CN114324584B - Steel structure detection method based on intelligent algorithm and ultrasonic phased array technology - Google Patents
Steel structure detection method based on intelligent algorithm and ultrasonic phased array technology Download PDFInfo
- Publication number
- CN114324584B CN114324584B CN202111546254.XA CN202111546254A CN114324584B CN 114324584 B CN114324584 B CN 114324584B CN 202111546254 A CN202111546254 A CN 202111546254A CN 114324584 B CN114324584 B CN 114324584B
- Authority
- CN
- China
- Prior art keywords
- steel structure
- damage
- intelligent algorithm
- phased array
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Landscapes
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
Abstract
The invention discloses a steel structure detection method based on an intelligent algorithm and an ultrasonic phased array technology, which comprises the following steps: acquiring initial information of a steel structure; grouping the steel structural members according to the member types; the method comprises the steps of taking initial information of a steel structure and a grouping situation of construction as modeling basis, and establishing a steel structure analysis model by means of structure analysis software; the structural analysis software simulates damage of components at different parts of the steel structure, so as to obtain modal information after damage; analyzing, summarizing and sorting the mode data after the damage of different parts to form a training sample; establishing a damage positioning model by adopting an intelligent algorithm; detecting the movement of an ultrasonic focusing point in a region; positioning the defect position; the field control computer processes the data and transmits the data back to the PC terminal computer, so that the functions of visual display and statistics are realized. The beneficial effects of the invention are as follows: the damage position location is accurate in the steel construction detects, and damage degree detection efficiency is high.
Description
Technical Field
The invention relates to the technical field of steel structure detection, in particular to a steel structure detection method based on an intelligent algorithm and an ultrasonic phased array technology.
Background
Compared with other structures, the steel structure has the advantages of light weight, good toughness, convenient construction, more environmental protection and the like, so the steel structure is widely applied to various building structures. However, with the increase of the service time, the rigid structure can be damaged to different degrees and at different positions. Once the steel structure in the building structure is damaged and left to develop, performance degradation occurs, even failure collapse resulting in immeasurable losses. Therefore, damage detection and health condition assessment of the steel structure have become hot spot problems of hot interest at home and abroad.
At present, a nondestructive detection method is generally adopted for the detection mode of the steel structure, such as ultrasonic detection, eddy current detection, magnetic memory detection, sound vibration detection and the like. The methods can well evaluate the conditions of the damaged part of the steel structure. However, the methods have the defects of complicated operation modes, incapability of arranging detection angles according to requirements, low detection efficiency, high requirements on operators and the like. The ultrasonic phased array technology is different from the above technologies, can flexibly control the focusing position of the sound beam, improve the detection signal-to-noise ratio, coverage rate and sensitivity, locate and image the interior of an object to be detected on the premise of not moving or less moving the transducer, has a relatively large detection range, and can realize high-efficiency detection in a small range.
In actual engineering, the volume of a steel structure is quite huge, undamaged components are mostly, and the defects of large workload, low efficiency, uneconomical and the like generally exist when the existing local detection method is used for detecting the components of the steel structure one by one. The development of intelligent algorithms in recent years brings about a desire to solve this problem. The intelligent algorithm has the advantages of information processing parallelism, self-organization, self-learning, associative memory function, strong robustness and fault tolerance and the like, and is widely applied to various fields of civil engineering and the like. The structural damage positioning method using the intelligent algorithm does not need priori knowledge of structural dynamic characteristics, and has the advantage of non-parameter damage positioning; the method can acquire the implicit relation between the input and the output hidden in the sample data through training and learning, and can filter noise and extract the inherent characteristics of things under the noisy condition, so that the method is more suitable for damage positioning of a structure with a large amount of noise and measurement errors. However, due to the self-limiting problem of the intelligent algorithm, namely that the damage part cannot be accurately positioned to a point when a positioning model is designed, the damage part can be positioned to a certain area only through modal parameter information.
Disclosure of Invention
Aiming at the problems of low detection efficiency and difficult damage positioning in the current detection in the prior art, the invention provides a steel structure detection method based on an intelligent algorithm and an ultrasonic phased array technology, which has accurate positioning and high detection efficiency.
The invention discloses a steel structure detection method based on an intelligent algorithm and an ultrasonic phased array technology, which is characterized by comprising the following steps of:
acquiring initial information of a steel structure;
grouping the steel structural members according to the member types;
taking initial information of the steel structure and the grouping situation of the construction as modeling basis, and establishing a steel structure analysis model by means of a structure analysis program or structure analysis software;
the structural analysis program simulates damage of components at different parts of the steel structure, so as to obtain modal information after damage;
analyzing, summarizing and sorting the mode data after the damage of different parts to form a training sample;
the intelligent algorithm is adopted to take damage conditions of different components of the steel structure as input parameters, corresponding modal parameters as output parameters, and different input parameters and output parameters are combined to form a training sample; training and learning the model constructed by the intelligent algorithm by utilizing the combined training sample, and continuously performing iterative computation until the learning and training result of the model reaches the specified precision requirement and establishing an intelligent algorithm-based damage positioning model if the learning result does not reach the precision requirement; the intelligent algorithm comprises a group intelligent algorithm, a simulated annealing algorithm, a Bayesian method, a Gaussian process, a neural network, various agent models and the like;
according to the positioning information given by the intelligent algorithm damage positioning system, a PC terminal computer belonging to the ultrasonic phased array system realizes the movement of an ultrasonic focusing point to perform region detection by changing the setting of a multichannel instrument;
the detection personnel hold the array probe to transmit a plurality of groups of signals to the region to be detected, and the receiving end receives echo signals of the region to be detected and intercepts a plurality of groups of scattered echo signals; inverting the time sequence of each received group of scattered signals, selecting a time point with the maximum amplitude value in each group, and positioning the defect position;
the field control computer processes the acquired data, and inputs the processed data to the PC terminal computer of the control room in a long-distance transmission communication mode, so that visual display and statistics functions are realized.
Further, the steel structure initial information comprises construction drawing information, steel structure line information, steel structure material information and current state steel structure modal information of the bridge.
Furthermore, in order to improve the accuracy and convergence rate of the intelligent algorithm for judging the damage position of the steel structure, the whole steel structure is scattered into different sub-components according to the type of the components, and the steel structure can be subdivided into beam components, rod components, supporting components and the like according to the stress condition of the steel structure.
When the construction analysis software is used for modeling, a steel structure model under a nondestructive condition is firstly established according to the grouping condition of each component of the design information, the models are grouped according to the types of the sub-components, and the damage condition of each sub-component is digitized to form training samples by using later statistical information.
Furthermore, the structural damage part simulation process should simulate all the sub-components which are possibly damaged one by one, and obtain damage mode information under the damage state of a single component, which is the most important and complex task in the whole detection method.
The damage introducing mode can reduce the modulus of a damage part, set a unit notch and even remove part of units. Specifically, damage is introduced into the original nondestructive model, the damage-introduced part is determined according to the grouping condition of the sub-components, each sub-component is ensured to be damaged at least once, the damage-introduced mode can be adopted to reduce the modulus of the damage part, set up a unit gap and even remove part of units, and the structural analysis program is utilized to output the modal parameters of different parts of the steel structure in the single damage state.
Furthermore, the single damage state means that only a single damage working condition of a component is required to be simulated each time in the structural analysis model, and the intelligent algorithm is used for randomly combining the damage working conditions of the single components and the corresponding mode samples to obtain multi-damage working condition corresponding mode information of multiple components damaged simultaneously.
Furthermore, the training sample has universality for the current detection and the subsequent detection of the steel structure to be detected, and the data is still applicable no matter how the performance of the steel structure is degraded in the subsequent service period, and belongs to a permanent structure data model.
Further, after the structural analysis model is built, the damage position of the steel structure needs to be calculated reversely according to the actually measured steel structure modal information, the damage positioning precision of the intelligent algorithm is judged, if the precision requirement is met, the building of the intelligent damage positioning model is completed, otherwise, the intelligent algorithm needs to be optimized in a iterated mode again until the precision requirement is met; the intelligent algorithm adopts a normalized damage signal index NDSI as a network input vector to perform specific damage positioning, the normalized damage signal index NDSI is used as damage identification of the network input vector, and the error between the positioning damage position and the actual damage position of the intelligent algorithm is smaller than the maximum scanning range of the ultrasonic phased array technology, so that the accuracy requirement is met.
Furthermore, the multichannel instrument is divided into an array transmitting part and an array receiving part, and is controlled by a PC terminal computer, and the scanning of the area to be detected is realized by controlling the position of the phased array probe.
Further, the phased array probe is composed of a focusing sound beam, the focusing sound beam is composed of a certain number of array elements, and the PC terminal computer controls the phased array probe to scan the area to be detected by moving the array elements.
Further, the field control computer processes the acquired data as follows: the array receiving circuit converts the reflected ultrasonic signals into measurable voltages, data stored in the memory of the field control computer are finally obtained through data processing, and the bus is converted into an RS232 bus and an RS485 bus to realize long-distance transmission and then converted into RS232. In the operation of computer software, the two-way data communication can be realized by programming the RS232 bus.
The beneficial effects of the invention are as follows: the steel structure detection efficiency is greatly improved by fusing an intelligent algorithm positioning prediction technology and an ultrasonic phased array detection technology; the intelligent algorithm positioning system utilizes the learning and iteration functions of the algorithm to realize the preliminary positioning of the damage position according to the actual modal parameters of the steel structure only through small manpower and material resource consumption; after the ultrasonic phased array system is initially positioned, the PC terminal computer controls the phased array probe to accurately scan and detect the region to be detected, the scanning range is enlarged by changing the position of the array element, the advantage of accurate detection in a small range of the ultrasonic phased array technology is fully exerted, the problems that the traditional detection method is difficult in positioning the damaged position and low in detection efficiency are solved, and the steel structure detection technology is further improved.
Drawings
FIG. 1a is a flow chart of the present invention;
FIG. 1b is a schematic diagram of a detection method of the present invention;
FIG. 2 is a flow chart of the intelligent algorithm of the present invention;
FIG. 3 is a flow chart of the ultrasonic phased array technique of the invention;
FIG. 4 is a schematic diagram of the operation of the ultrasonic phased array technique;
fig. 5 is a diagram of the detection effect of the ultrasonic phased array technology.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
FIGS. 1a and 1b are block diagrams of a steel structure detection method based on an intelligent algorithm and an ultrasonic phased array technology, which comprise an intelligent algorithm system as shown in FIG. 2 and an ultrasonic phased array technology system as shown in FIG. three, and specifically comprise the following steps
S1, acquiring initial information of a steel structure;
s2, grouping steel structural members according to the types of the members;
s3, taking initial information of the steel structure and the grouping situation of construction as modeling basis, and establishing a steel structure analysis model by means of a structure analysis program;
s4, simulating damage to components at different parts of the steel structure by a structural analysis program, and further obtaining mode information after damage;
s5, analyzing, summarizing and sorting the modal data after the injury of different parts to form a training sample;
s6, the intelligent algorithm takes damage conditions of different components of the steel structure as input parameters, corresponding modal parameters as output parameters, and combines different input parameters and output parameters to form a training sample; training and learning the model constructed by the intelligent algorithm by utilizing the combined training sample, and continuously performing iterative computation until the learning and training result of the model reaches the specified precision requirement and establishing an intelligent algorithm-based damage positioning model if the learning result does not reach the precision requirement; the intelligent algorithm comprises a group intelligent algorithm, a simulated annealing algorithm, a Bayesian method, a Gaussian process, a neural network, various agent models and the like;
s7, according to the positioning information given by the intelligent algorithm damage positioning system, a PC terminal belonging to the ultrasonic phased array system realizes the movement of an ultrasonic focusing point to perform region detection by changing the setting of a multichannel instrument;
s8, the detector holds the array probe to transmit a plurality of groups of signals to the area to be detected, and the receiving end receives echo signals of the area to be detected and intercepts a plurality of groups of scattered echo signals; and inverting the time sequence of each received scattered signal group, selecting a time point with the maximum amplitude value in each group, and positioning the defect position.
S9, the site control computer processes part of data, and inputs the processed data to a PC terminal computer of a control room in a long-distance transmission communication mode, so that visual display and statistics functions are realized.
In the step S1, steel structure construction drawing information, steel structure line information and steel structure material information are required to be acquired from a steel structure operator in an initial preparation stage, and corresponding dynamic characteristic tests are required to be organized to obtain the modal parameters of the current steel structure.
In the S2 step, in order to improve the accuracy and convergence rate of the intelligent algorithm on the judgment of the damage position of the steel structure, the whole steel structure is scattered into different sub-components according to the type of the components, and the steel structure can be subdivided into beam components, rod components, supporting components and the like according to the stress condition of the steel structure.
And S3, when the structural analysis program is used for modeling, firstly, a steel structure model under the condition of no damage is established according to the grouping condition of each component of the design information, and the models are grouped according to the types of the sub-components.
And S4, introducing damage into the original nondestructive model, determining the damage-introducing part according to the grouping condition of the sub-components, and ensuring that each sub-component is at least subjected to damage once, wherein the damage-introducing mode can adopt the mode of reducing the modulus of the damage part, setting a unit notch and even removing part of units, and outputting the modal parameters of different parts of the steel structure in a single damage state by using a structure analysis program.
The construction of the digitization of the damage information means that each damage information is represented in a matrix form as follows: beam member damage is noted as 1 0, rod member damage is noted as 0 1 0 support member damage is noted as 0 0 1, etc. The structural sub-members, including but not limited to beam members, bar members, support members, should be classified according to the actual steel structural properties.
In the step S5, the data sample has universality for the current detection and the subsequent detection of the steel structure to be detected, and the data is still applicable no matter how the performance of the steel structure is degraded in the subsequent service period, and belongs to a permanent structural data model.
And S6, combining, learning and iterating training samples formed by the damage conditions of different components of the steel structure and corresponding modal parameters to establish a damage positioning model, after the model is established, reversely calculating the damage position of the steel structure according to the actually measured modal information of the steel structure, judging the damage positioning precision of the intelligent algorithm, if the precision requirement is met, establishing the intelligent damage positioning model, otherwise, re-iterating and optimizing the intelligent algorithm until the precision requirement is met. The error between the positioning damage position of the intelligent algorithm and the actual damage position is smaller than the maximum scanning range of the ultrasonic phased array technology, so that the accuracy requirement is met.
In the step S7, the design of the multichannel instrument can be divided into two parts of array transmitting and array receiving, a command is initiated by a terminal computer, a data input stage is started, the scanning of the sub-component area to be detected is realized by controlling the position of the phased array probe, the data input is stopped after the scanning of all the sub-component detection areas is finished, and a data transfer stage is entered. And after analyzing and storing the data of the control computer, the PC terminal checks the next sub-component until all the sub-components are detected.
The phased array probe consists of a focusing sound beam, the focusing sound beam consists of a certain number of array elements, and the PC terminal computer controls the phased array probe to scan the area to be detected by moving the array elements.
The number of the focused sound beams and the array element components of the phased array probe is determined by an actual detection range, for example, one focused sound beam composed of 16 array elements is adopted, and the effective detection range is 16mm.
In the step S9, the array receiving circuit converts the reflected ultrasonic signals into measurable voltage, and data stored in the memory of the field control computer is finally obtained through data processing, and the data is converted into RS232 bus and RS485 bus after long-distance transmission is realized. In the operation of computer software, the two-way data communication can be realized by programming the RS232 bus.
The embodiments described in the present specification are merely examples of implementation forms of the inventive concept, and the scope of protection of the present invention should not be construed as being limited to the specific forms set forth in the embodiments, but also equivalent technical means that can be conceived by those skilled in the art according to the inventive concept.
Claims (9)
1. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology is characterized by comprising the following steps of:
acquiring initial information of a steel structure;
grouping the steel structural members according to the member types;
taking initial information of the steel structure and the grouping situation of the construction as modeling basis, and establishing a steel structure analysis model by means of a structure analysis program; when the construction analysis software is used for modeling, firstly, a steel structure model under a nondestructive condition is established according to the grouping condition of each component of design information, the models are grouped according to the types of the sub-components, and the damage condition of each sub-component is digitalized and used for forming training samples by later statistical information;
the structural analysis program simulates damage of components at different parts of the steel structure, so as to obtain modal information after damage;
analyzing, summarizing and sorting the mode data after the damage of different parts to form a training sample;
the intelligent algorithm is adopted to take damage conditions of different components of the steel structure as input parameters, corresponding modal parameters as output parameters, and different input parameters and output parameters are combined to form a training sample; training and learning the model constructed by the intelligent algorithm by utilizing the combined training sample, and continuously performing iterative computation until the learning and training result of the model reaches the specified precision requirement and establishing an intelligent algorithm-based damage positioning model if the learning result does not reach the precision requirement; the intelligent algorithm comprises a group intelligent algorithm, a simulated annealing algorithm, a Bayesian method, a Gaussian process, a neural network and various agent models;
according to the positioning information given by the intelligent algorithm damage positioning system, a PC terminal computer belonging to the ultrasonic phased array system realizes the movement of an ultrasonic focusing point to perform region detection by changing the setting of a multichannel instrument;
the detection personnel hold the array probe to transmit a plurality of groups of signals to the region to be detected, and the receiving end receives echo signals of the region to be detected and intercepts a plurality of groups of scattered echo signals; inverting the time sequence of each received group of scattered signals, selecting a time point with the maximum amplitude value in each group, and positioning the defect position;
the field control computer processes the acquired data, and inputs the processed data to the PC terminal computer of the control room in a long-distance transmission communication mode, so that visual display and statistics functions are realized.
2. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology as claimed in claim 1, wherein the method comprises the following steps: the steel structure initial information comprises construction drawing information, steel structure line information, steel structure material information and current state steel structure modal information of the bridge.
3. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology as claimed in claim 1, wherein the method comprises the following steps: in order to improve the accuracy and convergence rate of the intelligent algorithm for judging the damage position of the steel structure, the whole steel structure is scattered into different sub-components according to the type of the components, and the steel structure can be subdivided into beam components, rod components and supporting components according to the stress condition of the steel structure.
4. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology as claimed in claim 1, wherein the method comprises the following steps: the damage is introduced into the original nondestructive model, the damage-introduced part is determined according to the grouping condition of the sub-components, each sub-component is ensured to be damaged at least once, the damage-introduced mode can be used for reducing the modulus of the damaged part, setting a unit notch and even removing part of units, and the structural analysis software is used for outputting the modal parameters of different parts of the steel structure in the single damage state.
5. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology as claimed in claim 4, wherein the method comprises the following steps: the single damage state means that only a single component damage working condition needs to be simulated each time in a structural analysis model, and each single component damage working condition and a corresponding mode sample are randomly combined by an intelligent algorithm to obtain multi-component damage working condition corresponding mode information with multiple damaged components simultaneously.
6. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology as claimed in claim 1, wherein the method comprises the following steps: after the structural analysis model is built, the damage position of the steel structure needs to be reversely calculated according to the actually measured steel structure modal information, the damage positioning precision of the intelligent algorithm is judged, if the precision requirement is met, the intelligent damage positioning model is built, otherwise, the intelligent algorithm needs to be optimized again in an iterating mode until the precision requirement is met; the intelligent algorithm adopts a normalized damage signal index NDSI as a network input vector to perform specific damage positioning, the normalized damage signal index NDSI is used as damage identification of the network input vector, and the error between the positioning damage position and the actual damage position of the intelligent algorithm is smaller than the maximum scanning range of the ultrasonic phased array technology, so that the accuracy requirement is met.
7. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology as claimed in claim 1, wherein the method comprises the following steps: the multichannel instrument is divided into an array transmitting part and an array receiving part, and is controlled by a PC terminal computer, and the scanning of the area to be detected is realized by controlling the position of the phased array probe.
8. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology as claimed in claim 7, wherein the method comprises the following steps: the phased array probe consists of a focusing sound beam, the focusing sound beam consists of a certain number of array elements, and the PC terminal computer controls the phased array probe to scan the area to be detected by moving the array elements.
9. The steel structure detection method based on the intelligent algorithm and the ultrasonic phased array technology as claimed in claim 1, wherein the method comprises the following steps: the field control computer processes the acquired data as follows: the array receiving circuit converts the reflected ultrasonic signals into measurable voltages, data stored in the memory of the field control computer are finally obtained through data processing, and the bus is converted into an RS232 bus and an RS485 bus to realize long-distance transmission and then converted into RS232.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111546254.XA CN114324584B (en) | 2021-12-16 | 2021-12-16 | Steel structure detection method based on intelligent algorithm and ultrasonic phased array technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111546254.XA CN114324584B (en) | 2021-12-16 | 2021-12-16 | Steel structure detection method based on intelligent algorithm and ultrasonic phased array technology |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114324584A CN114324584A (en) | 2022-04-12 |
| CN114324584B true CN114324584B (en) | 2023-09-05 |
Family
ID=81052008
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111546254.XA Active CN114324584B (en) | 2021-12-16 | 2021-12-16 | Steel structure detection method based on intelligent algorithm and ultrasonic phased array technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114324584B (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101566601A (en) * | 2009-05-04 | 2009-10-28 | 北京航空航天大学 | System for recognizing tensile damage state of 16Mn steel force-bearing part by adopting neural network and coupling iteration |
| CN102279223B (en) * | 2011-05-16 | 2013-03-20 | 北京航空航天大学 | Identifying and assessing system for deformation and damage of 16Mn steel welded structure on basis of SNF (Strongest Neighbor Filter) and DSD (Deformation Sensitive Decimation) policies |
| CN204612669U (en) * | 2015-05-20 | 2015-09-02 | 中国海洋石油总公司 | A kind of crude oil pipeline wax deposition thickness off-line detection device |
| CN111272886A (en) * | 2020-03-24 | 2020-06-12 | 华东理工大学 | Pressure vessel damage positioning method based on convolutional neural network |
| CN111561901A (en) * | 2020-04-15 | 2020-08-21 | 交通运输部水运科学研究所 | Steel structure strain detection fault identification method based on deep learning |
| CN111767897A (en) * | 2020-07-14 | 2020-10-13 | 上海应用技术大学 | Support vector machine-based steel rail crack defect identification method |
| CN112131781A (en) * | 2020-08-26 | 2020-12-25 | 浙江工业大学 | Steel structure damage detection method based on full-connection neural network and transfer rate function |
| KR102256181B1 (en) * | 2019-12-30 | 2021-05-27 | 한국과학기술원 | Method of inspecting and evaluating coating state of steel structure and system for the same |
| CN114813973A (en) * | 2022-03-09 | 2022-07-29 | 浙江大学 | Bolt loosening detection method combining time reversal technology and BP neural network |
| CN115754022A (en) * | 2022-11-29 | 2023-03-07 | 东南大学 | Steel truss welding node damage degree identification method based on acoustic emission |
-
2021
- 2021-12-16 CN CN202111546254.XA patent/CN114324584B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101566601A (en) * | 2009-05-04 | 2009-10-28 | 北京航空航天大学 | System for recognizing tensile damage state of 16Mn steel force-bearing part by adopting neural network and coupling iteration |
| CN102279223B (en) * | 2011-05-16 | 2013-03-20 | 北京航空航天大学 | Identifying and assessing system for deformation and damage of 16Mn steel welded structure on basis of SNF (Strongest Neighbor Filter) and DSD (Deformation Sensitive Decimation) policies |
| CN204612669U (en) * | 2015-05-20 | 2015-09-02 | 中国海洋石油总公司 | A kind of crude oil pipeline wax deposition thickness off-line detection device |
| KR102256181B1 (en) * | 2019-12-30 | 2021-05-27 | 한국과학기술원 | Method of inspecting and evaluating coating state of steel structure and system for the same |
| CN111272886A (en) * | 2020-03-24 | 2020-06-12 | 华东理工大学 | Pressure vessel damage positioning method based on convolutional neural network |
| CN111561901A (en) * | 2020-04-15 | 2020-08-21 | 交通运输部水运科学研究所 | Steel structure strain detection fault identification method based on deep learning |
| CN111767897A (en) * | 2020-07-14 | 2020-10-13 | 上海应用技术大学 | Support vector machine-based steel rail crack defect identification method |
| CN112131781A (en) * | 2020-08-26 | 2020-12-25 | 浙江工业大学 | Steel structure damage detection method based on full-connection neural network and transfer rate function |
| CN114813973A (en) * | 2022-03-09 | 2022-07-29 | 浙江大学 | Bolt loosening detection method combining time reversal technology and BP neural network |
| CN115754022A (en) * | 2022-11-29 | 2023-03-07 | 东南大学 | Steel truss welding node damage degree identification method based on acoustic emission |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114324584A (en) | 2022-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102692188B (en) | Dynamic crack length measurement method for machine vision fatigue crack propagation test | |
| CN113219070B (en) | Novel structural damage positioning method based on acoustic emission | |
| CN112418266A (en) | Pile foundation integrity classification and identification method based on convolutional neural network | |
| CN114113332A (en) | Prefabricated column sleeve grouting nondestructive testing method based on elastic waves and machine learning | |
| CN111445515A (en) | Underground cylinder target radius estimation method and system based on feature fusion network | |
| CN112731377A (en) | Dielectric constant inversion method, roadbed detection method and detection system | |
| CN114324584B (en) | Steel structure detection method based on intelligent algorithm and ultrasonic phased array technology | |
| CN111443131B (en) | Method for detecting grouting compactness of steel bar sleeve | |
| CN111678991B (en) | Method for nondestructive testing damage identification of concrete structure | |
| CN112131781B (en) | Steel structure damage detection method based on fully-connected neural network and transfer rate function | |
| CN111579647B (en) | Concrete member corrosion degree detection method and system based on analytic hierarchy process | |
| CN112816557B (en) | Defect detection method, device, equipment and storage medium | |
| CN115144259A (en) | Method and system for detecting deformation resistance of steel | |
| CN113075289B (en) | Metal cylinder defect parameter detection method and system | |
| Zhao et al. | Research on the application of computer intelligent detection in civil engineering technology | |
| CN113092588A (en) | Ultrasonic phased array detection device and detection method | |
| CN108152373B (en) | System and method for measuring mechanical property of composite material containing pores based on pore size identification | |
| CN117949542B (en) | Industrial pipe gallery column-holding scaffold firmness detection method, medium and system | |
| CN112213396A (en) | Nondestructive testing method for ballastless track plate of track traffic | |
| CN111241725A (en) | Structure response reconstruction method for generating countermeasure network based on conditions | |
| CN111210409A (en) | Condition-based generation confrontation network structure damage identification method | |
| Dekhterev et al. | Diagnostics of defects of monolithic reinforced concrete structures using neural network technologies | |
| CN116953196B (en) | Defect detection and safety state assessment method for steel tee joint | |
| CN116482114A (en) | Method for identifying damage of steel structural beam after fire disaster | |
| CN111291490B (en) | Nonlinear mapping intelligent modeling method for structure multi-scale heterogeneous response |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |