The use of frequency and wavelet analysis for monitoring surface quality of wood machining applications.
The research described in this study is part of a project to provide the technology and theory to quantify surface quality for a variety of wood and wood-based products. The ultimate goal is to provide a means of monitoring trends in surface quality, which can be used to discriminate between "good" products and "bad" products (the methods described in this research are not intended to provide "grading" of individual workpieces) as well as to provide information to the machine operator as to the source of poor-quality machined surfaces. This research investigates the use of both frequency domain analysis as well as the more advanced joint time frequency analysis (JTFA). The disadvantages of traditional frequency analysis as well as the potential of the JTFA are illustrated. Sample surface profiles from actual machining defects were analyzed using traditional frequency analysis. A surface with multiple machining defects was analyzed with both traditional frequency analysis and JTFA (harmonic wavelet). Although the analysis was empirical in nature, the results show that the harmonic wavelet transform is able to detect both stationary and non-stationary surface irregularities as well as pulses (localized defects).
Department of Wood and Paper Science, North Carolina State University, North Carolina 27695, USA. richard_lemaster@ncsu.edu
Richard L
RL
Lemaster