A three-dimensional displacement high-precision monitoring method and system for an isolation bearing

Abstract

The application relates to the technical field of data processing, in particular to a three-dimensional displacement high-precision monitoring method and system for an isolation bearing, which comprises the following steps: acceleration data of the isolation bearing in different axial directions in a preset time period and a frequency spectrum diagram of each axial direction are acquired; a main seismic frequency is screened out according to the amplitude value distribution of each frequency in the frequency spectrum diagram of each axial direction; a relative energy value of each axial direction is obtained according to the amplitude value proportion of the main seismic frequency in the frequency spectrum diagram of each axial direction; the acceleration data of each axial direction is corrected according to the correlation of the acceleration data between each axial direction and other axial directions, in combination with the distribution of the acceleration data of each axial direction and the relative energy value, to obtain correction data of each axial direction; and three-dimensional displacement data of the isolation bearing is determined based on the integral results of the correction data of each axial direction. The application can effectively inhibit other interference components and improve the monitoring precision of the displacement data of the isolation bearing.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a method and system for high-precision three-dimensional displacement monitoring of seismic isolation bearings. Background Technology

[0002] Seismic isolation bearings are devices installed between the foundation and superstructure of a building, designed to reduce the impact of earthquakes on the building by absorbing and reducing the energy transmitted by seismic waves. By accurately monitoring the three-dimensional displacement of the seismic isolation bearings under seismic waves, the deformation of the bearings can be assessed in real time, determining their operational status and promptly identifying potential damage or failure risks. Furthermore, monitoring the three-dimensional displacement of the seismic isolation bearings under seismic waves helps optimize seismic isolation design and verify the effectiveness of seismic isolation, providing a reliable basis for subsequent engineering improvements.

[0003] High-precision monitoring of the three-dimensional displacement of seismic isolation bearings during earthquakes is typically achieved using the acceleration integration method. Accelerometers are commonly used to monitor the acceleration changes of seismic isolation bearings in real time under seismic loading. These sensors can accurately capture acceleration data of the bearings in the X, Y, and Z axes. By performing second-order integration on the acceleration data, the displacement of the bearings in the three axes can be calculated, thus providing a scientific basis for seismic design optimization and improving the seismic resistance and safety of buildings.

[0004] However, when using the acceleration integral method to determine the three-dimensional displacement of seismic isolation bearings under earthquakes, interference from other non-seismic signals may occur. These non-seismic signals may originate from equipment noise, temperature changes, or other environmental factors. Although these signals are unrelated to seismic waves, they can still affect the detection results of the acceleration sensor, thereby introducing errors and resulting in poor accuracy of the three-dimensional displacement detection results of the seismic isolation bearings. Summary of the Invention

[0005] To address the problem that existing methods for determining the three-dimensional displacement of seismic isolation bearings under earthquakes using the acceleration integration method suffer from poor accuracy due to the influence of other factors, this invention aims to provide a high-precision method and system for monitoring the three-dimensional displacement of seismic isolation bearings. The specific technical solution adopted is as follows:

[0006] In a first aspect, the present invention provides a method for high-precision three-dimensional displacement monitoring of seismic isolation bearings, comprising:

[0007] Acquire acceleration data of seismic isolation bearings in different axes and spectrum diagrams for each axis within a preset time period;

[0008] The main seismic frequency is selected based on the amplitude distribution of each frequency in the spectrum of each axis, and the relative energy value of each axis is obtained based on the amplitude proportion of the main seismic frequency in the spectrum of each axis.

[0009] Based on the correlation between acceleration data of each axis and other axes, and combined with the distribution of acceleration data and relative energy value of each axis, the acceleration data of each axis is corrected to obtain the corrected data of each axis.

[0010] Based on the integral results of the correction data for each axis, the three-dimensional displacement data of the seismic isolation bearing is determined.

[0011] Preferably, the step of selecting the dominant seismic frequency based on the amplitude distribution of each frequency in the spectrum of each axis specifically includes:

[0012] Based on the amplitude distribution of each frequency and its adjacent frequencies in the spectrum of each axis, and combined with the value of each frequency, the distribution characteristic value of each frequency in the spectrum of each axis is obtained.

[0013] Based on the distribution characteristics and amplitude distribution of each frequency across all axes, the seismic dominant frequency index for each frequency is obtained;

[0014] The frequency corresponding to the maximum value of the earthquake dominance index is taken as the earthquake dominance frequency.

[0015] Preferably, the step of obtaining the distribution characteristic value of each frequency in the spectrum of each axis based on the amplitude distribution of each frequency and its adjacent frequencies in the spectrum of each axis, combined with the value of each frequency, specifically includes:

[0016] For any axial spectrum, any frequency is selected as the chosen frequency.

[0017] Arrange all frequencies according to a preset order of values, and obtain the reference frequency adjacent to the selected frequency in the frequency arrangement order;

[0018] Based on the amplitude of the selected frequency and the amplitude of the reference frequency, determine the amplitude comparison coefficient; based on the negative correlation coefficient corresponding to the value of the selected frequency, determine the frequency characteristic coefficient.

[0019] The product of the amplitude comparison coefficient and the frequency characteristic coefficient is used as the distribution characteristic value of the selected frequency in the spectrum of any axis.

[0020] Preferably, obtaining the seismic dominance index for each frequency based on the distribution characteristic values ​​and amplitude distribution of each frequency across all axes specifically includes:

[0021] The product of the amplitude and distribution characteristic value of the selected frequency in the spectrum of each axis is used as the dominant frequency factor of each axis at the selected frequency; the sum of the dominant frequency factors of all axes at the selected frequency is used as the seismic dominant frequency index of the selected frequency.

[0022] Preferably, the step of correcting the acceleration data for each axis based on the correlation between the acceleration data of each axis and other axes, combined with the distribution and relative energy value of the acceleration data for each axis, to obtain corrected data for each axis, specifically includes:

[0023] Based on the combined results of the correlation between acceleration data for each axis and every other axis, the data availability factor for each axis is obtained;

[0024] Based on the available data factors for each axis and the equilibrium of acceleration data in the same axis, the relative distribution of data for each axis is analyzed. Combining the differences between the relative distribution of data and the relative energy values, the effective seismic wave factor for each axis is obtained.

[0025] By using the seismic wave effective factor for each axis, the acceleration data for each axis is corrected to obtain the corrected data for each axis.

[0026] Preferably, the step of obtaining the data availability factor for each axis based on the comprehensive result of the correlation between acceleration data of each axis and each other specifically includes:

[0027] Choose any one axis as the selected axis, and use each other axis except the selected axis as the reference axis;

[0028] Calculate the correlation coefficient between the selected axis and the acceleration data corresponding to each reference axis, and use the mean of the correlation coefficients between the selected axis and all reference axes as the available data factor for the selected axis.

[0029] Preferably, the step of analyzing the relative distribution of data for each axis based on the available data factor and the equilibrium of acceleration data for the same axis, and combining the differences between the relative data distribution and the relative energy value, to obtain the effective seismic wave factor for each axis specifically includes:

[0030] The product of the mean of all acceleration data along the selected axis and the available data factor is used as the response characteristic index of the selected axis; the ratio between the response characteristic index of the selected axis and the sum of the response characteristic indices of all axes is used as the relative contribution of the selected axis.

[0031] The difference between the relative contribution and relative energy value of the selected axis is negatively correlated and normalized to obtain the effective factor of the seismic wave along the selected axis.

[0032] Preferably, the step of correcting the acceleration data for each axis using the seismic wave effective factor for each axis to obtain corrected data for each axis specifically includes:

[0033] The product of the seismic wave effective factor for the selected axis and the acceleration data for each acceleration data point along the selected axis is used as the correction data for each acceleration data point along the selected axis.

[0034] Preferably, obtaining the relative energy value for each axis based on the amplitude proportion of the dominant seismic frequency for each axis specifically includes:

[0035] The ratio between the amplitude of the dominant seismic frequency in each axis and the sum of the amplitudes of the dominant seismic frequencies in all axes is taken as the relative energy value for each axis.

[0036] Secondly, the present invention provides a three-dimensional displacement high-precision monitoring system for seismic isolation bearings, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the computer program is executed by the processor, it implements the steps of a three-dimensional displacement high-precision monitoring method for seismic isolation bearings.

[0037] The embodiments of the present invention have at least the following beneficial effects:

[0038] This invention first acquires acceleration data and corresponding frequency spectra for each axis, extracting the frequency components for each axis. Then, firstly, based on the characteristics of the frequency distribution, it selects the dominant frequency for each axis that best matches the seismic wave distribution, determining the dominant seismic wave frequency. Secondly, the proportion of frequency amplitude at the dominant seismic frequency for each axis reflects the proportion of energy propagated by the seismic wave in each axis. Furthermore, it considers not only the correlation between acceleration data across different axes but also the distribution of acceleration data for each axis and the consistency between relative energy values. This ensures that the process of correcting the acceleration data for each axis fully considers the characteristics of seismic waves, retaining data with a higher degree of consistency with seismic wave characteristics. Finally, the corrected acceleration data is used for acceleration integration to obtain high-precision displacement values ​​for each axis of the seismic isolation bearing under seismic loading. This invention's correction process for the acceleration data of each axis strengthens the seismic wave-related components while suppressing noise or interference signals unrelated to seismic waves, thus obtaining more accurate acceleration data under the influence of seismic waves and improving the accuracy of the displacement data obtained by the final integration method. Attached Figure Description

[0039] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart of the steps of a three-dimensional high-precision displacement monitoring method for seismic isolation bearings provided by the present invention;

[0041] Figure 2 This is the acceleration variation curve of the X-axis over a period of time provided by the present invention;

[0042] Figure 3 This is the acceleration variation curve of the Y-axis over a period of time provided by the present invention;

[0043] Figure 4 This is the acceleration variation curve of the Z-axis over a period of time provided by the present invention;

[0044] Figure 5 This is a schematic diagram of the acceleration data of the X-axis over a preset time period provided by the present invention;

[0045] Figure 6 This is a schematic diagram of the acceleration data of the Y-axis over a preset time period provided by the present invention;

[0046] Figure 7 This is a schematic diagram of the acceleration data of the Z-axis over a preset time period provided by the present invention;

[0047] Figure 8 This invention provides a spectrum diagram of the X-axis within a preset time period.

[0048] Figure 9 This invention provides a spectrum diagram of the Y-axis within a preset time period.

[0049] Figure 10 This invention provides a spectrum diagram of the Z-axis within a preset time period.

[0050] Figure 11 This is a flowchart of the steps for obtaining correction data for each axis provided by the present invention. Detailed Implementation

[0051] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a three-dimensional high-precision displacement monitoring method and system for seismic isolation bearings proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0053] The following description, in conjunction with the accompanying drawings, details the specific scheme of a three-dimensional high-precision displacement monitoring method and system for seismic isolation bearings provided by the present invention.

[0054] Please see Figure 1 The diagram illustrates a flowchart of a high-precision three-dimensional displacement monitoring method for seismic isolation bearings according to an embodiment of the present invention. The method includes the following steps:

[0055] Step S100: Obtain the acceleration data of the seismic isolation bearing in different axes and the spectrum of each axis within a preset time period.

[0056] Specifically, this embodiment focuses on the acceleration data of seismic isolation bearings under three different axial directions during vibration. The three axes are the X-axis, Y-axis, and Z-axis, designed to capture the lateral, longitudinal, and vertical motion of the bearings in the horizontal plane, respectively. These three axes together form a three-dimensional orthogonal coordinate system. By installing sensors, the three-dimensional acceleration changes of the bearings under seismic loading can be captured in real time, laying the foundation for subsequent high-precision displacement calculations.

[0057] More specifically, this embodiment uses a MEMS accelerometer to collect acceleration data. As a specific example, the installation position of the MEMS accelerometer can be as follows: For the MEMS accelerometers on the X and Y axes: they can be installed on both sides of the seismic isolation bearing (or the upper and lower parts of the bearing) to ensure that acceleration in the horizontal plane (X-axis and Y-axis) can be monitored separately. For the MEMS accelerometer on the Z axis: it should be installed in the vertical direction of the seismic isolation bearing (usually located at the lower part or bottom surface of the bearing) to measure acceleration in the vertical direction. This is well-known technology and is only briefly introduced here. In other embodiments, implementers can set it according to the specific implementation scenario.

[0058] In this embodiment, when seismic waves act on the support, the sensor responds immediately and begins to capture changes in acceleration. The system records the acceleration data measured by the sensor in real time and generates acceleration change curves along three axes. Figure 2 , Figure 3 and Figure 4 As shown, the acceleration changes along the X, Y, and Z axes over a period of time are collected. Furthermore, this embodiment divides the earthquake process into several preset time periods, which helps to more accurately analyze the propagation characteristics of seismic waves in different time periods. The duration of each preset time period is equal.

[0059] As a concrete example, such as Figure 5 , Figure 6 and Figure 7 It shows a schematic diagram of the acceleration data of the three axes X, Y and Z within a preset time period, where the preset time period is 5 seconds long.

[0060] Finally, Fourier transforms were performed on the acceleration data of the seismic isolation bearings in each axis within the preset time period to obtain the spectrum of acceleration data for each axis, such as... Figure 8 , Figure 9 and Figure 10 As shown. The Fourier transform method is a well-known technique and will not be discussed in detail here.

[0061] Step S200: Select the main seismic frequency based on the amplitude distribution of each frequency in the spectrum diagram of each axis, and obtain the relative energy value of each axis based on the amplitude proportion of the main seismic frequency in the spectrum diagram of each axis.

[0062] Firstly, during an earthquake, the dominant frequency components of seismic waves determine the characteristics of the waves, especially their impact on structures. When performing Fourier transforms on the time-series accelerations along the X, Y, and Z axes, the resulting spectrograms reflect the vibration intensity of different frequency components. Specifically, seismic waves tend to exhibit a lower frequency range, with low-frequency components often representing the dominant seismic frequency. Lower frequencies and sharp peaks typically correspond to areas of concentrated energy transmission. Therefore, components with lower frequencies and sharp peaks in the spectrograms generally reflect the dominant frequency of the seismic wave well. Based on this characteristic, the most consistent dominant frequency characteristics, i.e., the dominant seismic frequency, are selected by analyzing the amplitude distribution of each frequency component in the spectrograms for each axis.

[0063] As a specific example, the method for selecting the main seismic frequency based on the amplitude distribution of each frequency in the spectrum of each axis can be implemented by steps S201 to S203.

[0064] Step S201: Based on the amplitude distribution of each frequency and its adjacent frequencies in the spectrum diagram of each axis, and combined with the value of each frequency, obtain the distribution characteristic value of each frequency in the spectrum diagram of each axis.

[0065] Specifically, the feature analysis process is exactly the same for the X, Y, and Z axes. This embodiment uses the spectrum of any one axis as an example for illustration. For example, taking the spectrum of the X-axis as an example, any frequency in the spectrum corresponding to the X-axis is selected as the chosen frequency.

[0066] The first step is to arrange all frequencies according to the preset order of their values, and then obtain the reference frequency adjacent to the selected frequency from the frequency arrangement.

[0067] like Figure 8 As shown, the peaks in the downward-facing spectrum along the X-axis are sharp at lower frequencies. Based on this characteristic, the amplitude distribution between each frequency and its two adjacent frequencies is analyzed. More specifically, in this embodiment, the preset order is ascending, meaning all frequencies in the downward-facing spectrum along the X-axis are arranged in ascending order of frequency value. In this arrangement, the frequency adjacent to the left of the selected frequency and the frequency adjacent to the right of the selected frequency are both recorded as adjacent reference frequencies.

[0068] It should be noted that this feature analysis is not performed when it is impossible to obtain two adjacent frequencies simultaneously.

[0069] The second step is to determine the amplitude comparison coefficient based on the amplitude of the selected frequency and the amplitude of the reference frequency; to determine the frequency characteristic coefficient based on the negative correlation coefficient corresponding to the value of the selected frequency; and to use the product of the amplitude comparison coefficient and the frequency characteristic coefficient as the distribution characteristic value of the selected frequency in the spectrum of any axis.

[0070] As a concrete example, if we take the i-th frequency in the spectrum along the X-axis as the selected frequency, then the distribution characteristic value of the selected frequency in the spectrum along the X-axis can be expressed by the formula:

[0071]

[0072] in, The distribution characteristic value of a selected frequency in the spectrum along the X-axis is represented by , where i represents the i-th frequency in the spectrum. This represents the amplitude corresponding to the selected frequency in the spectrum along the X-axis, which is also the amplitude corresponding to the i-th frequency in the spectrum along the X-axis. This represents the amplitude corresponding to a reference frequency in the spectrum along the X-axis, which is also the amplitude corresponding to the (i-1)th frequency in the spectrum along the X-axis. This represents the amplitude corresponding to another reference frequency in the spectrum along the X-axis, which is also the amplitude corresponding to the (i+1)th frequency in the spectrum along the X-axis. This indicates the frequency value corresponding to the selected frequency in the spectrum along the X-axis, for example, 5Hz. This represents an exponential function with the natural constant e as its base.

[0073] The amplitude comparison coefficient reflects the amplitude comparison between adjacent frequencies of the selected frequency in the spectrum. The larger the value, the larger the amplitude of the component at the selected frequency and the smaller the amplitude of the surrounding frequencies. This indicates that there is a greater degree of sharp peak at the selected frequency in the spectrum. These are frequency characteristic coefficients. By applying negative correlation processing to the frequency values, low-frequency features can be screened out.

[0074] When both the amplitude comparison coefficient and the frequency characteristic coefficient are large, it indicates that the amplitude distribution characteristics of the selected frequency conform to the characteristics of seismic waves to a greater extent, and thus the selected frequency is more likely to be the main frequency of seismic waves.

[0075] It should be understood that the amplitude corresponding to the frequency is the value of the vertical axis in the spectrum graph, and the frequency is the value of the horizontal axis in the spectrum graph.

[0076] Step S202: Based on the distribution characteristic values ​​and amplitude distribution of each frequency across all axes, the seismic dominant frequency index for each frequency is obtained.

[0077] During the propagation of seismic waves, the dominant frequency of the seismic wave typically influences vibrations along multiple axes. If, at a certain frequency, the spectral amplitudes of all three axes are high and conform to the dominant frequency of the seismic wave, it means that this frequency component has significant energy transfer in all three directions. This indicates that this frequency component closely matches the dominant frequency of the seismic wave and is likely the main frequency component of the seismic wave.

[0078] Specifically, seismic waves typically possess a dominant frequency during propagation, which can elicit strong responses in all directions. If a high amplitude of this frequency component is observed along all three axes while conforming to the seismic dominant frequency, it indicates that it makes a significant contribution to the propagation of seismic waves in all directions, thus suggesting that the frequency as a whole conforms to the seismic dominant frequency.

[0079] Based on this characteristic, the product of the amplitude and distribution characteristic value of the selected frequency in the spectrum of each axis is taken as the dominant frequency factor of each axis at the selected frequency; the sum of the dominant frequency factors of all axes at the selected frequency is taken as the seismic dominant frequency index of the selected frequency.

[0080] Step S203: The frequency corresponding to the maximum value of the earthquake dominant frequency index is taken as the earthquake dominant frequency.

[0081] The seismic dominance index for a selected frequency characterizes the degree to which the selected frequency conforms to the characteristics of seismic dominance across the three axes of X, Y, and Z. The larger the value of the seismic dominance index, the greater the degree to which the corresponding frequency conforms to the characteristics of seismic dominance, and thus the greater the likelihood that the corresponding frequency belongs to the dominant frequency of the seismic wave.

[0082] Secondly, the dominant frequency of an earthquake represents the main energy component in the propagation of seismic waves, typically the core frequency. At the dominant frequency, the vibration components along the X, Y, and Z axes reflect the energy distribution of the seismic wave in each direction. Based on this characteristic, by analyzing the amplitude proportion of the dominant frequency along each axis, the propagation of the seismic wave in each axis can be assessed, and the relative energy value of the seismic wave in each axis can be quantified.

[0083] Specifically, the ratio between the amplitude of the dominant seismic frequency in each axis and the sum of the amplitudes of the dominant seismic frequencies in all axes is used as the relative energy value for each axis.

[0084] By analyzing the amplitude proportions of frequency components corresponding to the principal frequency of an earthquake along different axes, the propagation characteristics of seismic waves in various directions can be revealed. If the amplitude proportion of a frequency component along a certain axis is large, it indicates that the seismic wave propagates with stronger energy in that direction; conversely, it indicates that the seismic wave propagates with weaker energy. In other words, the relative energy value corresponding to each axis characterizes the proportion of energy distribution of the seismic wave along each axis and is a quantitative indicator of the inherent characteristics of seismic waves.

[0085] Step S300: Based on the correlation between the acceleration data of each axis and other axes, and combined with the distribution of the acceleration data of each axis and the relative energy value, the acceleration data of each axis is corrected to obtain the corrected data of each axis.

[0086] To determine whether the accelerations along the X, Y, and Z axes conform to seismic wave characteristics, it's necessary to consider the consistency between the accelerations and the magnitude of seismic wave propagation energy, based on the comparability of the accelerations. Greater consistency indicates less interference with the seismic waves, requiring less correction to the original data. Conversely, less consistency indicates greater influence of other interfering signals on the effective seismic wave components represented by the acceleration data, necessitating greater correction to the original data.

[0087] Based on this, the first aspect is to analyze the data correlation between different axial down-acceleration data, the second aspect is to analyze the relative effectiveness of each axial down-acceleration data, and the third aspect is to analyze the consistency between the relative effectiveness of each axial down-acceleration data and the relative energy distribution. The results of the three aspects of feature analysis are combined to screen the effective seismic signals in each axial down-acceleration data and suppress non-seismic interference in order to achieve the correction operation of the acceleration data.

[0088] As a concrete example, such as Figure 11 As shown, the method for obtaining correction data for each axis can be implemented from step S301 to step S303.

[0089] Step S301: Based on the comprehensive result of the correlation between acceleration data of each axis and each other axis, obtain the data availability factor for each axis.

[0090] Seismic waves exhibit directionality during propagation, meaning that when they propagate along a specific direction, they affect vibrations along different axes. To determine the comparability of acceleration data along the X, Y, and Z axes, the correlation between accelerations along different axes was analyzed. If the Pearson correlation coefficient between the X, Y, and Z axis acceleration data approaches 1 over a certain period, it means that the acceleration data along these three axes change almost synchronously, reflecting their responses to the same seismic wave. Therefore, the closer the Pearson correlation coefficient between each axis and the other axes is to 1, the greater the comparability of the acceleration changes along the X, Y, and Z axes.

[0091] Based on this characteristic, when the combined result of the Pearson correlation coefficient of the acceleration data between each axis and the other axes is close to 1, it indicates that the characteristic distribution of the acceleration data of the three axes has a high degree of consistency, which in turn indicates that their response under the action of seismic waves is reliable.

[0092] Specifically, the first step is to select any one axis as the chosen axis and use every other axis as a reference axis. For example, if the axis corresponding to the X-axis is selected, then the axes corresponding to the Y-axis and Z-axis are both reference axes.

[0093] The second step is to calculate the correlation coefficient between the selected axis and the acceleration data corresponding to each reference axis, and use the mean of the correlation coefficients between the selected axis and all reference axes as the available data factor for the selected axis.

[0094] As a concrete example, the data for the selected axis can be expressed by the following formula using a factor: ,in This indicates the available data factor for the X-axis, which is the available data factor for the selected axis. This represents the set of axial downward acceleration data corresponding to the X-axis. This represents the set of axial downward acceleration data corresponding to the Y-axis. This represents the set of axial downward acceleration data corresponding to the Z-axis. The Pearson correlation coefficient represents the relationship between the accelerations along the X-axis and the Y-axis. This represents the Pearson correlation coefficient between the acceleration data corresponding to the X-axis and the acceleration data corresponding to the Z-axis.

[0095] The above calculation process reflects the combined results of the correlation coefficients between the acceleration data of the X-axis and Y-axis, and between the acceleration data of the X-axis and Z-axis, and provides a balanced representation of the availability and reliability of the acceleration data along the X-axis.

[0096] Step S302: Analyze the relative distribution of data for each axis based on the available data factors for each axis and the equilibrium of acceleration data for the same axis. Combine the differences between the relative data distribution and the relative energy values ​​to obtain the effective seismic wave factor for each axis.

[0097] Since the direction of seismic wave propagation is unique, the equilibrium of acceleration data in each axis should be consistent with the axial component of the direction of seismic wave propagation. If the effective distribution of acceleration data in a certain axis is close to the energy distribution in that axis, it means that the relationship between the acceleration data in that axis and the direction of seismic wave propagation is consistent, that is, the characteristic distribution of acceleration data in that axis conforms to the characteristics of seismic waves.

[0098] Specifically, this embodiment uses any one axis as an example, specifically the axis corresponding to the X-axis, which is the selected axis in this embodiment. The first step is to use the product of the mean of all acceleration data for the selected axis and the available data factor as the response characteristic index of the selected axis; the ratio between the response characteristic index of the selected axis and the sum of the response characteristic indices of all axes is used as the relative contribution level of the selected axis.

[0099] As a concrete example, the relative contribution of a selected axis can be expressed by the formula:

[0100]

[0101] in, This indicates the relative contribution of the selected axis, where X represents the axis corresponding to the X-axis. This represents the mean of all acceleration data along the X-axis. Factors can be used to represent the data corresponding to the X-axis along the axial direction. This represents the mean of all acceleration data along the W-axis. The W-axis represents the available data along the corresponding axis, and the values ​​of W include X, Y, and Z.

[0102] This reflects the intensity of the X-axis acceleration data. This reflects the availability and relevance of X-axis acceleration data. The larger the value of the response characteristic index, the stronger the availability of the X-axis acceleration data, the higher the synchronization between the X-axis acceleration data and the acceleration data of other axes, and the more likely it is caused by the same earthquake source.

[0103] It reflects the cumulative result of the total effective response of the seismic isolation bearing within the current preset time period. The ratio calculation result reflects the proportion of the effective response in the X-axis direction to the overall effective response, and reflects the relative effective contribution between the X-axis acceleration data and the overall three-dimensional data distribution.

[0104] The second step is to perform negative correlation normalization on the difference between the relative contribution and relative energy value of the selected axis to obtain the effective factor of the seismic wave along the selected axis.

[0105] The relative contribution of the selected axis reflects the proportion of the relative effective response between the acceleration data of the selected axis and all axes as a whole. The relative energy value of the selected axis reflects the proportion of the energy distribution of the seismic wave under the selected axis, representing the directional characteristics of the seismic wave in the X-axis direction.

[0106] The closer the relative contribution of the selected axis is to the relative energy value, the closer or more similar the actual acceleration distribution under the selected axis is to the actual energy distribution of the seismic wave under the selected axis. This indicates that the actual acceleration distribution under the selected axis conforms to the characteristics of the seismic wave to a greater extent, and that the acceleration data under the selected axis has more effective components and is less affected by interference.

[0107] The greater the difference between the relative contribution and the relative energy value of the selected axis, the greater the difference between the actual acceleration distribution and the actual energy distribution of the seismic wave under the selected axis. This indicates that the acceleration data under the selected axis is less effective and more susceptible to interference.

[0108] As a concrete example, the calculation process for the effective factor of seismic waves along a selected axis can be expressed by the formula: ,in, This represents the seismic wave efficacy factor along the selected axis, where X represents the axis corresponding to the X-axis. This indicates the relative contribution level of the selected axis. This indicates the relative energy value along the selected axis. It is a linear normalization function.

[0109] Thus, the effective factor of seismic waves for each axis can be obtained using the same method, which characterizes the extent to which the characteristic distribution of acceleration data for each axis conforms to the seismic wave characteristics.

[0110] Step S303: Using the effective factor of seismic waves for each axis, the acceleration data for each axis is corrected to obtain the corrected data for each axis.

[0111] In seismic wave analysis, to remove non-seismic wave interference signals, it is necessary to eliminate components unrelated to seismic waves from the acceleration data. The more the characteristic distribution of acceleration data along each axis conforms to the characteristics of seismic waves, the stronger the correlation between the acceleration data along that axis and the main energy propagation of seismic waves; in this case, the higher the degree to which the actual acceleration distribution along that axis can be preserved. Conversely, the greater the difference between the characteristic distribution of acceleration data along each axis and the characteristics of seismic waves, the weaker the correlation between the acceleration data along that axis and the main energy propagation of seismic waves; in this case, the lower the degree to which the actual acceleration distribution along that axis can be preserved.

[0112] Specifically, the product of the seismic wave effective factor for the selected axis and each acceleration data point along the selected axis is used as the correction data for each acceleration data point along the selected axis. It should be understood that for each acceleration data point along each axis within a preset time period, the seismic wave effective factor can be used for correction, resulting in the corresponding corrected acceleration data, which is the correction data.

[0113] The seismic wave effective factor reflects the effective intensity of the acceleration data along each axis that conforms to the characteristics of seismic waves. Using a product, the seismic wave-related components of the acceleration data along each axis can be enhanced while suppressing noise or interference signals unrelated to seismic waves. Correcting the actual acceleration data is equivalent to retaining the effective seismic wave components in the acceleration and removing other interference signals, thus obtaining more accurate acceleration data under the influence of seismic waves.

[0114] Step S400: Based on the integration results of the correction data for each axis, determine the three-dimensional displacement data of the seismic isolation bearing.

[0115] Specifically, within a preset time period, a double integration is performed on all corrected data for each axis to obtain the displacement data for the corresponding axis. In this embodiment, for the three different axes of X, Y, and Z, high-precision displacement data of the seismic isolation bearing within the preset time period can be obtained respectively, which can accurately reflect the high-precision displacement influence of seismic waves on the seismic isolation bearing in the three axes. If there are multiple preset time periods in the displacement monitoring process of the seismic isolation bearing, in other embodiments, the displacement data of all preset time periods can be accumulated to obtain the total displacement.

[0116] It should be noted that the method of double integration of acceleration is a well-known technique, that is, acceleration is the second derivative of displacement, which means that displacement can be obtained by double integration of acceleration, and will not be elaborated further here.

[0117] In summary, compared to existing technologies where the influence of non-seismic waves accumulates gradually through acceleration integration, leading to inaccurate three-dimensional displacement monitoring of seismic isolation bearings under earthquakes, this invention accurately obtains the high-precision three-dimensional displacements of seismic isolation bearings along the X, Y, and Z axes by analyzing the acceleration variation spectrum of the seismic isolation bearings in the X, Y, and Z axes under earthquakes. Specifically, firstly, Fourier transform analysis is used to analyze the spectrum of the X, Y, and Z axes over each time period to extract each frequency component, thereby determining the dominant frequency of the seismic wave. Next, the amplitude intensity of the X, Y, and Z axes at the dominant frequency is used to measure the main propagation energy of the seismic wave. Subsequently, the acceleration data for each axis is corrected based on whether the characteristic distribution of acceleration along the X, Y, and Z axes conforms to the characteristics of seismic waves, ensuring consistency with the seismic wave characteristics and removing non-seismic wave interference signals. Finally, the corrected acceleration data is used for acceleration integration to calculate the high-precision displacement values ​​of the seismic isolation bearings along the X, Y, and Z axes under earthquake loading.

[0118] This invention also provides a high-precision three-dimensional displacement monitoring system for seismic isolation bearings, including a memory, a processor, and a computer program stored in the memory and running on the processor. When executed by the processor, the computer program implements the steps of a high-precision three-dimensional displacement monitoring method for seismic isolation bearings. Since a detailed description of an embodiment of a high-precision three-dimensional displacement monitoring method for seismic isolation bearings has been provided, further elaboration will not be repeated here.

[0119] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for high-precision three-dimensional displacement monitoring of seismic isolation bearings, characterized in that, The method includes the following steps: Acquire acceleration data of seismic isolation bearings in different axes and spectrum diagrams for each axis within a preset time period; The main seismic frequency is selected based on the amplitude distribution of each frequency in the spectrum of each axis, and the relative energy value of each axis is obtained based on the amplitude proportion of the main seismic frequency in the spectrum of each axis. Based on the correlation between acceleration data of each axis and other axes, and combined with the distribution of acceleration data and relative energy value of each axis, the acceleration data of each axis is corrected to obtain the corrected data of each axis. Based on the integral results of the correction data for each axis, the three-dimensional displacement data of the seismic isolation bearing is determined; The process involves correcting the acceleration data for each axis based on the correlation between acceleration data for each axis and other axes, combined with the distribution and relative energy value of acceleration data for each axis, to obtain corrected data for each axis. Specifically, this includes: Choose any axis as the selected axis and each other axis as the reference axis; calculate the correlation coefficient between the acceleration data corresponding to the selected axis and each reference axis, and use the mean of the correlation coefficients between the selected axis and all reference axes as the data available factor for the selected axis; The product of the mean of all acceleration data along the selected axis and the available data factor is used as the response characteristic index of the selected axis; the ratio between the response characteristic index of the selected axis and the sum of the response characteristic indices of all axes is used as the relative contribution degree of the selected axis; the difference between the relative contribution degree and the relative energy value of the selected axis is negatively correlated and normalized to obtain the effective seismic wave factor of the selected axis. The product of the seismic wave effective factor for the selected axis and the acceleration data for each acceleration data point along the selected axis is used as the correction data for each acceleration data point along the selected axis.

2. The method for high-precision three-dimensional displacement monitoring of seismic isolation bearings according to claim 1, characterized in that, The process of selecting the main seismic frequency based on the amplitude distribution of each frequency in the spectrum of each axis specifically includes: Based on the amplitude distribution of each frequency and its adjacent frequencies in the spectrum of each axis, and combined with the value of each frequency, the distribution characteristic value of each frequency in the spectrum of each axis is obtained. Based on the distribution characteristics and amplitude distribution of each frequency across all axes, the seismic dominant frequency index for each frequency is obtained; The frequency corresponding to the maximum value of the earthquake dominance index is taken as the earthquake dominance frequency.

3. The method for high-precision three-dimensional displacement monitoring of seismic isolation bearings according to claim 2, characterized in that, The step of obtaining the distribution characteristic value of each frequency in the spectrum of each axis based on the amplitude distribution of each frequency and its adjacent frequencies in the spectrum of each axis, combined with the value of each frequency, specifically includes: For any axial spectrum, any frequency is selected as the chosen frequency. Arrange all frequencies according to a preset order of values, and obtain the reference frequency adjacent to the selected frequency in the frequency arrangement order; Based on the amplitude of the selected frequency and the amplitude of the reference frequency, determine the amplitude comparison coefficient; based on the negative correlation coefficient corresponding to the value of the selected frequency, determine the frequency characteristic coefficient. The product of the amplitude comparison coefficient and the frequency characteristic coefficient is used as the distribution characteristic value of the selected frequency in the spectrum of any axis.

4. The method for high-precision three-dimensional displacement monitoring of seismic isolation bearings according to claim 3, characterized in that, The process of obtaining the seismic dominance index for each frequency based on the distribution characteristics and amplitude distribution across all axes specifically includes: The product of the amplitude and distribution characteristic value of the selected frequency in the spectrum of each axis is used as the dominant frequency factor of each axis at the selected frequency; the sum of the dominant frequency factors of all axes at the selected frequency is used as the seismic dominant frequency index of the selected frequency.

5. A method for high-precision three-dimensional displacement monitoring of seismic isolation bearings according to claim 1, characterized in that, The process of obtaining the relative energy value for each axis based on the amplitude proportion of the main seismic frequency in the spectrum of each axis specifically includes: The ratio between the amplitude of the dominant seismic frequency in each axis and the sum of the amplitudes of the dominant seismic frequencies in all axes is taken as the relative energy value for each axis.

6. A high-precision three-dimensional displacement monitoring system for seismic isolation bearings, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the computer program is executed by the processor, it implements the steps of a three-dimensional high-precision displacement monitoring method for seismic isolation bearings as described in any one of claims 1-5.

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