A method and device for wind turbine equipment fault screening and statistics

Abstract

The embodiment of the invention discloses a wind turbine unit equipment fault screening and statistical method and device. The wind turbine unit equipment fault screening and statistical method includes: performing pretreatment on initial data acquired by an equipment sensor, and acquiring a data list in a preset formant; screening the fault time and reset time corresponding to each sub fault class name from the data list through a fault screening algorithm, and calculating out the stop time corresponding to each sub fault class name; counting the stop time and the stop frequency of sub fault class names corresponding to all the main fault class names according to a corresponding relation between the main fault class names and the sub fault class names, acquiring the stop time and the stop frequency of each main fault class name, and generating a visual graph corresponding to main faults. The method and device can efficiently and accurately count faults of wind turbine unit equipment, can generate the data into the visual graph, and can allow mangers of wind power enterprises to visually know a distribution condition of various main faults of each unit.

Description

technical field [0001] The invention relates to the technical field of wind power, in particular to a method and device for fault screening and statistics of wind turbine equipment. Background technique [0002] As a renewable and clean energy, wind energy has attracted great attention from all over the world under the background of global energy crisis and environmental deterioration, especially in my country. However, there are many components in wind turbine equipment, which may cause power generation loss due to failure. Knowing the downtime of various faults, so that the distribution of various faults of each unit in each wind farm can be counted, which is of great significance for the management of wind power enterprises to make technical adjustments and quality management in the operation and maintenance of unit equipment components. [0003] As far as a wind farm is concerned, there are at least hundreds of thousands of rows of data collected each month on average, ...

AI Technical Summary

Problems solved by technology

Therefore, the occurrence of fault values ​​is completely irregular. For such a large amount of data, it is necessary to manually screen and calculate the fault distribution according to the location of the wind farm, the unit, and the fault category, which will consume a lot of human resources and time, and will cause errors in manual statistics. Larger, making the statistical accuracy not high

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