Vibration characteristic evaluation device, vibration characteristic evaluation system, and vibration characteristic evaluation method

Abstract

To obtain an accurate attenuation constant regardless of the smoothing state of power spectrum density when a half power method is used.SOLUTION: A vibration characteristic evaluation device 10 includes a first calculation unit 102 that calculates a first power spectral density by performing Fourier transform on observation data representing a vibration state of a structure, a second calculation unit 104 that calculates a natural frequency from a frequency at a peak position of a first smoothed power spectral density obtained by smoothing the first power spectral density and calculates a first damping constant from a peak shape, a third calculation unit 105 that calculates a second power spectral density in a one mass-point model using a predetermined second damping constant as a parameter, a fourth calculation unit 107 that calculates a third damping constant from a peak shape of the second smoothed power spectral density obtained by smoothing the second power spectral density, and a correction unit 109 that corrects the first damping constant using a first correction coefficient calculated from the second damping constant and the third damping constant.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present disclosure relates to a vibration characteristics evaluation device, a vibration characteristics evaluation system, and a vibration characteristics evaluation method. [Background technology]

[0002] Conventionally, structural monitoring systems have been known that observe the shaking of a structure during an earthquake using sensors such as accelerometers, automatically evaluate the soundness of the structure after the earthquake using the observed data, and display the results to the user (for example, facility manager). The soundness of a structure can be evaluated based on the magnitude of the maximum response during the earthquake (maximum acceleration, maximum story deformation angle, etc.), or based on the degree of change in vibration characteristics (natural frequency, damping constant, etc.) before, during, or after the earthquake.

[0003] The above evaluation cannot be performed unless an earthquake occurs. However, although a structure is at its stiffest and exhibits a high natural frequency when it is completed, some structures have a natural frequency that decreases with each passing day. Therefore, it is important for structural monitoring not only to wait for an earthquake, which may occur at any time, but also to check the vibration characteristics on a daily basis. For this reason, some structural monitoring systems have the function of observing microtremors on a daily basis to check the vibration characteristics (see, for example, Patent Document 1).

[0004] Here, we will explain methods for understanding vibration characteristics from observation data (identification methods). Identification methods are broadly divided into two domains: frequency domain and time domain. Among frequency domain methods, the half-power method is a simple method that targets observation data under microtremors and allows identification from a single point of observation data. This method involves performing a Fourier transform on the observation data under microtremors to obtain the power spectral density, then determining the natural frequency from the frequency at the peak position, and then determining the damping constant from the shape of the peak. This type of method makes it possible to evaluate vibration characteristics from daily microtremors, and the validity of the results can also be judged by looking at the shape of the spectrum used in the half-power method. For this reason, it can be said to be a useful method for monitoring by observing daily microtremors over long periods of time. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2003-322585 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the power spectral density used in the half-power method contains estimation errors because it is calculated by Fourier transforming the observed data. Therefore, to use the half-power method, it is necessary to smooth the power spectral density using a spectral window or other method. While smoothing can highlight the original components of the signal, it also distorts the shape of the spectrum. As a result, the attenuation constant calculated using the half-power method may vary depending on the degree of smoothing and may even be overestimated.

[0007] An object of the present disclosure is to provide a vibration characteristics evaluation device, system, and method that can obtain a highly accurate damping constant when using the half-power method, regardless of the degree of smoothing of the power spectral density. [Means for solving the problem]

[0008] In order to achieve the above object, a vibration characteristics evaluation device according to the present disclosure includes an acquisition unit that acquires observation data representing a vibration state of a structure, a first calculation unit that calculates a first power spectral density by Fourier transforming the observation data, a first smoothing unit that smooths the first power spectral density to obtain a first smoothed power spectral density, a second calculation unit that calculates a natural frequency from a frequency at a peak position of the first smoothed power spectral density and calculates a first damping constant from a peak shape of the first smoothed power spectral density, a third calculation unit that calculates a second power spectral density of a one-mass model having a mass under an excitation force with constant frequency component magnitudes, using a predetermined second damping constant as a parameter, a second smoothing unit that smooths the second power spectral density to obtain the second smoothed power spectral density, a fourth calculation unit that calculates a third damping constant from the peak shape of the second smoothed power spectral density, a fifth calculation unit that calculates a first correction coefficient from the second damping constant and the third damping constant, and a correction unit that corrects the first damping constant using the first correction coefficient. [Effects of the Invention]

[0009] According to the present disclosure, when using the half-power method, an accurate attenuation constant can be obtained regardless of the degree of smoothing of the power spectral density. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a diagram illustrating an example of a configuration of a vibration characteristic evaluation system according to an embodiment. [Figure 2] 1 is a block diagram showing an example of a hardware configuration of a vibration characteristic evaluation apparatus according to an embodiment. [Figure 3] 10 is a graph illustrating a half-power method. [Figure 4] 1 is a block diagram showing an example of a functional configuration of a vibration characteristic evaluation apparatus according to an embodiment; [Figure 5]Graphs (A) and (B) show examples of spectra obtained when a Hanning window is applied to a non-dimensional power spectral density. [Figure 6] 10 is a graph showing an example of a correspondence relationship between a third damping constant and a first correction coefficient. [Figure 7] 10 is a graph showing an example of observation data obtained on the rooftop floor of a building. [Figure 8] 8(A) to 8(D) are graphs showing an example of the power spectral density of the observation data shown in FIG. 7. [Figure 9] 10 is a flowchart showing an example of the flow of a damping constant correction process by a vibration characteristics evaluation program according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] An example of an embodiment of the technology of the present disclosure will be described in detail below with reference to the drawings. Note that components and processes that perform the same operations, actions, and functions are given the same reference numerals throughout the drawings, and redundant explanations may be omitted as appropriate. Each drawing is merely a schematic illustration to allow a sufficient understanding of the technology of the present disclosure. Therefore, the technology of the present disclosure is not limited to the illustrated examples. Furthermore, in this embodiment, explanations of configurations that are not directly related to the technology of the present disclosure or well-known configurations may be omitted.

[0012] 1 is a diagram showing an example of the configuration of a vibration characteristic evaluation system 100 according to this embodiment. The vibration characteristic evaluation system 100 according to this embodiment includes a vibration characteristic evaluation device 10, a sensor 21, a communication device 22, a cloud server 30, and a user terminal 40.

[0013] The sensor 21 and the communication device 22 are disposed in a structure 20 whose vibration characteristics are to be evaluated. The structure 20 is shown as, for example, a high-rise building or other building, but is not limited to a building and includes any structure. At least one sensor 21 is installed, for example, on an upper floor of the structure 20. The sensor 21 is preferably installed near the roof where responses of low-order modes such as the first mode or second mode are excited. The sensor 21 may be, for example, an accelerometer, a speedometer, a displacement meter (GPS (Global Positioning System) observation, etc.), or the like. The sensor 21 is connected to the communication device 22 wirelessly or via a wire. The sensor 21 and the communication device 22 may be provided separately or integrally.

[0014] The vibration characteristic evaluation device 10 is communicably connected to each of the cloud server 30 and the user terminal 40 via a network N. The network N is, for example, a network such as the Internet, a LAN (Local Area Network), or a WAN (Wide Area Network).

[0015] The sensor 21 is a sensor for detecting the vibration state of the structure 20 and outputting the observation data obtained. Here, the "vibration state of the structure 20" includes, for example, the daily tremors of the structure 20, vibrations of the structure 20 due to strong winds, etc. The communication device 22 transmits the observation data output from the sensor 21 to the cloud server 30 via the network N. The cloud server 30 is an example of a storage unit that stores the observation data output from the sensor 21.

[0016] The vibration characteristic evaluation device 10 may be, for example, a general-purpose computer such as a personal computer (PC) or a server computer. The vibration characteristic evaluation device 10 acquires observation data of the sensor 21 from a cloud server 30 via a network N periodically or at any timing. The vibration characteristic evaluation device 10 also transmits evaluation results of the vibration characteristics of the structure 20 to a user terminal 40 via the network N. The user terminal 40 may be, for example, a terminal device such as a PC, a tablet terminal, or a smartphone.

[0017] 2 is a block diagram showing an example of the hardware configuration of a vibration characteristic evaluation device 10 according to this embodiment. The vibration characteristic evaluation device 10 according to this embodiment includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a storage 14, an input unit 15, a monitor 16, and a communication interface (I / F) 17. Each component is connected to each other via a bus 18 so as to be able to communicate with each other.

[0018] The CPU 11 is a central processing unit that executes various programs and controls each part. That is, the CPU 11 reads a program from the ROM 12 or the storage 14 and executes the program using the RAM 13 as a work area. The CPU 11 controls each of the above components and performs various arithmetic processing in accordance with the program stored in the ROM 12 or the storage 14. In this embodiment, the ROM 12 or the storage 14 stores a vibration characteristics evaluation program.

[0019] The ROM 12 stores various programs and various data. The RAM 13 temporarily stores programs or data as a working area. The storage 14 is configured with an HDD (Hard Disk Drive) or an SSD (Solid State Drive) and stores various programs including an operating system and various data. The storage 14 may store the above-mentioned observation data instead of the cloud server 30.

[0020] The input unit 15 includes a pointing device such as a mouse and a keyboard, and is used to input various information to the device itself.

[0021] The monitor 16 is, for example, a liquid crystal display, and displays various information. The monitor 16 may be a touch panel type monitor, and may function as the input unit 15.

[0022] The communication interface 17 is an interface for the device itself to communicate with other external devices, and uses standards such as Ethernet (registered trademark), FDDI (Fiber Distributed Data Interface), and Wi-Fi (registered trademark).

[0023] Now, the half power method will be described with reference to FIG.

[0024] FIG. 3 is a graph used to explain the half-power method. In FIG. 3, the horizontal axis indicates the frequency, and the vertical axis indicates the power spectrum density. For example, observation records under constant microtremors are widely used to confirm the vibration characteristics of a structure 20. The half-power method is a method in which the input during constant microtremors is considered to be a random external force, and the power spectrum density is calculated from the observation records to estimate the damping constant in the frequency domain. For example, if the peak value of the power spectrum density is X r and the peak value X r The natural frequency at f r Let the peak value be X r Half the value of X r If it is set to / 2, the half value is X r The frequency width at / 2 is Δ. The damping constant h can be expressed as follows:

[0025] h=Δ / 2f r (1)

[0026] As mentioned above, in the half-power method, the power spectral density obtained by Fourier transform contains estimation errors, so smoothing is performed as a preprocessing step. Therefore, depending on the degree of smoothing, the attenuation constant h may be overestimated.

[0027] For this reason, the vibration characteristic evaluation apparatus 10 according to this embodiment corrects the influence of smoothing when evaluating the damping constant h using the half-power method, thereby enabling the damping constant h to be evaluated with high accuracy regardless of the degree of smoothing. Hereinafter, the process of "correcting the influence of smoothing when evaluating the damping constant h using the half-power method" will be referred to as the damping constant correction process.

[0028] Next, the functional configuration of the vibration characteristic evaluation apparatus 10 according to this embodiment will be described with reference to FIG.

[0029] FIG. 4 is a block diagram showing an example of the functional configuration of the vibration characteristic evaluation apparatus 10 according to this embodiment.

[0030] 4, the vibration characteristics evaluation device 10 according to this embodiment includes, as functional components, an acquisition unit 101, a first calculation unit 102, a first smoothing unit 103, a second calculation unit 104, a third calculation unit 105, a second smoothing unit 106, a fourth calculation unit 107, a fifth calculation unit 108, a correction unit 109, and an output unit 110. Each functional component is realized by the CPU 11 reading out a vibration characteristics evaluation program stored in the ROM 12 or the storage 14, expanding the program in the RAM 13, and executing the program.

[0031] The acquisition unit 101 acquires observation data representing the vibration state of the structure 20 from, for example, the cloud server 30 or the storage 14.

[0032] The first calculation unit 102 calculates a first power spectral density by performing a Fourier transform on the observation data acquired by the acquisition unit 101 .

[0033] The first smoothing unit 103 smooths the first power spectral density calculated by the first calculation unit 102 to obtain a first smoothed power spectral density. For example, a Hanning window is used to smooth this first power spectral density. The Hanning window is a type of digital filter and is a spectral window that is relatively often used for spectrum smoothing. The Hanning window is expressed by the following equation, for example. Note that the applicable digital filter is not limited to the Hanning window, and any digital filter that can be used as a spectral window may be used. Furthermore, a spectral window that assumes continuous time, such as a Parzen window, may also be used.

[0034] JPEG2026017048000002.jpg990(2)

[0035] However, H k and H k - (- is H k (directly above , and so on) are the values ​​of the spectrum at the kth frequency before and after applying the window. When actually smoothing a spectrum, the smoothing is carried out by repeatedly applying the same window to the spectrum after applying this window. The spectrum H after applying it n times is k - is the spectrum before application H k It can also be expressed by the following formula using

[0036] JPEG2026017048000003.jpg956(3)

[0037] However, p n,i (i=0,1,...,2n) is the 2n+1 weighting coefficients determined for the number of times the window is applied, n. Here, the bandwidth b is an index that indicates the degree of smoothing by the spectral window. The bandwidth b is the variance σ of the target spectral window. 2In the case of a Hanning window, which is a type of digital window, the bandwidth b can be calculated using the following formula, taking into account the frequency interval Δf of the spectrum.

[0038] JPEG2026017048000004.jpg23110(4)

[0039] The second calculation unit 104 calculates the natural frequency f from the frequency at the peak position of the first smoothed power spectrum density smoothed by the first smoothing unit 103 using the half-power method. r is calculated, and the frequency width Δ and the first damping constant h^ (^ is just above h, and the same applies below) are calculated from the peak shape of the first smoothed power spectrum density.

[0040] The third calculation unit 105 calculates the second power spectrum density of a one-mass model having a mass m under an excitation force with the magnitude of the frequency component constant (=C) using a predetermined damping constant h0 (hereinafter referred to as the second damping constant h0) as a parameter. Note that the natural frequency and the frequency interval of the spectrum in the one-mass model are set, for example, to a value f set from observation data of microtremors. r and Δf are adopted.

[0041] Second smoothing unit 106 obtains a second smoothed power spectral density by smoothing the second power spectral density calculated by third calculation unit 105. To smooth this second power spectral density, the Hanning window is used n times, as in the case of the first power spectral density.

[0042] The fourth calculation unit 107 calculates an attenuation constant (hereinafter referred to as the third attenuation constant h ) from the peak shape of the second smoothed power spectrum density smoothed by the second smoothing unit 106. est ) is calculated.

[0043] Here, the influence of the spectral window will be explained with reference to Figures 5(A) and 5(B). We will consider the non-dimensional power spectral density of the acceleration of a one-mass model with mass m under an excitation force where the magnitude of the frequency component when expressed in power spectral density is C (constant). The non-dimensional power spectral density is the power spectral density P(f) expressed as C / m 2 In the examples of Figures 5(A) and 5(B), the frequency f0 of the mass point is set to 0.33 Hz, and the damping constant h is set to two values: 1% and 5%.

[0044] Figures 5(A) and 5(B) are graphs showing examples of spectra obtained when a Hanning window is applied to a dimensionless power spectral density. Figure 5(A) shows an example when the damping constant h=1%, and Figure 5(B) shows an example when the damping constant h=5%. The frequency interval Δf of the spectrum is 1 / 1638.4 Hz (for example, 20 Hz sampling). 15 In Figures 5(A) and 5(B), the horizontal axis represents f / f0, which is non-dimensionalized by the frequency f0. The vertical axis represents the non-dimensional power spectral density.

[0045] The spectra shown in Figures 5(A) and 5(B) are the results of applying a Hann window to a nondimensional power spectral density. Here, the number of applications (n) was set to four: 11, 43, 171, and 384. The bandwidth (b) values ​​for each number of applications (n) correspond to 0.005 Hz, 0.01 Hz, 0.02 Hz, and 0.03 Hz. The spectra before smoothing using the Hann window (unsmoothed) are also shown. In the examples shown in Figures 5(A) and 5(B), B1 is the spectrum without smoothing, B2 is the spectrum with bandwidth (b) = 0.005 Hz, B3 is the spectrum with bandwidth (b) = 0.01 Hz, B4 is the spectrum with bandwidth (b) = 0.02 Hz, and B5 is the spectrum with bandwidth (b) = 0.03 Hz.

[0046] When the attenuation constant h is small, at 1%, the height of the spectrum decreases significantly as the bandwidth b increases. On the other hand, when the attenuation constant h is large, at 5%, the difference in shape due to differences in bandwidth b is relatively small. Table 1 shows the estimated attenuation constant h^ (= first attenuation constant h^) when the half-power method is applied to each spectrum.

[0047] [Table 1]

[0048] When the attenuation constant h is small, such as 1%, it can be seen that the larger the bandwidth b, the more significant the difference between the values ​​of the attenuation constant h and the first attenuation constant h^.

[0049] Returning to FIG. 4, the fifth calculation unit 108 calculates the second damping constant h0 and the third damping constant h est The first correction coefficient β is calculated by, for example, dividing the second damping constant h0 by the third damping constant h est It can be found by dividing by .

[0050] The corrector 109 corrects the first attenuation constant h^ using the first correction coefficient β calculated by the fifth calculator 108. Specifically, the corrector 109 corrects the first attenuation constant h^ by multiplying it by the third attenuation constant h est The second correction coefficient β^ (^ is just above β, and so on) is calculated as the third damping constant h est and the first correction coefficient β, and the first damping constant h^ is corrected using the specified second correction coefficient β^. The corrected damping constant h (corrected first damping constant h^) can be obtained, for example, by multiplying the first damping constant h^ by the second correction coefficient β^.

[0051] The output unit 110 outputs the attenuation constant h obtained by correcting the first attenuation constant ĥ by the correction unit 109. The output destination may be the storage 14, the monitor 16, or the user terminal 40, for example.

[0052] That is, the vibration characteristic evaluation device 10 according to this embodiment corrects the influence of the spectral window when the half-power method is applied to the power spectral density. First, as described above, the first power spectral density is calculated from the time-series observation data of acceleration obtained by, for example, performing microtremor observation, and the Hanning window is applied a number of times n corresponding to the predetermined bandwidth b. Then, the natural frequency f of the peak position of the spectrum is calculated. r After calculating the first damping constant h^, the half-power method is used to calculate the first correction coefficient β. Then, as described above, the second power spectrum density of the one-mass model calculated analytically is used to calculate the first correction coefficient β. In other words, the third damping constant h^ is calculated by the half-power method when the Hanning window is applied the same number of times as above, n, using the second damping constant h0 as a parameter. est and calculate the second damping constant h0 and the third damping constant h est Using the first correction coefficient β (= h0 / h est ) is found.

[0053] Figure 6 shows the third damping constant h est 6 is a graph showing an example of the correspondence relationship between the third damping constant h and the first correction coefficient β. est (The estimated value of the damping constant h est ), and the vertical axis represents the first correction coefficient β (= h0 / h est ) is shown.

[0054] The first damping constant h^ is the third damping constant h est The second correction coefficient β^ corresponding to this assumption is identified from the correspondence shown in Figure 6, and the identified second correction coefficient β^ is multiplied by the first attenuation constant h^ to obtain the attenuation constant h corrected for the influence of the spectral window (the corrected first attenuation constant h^).

[0055] Next, with reference to Fig. 7 and Figs. 8(A) to 8(D), an example using acceleration records obtained by microtremor observations carried out in a 24-story building will be described.

[0056] Figure 7 is a graph showing an example of observation data obtained on the rooftop of a building. In Figure 7, the horizontal axis indicates time and the vertical axis indicates acceleration. This observation data was recorded for approximately 27 minutes (sampling 20 Hz, data count 2 15 8(A) to 8(D) are graphs showing examples of the power spectral density of the observation data shown in FIG. 7. In FIGS. 8(A) to 8(D), the horizontal axis represents frequency, and the vertical axis represents power spectral density (PSD). The number of times n the Hanning window was applied was set to four: 11, 43, 171, and 384. FIG. 8(A) shows the power spectral density when n=11, and FIG. 8(B) shows the power spectral density when n=43. FIG. 8(C) shows the power spectral density when n=171, and FIG. 8(D) shows the power spectral density when n=384. The natural frequency f r is approximately 0.33 Hz, the respective bandwidth b values ​​correspond to 0.005 Hz, 0.01 Hz, 0.02 Hz, and 0.03 Hz.

[0057] Table 2 shows the value of the first attenuation constant h^ (before correction) estimated by the half-power method, together with the value of the first attenuation constant h^ (after correction) after correction using the attenuation constant correction process according to this embodiment.

[0058] [Table 2]

[0059] The values ​​of the correction coefficient β used here are identified by the plots in the graph shown in Figure 6. The value of the first attenuation constant h^ after correction was approximately 1.2%, regardless of the value of the bandwidth b. The attenuation constant correction process according to this embodiment makes it possible to obtain stable estimation results.

[0060] Next, the operation of the vibration characteristic evaluation device 10 according to this embodiment will be described with reference to FIG.

[0061] FIG. 9 is a flowchart showing an example of the flow of the damping constant correction process by the vibration characteristic evaluation program according to this embodiment.

[0062] The CPU 11 reads out a vibration characteristic evaluation program from the ROM 12 or the storage 14 and executes it, thereby executing each step shown in FIG.

[0063] First, in step S101, the CPU 11 acquires observation data representing the vibration state of the structure 20 from the cloud server 30 or the storage 14, for example.

[0064] In step S102, the CPU 11 calculates a first power spectral density by performing a Fourier transform on the observation data acquired in step S101.

[0065] In step S103, the CPU 11 smooths the first power spectral density calculated in step S102 to obtain a first smoothed power spectral density (applied n times). As described above, for example, a Hanning window is used to smooth this first power spectral density.

[0066] In step S104, the CPU 11 calculates the natural frequency f from the frequency at the peak position of the first smoothed power spectrum density smoothed in step S103. r Calculate.

[0067] In step S105, the CPU 11 calculates the frequency width Δ and the first damping constant ĥ from the peak shape of the first smoothed power spectrum density.

[0068] In step S106, the CPU 11 calculates the second power spectrum density of the one-mass model having a mass m under the excitation force in which the magnitude of the frequency component when expressed as the power spectrum density is constant (=C) using the predetermined second damping constant h0 as a parameter. Note that the natural frequency and the frequency interval of the spectrum in the one-mass model are set to, for example, a value f set from the observation data of the microtremor. rand Δf are adopted.

[0069] In step S107, CPU 11 smooths the second power spectral density calculated in step S106 to obtain a second smoothed power spectral density (applied n times). The Hanning window is used to smooth this second power spectral density, as in the case of the first power spectral density.

[0070] In step S108, the CPU 11 calculates the third attenuation constant h from the peak shape of the second smoothed power spectral density smoothed in step S107. est Calculate.

[0071] In step S109, the CPU 11 calculates the second damping constant h0 and the third damping constant h est The first correction coefficient β is calculated by, for example, dividing the second damping constant h0 by the third damping constant h est It can be found by dividing by .

[0072] In step S110, the CPU 11 determines the second correction coefficient β^ from the first correction coefficient β calculated in step S109. Specifically, as described above, the first damping constant h^ is calculated by multiplying the first damping constant h^ by the third damping constant h^. est The second correction coefficient β^ corresponding to the third damping constant h shown in Figure 6 is est and the first correction coefficient β.

[0073] In step S111, the CPU 11 corrects the first damping constant h^ using the second correction coefficient β^ determined in step S110, and ends the damping constant correction process according to the vibration characteristic evaluation program. The corrected damping constant h (corrected first damping constant h^) can be calculated, for example, by multiplying the first damping constant h^ by the second correction coefficient β^.

[0074] As described above, according to this embodiment, when the half-power method is used, it is possible to obtain an accurate attenuation constant regardless of the degree of smoothing of the power spectrum density.

[0075] In addition, by applying the Hanning window multiple times to the power spectral density calculated from the observation data, the shape of the spectrum is smoothed, and it approaches the spectral shape of a single-mass model that has undergone similar smoothing processing. Therefore, by using the correction coefficient calculated from the single-mass model, the damping constant can be calculated with high accuracy from the observation data.

[0076] The present disclosure is not limited to the above-described embodiment, and various modifications and applications are possible without departing from the gist of the present disclosure.

[0077] The vibration characteristic evaluation apparatus according to the embodiment has been described above as an example. The embodiment may be in the form of a program for causing a computer to execute the functions of each unit of the vibration characteristic evaluation apparatus, or in the form of a program product including the program. The embodiment may also be in the form of a computer-readable non-transitory storage medium storing the program.

[0078] Furthermore, the configuration of the vibration characteristic evaluation device described in the above embodiment is merely an example, and may be changed depending on the situation without departing from the spirit of the invention.

[0079] Furthermore, the processing flow of the program described in the above embodiment is also an example, and unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged within the scope of the main idea.

[0080] In the above embodiment, the processing according to the embodiment is realized by a software configuration using a computer by executing a program, but the present invention is not limited to this. The embodiment may be realized by, for example, a hardware configuration or a combination of a hardware configuration and a software configuration. [Explanation of symbols]

[0081] 10. Vibration characteristic evaluation device 11 CPU 12 ROM 13 RAM 14. Storage 15 Input section 16 monitors 17 Communication I / F 18 Bus 20 Structures 21 Sensors 22 Communication equipment 30 Cloud Servers 40 User terminals 100 Vibration Characterization System 101 Acquisition Department 102 1st calculation section 103 1st smoothing section 104 2nd calculation section 105 3rd calculation section 106 Second smoothing section 107 4th calculation section 108 5th Calculation Department 109 Correction Unit 110 Output section

Claims

1. an acquisition unit that acquires observation data representing the vibration state of the structure; a first calculation unit that calculates a first power spectral density by Fourier transforming the observation data; a first smoothing unit that smooths the first power spectral density to obtain a first smoothed power spectral density; a second calculation unit that calculates a natural frequency from a frequency at a peak position of the first smoothed power spectrum density and calculates a first damping constant from a peak shape of the first smoothed power spectrum density; a third calculation unit that calculates a second power spectrum density in a one mass point model having a mass under an excitation force with a constant magnitude of frequency components, using a predetermined second damping constant as a parameter; a second smoothing unit that smooths the second power spectral density to obtain a second smoothed power spectral density; a fourth calculation unit that calculates a third attenuation constant from the peak shape of the second smoothed power spectral density; a fifth calculation unit that calculates a first correction coefficient from the second damping constant and the third damping constant; a correction unit that corrects the first damping constant using the first correction coefficient; Vibration characteristics evaluation device equipped with

2. the first smoothing unit smooths the first power spectral density using a Hanning window; the second smoothing unit smooths the second power spectral density using the Hanning window. The vibration characteristic evaluation device according to claim 1 .

3. the correction unit specifies a second correction coefficient corresponding to the first damping constant when the first damping constant is regarded as the third damping constant from a correspondence relationship between the third damping constant and the first correction coefficient, and corrects the first damping constant using the specified second correction coefficient. The vibration characteristic evaluation device according to claim 1 .

4. a sensor that detects the vibration state of the structure and outputs the obtained observation data; a storage unit that stores the observation data output from the sensor; a vibration characteristic evaluation device according to any one of claims 1 to 3, which evaluates vibration characteristics of the structure using the observation data stored in the storage unit; a display unit that displays the evaluation results output from the vibration characteristic evaluation device; and Vibration characteristics evaluation system equipped with

5. Obtaining observation data that shows the vibration state of the structure, calculating a first power spectral density by Fourier transforming the observed data; smoothing the first power spectral density to obtain a first smoothed power spectral density; calculating a natural frequency from the frequency of a peak position of the first smoothed power spectral density; and calculating a first damping constant from the peak shape of the first smoothed power spectral density; calculating a second power spectrum density in a one mass point model having a mass under an excitation force with a constant magnitude of frequency components using a predetermined second damping constant as a parameter; smoothing the second power spectral density to obtain a second smoothed power spectral density; calculating a third attenuation constant from the peak shape of the second smoothed power spectral density; calculating a first correction coefficient from the second damping constant and the third damping constant; a process of correcting the first damping constant using the first correction coefficient; A computer-implemented vibration characterization method.

Images