Abstract
This paper presents a novel technique of monitoring laser surface remelting (LSR) via measurements of process generated acoustic emission (AE). The LSR conditions include a variable laser power level and an ambient air or argon 5.0 inert gas atmosphere. The microstructure and microhardness of the remelted surface layer are evaluated. The recorded AE signal datasets are analysed via the wavelet decomposition technique. The resulting energy and energy proportions of approximation and detail coefficients are calculated. The decomposed AE signal features are evaluated in correlation with the LSR process conditions. A supervised machine learning cubic support vector machine classifier type is used for the classification of laser pulses. The experimental results show an overall 98% classification accuracy into the corresponding LSR laser power level and atmosphere conditions, confirming the utility of monitoring the LSR process and the resulting material surface layer characteristics via the AE wavelet decomposition technique.
Highlights
Laser surface remelting (LSR) is a selective heat treatment process used in manufacturing for improving the surface durability and performance of a variety of engineering products, such as tools, dies, gears, camshafts and other machine components
Article history: This paper presents a novel technique of monitoring laser surface remelting (LSR) via Received 20 August 2021 measurements of process generated acoustic emission (AE)
During the LSR process, a laser pulse with high energy concentration is directed onto a selected surface area of the specimen
Summary
Laser surface remelting (LSR) is a selective heat treatment process used in manufacturing for improving the surface durability and performance of a variety of engineering products, such as tools, dies, gears, camshafts and other machine components. The proper application of the LSR process to a selected surface of a component enables the capability of operation in environments characterised by severe mechanical and thermal stress. The LSR process is commonly applied to carbon steels but can be used for magnetisation of austenitic stainless steels, for selective processing of inhomogeneous cast iron microstructures or other applications [1e3]. The LSR process conditions in combination with the substrate material define the resulting characteristics of the surface laser hardened zone (LHZ). LSR parameters such as laser power, laser pulse time, worktable travel speed, gas atmosphere type and steel carbon content exert an influence on the obtained microstructure, hardness and LHZ depth [5e8]
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