A long-distance laser tower bolt vibration measurement system and method

Abstract

The present application relates to the technical field of laser vibration measurement, and discloses a long-distance laser iron tower bolt vibration measurement system and method, wherein the system emits a laser beam through a laser emission module and focuses on the position of the bolt to be measured, receives the reflected laser signal through a laser receiving module, converts the laser signal into an electric signal, determines the signal intensity deviation, sends the signal intensity deviation to a UAV navigation module, adjusts the distance and posture of the UAV relative to the position of the bolt to be measured according to the signal intensity deviation through the UAV navigation module, determines the spraying position of the UAV, thereby improving the spraying accuracy, sprays the position of the bolt to be measured through a spraying light spray module, and determines the vibration frequency spectrum data of the bolt position under the preset vibration measurement condition based on the electric signal received by the laser receiving module through a vibration measurement module, thereby obtaining effective reflected signals, enabling long-distance vibration measurement, and improving the accuracy of the vibration measurement result.

Description

Technical Field

[0001] This invention relates to the field of laser vibration measurement technology, and in particular to a long-distance laser vibration measurement system and method for iron tower bolts. Background Technology

[0002] In the field of power technology, there is a great demand for measuring the vibration of objects, especially the vibration displacement and loosening of tower bolts. Currently, an increasing number of studies are beginning to use laser vibrometer technology for object vibration measurement, but these studies mainly focus on short-range, indoor steady-state vibration measurements. The technology and equipment for outdoor long-distance vibration measurement are still in their early stages of development. Due to many uncontrollable factors such as outdoor weather, buoyancy, optics, and interference, outdoor long-distance vibration measurement is very difficult, especially when the measured object has low reflectivity, making it impossible to return a valid optical signal, and it is also difficult to alter the object itself.

[0003] The most typical application scenario is the detection of loose bolts on power transmission towers. However, the detection of loose bolts on power transmission towers faces many unfavorable factors such as the poor reflectivity of the material itself and the complex outdoor environment, making it difficult to obtain effective reflection signals. This can easily lead to the risk that the measurement distance needs to be relatively short and the vibration measurement results are inaccurate. Summary of the Invention

[0004] This invention provides a long-distance laser tower bolt vibration measurement system and method, which solves the technical problems faced in the detection of loose bolts in power transmission towers, such as the poor reflectivity of the material itself and the complex outdoor environment, which make it difficult to obtain effective reflection signals and easily lead to the risk of requiring a short measurement distance and inaccurate vibration measurement results.

[0005] In view of this, the first aspect of the present invention provides a long-distance laser tower bolt vibration measurement system, which also includes a laser vibration measurement module, and the drone is equipped with a drone navigation module and a spray reflective spray module;

[0006] The laser vibration measurement module includes a laser emitting module, a laser receiving module, and a vibration measurement module;

[0007] The laser emitting module is used to emit a laser beam and focus the laser beam onto the position of the bolt to be tested;

[0008] The laser receiving module is used to receive the laser signal reflected back by the laser beam at the position of the bolt to be tested, convert the laser signal into an electrical signal, compare the received electrical signal with a preset electrical signal, determine the signal strength deviation, and send the signal strength deviation to the UAV navigation module.

[0009] The drone navigation module is used to adjust the distance and attitude of the drone relative to the position of the bolt to be tested according to the signal strength deviation, until the signal strength deviation is greater than a preset signal strength deviation threshold, so as to determine the spraying position of the drone.

[0010] The reflective spraying module is used to spray reflective spray onto the position of the bolt to be tested based on the spraying position of the UAV according to a preset spraying path and spraying parameters.

[0011] The vibration measurement module is used to determine the vibration spectrum data of the bolt position based on the electrical signal received by the laser receiving module under preset vibration measurement conditions.

[0012] Preferably, the laser receiving module includes a photoelectric conversion module and a signal processing module;

[0013] The photoelectric conversion module is used to convert the laser signal into an electrical signal;

[0014] The signal processing module is used to determine the corresponding signal spectrum data based on the received electrical signal, and is also used to compare the signal spectrum data with the signal spectrum data of a preset electrical signal to determine the signal amplitude deviation as the signal strength deviation.

[0015] Preferably, the system further includes an image acquisition module, an image recognition module, and a spraying control module;

[0016] The image acquisition module is used to acquire the spraying image after the position of the bolt to be tested is sprayed;

[0017] The image recognition module is used to perform image recognition on the sprayed image of the bolt position to be tested after spraying, and to determine the sprayed area of ​​the bolt position to be tested; it is also used to identify the spraying effect of the bolt position to be tested based on a pre-trained spraying recognition model, so as to determine whether the spraying effect of the bolt position to be tested is positive. If the spraying effect of the bolt position to be tested is determined to be negative, a spraying signal is generated and sent to the spraying control module.

[0018] The spraying control module is used to spray reflective spray again on the position of the bolt to be tested based on the spraying signal until the spraying effect of the bolt position is excellent, and then stop spraying.

[0019] Preferably, the system further includes:

[0020] The data acquisition module is used to acquire multiple historical spraying images of bolts of different bolt types after they have been sprayed, and to construct an image set;

[0021] The capacity expansion module is used to expand the capacity of the image set to obtain an expanded image set;

[0022] The spraying area comparison module is used to calculate the spraying area of ​​each historical spraying image in the expanded image set, determine the maximum spraying area of ​​each historical spraying image, compare the maximum spraying area of ​​each historical spraying image with a preset spraying area threshold, and determine whether the spraying effect of each historical spraying image is positive or negative based on the comparison result.

[0023] The image labeling module is used to classify the expanded image set according to the positive and negative states of the spraying effect, and to label the positive and negative states of the spraying effect of each historical spraying image.

[0024] The training sample construction module is used to construct a training sample set based on the augmented image set and the labels of positive and negative spraying effects;

[0025] The training module is used to train the convolutional neural network using the training sample set, wherein the historical spraying images are used as input and the labels of the positive and negative spraying effects corresponding to the historical spraying images are used as output for training, and a spraying recognition model is obtained.

[0026] Preferably, the system further includes: a signal feedback module;

[0027] The vibration measurement module is also used to determine the signal strength value based on the vibration spectrum data of the bolt position, and send the signal strength value to the signal feedback module;

[0028] The signal feedback module is used to compare the signal strength value with a preset signal strength threshold and send the signal strength comparison result to the spraying control module.

[0029] The spraying control module is used to optimize the spraying parameters based on the signal strength comparison results, and the spraying parameters include the spraying flow rate.

[0030] Secondly, the present invention also provides a long-distance laser vibration measurement method for tower bolts. Using the aforementioned long-distance laser vibration measurement system for tower bolts, this method includes the following steps:

[0031] A laser beam is emitted by a laser emission module and focused onto the position of the bolt to be tested.

[0032] The laser receiving module receives the laser signal reflected back from the position of the bolt to be tested by the laser beam, converts the laser signal into an electrical signal, and compares the received electrical signal with a preset electrical signal to determine the signal strength deviation.

[0033] The drone navigation module adjusts the distance and attitude of the drone relative to the position of the bolt to be tested based on the signal strength deviation until the signal strength deviation is greater than a preset signal strength deviation threshold, so as to determine the spraying position of the drone.

[0034] The reflective spray module sprays reflective spray onto the bolt position to be tested based on the spraying position of the UAV and according to the preset spraying path and spraying parameters.

[0035] The vibration spectrum data of the bolt position is determined by the vibration measurement module based on the electrical signal received by the laser receiving module under preset vibration measurement conditions.

[0036] Preferably, the laser receiving module includes a photoelectric conversion module and a signal processing module; then, the step of receiving the laser signal reflected back by the position of the bolt under test through the laser receiving module, converting the laser signal into an electrical signal, and comparing the received electrical signal with a preset electrical signal to determine the signal strength deviation specifically includes:

[0037] The laser receiving module receives the laser signal reflected back from the position of the bolt to be tested by the laser beam;

[0038] The laser signal is converted into an electrical signal by the photoelectric conversion module.

[0039] The signal processing module determines the corresponding signal spectrum data based on the received electrical signal, and also compares the signal spectrum data with the signal spectrum data of a preset electrical signal to determine the signal amplitude deviation as the signal strength deviation.

[0040] Preferably, the method further includes:

[0041] Obtain the spraying image of the bolt position to be tested after it has been sprayed;

[0042] Image recognition is performed on the sprayed image of the bolt position to be tested after spraying to determine the sprayed area of ​​the bolt position to be tested;

[0043] The spraying effect at the location of the bolt to be tested is identified based on a pre-trained spraying recognition model to determine whether the spraying effect at the location of the bolt to be tested is positive.

[0044] If the spraying effect at the location of the bolt to be tested is determined to be negative, a spraying signal is generated, and the location of the bolt to be tested is sprayed with reflective spray again based on the spraying signal until the spraying effect at the location of the bolt to be tested is excellent, at which point the spraying stops.

[0045] Preferably, the method further includes:

[0046] Acquire multiple historical images of bolts of different bolt types after they have been coated, and construct an image set;

[0047] The image set is enlarged to obtain an enlarged image set;

[0048] The spraying area of ​​each historical spraying image in the enhanced image set is calculated to determine the maximum spraying area of ​​each historical spraying image. The maximum spraying area of ​​each historical spraying image is compared with a preset spraying area threshold. Based on the comparison result, it is determined whether the spraying effect of each historical spraying image is positive or negative.

[0049] The enlarged image set is classified according to the positive and negative spraying effect, and the positive and negative spraying effect of each historical spraying image is marked.

[0050] A training sample set is constructed based on the augmented image set and the labels indicating positive and negative spraying effects;

[0051] The convolutional neural network is trained using the training sample set, wherein the historical spraying images are used as input and the labels of positive and negative spraying effects corresponding to the historical spraying images are used as output for training, and a spraying recognition model is obtained.

[0052] Preferably, the method further includes:

[0053] The signal strength value is determined based on the vibration spectrum data at the bolt location;

[0054] The signal strength value is compared with a preset signal strength threshold to obtain a signal strength comparison result;

[0055] The spraying parameters, including the spraying flow rate, are optimized based on the signal strength comparison results.

[0056] As can be seen from the above technical solutions, the present invention has the following advantages:

[0057] This invention emits a laser beam from a laser emitting module and focuses it onto the bolt to be tested. A laser receiving module receives the reflected laser signal and converts it into an electrical signal. The signal strength deviation is determined and sent to a drone navigation module. The drone navigation module adjusts the distance and attitude of the drone relative to the bolt based on the signal strength deviation to determine the spraying position, thus improving spraying accuracy. A reflective spraying module sprays reflective mist onto the bolt. A vibration measurement module, under preset vibration conditions, determines the vibration spectrum data of the bolt position based on the electrical signal received by the laser receiving module, thereby obtaining an effective reflected signal. This allows for long-distance vibration measurement and further improves the accuracy of the measurement results. Attached Figure Description

[0058] Figure 1 This is a schematic diagram of a long-distance laser tower bolt vibration measurement system provided in an embodiment of the present invention;

[0059] Figure 2 A flowchart illustrating a long-distance laser vibration measurement method for iron tower bolts, provided as an embodiment of the present invention. Detailed Implementation

[0060] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0061] For easier understanding, please refer to Figure 1 The present invention provides a long-distance laser tower bolt vibration measurement system, which also includes a laser vibration measurement module 10. The drone is equipped with a drone navigation module 20 and a spray reflective spray module 30.

[0062] The laser vibration measurement module 10 includes a laser emitting module 11, a laser receiving module 12, and a vibration measurement module 13;

[0063] The laser emitting module 11 is used to emit a laser beam and focus the laser beam to the position of the bolt to be tested;

[0064] The laser receiving module 12 is used to receive the laser signal reflected back by the position of the bolt to be tested, convert the laser signal into an electrical signal, compare the received electrical signal with a preset electrical signal, determine the signal strength deviation, and send the signal strength deviation to the UAV navigation module 20.

[0065] When the laser beam is emitted to the position of the bolt to be tested, part of the laser energy is absorbed and the other part is reflected, forming a reflected laser signal which is received by the laser receiving module 12.

[0066] The preset electrical signal is the standard electrical signal for laser ranging.

[0067] In one example, the laser receiving module 12 includes a photoelectric conversion module and a signal processing module;

[0068] The photoelectric conversion module is used to convert laser signals into electrical signals;

[0069] The signal processing module is used to determine the corresponding signal spectrum data based on the received electrical signal, and also to compare the signal spectrum data with the preset signal spectrum data of the electrical signal to determine the signal amplitude deviation as the signal strength deviation.

[0070] Understandably, the signal processing module obtains the corresponding signal spectrum data of the electrical signal, compares the signal spectrum data with the preset signal spectrum data of the electrical signal, where the signal spectrum data includes the signal amplitude, signal phase and frequency, and determines the signal amplitude deviation, which is then used as the signal strength deviation.

[0071] The drone navigation module 20 is used to adjust the distance and attitude of the drone relative to the position of the bolt to be tested according to the signal strength deviation, until the signal strength deviation is greater than the preset signal strength deviation threshold, so as to determine the spraying position of the drone.

[0072] It should be noted that the signal strength deviation reflects the intensity of the laser beam relative to the bolt position. The signal strength deviation is compared with a preset signal strength deviation threshold. If the signal strength deviation is less than the preset threshold, it means that the intensity of the laser beam relative to the bolt position is low. In this case, the distance and attitude of the drone relative to the bolt position need to be adjusted, such as by closing the distance and adjusting the flight attitude. When the signal strength deviation is greater than the preset threshold, the current hovering position of the drone is determined to be the spraying position.

[0073] The reflective spray module 30 is used to spray reflective spray onto the bolt position to be tested according to the spray path and spray parameters preset based on the drone spray position.

[0074] The reflective spray module sprays the coating onto the drone after determining the spraying location. The spraying path is pre-set based on the relative distance and the drone's attitude, ensuring that the coating is applied evenly, with appropriate coverage, and at a suitable spraying distance.

[0075] It's important to note that the surfaces of the bolts on the towers being tested are typically rough metal surfaces with low reflectivity. The unevenness leads to extensive diffuse reflection. This results in insufficient effective signals during laser vibration measurement, significantly reducing the signal-to-noise ratio and potentially causing test failure. The purpose of applying reflective spray is to enhance the reflectivity of the tested area. This spray consists of very small (typically between 1 and 850 micrometers) high-refractive-index reflective microspheres with negligible mass but excellent reflectivity.

[0076] The vibration measurement module 13 is used to determine the vibration spectrum data of the bolt position based on the electrical signal received by the laser receiving module 12 under preset vibration measurement conditions.

[0077] The vibration measurement condition involves striking the tower with an external force (such as a hammer, vibrator, or other excitation device) to generate low-frequency, high-energy elastic waves. At this time, the frequency, amplitude, and other information of the laser signal reflected back by the received laser will change and be converted into an electrical signal. By performing a Fourier transform on the electrical signal, the vibration spectrum data of the bolt position can be obtained, and the vibration situation at the bolt position can be analyzed.

[0078] It should be noted that this invention uses a laser emitting module to emit a laser beam and focus it on the bolt position to be tested. A laser receiving module receives the reflected laser signal and converts it into an electrical signal to determine the signal strength deviation. This deviation is then sent to a drone navigation module, which adjusts the distance and attitude of the drone relative to the bolt position based on the deviation to determine the spraying location, thereby improving spraying accuracy. A reflective spraying module sprays reflective mist onto the bolt position, and a vibration measurement module, under preset vibration conditions, determines the vibration spectrum data of the bolt position based on the electrical signal received by the laser receiving module. This provides an effective reflected signal, enabling long-distance vibration measurement and improving the accuracy of the results.

[0079] In one specific embodiment, the system further includes an image acquisition module, an image recognition module, and a spraying control module;

[0080] The image acquisition module is used to acquire the sprayed image of the bolt position to be tested after it has been sprayed.

[0081] The image acquisition module can be a camera.

[0082] The image recognition module is used to perform image recognition on the sprayed image of the bolt position to be tested after it has been sprayed, and to determine the sprayed area of ​​the bolt position to be tested; it is also used to identify the spraying effect of the bolt position to be tested based on the pre-trained spraying recognition model, so as to determine whether the spraying effect of the bolt position to be tested is positive. If the spraying effect of the bolt position to be tested is determined to be negative, a spraying signal is generated and sent to the spraying control module.

[0083] The coating effect at the test bolt location is considered positive if it meets the requirements, and negative if it does not.

[0084] The spraying control module is used to spray reflective spray again on the position of the bolt to be tested based on the spraying signal until the spraying effect of the position of the bolt to be tested is excellent, and then stop spraying.

[0085] In one specific embodiment, the system further includes:

[0086] The data acquisition module is used to acquire multiple historical spraying images of bolts of different bolt types after they have been sprayed, and to construct an image set.

[0087] The bolt types include hexagonal bolts, pentagonal bolts, or round bolts. At the same time, the layout of the bolts is extremely dense, while some parts are sparse, which will affect the spraying effect.

[0088] The capacity expansion module is used to expand the image set to obtain an expanded image set;

[0089] Among these methods, considering climate and weather conditions, the enhancement measures include adjusting image brightness, contrast, saturation, or rotation.

[0090] The spraying area comparison module is used to calculate the spraying area of ​​each historical spraying image in the expanded image set, determine the maximum spraying area of ​​each historical spraying image, compare the maximum spraying area of ​​each historical spraying image with a preset spraying area threshold, and determine whether the spraying effect of each historical spraying image is positive or negative based on the comparison result.

[0091] In determining the maximum spraying area of ​​a historical spraying image, the spraying image can be processed into grayscale and binarized to obtain a binary image. Edge detection is then performed on the binary image to determine the shape of the spraying area. Finally, the number of pixels within the shape of the spraying area is calculated to determine the maximum spraying area of ​​the spraying image.

[0092] Understandably, the maximum sprayed area of ​​a historical sprayed image is compared with a preset sprayed area threshold. If the maximum sprayed area of ​​the historical sprayed image is greater than the preset sprayed area threshold, it means that the spraying effect of the historical sprayed image meets the requirements, and the corresponding spraying effect of the historical sprayed image is positive. If the maximum sprayed area of ​​the historical sprayed image is less than the preset sprayed area threshold, it means that the spraying effect of the historical sprayed image does not meet the requirements, and the corresponding spraying effect of the historical sprayed image is negative.

[0093] The image labeling module is used to classify the expanded image set according to the positive and negative states of the spraying effect, and to label the positive and negative states of the spraying effect of each historical spraying image.

[0094] The training sample construction module is used to construct a training sample set based on the enlarged image set and the positive and negative labels of the spraying effect;

[0095] The training module is used to train the convolutional neural network using a training sample set. The training takes historical spraying images as input and outputs labels indicating the positive or negative spraying effects corresponding to the historical spraying images, thus training a spraying recognition model.

[0096] In one specific embodiment, the system further includes: a signal feedback module;

[0097] The vibration measurement module is also used to determine the signal strength value based on the vibration spectrum data of the bolt position and send the signal strength value to the signal feedback module;

[0098] The signal feedback module is used to compare the signal strength value with the preset signal strength threshold and send the signal strength comparison result to the spraying control module.

[0099] The spraying control module is used to optimize spraying parameters based on signal strength comparison results. Spraying parameters include spraying flow rate.

[0100] The signal strength value reflects the spraying effect. If the signal strength value is not high, the spraying parameters can be further optimized. At the same time, the drone is also equipped with a flow sensor to monitor the spraying flow rate. If the spraying effect meets the requirements, the drone stops spraying and returns to the ground; if it does not meet the requirements, it continues to execute the spraying program.

[0101] The above is a detailed description of an embodiment of a long-distance laser tower bolt vibration measurement system provided by the present invention. The following is a detailed description of an embodiment of a long-distance laser tower bolt vibration measurement method provided by the present invention.

[0102] For easier understanding, please refer to Figure 2 The present invention provides a long-distance laser vibration measurement method for tower bolts, which utilizes the aforementioned long-distance laser tower bolt vibration measurement system. This method includes the following steps:

[0103] 101. Emits a laser beam through the laser emitting module and focuses the laser beam onto the position of the bolt to be tested;

[0104] 102. The laser signal reflected back from the position of the bolt to be tested by the laser receiving module is received and converted into an electrical signal. The received electrical signal is compared with a preset electrical signal to determine the signal strength deviation.

[0105] 103. Adjust the distance and attitude of the drone relative to the position of the bolt to be tested by the drone navigation module according to the signal strength deviation until the signal strength deviation is greater than the preset signal strength deviation threshold, so as to determine the spraying position of the drone.

[0106] 104. Based on the spraying position of the UAV, reflective spray is applied to the position of the bolt to be tested according to the preset spraying path and spraying parameters by using a reflective spraying module.

[0107] 105. Under preset vibration measurement conditions, the vibration spectrum data of the bolt position is determined by the vibration measurement module based on the electrical signal received by the laser receiving module.

[0108] In one specific embodiment, the laser receiving module includes a photoelectric conversion module and a signal processing module; then step 102 specifically includes:

[0109] 1021. Receive the laser signal reflected back from the position of the bolt to be tested by the laser receiving module;

[0110] 1022. The laser signal is converted into an electrical signal through a photoelectric conversion module;

[0111] 1023. The signal processing module determines the corresponding signal spectrum data based on the received electrical signal, and also compares the signal spectrum data with the preset signal spectrum data of the electrical signal to determine the signal amplitude deviation as the signal strength deviation.

[0112] In one specific embodiment, the method further includes:

[0113] Obtain the spraying image of the bolt location to be tested after it has been sprayed;

[0114] Image recognition is performed on the sprayed image of the bolt position to be tested to determine the sprayed area of ​​the bolt position;

[0115] The spraying effect at the position of the bolt under test is identified based on a pre-trained spraying recognition model to determine whether the spraying effect at the position of the bolt under test is positive.

[0116] If the spraying effect at the location of the bolt to be tested is determined to be negative, a spraying signal is generated. Based on the spraying signal, the location of the bolt to be tested is sprayed with reflective spray again until the spraying effect at the location of the bolt to be tested is excellent, and then the spraying stops.

[0117] In one specific embodiment, the method further includes:

[0118] Acquire multiple historical images of bolts of different bolt types after they have been coated, and construct an image set;

[0119] The image set is enlarged to obtain an enlarged image set;

[0120] The spraying area of ​​each historical spraying image in the expanded image set is calculated to determine the maximum spraying area of ​​each historical spraying image. The maximum spraying area of ​​each historical spraying image is compared with a preset spraying area threshold. Based on the comparison result, it is determined whether the spraying effect of each historical spraying image is positive or negative.

[0121] The enlarged image set is classified according to the positive and negative spraying effects, and the positive and negative spraying effects of each historical spraying image are marked.

[0122] A training sample set is constructed based on the augmented image set and the positive and negative labels of the spraying effect;

[0123] The convolutional neural network is trained using a training sample set, with historical spraying images as input and the labels of positive and negative spraying effects corresponding to the historical spraying images as output, to obtain a spraying recognition model.

[0124] In one specific embodiment, the method further includes:

[0125] The signal strength value is determined based on the vibration spectrum data at the bolt location;

[0126] The signal strength value is compared with a preset signal strength threshold to obtain the signal strength comparison result;

[0127] The spraying parameters, including the spraying flow rate, are optimized based on the signal strength comparison results.

[0128] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the system described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0129] In the several embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0130] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A long-distance laser tower bolt vibration measurement system comprising a drone, characterized in that, It also includes a laser vibration measurement module, and the drone is equipped with a drone navigation module and a spray reflector spray module; The laser vibration measurement module includes a laser emitting module, a laser receiving module, and a vibration measurement module; The laser emitting module is used to emit a laser beam and focus the laser beam onto the position of the bolt to be tested; The laser receiving module is used to receive the laser signal reflected back by the laser beam at the position of the bolt to be tested, convert the laser signal into an electrical signal, compare the received electrical signal with a preset electrical signal, determine the signal strength deviation, and send the signal strength deviation to the UAV navigation module. The drone navigation module is used to adjust the distance and attitude of the drone relative to the position of the bolt to be tested according to the signal strength deviation, until the signal strength deviation is greater than a preset signal strength deviation threshold, so as to determine the spraying position of the drone. The reflective spraying module is used to spray reflective spray onto the position of the bolt to be tested based on the spraying position of the UAV according to a preset spraying path and spraying parameters. The vibration measurement module is used to determine the vibration spectrum data of the bolt position based on the electrical signal received by the laser receiving module under preset vibration measurement conditions.

2. The long-distance laser tower bolt vibration measurement system according to claim 1, characterized in that, The laser receiving module includes a photoelectric conversion module and a signal processing module; The photoelectric conversion module is used to convert the laser signal into an electrical signal; The signal processing module is used to determine the corresponding signal spectrum data based on the received electrical signal, and is also used to compare the signal spectrum data with the signal spectrum data of a preset electrical signal to determine the signal amplitude deviation as the signal strength deviation.

3. The long-distance laser tower bolt vibration measurement system according to claim 1, characterized in that, It also includes an image acquisition module, an image recognition module, and a spraying control module; The image acquisition module is used to acquire the spraying image after the position of the bolt to be tested is sprayed; The image recognition module is used to perform image recognition on the sprayed image of the bolt position to be tested after spraying, and to determine the sprayed area of ​​the bolt position to be tested; it is also used to identify the spraying effect of the bolt position to be tested based on a pre-trained spraying recognition model, so as to determine whether the spraying effect of the bolt position to be tested is positive. If the spraying effect of the bolt position to be tested is determined to be negative, a spraying signal is generated and sent to the spraying control module. The spraying control module is used to spray reflective spray again on the position of the bolt to be tested based on the spraying signal until the spraying effect of the bolt position is excellent, and then stop spraying.

4. The long-distance laser tower bolt vibration measurement system according to claim 3, characterized in that, Also includes: The data acquisition module is used to acquire multiple historical spraying images of bolts of different bolt types after they have been sprayed, and to construct an image set; The capacity expansion module is used to expand the capacity of the image set to obtain an expanded image set; The spraying area comparison module is used to calculate the spraying area of ​​each historical spraying image in the expanded image set, determine the maximum spraying area of ​​each historical spraying image, compare the maximum spraying area of ​​each historical spraying image with a preset spraying area threshold, and determine whether the spraying effect of each historical spraying image is positive or negative based on the comparison result. The image labeling module is used to classify the expanded image set according to the positive and negative states of the spraying effect, and to label the positive and negative states of the spraying effect of each historical spraying image. The training sample construction module is used to construct a training sample set based on the enlarged image set and the labels of positive and negative spraying effects; The training module is used to train the convolutional neural network using the training sample set, wherein the historical spraying images are used as input and the labels of the positive and negative spraying effects corresponding to the historical spraying images are used as output for training, and a spraying recognition model is obtained.

5. The long-distance laser tower bolt vibration measurement system according to claim 3, characterized in that, Also includes: Signal feedback module; The vibration measurement module is also used to determine the signal strength value based on the vibration spectrum data of the bolt position, and send the signal strength value to the signal feedback module; The signal feedback module is used to compare the signal strength value with a preset signal strength threshold and send the signal strength comparison result to the spraying control module. The spraying control module is used to optimize the spraying parameters based on the signal strength comparison results, and the spraying parameters include the spraying flow rate.

6. A method for long-distance laser vibration measurement of tower bolts, using the long-distance laser vibration measurement system for tower bolts as described in any one of claims 1 to 5, characterized in that, This method includes the following steps: A laser beam is emitted by a laser emission module and focused onto the position of the bolt to be tested. The laser receiving module receives the laser signal reflected back from the position of the bolt to be tested by the laser beam, converts the laser signal into an electrical signal, and compares the received electrical signal with a preset electrical signal to determine the signal strength deviation. The drone navigation module adjusts the distance and attitude of the drone relative to the position of the bolt to be tested based on the signal strength deviation until the signal strength deviation is greater than a preset signal strength deviation threshold, so as to determine the spraying position of the drone. The reflective spray module sprays reflective spray onto the bolt position to be tested based on the spraying position of the UAV and according to the preset spraying path and spraying parameters. The vibration spectrum data of the bolt position is determined by the vibration measurement module based on the electrical signal received by the laser receiving module under preset vibration measurement conditions.

7. The long-distance laser tower bolt vibration measurement method according to claim 6, wherein the laser receiving module comprises a photoelectric conversion module and a signal processing module; characterized in that, The laser receiving module receives the laser signal reflected back from the position of the bolt under test, converts the laser signal into an electrical signal, and compares the received electrical signal with a preset electrical signal to determine the signal strength deviation. The specific steps include: The laser receiving module receives the laser signal reflected back from the position of the bolt to be tested by the laser beam; The laser signal is converted into an electrical signal by the photoelectric conversion module. The signal processing module determines the corresponding signal spectrum data based on the received electrical signal, and also compares the signal spectrum data with the signal spectrum data of a preset electrical signal to determine the signal amplitude deviation as the signal strength deviation.

8. The long-distance laser tower bolt vibration measurement method according to claim 6, characterized in that, Also includes: Obtain the spraying image of the bolt position to be tested after it has been sprayed; Image recognition is performed on the sprayed image of the bolt position to be tested after spraying to determine the sprayed area of ​​the bolt position to be tested; The spraying effect at the location of the bolt to be tested is identified based on a pre-trained spraying recognition model to determine whether the spraying effect at the location of the bolt to be tested is positive. If the spraying effect at the location of the bolt to be tested is determined to be negative, a spraying signal is generated, and the location of the bolt to be tested is sprayed with reflective spray again based on the spraying signal until the spraying effect at the location of the bolt to be tested is excellent, at which point the spraying stops.

9. The long-distance laser tower bolt vibration measurement method according to claim 8, characterized in that, Also includes: Acquire multiple historical images of bolts of different bolt types after they have been coated, and construct an image set; The image set is enlarged to obtain an enlarged image set; The spraying area of ​​each historical spraying image in the enhanced image set is calculated to determine the maximum spraying area of ​​each historical spraying image. The maximum spraying area of ​​each historical spraying image is compared with a preset spraying area threshold. Based on the comparison result, it is determined whether the spraying effect of each historical spraying image is positive or negative. The enlarged image set is classified according to the positive and negative spraying effect, and the positive and negative spraying effect of each historical spraying image is marked. A training sample set is constructed based on the augmented image set and the labels indicating positive and negative spraying effects; The convolutional neural network is trained using the training sample set, wherein the historical spraying images are used as input and the labels of positive and negative spraying effects corresponding to the historical spraying images are used as output for training, and a spraying recognition model is obtained.

10. The long-distance laser tower bolt vibration measurement method according to claim 8, characterized in that, Also includes: The signal strength value is determined based on the vibration spectrum data at the bolt location; The signal strength value is compared with a preset signal strength threshold to obtain a signal strength comparison result; The spraying parameters, including the spraying flow rate, are optimized based on the signal strength comparison results.

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