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Timely sensing the abnormal condition of the bearings plays a crucial role in ensuring the normal and safe operation of the rotating machine. Most traditional bearing fault diagnosis methods are developed from machine learning, which might rely on the manual design features and prior knowledge of the faults. In this paper, based on the advantages of CNN model, a two-step fault diagnosis method developed from wavelet packet transform (WPT) and convolutional neural network (CNN) is proposed for fault diagnosis of bearings without any manual work. In the first step, the WPT is designed to obtain the wavelet packet coefficients from raw signals, which then are converted into the gray scale images by a designed data-to-image conversion method. In the second step, a CNN model is built to automatically extract the representative features from gray images and implement the fault classification. The performance of the proposed method is evaluated by a real rolling-bearing dataset. From the experimental study, it can be seen the proposed method presents a more superior fault diagnosis capability than other machine-learning-based methods.

Suggestions for improving the efficiency and life expectancy of wind turbine blades are proposed in this paper. A new airfoil shape with wide leading edge nose and large camber has been investigated by numerical simulation with a range of attack angles. The results show that the lift-drag ratio of the airfoil is greater than that of the conventional airfoil at large attack angles (α>20°). Changing the local roughness on blade surfaces to improve the wind turbine performance is discussed in the paper. A new mechanism and method of analysing life expectancy of a blade with flow induced vibration in oscillating flow has been given. It is proved that the damping of blade material and structure has great influence on the endurance lifetime of blades. The investigation indicates further that the equilibrium amplitude of vibration greatly influences the lifetime of blades. Changing the damping characteristic of a blade may significantly vary its equilibrium amplitude, so extending the life expectancy of blades. This paper provides the foundations for further study.

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