Oriented strandboard (OSB) is a wood-based composite product with the largest market share for residential and commercial construction. OSB composite products have introduced variability in their physical and mechanical properties due to their raw material and process variation. Reliable in-line non-destructive evaluation (NDE) devices are needed to rapidly determine OSB panel product quality during and after the manufacturing process. Wood specific gravity (SG) and moisture content (MC) play an important role in the wood composite manufacturing process. A real-time after-press monitoring device for locating SG and MC variations can supply information needed to control and improve mat formation, hot press schedules, detect MC-related problems, reduce product variation, and perform final product quality inspection. No real-time non-contact NDE methods are available for simultaneous detection of MC and SG variation. In this research, the radio frequency (RF) scanning technique was used to evaluate the MC and SG of OSB. The numerical simulation method assisted in developing RF sensors to nondestructively evaluate MC and SG of OSB composite specimens. MC and SG prediction models were derived based on RF testing results. The model behavior between relative humidity conditioned method and oven-drying conditioning method were compared. The results indicated the RF scanning technique can be successfully used as a NDE tool to measure MC and SG of OSB panel products. Numerical simulation can help deciding RF sensor geometry successfully and accurately. The MC and SG of OSB can be predicted with the models developed with the procedure used in this study. The RF scanning results are not only influenced by material physical properties, but also influenced by their MC conditioning method, such as relative humidity conditioned method and oven-drying conditioning method.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-4711 |
| Date | 09 August 2008 |
| Creators | Liu, Xiaojian |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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