Non-communication mode time synchronization method based on modal parameters

Abstract

The invention discloses a non-communication mode time synchronization method based on modal parameters. According to the method, a structure with proportional damping is provided, the phase difference between the measuring points of each order of modal shape under time synchronization is an integral multiple of 180 degrees, the time delay between nodes changes the phase difference, an objective function is constructed, the time delay between the nodes is estimated through the change of the phase difference between the measuring points, and data synchronization between the measuring points is achieved on the premise that communication is not needed. Compared with a time synchronization method based on a communication mode, the method does not need the support of communication hardware, saves the energy consumption caused by communication, improves the cruising ability, and is suitable for the continuous monitoring of the structure.

Description

Technical Field

[0001] The invention belongs to the field of computer technology, and in particular relates to a non-communication time synchronization method based on modal parameters. Background Art

[0002] Wireless sensor networks are widely used in structural health monitoring, environmental monitoring, traffic management, disaster relief and other fields. As a distributed system, there may always be time differences between the local nodes, and the data synchronization accuracy of each node has a great impact on the analysis results. Therefore, time synchronization is one of the key issues that must be solved in practical applications of wireless sensor networks.

[0003] At present, wireless sensor networks mainly use time synchronization methods based on communication modes, that is, nodes achieve clock synchronization by exchanging timestamp information through wireless communication. Typical methods include RBS synchronization method, DMTS synchronization method, FTSP synchronization method, TPSN synchronization method, Tiny-sync and Mini-sync time synchronization methods, etc. The synchronization accuracy of this type of method varies with the network scale, environmental interference and network busyness. At the same time, each node is required to install a wireless communication module. The communication between nodes increases the energy consumption of the nodes and greatly reduces the endurance of the nodes. It is not suitable for long-term continuous monitoring. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a non-communication time synchronization method based on modal parameters.

[0005] In a first aspect, the present invention provides a non-communication time synchronization method based on modal parameters, comprising the following steps: Step S1, deploying wireless sensors at different measuring points on the structure with proportional damping, and then using the wireless sensors to collect response data; at least one wireless sensor is deployed at each measuring point; Step S2: The wireless sensors at all measuring points respond Grouping, p = 1, 2, ..., L, L represents the total number of measurement points, each group S r All measurement points are collected synchronously, r=1, 2, ..., N ref ; There is no need for time synchronization between the groups using communication methods; Step S3: Use the wireless sensor response to identify the modal parameters of the structure with proportional damping to obtain the i-th order system modal vibration matrix ; Step S4: Select one of the groups as the reference group S ref , calculate other groups S r With reference group S refThe objective function f related to the phase difference error and time delay r (dt), and then get the time delay estimate ; Specifically: The phase difference between the measuring points is defined as: (1) in express The lth component of yes Estimate of, mod means remainder operation, Indicates the phase difference between measuring point l and measuring point m, phase(*) indicates the phase of *; right Perform the following update process so that At [-90,90]: (2) Where M represents the correction factor; The objective function is constructed using the updated phase difference: (3) Where Nc is the total number of modes involved in the time delay estimation; S r and S ref Estimated time delay between By minimizing the objective function f r (dt) get; Step S5: Estimation based on time delay , perform data synchronization processing on the original response data of the wireless sensor to synchronize the data between each group.

[0006] Preferably, the test signal type of all wireless sensors in step S1 is acceleration, velocity or displacement. All wireless sensors have the same test direction and the same test signal type, and there is no need to exchange time information between the test points by communication.

[0007] Preferably, the number of measuring points in each group in step S2 may be the same or different.

[0008] Preferably, step S3 specifically comprises: The output covariance matrix R(n) is constructed using the wireless sensor responses of each group: (4) (5) Among them, r pq (n) is the cross-correlation function between channels p and q, represents the wireless sensor response of channel p at time t; n represents the time-shift variable, and j represents the number of data sampling points; Construct the Toeplitz matrix from the output covariance matrix R(n): (6) Where k represents the maximum time shift of the Toeplitz matrix; To T 1|k Perform singular value decomposition: (7) in and are all orthogonal matrices, namely: , ; Assuming the system is observable and controllable, then T 1|k The rank of is N, and the number of its non-zero singular values ​​is N, that is, , , ; Extract the extended observable matrix T i : (8) Extract T i The first L rows of the output matrix C are: (9) Define T1 as T i The first L* (k-1) rows of T2 are T i The last L*(k-1) rows are as follows: ; (10) The system state matrix A is obtained from T1 and T2: (11) in represents the pseudo-inverse of a matrix; Perform eigenvalue decomposition on matrix A to obtain eigenvalue μ i and the eigenvector (i=1,2,…,N); According to the eigenvalue μ i Calculate the natural frequency and modal damping ratio : (12) (13) in represents the sampling time interval, represents the conjugate complex number, represents the real part; According to the output matrix C and eigenvector Calculate the modal vibration matrix of the i-th order system for: (14)

[0009] Preferably, step S5 is specifically: , p∈S r (15) in The data after synchronization.

[0010] In a second aspect, the present invention provides a non-communication time synchronization system for implementing the method, comprising: A data acquisition module is responsible for collecting response data using wireless sensors located at different measuring points of the structure with proportional damping; The data preprocessing module is responsible for grouping the wireless sensor responses of all measurement points; The modal parameter identification module is responsible for identifying the modal parameters of the structure with proportional damping using the wireless sensor response; The time delay estimation calculation module is responsible for constructing the objective function related to the phase difference error between other groups and the reference group and the time delay, and then obtaining the time delay estimation; The data synchronization module is responsible for synchronizing the original response data of the wireless sensor based on the time delay estimation.

[0011] In a third aspect, the present invention provides an electronic device, characterized in that it includes a processor and a memory, the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement the method.

[0012] In a fourth aspect, the present invention provides a machine-readable storage medium, characterized in that the machine-readable storage medium stores machine-executable instructions, and when the machine-executable instructions are called and executed by a processor, the machine-executable instructions prompt the processor to implement the method.

[0013] The beneficial effects of the present invention are: Based on the innovative discovery that time delay can phase-shift and quantize the modal vibration mode and has no effect on the natural frequency and damping ratio, the present invention proposes a structure with proportional damping, in which the phase difference between the measuring points of each order of modal vibration mode under time synchronization is an integer multiple of 180 degrees, and the time delay between nodes changes the phase difference. An objective function is constructed, and the time delay between nodes is estimated by the change in the phase difference between the measuring points, thereby achieving data synchronization between the measuring points without the need for communication.

[0014] Compared with the time synchronization method based on communication mode, this method does not require communication hardware support, saves energy consumption caused by communication, improves endurance, and is suitable for continuous structural monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a flow chart of a time synchronization method provided by an embodiment of the present invention.

[0017] Figure 2 It is a seven-degree-of-freedom linear system.

[0018] Figure 3 is the variation of the objective function with dt, where (a) Nc=1, (b) Nc=2, (c) Nc=4, and (d) Nc=7.

[0019] Figure 4 It is the layout of bridge measuring points.

[0020] Figure 5 is the variation of the objective function with dt, where (a) Nc=1, (b) Nc=2, (c) Nc=5, and (d) Nc=11.

[0021] Figure 6 is the time delay between S2 and S4. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0023] In structural dynamics, damping is often divided into proportional damping and non-proportional damping. High-stiffness, low-damping structures (such as concrete bridges) can generally be considered to have proportional damping. Figure 1 As shown, the non-communication time synchronization method with a proportional damping structure provided in an embodiment of the present invention includes the following steps:

[0024] Step S1, deploying wireless sensors at different measuring points on a structure with proportional damping (the structure with proportional damping may be a high-rigidity, low-damping structure, such as a concrete bridge), and then using the wireless sensors to collect data; deploying at least one wireless sensor at each measuring point; all wireless sensors have the same test direction, for example, the test directions are all vertical directions, the test signal types are the same, and there is no need to use a communication method to exchange time information between the measuring points; The test signal type for all wireless sensors is acceleration, velocity or displacement.

[0025] Step S2: The wireless sensors at all measuring points respond Grouping, p = 1, 2, ..., L, L represents the total number of measurement points, each group S r (r=1, 2, ..., N ref ) are collected synchronously; there is no need for time synchronization between the groups using communication methods. The number of measurement points in each group can be the same or different.

[0026] Step S3: using the collected data to identify the modal parameters of the structure with proportional damping; specifically: The output covariance matrix R(n) is constructed using the wireless sensor responses of each group: (1) (2) Among them, r pq (n) is the cross-correlation function between channels p and q, represents the wireless sensor response of channel p at time t. n represents the time-shift variable, and j represents the number of data sampling points.

[0027] Construct the Toeplitz matrix from the output covariance matrix R(n): (2) Where k represents the maximum time shift of the Toeplitz matrix.

[0028] To T 1|k Perform singular value decomposition: (3) in and are all orthogonal matrices, namely: , Assuming the system is observable and controllable, then T 1|k The rank of is N, and the number of its non-zero singular values ​​is N, that is, , , .

[0029] Extract the extended observable matrix T i : (4) Extract T i The first L rows of the output matrix C are: (5) Define T1 as T i The first L* (k-1) rows of T2 are T i The last L*(k-1) rows are as follows: ; (6) The system state matrix A is obtained from T1 and T2: (7) in Represents the pseudoinverse of a matrix.

[0030] Perform eigenvalue decomposition on matrix A to obtain eigenvalue μ i and the eigenvector (i=1,2,…,N).

[0031] According to the eigenvalue μ i Calculate the natural frequency and modal damping ratio : (8) (9) in represents the sampling time interval, represents the conjugate complex number, represents the real part; According to the output matrix C and eigenvector Calculate the modal vibration matrix of the i-th order system for: (10) Step S4: Select one set of data as the reference set S ref , calculate other groups S r With reference group S ref The objective function f related to the phase difference error and time delay r (dt); specifically: The phase difference between the measuring points is defined as: (11) in yes Estimate of, mod means remainder operation, Indicates the phase difference between measuring point l and measuring point m, phase(*) indicates the phase of *, represents the lth component of the modal vibration matrix of the i-th order system, i represents the i-th order mode involved in the time delay estimation; right Perform the following update process so that At [-90,90]: (12) Where M represents the correction coefficient, which is an integer between -1 and 1.

[0032] The objective function is constructed using the updated phase difference: (13) Where Nc is the total number of modes involved in the time delay estimation; S r and S ref Estimated time delay between By minimizing the objective function f r (dt) is obtained.

[0033] (14) The subscript r represents the rth group, and R represents a real number; Step S5: Estimation based on time delay , process the original collected data of the wireless sensor to synchronize the data between groups; specifically: , p∈S r (15) in The data after synchronization.

[0034] This embodiment also performs numerical simulation analysis: Take the analysis of a 7-DOF linear time-invariant system as an example. Figure 2 As shown. The mass of each mass block is 1kg, K1=10kN / m, K2=20kN / m, and the damping matrix is ​​C=0.2M+0.0003K, where M and K are the mass matrix and stiffness matrix of the system respectively. Since the damping matrix is ​​a linear combination of the mass matrix and the stiffness matrix, the system is a proportional damping system. Unrelated random excitations are applied to each mass block, and the acceleration response of each mass block is collected. The sampling frequency is 15Hz, the acquisition time is 10 minutes, and there is 20% measurement noise in the response signal. Two independent acquisition systems S1 and S2 are used to collect data, where channels m1-m4 are collected by S1, and m5-m7 are collected by S2. S2 has a 2s delay relative to S1.

[0035] The modal parameters of the response data are identified by using step 3 of this embodiment, and the results are shown in Tables 1 and 2. Table 1 shows that the frequency and damping ratio obtained by using asynchronous data have higher accuracy. Table 2 shows that due to the existence of time delay, the phase difference of m5-m7 (S2 acquisition) minus the phase difference of m1-m4 (S1 acquisition) no longer satisfies the integer multiple relationship of 180, but is phase shifted on the original basis. (Due to the existence of identification errors, the numerical values ​​are not completely equal to the theoretical values, but they are very consistent).

[0036] According to formula (13), the objective function is calculated with dt in the range [0,15] at intervals of 0.001s. Figure 3 The objective function changes in the interval. It can be seen that when the first order is involved in the calculation (Nc=1), the objective function has many approximate local minimum values, because the first order mode cannot determine the unique time delay. When Nc=2,4,7, it is determined that the global minimum is found when dt=2, that is, the time delay between s1 and s2 is determined to be 2s, which is also consistent with the simulation conditions, indicating that the obtained results are correct.

[0037] Table 1 Comparison of estimated and theoretical values ​​of frequency and damping ratio

[0038] Table 2 Phase comparison between estimated vibration mode values ​​and theoretical values

[0039] The method of the embodiment of the present invention is applied to Figure 4 In the modal parameter identification of a bridge with proportional damping (the first 11 modes are basically real modes), the bridge vibrates under environmental excitation, and two monitoring systems are arranged on the bridge: 1) Synchronous acquisition system: 12 acceleration sensors are arranged on the S1-4 sections of the bridge, and 3 sensors are arranged on each longitudinal section ( Figure 4 1) Asynchronous acquisition system: Two independent acquisition systems are placed on S2 and S4 at the same time (without communication between them). Two sensors are arranged on each longitudinal section, one perpendicular to the side and the other perpendicular to the bridge deck, as shown in the green arrow in the figure. Figure 4 shown.

[0040] The asynchronous data is analyzed using step three of this embodiment, with a sampling frequency of 12 Hz and 10 minutes of data, i.e., 7200 data for each channel. The recognition results of synchronously collected data and asynchronously collected data are compared as shown in Tables 3 and 4, where L1-L3 are modes of the vertical side, and V1-V7 are modes of the vertical bridge deck. It can be seen that the natural frequencies identified by the two are very consistent, while the vibration mode phases are different. Using the asynchronous data recognition results, dt is calculated according to formula (13) in the interval of 0.001s in the interval of [-20, 20], and the results are as follows: Figure 5 As shown. When Nc is 1, the objective function has multiple close local minima, and the global minimum is reached at dt=9.042s; when Nc=2, 5 and 11, the global minimum is reached at dt=-6.377s, so it is determined that there is a 6.377s time delay between S2 and S4 (S4 is delayed compared to S2). The data is then resynchronized, and then the modal parameters are identified using traditional SSI-COV. The results are compared with the synchronized data results as shown in Tables 3 and 4. It can be seen that the frequency and vibration mode are very consistent, indicating that the method of the present invention correctly finds the time delay between S2 and S4. The time delay between S2 and S4 during data acquisition is as shown in Table 3 and Table 4. Figure 6 As shown, it can be seen that the time delay between S2 and S4 increases slowly and linearly, which is consistent with the actual situation.

[0041] Table 3 Comparison of horizontal modal natural frequencies and vibration shape phases of synchronized, asynchronous, and resynchronized data

[0042] Table 4 Comparison of vertical modal natural frequency and vibration shape phase of synchronized, asynchronous and resynchronized data

[0043] Therefore, the method of this embodiment can achieve data synchronization between nodes without the need for communication. Compared with the time synchronization method based on the communication mode, this method does not require communication hardware support, saves energy consumption caused by communication, improves endurance, and is suitable for continuous structural monitoring.

[0044] In addition, it should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0045] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0046] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0047] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0048] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A non-communication time synchronization method based on modal parameters, characterized in that The following steps are involved: Step S1, deploying wireless sensors at different measuring points on the structure with proportional damping, and then using the wireless sensors to collect response data; at least one wireless sensor is deployed at each measuring point; Step S2: The wireless sensors at all measuring points respond Grouping, p = 1, 2, ..., L, L represents the total number of measurement points, each group S r All measurement points are collected synchronously, r=1, 2, ..., N ref ; There is no need for time synchronization between the groups using communication methods; Step S3: Use the wireless sensor response to identify the modal parameters of the structure with proportional damping to obtain the i-th order system modal vibration matrix ; Step S4: Select one of the groups as the reference group S ref , calculate other groups S r With reference group S ref The objective function f related to the phase difference error and time delay r (dt), and then get the time delay estimate ; Specifically: The phase difference between the measuring points is defined as: (1) in express The lth component of yes Estimate of, mod means remainder operation, Indicates the phase difference between measuring point l and measuring point m, phase(*) indicates the phase of *; right Perform the following update process so that At [-90,90]: (2) Where M represents the correction factor; The objective function is constructed using the updated phase difference: (3) Where Nc is the total number of modes involved in the time delay estimation; By minimizing the objective function f r (dt), we get S r and S ref Estimated time delay between ; Step S5: Estimation based on time delay , perform data synchronization on the original response data of the wireless sensor.

2. The method according to claim 1, characterized in that: In step S1, the test signal types of all wireless sensors are acceleration, velocity or displacement.

3. The method according to claim 1, characterized in that: In step S1, all wireless sensors have the same test direction and the same test signal type, and there is no need to exchange time information between the test points using a communication method.

4. The method according to claim 1, characterized in that: In step S2, the number of measuring points in each group may be the same or different.

5. The method according to claim 1, characterized in that: Step S3 specifically includes: The output covariance matrix R(n) is constructed using the wireless sensor responses of each group: (4) (5) Among them, r pq (n) is the cross-correlation function between channels p and q, represents the wireless sensor response of channel p at time t; n represents the time-shift variable, and j represents the number of data sampling points; Construct the Toeplitz matrix from the output covariance matrix R(n): (6) Where k represents the maximum time shift of the Toeplitz matrix; To T 1|k Perform singular value decomposition: (7) in and are all orthogonal matrices, namely: , ; Assuming the system is observable and controllable, then T 1|k The rank of is N, and the number of its non-zero singular values ​​is N, that is, , , ; Extract the extended observable matrix T i : (8) Extract T i The first L rows of the output matrix C are: (9) Define T1 as T i The first L* (k-1) rows of T2 are T i The last L*(k-1) rows are as follows: ； (10) The system state matrix A is obtained from T1 and T2: (11) in represents the pseudo-inverse of a matrix; Perform eigenvalue decomposition on matrix A to obtain eigenvalue μ i and the eigenvector (i=1,2,…,N); According to the eigenvalue μ i Calculate the natural frequency and modal damping ratio : (12) (13) in represents the sampling time interval, represents the conjugate complex number, represents the real part; According to the output matrix C and eigenvector Calculate the modal vibration matrix of the i-th order system for: (14)。 6. The method according to claim 1, characterized in that: Step S5 specifically includes: ,p∈S r (15) in The data after synchronization.

7. A non-communication time synchronization system implementing the method according to any one of claims 1 to 6, characterized in that include: A data acquisition module is responsible for collecting response data using wireless sensors located at different measuring points of the structure with proportional damping; The data preprocessing module is responsible for grouping the wireless sensor responses of all measurement points; The modal parameter identification module is responsible for identifying the modal parameters of the structure with proportional damping using the wireless sensor response; The time delay estimation calculation module is responsible for constructing the objective function related to the phase difference error between other groups and the reference group and the time delay, and then obtaining the time delay estimation; The data synchronization module is responsible for synchronizing the original response data of the wireless sensor based on the time delay estimation.

8. An electronic device, characterized in that: The invention comprises a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement the method according to any one of claims 1 to 6.

9. A machine-readable storage medium, characterized in that: The machine-readable storage medium stores machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions prompt the processor to implement the method described in any one of claims 1 to 6.

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