CN115791891A - Structural damage identification method and system based on piezoelectric impedance technology - Google Patents
Structural damage identification method and system based on piezoelectric impedance technology Download PDFInfo
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Abstract
The invention provides a structure damage identification method and system based on a piezoelectric impedance technology, and relates to the technical field of structure detection. The structural damage identification method and system based on the piezoelectric impedance technology comprise a piezoelectric sensor array, wherein the piezoelectric sensor array is connected with an impedance analyzer, the impedance analyzer is connected with a central processing computer, and the central processing computer is bidirectionally connected with a data preprocessing module, a data fitting module, a temperature compensation module and a feedback learning module. The feedback learning system is based on a deep learning method and a probability statistical method, and combines a sparse data reconstruction theory, so that the influence of massive incomplete data on damage identification precision in a long-term monitoring process of the system in use can be effectively reduced, and the system can achieve efficient and accurate positioning and identification on structural damage through a small amount of early-stage data.
Description
Technical Field
The invention relates to the technical field of structure detection, in particular to a structure damage identification method and system based on a piezoelectric impedance technology.
Background
The piezoelectric impedance technology is a detection technology which utilizes the electromechanical coupling characteristic of a piezoelectric sensor, detects and analyzes a piezoelectric impedance signal transmitted by the sensor and determines the development condition of the internal damage of a structure, the technology is mainly applied to the field of structural damage detection to detect structural damage in various working environments, most of the existing structural damage identification methods and systems based on the piezoelectric impedance technology adopt the function of comparing impedance signals before and after damage to realize damage detection, but the problems that the piezoelectric material and a bonding layer are temperature-sensitive materials exist, so that the existing methods and systems are easy to cause the problem of a detection result due to large temperature difference when in use, and meanwhile, when the existing methods and systems are used, the capacity of further analyzing and identifying the damage after the detection is finished is not provided, and the integral using effect is poor.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a structural damage identification method and system based on a piezoelectric impedance technology, and solves the problems that the existing system is easy to cause poor detection result precision due to outdoor temperature difference when in use, and the detection result cannot be further refined and studied and analyzed.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme: a structural damage identification method and system based on piezoelectric impedance technology comprises a piezoelectric sensor array, wherein the piezoelectric sensor array is connected with an impedance analyzer, and the impedance analyzer is connected with a central processing computer;
the central processing computer is bidirectionally connected with a data preprocessing module, a data fitting module, a temperature compensation module and a feedback learning module.
Preferably, the data preprocessing module comprises a database, and the database is connected with a data transmission module, a data recording module and a data processing module.
Preferably, the data processing module is connected with a coordinate establishing module and a curve establishing module.
Preferably, the temperature compensation module comprises a temperature recording module and a temperature processing module, the temperature recording module is connected with a temperature measuring module and a temperature storage module, and the temperature processing module is connected with a temperature fitting module.
Preferably, the feedback learning module comprises a feedback learning system, and the feedback learning system is connected with a deep learning method, a probability statistical method and a sparse data reconstruction method.
Preferably, the data fitting module comprises a fitting model module, and the fitting model module is connected with an impedance fitting model and a temperature fitting model.
Preferably, the impedance fitting model is connected with a piezoelectric structure coupling model, and the temperature fitting model is connected with a nonlinear temperature coupling model.
A structural damage identification method based on a piezoelectric impedance technology specifically comprises the following steps:
s1, instrument installation
Fixedly arranging the piezoelectric sensor array on the surface of a test piece to be tested through an adhesive, connecting the piezoelectric sensor array with an impedance analyzer through a wire, and connecting the impedance analyzer with a central processing computer;
s2. Data acquisition
Starting an impedance analyzer, acquiring data through a data preprocessing module of a central processing computer, and transmitting and recording the data through a data transmission module and a data recording module of a database;
s3, data processing
Establishing an impedance curve of the acquired data through a data processing module, replacing a plurality of test pieces to be detected with different damage degrees, repeating the process from S1 to S2, and measuring the impedance curve of the test pieces to be detected under different damage degrees;
s4, result fitting
Inputting a plurality of groups of different impedance curves into a fitting model module, fitting a detection result through an impedance fitting model connected with a piezoelectric structure coupling model to realize damage identification, setting a component to be detected into different temperature environments, repeating the processes from S1 to S3 to measure the impedance curves at different temperatures, and correcting data based on different temperatures when damage identification is carried out through measurement of the piezoelectric structure coupling model and the nonlinear temperature coupling model;
s5, feedback learning
And replacing different types of test pieces for multiple detection, inputting the detection result into a feedback learning module, and combining a deep learning method and a probability statistical method with a sparse data reconstruction method to enable a feedback learning system to perform deep learning so as to realize autonomous damage detection and identification during subsequent use of the system.
(III) advantageous effects
The invention provides a structural damage identification method and system based on a piezoelectric impedance technology. The method has the following beneficial effects:
1. compared with the existing system, the system is provided with the feedback learning module in the central processing computer, the feedback learning module is internally provided with the feedback learning system, the feedback learning system is based on a deep learning method and a probability statistical method and combines a sparse data reconstruction theory, the influence of massive incomplete data on damage identification precision in the long-term monitoring process of the system in use can be effectively reduced, the system can achieve efficient and accurate positioning identification on structural damage through a small amount of early-stage data, and self-damage identification of the piezoelectric sensing system is achieved.
2. Compared with the existing system, the system adds the nonlinear temperature coupling model into the fitting model of the data fitting module, so that when a user uses the system, the impedance curve at different temperatures can be measured through the temperature compensation module, the defect that the nonlinearity of materials in the detection principle is not considered enough in the existing system is overcome, and the accuracy of the system in a temperature-varying environment is improved from the aspect of mechanism description.
3. Compared with the existing system, the system has the advantages that the piezoelectric wafer is set to be the piezoelectric sensor array, the piezoelectric sensor array is fixed to the surface of a test piece to be detected, various damage identification researches on different materials, structures and working conditions in practical engineering are carried out, and the overall detection precision and detection effect of the system are improved.
Drawings
FIG. 1 is a schematic flow diagram of the system of the present invention;
FIG. 2 is a schematic flow diagram of a data preprocessing module according to the present invention;
FIG. 3 is a schematic flow chart of a temperature compensation module according to the present invention;
FIG. 4 is a schematic flow chart diagram of a feedback learning module according to the present invention;
FIG. 5 is a schematic flow chart of a data fitting module according to the present invention.
1, a piezoelectric sensor array; 2. an impedance analyzer; 3. a central processing computer; 4. a data preprocessing module; 5. a temperature compensation module; 6. a feedback learning module; 7. a data fitting module; 401. a database; 402. a data transmission module; 403. a data recording module; 404. a data processing module; 405. a coordinate establishing module; 406. a curve establishing module; 501. a temperature recording module; 502. a temperature measurement module; 503. a temperature storage module; 504. a temperature processing module; 505. a temperature fitting module; 601. a feedback learning system; 602. a deep learning method; 603. a probability statistical method; 604. a sparse data reconstruction method; 701. a fitting model module; 702. an impedance fitting model; 703. a piezoelectric structure coupling model; 704. fitting a model by temperature; 705. a non-linear temperature coupling model.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
as shown in fig. 1-5, an embodiment of the present invention provides a structural damage identification method and system based on a piezoelectric impedance technology, including a piezoelectric sensor array 1, where the piezoelectric sensor array 1 is connected to an impedance analyzer 2, which is favorable for implementing a basic impedance detection function of the system, and the impedance analyzer 2 is connected to a central processing computer 3, which is favorable for providing a basis for data analysis and processing of the computer;
the central processing computer 3 is bidirectionally connected with a data preprocessing module 4, a data fitting module 7, a temperature compensation module 5 and a feedback learning module 6, which is beneficial to realizing the data analysis processing function of the system and realizing the deep learning of the system to the data.
The data preprocessing module 4 comprises a database 401, the database 401 is connected with a data transmission module 402, a data recording module 403 and a data processing module 404, which are beneficial for a user to transmit and record the detection data through the system, and the data processing module 404 is connected with a coordinate establishing module 405 and a curve establishing module 406, which are beneficial for the system to establish the acquired data to form an impedance curve.
The temperature compensation module 5 comprises a temperature recording module 501 and a temperature processing module 504, and is beneficial to collecting and recording temperature data of the environment, the temperature recording module 501 is connected with a temperature measuring module 502 and a temperature storage module 503, the temperature processing module 504 is connected with a temperature fitting module 505, and is beneficial to recording the collected data, and performs impedance curve fitting on the data at each temperature, the feedback learning module 6 comprises a feedback learning system 601, the feedback learning system 601 is connected with a deep learning method 602, a probability statistical method 603 and a sparse data reconstruction method 604, the whole system is based on a physical model, and the function of performing deep feedback learning by the system is facilitated.
The data fitting module 7 comprises a fitting model module 701, the fitting model module 701 is connected with an impedance fitting model 702 and a temperature fitting model 704, the impedance fitting model 702 is connected with a piezoelectric structure coupling model 703, and the temperature fitting model 704 is connected with a nonlinear temperature coupling model 705, so that the function of combining and fitting the temperature of the system is realized, and the system can compensate the measurement result according to the temperature environment.
A structural damage identification method based on a piezoelectric impedance technology specifically comprises the following steps:
s1, instrument installation
The piezoelectric sensor array 1 is fixedly arranged on the surface of a test piece to be tested through an adhesive, the piezoelectric sensor array 1 is connected with the impedance analyzer 2 through an electric wire, and the impedance analyzer 2 is connected with the central processing computer 3, so that the basic data acquisition function of the system can be realized;
s2. Data acquisition
Starting the impedance analyzer 2, acquiring data through a data preprocessing module 4 of the central processing computer 3, and transmitting and recording the data through a data transmission module 402 and a data recording module 403 of a database 401 to realize the data acquisition function of the system;
s3, data processing
The acquired data is subjected to impedance curve establishment through the data processing module 404, a plurality of test pieces to be detected with different damage degrees are replaced, the process from S1 to S2 is repeated, impedance curves of the test pieces to be detected with different damage degrees are measured, and the system can conveniently fit the measurement results in the following process;
s4, result fitting
Inputting a plurality of groups of different impedance curves into a fitting model module 701, fitting a detection result through an impedance fitting model 702 connected with a piezoelectric structure coupling model 703 to realize damage identification, setting a component to be detected into different temperature environments, repeating the processes from S1 to S3 to measure impedance curves at different temperatures, and correcting data at different temperatures when damage identification is carried out through the piezoelectric structure coupling model 703 and a nonlinear temperature coupling model 705, so that the detection accuracy of the whole system at different temperatures is improved;
s5, feedback learning
The different types of test pieces are replaced for multiple detection, the detection result is input into the feedback learning module 6, the feedback learning system 601 is enabled to perform deep learning by combining the deep learning method 602 and the probability statistical method 603 with the sparse data reconstruction method 604, autonomous damage detection and recognition during subsequent use of the system are achieved, the system is favorable for deep learning through multiple use, and the using effect of the system is improved.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A structural damage identification system based on piezoelectric impedance technology comprises a piezoelectric sensor array (1), and is characterized in that: the piezoelectric sensor array (1) is connected with an impedance analyzer (2), and the impedance analyzer (2) is connected with a central processing computer (3);
the central processing computer (3) is connected with a data preprocessing module (4), a data fitting module (7), a temperature compensation module (5) and a feedback learning module (6) in a bidirectional mode.
2. A structural damage identification system based on piezoelectric impedance technology as claimed in claim 1, wherein: the data preprocessing module (4) comprises a database (401), and the database (401) is connected with a data transmission module (402), a data recording module (403) and a data processing module (404).
3. A structural damage identification system based on piezoelectric impedance technology as claimed in claim 2, wherein: the data processing module (404) is connected with a coordinate establishing module (405) and a curve establishing module (406).
4. A piezoelectric impedance technology based structural damage identification system as claimed in claim 1, wherein: the temperature compensation module (5) comprises a temperature recording module (501) and a temperature processing module (504), the temperature recording module (501) is connected with a temperature measuring module (502) and a temperature storage module (503), and the temperature processing module (504) is connected with a temperature fitting module (505).
5. A structural damage identification system based on piezoelectric impedance technology as claimed in claim 1, wherein: the feedback learning module (6) comprises a feedback learning system (601), and the feedback learning system (601) is connected with a deep learning method (602), a probability statistical method (603) and a sparse data reconstruction method (604).
6. A structural damage identification system based on piezoelectric impedance technology as claimed in claim 1, wherein: the data fitting module (7) comprises a fitting model module (701), and an impedance fitting model (702) and a temperature fitting model (704) are connected to the fitting model module (701).
7. A piezoelectric impedance technology based structural damage identification system as claimed in claim 6, wherein: the impedance fitting model (702) is connected with a piezoelectric structure coupling model (703), and the temperature fitting model (704) is connected with a nonlinear temperature coupling model (705).
8. A structural damage identification method based on a piezoelectric impedance technology is characterized by comprising the following steps:
s1, instrument installation
Fixedly arranging a piezoelectric sensor array (1) on the surface of a test piece to be tested through an adhesive, connecting the piezoelectric sensor array (1) with an impedance analyzer (2) through a wire, and connecting the impedance analyzer (2) with a central processing computer (3);
s2. Data acquisition
Starting an impedance analyzer (2), performing data acquisition through a data preprocessing module (4) of a central processing computer (3), and performing data transmission and recording on data through a data transmission module (402) and a data recording module (403) of a database (401);
s3, data processing
Establishing an impedance curve of the acquired data through a data processing module (404), replacing a plurality of test pieces to be detected with different damage degrees, repeating the process from S1 to S2, and measuring the impedance curve of the test pieces to be detected under different damage degrees;
s4, fitting results
Inputting a plurality of groups of different impedance curves into a fitting model module (701), fitting a detection result through an impedance fitting model (702) connected with a piezoelectric structure coupling model (703) to realize damage identification, setting a component to be detected into different temperature environments, repeating the processes from S1 to S3 to measure the impedance curves at different temperatures, and compensating data based on different temperatures when damage identification is carried out through the piezoelectric structure coupling model (703) and a nonlinear temperature coupling model (705);
s5, feedback learning
The test pieces of different types are replaced to carry out detection for multiple times, the detection result is input into a feedback learning module (6), and the feedback learning system (601) carries out deep learning by combining a deep learning method (602) and a probability statistical method (603) with a sparse data reconstruction method (604), so that autonomous damage detection and identification during subsequent use of the system are realized.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117309060A (en) * | 2023-10-20 | 2023-12-29 | 广东省装饰有限公司 | Building curtain wall structure performance monitoring system based on cloud computing |
| CN117330604A (en) * | 2023-12-01 | 2024-01-02 | 深圳市城市公共安全技术研究院有限公司 | Automatic temperature compensation method, device, computer equipment and storage medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117309060A (en) * | 2023-10-20 | 2023-12-29 | 广东省装饰有限公司 | Building curtain wall structure performance monitoring system based on cloud computing |
| CN117309060B (en) * | 2023-10-20 | 2024-05-17 | 广东省装饰有限公司 | Building curtain wall structure performance monitoring system based on cloud computing |
| CN117330604A (en) * | 2023-12-01 | 2024-01-02 | 深圳市城市公共安全技术研究院有限公司 | Automatic temperature compensation method, device, computer equipment and storage medium |
| CN117330604B (en) * | 2023-12-01 | 2024-05-07 | 深圳市城市公共安全技术研究院有限公司 | Automatic temperature compensation method, device, computer equipment and storage medium |
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