Oil monitoring for wind turbine gearboxes can reflect wear and lubrication conditions, and better identify pits on the tooth surface, fatigue wear, and other early faults. However, oil monitoring with one or several single predicting models brings inaccuracy due to the intrinsic merits and demerits of the models. In this work, oil monitoring and fault pre-warning of wind turbine gearboxes were studied based on oil inspection data of three wind turbines that have been working continuously for 3.5 years. The Grey Model (GM) and the Double Exponential Smoothing (DES) were combined by a modified inverse-variance weighting method proposed in this work, which used relative errors to calculate weight coefficients, reducing the errors and improving the accuracy as a whole. The predicted data were compared with the measured data to verify the predicting accuracy. Subsequently, a statistical method and linear regression method were adopted to jointly develop a pre-warning threshold for the oil inspection data. Comparing the predicted data with the threshold, the results showed that one of the wind turbines was in a warning state. The prediction was validated by an endoscope inspection of the gearbox, which found that some parts were slightly worn.

The throughput of a belt conveyor system is the primary design parameter when considering a new installation, determined by the cross-section of the material on the belt, coupled with the belt speed. Optimizing this area not only improves efficiency, but also minimizes capital costs through the optimal selection of equipment. Whilst speed-related optimization has seen considerable attention, the cross-sectional area has largely been neglected due to existing design constraints of the system. Conventional belt conveyors typically utilize a 3-idler troughing configuration, which forms a trapezoidal cross-section with a parabolic surcharge. The rigidity of this support directly limits the geometry of the cross-section that may be considered. A new conveyor system developed at the University of Newcastle supports the conveyor belt by a rail-based carriage, with no relative movement between the belt and carriage. This configuration allows the cross-section of the belt to be freely optimized in order to maximize the material throughput for a given belt width, or alternatively to minimize the belt width for a given throughput. This article utilizes the calculus of variations to optimize the form of this cross section, and demonstrates that an increase in throughput of up to 30% is possible, compared to troughed installations.