CN113343554B - 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. The method comprises the steps of obtaining a tiny vibration video of a dam top of a damaged arch dam under the action of a drainage load; decomposing the shot dam crest vibration video to obtain local phase information of the video; obtaining natural frequency of the arch dam and vibration mode information of the arch dam according to the local phase information; the natural frequency of the arch dam and the vibration type information of the arch dam are imported 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. The dynamic characteristics of the arch dam can be obtained through the tiny vibration video of the dam top under the action of the leakage load of the arch dam, an arch dam refined model and a dynamic damage database are built through the undamaged arch dam data, an underwater damage identification model of the arch dam is built by combining machine learning, and finally, underwater damage identification of the damaged arch dam including the underwater damage range, damage degree and damage position information of the arch dam is realized, so that the accuracy is high.
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
The arch dam may be damaged underwater due to various factors. The method has the advantages of fast judging the underwater damaged part and determining the damaged range, has important guiding significance for emergency rescue and quick repair under the emergency state of the arch dam, and has important significance for guaranteeing the whole stability of the structure and the personal and property safety of downstream people.
The underwater damage identification of the arch dam can be divided into local damage identification and global damage identification, and the common technology for the local damage identification comprises the following steps:
(1) Local area fixed inspection, such as X-ray, acoustic emission, underwater robots and the like, is complex in underwater operation, and consumes time and labor;
(2) Sensors such as stress strain and temperature are pre-embedded for monitoring, and the sensors can only monitor explosion damage of nearby areas, and meanwhile, the damage range is difficult to determine.
For the above reasons, a method is needed that is easy to implement and that can accurately identify a lesion.
Disclosure of Invention
The invention aims at overcoming the defects of the prior art, and provides an underwater damage identification method, terminal equipment and storage medium for an arch dam, which are easy to realize and can accurately identify damage.
The invention relates to an underwater damage identification method for an arch dam, which comprises the following steps: the method comprises the steps of obtaining a tiny vibration video of the dam top of a damaged arch dam under the action of a drainage load;
decomposing the shot dam crest vibration video to obtain local phase information of the video;
obtaining natural frequency of the arch dam and vibration mode information of the arch dam according to the local phase information;
and importing the natural frequency of the arch dam and the vibration mode information 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 construction method of the damage identification model comprises the following steps of
Constructing an arch dam finite element model based on the undamaged arch dam;
establishing an arch dam natural frequency database and a vibration mode power damage database based on the arch dam finite element model;
and establishing a damage identification model based on the damage database.
Preferably, the constructing the arch dam finite element model based on the undamaged arch dam includes:
acquiring a tiny vibration video of the dam top of the undamaged arch dam under the action of a drainage load;
decomposing the shot dam crest vibration video to obtain local phase information of the video;
obtaining natural frequency of the arch dam 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 natural frequency of the arch dam and the vibration mode information of the arch dam as correction targets 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 parameters of the initial arch dam finite element model to obtain the arch dam finite element model.
Preferably, the building of the arch dam natural frequency and vibration dynamic damage database based on the arch dam finite element model comprises
Establishing arch dam finite element models under different damage states according to the arch dam finite element models;
based on finite element models of arch dams in different damage states, a natural frequency damage database and a vibration mode dynamic damage database of the arch dams are established according to finite element modal analysis.
Preferably, the different destructive states comprise different positions and/or different ranges and/or different degrees of destructive states.
Preferably, establishing the damage identification model based on the damage database comprises
According to the arch dam natural frequency damage database, a machine learning algorithm is adopted to establish an arch dam damage range identification model and an arch dam damage degree identification model;
and establishing an arch dam damage position identification model by adopting a machine learning algorithm according to the vibration mode power damage database.
Preferably, the dam crest vibration video is acquired through an unmanned aerial vehicle.
Preferably, 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 in the camera visual field range, and the dam crest outline is clearly visible;
and adjusting the shooting angle of the camera, and shooting tiny vibration of the dam crest under the action of the drainage load vertically downwards.
The invention also provides a terminal device comprising a memory, a processor and a computer program stored in the memory and operable on the processor, the processor implementing the steps of the above method when executing the computer program.
The invention also provides a storage medium storing a computer program which when executed by a processor implements the steps of the above method.
The beneficial effects of the invention are as follows:
1. the dynamic characteristics of the arch dam can be obtained through the tiny vibration video of the dam top under the action of the leakage load of the arch dam, an arch dam refined model and a dynamic damage database are built through the undamaged arch dam data, an underwater damage identification model of the arch dam is built by combining machine learning, and finally, underwater damage identification of the damaged arch dam including the underwater damage range, damage degree and damage position information of the arch dam is realized, so that the accuracy is high.
2. By adopting unmanned aerial vehicle non-contact measurement, the full-field motion information of the arch dam can be obtained so as to extract more accurate natural frequency and vibration mode, thereby meeting the requirements of finite element model updating and damage identification.
3. The method has the advantages that the construction of the damage identification model is realized by utilizing the acquired vibration video and combining a machine learning algorithm, so that the underwater damage identification of the damaged arch dam is realized, a contact sensor is not required to be arranged, the operation is more convenient, efficient and quick, a large amount of manpower, material resources and financial resources can be saved, and the damage can be realized more easily and accurately.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention;
FIG. 2 is a schematic flow chart of an embodiment of the present invention;
fig. 3 is a schematic view of the submerged damage identification device/terminal equipment of the arch dam of the present invention.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved by the present application more clear, 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 for purposes of illustration only and are not intended to limit the present application.
It should be noted that the terms "first," "second," and "second" are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implying a number of technical features being indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
As shown in fig. 1, the flow of the method is as follows:
s101: acquiring a tiny vibration video of the dam top of the damaged arch dam under the action of a drainage load;
s102: decomposing the shot dam crest vibration video to obtain local phase information of the video; specifically, shot dam crest vibration videos are led into a computer to be processed, a complex-domain steerable pyramid filter bank is adopted, and arch dam vibration videos are decomposed to obtain local spatial amplitude and local phase information of the videos.
S103: obtaining natural frequency of the arch dam and vibration mode information of the arch dam according to the local phase information; converting the obtained local phase information of the arch dam into a frequency domain, and identifying the natural frequency of the arch dam; and further filtering, amplifying and reconstructing the phase signals to finally obtain the arch dam vibration mode information.
S104: and importing the natural frequency of the arch dam and the vibration mode information 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.
The damage identification model is pre-constructed according to an undamaged arch dam, and the process comprises the following steps:
s201: acquiring a tiny vibration video of the dam top of the damaged arch dam under the action of a drainage load;
s202: decomposing the shot dam crest vibration video to obtain local phase information of the video; specifically, shot dam crest vibration videos are led into a computer to be processed, a complex-domain steerable pyramid filter bank is adopted, and arch dam vibration videos are decomposed to obtain local spatial amplitude and local phase information of the videos.
S203: obtaining natural frequency of the arch dam and vibration mode information of the arch dam according to the local phase information; converting the obtained local phase information of the arch dam into a frequency domain, and identifying the natural frequency of the arch dam; and further filtering, amplifying and reconstructing the phase signals to finally obtain the arch dam vibration mode information.
S204: and constructing a damage identification model.
Wherein S204 further comprises:
s204a: 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 tiny vibration video of the dam top of the undamaged arch dam under the action of a drainage load;
decomposing the shot dam crest vibration video to obtain local phase information of the video;
obtaining natural frequency of the arch dam 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 natural frequency of the arch dam and the vibration mode information of the arch dam as correction targets 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 parameters of the initial arch dam finite element model to obtain the arch dam finite element model.
S204b: establishing an arch dam natural frequency database and a vibration mode power damage database based on the arch dam finite element model;
specifically comprises
Establishing arch dam finite element models under different damage states according to the arch dam finite element models;
based on finite element models of arch dams in different damage states, a natural frequency damage database and a vibration mode dynamic damage database of the arch dams are established according to finite element modal analysis.
S204c: and establishing a damage identification model based on the damage database.
Specifically comprises
According to the arch dam natural frequency damage database, a machine learning algorithm is adopted to establish an arch dam damage range identification model and an arch dam damage degree identification model;
and establishing an arch dam damage position identification model by adopting a machine learning algorithm according to the vibration mode power damage database.
Example 1
In the embodiment, the method is adopted to perform damage identification on a parabolic concrete double arch dam, a dam top elevation 640.5m, a river bed building base elevation 410m, a maximum dam height 230.5m, a dam top arc length 552.55m and a thickness-height ratio of 0.216. The video is acquired through an unmanned plane, and the machine learning algorithm comprises a support vector regression machine and a convolutional neural network, and the specific flow is shown in fig. 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 in the camera visual field range, and the dam crest outline is clearly visible;
adjusting the shooting angle of a camera, and shooting tiny vibration of the dam crest under the action of a drainage load vertically downwards; the unmanned aerial vehicle is a Xinjiang Mavic 2Pro unmanned aerial vehicle with the shooting capability of 4K with the color depth of 10 bits, and flies to the position right above the dam crest through a positioning system.
S102: decomposing the shot dam crest vibration video to obtain local phase information of the video; specifically, shot dam crest vibration videos are led into a computer to be processed, a complex-domain steerable pyramid filter bank is adopted, and arch dam vibration videos are decomposed to obtain local spatial amplitude and local phase information of the videos.
S103: obtaining natural frequency of the arch dam and vibration mode information of the arch dam according to the local phase information; converting the obtained local phase information of the arch dam into a frequency domain, and identifying the natural frequency of the arch dam; and further filtering, amplifying and reconstructing the phase signals to finally obtain the arch dam vibration mode information.
S104: and importing the natural frequency of the arch dam and the vibration mode information 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.
The damage identification model is pre-constructed according to an undamaged arch dam, and the process comprises the following steps:
s201: acquiring a tiny vibration video of the dam top of the damaged arch dam under the action of a drainage load;
s202: decomposing the shot dam crest vibration video to obtain local phase information of the video; specifically, shot dam crest vibration videos are led into a computer to be processed, a complex-domain steerable pyramid filter bank is adopted, and arch dam vibration videos are decomposed to obtain local spatial amplitude and local phase information of the videos.
S203: obtaining natural frequency of the arch dam and vibration mode information of the arch dam according to the local phase information; converting the obtained local phase information of the arch dam into a frequency domain, and identifying the natural frequency of the arch dam; and further filtering, amplifying and reconstructing the phase signals to finally obtain the arch dam vibration mode information.
S204: and constructing a damage identification model.
Wherein S204 further comprises:
s204a: 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 tiny vibration video of the dam top of the undamaged arch dam under the action of a drainage load;
decomposing the shot dam crest vibration video to obtain local phase information of the video;
obtaining natural frequency of the arch dam 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 natural frequency of the arch dam and the vibration mode information of the arch dam as correction targets 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 parameters of the initial arch dam finite element model to obtain the arch dam finite element model.
S204b: establishing an arch dam natural frequency database and a vibration mode power damage database based on the arch dam finite element model;
specifically comprises
Establishing arch dam finite element models under different damage states according to the arch dam finite element models;
based on finite element models of arch dams in different damage states, a natural frequency damage database and a vibration mode dynamic damage database of the arch dams are established according to finite element modal analysis.
Wherein, the different damage states comprise different positions, different ranges and different degrees of damage states.
S204c: and establishing a damage identification model based on the damage database.
Specifically comprises
According to the arch dam natural frequency damage database, a support vector regression machine is adopted to establish an arch dam damage range identification model and an arch dam damage degree identification model;
and establishing an arch dam damage position identification model by adopting a convolutional neural network according to the vibration mode dynamic damage database.
Fig. 3 is a schematic diagram of an apparatus for identifying underwater damage to an arch dam/terminal device according to an embodiment of the present application. As shown in fig. 3, the arch dam underwater damage recognition device/terminal equipment 6 of this embodiment includes: a processor 60, a memory 61, and a computer program 62 stored in the memory 61 and executable on the processor 60, such as a arch dam underwater damage identification program. The processor 60, when executing the computer program 62, performs the steps of the various embodiments of the method for identifying submerged arc dams described above, such as steps 101 through 104 shown in fig. 1. Alternatively, the processor 60, when executing the computer program 62, performs the functions of the modules/units of the apparatus embodiments described above.
By way of example, 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 complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the computer program 62 in the arch dam underwater damage identification device/terminal device 6. For example, the computer program 62 may be divided into a synchronization module, a summary module, an acquisition module, and a return module (modules in the virtual device), each of which specifically functions as follows:
the arch dam underwater damage recognition device/terminal equipment 6 can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The arch dam submerged damage identification device/terminal may include, but is not limited to, a processor 60, a memory 61. It will be appreciated by those skilled in the art that fig. 3 is merely an example of the arch dam submerged damage identification apparatus/terminal device 6 and is not intended to be limiting of the arch dam submerged damage identification apparatus/terminal device 6, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the arch dam submerged damage identification apparatus/terminal device may also include input and output devices, network access devices, buses, etc.
The processor 60 may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 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 device/terminal device 6, for example, a plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash memory Card (Flash Card) or the like provided on the arch dam underwater damage identification device/terminal device 6. Further, the memory 61 may also comprise both an internal memory unit and an external memory device of the arch dam underwater damage identification device/terminal device 6. The memory 61 is used to store the computer program and other programs and data required for the arch dam underwater damage identification device/terminal equipment. The memory 61 may also be used for temporarily storing 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-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a 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 process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
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 solution. 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 manners. For example, the apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each method embodiment described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; 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 scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (6)
1. An arch dam underwater damage identification method is characterized in that: the method comprises
Acquiring a tiny vibration video of the dam top of the damaged arch dam under the action of a drainage load;
decomposing the shot dam crest vibration video to obtain local phase information of the video;
obtaining natural frequency of the arch dam and vibration mode information of the arch dam according to the local phase information;
importing the natural frequency of the arch dam and the vibration mode information 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;
the damage identification model is constructed by utilizing the acquired vibration video and combining a machine learning algorithm, and the construction method comprises the following steps of
Constructing an arch dam finite element model based on the undamaged arch dam;
establishing an arch dam natural frequency database and a vibration mode power damage database based on the arch dam finite element model;
establishing a damage identification model based on the damage database;
the constructing the arch dam finite element model based on the undamaged arch dam comprises the following steps:
acquiring a tiny vibration video of the dam top of the undamaged arch dam under the action of a drainage load;
decomposing the shot dam crest vibration video to obtain local phase information of the video;
obtaining natural frequency of the arch dam 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;
the natural frequency of the arch dam and the vibration mode information of the arch dam are used as correction targets of the initial arch dam finite element model, a specific response surface function form is determined according to sample data obtained through response surface test, and parameters of the initial arch dam finite element model are updated to obtain the arch dam finite element model;
the method for establishing the arch dam natural frequency and vibration mode dynamic damage database based on the arch dam finite element model comprises the following steps of
Establishing arch dam finite element models under different damage states according to the arch dam finite element models;
based on finite element models of arch dams in different damage states, establishing a natural frequency damage database and a vibration type dynamic damage database of the arch dams according to finite element modal analysis;
the creating of the damage identification model based on the damage database comprises
According to the arch dam natural frequency damage database, a machine learning algorithm is adopted to establish an arch dam damage range identification model and an arch dam damage degree identification model;
and establishing an arch dam damage position identification model by adopting a machine learning algorithm according to the vibration mode power damage database.
2. The method for identifying underwater damage to an arch dam of claim 1, wherein: the different destructive states comprise different positions and/or different ranges and/or different degrees of destructive states.
3. The method for identifying underwater damage to an arch dam of claim 1, wherein: and the dam crest vibration video is acquired through the unmanned aerial vehicle.
4. A method of identifying an underwater failure of an arch dam as claimed in claim 3, wherein: the acquisition 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 in the camera visual field range, and the dam crest outline is clearly visible;
and adjusting the shooting angle of the camera, and shooting tiny vibration of the dam crest under the action of the drainage load vertically downwards.
5. An arch dam underwater damage identification device/terminal device 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, implements the steps of the method according to any one of claims 1 to 4.
6. A computer-readable storage medium storing a computer program, characterized in that: the computer program implementing the steps of the method according to any one of claims 1 to 4 when executed by a processor.
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