Decay Detection through Automatic Recognition of Acoustic Velocity Pattern

Concealed internal decay presents a special problem in managing urban trees for public safety. Effective nondestructive testing methods capable of locating and quantifying wood decay and defects are needed by urban forest managers and arborists to determine the physical condition of trees and promote public safety. In this study, we examined acoustic velocity patterns in sound Melia azedarach trunk sections as well as the sections with artificial defects. Field testing was then conducted on Ginkgo biloba and Cinnamomum camphora trees to test the feasibility of using the measured acoustic velocity patterns to diagnose internal condition of the trees. The results confirmed that the acoustic velocities measured in sound trunk sections conformed to the second order polynomial relationships. Center rot caused significant changes in acoustic velocity patterns when the diameter of the hole reached 11 cm and beyond. Successful filed inspection cases indicate that acoustic velocity pattern recognition can be used effectively for inspecting trees in urban settings.