Time synchronization monitoring methods, devices, terminal equipment, and storage media
By using modal analysis and error fitting techniques, the problem of asynchronous monitoring data in super high-rise buildings was solved, achieving low-cost data synchronization and improving the accuracy of structural damage identification and safety assessment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN URBAN PUBLIC SAFETY & TECH INST CO LTD
- Filing Date
- 2023-03-02
- Publication Date
- 2026-05-26
AI Technical Summary
Monitoring data from different locations in super high-rise buildings are out of sync over time, and traditional methods are costly and difficult to implement.
By collecting and monitoring data signals, modal analysis is performed to obtain intrinsic mode function signals. The fitting error is used to obtain the relative time error, and the error is eliminated to achieve data synchronization.
It reduces the cost of time synchronization monitoring and provides a more accurate data foundation for structural damage identification and safety assessment.
Smart Images
Figure CN116232520B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of time synchronization monitoring technology, and in particular to a time synchronization monitoring method, apparatus, terminal equipment, and storage medium. Background Technology
[0002] Structural health monitoring of super high-rise buildings has been widely applied. However, in order to achieve comprehensive monitoring of super high-rise buildings, a large number of monitoring sensors are usually deployed. These sensors are often placed in different locations of the super high-rise buildings, which leads to the problem of asynchronous monitoring data in the time synchronization monitoring of super high-rise buildings.
[0003] Traditional methods for solving the time synchronization problem in super high-rise buildings mainly involve: forming a network of sensors at different locations through optical fiber to eliminate time errors; however, adding new optical fibers inside super high-rise buildings is not only costly but also difficult to construct; or adding BeiDou time synchronization function to each monitoring sensor local network to eliminate time synchronization problems, but the implementation cost is too high and it is difficult to popularize. Summary of the Invention
[0004] The main objective of this application is to provide a time synchronization monitoring method, device, terminal equipment, and storage medium, which aims to solve the technical problem of time error in monitoring data from different locations during time synchronization monitoring of ultra-high-rise buildings. This can reduce the monitoring cost of time synchronization, synchronously analyze monitoring data from different locations, and thus provide a more accurate data foundation for structural damage identification and safety assessment.
[0005] To achieve the above objectives, this application provides a time synchronization monitoring method, the time synchronization monitoring method comprising:
[0006] Collect corresponding monitoring data signals for different locations of the preset building;
[0007] Modal analysis is performed on the monitoring data signal to obtain several corresponding intrinsic mode function signals;
[0008] The relative time error of the position is obtained by fitting the error between the intrinsic mode function signals.
[0009] Based on the relative time error, the errors between the monitoring data signals are eliminated to obtain synchronized monitoring data.
[0010] Optionally, the step of fitting the error between the intrinsic mode function signals to obtain the relative time error of the position includes:
[0011] The intrinsic mode function signal is simplified to obtain the corresponding analog function;
[0012] The relative time error of the position is obtained by fitting the error between the simulation functions.
[0013] Optionally, the step of fitting the error between the simulation functions to obtain the relative time error of the position includes:
[0014] Obtain a preset error fitting function, wherein the error fitting function includes the linear relationship between the simulation function and the preset acquisition period;
[0015] Based on the error fitting function, the simulation function and the acquisition period are calculated sequentially to obtain the relative time error of the position.
[0016] Optionally, the acquisition period includes at least one or more, and the step of calculating the simulation function and the acquisition period sequentially based on the error fitting function to obtain the relative time error of the position includes:
[0017] The corresponding simulation time error is obtained by substituting the acquisition period and the simulation function into the error fitting function in sequence.
[0018] The simulated time error is compared to obtain the relative time error of the position.
[0019] Optionally, the step of eliminating errors between the monitoring data signals based on the relative time error to obtain synchronized monitoring data includes:
[0020] Select any one of the monitoring data signals from the plurality of monitoring data signals as the reference signal;
[0021] Based on the relative time error, the reference time error of the monitoring data signal relative to the reference signal is calculated sequentially;
[0022] After eliminating the reference time error, synchronized monitoring data is obtained.
[0023] Optionally, the step of eliminating errors between the monitoring data signals based on the relative time error to obtain synchronized monitoring data includes:
[0024] The reference time error is sequentially transformed and removed to obtain the monitoring data of the building.
[0025] Optionally, the step of performing modal analysis on the monitoring data signal to obtain a plurality of corresponding intrinsic mode function signals includes:
[0026] Modal analysis is performed on the monitoring data signal at any time point to obtain several corresponding intrinsic mode function signals.
[0027] This application also proposes a time synchronization monitoring device, which includes:
[0028] The signal acquisition module is used to collect corresponding monitoring data signals for different locations of the preset building;
[0029] The modal analysis module performs modal analysis on the monitoring data signal to obtain a number of corresponding intrinsic mode function signals;
[0030] An error fitting module is used to fit the error between the intrinsic mode function signals to obtain the relative time error of the position.
[0031] An error elimination module is used to eliminate errors between the monitoring data signals based on the relative time error, so as to obtain synchronized monitoring data.
[0032] This application also proposes a terminal device, which includes a memory, a processor, and a time synchronization monitoring program stored in the memory and executable on the processor. When the time synchronization monitoring program is executed by the processor, it implements the steps of the time synchronization monitoring method described above.
[0033] This application also proposes a computer-readable storage medium storing a time synchronization monitoring program, which, when executed by a processor, implements the steps of the time synchronization monitoring method described above.
[0034] The time synchronization monitoring method, device, terminal equipment, and storage medium proposed in this application collect corresponding monitoring data signals at different locations of a preset building; perform modal analysis on the monitoring data signals to obtain several intrinsic modal function signals; fit the errors between the intrinsic modal function signals to obtain the relative time error at each location; and based on the relative time error, eliminate the errors between the monitoring data signals to obtain synchronized monitoring data. By combining modal analysis, the monitoring data at different locations of the building is synchronized in time. That is, monitoring data signals from different locations are collected, intrinsic modal function signals are obtained based on modal analysis, and the intrinsic modal function signals are fitted to obtain and eliminate the time errors at each location. This can solve the technical problem of time errors in monitoring data at different locations in super high-rise time synchronization monitoring, reduce the monitoring cost of time synchronization, and synchronously analyze monitoring data from different locations, thereby providing a more accurate data foundation for structural damage identification and safety assessment. Attached Figure Description
[0035] Figure 1 This is a schematic diagram of the functional modules of the terminal equipment to which the time synchronization monitoring device of this application belongs;
[0036] Figure 2 This is a flowchart illustrating a first exemplary embodiment of the time synchronization monitoring method of this application;
[0037] Figure 3 This is a schematic diagram of the monitoring data signal x1(t) involved in the time synchronization monitoring method of this application;
[0038] Figure 4 This is a schematic diagram of the monitoring data signal x2(t) involved in the time synchronization monitoring method of this application;
[0039] Figure 5 This is a schematic diagram of the simulation function of x1(t) involved in the time synchronization monitoring method of this application;
[0040] Figure 6 This is a schematic diagram of the simulation function of x2(t) involved in the time synchronization monitoring method of this application;
[0041] Figure 7 This is a flowchart illustrating a second exemplary embodiment of the time synchronization monitoring method of this application;
[0042] Figure 8 This is a schematic diagram of the simulation function f1j(t) involved in the time synchronization monitoring method of this application;
[0043] Figure 9 This is a schematic diagram of the simulation function f2j(t) involved in the time synchronization monitoring method of this application;
[0044] Figure 10 This is a flowchart illustrating a third exemplary embodiment of the time synchronization monitoring method of this application.
[0045] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0046] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.
[0047] The main solution of this application embodiment is as follows: For different locations of a preset building, corresponding monitoring data signals are collected; modal analysis is performed on the monitoring data signals to obtain several intrinsic modal function signals; the errors between the intrinsic modal function signals are fitted to obtain the relative time error of the location; based on the relative time error, the errors between the monitoring data signals are eliminated to obtain synchronized monitoring data. By combining modal analysis, the monitoring data at different locations of the building are synchronized in time. That is, monitoring data signals at different locations are collected, intrinsic modal function signals are obtained based on modal analysis, and the intrinsic modal function signals are fitted to obtain and eliminate the time errors at each location. This solves the technical problem of time errors in monitoring data at different locations during time synchronization monitoring of super high-rise buildings, reduces the monitoring cost of time synchronization, and allows for simultaneous analysis of monitoring data at different locations, thereby providing a more accurate data foundation for structural damage identification and safety assessment.
[0048] Technical terms used in the embodiments of this application:
[0049] Modal analysis is a method for studying the dynamic characteristics of structures, generally applied in the field of engineering vibration. A mode refers to the inherent vibration characteristics of a mechanical structure; each mode has a specific natural frequency, damping ratio, and mode shape. The process of analyzing these modal parameters is called modal analysis. Based on the calculation method, modal analysis can be divided into computational modal analysis and experimental modal analysis. Modal analysis can decompose complex signals into a finite number of intrinsic mode functions (IMFs), and each IMF component contains local characteristic signals of the original signal at different time scales.
[0050] Empirical Mode Decomposition (EMD) decomposes signals based on the time-scale characteristics of the data itself, without the need to pre-define any basis functions.
[0051] This is fundamentally different from Fourier decomposition and wavelet decomposition methods based on a priori harmonic basis functions and wavelet basis functions. Due to this characteristic, the EMD method can theoretically be applied to the decomposition of any type of signal, thus possessing significant advantages in processing non-stationary and nonlinear data. It is suitable for analyzing nonlinear and non-stationary signal sequences and has a high signal-to-noise ratio. Therefore, since its inception, the EMD method has been rapidly and effectively applied in various engineering fields, such as in the analysis of marine, atmospheric, and astronomical observation data and seismic records, mechanical fault diagnosis, damping identification of dense-frequency dynamic systems, and modal parameter identification of large-scale civil engineering structures. The key to this method is empirical mode decomposition, which decomposes complex signals into a finite number of intrinsic mode functions (IMFs). Each IMF component contains local characteristic signals of the original signal at different time scales. Empirical mode decomposition can stationary data, and then perform Hilbert transform to obtain a time-spectrum diagram, yielding physically meaningful frequencies. Compared to methods such as Short-Time Fourier Transform and Wavelet Decomposition, this method is intuitive, direct, a posteriori, and adaptive because the basis functions are derived from the data itself. Since the decomposition is based on the local characteristics of the signal sequence's time scale, it possesses adaptability.
[0052] Intrinsic modulus function: An intrinsic modulus function satisfies the following two conditions: (1) The number of local extrema and zero crossings of the function is equal or differs by at most one over the entire time range; (2) At any time point, the average of the envelope of the local maximum (upper envelope) and the envelope of the local minimum (lower envelope) is zero.
[0053] The embodiments of this application take into account that comprehensive monitoring of super high-rise buildings generally involves the deployment of a large number of monitoring sensors. These sensors are often arranged in different locations within the super high-rise building, which leads to the problem of asynchronous monitoring data in the time synchronization monitoring of super high-rise buildings.
[0054] Traditional methods for solving the time synchronization problem in super high-rise buildings mainly involve: forming a network of sensors at different locations through optical fiber to eliminate time errors; however, adding new optical fibers inside super high-rise buildings is not only costly but also difficult to construct; or adding BeiDou time synchronization function to each monitoring sensor local network to eliminate time synchronization problems, but the implementation cost is too high and it is difficult to popularize.
[0055] Therefore, the embodiments of this application, starting from solving the practical problem of time errors in monitoring data from different locations in the time synchronization monitoring of super high-rise buildings, and combining the analytical capabilities of instantaneous modal analysis technology for building structures, propose a time synchronization monitoring method for super high-rise buildings based on instantaneous modal analysis. This method solves the technical problem of time errors in monitoring data from different locations in the time synchronization monitoring of super high-rise buildings, reduces the monitoring cost of time synchronization, and synchronously analyzes monitoring data from different locations, thereby providing a more accurate data foundation for structural damage identification and safety assessment.
[0056] Specifically, refer to Figure 1 , Figure 1 This diagram illustrates the functional modules of the terminal device to which the time synchronization monitoring device of this application belongs. The time synchronization monitoring device can be an independent device capable of time synchronization monitoring, and it can be implemented on the terminal device in hardware or software form. The terminal device can be a smart mobile terminal with data processing capabilities, such as a mobile phone or tablet computer, or it can be a fixed terminal device or server with data processing capabilities.
[0057] In this embodiment, the terminal device to which the time synchronization monitoring device belongs includes at least an output module 110, a processor 120, a memory 130, and a communication module 140.
[0058] The memory 130 stores the operating system and the time synchronization monitoring program. The time synchronization monitoring device can collect corresponding monitoring data signals for different locations of a preset building; perform modal analysis on the monitoring data signals to obtain several corresponding intrinsic mode function signals; fit the errors between the intrinsic mode function signals to obtain the relative time error of the location; and store the synchronized monitoring data obtained after eliminating errors between monitoring data signals based on the relative time error in the memory 130. The output module 110 can be a display screen, etc. The communication module 140 can include a WIFI module, a mobile communication module, and a Bluetooth module, etc., and communicates with external devices or servers through the communication module 140.
[0059] When the time synchronization monitoring program in memory 130 is executed by the processor, it performs the following steps:
[0060] Collect corresponding monitoring data signals for different locations of the preset building;
[0061] Modal analysis is performed on the monitoring data signal to obtain several corresponding intrinsic mode function signals;
[0062] The relative time error of the position is obtained by fitting the error between the intrinsic mode function signals.
[0063] Based on the relative time error, the errors between the monitoring data signals are eliminated to obtain synchronized monitoring data.
[0064] Furthermore, when the time synchronization monitoring program in memory 130 is executed by the processor, it also performs the following steps:
[0065] The intrinsic mode function signal is simplified to obtain the corresponding analog function;
[0066] The relative time error of the position is obtained by fitting the error between the simulation functions.
[0067] Furthermore, when the time synchronization monitoring program in memory 130 is executed by the processor, it also performs the following steps:
[0068] Obtain a preset error fitting function, wherein the error fitting function includes the linear relationship between the simulation function and the preset acquisition period;
[0069] Based on the error fitting function, the simulation function and the acquisition period are calculated sequentially to obtain the relative time error of the position.
[0070] Furthermore, when the time synchronization monitoring program in memory 130 is executed by the processor, it also performs the following steps:
[0071] The corresponding simulation time error is obtained by substituting the acquisition period and the simulation function into the error fitting function in sequence.
[0072] The simulated time error is compared to obtain the relative time error of the position.
[0073] Furthermore, when the time synchronization monitoring program in memory 130 is executed by the processor, it also performs the following steps:
[0074] Select any one of the monitoring data signals from the plurality of monitoring data signals as the reference signal;
[0075] Based on the relative time error, the reference time error of the monitoring data signal relative to the reference signal is calculated sequentially;
[0076] After eliminating the reference time error, synchronized monitoring data is obtained.
[0077] Furthermore, when the time synchronization monitoring program in memory 130 is executed by the processor, it also performs the following steps:
[0078] The reference time error is sequentially transformed and removed to obtain the monitoring data of the building.
[0079] Furthermore, when the time synchronization monitoring program in memory 130 is executed by the processor, it also performs the following steps:
[0080] Modal analysis is performed on the monitoring data signal at any time point to obtain several corresponding intrinsic mode function signals.
[0081] This embodiment, through the above-described scheme, specifically collects corresponding monitoring data signals at different locations of a preset building; performs modal analysis on the monitoring data signals to obtain several intrinsic mode function (IMF) signals; fits the errors between the IMF signals to obtain the relative time error at each location; and based on the relative time error, eliminates the errors between the monitoring data signals to obtain synchronized monitoring data. By combining modal analysis, the monitoring data at different locations of the building is synchronized in time. That is, monitoring data signals are collected from different locations, IMF signals are obtained based on modal analysis, and the IMF signals are fitted to obtain and eliminate the time errors at each location. This solves the technical problem of time errors in monitoring data from different locations in time synchronization monitoring of super high-rise buildings, reduces the monitoring cost of time synchronization, and provides a more accurate data foundation for structural damage identification and safety assessment by simultaneously analyzing monitoring data from different locations.
[0082] Based on, but not limited to, the terminal device architecture described above, this application proposes method embodiments.
[0083] Reference Figure 2 , Figure 2 This is a flowchart illustrating a first exemplary embodiment of the time synchronization monitoring method of this application. The time synchronization monitoring method includes:
[0084] Step S210: Collect corresponding monitoring data signals for different locations of the preset building;
[0085] The execution subject of the method in this embodiment can be a time synchronization monitoring device, a time synchronization monitoring terminal device, or a server. This embodiment takes a time synchronization monitoring device as an example. The time synchronization monitoring device can be integrated into terminal devices such as smartphones and tablets with data processing functions.
[0086] This embodiment mainly enables time-synchronous monitoring of super high-rise buildings, especially super high-rise buildings. It can reduce the monitoring cost of time synchronization, and simultaneously analyze monitoring data from different locations, thereby providing a more accurate data foundation for structural damage identification and safety assessment.
[0087] This embodiment addresses the practical problem of time errors in monitoring data from different locations during time synchronization monitoring of super high-rise buildings. By combining the analytical capabilities of instantaneous modal analysis (IMA) technology for building structures, it proposes a time synchronization monitoring method for super high-rise buildings based on IMA. This method solves the technical problem of time errors in monitoring data from different locations during time synchronization monitoring of super high-rise buildings, reduces the monitoring cost of time synchronization, and enables simultaneous analysis of monitoring data from different locations, thereby providing a more accurate data foundation for structural damage identification and safety assessment.
[0088] Specifically, this embodiment collects monitoring data signals from a super high-rise building using sensors, including but not limited to accelerometers and gravity sensors. This embodiment uses an accelerometer to illustrate the use of a super high-rise building. In the super high-rise building, accelerometers at different locations collect acceleration data signals x1(t), x2(t), x2(t)...xi(t)...xn-1(t), xn(t), where i represents a different location. The sampling frequency is 1 / T, the total sampling time is S, and the total number of sampling points is not less than 2000, i.e., S / T > 2000. (Reference) Figure 3 and Figure 4 , Figure 3 This is a schematic diagram of the monitoring data signal x1(t) involved in the time synchronization monitoring method of this application. Figure 4 This is a schematic diagram of the monitoring data signal x2(t) involved in the time synchronization monitoring method of this application.
[0089] Step S220: Perform modal analysis on the monitoring data signal to obtain a number of corresponding intrinsic mode function signals;
[0090] Specifically, based on the empirical mode decomposition (EMD) method, the data signal xi(t) collected by the monitoring sensors at different locations is decomposed into several intrinsic mode function (IMF) data signals cij(t), where j represents different IMF data signals. In this embodiment, it is preferred that there are no less than 5 IMF data signals. In other embodiments, it can also be decomposed into no less than 2 or more IMF signals.
[0091] More specifically, Figure 5 Figure 5 shows a schematic diagram of the analog function of x1(t) involved in the time synchronization monitoring method of this application. Through modal analysis, x1(t) is decomposed into five intrinsic mode function signals, namely c11(t), c12(t), c13(t), c14(t), and c15(t). Figure 6 This is a schematic diagram of the simulation function of x2(t) involved in the time synchronization monitoring method of this application, as shown below. Figure 6As shown, x2(t) is decomposed into five intrinsic mode function signals through modal analysis, namely c21(t), c22(t), c23(t), c24(t), and c25(t).
[0092] Furthermore, modal analysis is performed on the monitoring data signal at any given time point to obtain several corresponding intrinsic mode function signals.
[0093] Specifically, to improve the efficiency and accuracy of modal analysis, embodiments of this application perform time-synchronized monitoring of super high-rise buildings based on instantaneous modal analysis, for example, such as... Figure 3 As shown, modal analysis of the monitoring data signal x1 with t = 2s can be decomposed into the following: Figure 5 c11(2), c12(2), c13(2), c14(2), c15(2) are shown.
[0094] Step S230: Fit the error between the intrinsic mode function signals to obtain the relative time error of the position;
[0095] Since variables do not necessarily have linear relationships—for example, the relationship between acceleration data signals of super high-rise buildings and time, or the relationship between the efficacy of treatment and the length of treatment—curve fitting refers to selecting an appropriate curve type to fit the observed data and using the fitted curve equation to analyze the relationship between the two variables.
[0096] Therefore, embodiments of this application fit the errors between intrinsic modulus function signals to obtain the relative time errors between positions. Here, the relative time error is the time error between adjacent positions; further, the relative time error is the time error between each position; even further, the relative time error is the time error between a selected reference position and the reference position. Fitting methods include, but are not limited to, least squares, Lagrange interpolation, Newton interpolation, Newton iteration, interval bisection, secant method, Jacobi iteration, and Newton-Cotes numerical integration.
[0097] Step S240: Based on the relative time error, eliminate the error between the monitoring data signals to obtain synchronized monitoring data.
[0098] Traditional synchronous monitoring requires either laying long-distance communication fiber optic cables or adding BeiDou timing sensors. Therefore, this embodiment combines instantaneous modal analysis technology to automatically correct signals with time errors at different locations. This enables synchronous monitoring of different monitoring points without adding auxiliary equipment and facilities, thus reducing monitoring costs.
[0099] This embodiment, through the above-described scheme, specifically by combining modal analysis, synchronizes the monitoring data from different locations of the building in time. That is, it collects monitoring data signals from different locations, obtains intrinsic mode function signals based on modal analysis, fits the intrinsic mode function signals, obtains and eliminates the time errors at each location, and can solve the technical problem of time errors in monitoring data from different locations in time synchronization monitoring of super high-rise buildings. It can reduce the monitoring cost of time synchronization, synchronously analyze monitoring data from different locations, and thus provide a more accurate data foundation for structural damage identification and safety assessment.
[0100] Reference Figure 7 , Figure 7 This is a flowchart illustrating a second exemplary embodiment of the time synchronization monitoring method of this application. Based on the above... Figure 2 In the embodiment shown, step S230, fitting the error between the intrinsic mode function signals to obtain the relative time error of the position, includes:
[0101] Step S710: Simplify the intrinsic mode function signal to obtain the corresponding analog function;
[0102] Specifically, because different features have different dimensions or units of measurement, and their ranges of variation are on different orders of magnitude, without normalization and / or standardization, some indicators may be overlooked, affecting the results of data analysis. Normalization is essentially a linear change, which has many desirable properties, such as not changing the original data's order; and not changing the relative value of the difference between values a and b.
[0103] Therefore, normalization of the intrinsic mode function (IMF) signal is preferred in this embodiment. In other embodiments, simplification methods such as standardization can also be used. By dividing each of the different IMF data signals cij(t) by its maximum value, the normalized analog function fij(t) is obtained, making the processed IMF signal more conducive to analysis. (Reference) Figure 8 and Figure 9 , Figure 8 This is a schematic diagram of the simulation function f1j(t) involved in the time synchronization monitoring method of this application; Figure 9 This is a schematic diagram of the simulation function f2j(t) involved in the time synchronization monitoring method of this application.
[0104] Step S720: Fit the error between the simulation functions to obtain the relative time error of the position.
[0105] Specifically, any point in time is selected, and the simulation functions corresponding to adjacent positions are fitted sequentially to obtain the time error between different positions.
[0106] Further, step S720, fitting the error between the simulation functions to obtain the relative time error of the position, includes:
[0107] Step S721: Obtain a preset error fitting function, wherein the error fitting function includes the linear relationship between the simulation function and the preset acquisition period;
[0108] This application uses the least squares method as a preferred example. It should be noted that the least squares method is an optimization technique. It finds the best function match for the data by minimizing the sum of squared errors. The least squares method can be used to easily obtain unknown data while minimizing the sum of squared errors between the obtained data and the actual data.
[0109] Specifically, based on the least squares method, the error fitting function is selected as follows:
[0110]
[0111] In the formula, δt is set as the sampling period T for structural monitoring, m i f is a positive integer ij Let be the j-th simulation function at position i; t is the current time point.
[0112] Step S722: Based on the error fitting function, calculate the simulation function and the acquisition period in sequence to obtain the relative time error of the position.
[0113] Specifically, m was calculated separately. i E at times 1, 2, 3...n mi The value is used to obtain the corresponding simulation time error E. mi .
[0114] Further, the acquisition period includes at least one or more steps. Step S722, based on the error fitting function, sequentially calculates the simulation function and the acquisition period to obtain the relative time error of the position, including:
[0115] Step S7220: Substitute the acquisition period and the simulation function into the error fitting function in sequence to calculate the corresponding simulation time error;
[0116] Step S7221: Compare the simulated time error to obtain the relative time error of the position.
[0117] Specifically, in this embodiment, n is 1000 as an example; in other embodiments, it can be greater than or less than 1000. The calculated E... mi The numerical values are compared sequentially. If m i =k i At time, the obtained Emi If the minimum value is found, then this k can be selected. i δt as f ij and f (i-1)j The time error can be calculated by analogy. Similarly, the time error of the measured data between different positions i=1, 2, 3...n can be obtained.
[0118] This embodiment, through the above-described scheme, specifically simplifies the intrinsic modulus function signal to obtain the corresponding analog function; obtains a preset error fitting function, which includes the linear relationship between the analog function and a preset acquisition period; sequentially substitutes the acquisition period and the analog function into the error fitting function to calculate the corresponding analog time error; compares the analog time errors to obtain the relative time error of the position. By simplifying the intrinsic modulus function signal to obtain several analog functions, calculating the corresponding analog time difference based on the error fitting function, and comparing the various analog time errors to obtain the relative time error, the accuracy of calculating the relative time error can be improved, thereby improving the accuracy of time synchronization monitoring.
[0119] Reference Figure 10 , Figure 10 This is a flowchart illustrating a third exemplary embodiment of the time synchronization monitoring method of this application. Based on the above... Figure 2 In the illustrated embodiment, step S240, based on the relative time error, eliminates the error between the monitoring data signals to obtain synchronized monitoring data, including:
[0120] Step S1010: Select any one of the monitoring data signals from the plurality of monitoring data signals as a reference signal;
[0121] Specifically, time errors are eliminated. For example, if the monitoring data signal x1(t) at position x1 is used as the reference, then x1(t) is the reference signal, k2δt is the time error of the data x2(t) at monitoring position x2 relative to x1(t), and k3δt is the time error of the data x3(t) at monitoring position x3 relative to x2(t).
[0122] Step S1020: Based on the relative time error, calculate the reference time error of the monitoring data signal relative to the reference signal in sequence;
[0123] Specifically, the reference time error is the relative error of each point relative to the reference point, that is, relative to the reference signal. By analogy, the time error of different points relative to x1(t) can be obtained as follows:
[0124]
[0125] In the formula, k s δt is E mi, i represents different positions, ΔT i This represents the time error of each position relative to x1.
[0126] Step S1030: Remove the reference time error to obtain synchronized monitoring data.
[0127] Further, step S1030, removing the reference time error to obtain synchronized monitoring data, includes: sequentially performing time transformation on the reference time error and removing it to obtain the monitoring data of the building.
[0128] Specifically, x1(t), x2(t), x3(t)...xi(t)...xn-1(t), xn(t) are transformed by time into x1(t), x2(t-ΔT2), x3(t-ΔT3)...xi(t-ΔT4)...xn-1(t-ΔT2) respectively. n-1 ), xn(t-ΔT n ).
[0129] From this point on, the newly obtained monitoring data are x1(t), x2(t-ΔT2), x3(t-ΔT3)...xi(t-ΔT). i ...x n-1 (t-ΔT) n-1 ), x n (t-ΔT) n This is monitoring data that has been adjusted to remove time errors, and it can be used to conduct more accurate structural damage identification and safety assessment.
[0130] This embodiment, through the above-described scheme, specifically selects any one of the monitored data signals as a reference signal; based on the relative time error, it sequentially calculates the reference time error of each monitored data signal relative to the reference signal; and then removes the reference time error to obtain synchronized monitoring data. By selecting any one monitored data signal as the reference signal and calculating and removing the time error of each monitored data signal relative to the reference signal, the calculation efficiency of time errors between different locations can be improved, thereby improving the efficiency of time synchronization monitoring and reducing monitoring costs.
[0131] Furthermore, this application also proposes a time synchronization monitoring device, which includes:
[0132] The signal acquisition module is used to collect corresponding monitoring data signals for different locations of the preset building;
[0133] The modal analysis module performs modal analysis on the monitoring data signal to obtain a number of corresponding intrinsic mode function signals;
[0134] An error fitting module is used to fit the error between the intrinsic mode function signals to obtain the relative time error of the position.
[0135] An error elimination module is used to eliminate errors between the monitoring data signals based on the relative time error, so as to obtain synchronized monitoring data.
[0136] The principle and implementation process of time synchronization monitoring in this embodiment are explained in the above embodiments and will not be repeated here.
[0137] Furthermore, this application also proposes a terminal device, which includes a memory, a processor, and a time synchronization monitoring program stored in the memory and executable on the processor. When the time synchronization monitoring program is executed by the processor, it implements the steps of the time synchronization monitoring method described above.
[0138] Since this time synchronization monitoring program employs all the technical solutions of all the aforementioned embodiments when executed by the processor, it has at least all the beneficial effects brought about by all the technical solutions of all the aforementioned embodiments, which will not be elaborated here.
[0139] Furthermore, embodiments of this application also propose a computer-readable storage medium storing a time synchronization monitoring program, which, when executed by a processor, implements the steps of the time synchronization monitoring method described above.
[0140] Since this time synchronization monitoring program employs all the technical solutions of all the aforementioned embodiments when executed by the processor, it has at least all the beneficial effects brought about by all the technical solutions of all the aforementioned embodiments, which will not be elaborated here.
[0141] Compared to existing technologies, the time synchronization monitoring method, apparatus, terminal equipment, and storage medium proposed in this application collect corresponding monitoring data signals at different locations of a preset building; perform modal analysis on the monitoring data signals to obtain several intrinsic modal function signals; fit the errors between the intrinsic modal function signals to obtain the relative time error at each location; and based on the relative time error, eliminate the errors between the monitoring data signals to obtain synchronized monitoring data. By combining modal analysis to synchronize the monitoring data at different locations of the building in time—that is, by collecting monitoring data signals from different locations, obtaining intrinsic modal function signals based on modal analysis, fitting the intrinsic modal function signals to obtain and eliminate the time errors at each location—this solves the technical problem of time errors in monitoring data from different locations in ultra-high-rise building time synchronization monitoring. It can reduce the monitoring cost of time synchronization, synchronously analyze monitoring data from different locations, and thus provide a more accurate data foundation for structural damage identification and safety assessment.
[0142] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.
[0143] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.
[0144] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, controlled terminal, or network device, etc.) to execute the methods of each embodiment of this application.
[0145] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.
Claims
1. A method of time synchronization monitoring, the method comprising: The time synchronization monitoring method includes the following steps: Collect corresponding monitoring data signals for different locations of the preset building; Modal analysis is performed on the monitoring data signal to obtain several corresponding intrinsic mode function signals; The relative time error of the position is obtained by fitting the error between the intrinsic mode function signals. Based on the relative time error, the error between the monitoring data signals is eliminated to obtain synchronized monitoring data; The step of fitting the error between the intrinsic mode function signals to obtain the relative time error of the position includes: The intrinsic mode function signal is simplified to obtain the corresponding analog function; Fitting the errors between the simulation functions to obtain the relative time error of the position specifically includes: Obtain a preset error fitting function, wherein the error fitting function includes the linear relationship between the simulation function and the preset acquisition period; Based on the error fitting function, the simulation function and the acquisition period are calculated sequentially to obtain the relative time error of the position. The acquisition period includes at least one or more, specifically including: substituting the acquisition period and the simulation function into the error fitting function sequentially to calculate the corresponding simulation time error; comparing the simulation time error to obtain the relative time error of the position.
2. The time synchronization monitoring method of claim 1, wherein, The step of eliminating errors between the monitoring data signals based on the relative time error to obtain synchronized monitoring data includes: Select any one of the monitoring data signals from the plurality of monitoring data signals as the reference signal; Based on the relative time error, the reference time error of the monitoring data signal relative to the reference signal is calculated sequentially; After eliminating the reference time error, synchronized monitoring data is obtained.
3. The time synchronization monitoring method of claim 2, wherein, The step of eliminating errors between the monitoring data signals based on the relative time error to obtain synchronized monitoring data includes: The reference time error is sequentially transformed and removed to obtain the monitoring data of the building.
4. The time synchronization monitoring method of claim 1, wherein, The step of performing modal analysis on the monitoring data signal to obtain a plurality of corresponding intrinsic mode function signals includes: Modal analysis is performed on the monitoring data signal at any time point to obtain several corresponding intrinsic mode function signals.
5. A time synchronization monitoring apparatus characterized by comprising: The time synchronization monitoring device includes: The signal acquisition module is used to collect corresponding monitoring data signals for different locations of the preset building; The modal analysis module performs modal analysis on the monitoring data signal to obtain a number of corresponding intrinsic mode function signals; An error fitting module is used to fit the errors between the intrinsic mode function signals to obtain the relative time error of the position; the error fitting module is also used to simplify the intrinsic mode function signals to obtain the corresponding analog functions; fit the errors between the analog functions to obtain the relative time error of the position; the error fitting module is also used to obtain a preset error fitting function, the error fitting function including the linear relationship between the analog function and a preset acquisition period; based on the error fitting function, sequentially calculate the analog function and the acquisition period to obtain the relative time error of the position, the acquisition period including at least one or more; the error fitting module is also used to sequentially substitute the acquisition period and the analog function into the error fitting function to calculate the corresponding analog time error; compare the analog time errors to obtain the relative time error of the position; An error elimination module is used to eliminate errors between the monitoring data signals based on the relative time error, so as to obtain synchronized monitoring data.
6. A terminal device, characterized by comprising: The terminal device includes a memory, a processor, and a time synchronization monitoring program stored in the memory and executable on the processor. When the time synchronization monitoring program is executed by the processor, it implements the steps of the time synchronization monitoring method as described in any one of claims 1-4.
7. A computer readable storage medium characterized by The computer-readable storage medium stores a time synchronization monitoring program, which, when executed by a processor, implements the steps of the time synchronization monitoring method as described in any one of claims 1-4.