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Arboriculture & Urban Forestry Online
Volume 37, Issue 5 — September 2011

Preliminary Evidence for Using Statistical Classification of Vibration Waveforms as an Initial Decay Detection Tool    (View PDF)

Anthony N. Mucciardi, Christoper J. Luley, and Kevin H. Gormally

Abstract: Arborists commonly use sounding during an initial evaluation of urban trees to determine the presence of advanced decay and hollows. Striking the trunk with a mallet produces stress waves that propagate through the wood and, in turn, generate characteristic audible sounds. Successful application of this procedure, however, requires subjective evaluation of the sonic variations that result from different wood species and densities, and various ambient noise conditions. Therefore, a statistical classification approach was developed for automatically identifying decay from stress waves captured using an accelerometer probe that is less subjective and more reproducible than an operator-in-the-loop approach. The classification algorithms were designed to detect the presence of decay from aberrant characteristics of the vibration waveform and do not rely on sonic velocity changes commonly used in most sonic testing for decay. The approach was tested in a preliminary study on 36 segmented trunk samples representing a wide range of typical urban tree species and decay types. The classifier successfully identified the decay status of 83% of the samples independent of species and trunk diameter. The results of this feasibility study cannot be transferred to real world tree inspection without additional testing on standing trees, but do demonstrate the potential of using accelerometers supplemented with a statistical classifier to support an initial assessment of decay in urban trees by an arborist.

Keywords: Accelerometer; Decay Detection; Feature Extraction; Pattern Classification; Sounding; Stress Waves; Urban Trees; Vibration Waves Wood Decay.

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