CN115343366A

CN115343366A - Bridge structure monitoring system based on acoustic emission technology

Info

Publication number: CN115343366A
Application number: CN202211087110.7A
Authority: CN
Inventors: 邓军明
Original assignee: Individual
Current assignee: Individual
Priority date: 2022-09-07
Filing date: 2022-09-07
Publication date: 2022-11-15

Abstract

The invention discloses a bridge structure monitoring system based on an acoustic emission technology, which comprises a plurality of acoustic emission sensors, an information acquisition box and a cloud server; the information acquisition box comprises an analysis module and a communication module, the signal output ends of the acoustic emission sensors are electrically connected with the signal input end of the analysis module, the signal output end of the analysis module is electrically connected with the signal input end of the communication module, and the signal output end of the communication module is in radio signal connection with the cloud server. The intelligent safety early warning and emergency management system is established by the acoustic emission technology monitoring system, so that the measurement precision is high, the system is stable, the monitoring data can be uploaded to the monitoring early warning and emergency management platform in real time, and the early warning and emergency disposal capabilities are improved.

Description

Bridge structure monitoring system based on acoustic emission technology

Technical Field

The invention relates to the technical field of on-line automatic monitoring of bridge steel bridges, in particular to a bridge structure monitoring system based on an acoustic emission technology.

Background

The newly-built large-span and extra-large-span bridge mainly adopts a steel structure, and the proportion of newly-built other bridge steel structures is obviously improved. The highway construction unit should combine concrete project, organize to develop the special research in aspects such as promoting steel structure bridge quality, guaranteeing structure safety durable, promoting standardized construction, promote scientific and technological achievement, tamp the technical basis, promote the improvement of steel structure bridge overall technology level for promoting highway construction transformation upgrade, promote highway bridge quality, full play steel structure bridge performance advantage.

The prior art provides a new technical research and application for carrying out online dynamic monitoring on steel and welding seams of a steel structure bridge by using an Acoustic Emission (AE) technology, but in the prior art, a further research is needed on how to specifically use the acoustic emission technology to monitor the steel and the welding seams of the steel structure bridge, so that the invention provides a bridge structure monitoring system based on the acoustic emission technology.

Disclosure of Invention

The invention provides a bridge structure monitoring system based on an acoustic emission technology, which aims to solve the problems in the background technology.

In order to achieve the purpose, the invention adopts the following technical scheme:

a bridge structure monitoring system based on an acoustic emission technology comprises a plurality of acoustic emission sensors, an information acquisition box and a cloud server;

the information acquisition box comprises an analysis module and a communication module, the signal output ends of the acoustic emission sensors are electrically connected with the signal input end of the analysis module, the signal output end of the analysis module is electrically connected with the signal input end of the communication module, and the signal output end of the communication module is in radio signal connection with the cloud server.

As a further improvement scheme of the technical scheme: the acoustic emission sensors are all installed on the bridge steel box bottom plate, and 6 acoustic emission line sensors are installed on the left side and the right side of the bridge steel box bottom plate every span respectively.

As a further improvement scheme of the technical scheme: the analysis module is an FPGA and an ARM based on an SOC architecture, wherein the SOC is the integration of a software system and a hardware system, and the FPGA and the ARM are chips capable of changing the internal structure through programming.

As a further improvement scheme of the technical scheme: the acoustic emission sensor is used for receiving stress wave signals caused by the bridge steel box bottom plate during crack propagation, plastic deformation or phase change and sending the stress wave signals to the analysis module.

As a further improvement scheme of the technical scheme: the analysis module is used for performing frequency domain filtering, waveform processing, acoustic emission impact characteristic parameter extraction and impact parameter evaluation and rating on the received stress wave signals, and wirelessly transmitting the processed waveform, parameters and rating data to the cloud server through the communication module.

As a further improvement scheme of the technical scheme: the user can check and download the waveform, the parameters and the rating data of the bottom plate of the bridge steel box in real time through the cloud server.

As a further improvement scheme of the technical scheme: the communication module is any one of a 5G communication module, a 4G communication module, a Bluetooth module and a WiFi module.

As a further improvement scheme of the technical scheme: the system comprises the following specific detection steps:

s1, when the surface crack of the box Liang Gangban expands, and plastic deformation or phase change and the like can cause strain energy to be rapidly released to generate stress waves, the plurality of acoustic emission sensors receive stress wave signals and then the information acquisition box carries out signal analysis;

s2, performing frequency domain filtering, waveform processing, acoustic emission impact characteristic parameter extraction and impact parameter evaluation and grading on the stress wave signal by adopting an FPGA and ARM analysis module based on an SOC framework,

and S3, after the analysis module digitalizes the AD signal, the waveform, the parameter and the rating data are transmitted to a cloud server through a communication module, and a user can check and download the waveform, the parameter and the rating data in real time.

Compared with the prior art, the invention has the beneficial effects that:

the system establishes an intelligent safety early warning and emergency management system through the acoustic emission technology monitoring system, so that the measurement precision is high, the system is stable, monitoring data can be uploaded to a monitoring early warning and emergency management platform in real time, and the early warning and emergency disposal capability is improved.

The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings. The detailed description of the present invention is given in detail by the following examples and the accompanying drawings.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

FIG. 1 is a schematic general view of an installation of a bridge structure monitoring system based on acoustic emission technology according to the present invention;

FIG. 2 is a schematic structural diagram of a bridge structure monitoring system based on acoustic emission technology according to the present invention;

FIG. 3 is a schematic diagram of the signal input and output of the FPGA chip of the present invention;

FIG. 4 is a schematic diagram of the working principle of the FIR filter of the present invention;

FIG. 5 is a tolerance map of an ideal low pass filter of the present invention (f 1 passband bandwidth; f2 transition bandwidth);

FIG. 6 is a schematic diagram of waveforms of phase function, impulse response, and amplitude function of the present invention when the length N is even and even symmetric;

FIG. 7 is a waveform diagram illustrating the waveforms of the phase function, impulse response and amplitude function when the length N is even and odd symmetric according to the present invention;

FIG. 8 is a waveform diagram illustrating the waveforms of the phase function, impulse response, and amplitude function according to the present invention when the length N is odd and odd symmetric;

FIG. 9 is a schematic diagram of waveforms of phase function, impulse response, and amplitude function when the length N is odd and odd symmetric according to the present invention;

FIG. 10 is a schematic diagram of a cross-sectional structure of an FIR filter according to the present invention;

FIG. 11 is a schematic diagram of an odd FIR linear phase system according to the present invention;

FIG. 12 is a schematic diagram of the structure of the FIR linear phase system when the number is even according to the present invention.

Detailed Description

The principles and features of this invention are described below in conjunction with the following drawings, which are set forth to illustrate, but are not to be construed to limit the scope of the invention. The invention is described in more detail in the following paragraphs by way of example with reference to the accompanying drawings. Advantages and features of the present invention will become apparent from the following description and from the claims. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

Referring to fig. 1 to 12, in an embodiment of the present invention, a bridge structure monitoring system based on an acoustic emission technology includes a plurality of acoustic emission sensors, an information collection box, and a cloud server;

the inside of information acquisition box includes analysis module and communication module, a plurality of acoustic emission sensor's signal output part all with analysis module's signal input part electric connection, analysis module's signal output part and communication module's signal input part electric connection, communication module's signal output part and high in the clouds server radio signal connection, communication module is any one of 5G communication module, 4G communication module, bluetooth module, wiFi module.

Specifically, a plurality of acoustic emission sensors are all installed on the bridge steel box bottom plate, 6 acoustic emission line sensors are installed on the left side and the right side of each bridge steel box bottom plate, and the acoustic emission sensors are used for receiving stress wave signals caused by the bridge steel box bottom plate during crack propagation, plastic deformation or phase change and sending the stress wave signals to the analysis module.

Specifically, the analysis module of the FPGA and the ARM based on the SOC framework is used for carrying out frequency domain filtering, waveform processing, acoustic emission impact characteristic parameter extraction and impact parameter evaluation and grading on received stress wave signals, transmitting processed waveforms, parameters and grading data to a cloud server in a wireless mode through a communication module, and enabling a user to check and download the waveforms, the parameters and the grading data of the bridge steel box bottom plate in real time through the cloud server.

The FPGA and the ARM of the Soc perform frequency domain filtering, waveform processing, acoustic emission impact characteristic parameter extraction and evaluation and grading of impact parameters on the signals:

1) The SOC is the integration of a software system and a hardware system, and the FPGA and the ARM are chips which can change the internal structure through programming.

2) When the surface crack propagation, plastic deformation or phase change and the like are generated on the surface of the steel, the strain energy can be quickly released to generate a frequency signal of the stress wave, the leakage acoustic emission signal is a broadband random noise signal, and the strongest leakage acoustic emission signals are all concentrated in a relatively low-frequency range of 0-400kHz.

a. In a radio frequency communication system, no matter whether signals are transmitted or received, interference signals need to be filtered, specific frequency signals are selected for analysis, digital filtering is realized on the basis of an FPGA and an ARM of an Soc framework, and signals input and output of an FPGA chip are shown in figure 3.

Principle of fir digital filtering: as shown in fig. 3, the signal is analog-to-digital converted by an a/D device to convert the analog signal into a digital signal; in order to ensure that the signal processing can not generate distortion, the sampling speed of the signal must meet the Shannon sampling theorem, and generally 4-5 times of the upper limit of the signal frequency is taken as the sampling frequency; in general, a successive approximation type a/D converter with a high speed is available, regardless of whether a multiply-accumulate method or a distributed algorithm is adopted to design an FIR filter, data output by the filter is a series of sequences, and digital-to-analog conversion is required to be performed in order to enable the filter to be intuitively reflected, so that an output of the FIR filter formed by an FPGA is required to be externally connected with a D/a module. The FPGA has regular internal logic arrays and rich connecting line resources, is particularly suitable for digital signal processing tasks, has better parallelism and expandability compared with a general DSP chip taking serial operation as a leading factor, and can design a high-speed FIR digital filter by utilizing a fast algorithm of FPGA multiply-accumulate. An ideal FIR filter, requiring a constant amplitude-frequency response in the passband; the phase frequency is correspondingly a linear function of the frequency, and the amplitude-frequency response in the stop band is zero, as shown in fig. 4 and 5 below.

The characteristics of FIR digital filtering: condition of linear phase

If the unit sample response h (n) of the FIR filter is real and either of the following conditions is met:

even symmetry h (N) = h (N-1-N)

Odd symmetry h (N) = -h (N-1-N)

With a center of symmetry at N = (N-1)/2, the filter has an accurate linear phase.

1) Linear phase characteristics and amplitude function characteristics:

h (n) even symmetry

The amplitude function H (ω) comprises positive and negative values and the phase function is a strictly linear phase, indicating that the filter has a delay of (N-1)/2 samples, which is equal to half the length of the unit sample response H (N). In fig. 6, the linear phase has no 90 ° additional phase shift, the amplitude function has a zero at pi, and is odd symmetric for ω = pi, and therefore is not suitable as a high pass filter. In fig. 7, the linear phase has no 90 ° additional phase shift, and the amplitude function is even symmetric at ω =0, π, 2 π, and is therefore suitable as a low-pass, high-pass filter.

2) h (n) odd symmetry

FIG. 6 and FIG. 7 are waveform diagrams of phase function, impulse response and amplitude function when the length N is even number and even symmetry

The phase function is still linear but with an intercept of pi/2 at zero frequency (ω = 0). Not only is there a delay of (N-1) samples, but a phase shift of π/2 is also produced. In fig. 6, the linear phase has an additional phase shift of 90 °, the amplitude function is zero at 0, 2 pi, and is odd symmetric for ω =0, 2 pi and even symmetric for ω = pi.

The filters shown in fig. 8 and 9 are suitable for use in differentiators and 90 ° phase shifters.

For the FIR filter, the unit impulse response h (N) is a N-point sequence (N is more than or equal to 0 and less than or equal to N), namely a system function.

FIR filters have several basic structures ]: cross-section (convolution type, direct type), cascade type, frequency sampling type, and fast convolution type. For the cross-section, the differential equation of the system is expressed as

The schematic diagram is shown in FIG. 10

Symmetric impulse response usable by unit impulse response filter of causal FIR system with N-order linear phase

h[n]＝h[N-n]

Or an anti-symmetric impulse response.

h[n]＝-h[N-n]

The impulse response of an FIR transfer function with a symmetric impulse response can be written as follows:

when N is an even number

When N is an odd number

c. Filter structure

The structure of the FIR linear phase system can be transformed as shown in fig. 11 and 12.

3) The process of extracting the acoustic emission impact characteristic parameters and evaluating and grading the impact parameters refers to the signal analysis process of fig. 10:

a. time of arrival of signal

The output signal is used to record the time of arrival of the acoustic emission signal.

The data width of the acoustic emission signal determines the maximum distance Lmax between two acoustic emission signals in emission detection, and the Lmax is approximately equal to 50m in general, so that

The data width can be determined from the value

Substituting data to obtain N =18.9, so taking N =19 can satisfy the above requirement.

b. Channel number

The signal is used for recording the channel number corresponding to the acoustic emission signal, and the total number of the channels is 32 channels, so that the acoustic emission signal can be realized by 5-bit data width.

c. Ringing count

This signal is used to record the number of ringing pulses generated by an acoustic emission signal. Since the finally obtained data is transmitted in a PCI bus mode, the total output data width is 32 bits, the data width of the obtained ringing count is 8 bits, the maximum recorded ringing number is 256, and the requirement of the acoustic emission signal can be usually met.

d. Marker bit

The high level is effective and used for indicating that the characteristic parameters of the acoustic emission signals are recorded by the FPGA, so that the subsequent circuit can read the characteristic parameters conveniently.

The system is a defect intelligent positioning method, which utilizes acoustic emission characteristic parameters as an acoustic emission source positioning method input by an artificial neural network, is a positioning method with great potential, and is particularly suitable for the conditions of various materials and complex structure.

The foregoing is merely a preferred embodiment of the invention and is not intended to limit the invention in any manner; the present invention may be readily implemented by those of ordinary skill in the art as illustrated in the accompanying drawings and described above; however, those skilled in the art should appreciate that they can readily use the disclosed conception and specific embodiments as a basis for designing or modifying other structures for carrying out the same purposes of the present invention without departing from the scope of the invention as defined by the appended claims; meanwhile, any changes, modifications, and evolutions of the equivalent changes of the above embodiments according to the actual techniques of the present invention are still within the protection scope of the technical solution of the present invention.

Claims

1. A bridge structure monitoring system based on an acoustic emission technology is characterized by comprising a plurality of acoustic emission sensors, an information acquisition box and a cloud server;

2. The system of claim 1, wherein the acoustic emission sensors are mounted on the bottom plate of the steel box, and 6 acoustic emission line sensors are mounted on the left and right sides of the bottom plate of the steel box.

3. The system of claim 2, wherein the analysis module is an FPGA and an ARM based on a SOC architecture, wherein the SOC is an integration of a software system and a hardware system, and the FPGA and the ARM are chips capable of changing an internal structure by programming.

4. The system of claim 3, wherein the acoustic emission sensor is configured to receive a stress wave signal generated by the steel box bottom plate of the bridge during crack propagation, plastic deformation or phase change, and transmit the stress wave signal to the analysis module.

5. The system of claim 4, wherein the analysis module is configured to perform frequency-domain filtering, waveform processing, acoustic emission impact characteristic parameter extraction, and impact parameter evaluation and rating on the received stress wave signal, and wirelessly transmit the processed waveform, parameters, and rating data to the cloud server through the communication module.

6. The system of claim 5, wherein the waveform, parameters and rating data of the bottom plate of the bridge steel box can be viewed and downloaded by a user in real time through the cloud server.

7. The system for monitoring a bridge structure based on acoustic emission technology of claim 6, wherein the communication module is any one of a 5G communication module, a 4G communication module, a Bluetooth module and a WiFi module.

8. The system for monitoring the bridge structure based on the acoustic emission technology according to any one of claims 1 to 7, wherein the system comprises the following specific detection steps:

s1, when the surface crack of the box Liang Gangban expands, plastically deforms or changes phase and the like, strain energy can be quickly released to generate stress waves, and the stress wave signals are received by the acoustic emission sensors and then are analyzed by the information acquisition box;