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).

An investigation of the use of active infrared thermography to detect localized surface anomalies in lumber.

Efforts are being pursued to improve and automate processes for grading, trimming, and cutting up softwood and hardwood lumber by automated, non-contact, non-labor-intensive methods. Existing technology for detecting defects in lumber has focused heavily on the use of charged coupled device scanners or cameras, but these devices are limited by inherent color differences of the material. Thermography has been proven to detect knots in lumber, but the use of active thermography has not been investigated in terms of detecting dents, holes, and gouges. This research focused on four heating techniques, i.e. defect side heating, back side heating, forced air heating, and pulsed thermography, to detect dents, holes, gouges, and knots. All four heating methods proved successful for at least two defect types. Implementation of these techniques in an industrial setting will depend on the requirements of the manufacturer and the physical limitations of the industrial line.

Process monitoring evaluation and implementation for the wood abrasive machining process.

Wood processing industries have continuously developed and improved technologies and processes to transform wood to obtain better final product quality and thus increase profits. Abrasive machining is one of the most important of these processes and therefore merits special attention and study. The objective of this work was to evaluate and demonstrate a process monitoring system for use in the abrasive machining of wood and wood based products. The system developed increases the life of the belt by detecting (using process monitoring sensors) and removing (by cleaning) the abrasive loading during the machining process. This study focused on abrasive belt machining processes and included substantial background work, which provided a solid base for understanding the behavior of the abrasive, and the different ways that the abrasive machining process can be monitored. In addition, the background research showed that abrasive belts can effectively be cleaned by the appropriate cleaning technique. The process monitoring system developed included acoustic emission sensors which tended to be sensitive to belt wear, as well as platen vibration, but not loading, and optical sensors which were sensitive to abrasive loading.