A wind power blade fault detection method based on an aerial image
A wind power blade and fault detection technology, applied in image analysis, image data processing, instruments, etc., can solve the problems of inability to provide real-time detection results, high risk, high cost, etc., and achieve convenient storage and marking of blade detection conditions, The effect of reducing downtime and accident rates, and labor costs
Inactive Publication Date: 2019-05-10
HARBIN UNIV OF SCI & TECH
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[0003] At present, the fault detection methods for wind power blades mainly have the following limitations: (1) The on-site inspection of artificial blades mostly uses the visual method and the tapping method. Although the two methods are simple, they are greatly dependent on the inspectors. It is difficult to accurately judge defect damage; manual detection has limitations in accuracy, speed, and safety, and detection has problems such as low efficiency, unreliable results, high risk, and high cost; (2) detection methods based on various sensors cannot be used from multiple Identifying the detailed defects of wind turbine blade defects from different angles cannot give real-time detection results and is expensive; (3) There are few research results on wind turbine blade defect detection based on UAV aerial images, there is no efficient solution strategy, and there is no application engineering practice
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[0038] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them; based on The embodiments of the present invention and all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0039] see figure 1 , the present invention provides a technical solution: a wind turbine blade fault detection method based on aerial images, comprising the following steps:
[0040] A. UAVs collect images of wind turbine blades;
[0041] B. Construct a three-dimensional visualization model of wind power blades;
[0042] C. Leaf image defect detection;
[0043] D. Classification of leaf image defect regions.
[0044] like figure 1 As shown...
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The invention discloses a wind power blade fault detection method based on an aerial image, which takes an aerial image of an unmanned aerial vehicle as a research object, and comprises the followingsteps of: A, enhancing the aerial image of a wind power blade; B, constructing a three-dimensional visualization model of the wind turbine blade; C,carrying out wind turbine blade image defect detection; D, classifying defect areas of the wind turbine blade images; according to the wind turbine blade fault detection method, the manpower and material resource cost of wind turbine blade fault detection can be saved, the fault position is displayed, and the accuracy of wind turbine blade fault detection is effectively improved.
Description
technical field [0001] The invention relates to the technical field of wind power blades, in particular to a fault detection method for wind power blades based on aerial images. Background technique [0002] Wind turbine blades are an important part of wind turbines, and they are also one of the most vulnerable components. An efficient fault detection method for wind turbine blades can not only save manpower and material resources, but also eliminate problems in time, making the wind power generation process safer and more efficient. smooth. [0003] At present, the fault detection methods for wind power blades mainly have the following limitations: (1) The on-site inspection of artificial blades mostly uses the visual method and the tapping method. Although the two methods are simple, they are greatly dependent on the inspectors. It is difficult to accurately judge defect damage; manual detection has limitations in accuracy, speed, and safety, and detection has problems su...
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IPC IPC(8): G06T7/00G06T17/00
Inventor 高俊山段立勇邓立为
Owner HARBIN UNIV OF SCI & TECH