Arboriculture & Urban Forestry 37(5): September 2011 Arboriculture & Urban Forestry 2011. 37(5): 191–199 191 Preliminary Evidence for Using Statistical Classification of Vibration Waveforms as an Initial Decay Detection Tool 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 ambi- ent 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. Key Words. Accelerometer; Decay Detection; Feature Extraction; Pattern Classification; Sounding; Stress Waves; Urban Trees; Vibration Waves Wood Decay. Sounding is a practical and widely accepted field technique for initially establishing the presence or absence of internal decay in trees, including those in urban settings (Boyce 1961; Mat- theck and Breloer 1994) and wood in service (Zabel and Mor- rell 1992). An arborist evaluates the soundness of a tree by strik- ing the trunk with a mallet, hammer, or other solid object and analyzing the resulting sounds for abnormal characteristics as- sociated with decay. The acoustic structure of the sound is de- termined by the propagation of the vibration waves though the volume of sound wood, decayed wood, or any internal voids, such as those created by enzymatic degradation by fungi. The effectiveness of sounding as a preliminary evalua- tion tool has been discussed (Boyce 1961), but no research literature appears to address the subject with statistical rigor. However, it is clear that sounding is a learned skill and its ef- fectiveness is therefore subject to the experience of the evalu- ator and, in particular, his/her ability to adapt to the vari- ability introduced when evaluating different tree specimens, including the bark thickness, trunk diameter, and amount of decay. Alternatively, aberrant sonic wave propagation can be auto- matically detected using a noninvasive sensor system. The authors propose a novel accelerometer-based system that is inspired by an arborist’s approach to sounding analysis. An accelerometer is a precise electro-mechanical analog to the human ear; it is a small sensor that measures reverberations of the trunk surface as the rate of change of the surface’s movement (velocity) with respect to time. The sensor picks up low amplitude vibrations, amplifies them, and converts them into a digital signal for further process- ing. Compared to classical sounding, analytical classification of waveforms recorded by an accelerometer can offer arborists a less subjective and more reproducible noninvasive method of initially detecting decay in urban trees. Data recorded by the accelerometer is insensitive to ambient noise, operates at a much higher sensitiv- ity to frequencies of interest than the human ear, and does not lose its frequency discrimination over time like the human operator. Recent research has introduced numerous instrumented systems for nondestructive decay detection that aim to improve the accura- cy of preliminary tree health evaluations and reduce the chance of human errors (Mattheck and Bethge 1993; Bucur 2003; Nicolotti 2003; Axmon et al. 2004; Gilbert and Smiley 2004; Wang et al. 2008; Brashawet al. 2009). These systems employ methods that range from relatively simple stress wave and ultrasonic single-path timing calculators to more advanced tomographic reconstruction algorithms based on multipath propagation measurements. These noninvasive detection methods can accurately reveal the general location and magnitude of defects and fine resolution of the de- cay can then be achieved using microdrilling (Wang et al. 2008). Single-path timing methods (Mattheck and Bethge 1993; Wang et al. 2004; Kazemi-Najafi et al. 2009) detect decay sim- ply by comparing a modeled transmission time along a single path through transverse sections of the wood to the observed time. The benefit of these systems’ simplicity, however, is offset by their limited capabilities for decay detection. Stress wave ve- locity varies substantially across tree samples, even intact trees and a standard reference velocity are not readily available for the data interpretation (Wang et al. 2005; Wang and Allison 2008). These concepts have been extended to more extensive, complex, and expensive multipath systems based on a ring of sensors. Rinn (1999) was the first to publish on multipath to- mography using chains of electronically independent sources ©2011 International Society of Arboriculture
September 2011
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