Early warning method for fan generator bearing fault

Abstract

The invention discloses an early warning method for a fan generator bearing fault. The early warning method for the fan generator bearing fault comprises the steps that power type data of a plurality of fans and generator bearing temperature type data are acquired; the time period is segmented, and the power type data and the generator bearing temperature type data are matched with time segments to obtain the power type data and the generator bearing temperature type data in the corresponding time segments; according to the sequence of the time segments, the following operations are repeatedly executed in each time segment, specifically, a, according to the power type data and the generator bearing temperature type data collected in the current time segment, clustering is carried out on the a fan, and an early warning value of the generator bearing temperature data is obtained; and b, comparing the generator bearing temperature data with the early warning value, and if the generator bearing temperature data is greater than the early warning value, early warning need to be carried out on a generator corresponding to the generator bearing temperature data. According to the early warning method for the fan generator bearing fault, the early warning capability of a generator bearing can be improved.

Description

technical field [0001] The invention relates to the technical field of fan generator bearing faults, in particular to an early warning method for fan generator bearing faults. Background technique [0002] Generator bearings are an important part of wind turbine generators, and they are also parts that are prone to problems. Because the wind turbines in the wind farm are distributed in clusters, the number of wind turbines is large, the distribution of wind turbines spans a large area, and the number of employees in the wind farm is small, it is impossible to carry out detailed inspections on the generator bearings of all wind turbines. At the same time, some components are It is not easy to observe and disassemble, which also increases the difficulty of investigation. How to analyze the existing operating data to give early warning before failure is the common expectation of all operating wind farms. Diagnosing abnormalities at the early stage of faults can create a good ...

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Problems solved by technology

Since the wind turbines in the wind farm are distributed in clusters, the number of wind turbines is large, the distribution of wind turbines spans a large area, and the number of employees in the wind farm is small, it is impossible to carry out detailed inspections on the generator bearings of all wind turbines. At the same time, some components are It is not easy to observe and disassemble, which also increases the difficulty of investigation

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