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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.


(A) Waveforms simulated at 12 cm from the end of the PVC rod at an angle of 0–90° with the location of the PLB, which was made at 1 mm off center on the rod end. (B) Waveforms simulated at 12 cm from the end of the PVC rod, with PLB at 0–3 mm from the center of the rod end. The schematic at the bottom-left of the graphs shows the location of sources and sensors, when viewed perpendicular to the rod end.
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Figure 4: (A) Waveforms simulated at 12 cm from the end of the PVC rod at an angle of 0–90° with the location of the PLB, which was made at 1 mm off center on the rod end. (B) Waveforms simulated at 12 cm from the end of the PVC rod, with PLB at 0–3 mm from the center of the rod end. The schematic at the bottom-left of the graphs shows the location of sources and sensors, when viewed perpendicular to the rod end.

Mentions: When increasing the angle between the AE source (PLB) and the sensor, the amplitude of the first-arriving S0 mode was not affected (Figures 4A and 5A). The A0 mode amplitude, in contrast, decreased with increasing detection angle, until it completely disappeared at 90°. The A0 amplitude decrease was proportionate to the cosine of the detector angle, but because of the anisotropy of wood, the decrease in A0 amplitude deviated somewhat from the cosine function for the wooden rod (Figure 5A). The distance of the AE source from the axis of the rod has a significant influence on the amplitude of the A0 mode as well (Figures 4B and 5B). With constant angle between source and detector (0°), the A0 mode amplitude decreased linearly with decreasing distance between the source and the center of the rod.


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)

(A) Waveforms simulated at 12 cm from the end of the PVC rod at an angle of 0–90° with the location of the PLB, which was made at 1 mm off center on the rod end. (B) Waveforms simulated at 12 cm from the end of the PVC rod, with PLB at 0–3 mm from the center of the rod end. The schematic at the bottom-left of the graphs shows the location of sources and sensors, when viewed perpendicular to the rod end.
© Copyright Policy
Related In: Results  -  Collection

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

Figure 4: (A) Waveforms simulated at 12 cm from the end of the PVC rod at an angle of 0–90° with the location of the PLB, which was made at 1 mm off center on the rod end. (B) Waveforms simulated at 12 cm from the end of the PVC rod, with PLB at 0–3 mm from the center of the rod end. The schematic at the bottom-left of the graphs shows the location of sources and sensors, when viewed perpendicular to the rod end.
Mentions: When increasing the angle between the AE source (PLB) and the sensor, the amplitude of the first-arriving S0 mode was not affected (Figures 4A and 5A). The A0 mode amplitude, in contrast, decreased with increasing detection angle, until it completely disappeared at 90°. The A0 amplitude decrease was proportionate to the cosine of the detector angle, but because of the anisotropy of wood, the decrease in A0 amplitude deviated somewhat from the cosine function for the wooden rod (Figure 5A). The distance of the AE source from the axis of the rod has a significant influence on the amplitude of the A0 mode as well (Figures 4B and 5B). With constant angle between source and detector (0°), the A0 mode amplitude decreased linearly with decreasing distance between the source and the center of the rod.

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.