CN104732097A - Correcting method for power spectrum in modal frequency identification of railroad bridge under strong signal interference - Google Patents

Abstract

The invention discloses a method for correcting power spectrum data in modal frequency identification of railway bridges under strong signal interference. Install the acceleration sensor on the railway bridge, analyze the power spectrum of the time-domain vibration signal obtained by the acceleration sensor, and obtain the measured power spectrum curve; establish the finite element analysis model of the railway bridge, and analyze the dynamic characteristics to obtain the theoretical modal frequency of the railway bridge , according to the theoretical modal frequency, determine the frequency interval of the measured power spectrum curve to be corrected; use DS evidence theory to correct the data of the measured power spectrum curve in the frequency range to be corrected, and identify the railway bridge according to the peak position of the corrected power spectrum curve The measured modal frequency of . After the present invention corrects the measured power spectrum data of the railway bridge, it can accurately identify the modal frequency of the railway bridge, effectively overcomes the adverse effects of strong signal interference on the measured power spectrum data, and will be widely used and popularized .

Description

Correction method of power spectrum in modal frequency identification of railway bridge under strong signal interference

technical field

The invention relates to the field of non-destructive testing of railway bridge engineering, in particular to a method for correcting power spectrum data in modal frequency identification of railway bridges under strong signal interference.

Background technique

High-speed trains may generate relatively large vibrations when running on railway bridges, and the impact on the safety of high-speed trains and bridge structures must be taken seriously. Therefore, carrying out vibration monitoring for railway bridges has important application value for ensuring the operation safety of railway bridges. The important content of railway bridge vibration monitoring is to identify the modal frequency of the bridge, and reflect the vibration state of the railway bridge through the change of the modal frequency. The common method of bridge modal frequency identification is the peak picking method based on power spectrum analysis, that is, an acceleration sensor is installed on the bridge structure, and the time domain signal of structural vibration is collected through the acceleration sensor, and then the power spectrum analysis is performed on the vibration time domain signal to obtain the power Spectral curve, according to the principle that the power spectrum curve has a peak value at the structural modal frequency, the bridge modal frequency can be directly identified from the power spectrum diagram. The peak picking method has been widely used in the modal frequency identification of highway bridge structures.

However, when the peak picking method is used to identify the modal frequencies of railway bridges, there is a problem of strong signal interference. This is because a variety of instruments and communication equipment are installed in the line engineering of railway bridges to transmit information about the operating conditions of rolling stock, the status of driving equipment, and instructions and orders for driving. These instruments and communication equipment will produce significant strong interference signals in the vibration time domain signal of the railway bridge, resulting in not only peaks corresponding to the measured modal frequencies of the bridge on the power spectrum curve, but also "pseudo" caused by various interference signals. peaks, which cause "false" peaks that are random. Therefore, the strong interference signal will cause the power spectrum diagram to be more disordered, and the modal frequency of the railway bridge cannot be directly determined according to the peak value of the power spectrum.

Contents of the invention

Purpose of the invention: In order to overcome the deficiencies in the prior art, the present invention provides a method for correcting the power spectrum in the modal frequency identification of railway bridges under strong signal interference, which is used to solve the problems in identifying the modal frequencies of railway bridges using the peak method. The technical problem that the power spectrum diagram is relatively disordered due to strong interference, and the modal frequency of the railway bridge cannot be determined directly according to the peak value of the power spectrum.

Technical scheme: in order to achieve the above object, the technical scheme adopted in the present invention is:

A method for correcting power spectrum in modal frequency identification of railway bridges under strong signal interference, comprising the following steps performed in sequence:

Step 1, the acceleration sensor is installed on the railway bridge to measure the time domain vibration signal of the railway bridge;

Step 2, performing power spectrum analysis on the time-domain vibration signal acquired by the acceleration sensor to obtain a measured power spectrum curve;

Step 3, establish the finite element analysis model of the railway bridge, and perform dynamic characteristic analysis to obtain the theoretical modal frequency f _D of the railway bridge; and _determine the frequency interval to be corrected for the measured power spectrum curve according to the theoretical modal frequency f D as [f ₁ ,f ₂ ], wherein, the lower limit value of the frequency interval f ₁ =f _D ×0.9, the upper limit value of the frequency interval f ₂ =f _D ×1.1;

Step 4. Use DS evidence theory to correct the data in the frequency range [f ₁ , f ₂ ] of the measured power spectrum curve obtained in step 2;

Step 5: Identify the measured modal frequency f _E of the railway bridge according to the peak position of the corrected power spectrum curve.

Further, in the present invention, in step 2, a set of measured power spectrum curves is obtained every 10 minutes; in step 4, the correction method is as follows: for the frequency value f _i within the frequency interval [f ₁ , f ₂ ], m ₁ (f _i ), m ₂ (f _i ), m ₃ (f _i ), m ₄ (f _i ), m ₅ (f _i ), m ₆ (f _i ) are 6 groups obtained within 1 hour respectively The power spectrum value corresponding to the frequency value f _i in the measured power spectrum curve; calculate the corrected power spectrum value M(f _i ) corresponding to the frequency value f _i within the hour according to the following formulas (1) to (5):

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 5</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 5</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

$\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 6</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 6</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

The measured power spectrum values corresponding to all frequency values in the frequency interval [f ₁ , f ₂ ] are corrected according to the above method, and finally the corrected power spectrum curve is obtained.

Beneficial effects: Due to the significant strong interference signal in the line engineering of the railway bridge, the power spectrum diagram is relatively disordered, and the modal frequency of the railway bridge cannot be determined according to the peak value of the power spectrum. The invention adopts the D-S evidence theory to correct the measured power spectrum data, which can effectively suppress the power spectrum value caused by the strong interference signal, and remarkably amplify the power spectrum value corresponding to the measured modal frequency, so that the modal frequency of the railway bridge can be accurately identified. The method is simple and convenient to implement, and can be widely promoted and applied.

Description of drawings

Fig. 1 is the front view of Nanjing Dashengguan Bridge of Beijing-Shanghai high-speed railway in the embodiment of the present invention;

Fig. 2 is the data of 6 groups of measured power spectrum curves in the frequency interval to be corrected in the embodiment of the present invention;

Fig. 3 is a power spectrum curve after correction in the frequency interval to be corrected in the embodiment of the present invention.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings.

A method for correcting power spectrum in railway bridge modal frequency identification under strong signal interference of the present invention, the method comprises the following steps:

(1) The acceleration sensor is installed on the railway bridge to measure the time domain vibration signal of the railway bridge;

(2) With 10 minutes as the calculation interval, the power spectrum analysis is performed on the time-domain vibration signal obtained by the acceleration sensor, and 6 sets of measured power spectrum curves can be obtained within 1 hour;

(3) Establish the finite element analysis model of the railway bridge, and analyze the dynamic characteristics to obtain the theoretical modal frequency f _D of the railway bridge. According to the theoretical modal frequency f _D , the frequency interval to be corrected for the measured power spectrum curve is determined as [f ₁ , f ₂ ], where the lower limit value f ₁ of the frequency interval is f ₁ = f _D × 0.9, and the upper limit of the frequency interval The value f ₂ is f ₂ =f _D ×1.1.

(4) Taking 1 hour as the calculation interval, the DS evidence theory is used to correct the data of the six groups of measured power spectrum curves obtained in step (2) within the frequency interval [f ₁ , f ₂ ] to be corrected:

(4a) Let f _i be a certain frequency value in the frequency interval [f ₁ , f ₂ ], m ₁ (f _i ), m ₂ (f _i ), m ₃ (f _i ), m ₄ (f _i ) , m ₅ (f _i ), m ₆ (f _i ) are the power spectrum values corresponding to the frequency f _i in the six groups of measured power spectrum curves respectively, then the corrected power spectrum value M(f _i ) is calculated according to the following formula ( T ₁ (f _i ), T ₂ (f _i ), T ₃ (f _i ) and T ₄ (f _i ) are intermediate calculation results):

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}$

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 5</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 5</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 6</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 6</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}$

(4b) Correct the measured power spectrum values corresponding to all frequency values in the frequency interval [f ₁ , f ₂ ] according to step (4a), and finally obtain the corrected power spectrum curve.

(5) Identify the measured modal frequency f _E of the railway bridge according to the peak position of the corrected power spectrum curve.

Example:

Taking the modal frequency recognition of the Nanjing Dashengguan Bridge of the Beijing-Shanghai High-speed Railway as an example below, the specific implementation process of the present invention is illustrated:

(1) The overall structure of Nanjing Dashengguan Bridge is shown in Figure 1. A vertical acceleration sensor is installed at the mid-span position of the bridge to measure the time-domain vibration signal of the railway bridge.

(2) With 10 minutes as the calculation interval, the power spectrum analysis is performed on the time-domain vibration signals obtained by the acceleration sensor, and 6 sets of measured power spectrum curves can be obtained within 1 hour.

(3) Establish the finite element analysis model of Nanjing Dashengguan Bridge, and conduct dynamic characteristic analysis (the analysis results of the first-order vertical vibration frequency are given in this embodiment). The calculation shows that the theoretical modal frequency f _D of the first-order vertical vibration of Dashengguan Bridge is 0.3280Hz, so the frequency range to be corrected for the measured power spectrum curve is [0.2952Hz, 0.3608Hz].

(4) The data of the 6 groups of measured power spectrum curves obtained in step (2) in the frequency range [0.2952Hz, 0.3608Hz] to be corrected are shown in Figure 2. It can be seen from the figure that the power spectrum identified multiple times under strong signal interference is relatively disordered, and the first-order vertical vibration frequency of the bridge cannot be effectively determined.

(5) The 6 groups of measured power spectrum data corresponding to all frequency values in the frequency interval [0.2952Hz, 0.3608Hz] are corrected using DS evidence theory, and the corrected power spectrum curve is shown in Figure 3. From the peak position in the figure, it can be accurately identified that the measured frequency f _E of the first-order vertical vibration is 0.3174Hz. Therefore, using DS evidence theory to correct the measured power spectrum data can effectively suppress the power spectrum value caused by strong interference signals, and significantly amplify the power spectrum value corresponding to the measured modal frequency, which shows that this method is suitable for railway bridges. Structural modal frequency identification for strong signal interference.

The above is only a preferred embodiment of the present invention, it should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, some improvements and modifications can also be made. It should be regarded as the protection scope of the present invention.

Claims (2)

1. the modification method of power spectrum in railroad bridge identification of mode frequency under strong signal disturbing, is characterized in that: comprise the following steps that order performs:

Step one, degree of will speed up sensor is arranged on railroad bridge, in order to measure the time domain vibration signal of railroad bridge;

Step 2, to acceleration transducer obtain time domain vibration signal carry out power spectrumanalysis, obtain measured power spectral curve;

Step 3, set up railroad bridge finite element analysis model, action edge specificity analysis of going forward side by side, obtain the theoretical model frequency f of railroad bridge _d; And according to theoretical model frequency f _dthat determines measured power spectral curve treats that frequency of amendment interval is for [f ₁, f ₂], wherein, the lower limit f of frequency separation ₁=f _d× 0.9, the higher limit f of frequency separation ₂=f _d× 1.1;

Step 4, employing D-S evidence theory are treating frequency of amendment interval [f to the measured power spectral curve that step 2 obtains ₁, f ₂] in data revise;

Step 5, identify the actual measurement model frequency f of railroad bridge according to the peak of power spectrum curve after revising _e.

2. the modification method of power spectrum in railroad bridge identification of mode frequency under strong signal disturbing according to claim 1, is characterized in that: in step 2, within every 10 minutes, obtains one group of measured power spectral curve; In step 4, the method for correction is as follows: at frequency separation [f ₁, f ₂] in frequency values f _i, m ₁(f _i), m ₂(f _i), m ₃(f _i), m ₄(f _i), m ₅(f _i), m ₆(f _i) be respectively respective frequencies value f in the 6 groups of measured power spectral curves obtained in 1 hour _ipower spectral value; Frequency values f in this hour is calculated according to following (1) to (5) formula _icorresponding revised power spectral value M (f _i):

$T_1\left(f_i\right)=\frac{m_1\left(f_i\right)\&times;m_2\left(f_i\right)}{1-m_1\left(f_i\right)\&times;m_2\left(f_i\right)}---\left(1\right)$

$T_2\left(f_i\right)=\frac{T_1\left(f_i\right)\&times;m_3\left(f_i\right)}{1-T_1\left(f_i\right)\&times;m_3\left(f_i\right)}---\left(2\right)$

$T_3\left(f_i\right)=\frac{T_2\left(f_i\right)\&times;m_4\left(f_i\right)}{1-T_2\left(f_i\right)\&times;m_4\left(f_i\right)}---\left(3\right)$

$T_4\left(f_i\right)=\frac{T_3\left(f_i\right)\&times;m_5\left(f_i\right)}{1-T_3\left(f_i\right)\&times;m_5\left(f_i\right)}---\left(4\right)$

$M\left(f_i\right)=\frac{T_4\left(f_i\right)\&times;m_6\left(f_i\right)}{1-T_4\left(f_i\right)\&times;m_6\left(f_i\right)}---\left(5\right)$

To frequency separation [f ₁, f ₂] in measured power spectrum corresponding to all frequency values revise all as stated above, finally obtain revised power spectrum curve.