Fault diagnosis method for wind-power gear case

Abstract

The invention discloses a fault diagnosis method for a wind-power gear case. The fault diagnosis method comprises the following steps: vibration signals and rotating speed pulse signals of the wind-power gear case in operation are acquired, and corresponding power generator output power is also acquired; order time spectrum analysis is performed on the acquired vibration signals and the rotating speed pulse signals so that meshing vibration energy is obtained; the meshing vibration energy and the corresponding power generator output power are fit via a least square method so that a curve of change of the meshing vibration energy along with the power generator output power is obtained; and mean value normalization processing is performed on the real-time meshing vibration energy obtained by utilizing the curve after the order time spectrum analysis is performed on the vibration signals and the rotating speed pulse signals acquired in real time so that the normalized real-time meshing vibration energy is obtained, and fault diagnosis for the wind-power gear case is realized via analyzing the normalized real-time meshing vibration energy. Influence of load change of the wind-power gear box on the vibration signals of the wind-power gear box is weakened so that reliability of fault diagnosis is enhanced.

Description

【Technical Field】 [0001] The invention belongs to the technical field of fault diagnosis of rotating machinery, and particularly relates to a fault diagnosis method for a wind power gearbox. 【Background technique】 [0002] In the past ten years, wind energy has become an important part of the energy system of all countries in the world. Due to the particularity of wind energy, wind turbines are mostly installed in areas with rich wind energy such as Gobi, mountainous areas, and islands. However, these areas have harsh climate conditions and large temperature differences between day and night. Components are extremely prone to failure during operation, causing the unit to shut down and causing huge economic losses. The gearbox is the most critical component for fault monitoring and diagnosis of wind turbines. Whether it can operate safely and efficiently has a direct impact on the reliability of wind turbines. Gearbox fault diagnosis is generally divided into four steps: signal ...

AI Technical Summary

Problems solved by technology

Unstable operating conditions will also cause dynamic changes in component failure characteristics. Sometimes the reflection of operating condition changes in the feature layer is very similar to the changes caused by faults, which increases the difficulty of feature parameter extraction.

Since the signal instability caused by operating conditions violates the stationary assumption of traditional gearbox vibration signal processing methods, some characteristic parameters that are strong in stationary conditions fail in fault diagnosis of wind turbine gearboxes

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