CN113807268A - Cylindrical object vibration detection method and device and computer storage medium - Google Patents
Cylindrical object vibration detection method and device and computer storage medium Download PDFInfo
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- CN113807268A CN113807268A CN202111105615.7A CN202111105615A CN113807268A CN 113807268 A CN113807268 A CN 113807268A CN 202111105615 A CN202111105615 A CN 202111105615A CN 113807268 A CN113807268 A CN 113807268A
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Abstract
The application provides a cylindrical object vibration detection method, a cylindrical object vibration detection device and a computer storage medium, wherein the method comprises the following steps: converting the position change time sequence of the cylindrical object from a time domain to a frequency domain to obtain a position change frequency spectrum signal; removing zero-valued peaks on the position-variation spectrum number; calculating a series of maxima of the residual spectrum on the location change spectrum number; determining candidate peak positions on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number; determining a base frequency sequence according to the candidate peak position on the position change spectrum number and the corresponding frequency multiplication; and determining the vibration detection result of the cylindrical object according to the base frequency sequence. The method and the device can accurately and rapidly position the credible peak position under the conditions of complex background and numerous miscellaneous frequencies, and can give out a possible base frequency sequence according to frequency multiplication and peak values.
Description
Technical Field
The embodiment of the application relates to the field of computer vision, in particular to a cylindrical object vibration detection method and device and a computer storage medium.
Background
Vibration detection methods for cylindrical objects (e.g., such as guys on cable bridges, high-voltage power transmission lines, bridge columns, wires, ropes, etc.) generally include contact type and non-contact type.
Taking a cable as an example, the contact type vibration detection technology uses some kind of acceleration sensor attached to a target object to measure a vibration signal. Currently, the existing contact type vibration detection technology includes a vibration frequency method represented by an acceleration sensor, a magnetic flux method represented by an electromagnetic sensor, and a pressure method represented by a feed-through test ring, and these probes are all in contact with a cable to perform measurement. Contact-type techniques are costly, complex to implement on-site, difficult to operate, and most on-site conditions do not allow for the placement of sensors on the target object.
Non-contact vibration detection techniques include the use of both microwave radar technology and computer vision technology. The vibration detection technology based on the microwave radar often needs to hit the cable with a hammer to increase the vibration amplitude of the cable, so the sensitivity of the vibration detection technology is generally lower than that of the vibration detection technology based on computer vision. Computer vision based vibration detection techniques basically use a method of feature matching to track the position change of an object in each frame. In order to improve the cable identification precision, an image segmentation method based on a convolutional neural network is applied to cable identification, and then the gravity center method is used for tracking the position of each frame of cable.
However, in the prior art, under the conditions of a complex background and numerous spurious frequencies, the position of a credible peak cannot be accurately and rapidly positioned, and a possible fundamental frequency sequence can be given according to frequency multiplication and the peak value.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a vibration detection scheme for a cylindrical object, which overcomes or alleviates the above-mentioned drawbacks in the prior art.
A method of detecting vibration of a cylindrical object, comprising:
converting the position change time sequence of the cylindrical object from a time domain to a frequency domain to obtain a position change frequency spectrum signal;
removing zero-valued peaks on the position-variation spectrum number;
calculating a series of maxima of the residual spectrum on the location change spectrum number;
determining candidate peak positions on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number;
determining a base frequency sequence according to the candidate peak position on the position change spectrum number and the corresponding frequency multiplication;
and determining the vibration detection result of the cylindrical object according to the base frequency sequence.
Optionally, the calculating a maximum of the remaining spectrum on the location change spectrum number comprises: calculating a peak height-half width ratio corresponding to the maximum value of the residual frequency spectrum on the position change spectrum number; identifying high-frequency background information from the residual frequency spectrum on the position change spectrum number, and calculating a corresponding high-frequency background value;
correspondingly, the determining the candidate peak position on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number includes: and determining a peak value which is larger than the high frequency background value and larger than a relatively loose peak height-full width at half maximum ratio in the residual frequency spectrum on the position change spectrum number, and taking the corresponding peak position as the candidate peak position.
Optionally, the removing zero-valued peaks on the position-variation spectrum number previously comprises: and carrying out logarithmic transformation on the position change spectrum number, and determining a zero-value peak position on the position change spectrum number according to a result of the logarithmic transformation.
Optionally, the determining a fundamental frequency sequence according to the candidate peak position on the position change spectrum number and the frequency multiplication corresponding to the candidate peak position comprises: and selecting the corresponding frequency multiplication of the candidate peak position on the position change frequency spectrum number, and determining a fundamental frequency sequence.
Optionally, the converting the time-domain to frequency-domain of the position change time sequence of the cylindrical object to obtain a position change spectrum signal includes:
segmenting the image of the cylindrical object to obtain a plurality of frames of local images of the cylindrical object;
and generating a position change time sequence of the cylindrical object according to the gravity centers of the cylindrical objects in the local images of the cylindrical objects of two adjacent frames.
Optionally, the segmenting the image of the cylindrical object to obtain multiple frames of local images of the cylindrical object includes: and segmenting the image of the cylindrical object by using a multi-sliding window to obtain a plurality of frames of local images of the cylindrical object.
Optionally, after the image of the cylindrical object is segmented to obtain multiple frames of the local images of the cylindrical object, the generating a position change time sequence of the cylindrical object according to two adjacent frames of the gravity center of the cylindrical object corresponding to the local images of the cylindrical object includes: and calculating the gravity center of the cylindrical object in the local images of the two frames of the cylindrical object.
Optionally, the generating a time sequence of position changes of the cylindrical object according to the center of gravity of the cylindrical object in the two adjacent frames of the local images of the cylindrical object includes:
generating a position change time source sequence of the cylindrical object according to the gravity center of the cylindrical object in the local images of the two adjacent frames of the cylindrical object;
and performing clustering analysis on the position change time source sequence of the cylindrical object to generate the position change time sequence of the cylindrical object.
Optionally, the segmenting the image of the cylindrical object to obtain multiple frames of the local images of the cylindrical object includes: and determining and separating the image of the cylindrical object from the target video based on the deep convolutional neural network.
Optionally, the pair of depth convolution based neural networks before determining and separating the image of the cylindrical object from the target video includes: and carrying out image enhancement processing on the source video to obtain the target video, wherein the image enhancement comprises at least one of brightness enhancement, motion enhancement and vibration compensation.
Optionally, the determining, according to the fundamental frequency sequence, a vibration detection result of the cylindrical object includes:
predicting the vibration health condition of the cylindrical object according to the base frequency sequence based on the historical vibration detection result of the cylindrical object to obtain a vibration health condition prediction result;
and determining the vibration detection result of the cylindrical object according to the vibration health condition prediction result.
Optionally, the predicting the vibration health condition of the cylindrical object according to the base frequency sequence based on the historical vibration detection result of the cylindrical object to obtain a vibration health condition prediction result includes:
if the historical vibration detection result of the cylindrical object shows that the frequency value sequence curve is simple or tends to be obvious, predicting the vibration health condition of the cylindrical object by adopting a data fitting and extrapolation algorithm according to the fundamental frequency sequence to obtain a vibration health condition prediction result;
and if the frequency value sequence curve is complex and tends to be unobvious, predicting the vibration health condition of the cylindrical object by adopting a deep neural network time sequence prediction algorithm according to the fundamental frequency sequence to obtain a vibration health condition prediction result.
A vibration detecting apparatus for a cylindrical object, comprising:
the conversion unit is used for converting the position change time sequence of the cylindrical object from a time domain to a frequency domain to obtain a position change frequency spectrum signal;
the peak searching unit is used for removing zero peak positions on the position change frequency spectrum number; calculating a series of maxima of the residual spectrum on the location change spectrum number; determining candidate peak positions on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number;
a sequence determining unit, configured to determine a base frequency sequence according to the candidate peak position on the position change spectrum number and the corresponding frequency multiplication;
and the vibration detection unit is used for determining the vibration detection result of the cylindrical object according to the base frequency sequence.
A computer storage medium having stored thereon a computer executable program operative to perform a method according to any of the embodiments of the present application.
In the embodiment of the application, the position change frequency spectrum signal is obtained by converting the position change time sequence of the cylindrical object from a time domain to a frequency domain; determining a base frequency sequence according to the candidate peak position on the position change spectrum number and the corresponding frequency multiplication; and determining the vibration detection result of the cylindrical object according to the fundamental frequency sequence, thereby accurately and rapidly positioning the credible peak position under the conditions of complex background and numerous miscellaneous frequencies, and providing a possible fundamental frequency sequence according to the frequency multiplication and the peak value.
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Some specific embodiments of the present application will be described in detail hereinafter by way of illustration and not limitation with reference to the accompanying drawings. The same reference numbers in the drawings identify the same or similar elements or components. Those skilled in the art will appreciate that the drawings are not necessarily drawn to scale. In the drawings:
FIG. 1 is a schematic diagram of a system architecture for implementing the vibration detection method for cylindrical objects according to the present application;
FIG. 2 is a schematic flow chart illustrating a method for detecting vibration of a cylindrical object according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of the segmentation and the generation of a position change time sequence by a computation center according to the embodiment of the present application;
FIG. 4 is a schematic diagram of the application of the scheme of the application to a detection scene of a bridge cable;
fig. 5 is a schematic flow chart of the vibration detection device for a cylindrical object in the embodiment of the present application.
Detailed Description
It is not necessary for any particular embodiment of the invention to achieve all of the above advantages at the same time.
In order to make those skilled in the art better understand the technical solutions in the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application shall fall within the scope of the protection of the embodiments in the present application.
FIG. 1 is a schematic diagram of a system architecture for implementing the vibration detection method for cylindrical objects according to the present application; the system performs photographing detection on the cylindrical object 100 at a certain distance. Of course, multiple cylindrical objects may be in the same field of view of the camera. As shown in fig. 1, it includes: a portable box 101, a camera device 102, a camera lens 103, a data transfer and control line 104, a computing unit 105, a user interface 106, and a database or server 107, the camera device 102, the data transfer and control line 104, the computing unit 105 being housed in the portable box 101, the computing unit 105 being, for example, a microcomputer, a microprocessor, an FPGA-based or a GPU-based processor. In the present application, the camera lens 103 is provided in the device case 101, thereby providing an integrated system; the camera lens 103 and the camera apparatus 102 may also be separated from the portable box 101 as a separate type system. The camera device 102 is connected to a computing unit 105 via a data transfer and control line 104 (including a USB line or a network line or a wireless network, etc.). The captured images or videos may be uploaded to a database or server 107 for storage or further analysis. The user may control the entire system, including displaying or manipulating images or video, through the user interface 106 (including screen/mouse/keyboard, etc.).
Further, in order to reduce the vibration of the surrounding environment affecting the vibration detection of the cylindrical object 100 by the system, a vibration-proof pad or a vibration-proof spring structure 108 is added on the base of the camera 102. In the case of a compact system, a shock pad or shock spring structure 109 is also added to the base or support of the portable case 101.
Further, the acceleration sensor 110 may be provided on the camera apparatus 102 to measure the vibration frequency of the camera apparatus 102 itself, so as to remove the frequency caused by the self-vibration of the camera apparatus, i.e., remove the noise frequency, in the execution of the following steps S205 to 207, thereby ensuring the accuracy of the detection result.
FIG. 2 is a schematic flow chart illustrating a method for detecting vibration of a cylindrical object according to an embodiment of the present disclosure; as shown in fig. 2, it includes:
s201, segmenting the image of the cylindrical object to obtain multiple frames of local images of the cylindrical object;
in step S201, the segmenting is performed on the image of the cylindrical object to obtain multiple frames of the local images of the cylindrical object, including: and segmenting the image of the cylindrical object by using a multi-sliding window to obtain a plurality of frames of local images of the cylindrical object, thereby reducing the separation error caused by violent vibration of the cylindrical object.
S202, generating a position change time sequence of the cylindrical object according to the gravity centers of the cylindrical objects in the local images of the cylindrical objects of two adjacent frames.
In step S202, the center of gravity of the cylindrical object in the two frames of the local images of the cylindrical object is calculated, and the position change time sequence of the cylindrical object is generated according to the center of gravity of the cylindrical object in the two adjacent frames of the local images of the cylindrical object.
In step S202, according to two adjacent frames of the local images of the cylindrical object corresponding to the center of gravity of the cylindrical object, a position change time sequence of the cylindrical object is generated, which includes:
generating a position change time source sequence of the cylindrical object according to the gravity center of the cylindrical object in the local images of the two adjacent frames of the cylindrical object;
and performing clustering analysis on the position change time source sequence of the cylindrical object to generate the position change time sequence of the cylindrical object.
FIG. 3 is a schematic diagram of the segmentation and the generation of a position change time sequence by a computation center according to the embodiment of the present application; as shown in fig. 3, a plurality of sliding windows are provided, each sliding window may segment the image of the cylindrical object to obtain one frame of the local image of the cylindrical object, the sliding windows collectively obtain the local images of a plurality of frames of the cylindrical object, calculate the center of gravity of the cylindrical object corresponding to the local image of the frame of the cylindrical object, compare two adjacent frames of the local images of the cylindrical object corresponding to the center of gravity of the cylindrical object to obtain a position change time source sequence, perform cluster analysis on the position change time source sequence, and obtain a final position change time sequence, that is, the position change time sequence in step S202, thereby reducing the center of gravity calculation error caused by severe vibration. The clustering algorithm may be, for example, a k-means algorithm, or, in other embodiments, the clustering algorithm is directly replaced by an average or median.
If in fig. 3, one barycentric position value (x0, y0) is calculated for start time t0, and barycentric position value (xi, yi) of the sub-graph corresponding to a certain time ti is calculated, then the position change is dxi ═ xi-x0, and the position change is dxi ═ yi-y0, and for the local image of the cylindrical object in the frame with N frames, the position change source time series is (dx0, dy0), (dx1, dy1), …, (dxi, dy), …, (dxN, dyN); and clustering the position change source time sequence to obtain a position change time sequence.
S203, converting the position change time sequence of the cylindrical object from a time domain to a frequency domain to obtain a position change frequency spectrum signal;
s204, carrying out logarithmic transformation on the position change spectrum number, and determining a zero-value peak position on the position change spectrum number according to a result of the logarithmic transformation.
S205, removing zero peak positions on the position change frequency spectrum number;
s206, calculating a series of maximum values of the residual frequency spectrum on the position change spectrum number;
s207, calculating a peak height-half width ratio corresponding to the maximum value of the residual frequency spectrum on the position change spectrum number; identifying high-frequency background information from the residual frequency spectrum on the position change spectrum number, and calculating a corresponding high-frequency background value;
and S208, determining candidate peak positions on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number.
In step S208, determining a candidate peak position on the position change spectrum number according to the maximum value of the remaining spectrum on the position change spectrum number includes: and determining a peak value which is larger than the high-frequency background value and larger than a relatively loose peak height-full width at half maximum ratio in the residual frequency spectrum on the position change spectrum number, and taking the corresponding peak position as the candidate peak position, thereby realizing accurate and rapid positioning of a credible peak position under the conditions of a complex background and numerous miscellaneous frequencies.
S209, determining a fundamental frequency sequence according to the candidate peak position on the position change spectrum number and the corresponding frequency multiplication;
in step S209, determining a fundamental frequency sequence according to the candidate peak position on the position change spectrum number and the frequency multiplication corresponding to the candidate peak position, including: and selecting the corresponding frequency multiplication of the candidate peak position on the position change frequency spectrum number, and determining a base frequency sequence so as to determine possible multiple relations of the candidate peak position, such as 1.2Hz,2.4Hz and 3.6Hz ….
S210, determining the vibration detection result of the cylindrical object according to the base frequency sequence.
In step S210, determining a vibration detection result of the cylindrical object according to the fundamental frequency sequence, including:
predicting the vibration health condition of the cylindrical object according to the base frequency sequence based on the historical vibration detection result of the cylindrical object to obtain a vibration health condition prediction result;
and determining the vibration detection result of the cylindrical object according to the vibration health condition prediction result.
Optionally, the predicting the vibration health condition of the cylindrical object according to the fundamental frequency sequence based on the historical vibration detection result of the cylindrical object to obtain a vibration health condition prediction result includes:
if the historical vibration detection result of the cylindrical object shows that the frequency value sequence curve is simple or tends to be obvious, predicting the vibration health condition of the cylindrical object by adopting a data fitting and extrapolation algorithm according to the fundamental frequency sequence to obtain a vibration health condition prediction result; data fitting and extrapolation algorithms such as linear interpolation, polynomial interpolation, etc.
And if the frequency value sequence curve is complex and tends to be unobvious, predicting the vibration health condition of the cylindrical object by adopting a deep neural network time sequence prediction algorithm according to the fundamental frequency sequence to obtain a vibration health condition prediction result. The deep neural network time series prediction algorithm adopts a basic LSTM (Long Short-Term Memory) network structure.
In this embodiment, after the vibration health condition prediction result is obtained, a report may be created or an early warning may be issued, and the report and video data for each inspection may be stored in a database or a server via WiFi or other internet data transmission means. When the variation or trend in the vibration (frequency, amplitude) through the cylindrical object exceeds a certain alarm threshold, an alarm is issued to the user through the user interface or server and other alarm devices. The user can extract reports and video data from the server at any time.
Specifically, in another embodiment, the segmenting the image of the cylindrical object to obtain multiple frames of the local images of the cylindrical object includes: the method comprises the steps of determining and separating the image of the cylindrical object from a target video based on a deep convolutional neural network, so that the situation that the actual image has a complex background and the cylindrical object cannot be accurately identified under severe weather conditions and wrong shooting parameters can be solved.
Illustratively, for each frame of the target image, if the input is a color image, it is first converted to a grayscale image. The whole frame image size (width) is then changed to 512 x 512 image size as input to the deep convolutional neural network. Through the calculation of the depth convolution neural network, a mask image of 512 x 512 is output, then the mask image is amplified to be a (height, width) mask image, the size of the mask image is matched with the size of the whole frame image, and finally the original whole frame image is multiplied by the mask image, so that the image of the cylindrical object is separated, the calculation time is greatly reduced, and meanwhile, the segmentation precision of the cylindrical object can still be ensured.
Further, before determining and separating the image of the cylindrical object from the target video, the depth-based convolutional neural network comprises: and performing image enhancement processing on the source video to obtain the target video, wherein the image enhancement comprises at least one of brightness enhancement, motion enhancement and vibration compensation, so as to solve the influence caused by relatively strong vibration (such as passing by a large vehicle or a strong wind environment) outside the detection system equipment.
Specifically, for example, Gamma enhancement technology is used to improve the image brightness, i.e. brightness enhancement is realized; and enhancing the vibration amplitude of the cylindrical object in the image by using a motion enhancement technology, namely realizing motion enhancement. If the system has stronger vibration (such as the passing of a cart or a strong wind environment), after each frame image of the source video is matched with the first image, each frame image is subjected to vibration compensation by using the relative displacement of the source video to obtain a target video, so that the situation that when cylindrical objects such as a guy cable, a bridge pillar or a high-voltage line are detected, for example, when the guy cable is detected, the passing vehicle, people and the strong wind can cause vibration of measuring equipment, the shot images are also shaken, and spectrum signals irrelevant to the vibration of the guy cable are mixed in the measured spectrum to cause detection failure can be effectively solved.
The invention provides a whole set of anti-vibration scheme, which comprises the steps of adding anti-vibration measures to the measuring equipment on hardware and measuring the vibration frequency of the measuring equipment by an acceleration sensor of the measuring equipment. In software, the shaking displacement between frames is calculated by using an image matching algorithm on the whole frame image, and the self-vibration displacement of the cylindrical object is compensated
FIG. 4 is a schematic diagram of the application of the scheme of the application to a detection scene of a bridge cable; as shown in fig. 4, the cable vibration spectrum analysis result is obtained by using a camera with a frame frequency of 60f/s to shoot a video with 2000 × 800 pixels for 8 seconds, according to the data processing flow of fig. 2, and the result shows that the very accurate fundamental frequency sequence is 3.01, 6.13, 9.14, … 27.21.21 Hz, so that the fundamental frequency of the bridge cable is about 3.03 Hz.
FIG. 5 is a schematic flow chart of an apparatus for detecting vibration of a cylindrical object according to an embodiment of the present disclosure; as shown in fig. 5, it includes:
a converting unit 501, configured to perform time-domain to frequency-domain conversion on the position change time sequence of the cylindrical object to obtain a position change frequency spectrum signal;
a peak searching unit 502, configured to remove a zero-valued peak position on the position change spectrum number; calculating a series of maxima of the residual spectrum on the location change spectrum number; determining candidate peak positions on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number;
a sequence determining unit 503, configured to determine a base frequency sequence according to the candidate peak position on the position change spectrum number and the frequency multiplication corresponding to the candidate peak position;
a vibration detection unit 504, configured to determine a vibration detection result of the cylindrical object according to the fundamental frequency sequence.
In the embodiment shown in fig. 5, for a preferred explanation of each unit cell, reference may be made to the above method embodiment, and details are not repeated.
Thus, particular embodiments of the present subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may be advantageous.
It should also be noted that 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, an element defined by the phrase "comprising an …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, 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 the partial description of the method embodiment.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method of detecting vibration of a cylindrical object, comprising:
converting the position change time sequence of the cylindrical object from a time domain to a frequency domain to obtain a position change frequency spectrum signal;
removing zero-valued peaks on the position-variation spectrum number;
calculating a series of maxima of the residual spectrum on the location change spectrum number;
determining candidate peak positions on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number;
determining a base frequency sequence according to the candidate peak position on the position change spectrum number and the corresponding frequency multiplication;
and determining the vibration detection result of the cylindrical object according to the base frequency sequence.
2. The method for detecting vibration of a cylindrical object according to claim 1, wherein said calculating the maximum of the residual spectrum on the position change spectrum number comprises: calculating a peak height-half width ratio corresponding to the maximum value of the residual frequency spectrum on the position change spectrum number; identifying high-frequency background information from the residual frequency spectrum on the position change spectrum number, and calculating a corresponding high-frequency background value;
correspondingly, the determining the candidate peak position on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number includes: and determining a peak value which is larger than the high frequency background value and larger than a relatively loose peak height-full width at half maximum ratio in the residual frequency spectrum on the position change spectrum number, and taking the corresponding peak position as the candidate peak position.
3. The method for detecting the vibration of the cylindrical object according to claim 1, wherein the removing of the zero-valued peak positions on the position change spectrum number comprises: and carrying out logarithmic transformation on the position change spectrum number, and determining a zero-value peak position on the position change spectrum number according to a result of the logarithmic transformation.
4. The method for detecting the vibration of the cylindrical object according to claim 1, wherein the determining the base frequency sequence according to the candidate peak position on the position change spectrum number and the corresponding frequency multiplication comprises: and selecting the corresponding frequency multiplication of the candidate peak position on the position change frequency spectrum number, and determining a fundamental frequency sequence.
5. The method for detecting vibration of a cylindrical object according to any one of claims 1 to 4, wherein the step of converting the time-domain to frequency-domain of the position change of the cylindrical object to obtain a position change spectrum signal comprises:
segmenting the image of the cylindrical object to obtain a plurality of frames of local images of the cylindrical object;
and generating a position change time sequence of the cylindrical object according to the gravity centers of the cylindrical objects in the local images of the cylindrical objects of two adjacent frames.
6. The method for detecting the vibration of the cylindrical object according to claim 5, wherein the segmenting the image of the cylindrical object to obtain a plurality of frames of the local images of the cylindrical object comprises: and segmenting the image of the cylindrical object by using a multi-sliding window to obtain a plurality of frames of local images of the cylindrical object.
7. The method for detecting the vibration of the cylindrical object according to claim 5, wherein the generating the time sequence of the position change of the cylindrical object according to the gravity center of the cylindrical object in the two adjacent frames of the local images of the cylindrical object comprises:
generating a position change time source sequence of the cylindrical object according to the gravity center of the cylindrical object in the local images of the two adjacent frames of the cylindrical object;
and performing clustering analysis on the position change time source sequence of the cylindrical object to generate the position change time sequence of the cylindrical object.
8. The method for detecting the vibration of the cylindrical object according to claim 9, wherein the determining and separating the image of the cylindrical object from the target video based on the deep convolutional neural network comprises: and carrying out image enhancement processing on the source video to obtain the target video, wherein the image enhancement comprises at least one of brightness enhancement, motion enhancement and vibration compensation.
9. The method for detecting the vibration of the cylindrical object according to any one of claims 1 to 10, wherein the determining the vibration detection result of the cylindrical object according to the fundamental frequency sequence comprises:
predicting the vibration health condition of the cylindrical object according to the base frequency sequence based on the historical vibration detection result of the cylindrical object to obtain a vibration health condition prediction result;
and determining the vibration detection result of the cylindrical object according to the vibration health condition prediction result.
10. A vibration detecting apparatus for a cylindrical object, comprising:
the conversion unit is used for converting the position change time sequence of the cylindrical object from a time domain to a frequency domain to obtain a position change frequency spectrum signal;
the peak searching unit is used for removing zero peak positions on the position change frequency spectrum number; calculating a series of maxima of the residual spectrum on the location change spectrum number; determining candidate peak positions on the position change spectrum number according to the maximum value of the residual spectrum on the position change spectrum number;
a sequence determining unit, configured to determine a base frequency sequence according to the candidate peak position on the position change spectrum number and the corresponding frequency multiplication;
and the vibration detection unit is used for determining the vibration detection result of the cylindrical object according to the base frequency sequence.
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