Advanced Plasma Nitriding for Aluminum and Aluminum Alloys
Low hardness and wear resistance of aluminum alloys limit their use in practical application to automotive parts. Formation of hard aluminum nitride (AlN) layer on the surface can prolong the life time of aluminum automotive parts. Plasma nitriding was selected in the present study to form AlN layer on aluminum alloys. This processing is an environmental friendly method because of its low gas and energy consumption. Normal plasma nitriding requires long processing time to successfully form AlN layer. For advancing this surface treatment, refining microstructure and micro-alloying processes are proposed to activate the formation of AlN by plasma nitriding. Bulk Mechanical Alloying is used not only to make grain-size refinement but also to carry out micro alloying with addition of 1 mass%Ti. The formation rate of AlN layer is improved from 4:2 � 10 � 5 mm/s to 20:8 � 10 � 5 mm/s by microstructure refining. In particular, since the co-formed TiN with AlN works as a template in the initial state nitriding, the micro-alloyed aluminum can be nitrided even without pre-sputtering.
Microstructure of Nitrided AA5052 Aluminum Alloy Formed by Electron Beam Excited Plasma Technique
The nitriding of the AA5052 aluminum alloy was carried out using an electron beam excited plasma (EBEP) technique. The specimen was characterized with respect to the following properties: cryslallographic structure (X-raypowder diffraction) and the surface and cross sectional microstructures of the nitrided layer (AlN layer) observed by means of scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The AlN layer was uniformly formed on the AA5052 alloy with the thickness of around 4-5 μm. In the AlN layer, pillar-shaped grains were formed perpendicular to the surface with different orientations. The average grain size near the interface between the substrate and the AlN layer was smaller than that near the surface of the AlN layer. On the surface of the AlN layer, the nitrogen concentration was high, and in the middle of the AlN layer, it had a constant concentration like aluminum, and the concentration decreased as it approached the interface. The magnesium concentrates at the interface due to the formation of MgAl 2 O 4 .
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.