Early-warning method for gear case bearing fault of wind turbine generator system

Abstract

The invention provides an early-warning method for gear case bearing faults of a wind turbine generator system. The method comprises the following steps: collecting SCADA operation data, selecting parameters, analyzing parameter correlation, determining target variables and analysis variables, conducting interval analysis of the target variables, conducting target variable cluster statistic analysis, and determining states of a wind turbine generator system, wherein the selected parameters include gear case bearing temperature, gear case oil temperature, average wind speed, generator rotatingspeed and active power, correlation coefficients between the parameters are calculated, interval analysis is conducted by taking the analysis variables as an x-axis and the target variables as a y-axis, cluster statistic analysis of the target variables in the same interval is conducted, and whether gear case bearing faults of the wind turbine generator system exist is judged on the basis of faultalarm threshold values. According to the technical solution of the invention, an operation method is simple and highly efficient, the cost is not increased additionally, and fewer system resources are occupied.

Description

technical field [0001] The invention relates to a wind turbine fault early warning method, in particular to a wind turbine gearbox bearing fault early warning method based on cluster analysis. Background technique [0002] The operating environment of wind turbines is relatively harsh, and regular inspections and post-failure repairs are required for wind turbines. Due to the particularity of wind turbines, regular maintenance chooses to stop when the wind is small, and simple maintenance or replacement of consumables for wind turbines cannot find hidden dangers of major component failures. , and within the design life cycle, once the wind turbine fails, it needs to be shut down for maintenance, which will cause large economic losses. [0003] At present, the fault statistics of wind turbines show that the components with more faults are mainly converters, gearboxes, pitch systems, control cabinets, yaw systems, etc. According to the statistics of the operation data of some ...

AI Technical Summary

Problems solved by technology

For large components, if only the passive maintenance method after failure is adopted, it is easy to cause defects to expand, maintenance time is prolonged, long-term shutdown, and economic losses are aggravated. For offshore wind turbines, the cost of offshore transportation, hoisting, and maintenance is even higher

[0004] my country's wind power equipment technology started relatively late, and the wind turbines produced and operated in the early stage were mainly imported from foreign technologies or produced by purchasing production licenses. In the process of technology introduction, digestion and localization, the rapid development of my country's wind power industry At the same time, it pays attention to the rough development of output and output value, and pays insufficient attention to technical details, resulting in the failure rate of the current operating wind turbines far exceeding that of foreign wind turbines of the same type

[0005] At present, wind turbines are equipped with a supervisory control and data acquisition system (SCADA, supervisory control and data acquisition), which can monitor parameters such as wind turbine power, speed, and temperature of large components such as gearboxes and generators, and perform simple monitoring of the operating status of major components. Judgment, but generally only set a fixed threshold for a single parameter, poor timeliness

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