A structural vibration monitoring system and method that can be calibrated online

Abstract

This invention relates to the field of intelligent sensor technology and discloses an online calibrable structural vibration monitoring system and method. The system includes a vibration sensing module for sensing structural vibration and receiving excitation signals; a data acquisition module for converting the analog signals output by the vibration sensing module into digital signals and transmitting them to monitoring software, and outputting a sine wave signal to the vibration sensing module; and a vibration monitoring and calibration software module for controlling the data acquisition instrument, receiving data transmitted by the data acquisition instrument, analyzing vibration data, and calculating sensitivity online. By precisely controlling the sine wave signal input to the self-excitation coil and measuring the output signal of the response coil, the sensitivity values ​​of the sensor at different frequencies can be calculated, achieving precise calibration of the sensor sensitivity. By comparing the sensor's sensitivity values ​​at different time periods, changes in sensor performance can be evaluated, improving the accuracy and reliability of monitoring data.

Description

Technical Field

[0001] This invention relates to the field of intelligent sensor technology, specifically to a structural vibration monitoring system and method that can be calibrated online. Background Technology

[0002] Vibration monitoring devices are crucial equipment for monitoring the safety of engineering structures. Existing structural vibration monitoring devices lack online calibration capabilities and require periodic disassembly and calibration on a laboratory vibration table to determine their current sensitivity. In practical engineering implementation, the disassembly, testing, and reinstallation of vibration monitoring devices require significant manpower, time, and calibration costs, significantly increasing the operation and maintenance costs of the structural safety monitoring system. Consequently, most existing structural vibration monitoring devices are not calibrated for extended periods, leading to reduced reliability of vibration monitoring data and making it impossible to identify false alarms caused by large testing errors in the device itself when safety warnings are issued. Therefore, this paper proposes a structural vibration monitoring system and method with online calibration capability. Summary of the Invention

[0003] The purpose of this invention is to provide an online calibrable structural vibration monitoring system and method to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an online calibrable structural vibration monitoring system, comprising a vibration sensing module, a data acquisition module, and a vibration monitoring and calibration software module;

[0005] The vibration sensing module is used to sense structural vibration and receive excitation signals;

[0006] The data acquisition module is used to convert the analog signal output by the vibration sensing module into a digital signal and transmit it to the monitoring software, and output a sine wave signal to the vibration sensing module.

[0007] The vibration monitoring and calibration software module is used to control the data acquisition instrument, receive data transmitted by the data acquisition instrument, analyze vibration data, and perform online calibration sensitivity calculation.

[0008] The vibration sensing module is connected to the data acquisition module, and the data acquisition module is connected to the vibration monitoring and calibration software module.

[0009] Preferably, the vibration sensing module includes a housing, a permanent magnet is installed on the bottom inner side of the housing, a soft magnet is connected to the top of the permanent magnet, and a coil frame is provided on the top of the soft magnet.

[0010] Preferably, a self-excited coil and a response coil are wound around the outside of the coil frame, respectively. The winding directions of the self-excited coil and the response coil are opposite, and the number of turns of the self-excited coil is 99-101.

[0011] Preferably, the data acquisition module includes a data acquisition instrument, and a sine wave generator is mounted on the surface of the data acquisition instrument.

[0012] As a preferred embodiment, during online calibration, the aforementioned vibration monitoring and calibration software module accurately extracts the useful sine signal and amplitude of the calibration response output from the acquired signal, and accurately calculates the sensitivity value.

[0013] As a preferred option, the formula for calculating the sinusoidal signal x is as follows:

[0014]

[0015] Where f represents the amplitude and frequency of the excitation sinusoidal signal, respectively.

[0016] As a preferred option, the formula for calculating the response output signal is as follows:

[0017]

[0018] Where B is the amplitude of the response signal of the sensor response coil under the excitation of a sinusoidal signal only during calibration, and F is the response output signal of the sensor response coil under the excitation of a structural vibration signal only.

[0019] To reduce the impact of F(t) on the calibration results, calibration can be initiated when the structural vibration is relatively small. In this case, the sensor's output signal is:

[0020]

[0021] Where t is chosen to be 0 ≤ t ≤ 600 seconds;

[0022] right A smoothing transformation is performed to obtain a two-dimensional array of the spectrum curves of the signal output by the sensor's response coil. .

[0023] Preferably, after the above calibration is initiated, data is continuously collected for 600 seconds, and then FFT smoothing transformation is performed to obtain a two-dimensional array y of the spectrum curve of the sensor's response coil output signal during this time period:

[0024]

[0025] Where f is the frequency value, y is the spectral function of y after FFT transformation, x is the spectral function of x after FFT transformation, and F is the spectral function of F after FFT transformation.

[0026] Since the sampling frequency and acquisition time are the same, the f-sample quantized value of the two obtained spectrum two-dimensional arrays is the same, that is, the X-axis coordinate value of the two obtained spectrum curves is the same;

[0027] Subtract the two obtained spectrum curves and perform the subtraction calculation. Assuming S is the spectrum function of the response coil after FFT of the response data at the calibration frequency, then:

[0028]

[0029] because ,so .

[0030] This invention provides a method for an online calibrable structural vibration monitoring system, comprising the following steps:

[0031] S1. The self-excitation coil and response coil of the vibration sensing module are both set on the coil frame and in the magnetic cylinder of the sensor. The self-excitation coil receives the sinusoidal signal output by the data acquisition module, which is equivalent to the input current in the coil. As a result, the self-excitation coil generates an Ampere force with the same frequency and amplitude as the input sinusoidal signal. The Ampere force drives the response coil on the coil frame to move in the magnetic cylinder of the sensor. The response coil moves in the magnetic field and generates an electromotive force and an output voltage signal. The frequency of its output voltage signal is the same as the frequency of the sinusoidal signal input by the self-excitation coil. The amplitude of its output voltage signal is proportional to the amplitude of the sinusoidal signal input by the self-excitation coil. This proportionality coefficient is the inherent sensitivity value of the sensor. By changing the frequency value of the sinusoidal signal input by the self-excitation coil, the sensitivity value corresponding to different frequency values ​​of the sensor can be obtained.

[0032] S2. The data acquisition module acquires the output voltage signal and converts it into a digital signal, which is then transmitted to the vibration monitoring and calibration software module.

[0033] The S3 vibration monitoring and calibration software module uses FFT smoothing transformation and spectrum curve subtraction to accurately extract the frequency and amplitude of the sinusoidal signal output of the calibration response from the mixed signal, and then calculates the sensitivity value of the sensor at each frequency point. The algorithm of the calculation formula is used to accurately extract the frequency and amplitude of the sinusoidal signal output of the calibration response from the mixed signal and calculate the sensor sensitivity value.

[0034] S4. The sensor sensitivity change rate is used to assess the error rate of the currently acquired vibration data and to perform subsequent calibration to correct the currently acquired vibration data.

[0035] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects:

[0036] By precisely controlling the sinusoidal signal input to the self-excited coil and measuring the output signal of the response coil, the sensitivity value of the sensor at different frequencies can be calculated, achieving precise calibration of the sensor sensitivity. By comparing the sensor's sensitivity values ​​at different time periods, the changes in sensor performance can be evaluated, and the collected vibration data can be subsequently calibrated based on the sensitivity change rate, improving the accuracy and reliability of the monitoring data. The system can be calibrated online without disassembling the vibration sensor and sending it to the laboratory for calibration, greatly improving the real-time performance and efficiency of calibration. The calibration process can be completed simply by operating the monitoring software on the computer, eliminating the cumbersome steps of disassembly, inspection, and reinstallation, and greatly simplifying the calibration process. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a schematic diagram of the module connection of the present invention;

[0039] Figure 2 This is a schematic diagram of the vibration sensing sensor structure of the present invention;

[0040] Figure 3 This is the circuit schematic diagram of the present invention.

[0041] Explanation of reference numerals in the attached diagram: 1. Coil frame; 2. Soft magnet; 3. Self-excited coil; 4. Response coil; 5. Permanent magnet; 6. Housing. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] It should be noted that the structures, proportions, sizes, etc., shown in the accompanying drawings of this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed in the specification, and are not intended to limit the conditions under which this application can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size should still fall within the scope of the technical content disclosed in this application, provided that they do not affect the effects and purposes that this application can produce.

[0044] Example

[0045] Please see Figure 1-3 The present invention provides a technical solution: an online calibrable structural vibration monitoring system, comprising a vibration sensing module, a data acquisition module, and a vibration monitoring and calibration software module, wherein the vibration sensing module and the data acquisition module are connected to each other, and the data acquisition module and the vibration monitoring and calibration software module are connected to each other.

[0046] The vibration sensing module is used to sense structural vibration and receive excitation signals. The vibration sensing module adds a set of enameled wires to the coil frame 1 of the vibration sensor. The vibration sensor model is ZC2000.

[0047] The vibration sensing module includes a housing 6. A permanent magnet 5 is installed on the bottom inner side of the housing 6. A soft magnet 2 is connected to the top of the permanent magnet 5. A coil frame 1 is set on the top of the soft magnet 2. A self-excited coil 3 and a response coil 4 are wound around the outside of the coil frame 1, respectively. Figure 2 As shown, the winding directions of the self-excitation coil 3 and the response coil 4 are opposite. The self-excitation coil 3 is wound with 100 turns, and the surface of the self-excitation coil 3 is coated with three-proof paint to fix the enameled wire.

[0048] At the same time, the vibration sensor's 2-core BNC connector was changed to a 4-core aviation connector. The two ends of the newly wound enameled wire were soldered to the 3rd and 4th cores of the sensor's 4-core aviation connector to receive the sinusoidal signal output by the data acquisition instrument. The self-excitation coil 3 and the response coil 4 are both on the sensor's coil frame 1 and in the sensor's magnetic cylinder.

[0049] The data acquisition module is used to convert the analog signal output by the vibration sensing module into a digital signal and transmit it to the monitoring software, and output a sine wave signal to the vibration sensing module.

[0050] The data acquisition module includes a data acquisition unit, on which a sine wave generator is mounted. The model of the data acquisition unit is G01NET-3F. The circuit diagram of the sine wave generator module is shown below. Figure 3 As shown, where:

[0051] One end of R2 is connected to the RXD pin of U1, and the other end is connected to the UART1-TX / A1N5 / PD5 pin of U3;

[0052] One end of R3 is connected to the TXD pin of U1, and the other end is connected to the UART1-RX / A1N6 / PD6 pin of U3.

[0053] The sine wave generator has an internal chip, model AD9833, and is equipped with external capacitors, resistors and power supply circuits. The generator has an RS485 communication interface and can control its signal output frequency and stop output via commands.

[0054] The data acquisition unit has an RS485 communication interface. The signal generator module can be controlled by modifying the underlying program of the data acquisition unit and through the RS485 communication interface. The signal input terminals of the data acquisition unit are 8 BNC connectors, which can be changed to 8 4-pin aviation connectors. 1 pin of the 4-pin aviation connector is connected to the signal acquisition channel of the acquisition card, 2 pins are connected to the signal ground wire of the acquisition card, 3 pins are connected to the positive terminal of the signal generator output, and 4 pins are connected to the negative terminal of the signal generator output.

[0055] The vibration monitoring and calibration software module is used to control the data acquisition instrument, receive data transmitted by the data acquisition instrument, analyze vibration data, and perform online calibration sensitivity calculation.

[0056] The vibration monitoring and calibration software module is a secondary development based on the vibration monitoring software, adding calibration functions. The vibration monitoring software is G01NET-FDC.

[0057] During online calibration, the vibration monitoring and calibration software module accurately extracts the useful sinusoidal signal and amplitude of the calibration response output from the acquired signals, and accurately calculates the sensitivity value. During online calibration, the vibration monitoring system is excited not only by the sinusoidal signal output by the data acquisition instrument, but also by the structural vibration at the fixed position of the sensor.

[0058] The formula for calculating a sinusoidal signal xt is:

[0059]

[0060] Where f represents the amplitude and frequency of the excitation sinusoidal signal, respectively.

[0061] Assuming the sensor response coil's response output signal during calibration is jointly excited by the calibration excitation sinusoidal signal and the structural vibration signal, the formula for calculating the response output signal is:

[0062]

[0063] Where B is the amplitude of the response signal of the sensor response coil under the excitation sinusoidal signal only during calibration, and Ft is the response output signal of the sensor response coil under the excitation of the structural vibration signal only. Since the structural vibration signal is a random vibration signal, it may contain a prominent signal with the same frequency value as the excitation sinusoidal signal. If the influence of F(t) is not reduced, it will cause a large deviation in the sensitivity of the online calibration.

[0064] To reduce the impact of F(t) on the calibration results, calibration can be initiated when structural vibration is relatively low. For example, taking a bridge beam as the monitoring object, online calibration of the vibration monitoring system can be performed when wind speed is low and no vehicles are passing by. In this case, the frequency of structural vibration mainly consists of multiple natural frequency signals, and the amplitude is relatively stable. Therefore, the F(t) signal is relatively stable. To reduce the impact of F(t) on the calibration results, calibration can be initiated when structural vibration is relatively low. At this time, the sensor output signal is:

[0065]

[0066] Where t is chosen to be 0 ≤ t ≤ 600 seconds;

[0067] right By performing a smoothing transformation, a two-dimensional array of the spectrum curves of the sensor's response coil output signal during this time period is obtained. .

[0068] After calibration is initiated, data is continuously acquired for 600 seconds, and then FFT smoothing is performed to obtain a two-dimensional array yf of the spectrum curve of the sensor's response coil output signal during this time period:

[0069]

[0070] Where f is the frequency value, yf is the spectral function of yt after FFT transformation, xf is the spectral function of xt after FFT transformation, and Ff is the spectral function of Ft after FFT transformation.

[0071] Since the sampling frequency and acquisition time are the same, the f-sample quantized value of the two obtained spectrum two-dimensional arrays is the same, that is, the X-axis coordinate value of the two obtained spectrum curves is the same;

[0072] Subtracting the two obtained spectrum curves, assuming Sf is the spectrum function of the response coil after FFT at the calibrated frequency, then:

[0073]

[0074] because ,so ;

[0075] During calibration, since the frequency and amplitude of the excitation sinusoidal signal are set by the monitoring software via commands and are known parameter values, the frequency and amplitude A of the excitation sinusoidal signal are also known and can be obtained through a two-dimensional array. After obtaining the response amplitude value B corresponding to the frequency of the excitation sinusoidal signal, and obtaining the response amplitude B and frequency value of the sensor's response coil under the excitation sinusoidal signal based on the above method, dividing B by A gives the sensor's sensitivity value at this frequency.

[0076] By repeating the above method, sensor sensitivity values ​​corresponding to multiple frequencies can be obtained. Comparing these values ​​with the initial sensitivity values ​​at each frequency, the rate of change in sensor sensitivity at each frequency can be calculated. Based on this rate of change, the error rate of the currently acquired vibration data can be assessed, and the acquired vibration data can be calibrated using this error rate.

[0077] For example, if the sensitivity of a sensor decreases by 10% at all frequency points, dividing the currently collected vibration data by a coefficient of 0.9 will restore the currently collected vibration data to its normal value. Compared with the existing structural vibration monitoring system, which requires periodic disassembly and delivery to a vibration table in the laboratory for calibration, the structural vibration monitoring system of this invention does not require disassembly and can be calibrated simply by operating on a computer. This eliminates the tedious work of disassembling, sending for inspection, and reinstalling the vibration monitoring system, improving the convenience of structural vibration monitoring system calibration and reducing the calibration cost.

[0078] The present invention also provides a method for an online calibrable structural vibration monitoring system, comprising the following steps:

[0079] S1. The self-excitation coil 3 and the response coil 4 of the vibration sensing module are both set on the coil frame 1 of the sensor and in the magnetic cylinder. The self-excitation coil 3 receives the sinusoidal signal output by the data acquisition module, which is equivalent to the current input into the coil. As a result, the self-excitation coil generates an Ampere force with the same frequency and amplitude as the input sinusoidal signal. The Ampere force drives the response coil 4 on the coil frame 1 to move in the magnetic cylinder of the sensor. The response coil 4 moves in the magnetic field and generates an electromotive force and an output voltage signal. The frequency of its output voltage signal is the same as the frequency of the sinusoidal signal input to the self-excitation coil 3. The amplitude of its output voltage signal is proportional to the amplitude of the sinusoidal signal input to the self-excitation coil 3 by a fixed coefficient. This coefficient is the inherent sensitivity value of the sensor. By changing the frequency value of the sinusoidal signal input to the self-excitation coil 3, the sensitivity value corresponding to different frequency values ​​of the sensor can be obtained.

[0080] S2. The data acquisition module acquires the output voltage signal and converts it into a digital signal, which is then transmitted to the vibration monitoring and calibration software module.

[0081] The S3 vibration monitoring and calibration software module uses FFT smoothing transformation and spectrum curve subtraction to accurately extract the frequency and amplitude of the sinusoidal signal output of the calibration response from the mixed signal, and then calculates the sensitivity value of the sensor at each frequency point. The algorithm of the calculation formula is used to accurately extract the frequency and amplitude of the sinusoidal signal output of the calibration response from the mixed signal and calculate the sensor sensitivity value.

[0082] S4. The sensor sensitivity change rate is used to assess the error rate of the currently acquired vibration data and to perform subsequent calibration to correct the currently acquired vibration data.

[0083] In summary, by precisely controlling the sinusoidal signal input to the self-excited coil and measuring the output signal of the response coil, the sensitivity value of the sensor at different frequencies can be calculated, achieving precise calibration of the sensor sensitivity. By comparing the sensor's sensitivity values ​​over different time periods, the changes in sensor performance can be evaluated, and the collected vibration data can be subsequently calibrated based on the sensitivity change rate, improving the accuracy and reliability of the monitoring data. The system can be calibrated online without disassembling the vibration sensor and sending it to the laboratory for calibration, greatly improving the real-time performance and efficiency of calibration. The calibration process can be completed simply by operating the monitoring software on the computer, eliminating the cumbersome steps of disassembly, inspection, and reinstallation, and greatly simplifying the calibration process.

[0084] Those skilled in the art will understand that the features described in the various embodiments and / or claims of the present invention can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments and / or claims of the present invention can be combined or combined in various ways without departing from the spirit and teachings of the present invention. All such combinations and / or combinations fall within the scope of the present invention.

Claims

1. A monitoring method based on an online calibrable structural vibration monitoring system, characterized in that, The online calibrable structural vibration monitoring system includes a vibration sensing module, a data acquisition module, and a vibration monitoring and calibration software module. The vibration sensing module is used to sense structural vibration and receive excitation signals; The data acquisition module is used to convert the analog signal output by the vibration sensing module into a digital signal and transmit it to the monitoring software, and output a sine wave signal to the vibration sensing module. The vibration monitoring and calibration software module is used to control the data acquisition instrument, receive data transmitted by the data acquisition instrument, analyze vibration data, and perform online calibration sensitivity calculation. The vibration sensing module is connected to the data acquisition module, and the data acquisition module is connected to the vibration monitoring and calibration software module. The monitoring method includes the following steps: S1. The self-excitation coil (3) and response coil (4) of the vibration sensing module are both set on the coil frame (1) of the sensor and in the magnetic cylinder. The self-excitation coil (3) receives the sinusoidal signal output by the data acquisition module, which is equivalent to the current input into the coil. Then the self-excitation coil forms an Ampere force with the same frequency and amplitude as the input sinusoidal signal. The Ampere force drives the response coil (4) on the coil frame (1) to move in the magnetic cylinder of the sensor. The response coil (4) moves in the magnetic field and generates an electromotive force and an output voltage signal. The frequency of its output voltage signal is the same as the frequency of the sinusoidal signal input by the self-excitation coil (3). The amplitude of its output voltage signal is proportional to the amplitude of the sinusoidal signal input by the self-excitation coil (3). This proportional coefficient is the inherent sensitivity value of the sensor. By changing the frequency value of the sinusoidal signal input by the self-excitation coil (3), the sensitivity value corresponding to different frequency values ​​of the sensor can be obtained. S2. The data acquisition module acquires the output voltage signal and converts it into a digital signal, which is then transmitted to the vibration monitoring and calibration software module. The S3 vibration monitoring and calibration software module uses FFT smoothing transformation and spectrum curve subtraction to accurately extract the frequency and amplitude of the sinusoidal signal output of the calibration response from the mixed signal, and then calculates the sensitivity value of the sensor at each frequency point. The algorithm of the calculation formula is used to accurately extract the frequency and amplitude of the sinusoidal signal output of the calibration response from the mixed signal and calculate the sensor sensitivity value. S4. The sensor sensitivity change rate is used to assess the error rate of the currently acquired vibration data and to perform subsequent calibration to correct the currently acquired vibration data.

2. The method according to claim 1, characterized in that: The vibration sensing module includes a housing (6), a permanent magnet (5) is installed on the bottom inner side of the housing (6), a soft magnet (2) is connected to the top of the permanent magnet (5), and a coil frame (1) is provided on the top of the soft magnet (2).

3. The method according to claim 2, characterized in that: The outer side of the coil frame (1) is respectively wound with a self-excited coil (3) and a response coil (4). The winding directions of the self-excited coil (3) and the response coil (4) are opposite. The number of turns of the self-excited coil (3) is 99-101.

4. The method according to claim 1, characterized in that: The data acquisition module includes a data acquisition instrument, and a sine wave generator is mounted on the surface of the data acquisition instrument.

5. The method according to claim 1, characterized in that: During online calibration, the vibration monitoring and calibration software module accurately extracts the useful sine signal and amplitude of the calibration response output from the acquired signals and precisely calculates the sensitivity value.

6. The method according to claim 5, characterized in that: The formula for calculating the sinusoidal signal x(t) is: ； Where A and f are the amplitude and frequency values ​​of the excitation sinusoidal signal, respectively.

7. The method according to claim 6, characterized in that: The formula for calculating the response output signal is: ； Where B is the amplitude of the response signal of the sensor response coil under the excitation of a sinusoidal signal only during calibration, and F(t) is the response output signal of the sensor response coil under the excitation of a structural vibration signal only. To reduce the impact of F(t) on the calibration results, calibration can be initiated when the structural vibration is relatively small. In this case, the sensor's output signal is: ； Where t is chosen to be 0≤t≤600 seconds; right A smoothing transformation is performed to obtain a two-dimensional array of the spectrum curves of the signal output by the sensor's response coil. .

8. The method according to claim 7, characterized in that: After calibration is initiated, data is continuously collected for 600 seconds, and then FFT smoothing transformation is performed to obtain a two-dimensional array y(f) of the spectrum curve of the sensor's response coil output signal during this time period: ； Where f is the frequency value, y(f) is the spectral function of y(t) after FFT transformation, x(f) is the spectral function of x(t) after FFT transformation, and F(f) is the spectral function of F(t) after FFT transformation; Since the sampling frequency and acquisition time are the same, the f-sample quantized value of the two obtained spectrum two-dimensional arrays is the same, that is, the X-axis coordinate value of the two obtained spectrum curves is the same; Subtract the two obtained spectrum curves to calculate the spectrum. Assuming S(f) is the spectrum function of the response coil after FFT at the calibrated frequency, then: ； because ,so .

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