Mechanical characterization and analysis of tensile fracture modes of ultrasonically stir cast Al6082 composites reinforced with Cu powder premixed Metakaolin particles

The major drawback observed in the ceramic particles reinforced aluminium matrix composites (AMCs) is the reduction of ductility. Incorporating fine metallic particles along with the ceramic reinforcements in the aluminium matrix tends to improve the ductility of the AMCs. This work highlights the effects of dispersing micro (5-10 μm) copper (Cu) particles along with the nano (100-400 nm) Metakaolin particles in the Al6082 matrix. The Metakaolin particles were premixed with Cu powder by means of manual stirring followed by ball milling before embedding into the Al6082 matrix. The total reinforcement composition was maintained as 7.5 wt.% in which 2.5 wt.% consisted of Cu powder. The composites were synthesized using ultrasonication-aided stir casting process. The composites samples were subjected to T6 heat treatment before performing mechanical characterization. The composites with Cu powder premixed Metakaolin particles showed improvement in tensile strength, ductility, compressive strength and hardness. The microstructure evaluation of the composites was performed by Scanning Electron Microscope (SEM) and Optical Microscope (OM). The tensile fracture modes were studied by analysing the fracture surface morphology using SEM

A hybrid approach for fault diagnosis of spur gears using Hu invariant moments and artificial neural networks

Achieving a reliable fault diagnosis for gears under variable operating conditions is a pressing need of industries to ensure productivity by averting unwanted breakdowns. In the present work, a hybrid approach is proposed by integrating Hu invariant moments and an artificial neural network for explicit extraction and classification of gear faults using time-frequency transforms. The Zhao-Atlas-Marks transform is used to convert the raw vibrations signals from the gears into time-frequency distributions. The proposed method is applied to a single-stage spur gearbox with faults created using electric discharge machining in laboratory conditions. The results show the effectiveness of the proposed methodology in classifying the faults in gears with high accuracy