CN113343554A - Arch dam underwater damage identification method, terminal equipment and storage medium - Google Patents
Arch dam underwater damage identification method, terminal equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of dam structure health diagnosis, in particular to an arch dam underwater damage identification method, terminal equipment and a storage medium. Acquiring a micro vibration video of the top of the damaged arch dam under the action of a drainage load; decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video; obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information; and (3) importing the information of the natural frequency and the vibration mode of the arch dam into a pre-constructed damage identification model to obtain the information of the underwater damage range, the damage degree and the damage position of the arch dam. The dynamic characteristics of the arch dam can be obtained through a micro vibration video of the top of the arch dam under the action of a discharge load, a refined model and a dynamic damage database of the arch dam are established through non-damaged arch dam data, an underwater damage identification model of the arch dam is established by combining machine learning, and finally, underwater damage identification of the damaged arch dam including information of underwater damage range, damage degree and damage position of the arch dam is achieved, and the underwater damage identification is high in accuracy.
Description
Technical Field
The invention relates to the technical field of dam structure health diagnosis, in particular to an arch dam underwater damage identification method, terminal equipment and a storage medium.
Background
Arch dams can be damaged underwater due to various factors. The method has important guiding significance for rescue and disaster relief and quick repair under the emergency state of the arch dam by quickly judging the underwater damage part and determining the damage range, and has important significance for ensuring the integral stability of the structure and the personal and property safety of downstream people.
The identification of the underwater damage of the arch dam can be divided into local damage identification and global damage identification, and the common technologies for local damage identification include:
(1) the underwater operation of the technology is complex, time-consuming and labor-consuming;
(2) the sensors for detecting the pre-buried stress strain, temperature and the like can only detect the explosion damage of the nearby area, and simultaneously, the damage range is difficult to determine.
For the above reasons, there is a need for a method that is easy to implement and can accurately identify a defect.
Disclosure of Invention
The invention aims to provide an arch dam underwater damage identification method, terminal equipment and storage medium aiming at the defects of the prior art, which are easy to realize and can accurately identify damage.
The invention discloses an arch dam underwater damage identification method, which adopts the technical scheme that: the method comprises the steps of obtaining a micro-vibration video of the top of the damaged arch dam under the action of a drainage load;
decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video;
obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information;
and importing the information of the natural frequency and the vibration mode of the arch dam into a pre-constructed damage identification model to obtain the underwater damage range, the damage degree and the damage position information of the arch dam.
Preferably, the method for constructing the damage identification model includes
Constructing an arch dam finite element model based on the undamaged arch dam;
establishing an arch dam natural frequency database and a vibration type dynamic damage database based on the arch dam finite element model;
and establishing a damage identification model based on the damage database.
Preferably, the constructing an arch dam finite element model based on the undamaged arch dam comprises:
acquiring a micro vibration video of the top of the undamaged arch dam under the action of a drainage load;
decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video;
obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information;
establishing an initial arch dam finite element model according to the arch dam design data;
and taking the arch dam natural frequency and the arch dam vibration mode information as a correction target of the initial arch dam finite element model, determining a specific response surface function form according to sample data obtained by response surface test, and updating the parameters of the initial arch dam finite element model to obtain the arch dam finite element model.
Preferably, the database for establishing the natural frequency and vibration type dynamic damage of the arch dam based on the arch dam finite element model comprises
Establishing arch dam finite element models in different damage states according to the arch dam finite element models;
and establishing an arch dam natural frequency damage database and a vibration type dynamic damage database according to finite element modal analysis based on the arch dam finite element models in different damage states.
Preferably, the different damage states include different locations and/or different ranges and/or different degrees of damage states.
Preferably, the creating of the damage identification model based on the damage database comprises
Establishing an arch dam damage range identification model and an arch dam damage degree identification model by adopting a machine learning algorithm according to the arch dam natural frequency damage database;
and establishing an arch dam damage position identification model by adopting a machine learning algorithm according to the vibration type dynamic damage database.
Preferably, the dam crest vibration video is acquired through an unmanned aerial vehicle.
Preferably, the acquiring process includes
Controlling the unmanned aerial vehicle to fly above the top of the arch dam, and adjusting the height of the unmanned aerial vehicle and the focal length of the camera until the whole dam crest area is within the visual field range of the camera and the contour of the dam crest is clear and visible;
and adjusting the shooting angle of the camera, and vertically shooting the micro vibration of the dam top under the action of the drainage load downwards.
The invention also provides a terminal device, comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps of the method when executing the computer program.
The invention also provides a storage medium, which stores a computer program that, when executed by a processor, performs the steps of the above method.
The invention has the beneficial effects that:
1. the dynamic characteristics of the arch dam can be obtained through a micro vibration video of the top of the arch dam under the action of a discharge load, a refined model and a dynamic damage database of the arch dam are established through non-damaged arch dam data, an underwater damage identification model of the arch dam is established by combining machine learning, and finally, underwater damage identification of the damaged arch dam including information of underwater damage range, damage degree and damage position of the arch dam is achieved, and the underwater damage identification is high in accuracy.
2. By adopting unmanned aerial vehicle non-contact measurement, the full-field motion information of the arch dam can be obtained to extract more accurate natural frequency and vibration mode, so that the requirements of finite element model updating and damage identification are met.
3. The method has the advantages that the acquired vibration video is utilized, the establishment of a damage identification model is realized by combining a machine learning algorithm, the underwater damage identification of the damaged arch dam is further realized, a contact type sensor is not required to be arranged, the method is more convenient, efficient and rapid, the operation is easy, a large amount of manpower, material resources and financial resources can be saved, and the damage can be more easily realized and accurately identified.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic flow chart of an embodiment (preferred) of the present invention;
fig. 3 is a schematic diagram of the underwater damage identification device/terminal device of the arch dam of the invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It should be noted that the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.
As shown in fig. 1, the process of the method is as follows:
s101: acquiring a micro vibration video of the top of the damaged arch dam under the action of a drainage load;
s102: decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video; specifically, a shot dam crest vibration video is guided into a computer for processing, and the arch dam vibration video is decomposed by adopting a controllable pyramid filter bank in a complex domain to obtain the local spatial amplitude and the local phase information of the video.
S103: obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information; specifically, the acquired local phase information of the arch dam is converted into a frequency domain, and the natural frequency of the arch dam is identified; and further filtering, amplifying and reconstructing the phase signals to finally obtain the vibration mode information of the arch dam.
S104: and importing the information of the natural frequency and the vibration mode of the arch dam into a pre-constructed damage identification model to obtain the underwater damage range, the damage degree and the damage position information of the arch dam.
Wherein, the damage identification model is constructed in advance according to the undamaged arch dam, and the process comprises the following steps:
s201: acquiring a micro vibration video of the top of the damaged arch dam under the action of a drainage load;
s202: decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video; specifically, a shot dam crest vibration video is guided into a computer for processing, and the arch dam vibration video is decomposed by adopting a controllable pyramid filter bank in a complex domain to obtain the local spatial amplitude and the local phase information of the video.
S203: obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information; specifically, the acquired local phase information of the arch dam is converted into a frequency domain, and the natural frequency of the arch dam is identified; and further filtering, amplifying and reconstructing the phase signals to finally obtain the vibration mode information of the arch dam.
S204: and constructing a damage identification model.
Wherein, S204 includes:
s204 a: constructing an arch dam finite element model based on the undamaged arch dam (namely updating the arch dam finite element model);
specifically comprises
Acquiring a micro vibration video of the top of the undamaged arch dam under the action of a drainage load;
decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video;
obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information;
establishing an initial arch dam finite element model according to the arch dam design data;
and taking the arch dam natural frequency and the arch dam vibration mode information as a correction target of the initial arch dam finite element model, determining a specific response surface function form according to sample data obtained by response surface test, and updating the parameters of the initial arch dam finite element model to obtain the arch dam finite element model.
S204 b: establishing an arch dam natural frequency database and a vibration type dynamic damage database based on the arch dam finite element model;
specifically comprises
Establishing arch dam finite element models in different damage states according to the arch dam finite element models;
and establishing an arch dam natural frequency damage database and a vibration type dynamic damage database according to finite element modal analysis based on the arch dam finite element models in different damage states.
S204 c: and establishing a damage identification model based on the damage database.
Specifically comprises
Establishing an arch dam damage range identification model and an arch dam damage degree identification model by adopting a machine learning algorithm according to the arch dam natural frequency damage database;
and establishing an arch dam damage position identification model by adopting a machine learning algorithm according to the vibration type dynamic damage database.
Example one
In the embodiment, the method is adopted to perform damage identification on the parabolic concrete hyperbolic arch dam with the dam crest elevation 640.5m, the riverbed building base level elevation 410m, the maximum dam height 230.5m, the dam crest arc length 552.55m and the thickness-height ratio of 0.216. The video is obtained by an unmanned aerial vehicle, the machine learning algorithm comprises a support vector regression machine and a convolutional neural network, and the specific flow is shown in figure 2:
s101: controlling the unmanned aerial vehicle to fly above the top of the arch dam, and adjusting the height of the unmanned aerial vehicle and the focal length of the camera until the whole dam crest area is within the visual field range of the camera and the contour of the dam crest is clear and visible;
adjusting the shooting angle of the camera, and vertically shooting the micro vibration of the dam crest under the action of the drainage load downwards; wherein, this unmanned aerial vehicle is the big Xinjiang cavic 2Pro unmanned aerial vehicle that has 10 bit color depth 4K shooting ability, and it flies to dam crest directly over through positioning system.
S102: decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video; specifically, a shot dam crest vibration video is guided into a computer for processing, and the arch dam vibration video is decomposed by adopting a controllable pyramid filter bank in a complex domain to obtain the local spatial amplitude and the local phase information of the video.
S103: obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information; specifically, the acquired local phase information of the arch dam is converted into a frequency domain, and the natural frequency of the arch dam is identified; and further filtering, amplifying and reconstructing the phase signals to finally obtain the vibration mode information of the arch dam.
S104: and importing the information of the natural frequency and the vibration mode of the arch dam into a pre-constructed damage identification model to obtain the underwater damage range, the damage degree and the damage position information of the arch dam.
Wherein, the damage identification model is constructed in advance according to the undamaged arch dam, and the process comprises the following steps:
s201: acquiring a micro vibration video of the top of the damaged arch dam under the action of a drainage load;
s202: decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video; specifically, a shot dam crest vibration video is guided into a computer for processing, and the arch dam vibration video is decomposed by adopting a controllable pyramid filter bank in a complex domain to obtain the local spatial amplitude and the local phase information of the video.
S203: obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information; specifically, the acquired local phase information of the arch dam is converted into a frequency domain, and the natural frequency of the arch dam is identified; and further filtering, amplifying and reconstructing the phase signals to finally obtain the vibration mode information of the arch dam.
S204: and constructing a damage identification model.
Wherein, S204 includes:
s204 a: constructing an arch dam finite element model based on the undamaged arch dam (namely updating the arch dam finite element model);
specifically comprises
Acquiring a micro vibration video of the top of the undamaged arch dam under the action of a drainage load;
decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video;
obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information;
establishing an initial arch dam finite element model according to the arch dam design data;
and taking the arch dam natural frequency and the arch dam vibration mode information as a correction target of the initial arch dam finite element model, determining a specific response surface function form according to sample data obtained by response surface test, and updating the parameters of the initial arch dam finite element model to obtain the arch dam finite element model.
S204 b: establishing an arch dam natural frequency database and a vibration type dynamic damage database based on the arch dam finite element model;
specifically comprises
Establishing arch dam finite element models in different damage states according to the arch dam finite element models;
and establishing an arch dam natural frequency damage database and a vibration type dynamic damage database according to finite element modal analysis based on the arch dam finite element models in different damage states.
Wherein, the different damage states include different positions, different ranges and different degrees of damage states.
S204 c: and establishing a damage identification model based on the damage database.
Specifically comprises
Establishing an arch dam damage range identification model and an arch dam damage degree identification model by using a support vector regression machine according to the arch dam natural frequency damage database;
and establishing an arch dam damage position identification model by adopting a convolutional neural network according to the vibration type dynamic damage database.
Fig. 3 is a schematic diagram of an underwater damage identification device/terminal device for an arch dam according to an embodiment of the present application. As shown in fig. 3, the apparatus/terminal device 6 for identifying an underwater damage to an arch dam of this embodiment includes: a processor 60, a memory 61, and a computer program 62, such as an arch dam underwater crash identification program, stored in the memory 61 and operable on the processor 60. The processor 60, when executing the computer program 62, implements the steps of the above-mentioned various embodiments of the method for identifying an underwater damage to an arch dam, such as the steps 101 to 104 shown in fig. 1. Alternatively, the processor 60 implements the functions of the modules/units in the above-described device embodiments when executing the computer program 62.
Illustratively, the computer program 62 may be partitioned into one or more modules/units that are stored in the memory 61 and executed by the processor 60 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution process of the computer program 62 in the arch dam underwater damage identification apparatus/terminal device 6. For example, the computer program 62 may be divided into a synchronization module, a summarization module, an acquisition module, and a return module (a module in a virtual device), and each module specifically functions as follows:
the arch dam underwater damage recognition device/terminal device 6 may be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The arch dam underwater damage identification device/terminal equipment can include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will appreciate that fig. 3 is merely an example of the identification device/terminal device 6 for the underwater damage of the arch dam, and does not constitute a limitation to the identification device/terminal device 6 for the underwater damage of the arch dam, and may include more or less components than those shown, or combine some components, or different components, for example, the identification device/terminal device for the underwater damage of the arch dam may further include an input/output device, a network access device, a bus, etc.
The Processor 60 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 61 may be an internal storage unit of the arch dam underwater damage identification device/terminal device 6, such as a hard disk or a memory of the arch dam underwater damage identification device/terminal device 6. The memory 61 may also be an external storage device of the arch dam underwater damage identification apparatus/terminal device 6, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, which is equipped on the arch dam underwater damage identification apparatus/terminal device 6. Further, the memory 61 may also include both an internal storage unit and an external storage device of the arch dam underwater damage recognition apparatus/terminal device 6. The memory 61 is used for storing the computer program and other programs and data required by the arch dam underwater damage identification device/terminal equipment. The memory 61 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. An arch dam underwater damage identification method is characterized in that: the method comprises the following steps
Acquiring a micro vibration video of the top of the damaged arch dam under the action of a drainage load;
decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video;
obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information;
and importing the information of the natural frequency and the vibration mode of the arch dam into a pre-constructed damage identification model to obtain the underwater damage range, the damage degree and the damage position information of the arch dam.
2. The arch dam underwater damage identification method according to claim 1, wherein: the method for constructing the damage identification model comprises the following steps
Constructing an arch dam finite element model based on the undamaged arch dam;
establishing an arch dam natural frequency database and a vibration type dynamic damage database based on the arch dam finite element model;
and establishing a damage identification model based on the damage database.
3. The arch dam underwater damage identification method according to claim 2, wherein: the arch dam finite element model building based on the undamaged arch dam comprises the following steps:
acquiring a micro vibration video of the top of the undamaged arch dam under the action of a drainage load;
decomposing the dam crest vibration video obtained by shooting to obtain local phase information of the video;
obtaining the natural frequency and vibration mode information of the arch dam according to the local phase information;
establishing an initial arch dam finite element model according to the arch dam design data;
and taking the arch dam natural frequency and the arch dam vibration mode information as a correction target of the initial arch dam finite element model, determining a specific response surface function form according to sample data obtained by response surface test, and updating the parameters of the initial arch dam finite element model to obtain the arch dam finite element model.
4. The arch dam underwater damage identification method according to claim 2, wherein: the database for establishing the arch dam natural frequency and vibration type dynamic damage based on the arch dam finite element model comprises
Establishing arch dam finite element models in different damage states according to the arch dam finite element models;
and establishing an arch dam natural frequency damage database and a vibration type dynamic damage database according to finite element modal analysis based on the arch dam finite element models in different damage states.
5. The arch dam underwater damage identification method as claimed in claim 4, wherein: the different damage states include different locations and/or different ranges and/or different degrees of damage states.
6. The arch dam underwater damage identification method according to claim 2, wherein: establishing a damage identification model based on the damage database comprises
Establishing an arch dam damage range identification model and an arch dam damage degree identification model by adopting a machine learning algorithm according to the arch dam natural frequency damage database;
and establishing an arch dam damage position identification model by adopting a machine learning algorithm according to the vibration type dynamic damage database.
7. The arch dam underwater damage identification method according to claim 1, wherein: and the dam crest vibration video is acquired by an unmanned aerial vehicle.
8. The arch dam underwater damage identification method as claimed in claim 7, wherein: the acquisition process comprises
Controlling the unmanned aerial vehicle to fly above the top of the arch dam, and adjusting the height of the unmanned aerial vehicle and the focal length of the camera until the whole dam crest area is within the visual field range of the camera and the contour of the dam crest is clear and visible;
and adjusting the shooting angle of the camera, and vertically shooting the micro vibration of the dam top under the action of the drainage load downwards.
9. An arch dam underwater damage identification device/terminal apparatus comprising a memory, a processor and a computer program stored in said memory and operable on said processor, characterized in that: the processor, when executing the computer program, realizes the steps of the method according to any of claims 1 to 8.
10. A computer-readable storage medium storing a computer program, characterized in that: the computer program when executed by a processor implementing the steps of the method according to any one of claims 1 to 8.
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| CN115994465A (en) * | 2022-12-14 | 2023-04-21 | 中国人民解放军军事科学院国防工程研究院工程防护研究所 | Method for evaluating damage effect kNN of unexpected explosion air shock wave to bridge |
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