CN117473263A - Automatic recognition method and system for frequency and damping ratio of bridge vibration monitoring - Google Patents
Automatic recognition method and system for frequency and damping ratio of bridge vibration monitoring Download PDFInfo
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Abstract
A frequency and damping ratio automatic identification method and system for bridge vibration monitoring comprises the following steps: s1, carrying out Fourier transformation on actual monitoring data of a bridge to obtain approximate first-order self-vibration frequency of the bridge, and constructing a free damping vibration signal of a damped single-degree-of-freedom spring vibrator by setting an initial damping ratio; s2, positioning and screening out a plurality of signals with the highest degree of correlation with the constructed free damping vibration signals in the actual monitoring data by using a cross-correlation function; s3, dividing the screened first plurality of segments of signals into single-frequency free damping vibration signals and multi-frequency free damping vibration signals according to frequency spectrum analysis, and respectively calculating the single-frequency free damping vibration signals and the multi-frequency free damping vibration signals to obtain frequency and damping ratios. The invention has the advantages of wide applicability, high identification precision, high working efficiency and no need of priori information.
Description
Technical Field
The invention relates to the field of bridge health monitoring, in particular to an automatic frequency and damping ratio identification method and system for bridge vibration monitoring.
Background
The frequency and damping ratio are important modal parameters of the bridge structure, reflect the overall safety level of the bridge, and play an important role in bridge health monitoring. Bridge frequencies are typically obtained by fourier transforms. However, due to the influence of passing vehicles, the measurement of the frequency often has a certain error. On the other hand, how to accurately estimate the damping ratio from the monitored data remains a challenge.
The damping ratio is generally calculated by a half-power bandwidth method, an exponential decay method (EA), a random subspace identification method (SSI), a characteristic system implementation algorithm (ERA), an autoregressive model with exogenous input, frequency domain decomposition, a subspace state space identification numerical algorithm, continuous wavelet transformation and the like. Among these methods, the EA method is generally considered to be a relatively reliable and accurate method. However, this method requires a structural free vibration response and therefore can only be used for vibration tests where a controlled excitation can be applied, such as falling weights and jumping trucks.
In fact, during the daily operation of a bridge, the excitation to which the bridge is subjected is usually brought about by the traffic flow on the bridge. This is a typical non-stationary random excitation. The bridge does not generate free vibration under the random traffic flow. The excitation transmitted by the bridge peripheral traffic through the soil structure coupling effect can be approximately regarded as pulse excitation, namely the time of acting on the bridge is negligible compared with the time of the bridge vibration response. Under the excitation of the bridge, obvious free damping vibration is generated. If a similar free damping vibration signal cannot be found from the monitoring data of the bridge, it is difficult to accurately extract the damping ratio and frequency of the bridge. However, manually extracting such responses from large amounts of data by manual means is impractical.
Therefore, there is a technical difficulty in identifying the frequency to damping ratio of the bridge from the monitoring data of the bridge.
Disclosure of Invention
The invention mainly aims to overcome the defects in the prior art, and provides the automatic identification method and the system for the frequency and damping ratio of bridge vibration monitoring, which have the advantages of wide applicability, high identification precision, high working efficiency and no need of priori information.
The invention adopts the following technical scheme:
the automatic identification method for the frequency and damping ratio of bridge vibration monitoring is characterized by comprising the following steps of:
s1, carrying out Fourier transformation on actual monitoring data of a bridge to obtain approximate first-order self-vibration frequency of the bridge, and constructing a free damping vibration signal of a damped single-degree-of-freedom spring vibrator by setting an initial damping ratio;
s2, positioning and screening out the first segments of signals with the largest degree of correlation between the actual monitoring data and the constructed free damping vibration signals by using a cross-correlation function;
s3, dividing the screened first plurality of segments of signals into single-frequency free damping vibration signals and multi-frequency free damping vibration signals according to frequency spectrum analysis, and respectively calculating the single-frequency free damping vibration signals and the multi-frequency free damping vibration signals to obtain frequency and damping ratios;
and S4, drawing the frequencies and the damping of the signals of the first sections into frequency-damping scatter diagrams, and respectively averaging the calculated frequencies and damping ratios to obtain a final recognition result.
The step S1 specifically includes:
preprocessing actual monitoring data;
defining the acceleration signal of the preprocessed actual monitoring data as X (t), wherein the acceleration signal X (t) is the sampling frequency f s Sampling time is T X Of a signal length L X ，L X ＝f s T X ；
Fourier transforming X (t):
where e is the natural logarithm, i is the imaginary unit, ω is the circular frequency;
judging the position of the highest peak in the frequency spectrum through peak picking to obtain the approximate bridge first-order natural vibration frequency
The initial damping ratio is formulatedAnd is configured with a signal Y (t) damping the free damped vibrations of the single degree of freedom spring vibrator:
the signal Y (t) is the same as f in sampling frequency s Sampling time is T Y Of a signal length L Y ，L Y ＝f s T Y 。
The pretreatment comprises the following steps:
firstly, carrying out trend term removal processing on the actual monitoring data to remove the offset in an original signal;
secondly, low-pass filtering is carried out on the actual monitoring data to reduce interference of measurement noise.
The step S2 specifically includes:
calculating a cross-correlation function of the acceleration signal X (t) and the free damped vibration signal Y (t):
thereby obtaining a correlation vector between signals X (t) and Y (t)And at the same time obtain the lag index vector of the correlation +.>
Taking the first k values with the largest absolute value in the correlation vector R, finding the corresponding position indexes in the lag index vector L, screening out the first k segments of signals with the largest correlation degree between the actual monitoring data and the constructed free damping vibration signals, and X 1 (t)，X 2 (t)，……，X k (t)。
The step S3 specifically includes:
for the first several segments of signals X 1 (t)，X 2 (t)，……，X k (t) fourier transforming:
wherein e is natural logarithm, i is imaginary unit, ω is circular frequency, and the value range of k is 10-30;
peak value in each frequency spectrum is obtained through peak value pickup, wherein the peak value is larger than an initial set threshold value and is marked as an effective peak value; the signal with the effective peak number of 1 is the single-frequency free damping vibration signal, and the signal with the effective peak number of more than 1 is the multi-frequency free damping vibration signal.
In step S3, the single-frequency free damping vibration signal is directly calculated by using an exponential damping method to obtain a frequency and a damping ratio, and a peak value a in the signal is obtained through peak pickup m And corresponding time t m And the serial number m, the logarithm of the wave peak value and the serial number corresponding to the logarithm of the wave peak value are subjected to linear fitting through a least square method, and the obtained result is:
lnA＝a·n+b
wherein lnA is peak logarithmic value, n is wave number,
wherein M is the total wave number of the single-frequency free damping vibration signal;
calculating a damping ratio:
calculating the frequency:
in step S3, the multi-frequency free-damping vibration signal is decomposed into a plurality of single-frequency free-damping vibration signals by a variational nonlinear component decomposition method, and the respective frequency and damping ratio of each single-frequency free-damping vibration signal is calculated by an exponential decay method.
The utility model provides a frequency and damping ratio automatic identification system of bridge vibration monitoring which characterized in that includes:
the acceleration sensor is arranged below the main beam of the bridge and is used for converting the vibration acceleration of the bridge into a voltage signal so as to measure the vibration acceleration of the bridge;
the signal acquisition module receives the voltage signal transmitted by the acquisition accelerometer, converts the voltage signal from an analog signal to a digital signal, and records the signal;
the correlation analysis module is used for receiving the time-course signals recorded by the signal acquisition module and screening free damping vibration signals in the signals by using a cross-correlation function;
the time-frequency analysis module receives the free damping vibration signals output by the correlation analysis module, divides the free damping vibration signals into single-frequency free damping vibration signals and multi-frequency free damping vibration signals by utilizing Fourier transformation, and then decomposes the multi-frequency free damping vibration signals into a plurality of single-frequency free damping vibration signals by utilizing variational nonlinear component decomposition;
and the linear fitting module is used for receiving the single-frequency free damping vibration signal output by the time-frequency analysis module and calculating the frequency and damping of the bridge by utilizing linear fitting.
As can be seen from the above description of the present invention, compared with the prior art, the present invention has the following advantages:
1. the method can realize the whole process automatic identification from the extraction of the free attenuation signal from the actual measurement signal to the identification of the damping ratio, realize the automatic identification under the condition that a database is established without manually screening the signal section, can be well applied to real-time and continuous signal processing, and has wide application prospect in bridge health detection.
2. Compared with the traditional damping identification method, the damping single free damping signal with the structure self-vibration frequency structure, which is obtained by carrying out Fourier transformation on the actual signal, is insensitive to the vibration form of the free damping signal in the actual measurement signal, has strong robustness, and is more suitable for working in an operation environment.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a graph of acceleration time response at a distributed measurement point of a bridge;
FIG. 3 is a signal of free damped vibration of a constructed damped single degree of freedom spring vibrator;
FIG. 4 is a correlation coefficient between actual monitoring data of 03B0105 distributed measurement points and a constructed attenuation signal;
FIG. 5 is a schematic diagram of actual monitoring data and identified attenuation segments of 03B0105 distributed measurement points;
FIG. 6 is a damping ratio calculation process;
FIG. 7 is a graph showing the frequency-damping ratio scattering point distribution and the average value of 03B0105 distributed measuring points;
FIG. 8 is a correlation coefficient between the measured signal at 03B0114 distributed stations and the constructed attenuation signal;
FIG. 9 is a diagram of measured signals and identified attenuation segments of 03B0114 distributed stations;
FIG. 10 is a signal decomposition diagram;
FIG. 11 is a damping ratio calculation process;
FIG. 12 is a graph showing the distribution of the first-order frequency-damping ratio and the second-order frequency-damping ratio and the average value thereof.
The invention is further described in detail below with reference to the drawings and the specific examples.
Detailed Description
The invention is further described below by means of specific embodiments.
The invention will now be described in greater detail and with reference to the accompanying drawings and examples. The drawings and the embodiments provide a more visual understanding for the reader, so that the structure, the working principle and the application scene of the invention can be more clearly presented and understood.
Referring to fig. 1, a method for automatically identifying frequency and damping ratio of bridge vibration monitoring includes:
s1, carrying out Fourier transformation on actual monitoring data of a bridge to obtain approximate first-order self-vibration frequency of the bridge, and constructing a free damping vibration signal of a damped single-degree-of-freedom spring vibrator by setting an initial damping ratio.
The method specifically comprises the following steps:
the actual monitoring data is preprocessed. The pretreatment comprises the following steps: firstly, carrying out trend term removal processing on actual monitoring data to remove offset in an original signal; secondly, the interference of measurement noise is reduced by carrying out low-pass filtering on the actual monitoring data.
The acceleration signal of the preprocessed actual monitoring data is defined as X (t), and the signal X (t) is the sampling frequency f s Sampling time is T X Of a signal length L X ，L X ＝f s T X ；
Fourier transforming X (t):
where e is the natural logarithm, i is the imaginary unit, and ω is the circular frequency.
Judging the position of the highest peak in the frequency spectrum through peak picking to obtain the approximate bridge first-order natural vibration frequency
The initial damping ratio is formulatedAnd is configured with a signal Y (t) damping the free damped vibrations of the single degree of freedom spring vibrator:
the signal Y (t) is the same as f in sampling frequency s Sampling time is T Y Time series (recommended length is 10 times to 20 times of bridge approximate first-order period), signal length is L Y ，L Y ＝f s T Y 。
S2, positioning and screening out a plurality of signals with the highest degree of correlation with the constructed free damping vibration signals in the actual monitoring data by using a cross-correlation function. The method specifically comprises the following steps:
calculating a cross-correlation function of the acceleration signal X (t) and the free damped vibration signal Y (t):
thereby obtaining a correlation vector between signals X (t) and Y (t)And at the same time obtain the lag index vector of the correlation +.>
Taking the first k values with the largest absolute value in the correlation vector R, finding the corresponding position indexes in the lag index vector L, screening out the first k segments of signals with the largest correlation degree between the actual monitoring data and the constructed free damping vibration signals, and X 1 (t)，X 2 (t)，……，X k (t)。
S3, dividing the screened first plurality of segments of signals into single-frequency free damping vibration signals and multi-frequency free damping vibration signals according to frequency spectrum analysis, and respectively calculating the single-frequency free damping vibration signals and the multi-frequency free damping vibration signals to obtain frequency and damping ratios;
the method specifically comprises the following steps:
for the first several segments of signals X 1 (t)，X 2 (t)，……，X k (t) fourier transforming:
where e is the natural logarithm, i is the imaginary unit, and ω is the circular frequency. The value range of k is 10-30.
Peak value in each frequency spectrum is obtained through peak value pickup, wherein the peak value is larger than an initial set threshold value and is marked as an effective peak value; the signal with the effective peak number of 1 is a single-frequency free damping vibration signal, and the signal with the effective peak number of more than 1 is a multi-frequency free damping vibration signal.
Directly calculating a single-frequency free damping vibration signal by using an exponential damping method to obtain a frequency and damping ratio, and obtaining a peak value A in the signal through peak pickup m And corresponding time t m And the serial number m, the logarithm of the wave peak value and the serial number corresponding to the logarithm of the wave peak value are subjected to linear fitting through a least square method, and the obtained result is:
lnA＝a·n+b
wherein lnA is peak logarithmic value, n is wave number,
wherein M is the total wave number of the single-frequency free damping vibration signal;
calculating a damping ratio:
calculating the frequency:
for the multi-frequency free damping vibration signals, the signals are decomposed into a plurality of single-frequency free damping vibration signals by a variational nonlinear component decomposition method, and then the respective frequency and damping ratio of each single-frequency free damping vibration signal are calculated by an exponential decay method.
And S4, drawing the frequencies and the damping of the signals of the first sections into frequency-damping scatter diagrams, and respectively averaging the calculated frequencies and damping ratios to obtain a final recognition result.
Based on the above, the invention also provides an automatic recognition system for the frequency and damping ratio of bridge vibration monitoring, which comprises the following steps:
the acceleration sensor is arranged below the main beam of the bridge and is used for converting the vibration acceleration of the bridge into a voltage signal so as to measure the vibration acceleration of the bridge;
the signal acquisition module receives the voltage signal transmitted by the acquisition accelerometer, converts the voltage signal from an analog signal to a digital signal, and records the signal;
the correlation analysis module is used for receiving the time-course signals recorded by the signal acquisition module and screening free damping vibration signals in the signals by using a cross-correlation function;
the time-frequency analysis module receives the free damping vibration signals output by the correlation analysis module, divides the free damping vibration signals into single-frequency free damping vibration signals and multi-frequency free damping vibration signals by utilizing Fourier transformation, and then decomposes the multi-frequency free damping vibration signals into a plurality of single-frequency free damping vibration signals by utilizing variational nonlinear component decomposition;
and the linear fitting module is used for receiving the single-frequency free damping vibration signal output by the time-frequency analysis module and calculating the frequency and damping of the bridge by utilizing linear fitting.
The system of the invention adopts the automatic recognition method of the frequency and damping ratio of bridge vibration monitoring, draws the frequency and damping of the first several sections of signals into a frequency-damping scatter diagram, and respectively averages the calculated frequency and damping ratio to obtain the final recognition result.
The invention can automatically extract the low-order frequency and damping ratio of the bridge from the structural vibration monitoring signal, has the advantages of wide applicability, high identification precision, high working efficiency and no need of priori information, and has wide application prospect in bridge health detection.
Application example
Taking a certain Z24 bridge as an example, the bridge is a classical post-tensioning prestressed concrete double-unit box girder bridge, the main span is 30 meters, and the spans at two sides are 14 meters. The bridge is monitored for nearly one year, and manually-controllable damage is gradually applied in the later monitoring period. Researchers use a Z24 bridge as an engineering background of a civil engineering system, determine a study subject SIMCES, establish a reference problem of the Z24 bridge, and study a series of problems in the field of health monitoring, including natural frequency, vibration mode, damping ratio under bridge damage and structural modal parameter transformation caused by environmental factors, wherein the Z24 bridge becomes a base bridge for a plurality of students to study bridge health monitoring. Therefore, the bridge is selected as a research object of the test to have a strong practical meaning.
Some Z24 bridge monitoring is divided into 9 distributions, each distribution has 33 channels, 28 channels are located on the bridge deck, 5 fixed channels are reference points, 3 reference point channels are located on the bridge deck, and 2 test channels are located on the bridge pier. 65536 samples are collected by a certain Z24 bridge sensor at a sampling rate of 100Hz, and after bin format data provided by an SVS website are converted into a mat format in MATLAB, an acceleration time-course response curve of a certain distributed measuring point of the Z24 bridge can be obtained, as shown in figure 2. Under ambient excitation, there are many typical free decay signals for the vibration signal. It is worth mentioning that the measured data for identification does not need a plurality of measuring points, and the monitoring data collected by a single acceleration sensor can be used for identification by the method, so that the defect of installing a plurality of sensors can be avoided by adopting the automatic identification technology of the method.
Firstly, carrying out Fourier transformation on actual monitoring data to obtain approximate first-order self-vibration frequency of a bridge, and constructing a signal of free damping vibration of a damped single-degree-of-freedom spring oscillator by setting an initial damping ratio. Figure 3 shows a damped free decay time curve for the construct.
Next, the correlation coefficient between the measured signal and the constructed free damped vibration signal is determined by using the cross-correlation function, as shown in fig. 4, and the first several signals at the screening site are located by using the correlation magnitude between the two signals, and the result is shown in fig. 5.
And finally, further screening, namely separating the screened first plurality of segments of signals into single-frequency free damping vibration signals and multi-frequency free damping vibration signals according to spectrum analysis. And obtaining the peak value in each frequency spectrum through peak value pickup, wherein the peak value is larger than the initial set threshold value and is marked as an effective peak value. The signal with the effective peak number of 1 is a single-frequency free damping vibration signal, and the signal with the effective peak number of more than 1 is a multi-frequency free damping vibration signal.
For the single-frequency signal, the damping ratio and the frequency are obtained directly by using Fourier transformation and an exponential decay method, and the logarithm of the wave peak value and the corresponding serial number are subjected to linear fitting through a least square method, as shown in FIG. 6, wherein (a) is a certain extracted attenuation section, and (b) is the linear fitting of the peak value and the wave number. Further, the damping ratio and frequency were calculated, and as a result, the distribution of the distribution measuring point frequency-damping ratio scattering point distribution and the average value (+) were shown in fig. 7. Since in this example the original data only contains the first order free damped vibration signal, only the first order frequency can be obtained after fourier transformation of the damped section extracted from the measured data. The results of the automatic recognition proposed by the present invention are compared with the reference-based combined deterministic-random subspace and the natural frequency and damping ratio of the DBSCAN-based recognition, as shown in table 1.
TABLE 1
For further testing, the method can also be applied to the identification of the damping ratio of the multi-frequency free damping vibration signals, and selects the acceleration data (03B 0114) of the channel 5 at a certain moment of the Z24 bridge, or utilizes the damped single-degree-of-freedom free damping vibration signals constructed as shown in fig. 3 to position and screen the free damping signals in the actual measurement signals.
Next, the correlation coefficient between the measured signal and the constructed free damped vibration signal is determined by using the cross-correlation function, as shown in fig. 8, and the first several signals at the screening site are located by using the correlation magnitude between the two signals, and the result is shown in fig. 9.
For a multi-frequency signal, it is first decomposed into a plurality of single-frequency signals using a variational nonlinear component decomposition method, as shown in fig. 10, (a) is an original signal; (b) is a decomposed first order single frequency signal; (c) is a decomposed second order single frequency signal. FIG. 11 shows a process of calculating a damping ratio of a decomposed single frequency signal by using an exponential decay method, (a) is a decomposed single frequency signal; (b) is a peak pair value linear fit to wave number. And then, frequency is obtained by Fourier transformation on each single-frequency signal, and an arithmetic average value is taken, so that a frequency-damping scatter diagram of the vibration signal is freely attenuated, such as a first-order frequency-damping ratio, a second-order frequency-damping ratio scatter diagram and an average value (∈) thereof in FIG. 12. The results of the automatic recognition proposed by the present invention are compared with the reference-based combined deterministic-random subspace and the natural frequency and damping ratio of the DBSCAN-based recognition, as shown in table 2. The damping ratio automatic identification method based on the structural vibration monitoring data realizes automatic frequency and damping ratio identification, and can be well applied to real-time and continuous signal processing.
TABLE 2
Further, the vibration condition of the free damping signal screened from the measured signal is not very similar to the vibration condition of the signal of the damping single-degree-of-freedom free damping vibration, but can be identified and extracted finally. The attenuation segments in the data can be identified as long as the attenuation response curve present in the measured data approximately meets the shape of the constructed damped free attenuation curve. In the Z24 bridge actual measurement data test, the automatic mode identification method provided by the invention has strong robustness and is expected to be applied to real-time health monitoring.
It should be emphasized that the foregoing examples are merely illustrative of the present invention and are not meant to be the only definition thereof. While the invention has been described in detail with reference to preferred embodiments, those skilled in the relevant art will recognize that they can make suitable adjustments or substitutions of equivalents thereto, and that such changes should be made without departing from the spirit and scope of the invention, as defined by the claims.
Claims (8)
1. The automatic identification method for the frequency and damping ratio of bridge vibration monitoring is characterized by comprising the following steps of:
s1, carrying out Fourier transformation on actual monitoring data of a bridge to obtain approximate first-order self-vibration frequency of the bridge, and constructing a free damping vibration signal of a damped single-degree-of-freedom spring vibrator by setting an initial damping ratio;
s2, positioning and screening out the first segments of signals with the largest degree of correlation between the actual monitoring data and the constructed free damping vibration signals by using a cross-correlation function;
s3, dividing the screened first plurality of segments of signals into single-frequency free damping vibration signals and multi-frequency free damping vibration signals according to frequency spectrum analysis, and respectively calculating the single-frequency free damping vibration signals and the multi-frequency free damping vibration signals to obtain frequency and damping ratios;
and S4, drawing the frequencies and the damping of the signals of the first sections into frequency-damping scatter diagrams, and respectively averaging the calculated frequencies and damping ratios to obtain a final recognition result.
2. The automatic recognition method of the frequency and damping ratio for bridge vibration monitoring according to claim 1, wherein the step S1 specifically comprises:
preprocessing actual monitoring data;
defining the acceleration signal of the preprocessed actual monitoring data as X (t), wherein the acceleration signal X (t) is the sampling frequency f s Sampling time is T X Of a signal length L X ，L X ＝f s T X ；
Fourier transforming X (t):
where e is the natural logarithm, i is the imaginary unit, ω is the circular frequency;
judging the position of the highest peak in the frequency spectrum through peak picking to obtain the approximate bridge first-order natural vibration frequency
The initial damping ratio is formulatedAnd is configured with a signal Y (t) damping the free damped vibrations of the single degree of freedom spring vibrator:
the signal Y (t) is the same as f in sampling frequency s Sampling time is T Y Of a signal length L Y ，L Y ＝f s T Y 。
3. The automatic recognition method of the frequency-damping ratio of bridge vibration monitoring according to claim 2, wherein the preprocessing comprises:
firstly, carrying out trend term removal processing on the actual monitoring data to remove the offset in an original signal;
secondly, low-pass filtering is carried out on the actual monitoring data to reduce interference of measurement noise.
4. The automatic recognition method of the frequency and damping ratio for bridge vibration monitoring according to claim 2, wherein the step S2 specifically comprises:
calculating a cross-correlation function of the acceleration signal X (t) and the free damped vibration signal Y (t):
thereby obtaining a correlation vector between signals X (t) and Y (t)And at the same time obtain the lag index vector of the correlation +.>
Taking the first k values with the largest absolute value in the correlation vector R, finding the corresponding position indexes in the lag index vector L, screening out the first k segments of signals with the largest correlation degree between the actual monitoring data and the constructed free damping vibration signals, and X 1 (t)，X 2 (t)，……，X k (t)。
5. The automatic recognition method of the frequency and damping ratio for bridge vibration monitoring according to claim 1, wherein the step S3 specifically comprises:
for the first several segments of signals X 1 (t)，X 2 (t)，……，X k (t) fourier transforming:
where e is the natural logarithm, i is the imaginary unit, and ω is the circular frequency. The value range of k is 10-30;
peak value in each frequency spectrum is obtained through peak value pickup, wherein the peak value is larger than an initial set threshold value and is marked as an effective peak value; the signal with the effective peak number of 1 is the single-frequency free damping vibration signal, and the signal with the effective peak number of more than 1 is the multi-frequency free damping vibration signal.
6. The automatic recognition method of the frequency and damping ratio based on bridge vibration monitoring data according to claim 1, wherein the method comprises the following steps: in step S3, the single-frequency free damping vibration signal is directly calculated by using an exponential damping method to obtain a frequency and a damping ratio, and a peak value a in the signal is obtained through peak pickup m And corresponding time t m And the serial number m, the logarithm of the wave peak value and the serial number corresponding to the logarithm of the wave peak value are subjected to linear fitting through a least square method, and the obtained result is:
ln A＝a·n+b
wherein lnA is peak pair number, n is wave number,
wherein M is the total wave number of the single-frequency free damping vibration signal;
calculating a damping ratio:
calculating the frequency:
7. the automatic recognition method of the frequency and damping ratio based on bridge vibration monitoring data according to claim 1, wherein the method comprises the following steps: in step S3, the multi-frequency free-damping vibration signal is decomposed into a plurality of single-frequency free-damping vibration signals by a variational nonlinear component decomposition method, and the respective frequency and damping ratio of each single-frequency free-damping vibration signal is calculated by an exponential decay method.
8. The utility model provides a frequency and damping ratio automatic identification system of bridge vibration monitoring which characterized in that includes:
the acceleration sensor is arranged below the main beam of the bridge and is used for converting the vibration acceleration of the bridge into a voltage signal so as to measure the vibration acceleration of the bridge;
the signal acquisition module receives the voltage signal transmitted by the acquisition accelerometer, converts the voltage signal from an analog signal to a digital signal, and records the signal;
the correlation analysis module is used for receiving the time-course signals recorded by the signal acquisition module and screening free damping vibration signals in the signals by using a cross-correlation function;
the time-frequency analysis module receives the free damping vibration signals output by the correlation analysis module, divides the free damping vibration signals into single-frequency free damping vibration signals and multi-frequency free damping vibration signals by utilizing Fourier transformation, and then decomposes the multi-frequency free damping vibration signals into a plurality of single-frequency free damping vibration signals by utilizing variational nonlinear component decomposition;
and the linear fitting module is used for receiving the single-frequency free damping vibration signal output by the time-frequency analysis module and calculating the frequency and damping of the bridge by utilizing linear fitting.
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| CN117688480A (en) * | 2024-02-04 | 2024-03-12 | 四川华腾公路试验检测有限责任公司 | Bridge damage identification method based on damage frequency panorama and random forest |
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| CN117688480B (en) * | 2024-02-04 | 2024-05-14 | 四川华腾公路试验检测有限责任公司 | Bridge damage identification method based on damage frequency panorama and random forest |
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