Equipment and method for monitoring blades of wind turbine generator set

Abstract

The invention provides equipment and a method for monitoring blades of a wind turbine generator set. The equipment comprises a video collecting unit, a background image acquiring unit and an image abnormality detection unit, wherein the video collecting unit collects videos of the blades of the wind turbine generator set to acquire a video image sequence; the background image acquiring unit extracts background images from the acquired video image sequence; and the image abnormality detection unit detects whether the blades in the images in the video image sequence have abnormal image characteristics or not based on the extracted background images.

Description

technical field [0001] The present invention relates to the technical field of wind power generation, and more specifically, to a blade monitoring device and method for a wind turbine. Background technique [0002] With the increasing pressure of energy crisis and environmental pollution, countries pay more and more attention to the development and utilization of green energy. As one of the most widely developed and utilized green energy sources in the world, wind energy has developed rapidly. However, in the process of developing and utilizing wind energy in a low-temperature environment, the problem of blade icing has caused great difficulties. In this regard, a lot of research has been done on blade icing monitoring at home and abroad. For example, blade icing monitoring devices based on vibration signals, ambient temperature and humidity signals, and wind speed signals, and blade icing monitoring using infrared and acoustic emission technologies. The device, and output...

AI Technical Summary

Problems solved by technology

[0003] However, the existing blade icing monitoring devices and methods basically use indirect data to monitor icing indirectly, that is, to infer the icing phenomenon through the analysis of other signals. complex, and the operating conditions of the blades are not constant, so the indirect data may not be caused by the icing of the blades, which may easily lead to false or false reporting of icing

In addition, due to the limitations of the monitoring principle, the current blade icing monitoring devices and methods cannot detect the icing features in time. Therefore, when the icing features are found, the icing may already be serious, and it is impossible to accurately determine the location and location of the icing. The effective estimation of the amount of icing has caused great obstacles to the design of timely and effective anti-icing solutions.

Furthermore, the current blade icing monitoring devices and methods cannot meet the needs of tracking and researching the blade icing process, and at the same time cannot analyze and identify the icing behavior of the blades, which makes it difficult to design reliable and effective anti-icing solutions

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