Dalian University of Technology

Tao Sun

Ximing Sun

Shuo Zhang

Yuhu Wu

Jibang Li

Zongyang Lv

Zhenyu Wu

The present invention belongs to the technical field of fault diagnosis of aero-engines, and provides a method for fault diagnosis of an aero-engine rolling bearing based on random forest of power spectrum entropy. Aiming at the above-mentioned defects existing in the prior art, a method for fault diagnosis of an aero-engine rolling bearing based on random forest is provided, wherein test measured data for an aero-engine rolling bearing provided by a research institute are used for establishing a training dataset and a test dataset first; and based on an idea of fault feature extraction, time domain statistical analysis and frequency domain analysis are conducted on original collection data by adopting wavelet analysis; thereby realizing effective fault diagnosis from the perspective of engineering application.

Method for fault diagnosis of an aero-engine rolling bearing based on random forest of power spectrum entropy

An air, sea and underwater tilt tri-rotor UAV capable of performing vertical take-off and landing. By the method for controlling a submerged floating device and a tilt tri-rotor device, the UAV is switched among the vertical take-off and landing mode, fixed wing mode, water surface sailing mode and underwater submerging mode.

Air, sea and underwater tilt tri-rotor UAV capable of performing vertical take-off and landing

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Liaoning, China

Tao Sun