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Deciphering acoustic emission signals in drought stressed branches: the missing link between source and sensor.

Vergeynst LL, Sause MG, Hamstad MA, Steppe K - Front Plant Sci (2015)

Bottom Line: A problem encountered during this analysis is that the waveform changes significantly from source to sensor and lack of knowledge on wave propagation impedes research progress made in this field.Two wave propagation modes could be distinguished and we used the finite element model to interpret their behavior in terms of source position for both the PVC rod and a wooden rod.Both wave propagation modes were also identified in drying-induced signals from woody branches, and we used the obtained insights to provide recommendations for further AE research in plant science.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Plant Ecology, Department of Applied Ecology and Environmental Biology, Faculty of Bioscience Engineering, Ghent University Ghent, Belgium.

ABSTRACT
When drought occurs in plants, acoustic emission (AE) signals can be detected, but the actual causes of these signals are still unknown. By analyzing the waveforms of the measured signals, it should, however, be possible to trace the characteristics of the AE source and get information about the underlying physiological processes. A problem encountered during this analysis is that the waveform changes significantly from source to sensor and lack of knowledge on wave propagation impedes research progress made in this field. We used finite element modeling and the well-known pencil lead break source to investigate wave propagation in a branch. A cylindrical rod of polyvinyl chloride was first used to identify the theoretical propagation modes. Two wave propagation modes could be distinguished and we used the finite element model to interpret their behavior in terms of source position for both the PVC rod and a wooden rod. Both wave propagation modes were also identified in drying-induced signals from woody branches, and we used the obtained insights to provide recommendations for further AE research in plant science.

No MeSH data available.


Related in: MedlinePlus

Surface displacement at 12 cm from the end of a PVC rod, resulting from a PLB at the rod end, at 1 mm off center: (A) simulated (black) and experimental (gray) waveforms at 0° from the PLB location, (B) simulated waveform at 180°, and (C) Choi–Williams transformation of the simulated signal in (A) with velocity dispersion curves for the S0 and A0 mode.
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Figure 3: Surface displacement at 12 cm from the end of a PVC rod, resulting from a PLB at the rod end, at 1 mm off center: (A) simulated (black) and experimental (gray) waveforms at 0° from the PLB location, (B) simulated waveform at 180°, and (C) Choi–Williams transformation of the simulated signal in (A) with velocity dispersion curves for the S0 and A0 mode.

Mentions: Good correspondence between simulated surface displacement and experimentally obtained waveform at 12 cm from the PLB at the end of the PVC rod (Figure 1) confirms that the model configuration was valid (Figure 3A). Comparing simulated signals on both sides of the rod (Figures 3A,B), we can identify a first arrival of a symmetric wave at around 70 μs, due to the simultaneous out- and inward displacement at opposite sides of the rod. Subsequently, an anti-symmetric wave with lower velocity arrives at around 110 μs, with outward displacement at one side of the rod occurring simultaneously with inward displacement at the opposite side. A schematic representation of both wave modes is shown in Figure 3c. From the velocity dispersion curves of a cylindrical rod (Figure 3C) it can be seen that these arrival times correspond to the arrival of the fundamental symmetric (S0) and anti-symmetric (A0) wave mode, respectively. The good correspondence between CWD and the dispersion curves confirms that we are dealing with the S0 and A0 mode and provides added validation of the correctness of the finite element model.


Deciphering acoustic emission signals in drought stressed branches: the missing link between source and sensor.

Vergeynst LL, Sause MG, Hamstad MA, Steppe K - Front Plant Sci (2015)

Surface displacement at 12 cm from the end of a PVC rod, resulting from a PLB at the rod end, at 1 mm off center: (A) simulated (black) and experimental (gray) waveforms at 0° from the PLB location, (B) simulated waveform at 180°, and (C) Choi–Williams transformation of the simulated signal in (A) with velocity dispersion curves for the S0 and A0 mode.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4488601&req=5

Figure 3: Surface displacement at 12 cm from the end of a PVC rod, resulting from a PLB at the rod end, at 1 mm off center: (A) simulated (black) and experimental (gray) waveforms at 0° from the PLB location, (B) simulated waveform at 180°, and (C) Choi–Williams transformation of the simulated signal in (A) with velocity dispersion curves for the S0 and A0 mode.
Mentions: Good correspondence between simulated surface displacement and experimentally obtained waveform at 12 cm from the PLB at the end of the PVC rod (Figure 1) confirms that the model configuration was valid (Figure 3A). Comparing simulated signals on both sides of the rod (Figures 3A,B), we can identify a first arrival of a symmetric wave at around 70 μs, due to the simultaneous out- and inward displacement at opposite sides of the rod. Subsequently, an anti-symmetric wave with lower velocity arrives at around 110 μs, with outward displacement at one side of the rod occurring simultaneously with inward displacement at the opposite side. A schematic representation of both wave modes is shown in Figure 3c. From the velocity dispersion curves of a cylindrical rod (Figure 3C) it can be seen that these arrival times correspond to the arrival of the fundamental symmetric (S0) and anti-symmetric (A0) wave mode, respectively. The good correspondence between CWD and the dispersion curves confirms that we are dealing with the S0 and A0 mode and provides added validation of the correctness of the finite element model.

Bottom Line: A problem encountered during this analysis is that the waveform changes significantly from source to sensor and lack of knowledge on wave propagation impedes research progress made in this field.Two wave propagation modes could be distinguished and we used the finite element model to interpret their behavior in terms of source position for both the PVC rod and a wooden rod.Both wave propagation modes were also identified in drying-induced signals from woody branches, and we used the obtained insights to provide recommendations for further AE research in plant science.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Plant Ecology, Department of Applied Ecology and Environmental Biology, Faculty of Bioscience Engineering, Ghent University Ghent, Belgium.

ABSTRACT
When drought occurs in plants, acoustic emission (AE) signals can be detected, but the actual causes of these signals are still unknown. By analyzing the waveforms of the measured signals, it should, however, be possible to trace the characteristics of the AE source and get information about the underlying physiological processes. A problem encountered during this analysis is that the waveform changes significantly from source to sensor and lack of knowledge on wave propagation impedes research progress made in this field. We used finite element modeling and the well-known pencil lead break source to investigate wave propagation in a branch. A cylindrical rod of polyvinyl chloride was first used to identify the theoretical propagation modes. Two wave propagation modes could be distinguished and we used the finite element model to interpret their behavior in terms of source position for both the PVC rod and a wooden rod. Both wave propagation modes were also identified in drying-induced signals from woody branches, and we used the obtained insights to provide recommendations for further AE research in plant science.

No MeSH data available.


Related in: MedlinePlus