CN111830045A - Unmanned aerial vehicle wind power detection system and method based on BIM technology - Google Patents
Unmanned aerial vehicle wind power detection system and method based on BIM technology Download PDFInfo
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Abstract
The invention discloses an unmanned aerial vehicle wind power detection system and method based on a BIM technology, belongs to the technical field of wind power detection, and comprises an unmanned aerial vehicle subsystem, a BIM center and a server center. The unmanned aerial vehicle subsystem comprises an unmanned aerial vehicle aerial photography system, a patrol station and a ground communication station. The unmanned aerial vehicle consists of a flight control system, an obstacle avoidance system, a GPS positioning module, a camera and a picture transmission module. The ground communication station controls the unmanned aerial vehicle through wifi signals. The BIM center comprises an image processing module, an image recognition module, a three-dimensional modeling module and a sensor module. The server center consists of a control system, an alarm system and a defect detection system. The unmanned aerial vehicle is adopted for inspection, high-altitude operation and control by personnel are not needed, and a reference is provided for the detection of the unmanned aerial vehicle in the industrial indoor environment. Meanwhile, the evolution state of the wind turbine generator along with time can be observed by combining the BIM technology, and a good foundation is provided for later detection, maintenance and redesign.
Description
Technical Field
The invention belongs to the technical field of wind power detection, relates to a wind power detection system, and particularly relates to an unmanned aerial vehicle wind power detection system and method based on a BIM (building information modeling) technology.
Background
The wind turbine blade is one of the key parts of the wind turbine, and the performance of the wind turbine blade directly affects the performance of the whole system. According to statistics, the accident occurrence period of the wind power plant is mostly in the strong wind period, and the accident generated by the blades accounts for 30% of the accident, which inevitably causes high maintenance cost. In addition, the wind power tower is a bearing foundation of a wind turbine, plays a supporting role in the wind generating set, can absorb the vibration of the set, and is made of materials with enough rigidity and strength. However, wind turbine generators are often concentrated in areas with severe natural conditions, and wind power resources are distributed unevenly throughout the year, so that safety accidents of towers occur frequently, and economic benefits of wind power plants are seriously damaged.
Therefore, the defect detection of the blade and the tower needs to be carried out regularly, early detection is carried out, measures are taken as soon as possible, and the problem is solved in a sprouting state. The detection of the blade and the tower is mostly based on manual detection, and the traditional means such as blade detection is expected to be observed by a telescope and detected by a spider man, however, the traditional blade detection has the following defects: (1) the detection efficiency is low, and the labor intensity of workers is high; (2) high-altitude operation and high detection cost; (3) the detection time is long, and the loss of the shutdown generated energy is large.
The unmanned aerial vehicle plays a role of an aerial vehicle and is an efficient tool capable of acquiring live-action data; the real space data of the wind turbine generator set can be obtained by matching with the high-definition camera, and the three-dimensional model is finally obtained through algorithm correction and processing. At present, the wind power industry is technically more advanced, and unmanned planes are controlled to carry out blade inspection, such as Chinese patents with application numbers of 201610259711.X and 201611021798.3. But utilize unmanned aerial vehicle to mostly be blade detection to wind-powered electricity generation in the relevant patent that has disclosed, it is very strong to the detection limitation at other positions of wind turbine generator system.
The BIM technology can express various elements of the wind turbine generator in a digital form, so that the digitization of the generator is realized, and the visualization is carried out on three dimensions. In the BIM design, each professional designer can realize data sharing through the same platform, and the working efficiency is greatly improved. The BIM technology is applied to the wind power industry and has great advantages for the operation and maintenance of the wind turbine generator.
In view of the above, the invention provides an unmanned aerial vehicle wind power detection system and method based on the BIM technology.
Disclosure of Invention
The invention aims to provide an unmanned aerial vehicle wind power detection system based on a BIM technology, which aims to solve the problems of low detection efficiency, high detection cost, high-altitude operation of personnel and the like of the traditional wind turbine generator, reduce safety accidents of a wind power tower and reduce economic loss of a wind power plant. In addition, the system provides a data sharing platform for a plurality of professional technicians, when data of a certain professional changes, other professional researchers can rapidly obtain changed information, and work efficiency is improved.
The technical scheme adopted by the invention for solving the problems is as follows: an unmanned aerial vehicle wind power detection system based on a BIM technology is characterized in that Tekla software is adopted, and an initial three-dimensional model of a wind turbine generator is established according to parameters of a tower, blades, an engine room, a hub and the like in a design file; on the basis of the initial three-dimensional model, the unmanned aerial vehicle wind power detection system based on the BIM technology comprises: the unmanned aerial vehicle subsystem, the BIM center and the server center; the unmanned aerial vehicle subsystem includes unmanned aerial vehicle, patrols and examines station and ground communication station, BIM center includes image processing module, image recognition module, three-dimensional modeling module and sensor module, server center includes control system, alarm system and defect detecting system.
The working method of the unmanned aerial vehicle wind power detection system based on the BIM technology is characterized by comprising the following specific detection processes:
(1) the control system of the server center firstly receives the position information of the target wind turbine generator and then transmits the position information of the wind turbine generator to be detected to the unmanned aerial vehicle, the unmanned aerial vehicle flies along the target wind turbine generator according to the GPS positioning module, multi-angle macro shooting is carried out through an onboard camera, and meanwhile data are transmitted to the BIM center in real time;
(2) an image processing module of the BIM center performs image preprocessing and image segmentation on image data transmitted by the unmanned aerial vehicle, then sends the image data to an image recognition module to obtain optimized parameters of blades and towers of the wind turbine generator, sends the optimized information to a three-dimensional model module, performs coverage check on an initially established three-dimensional model, performs defect analysis on a target part to obtain position information of a defect, and sends corresponding information to a server center;
(3) a control system of the server center receives defect position information sent by the BIM center and sends corresponding defect information to the unmanned aerial vehicle subsystem through the control system;
(4) the ground communication station of the unmanned aerial vehicle subsystem receives an instruction from the server center, detects the flight state of the unmanned aerial vehicle and the working state of the airborne payload, adjusts the flight attitude, carries out high-definition camera shooting on the defect part of the wind turbine generator set which needs to be mainly detected through the airborne high-definition camera, and sends an image result to the BIM center;
(5) an image processing module of the BIM center performs operations such as calibration, denoising and enhancement on an image, then an image recognition module receives processed image information, the processed image information is recognized and compared with defect types stored by a defect detection system in a server center to obtain accurate defect types, marks are made at corresponding positions of a three-dimensional modeling module, and an alarm system gives an alarm; and simultaneously, storing the image data into a defect detection system for next detection, identification and comparison.
In the unmanned aerial vehicle subsystem, the unmanned aerial vehicle is a general name of an unmanned aerial vehicle outside a tower and an unmanned aerial vehicle inside the tower, the unmanned aerial vehicle outside the tower is used for detecting wind power blades and the outer surface of the tower, and the unmanned aerial vehicle inside the tower is used for detecting the internal structure of the tower; the inspection station consists of an in-tower inspection station and an out-tower inspection station, the unmanned aerial vehicle outside the tower flies and lands from the out-tower inspection station, and the unmanned aerial vehicle inside the tower flies and lands from the in-tower inspection station; the inspection station in the tower is arranged at the bottom of the tower.
Further, a miniature base station is arranged in the tower from low to high every 8m to ensure that the unmanned aerial vehicle in the tower has good communication when detecting the internal structure of the tower and solve the weak point of the GPS signal in the tower.
The unmanned aerial vehicle keeps away the barrier in the tower includes six directions in upper and lower, left and right, preceding, back to reduce the possibility that the inside unmanned aerial vehicle of pylon explodes the machine.
Further, unmanned aerial vehicle's paddle and camera all have the protection casing protection in the tower, the protection casing is the carbon fiber material of arc sphere and makes.
Further, unmanned aerial vehicle in the tower and unmanned aerial vehicle outside the tower are controlled by server center, need not the manual control, unmanned aerial vehicle is last to have arranged GPS orientation module.
Further, because many rotor unmanned aerial vehicle possess stably hover, control advantages such as simple, the reliability is high, easy maintenance, so many rotor unmanned aerial vehicle are all selected to unmanned aerial vehicle in the tower, outside the tower.
Further, the unmanned aerial vehicle outside the tower can resist at least 5-level wind speed, and the maximum flying height is more than 150 m.
The unmanned aerial vehicle outside the tower and the unmanned aerial vehicle inside the tower are both provided with a telephoto zooming pan-tilt camera and a high-resolution X-ray CCD camera, the pan-tilt camera is a Zenmulse Z30 pan-tilt camera, and the X-ray CCD camera is an enhanced high-resolution camera of Photonic Science.
Further, with the cloud platform camera reaches the unmanned aerial vehicle camera lens that X ray CCD camera cooperation was used can carry out 30 times optics and zoom, 6 times digital zooms, and the equivalent focal length is 29~872mm, and the minimum focus distance is 10~1200mm, and the optical zoom under the optics wide angle zoom the translation rate of moving is 4.6 s.
Further, the telephoto zoom holder camera is used for detecting surface defects of blades (cracks, fractures and the like) and towers (cracks, aging and the like); the X-ray CCD camera is used for detecting the blade pores, inclusion isovolumetric defects and welding defects in the tower welding seam.
The detection of the unmanned aerial vehicle outside the tower comprises macroscopic inspection of a wind power plant and microscopic inspection of a wind turbine generator.
Further, the macro-inspection of the unmanned aerial vehicle outside the tower is to check whether the wind turbine generator collapses, whether the blade is broken, whether the tower has obvious damage and other major accidents, the micro-inspection of the unmanned aerial vehicle outside the tower is that the unmanned aerial vehicle is close to the target part, and the blade of the wind turbine generator, the external surface condition of the tower and the like are mainly checked.
Further, when the unmanned aerial vehicle outside the tower patrols and examines the wind power blades, sudden changes of wind direction and wind speed need to be considered so as to ensure that the unmanned aerial vehicle cannot collide with the blades.
The inspection of the unmanned aerial vehicle in the tower is to detect the inner surface of the tower and other structures.
In the BIM center, Tekla software developed by Tekla company is adopted by the three-dimensional modeling module; a GPS positioning sensor is arranged at the head of the wind turbine generator; a wind speed sensor and a wind direction sensor are arranged on the wind turbine generator blade; sensors are arranged on key stress positions of a tower welding position, a flange connecting position, a cabin fish tower connecting position and the like of the tower, and stress and displacement information of corresponding positions is collected; and the information collected by the sensor is sent to the three-dimensional modeling module, and the mark is made at the corresponding position.
Furthermore, the weakest part of the wind turbine tower is often the welding seam part, rapid numbering and attribute definition of the welding seam can be realized in the model through secondary development of the three-dimensional modeling software Tekla, statistics of welding seam information is realized, and accordingly fine management of the welding seam is realized when the unmanned aerial vehicle detects the tower.
Further, the BIM center and the server center can be in two-way communication, the sensor modules can be in one-way communication with the server center, data measured by the sensor modules are transmitted to the server center, a control module of the server center transmits the data to a three-dimensional modeling module of the BIM center, and the three-dimensional modeling module makes information marks at corresponding positions of a three-dimensional model.
Furthermore, the three-dimensional model established by the three-dimensional modeling module is rendered, so that a high-quality model and video display data are manufactured, and the model can be more intuitively understood by each professional conveniently.
Image data shot by the unmanned aerial vehicle is transmitted to the image processing module of the BIM center, and the image processing module carries out operations such as calibration, denoising and enhancement on the image data.
Further, the image processing module transmits the processed image data to the image recognition module, obtains an accurate defect type by comparing the processed image data with the defect type stored in the defect detection system of the server center, and marks the corresponding part of the three-dimensional model; and storing the image data in a defect detection system.
Furthermore, the image recognition technology of the image recognition module is a deep learning convolutional neural network technology based on Google open elements, and can accurately recognize the defects of sand holes, cracks and peeling of the blades, tower welding seam defects, flange deformation and the like.
Further, the three-dimensional model of the wind turbine generator is updated once when the unmanned aerial vehicle detects the wind turbine generator, and the system automatically stores the detection result and the model of the wind turbine generator at last time before updating by covering every time.
Furthermore, the three-dimensional modeling software is developed for the second time, the tower welding seam is rapidly numbered and defined in attributes in the model, and the fine management of the tower welding seam can be realized.
Compared with the prior art, the invention has the following advantages and effects: the defects of traditional wind turbine blade detection and tower detection are obvious: the detection efficiency is low, the labor intensity of workers is high, high-altitude operation is required, the danger is high, and the economic benefit of the wind power plant is not improved. The unmanned aerial vehicle wind power detection system based on the BIM technology provided by the invention adopts the unmanned aerial vehicle to carry out routing inspection, so that high-altitude operation of personnel is not needed, and accidents are reduced; and unmanned aerial vehicle need not personnel and controls, can be by system automatic control, and the frequency of detection can be arranged by wind-powered electricity generation field staff by oneself, not only is limited to conventional inspection and maintenance inspection, improves greatly to the promptness of defect discovery. In addition, the existing unmanned aerial vehicle detection indoor application is few, particularly the industrial application environment with complex indoor environment, and the unmanned aerial vehicle detection in the tower provided by the invention provides a reference for the unmanned aerial vehicle detection in the industrial indoor environment.
Meanwhile, the BIM technology is introduced, wind power detection is expanded to three dimensions, the evolution state of the wind turbine generator along with time can be observed by combining the characteristics of the BIM technology, and a good foundation is provided for later detection, maintenance and redesign.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention.
Fig. 2 is a schematic view of unmanned aerial vehicle blade detection according to the present invention.
FIG. 3 is a schematic diagram of the system detection process of the present invention (the figure shows the detection steps of the system digitally).
Detailed Description
The present invention will be described in further detail below by way of examples with reference to the accompanying drawings, which are illustrative of the present invention and are not to be construed as limiting the present invention.
As shown in fig. 1, the invention provides an unmanned aerial vehicle wind power detection system and method based on the BIM technology, and the system comprises an unmanned aerial vehicle subsystem, a BIM center and a server center. The unmanned aerial vehicle subsystem includes unmanned aerial vehicle, patrols and examines station, ground communication station. The unmanned aerial vehicle consists of a flight control system, an obstacle avoidance system, a GPS positioning module, a camera and a picture transmission module. The inspection station consists of an inspection station outside the tower and an inspection station inside the tower. The ground communication station controls the unmanned aerial vehicle through wifi signals. The BIM central subsystem comprises an image processing module, an image recognition module, a three-dimensional modeling module and a sensor module. The server center consists of a control system, an alarm system and a defect detection system.
Example 1:
in this embodiment, an unmanned aerial vehicle wind power detection system and method based on the BIM technique can solve the problems of low detection efficiency, high detection cost, high-altitude operation of personnel and the like of the traditional wind turbine blades, and the specific detection method for the wind turbine blades is as follows:
firstly, a three-dimensional model of the wind turbine generator is established by utilizing three-dimensional modeling software Tekla according to parameters of a tower, blades, a cabin, a hub and the like in a wind turbine generator design file. When the unmanned aerial vehicle detects the wind power blade, the GPS positioning sensor of the wind turbine generator head sends the position of the head back to the control system of the server center, then the control system sends an instruction to the ground communication station in the unmanned aerial vehicle system, the ground communication station sends the instruction to the unmanned aerial vehicle of the inspection station outside the tower, the unmanned aerial vehicle flies along a long distance (more than 20 m) away from the target unit according to the positioning, the macro detection is carried out on the blade through the telephoto zoom holder camera, and the image data is transmitted to the BIM center in real time.
And an image processing module of the BIM center processes the image transmitted by the unmanned aerial vehicle and then sends the processed image to an image recognition module so as to obtain the optimized parameters of the blades of the wind turbine generator, and the optimized information is sent to a three-dimensional model module so as to perform coverage check on the initially established three-dimensional model. Meanwhile, defect analysis is carried out on a target part, if major accidents such as collapse, blade breakage and obvious damage to a tower frame of the wind turbine generator are found, information is immediately sent to a server center, and an alarm system sends out alarm warning; and if surface defects such as cracks and the like of the blades of the wind turbine generator are found, sending position information of the corresponding defects to a server center.
And the server center receives the defect position information sent by the BIM center and sends the corresponding defect position to the unmanned aerial vehicle outside the tower through the control module.
The ground communication station of the unmanned aerial vehicle subsystem receives an instruction from the server center, adjusts the flight attitude of the unmanned aerial vehicle through controlling the flight control system of the unmanned aerial vehicle, zooms the pan-tilt camera through telephoto, carries out high-definition shooting on the defect part of the wind turbine generator system needing important detection by combining the X-ray CCD camera, and sends an image result to the BIM center. In the detection process of flying to the key position of blade at unmanned aerial vehicle, the sudden change of wind direction, wind speed is inevitable in wind-powered electricity generation field, must ensure for this reason that the relative blade of unmanned aerial vehicle position also does not take place the collision accident when the wind speed increases suddenly, and the relative blade of patrolling and examining of unmanned aerial vehicle treats the observation face: the windward side, leeward side, front and rear edges should be in their "down wind" positions. The specific method comprises the following steps:
when the front edge of the blade A and the head of the cabin (appearing in the range of the dotted line shown in the figure 2) in the figure 2 are detected by the unmanned aerial vehicle, the unmanned aerial vehicle is positioned at the downwind position of the wind turbine generator, if the wind speed is suddenly increased, the unmanned aerial vehicle is blown away from the front edge of the blade A, and the collision between the unmanned aerial vehicle and the blade can be effectively avoided; when the cabin head is present in other areas, the collision accident of the unmanned aerial vehicle and the blade can be caused. And when the leeward side, the windward side and the rear edge of the blade A are inspected, the area range of the head of the engine room to be adjusted can be determined by a similar method.
An image processing module of the BIM center performs operations such as calibration, denoising and enhancement on an image, then an image recognition module receives processed image information, the processed image information is recognized and compared with defect types stored by a defect detection system in a server center to obtain accurate defect types, marks are made at corresponding positions of a three-dimensional modeling module, and an alarm system gives an alarm; and simultaneously, storing the image data into a defect detection system for next detection, identification and comparison.
Example 2:
the utility model provides an unmanned aerial vehicle wind-powered electricity generation detecting system and method based on BIM technique, can solve traditional wind turbine generator system pylon detection inefficiency, personnel high altitude construction scheduling problem, uses the inside detection of pylon here as an example, and its concrete detection method to wind turbine generator system pylon is as follows:
firstly, a three-dimensional model of the wind turbine generator is established by utilizing three-dimensional modeling software Tekla according to parameters of a tower, blades, a cabin, a hub and the like in a wind turbine generator design file. When the wind power plant detects the interior of the wind turbine tower, the ground communication station in the unmanned aerial vehicle system obtains an instruction of a control system of the server center, and sends an inspection instruction to the unmanned aerial vehicle of the inspection station in the tower, and the unmanned aerial vehicle flies from low to high from the bottom of the tower and detects the interior surface of the tower through the X-ray CCD camera, so that image data are transmitted to the BIM center in real time.
And an image processing module of the BIM center processes the image transmitted by the unmanned aerial vehicle and then sends the processed image to an image recognition module so as to obtain optimized parameters inside the tower of the wind turbine generator, and the optimized information is sent to a three-dimensional model module so as to perform coverage checking on the initially established three-dimensional model. Meanwhile, defect analysis is carried out on the target part, if major accidents such as breakage and collapse occur in the tower of the wind turbine generator, information is immediately sent to a server center, and an alarm system sends out alarm warning; and if the defects of cracks, incomplete penetration and the like of the welding line of the wind turbine tower are found, sending the position information of the corresponding defects to the server center.
And the server center receives the defect position information sent by the BIM center and sends the corresponding defect information to the unmanned aerial vehicle in the tower through the control system.
The ground communication station of the unmanned aerial vehicle subsystem receives an instruction from the server central control module, adjusts the flight attitude of the unmanned aerial vehicle, flies by attaching to the surface of a tower target, and simultaneously carries out X-ray detection on the defect part of the wind turbine generator set which needs to be mainly detected through the X-ray CCD camera, and sends an image result to the BIM center.
An image processing module of the BIM center performs operations such as calibration, denoising and enhancement on an image, then an image recognition module receives processed image information, the processed image information is recognized and compared with defect types stored by a defect detection system in a server center to obtain accurate defect types, numbers and attribute definitions are made at corresponding positions of a three-dimensional modeling module, and an alarm system gives an alarm; and simultaneously, storing the image data into a defect detection system for next detection, identification and comparison.
It should be noted that, the three-dimensional model of the wind turbine generator is updated once each time the unmanned aerial vehicle detects the wind turbine generator, and the system automatically stores the detection result and the model of the wind turbine generator last time before the update is covered each time, so that a good basis is provided for later detection, maintenance and redesign.
Those not described in detail in this specification are well within the skill of the art.
Although the present invention has been described with reference to the above embodiments, it should be understood that the scope of the present invention is not limited thereto, and that various changes and modifications can be made by those skilled in the art without departing from the spirit and scope of the present invention.
Claims (3)
1. An unmanned aerial vehicle wind power detection system based on a BIM technology is characterized in that Tekla software is adopted, and an initial three-dimensional model of a wind turbine generator is established according to a design file; on the basis of the initial three-dimensional model, the unmanned aerial vehicle wind power detection system based on the BIM technology comprises: the unmanned aerial vehicle subsystem, the BIM center and the server center; the unmanned aerial vehicle subsystem comprises an unmanned aerial vehicle, a patrol station and a ground communication station, the BIM center comprises an image processing module, an image identification module, a three-dimensional modeling module and a sensor module, and the server center comprises a control system, an alarm system and a defect detection system;
the unmanned aerial vehicle comprises an unmanned aerial vehicle outside the tower and an unmanned aerial vehicle inside the tower; the inspection station comprises an in-tower inspection station and an out-tower inspection station, and the in-tower inspection station is arranged at the bottom of the tower; a plurality of miniature base stations are arranged inside the tower from low to high, so that the unmanned aerial vehicle in the tower can be ensured to have good communication when detecting the internal structure of the tower, and the defect of weak GPS signals inside the tower is overcome; the unmanned aerial vehicle outside the tower and the unmanned aerial vehicle inside the tower are both provided with a telephoto zoom pan-tilt camera and a high-resolution X-ray CCD camera; the detection of the unmanned aerial vehicle outside the tower comprises macro inspection of a wind power plant and micro inspection of a wind turbine; when the unmanned aerial vehicle outside the tower patrols and examines the wind power blade, the control system controls the unmanned aerial vehicle to be in the downwind position of the blade surface to be observed so as to prevent the collision between the unmanned aerial vehicle and the blade caused by sudden change of wind speed.
2. The BIM technology-based unmanned aerial vehicle wind power detection system according to claim 1 or 2, wherein the three-dimensional model of the unmanned aerial vehicle is updated every time the unmanned aerial vehicle detects the wind turbine generator, and the system automatically stores the last detection result and the model thereof before each coverage update.
3. The working method of the BIM technology-based unmanned aerial vehicle wind power detection system according to any one of claims 1 or 2, characterized in that the specific detection process is as follows:
(1) the control system of the server center firstly receives the position information of the target wind turbine generator and then transmits the position information of the wind turbine generator to be detected to the unmanned aerial vehicle, the unmanned aerial vehicle flies along the target wind turbine generator according to the GPS positioning module, multi-angle macro shooting is carried out through an onboard camera, and meanwhile data are transmitted to the BIM center in real time;
(2) an image processing module of the BIM center performs image preprocessing and image segmentation on image data transmitted by the unmanned aerial vehicle, then sends the image data to an image recognition module to obtain optimized parameters of blades and towers of the wind turbine generator, sends the optimized information to a three-dimensional model module, performs coverage check on an initially established three-dimensional model, performs defect analysis on a target part to obtain position information of a defect, and sends corresponding information to a server center;
(3) a control system of the server center receives defect position information sent by the BIM center and sends corresponding defect information to the unmanned aerial vehicle subsystem through the control system;
(4) the ground communication station of the unmanned aerial vehicle subsystem receives an instruction from the server center, detects the flight state of the unmanned aerial vehicle and the working state of the airborne payload, adjusts the flight attitude, carries out high-definition camera shooting on the defect part of the wind turbine generator set which needs to be mainly detected through the airborne high-definition camera, and sends an image result to the BIM center;
(5) an image processing module of the BIM center operates the image, then an image recognition module receives the processed image information, the processed image information is recognized and compared with the defect types stored by a defect detection system in the server center to obtain accurate defect types, marks are made at the corresponding parts of the three-dimensional modeling module, and an alarm system gives an alarm; and simultaneously, storing the image data into a defect detection system for next detection, identification and comparison.
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