CN112924543A - Prediction method and system for safe damage state of steel structural member - Google Patents
Prediction method and system for safe damage state of steel structural member Download PDFInfo
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Abstract
The invention provides a method and a system for predicting the safe damage state of a steel structural member, wherein the method for predicting the safe damage state of the steel structural member comprises the following steps: acquiring vibration mode characteristic data of a steel structural part; based on a preset safety damage state classification model, generating corresponding steel structural part damage degree data according to the steel structural part vibration modal characteristic data; the classification model for the safe damage state is based on an artificial intelligence technology, a large number of different steel structure lamp poles are led into the system under different damage or corrosion states through self vibration mode characteristics, an intelligent classification mode for the safe damage state of the lamp poles is established through artificial intelligence learning training, and when new data is led in, the lamp pole safe damage state can be evaluated and judged quickly.
Description
Technical Field
The invention relates to the technical field of steel structural member detection, in particular to a method and a system for predicting a safety damage state of a steel structural member.
Background
With the continuous development of city scale in China, the steel road lamp pole becomes visible everywhere, and the functional characteristics borne by the lamp pole are gradually increased, so that the lamp pole has great influence on traffic safety, people's life, social security and city appearance of modern cities. In recent years, a plurality of street lamp pole dumping events of the street lamp poles in Beijing city have appeared, and how to effectively ensure the safe use of the street lamp poles in Beijing city and the accessory facilities and reduce the probability of the street lamp pole dumping accidents is a project problem to be solved urgently.
The road steel structure lamp post has the characteristics of small size, large quantity and wide distribution range, and the traditional detection technical means has low efficiency, needs to occupy and coordinate a large amount of manpower and material resources and is not beneficial to realizing the rapid detection and evaluation of the lamp post; at present, aiming at the detection work of steel structure lamp poles of urban roads, the detection work is mainly to judge whether the steel structure lamp pole meets the use requirement or not by acquiring the index parameters of the steel structure lamp pole, such as the morphological size characteristics, the material structure strength and the appearance damage condition, on site and matching with finite element modeling calculation of the steel structure lamp pole. The development of the detection and evaluation method generally needs multi-unit coordination, wherein detection units, street lamp management units, road management units, traffic management units and the like are involved, the handling of relevant procedures is complicated, meanwhile, detection personnel also need to ascend during field detection, lift car matching is needed, traffic is inevitably obstructed, normal passing of people is affected, the detection efficiency is low, only about 4-8 steel structure lamp poles can be detected in one day on average, and the requirement for large-scale quick detection of the steel structure lamp poles cannot be met.
Disclosure of Invention
In order to solve at least one of the above problems, a first aspect of the present invention provides a method for predicting a safe damage state of a steel structural member, including:
acquiring vibration mode characteristic data of a steel structural part;
based on a preset safety damage state classification model, generating corresponding steel structural part damage degree data according to the steel structural part vibration modal characteristic data;
the safety damage state classification model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data.
In a preferred embodiment, the acquiring of the vibration mode characteristic data of the steel structural member includes:
receiving vibration data of the steel structural part;
and carrying out signal processing on the vibration data to obtain the vibration modal characteristic data of the steel structural member.
In a preferred embodiment, the signal processing of the vibration data includes:
the vibration data is signal processed according to at least one of a fourier transform, a short-time fourier transform, and a wavelet analysis method.
In a preferred embodiment, the signal processing comprises: filtering (noise reduction), waveform separation, spectral analysis, and modal analysis.
The second aspect of the present invention provides a system for predicting a safe damage state of a steel structural member, including: a signal exciting device, a signal collecting device and a signal processing device,
the signal excitation device is used for exciting the steel structural part to generate vibration;
the signal acquisition device is used for receiving vibration signals of the steel structural part;
the signal processing device generates corresponding steel structural member damage degree data according to the steel structural member vibration modal characteristic data based on a preset safety damage state classification grading model; wherein,
the safety damage state classification grading model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data.
In a preferred embodiment, the signal excitation means comprises: a force hammer and a trigger fixed in conjunction with the force hammer, the trigger coupled with the signal processing device.
In a preferred embodiment, the signal acquisition device comprises: a detector coupled to the signal processing device.
In a preferred embodiment, the signal acquisition device further comprises: and the magnetic suction head is fixedly combined with the detector and is used for fixing the detector on a steel structural member.
A third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for predicting the safe damage state of the steel structural member when executing the program.
A fourth aspect of the present invention provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method for predicting a safe damage state of a steel structural member as set forth in any one of the above.
The invention has the advantages of
The invention provides a method and a system for predicting the safe damage state of a steel structural member, wherein the method for predicting the safe damage state of the steel structural member comprises the following steps: acquiring vibration mode characteristic data of a steel structural part; based on a preset safety damage state classification model, generating corresponding steel structural part damage degree data according to the steel structural part vibration modal characteristic data; the safety damage state classification grading model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data; the classification and classification model for the safe damage state is based on an artificial intelligence technology, self vibration modal characteristics of a large number of different steel structure lamp poles in different damage or corrosion states are led into the system, an intelligent classification and classification evaluation mode for the safe damage state of the lamp poles is established through artificial intelligence learning training, and when new data are led in, evaluation and judgment can be rapidly carried out on the safe damage state of the lamp poles; the method has the advantages of being low in detection cost, short in time consumption and simple in operation of the field lamp pole, being capable of achieving batch evaluation of the safety of the lamp pole structure, and providing a new method for rapid detection and evaluation work of the steel structure lamp pole in the future.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic flow chart of a method for predicting a safe damage state of a steel structural member in an embodiment of the invention;
FIG. 2 is a schematic structural diagram of a system for predicting a safe damage state of a steel structural member according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a computer electronic device suitable for use in implementing embodiments of the present invention.
Description of the drawings: 1. a rubber hammer; 2. a trigger; 3. a magnetic suction head; 4. a detector; 5. a host.
Detailed Description
The technical solutions in 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 only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
At present, aiming at the detection work of steel structure lamp poles of urban roads, the detection work is mainly to judge whether the steel structure lamp pole meets the use requirement or not by acquiring the index parameters of the steel structure lamp pole, such as the morphological size characteristics, the material structure strength and the appearance damage condition, on site and matching with finite element modeling calculation of the steel structure lamp pole. The development of the detection and evaluation method generally requires coordination of multiple units, including detection units, street lamp management units, road management units, traffic management units and the like, and the handling of related procedures is complicated. Meanwhile, in field detection, detection personnel still need to ascend, lift trucks are needed to cooperate, traffic is inevitably obstructed, normal passing of people is affected, the detection efficiency is low, only about 4-8 steel structure lamp poles can be detected in one day on average, and the requirement for large-scale quick detection of steel structure lamp poles cannot be met; according to the method, the vibration modal characteristics of the steel structure lamp post are obtained as an entry point, and the safety and the use performance of the steel structure lamp post are analyzed, judged and evaluated by obtaining the vibration modal characteristics corresponding to different damage degrees of the steel structure lamp post.
Based on this, referring to fig. 1, a first aspect of the present invention provides a method for predicting a safe damage state of a steel structural member, where the method for predicting the safe damage state of the steel structural member includes the following steps:
s1: acquiring vibration mode characteristic data of a steel structural part;
specifically, the vibration mode characteristics include: in a specific application scene, for example, the upper computer directly obtains the vibration modal characteristic data of the steel structural member in the server in a wired or wireless transmission mode, the mode is a direct obtaining mode, when the upper computer obtains original data of the vibration of the steel structural member in a wired or wireless transmission mode, the original data is processed by software in the upper computer to obtain the vibration modal characteristic data of the steel structural member, the mode is an indirect obtaining mode, and the situation needing to be explained is that the vibration modal characteristic data of the steel structural member is directly obtained or indirectly obtained.
S2: based on a preset safety damage state classification model, generating corresponding steel structural part damage degree data according to the steel structural part vibration modal characteristic data; the safety damage state classification model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data.
The classification and classification model for the safe damage state is based on an artificial intelligence technology, self vibration modal characteristics of a large number of different steel structure lamp poles in different damage or corrosion states are led into the system, an intelligent classification and classification evaluation mode for the safe damage state of the lamp poles is established through artificial intelligence learning training, and when new data are led in, evaluation and judgment can be rapidly carried out on the safe damage state of the lamp poles; the method has the advantages of being low in detection cost, short in time consumption and simple in operation of the field lamp pole, being capable of achieving batch evaluation of the safety of the lamp pole structure, and providing a new method for rapid detection and evaluation work of the steel structure lamp pole in the future.
In some embodiments, obtaining the vibrational modal characterization data of the steel structural member comprises:
receiving vibration data of the steel structural part;
and carrying out signal processing on the vibration data to obtain the vibration modal characteristic data of the steel structural member.
Specifically, the steel structure rod is knocked through the exciting device to vibrate, then a vibration signal of the steel structure rod is received through the signal collecting device, and the collected vibration data signal is processed through the signal processing software to obtain a vibration modal characteristic data parameter of the steel structure.
In some embodiments, signal processing the vibration data comprises: the vibration data is signal processed according to at least one of a fourier transform, a short-time fourier transform, and a wavelet analysis method.
For example, in signal processing, it is quite common that the signal contains noise, and the presence of noise increases the complexity of identifying discontinuities in the signal; the fourier transform is to integrate the original signal and the orthogonal trigonometric function base on infinity, and the larger the obtained integral value is, the more the triangular signal containing the frequency is; the principle of Wavelet transformation is similar to that of Wavelet transformation, except that an infinite-length trigonometric function base is transformed into a finite-length Wavelet base capable of attenuating (Wavelet-Wavelet, as the name suggests, "Wavelet" is a small waveform, so-called "small" means that the Wavelet is attenuating, and so-called "wave" means its volatility, and an oscillation form with alternate positive and negative amplitudes), the Wavelet transformation has two variables, namely scale and translation, and the scale controls the expansion and contraction of the Wavelet function, corresponding to the frequency; the amount of translation controls the translation of the wavelet function, corresponding to time. Therefore, not only the frequency information but also the specific position on the time domain can be known, and therefore, the Fourier transform can only obtain one frequency spectrum, and the wavelet transform can obtain one time frequency spectrum.
In a specific application scenario, the results of wavelet transform and fourier transform in gamma spectrum denoising processing are shown in table 1 below
| Noise reduction method | Energy ratio of noise reduction spectrum to original spectrum | Standard deviation of noise reduction spectrum and original spectrum |
| Fourier transform method | 0.9770 | 298.8176 |
| Wavelet transform method | 0.9977 | 43.2617 |
As can be seen from the data in table 1, when the wavelet transform is used for noise suppression, not only the energy ratio (0.9977) of the noise reduction result is higher than that (0.9770) of the fourier transform filter, but also a higher degree of similarity with the original energy spectrum is ensured; from the standard deviation of the noise reduction spectrum and the original spectrum, it can be seen that: in the wavelet transform, the standard deviation of the filtering result based on the Minimax threshold value and the original energy spectrum is 43.261, which is much smaller than that of the result 298.8176 of the fourier transform, and this shows that the noise reduction method based on the wavelet transform has higher precision compared with the traditional fourier transform method.
It should be noted that, when the vibration data is subjected to signal processing, a person skilled in the art may select one or more of fourier transform, short-time fourier transform, wavelet analysis, and the like to combine them according to actual situations, which is not limited by the present invention.
In some embodiments, the signal processing comprises: filtering (noise reduction), waveform separation, spectral analysis, and modal analysis.
The method for predicting the safe damage state of the steel structural member according to the present invention will be described with reference to specific examples.
The safety detection and evaluation method for the steel structure lamp post comprises the steps that firstly, a vibration signal of the steel structure lamp post is collected through collection equipment, the collection equipment consists of an artificial vibration exciter (exciting the lamp post to generate vibration), a magnetic detector (capable of being adsorbed on the lamp post) and a visual host (used for recording, storing, checking, processing and sending a vibration data signal to a receiving terminal, has a Beidou positioning function and is convenient for classification and arrangement of data), and the collection equipment is connected with the visual host through a signal transmission line; the acquisition processing software installed in the host can set related acquisition parameters, has the functions of recording, storing, checking and analyzing and processing vibration signals, can completely record original vibration data information (such as parameters of vibration waveform, frequency, duration, amplitude and the like) of the steel structure lamp pole, and simultaneously obtains relatively accurate vibration modal parameter data of the steel structure lamp pole based on various signal processing means such as filtering (noise reduction), waveform separation transformation, modal parameter identification and the like so as to provide basic data for subsequently judging the safety use performance of the steel structure lamp pole; then, an artificial intelligence technology is used as a basic neural network model (a safety damage state classification model), self vibration modal characteristics of a large number of different steel structure lamp poles in different damage or corrosion states are led into the system, a classification evaluation mode for intelligently evaluating the safety damage state of the lamp poles is established through artificial intelligence learning training, and when new data are led in, the system can quickly evaluate and judge the safety damage state of the lamp poles.
The invention relates to a prediction method of a safe damage state of a steel structural part, which takes the vibration modal characteristics of a steel structural lamp post as an entry point and analyzes, judges and evaluates the safety and the service performance of the steel structural lamp post by detecting the vibration modal characteristics corresponding to different damage degrees of the steel structural lamp post; the method has the advantages that: only 1-2 detection personnel are needed for field detection, generally no climbing operation is needed, normal passing of roads is not affected, the detection efficiency is high, and rapid detection of large-scale steel structure lamp poles can be realized; meanwhile, the invention abandons the characteristics of complex workload and low efficiency in the traditional lamp pole detection activity, avoids the influence on road traffic, and reduces the safety risk of detection personnel.
The second aspect of the present invention provides a system for predicting a safe damage state of a steel structural member, including: a signal exciting device, a signal collecting device and a signal processing device,
the signal excitation device is used for exciting the steel structural part to generate vibration;
the signal acquisition device is used for receiving vibration signals of the steel structural part;
the signal processing device generates corresponding steel structural member damage degree data according to the steel structural member vibration modal characteristic data based on a preset safety damage state classification grading model; wherein,
the safety damage state classification grading model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data.
The prediction system for the safe damage state of the steel structural part is based on an artificial intelligence technology, the self vibration modal characteristics of a large number of different steel structural lamp poles in different damage or corrosion states are led into the system, a classification grading evaluation mode for intelligently evaluating the safe damage state of the lamp poles is established through artificial intelligence learning training, and when new data are led in, the safe damage state of the lamp poles can be rapidly evaluated and judged.
Further, the signal excitation device includes: a force hammer and a trigger 2 fixed in conjunction with the force hammer, the trigger 2 being coupled to the signal processing device.
Further, the signal acquisition device comprises: a detector 4, said detector 4 being coupled to said signal processing means.
Further, the signal acquisition device further comprises: and the magnetic suction head 3 is fixedly combined with the wave detector 4, and the magnetic suction head 3 is used for fixing the wave detector 4 on a steel structural member.
Referring to fig. 2, a system for predicting a safe damage state of a steel structural member according to the present invention will be described with reference to an embodiment.
The safety detection system of the steel structure lamp post of the urban road mainly comprises a data acquisition and processing system and a safety evaluation and analysis system, wherein the data acquisition and processing system comprises acquisition equipment and acquisition and processing software, the acquisition equipment consists of an artificial vibration exciter, a magnetic detector 4 and a visual host 5, the acquisition equipment and the magnetic detector are connected through a signal transmission line, the artificial vibration exciter consists of a rubber hammer 1 and a trigger 2, and the rubber hammer 1 is used for exciting the lamp post to vibrate; the trigger 2 is used for triggering the acquisition system to start the acquisition work of the vibration signal; the magnetic detector 4 is used for receiving a vibration signal of the lamp post, and the magnetic detector 4 is fixedly combined with the corresponding position of the steel structure lamp post through the magnetic suction head 3; the visual host 5 is used for recording, storing, checking, processing and sending vibration data signals to the receiving terminal, has the Beidou positioning function and is convenient for classification and arrangement of data; the acquisition processing software is installed in a host 5 of the acquisition system, can set related acquisition parameters, has the functions of recording, storing, checking and analyzing and processing vibration signals, can completely record original vibration data information (such as parameters of vibration waveform, frequency, holding time, amplitude and the like) of the steel structure lamp pole, and simultaneously obtains relatively accurate vibration modal parameter data of the steel structure lamp pole based on various signal processing means such as filtering (noise reduction), waveform separation transformation, modal parameter identification and the like so as to provide basic data for subsequently judging the safety use performance of the steel structure lamp pole; the safety assessment analysis system is based on an artificial intelligence technology, a large number of different steel structure lamp poles are led into the system in self vibration mode characteristics under different damage or corrosion states, and a classification grading evaluation mode for intelligently evaluating the safety damage states of the lamp poles is established through artificial intelligence learning training. When new data are introduced, the system can quickly evaluate and judge the safety damage state of the lamp pole.
The prediction system for the safe damage state of the steel structural part takes the vibration modal characteristics of the steel structural lamp post as an entry point, and analyzes, judges and evaluates the safety and the service performance of the steel structural lamp post by detecting the vibration modal characteristics corresponding to different damage degrees of the steel structural lamp post; the system has the advantages that: only 1-2 detection personnel are needed for field detection, generally no climbing operation is needed, normal passing of roads is not affected, the detection efficiency is high, and rapid detection of large-scale steel structure lamp poles can be realized; meanwhile, the invention abandons the characteristics of complex workload and low efficiency in the traditional lamp pole detection activity, avoids the influence on road traffic, and reduces the safety risk of detection personnel.
The embodiment of the present invention further provides a specific embodiment of an electronic device, which can implement all the steps in the method for predicting a safe damage state of a steel structural member in the above embodiment, and referring to fig. 3, the electronic device specifically includes the following contents:
a processor (processor)301, a memory (memory)302, a communication Interface (Communications Interface)303, and a bus 304; the processor 301, the memory 302 and the communication interface 303 complete mutual communication through the bus 304; the communication interface 303 is used for information transmission among a prediction device of the safety damage state of the steel structural member, a client terminal, a defect monitoring device and other participating mechanisms;
the processor 301 is configured to call a computer program in the memory 302, and the processor implements all the steps in the method for predicting the safe damage state of the steel structural member in the above embodiment when executing the computer program, for example, the processor implements the following steps when executing the computer program:
s11: acquiring vibration mode characteristic data of a steel structural part;
s12: based on a preset safety damage state classification model, generating corresponding steel structural part damage degree data according to the steel structural part vibration modal characteristic data; the safety damage state classification model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data.
From the above description, the electronic device provided by the invention analyzes, judges and evaluates the safety and the service performance of the steel structure lamp pole by detecting the vibration modal characteristics corresponding to different damage degrees of the steel structure lamp pole; the equipment has the advantages that: only 1-2 detection personnel are needed for field detection, generally no climbing operation is needed, normal passing of roads is not affected, the detection efficiency is high, and rapid detection of large-scale steel structure lamp poles can be realized; meanwhile, the invention abandons the characteristics of complex workload and low efficiency in the traditional lamp pole detection activity, avoids the influence on road traffic, and reduces the safety risk of detection personnel.
An embodiment of the present invention further provides a computer-readable storage medium capable of implementing all the steps of the method for predicting a safe damage state of a steel structural member in the above embodiment, wherein the computer-readable storage medium stores a computer program, and the computer program implements all the steps of the method for predicting a safe damage state of a steel structural member in the above embodiment when executed by a processor, for example, the processor implements the following steps when executing the computer program:
s11: acquiring vibration mode characteristic data of a steel structural part;
s12: based on a preset safety damage state classification model, generating corresponding steel structural part damage degree data according to the steel structural part vibration modal characteristic data; the safety damage state classification model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data.
From the above description, the computer-readable storage medium provided by the invention analyzes, judges and evaluates the safety and the service performance of the steel structure lamp pole by detecting the vibration modal characteristics corresponding to different damage degrees of the steel structure lamp pole; the readable storage medium has the advantages that: only 1-2 detection personnel are needed for field detection, generally no climbing operation is needed, normal passing of roads is not affected, the detection efficiency is high, and rapid detection of large-scale steel structure lamp poles can be realized; meanwhile, the invention abandons the characteristics of complex workload and low efficiency in the traditional lamp pole detection activity, avoids the influence on road traffic, and reduces the safety risk of detection personnel.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment. Although embodiments of the present description provide method steps as described in the embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one of many possible orders of execution and does not represent a unique order of execution. When an actual apparatus or end product executes, it can execute sequentially or in parallel (e.g., parallel processors or multi-threaded environments, or even distributed data processing environments) according to the embodiments or methods shown in the drawings. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the embodiments of the present description, the functions of the respective modules may be implemented in the same software and/or hardware or the modules implementing the same functions may be implemented by a combination of a plurality of sub-modules or sub-units. The above-described apparatus embodiments are merely illustrative, and for example, the division of the units is merely a logical division, and other divisions may be realized in practice, 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 present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein. The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to part of the description of the method embodiment. In the description of the present specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the embodiments of the present specification. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the various embodiments or examples and features of the various embodiments or examples described in this specification can be combined and combined by those skilled in the art without contradiction. The above description is only an embodiment of the present disclosure, and is not intended to limit the present disclosure. Various modifications and changes may occur to those skilled in the art to which the embodiments of the present disclosure pertain. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification should be included in the scope of the claims of the embodiments of the present specification.
Claims (10)
1. The method for predicting the safe damage state of the steel structural member is characterized by comprising the following steps of:
acquiring vibration mode characteristic data of a steel structural part;
based on a preset safety damage state classification model, generating corresponding steel structural part damage degree data according to the steel structural part vibration modal characteristic data;
the safety damage state classification model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data.
2. The prediction method according to claim 1, wherein the obtaining of the vibration mode characteristic data of the steel structural member comprises:
receiving vibration data of the steel structural part;
and carrying out signal processing on the vibration data to obtain the vibration modal characteristic data of the steel structural member.
3. The prediction method of claim 2, wherein signal processing the vibration data comprises:
the vibration data is signal processed according to at least one of a fourier transform, a short-time fourier transform, and a wavelet analysis method.
4. The prediction method according to claim 3, wherein the signal processing comprises: filtering (noise reduction), waveform separation, spectral analysis, and modal analysis.
5. A prediction system for the safe damage state of a steel structural member is characterized by comprising a signal excitation device, a signal acquisition device and a signal processing device,
the signal excitation device is used for exciting the steel structural part to generate vibration;
the signal acquisition device is used for receiving vibration signals of the steel structural part;
the signal processing device generates corresponding steel structural member damage degree data according to the steel structural member vibration modal characteristic data based on a preset safety damage state classification grading model; wherein,
the safety damage state classification grading model is obtained by training historical steel structural member vibration mode characteristic data and historical steel structural member damage degree data.
6. The prediction system of claim 5, wherein the signal excitation device comprises: a force hammer and a trigger fixed in conjunction with the force hammer, the trigger coupled with the signal processing device.
7. The prediction system of claim 6, wherein the signal acquisition device comprises: a detector coupled to the signal processing device.
8. The prediction system of claim 7, wherein the signal acquisition device further comprises: and the magnetic suction head is fixedly combined with the detector and is used for fixing the detector on a steel structural member.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for predicting the safe damage state of a steel structural member according to any one of claims 1 to 4 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for predicting the safe damage state of a steel structural part according to any one of claims 1 to 4.
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