representing the intensity of the th sub-harmonic. is the th sub-harmonic phase.

[0049] According to the above analysis results, establish a quantitative relationship between minute geometric deformations and the propagation of vibration waves. The specific steps are as follows: Establish a mapping relationship through the non-linear fluctuation coefficient and minute geometric deformation data (such as strain, displacement, etc.). Adopt multiple regression analysis or the support vector machine (SVM) machine learning method to fit the quantitative relationship between geometric deformation and non-linear fluctuation to form a third data set. This relationship can be described by the following formula: Where: represents the frequency shift caused by geometric deformation. is the original frequency. , is the model coefficient, representing the influence of geometric deformation on frequency. and are the strain and displacement data of the local area respectively. is the error term.

[0050] Based on the distortion effect of minute geometric deformations on vibration waves, further analyze the fatigue and stress concentration of the support frame. The specific operations are as follows: Use the stress-strain analysis method to identify the stress concentration areas of each part of the support frame according to the stress changes caused by local deformations. Combine the propagation characteristics of vibration waves to analyze the influence of the fatigue accumulation effect on the support frame and predict potential failure points and damage areas.

[0051] Output the results of the non - linear wave effect analysis, including: the non - linear wave coefficient caused by minute geometric deformation. The offset of the vibration wave frequency and its quantitative relationship with geometric deformation. The fatigue and stress concentration conditions of the support frame, providing data support for subsequent automatic adjustment and optimization. Through the above steps, the non - linear wave effect analysis module can identify and quantitatively describe the impact of minute geometric deformation on the propagation of vibration waves, providing a scientific basis for the health monitoring and optimization of the support frame.

[0052] 4. In one embodiment, the adaptive correction algorithm module: Based on the third data set (generated by the non - linear wave effect analysis module), predicts the vibration characteristics of the support frame through an adaptive correction algorithm, generates design parameters for adjusting the geometric shape or material properties of the support frame, reduces vibration resonance and distortion effects, and optimizes the dynamic response of the support frame.

[0053] Receives the third data set from the non - linear wave effect analysis module. This data set includes the non - linear wave characteristics of the vibration wave, the quantitative relationship of minute geometric deformation, and the fatigue and stress concentration analysis results. The data content includes vibration signal error terms, non - linear wave coefficients, the change range of vibration frequencies, strain and displacement data, etc. Based on the third data set, an adaptive correction model is trained using support vector machine (SVM), random forest, or deep neural network. The training process includes: dividing the data set into a training set and a validation set. The training set is used for model training, and the validation set is used to test the accuracy of the model. The cross - validation method is used to improve the robustness of the model, ensuring consistent performance on different data sets. During the model training process, the model parameters are adjusted through gradient descent to minimize the error when the model predicts vibration characteristics.

[0054] Predict the vibration characteristics of the support frame through the trained model. The specific steps are as follows: Input the vibration wave data, geometric deformation data, frequency offset data, etc. obtained from the non - linear wave effect analysis module. The prediction model generates prediction results of the vibration characteristics of the support frame according to the input data, including the predicted vibration frequency, amplitude, and possible resonance regions. The output prediction results are used for subsequent adjustment of geometric shape or material properties.

[0055] Through a real - time feedback mechanism, during vibration testing or actual use, continuously monitor the vibration state of the support frame and feed the real - time data back to the adaptive correction algorithm module. Through reinforcement learning or adaptive control algorithms, adjust the geometric shape and material properties according to the feedback data to ensure effective optimization of the vibration response of the support frame under dynamic loads. Output the adjusted geometric shape or material properties of the support frame and generate a design parameter report. Output the vibration characteristic prediction and optimization results, including the adjusted frequency, vibration amplitude, and material properties, and form corresponding technical documents or implementation plans.

[0056] Through the above steps, the adaptive correction algorithm module can optimize the geometric shape and material properties of the support frame during its use, ensuring that its vibration characteristics are effectively controlled and adjusted, thereby improving the stability and service life of the support frame under dynamic loads.

[0057] 5. In one embodiment, the time-frequency and spatial decoupling analysis module: combines time-frequency analysis methods with spatial decoupling techniques to independently analyze the spatial patterns of vibration waves in sub-regions, capturing the interaction between the vibration wave propagation patterns and geometric deformations in each region. Receives vibration wave signals and geometric deformation signals from the second dataset and the third dataset, including time-domain vibration waveforms, frequency-domain characteristics, and strain and displacement data of spatial positions.

[0058] Perform time-frequency analysis on the vibration wave signal through time-frequency analysis methods. The specific steps include: Short-Time Fourier Transform (STFT): Divide the signal into several small time windows and perform Fourier transform on each time window to obtain the spectral information at each moment. Wavelet transform: Decompose the vibration wave signal at multiple scales to capture the fluctuation characteristics in different frequency ranges, obtaining the time-frequency distribution map of the vibration wave signal. The results of time-frequency analysis will be further used for spatial decoupling to help identify the vibration wave propagation patterns in different regions.

[0059] Based on the frequency-domain characteristics of the vibration wave signal and the geometric deformation data, independently analyze the vibration wave propagation patterns in sub-regions through spatial decoupling techniques. The operation steps are as follows: Divide the support frame into several regions according to its geometric structure and vibration characteristics, and each region corresponds to different vibration wave propagation characteristics. Independently analyze the vibration waves in each region to identify the vibration modes in that region. Specifically, through Finite Element Analysis (FEA) or modal analysis methods, model the vibration modes, strain, and displacement data in each region.

[0060] Use modal decomposition or modal synthesis to decompose the vibration modes of the overall structure into independent vibration modes for each region to improve the vibration analysis accuracy of each region.

[0061] Based on the time-frequency and spatial decoupling analysis, further analyze the interaction between the vibration wave propagation patterns and geometric deformations. Perform through the following steps: Compare the vibration modes extracted through time-frequency analysis with the vibration characteristics of each region obtained from spatial decoupling analysis to identify the differences and similarities in the vibration modes of each region. Combine the spectral characteristics of the vibration wave with the geometric deformation data of each region to analyze the influence of strain and displacement on the vibration wave propagation patterns, especially how the deformation in different regions affects the vibration wave propagation within that region. Under high-frequency vibration conditions, consider the nonlinear effects caused by small geometric deformations and analyze how local geometric changes alter the vibration wave propagation characteristics, identifying possible sub-harmonic and sub-harmonic generation effects.

[0062] Based on the results of time-frequency analysis and spatial decoupling, a quantitative relationship between vibration waves and geometric deformation is established. A mathematical model is established through regression analysis or machine learning methods (such as support vector machines, neural networks) to describe the relationship between geometric deformation and vibration wave propagation mode. Including the following: The correlation between vibration wave frequency and amplitude and strain and displacement in each area. The influence of small geometric deformation (such as displacement, local strain) on vibration wave propagation speed, propagation direction, reflection and attenuation.

[0063] Output the vibration wave propagation mode, geometric deformation and vibration wave interaction data of each region, including: Frequency domain characteristics and spatial propagation mode of vibration waves. Correlation analysis results of vibration modes and geometric deformations of each region. Simulate the coupling effect of vibration waves and geometric deformations in different regions.

[0064] Through the data sharing and feedback mechanism with the adaptive correction algorithm module, the time-frequency and space decoupling analysis results are input into the adaptive correction algorithm module to optimize the geometric shape or material properties of the support frame.

[0065] The time-frequency and space decoupling analysis module interacts with the adaptive correction algorithm module to dynamically correct the support frame structure according to the vibration wave propagation mode and geometric deformation data to ensure the optimization of its dynamic response. Through the work of the time-frequency and space decoupling analysis module, various characteristics in vibration wave propagation can be accurately captured, and the coupling effect between vibration modes and geometric deformations in different regions can be further revealed, providing necessary data support for subsequent support frame optimization and vibration correction.

[0066] Store data in a database or cloud platform and display monitoring results through display devices.

[0067] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A support frame monitoring system based on vibration analysis, characterized in that: include: A data acquisition module, which synchronously acquires vibration wave signals and geometric deformation signals of the support frame under the action of dynamic loads through multiple sensors, wherein the vibration wave signals are time domain waveforms, and the geometric deformation signals are strain and displacement data of various parts of the support frame. In the sensor step, all signals are marked by time stamps to form a first data set; A local vibration wave and geometric deformation coupled propagation modeling module is used to establish a local vibration wave propagation and geometric deformation coupled model based on the first data set, simulate the influence of the local deformation area of ​​the support frame on the vibration wave propagation, and combine the attenuation, reflection, nonlinear effect, subharmonic and subharmonic generation effects of the vibration wave under high frequency conditions to form a second data set; The nonlinear wave effect analysis module performs nonlinear wave analysis based on the second data set, identifies the distortion effect of small geometric deformation on the vibration wave, and establishes a quantitative relationship between the vibration wave propagation and small geometric deformation, revealing the fatigue and stress concentration of the support frame, thereby generating the third data set; An adaptive correction algorithm module predicts the vibration characteristics of the support frame through an adaptive correction algorithm according to the third data set, generates design parameters for adjusting the geometric shape or material characteristics of the support frame, and reduces vibration resonance and distortion effects; The time-frequency and space decoupling analysis module conducts independent regional analysis on the spatial modes of vibration waves based on design parameters combined with time-frequency analysis and space decoupling methods, captures the interaction between the vibration wave propagation mode and geometric deformation in each region, establishes a quantitative model between vibration waves and geometric deformation, and further reveals the coupling effect between the vibration modes and geometric deformation in different regions, providing data support for subsequent support frame optimization and vibration correction.

2. A support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The local vibration wave and geometric deformation coupling model is established by the following steps: according to the first data set, a model of the influence of the local deformation area of ​​the support frame on the vibration wave propagation is established through finite element analysis FEA; the vibration wave propagation of the support frame under dynamic load is simulated, and the attenuation, reflection and nonlinear effects of the local deformation area on the vibration wave are considered; the local vibration wave and geometric deformation coupling model is established by the following formula: in: Indicates that the support frame is in position and time The displacement field at time ; It represents the strain field in the local area, reflecting the influence of geometric deformation; represents the vibration wave propagation speed, which is affected by the local geometric deformation; represents the initial condition.

3. A support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The nonlinear wave effect analysis module includes: identifying the nonlinear components in the vibration wave through the time-frequency analysis method; identifying the harmonic, subharmonic and subharmonic components caused by small geometric deformation through high-order Fourier analysis; establishing the quantitative relationship between small geometric deformation and vibration wave propagation based on the analysis results obtained through the time-frequency analysis and high-order Fourier analysis to form a third data set; the nonlinear wave effect analysis is simulated based on the second data set through the following formula: in: Indicates frequency The nonlinear amplitude at ; is the nonlinear fluctuation coefficient, indicating the The intensity of subharmonics; It is Phase of subharmonics.

4. A support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The adaptive correction algorithm module includes: based on the third data set, performing model training by machine learning method to optimize the prediction of the vibration characteristics of the support frame; generating design parameters for adjusting the geometric shape or material characteristics of the support frame according to the prediction results to reduce vibration resonance and distortion effects and optimize the dynamic response of the support frame; using the following formula: in: Indicates the amount of geometry adjustment; and are the predicted and actual vibration frequency changes, respectively; and are the predicted and actual strain data, respectively; is the weight coefficient.

5. The support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The time-frequency and space decoupling analysis module includes: using the time-frequency analysis method to extract the frequency domain characteristics of the vibration wave; dividing the spatial propagation mode of the vibration wave into regions, using the spatial decoupling technology to independently analyze the local regions, and identifying the interaction between the vibration wave propagation mode and the geometric deformation in different regions; the time-frequency analysis is combined with the spatial decoupling, through the following formula: in, is the vibration mode in the frequency domain, is the frequency, is the space coordinate.

6. The support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The nonlinear effect of vibration waves caused by the minute geometric deformation includes the generation of subharmonics and sub-harmonics, and the generation effect is corrected by adjusting parameters in the nonlinear wave effect analysis module. The minute geometric deformation includes minute displacement of the structure and strain in a local area.

7. The support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The spatial decoupling analysis of vibration wave propagation uses a regional independent analysis module and a multi-region decoupling model to independently model the vibration waves, thereby optimizing local and global vibration analysis effects.

8. The support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The data acquisition module synchronously acquires vibration signals and geometric deformation signals through a multi-sensor cluster, wherein the vibration signal includes an acceleration signal and a displacement signal, and the geometric deformation signal includes a strain signal and displacement field data.

9. The support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The time-frequency and space decoupling analysis module performs multi-scale decomposition of vibration wave signals by using wavelet transform and short-time Fourier transform, thereby extracting vibration wave propagation modes and geometric deformation information at different scales, thereby optimizing the monitoring of the support frame.

10. The support frame monitoring system based on vibration analysis according to claim 1, characterized in that: The adaptive correction algorithm module generates design parameters for adjusting the geometric shape or material properties of the support frame by real-time analysis of the changing trends of vibration data and geometric deformation data. Specifically, the module collects vibration data through sensors, analyzes the vibration mode and geometric deformation of the support frame, and identifies stress concentration areas in various parts; based on vibration and strain analysis, generates design parameters for adjusting the physical properties of existing materials to optimize the dynamic performance of the system.

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