JP2016148549A - Structure displacement analysis apparatus and structure displacement analysis program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a structure displacement analysis apparatus capable of further accurately calculating displacement of a structure, and a structure displacement analysis program.SOLUTION: The structure displacement analysis apparatus includes: an acquisition unit that acquires acceleration data measured by an acceleration sensor attached to a measurement object structure; a wavelet transform unit that executes wavelet transform for the acceleration data; a frequency range setup unit that sets a frequency range suited for displacement analysis of the structure; a wavelet coefficient integration unit that integrates a wavelet coefficient obtained by the wavelet transform twice within the frequency range set by the setup unit; and a wavelet inverse transform unit that executes wavelet inverse transform for a result of the integration by the integration unit and calculates the displacement of the structure.SELECTED DRAWING: Figure 4

Description

  The present invention relates to a structure displacement analysis apparatus and a structure displacement analysis program.

  In recent years, many social infrastructures have deteriorated over time, and attention has been drawn to effective methods for diagnosing the state of structures that constitute social infrastructures. Monitoring road displacement, which is one of social infrastructures, and more specifically bridges, is important in identifying the causes of bridge fatigue and estimating the number and weight of vehicles passing over them. It is. Here, if it is attempted to directly measure the displacement, there arises a problem that it is difficult to determine the reference point, and the cost required for facilities such as wiring and scaffolding increases.

  On the other hand, in recent years, research has been advanced on using wireless accelerometers based on micro electromechanical systems (MEMS) to obtain sensor output values wirelessly and analyze displacement. Since the acceleration sensor can be easily attached to the measurement location, it has a great merit for monitoring displacement.

  In relation to the above, there is known an apparatus that obtains a displacement of a measurement object by second-order integrating acceleration measured by an acceleration sensor in the time direction (see, for example, Patent Document 1).

Japanese Patent Laying-Open No. 2015-10353

  Theoretically, displacement should be obtained by second-order integration of acceleration measured by an acceleration sensor. However, in reality, it is difficult to obtain an accurate result by this method. This is because the measurement result of the acceleration sensor includes noise that cannot be ignored, and the integration constant used for integration is often unknown.

  The present invention has been made in consideration of such circumstances, and an object of the present invention is to provide a structure displacement analysis apparatus and a structure displacement analysis program capable of calculating the displacement of a structure more accurately. One.

  One aspect of the present invention is an acquisition unit that acquires acceleration data measured by an acceleration sensor attached to a structure to be measured, a wavelet transform unit that performs wavelet transform on the acceleration data, and a displacement analysis of the structure A frequency range setting unit for setting a frequency range suitable for the wavelet, a wavelet coefficient integration unit for second-order integration of the wavelet coefficients obtained by the wavelet transform within the frequency range set by the setting unit, and integration by the integration unit And a wavelet inverse transform unit that calculates the displacement of the structure by performing wavelet inverse transform on the obtained result.

  In one aspect of the present invention, the structure may be a bridge through which a vehicle passes, and the wavelet transform unit may use an inverse double orthogonal wavelet as a mother wavelet.

  Moreover, in one aspect of the present invention, an input unit that receives an input operation by a user is further provided, and the frequency range setting unit sets the frequency range based on an input operation performed on the input unit. It is good.

  In the aspect of the invention, the frequency range setting unit may automatically reset the frequency range by analyzing the displacement calculated by the wavelet inverse transform unit.

  In another aspect of the present invention, a computer is caused to acquire acceleration data measured by an acceleration sensor attached to a structure to be measured, and the acceleration data is subjected to wavelet transform, which is suitable for displacement analysis of the structure. The frequency range is set, and within the set frequency range, the wavelet coefficient obtained by the wavelet transform is second-order integrated, and the wavelet inverse transform is performed on the result of the second-order integration to obtain the structure of the structure. This is a structure displacement analysis program for calculating displacement.

  According to one embodiment of the present invention, the displacement of a structure can be calculated more accurately.

It is a figure which shows an example of the use environment and structure of the structure displacement analysis apparatus. It is a figure which shows an example of the hardware constitutions of the structure displacement analysis apparatus. 3 is a flowchart showing a flow of processing executed by the structure displacement analysis apparatus 1. It is a figure for demonstrating the processing process by the structure displacement analyzer 1. FIG. It is a figure which shows an example of the half wavelength waveform which the displacement of the bridge B shows. It is a figure which shows an example of a reverse double orthogonal wavelet. It is a figure which shows the second-order integration of the wavelet coefficient obtained about the bridge B through which the vehicle V passes. It is a figure which shows an example of the result output screen for assisting reset of a frequency range. 5 is a flowchart showing a flow of processing including resetting of a frequency range, which is executed by the structure displacement analysis apparatus 1. It is an overhead view of the bridge B used as verification object. It is sectional drawing of the AA direction in FIG. It is the frequency analysis result of the bridge B analyzed by a fast Fourier transform (FFT; Fast Fourier Transform). It is the figure which compared the analysis result (analysis value) by the structure displacement analysis apparatus 1, and the measurement result (measurement value) measured by the laser Doppler displacement meter.

[Constitution]
Hereinafter, embodiments of a structure displacement analysis apparatus and a structure displacement analysis program of the present invention will be described with reference to the drawings. FIG. 1 is a diagram illustrating an example of a use environment and a configuration of the structure displacement analysis apparatus 1. The structure displacement analyzing apparatus 1 is an apparatus that analyzes the displacement of a structure such as a bridge B that vibrates when the vehicle V passes through. An acceleration sensor 60 is attached to the bridge B. For example, the acceleration sensor 60 measures acceleration at a predetermined sampling frequency, and transmits the measurement result to the communication device 80 by wireless or the like. The communication device 80 transfers the measurement result of the acceleration sensor 60 to the structure displacement analysis device 1 via a network NW such as a WAN (Wide Area Network) or a LAN (Local Area Network). The structure displacement analysis apparatus 1 may be configured to communicate directly with the acceleration sensor 60.

  FIG. 2 is a diagram illustrating an example of a hardware configuration of the structure displacement analysis apparatus 1. Hereinafter, the configuration of the structure displacement analyzing apparatus 1 will be described with reference to FIGS. 1 and 2. As shown in FIGS. 1 and 2, the structure displacement analyzing apparatus 1 includes a communication unit 10, an input unit 12, and an output unit 14. The communication unit 10 includes, for example, a network card for connecting to the network NW. The input unit 12 is an input device such as a keyboard, a mouse, or a touch panel. The output unit 14 is an LCD (Liquid Crystal Display), an organic EL (Electroluminescence) display device, or the like. The structure displacement analysis apparatus 1 is not limited to displaying the analysis result by the output unit 14, but may provide image data or the like to another computer apparatus via the network NW.

  As shown in FIG. 2, the structure displacement analysis apparatus 1 includes a CPU (Central Processing Unit) 20, a storage device 22, a drive device 24, and a memory device 26. The CPU 20 executes a program (structure displacement analysis program) stored in the storage device 22. The storage device 22 is, for example, a ROM, an HDD (Hard Disk Drive), a flash memory, or the like. Various portable storage media 28 are attached to the drive device 24. The memory device 26 is, for example, a RAM (Random Access Memory), and is used as a working memory by the CPU 20. The program stored in the storage device 22 may be stored in the storage device 22 in advance when the structure displacement analysis apparatus 1 is shipped, or the program stored in the storage medium 28 may be installed in the storage device 22. . In addition, the program stored in the storage device 22 may be downloaded from another computer device via the network NW and the communication unit 10.

  As shown in FIG. 1, the structure displacement analysis apparatus 1 includes a preprocessing unit 30, a wavelet transform unit 32, a frequency range setting unit 34, a wavelet coefficient integration unit 36, and a wavelet inverse transform unit 38. These functional units are, for example, software functional units that function when the CPU 20 executes a program. Some or all of these functional units may be hardware functional units such as LSI (Large Scale Integration) and ASIC (Application Specific Integrated Circuit).

[Process flow]
Hereinafter, processing of each functional unit of the structure displacement analysis apparatus 1 will be described with reference to a flowchart. FIG. 3 is a flowchart showing a flow of processing executed by the structure displacement analysis apparatus 1. Hereinafter, the processing of this flowchart will be described with reference to FIG. FIG. 4 is a diagram for explaining a processing process by the structure displacement analysis apparatus 1.

  First, acceleration data is acquired by the communication unit 10 (step S100). The acquired acceleration data is stored in the memory device 26 or the storage device 22. FIG. 4A is a diagram illustrating an example of acceleration data acquired by the communication unit 10.

  Next, filtering processing and zero padding processing are performed by the preprocessing unit 30 (steps S102 and S104). When analyzing the scene shown in FIG. 1, the filtering process is performed using a high-pass filter that excludes low frequencies of, for example, 0.1 [Hz] or less. As a result, a large displacement that may occur due to noise in the integration process can be excluded in advance. Further, the zero padding process is performed in order to normally operate the convolution process in the wavelet transform.

  Next, the wavelet transform unit 32 selects the mother wavelet (step S106. When analyzing the scene shown in FIG. 1, the displacement of the bridge B caused by the passage of the vehicle V is a half length having a very low frequency. The half-waveform waveform is a local waveform that does not form one wavelength including the plus side and the minus side, which is the displacement until the vehicle enters and exits the bridge B. This is because it mainly shows a movement that forcibly sinks vertically downward and returns to the original position when the vehicle leaves.Figure 5 shows an example of a half-wave waveform indicated by the displacement of the bridge B. Conventionally, analysis of half-waveform waveforms has been difficult, but the inverse double orthogonal wavelet (Reversebiothorgonal wavelet 2.2 (rbio2.2)) is used as the mother wavelet function. 6 shows an example of an inverse double orthogonal wavelet, which is an example of an inverse double orthogonal wavelet that detects the displacement caused by the passage of a vehicle. The inverse double orthogonal wavelet is also excellent in the phase reproducibility in the reconstruction described later.The inverse double orthogonal wavelet changes the phase when it is converted back to the time domain. Therefore, it is possible to suppress the occurrence of phase shift in the entire analysis.

  Next, the wavelet transform unit 32 performs wavelet transform using the mother wavelet selected in step S106 on the acceleration data that has been processed by the preprocessing unit 30 (step S108). The wavelet transform is performed by convolution processing of acceleration data and mother wavelet.

The wavelet transform is defined by, for example, equation (1). Here, W (b, a) is a wavelet coefficient, x (t) is a time series acceleration, ψ is a mother wavelet, a is a scale determining factor, and b is a shift determining factor. “*” Represents a conjugate complex number.

Expression (2) is a conditional expression indicating whether or not inverse wavelet transform is possible. The wavelet inverse transform is defined by equation (3).

From the equations (2) and (3), the time series data must be continuous according to the time and the scale determining factor a, but the measured acceleration data is generally discrete data. Therefore, the wavelet transform unit 32 performs a discrete continuous wavelet transform represented by Expression (4).

  FIG. 4B is a diagram illustrating an example of a processing result by the wavelet transform unit 32. As a result of the wavelet transform, three-dimensional data in which wavelet coefficients are associated with coordinates on a plane with time and frequency as axes is obtained.

  Return to the description of the flowchart. When the wavelet transform is performed, the frequency range setting unit 34 sets a frequency range in which wavelet coefficients are integrated and reconstructed (step S110). For example, the frequency range setting unit 34 sets a frequency range for performing wavelet transformation and wavelet inverse transformation in accordance with an input operation performed on the input unit 12 by the user. A broken line region R in FIG. 4B is an example of a frequency range set by the frequency range setting unit 34. As will be described later, when the scene shown in FIG. 1 is analyzed, the frequency range is set to, for example, 0.3 [Hz] to 10 [Hz]. Details of the setting of the frequency range will be described later.

Next, the wavelet coefficient integration unit 36 performs second-order integration of the wavelet coefficients within the frequency range set by the frequency range setting unit 34 (step S112). FIG. 4C shows an example of the result of second-order integration of wavelet coefficients. The second-order integration of wavelet coefficients is defined by equation (5).

  Next, the wavelet inverse transform unit 38 performs wavelet inverse transform on the second-order integral of the wavelet coefficients (step S114). When the wavelet coefficient obtained by wavelet transform of acceleration data is subjected to second-order integration, the displacement becomes the same as the wavelet coefficient obtained by wavelet transform. Therefore, if the second-order integral of wavelet coefficients obtained by wavelet transform of acceleration data is reconstructed by inverse wavelet transform, displacement can be obtained. FIG. 4D shows an example of a displacement obtained by inverse wavelet transformation.

Here, the displacement depending on the characteristics of the mother wavelet can be obtained by reconstructing the wavelet coefficient based on the measured acceleration. When the reconstruction of wavelet coefficients is shown by equation (6), the wavelet inverse transform is expressed using a delta function. Here, it is assumed that a _j and J are scales squared for convenience. a ₀ is the minimum scale, and δ _j is an index indicating the significant digits of the scale solution.

The following is the real part of the wavelet coefficient.

The reconstruction factor Cδ is expressed by equation (7).

In the process of inverse wavelet transformation, the estimated displacement value depends on the reconstructed frequency range. Therefore, the estimated displacement will be accurate when the frequency range is properly selected during reconstruction. As can be seen from equation (8), the displacement is obtained by numerically reconstructing the integral value of the wavelet coefficient in the wavelet domain obtained by wavelet transforming the measured acceleration.

  And the structure displacement analyzer 1 outputs the displacement (result) obtained by the wavelet inverse transformation by the output unit 14 (step S116).

[Regarding the setting of the frequency range]
As described above, the setting of the frequency range in step S110 in the flowchart of FIG. 3 is performed according to an input operation performed on the input unit 12 by the user, for example. The frequency range setting unit 34 may be set in advance according to the structure to be analyzed and set to a frequency range stored in the storage device 22 or the like.

  The frequency range is preferably obtained by analyzing the second-order integral of the wavelet coefficient. FIG. 7 is a diagram illustrating second-order integration of wavelet coefficients obtained for the bridge B through which the vehicle V passes. The left diagram in FIG. 6 shows the results up to 0 to 1 [Hz], and the right diagram in FIG. 6 shows the results up to 0 to 10 [Hz]. As shown in the left diagram of FIG. 6, the acceleration data of the bridge shows a large abnormal value at 0.2 [Hz]. To exclude this, the lower limit of the frequency range is set to a slightly high value, for example, 0.3 [ [Hz] is preferable. Regarding the upper limit of the frequency range, 1 to 11 [Hz] is conceivable, but in the region exceeding 10 [Hz], the integral value of the wavelet coefficient is close to zero, and it is preferable to set 10 [Hz] as the upper limit. .

  Here, it is preferable that the frequency range can be reset while referring to the result output in step S116 of FIG. FIG. 8 is a diagram illustrating an example of a result output screen for supporting the resetting of the frequency range. As shown in the figure, the structure displacement analysis apparatus 1 can visually recognize the first stable period T1 before the forced vibration by the vehicle V occurs and the second stable period T2 after the forced vibration by the vehicle V occurs. It displays using the output part 14 so that it may become. Each stable period is set as a period in which the entire monitoring period is divided by a predetermined width to obtain statistical index values such as variance and standard deviation, and the variance or the like is small. When the frequency range is not set appropriately, a bias occurs between the first stable period T1 and the second stable period T2, and for example, the average value of the displacement in the first stable period T1 and the displacement in the second stable period T2 Deviation occurs in the average value. The user may visually recognize this shift and reset the frequency range manually, or the structure displacement analyzer 1 may reset the frequency range repeatedly until the shift is within the allowable range. In addition, the structure displacement analysis apparatus 1 displays “OK” if the deviation is within the allowable range, and displays “NG” if the deviation is outside the allowable range, and supports manual resetting by the user. May be.

  FIG. 9 is a flowchart showing the flow of processing including resetting of the frequency range, which is executed by the structure displacement analysis apparatus 1. After the result output (step S116), the structure displacement analyzer 1 determines whether or not the frequency range needs to be reset (step S118). This determination may be performed based on an input operation performed on the input unit 12 by the user. For example, a difference between average values is obtained between the first stable period T1 and the second stable period T2 illustrated in FIG. If the difference is within the allowable range, it may be determined that it is not necessary to reset the frequency range, and if the difference is outside the allowable range, it is necessary to reset the frequency range.

  When it is determined that it is necessary to reset the frequency range, the structure displacement analyzer 1 resets the frequency range (step S120), and performs the processing from step S112 onward based on the reset frequency range. The resetting of the frequency range may be automatically performed by a predetermined width or may be manually input to the input unit 12 while the user looks at the display screen of the output unit 14.

[Verification example]
The inventor of the present application performed verification for confirming the accuracy of processing of the structure displacement analysis apparatus 1. FIG. 10 is an overhead view of the bridge B to be verified. FIG. 11 is a cross-sectional view in the AA direction in FIG. The single span composite bridge adopted for this verification is supported by three beams (G1, G2, G3). For measurement of acceleration, a three-axis wireless acceleration sensor (S1, S2, S3) was attached to the bridge B, and a laser Doppler displacement meter was used to verify whether or not the analysis could be performed more accurately. Laser reflection points (R1, R2, R3) were provided in the vicinity of the acceleration sensor. The beam has a length of 35.8 m and both ends are connected to an expansion joint. The sampling frequency of the acceleration sensor was 280 Hz.

  Under this condition, the forced vibration when the vehicle passed was 0.3 [Hz], and the resonance frequencies of the bridge B were 2.1 [Hz] and 2.8 [Hz]. FIG. 12 shows the frequency analysis result of the bridge B analyzed by Fast Fourier Transform (FFT).

  And the process equivalent to what was demonstrated in the Example was performed with respect to the acceleration data measured by each of acceleration sensor S1, S2, S3, and the displacement measured directly in a corresponding laser reflective point was compared. FIG. 13 is a diagram comparing the analysis result (analysis value) by the structure displacement analysis apparatus 1 and the measurement result (measurement value) measured by the laser Doppler displacement meter. The upper diagram of FIG. 13 is a diagram comparing the analysis result based on the measurement value of the acceleration sensor S1 attached to the beam G1 and the measurement result measured at the laser reflection point R1. The middle diagram of FIG. 13 is a diagram comparing the analysis result based on the measurement value of the acceleration sensor S2 attached to the beam G2 and the measurement result measured at the laser reflection point R2. The lower diagram of FIG. 13 is a diagram comparing the analysis result based on the measurement value of the acceleration sensor S2 attached to the beam G2 and the measurement result measured at the laser reflection point R2. As shown in the figure, it was found that analysis results sufficiently close to the measurement results were obtained at all measurement locations.

  According to the structure displacement analysis apparatus and the structure displacement analysis program of the present embodiment described above, the wavelet transform is performed on the acceleration data, the frequency range suitable for the displacement analysis of the structure is set, and the set frequency range The wavelet coefficient obtained by wavelet transform is second-order integrated, and the displacement of the structure is calculated more accurately by calculating the displacement of the structure by performing wavelet inverse transform on the integrated result. Can do.

  As mentioned above, although the form for implementing this invention was demonstrated using embodiment, this invention is not limited to such embodiment at all, In the range which does not deviate from the summary of this invention, various deformation | transformation and substitution Can be added.

DESCRIPTION OF SYMBOLS 1 Structure displacement analysis apparatus 10 Communication part 12 Input part 14 Output part 30 Preprocessing part 32 Wavelet transformation part 34 Frequency range setting part 36 Wavelet coefficient integration part 38 Wavelet inverse transformation part

Claims (5)

An acquisition unit for acquiring acceleration data measured by an acceleration sensor attached to the structure to be measured;
A wavelet transform unit that performs wavelet transform on the acceleration data;
A frequency range setting unit for setting a frequency range suitable for displacement analysis of the structure;
A wavelet coefficient integration unit for second-order integration of the wavelet coefficients obtained by the wavelet transform within the frequency range set by the frequency range setting unit;
A wavelet inverse transform unit that performs a wavelet inverse transform on the result of second-order integration by the wavelet coefficient integral unit to calculate a displacement of the structure;
A structure displacement analysis apparatus comprising: The structure is a bridge through which vehicles pass,
The wavelet transform unit uses an inverse double orthogonal wavelet as a mother wavelet.
The structure displacement analysis apparatus according to claim 1. It further includes an input unit that receives an input operation by the user,
The frequency range setting unit sets the frequency range based on an input operation performed on the input unit;
The structure displacement analysis apparatus according to claim 1 or 2. The frequency range setting unit automatically resets the frequency range by analyzing the displacement calculated by the wavelet inverse transform unit,
The structure displacement analysis apparatus according to any one of claims 1 to 3. On the computer,
Get acceleration data measured by an acceleration sensor attached to the structure to be measured,
Let the wavelet transform be performed on the acceleration data,
Set a frequency range suitable for displacement analysis of the structure,
Within the set frequency range, the wavelet coefficient obtained by the wavelet transform is second-order integrated,
A wavelet inverse transform is performed on the second-order integrated result to calculate the displacement of the structure;
Structure displacement analysis program.