Virtual shaft‐based synchronous analysis for bearing damage detection and its application in wind turbines

Abstract

Abstract A novel method for bearing damage detection is introduced in this paper. In conventionally operated bearings, when a bearing component is damaged, precise frequency response features are available for associating with the damaged components. In some applications such as in wind turbines, the speed of the shaft is very low, and the frequency contents of the damage‐induced impulsive response are low as well. Therefore, those damage‐induced vibration responses are mixed up with gearbox operational responses and hence unable to be separated with simple band‐pass or high‐pass filters. Hence, it is difficult to obtain the expected results by directly applying the traditional bearing fault diagnosis analysis methods, such as the acceleration enveloping analysis. The method proposed in this paper is to use a synthesized synchronous averaging method, which converts the bearing response from the physical shaft cycle domain into a virtual shaft cycle domain. The bearing damage feature response is generally not synchronized with the physical shaft, but in the synthesized virtual shaft, the bearing damage feature response becomes synchronous, while the signals originally synchronized with the physical shaft become nonsynchronous. Therefore, the synchronous averaging can be applied to enhance the signal‐to‐noise ratio of the bearing damage signature. Once the signal has been cleaned up in the virtual shaft cycle domain, it is then converted back into the physical shaft cycle domain for further analysis. Both numerical simulations and a wind turbine field example have been used to demonstrate the procedure and verify the feasibility for the proposed method.

Keywords

• bearing
• damage detection
• signal processing
• synchronous averaging
• virtual shaft
• wind turbine