The present project aims to develop a wood disease detection sensor based on a bio-mimetic principle: repeatedly hitting the tree and listening. Animals such as the Aye-aye Daubentonia madagascariensis use their long, thin finger to constantly hit the surface of the trunks. At the same time, their extremely sensitive ear allows them to differentiate and locate those areas where the wood emits a different sound. This variation in sound is due to the presence of tunnels dug by insects, so when Aye-aye detects a perforated area, it proceeds to break the bark of the wood with its teeth, extract the larva and eat it.

Currently, there are devices that either by ultrasound or impact, are able to determine properties of the wood such as hydration level or the presence of holes made by insects. For both cases, the main drawback is always the same: all the trees are different from each other and, in addition, they are covered with an irregular bark that distorts and attenuates the sound signal. This is the reason why their use is limited to already processed wood (planks) or to complex and slow analyses of individual trees. There is no solution that contemplates the analysis of whole forest. This would require a sensor that quickly and reliably detects the presence of diseases, regardless of its age and size. The key lies exactly in what the Aye-aye does: to hit the surface of the tree repeatedly. The difference in this case is that the goal is not to find anomalies, but to determine the main natural frequencies, as they are directly related to the health of the tree. The more acoustic responses are recorder, the easier it becomes to filter said natural frequencies, as they are the only component of the sound that always remain. That’s the reason why the sensor needs to hit the wood repeatedly (percussion).

The natural growth of the tree reduces the value of said frequencies while the diseases lead to the opposite effect, as they dehydrate the wood. By analysing the evolution of these frequencies, it is possible to detect whether the tree (or the forest) is sick or not.

The project is based on three main phases: sensor development, laboratory study and field tests in real forests. During the first phase, the necessary components to generate the percussion and capture the signals will be developed. During the second phase, signal filtering algorithms will be developed and tested against diseased and healthy wood samples.

Finally, taking advantage of the diseases of Lecanosticta Acicola, Dothistroma pini and Dothistroma septosporum, that are taking place in the north of Spain, validation tests will be carried out in a real forest. That is why the consortium is formed by TEKNIKER (research centre specialised in manufacturing and sensor technologies) and BASOEKIN (SME, an industry operating the economic sector related and in turn, member of Association of Basque Foresters).