Call Localization of Fat Greenling Hexagrammos otakii Using Two Stereo Underwater Recorders

2018 ◽  
Vol 52 (4) ◽  
pp. 129-138
Author(s):  
Kazuki Yamato ◽  
Ikuo Matsuo ◽  
Ryuzo Takahashi ◽  
Naoto Matsubara ◽  
Hiroki Yasuma

AbstractA recent study revealed that fat greenling Hexagrammos otakii produces call sounds during the spawning season; the number of fish calls increases on the spawning day. However, it is unknown where and how many individual fat greenling produce fish calls. This behavior of fat greenling could be estimated by localizing the fish calls. We propose a sound localization method that uses two stereo recorders, which can then be used to estimate two time differences of arrival for each fish call. First, the calls of fat greenling are recorded by two stereo recorders for 3 weeks during the spawning season. Second, the calls of fat greenling are detected from the recorded data by the automatic detection algorithm, which uses the acoustic features of the fish call, and the positions of fish calls are estimated by the proposed sound localization method. The analysis of the recorded data by using the proposed method localized most of the fish calls near the spawning bed. Furthermore, the number of calling individuals may be estimated by analyzing the relation between the time the fish call is produced and its localized position.

Author(s):  
Shaoguang Li ◽  
Alfredo Núñez ◽  
Zili Li ◽  
Rolf Dollevoet

Short pitch corrugation is commonly seen in all kinds of tracks. There is not yet a conclusive explanation in the literature for its initiation and growth mechanisms. In this paper, we use an axle box acceleration (ABA) measurement system to detect corrugation. ABA can be easily implemented in operational trains, providing direct and reliable health monitoring of the track. We have extended a detection algorithm for rail surface local short wavelength defects to also detect short pitch corrugation, which is a continuous defect over the track. A 3D transient FE wheel-track model is employed to find theoretical signature tunes of the wheel-track system response when passing over a short pitch corrugation. Numerical simulations agree with ABA measurement obtained in the Dutch rail network. Based on the signature tune identified, an automatic detection algorithm is developed. Preliminary results with the algorithm are discussed. Field observations show a good potential of the detection algorithm to be used by inframanagers, to detect and monitor corrugation.


2016 ◽  
Vol 119 ◽  
pp. S740
Author(s):  
P. Colleoni ◽  
A. Gambirasio ◽  
C. Bianchi ◽  
M. Fortunato ◽  
S. Andreoli

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