scholarly journals Terahertz time-domain spectral imaging using telecentric beam steering and an f-θ scanning lens: distortion compensation and determination of resolution limits

2020 ◽  
Vol 28 (18) ◽  
pp. 26612 ◽  
Author(s):  
Zachery B. Harris ◽  
Arjun Virk ◽  
Mahmoud E. Khani ◽  
M. Hassan Arbab
Keyword(s):  
Time Domain ◽  
Beam Steering ◽  
Spectral Imaging ◽  
Lens Distortion ◽  
Distortion Compensation ◽  
Resolution Limits ◽  
Scanning Lens

Memory-efficient algorithm for lens distortion compensation

2003 ◽  
Vol 95 (1) ◽  
pp. 139-141
Author(s):  
K. D. Kozmin ◽  
K. Hyyppä
Keyword(s):  
Efficient Algorithm ◽  
Lens Distortion ◽  
Distortion Compensation ◽  
Memory Efficient

Broadband Determination of Biodiesel Content in Petroleum Diesel Blends by Terahertz Time Domain Spectroscopy

2021 ◽  
pp. 1-1
Author(s):  
Mario Mendez Aller ◽  
Duu Sheng Ong ◽  
Harrison Lik Nang Lau ◽  
Sascha Preu
Keyword(s):  
Time Domain ◽  
Terahertz Time Domain Spectroscopy ◽  
Time Domain Spectroscopy

Deep Neural Network Classification of In Vivo Burn injuries with Different Etiologies Using THz Time-Domain Spectral Imaging

2021 ◽  
Author(s):  
Omar B. Osman ◽  
Zachery B. Harris ◽  
Juin-Wan Zhou ◽  
Mahmoud E. Khani ◽  
Andrew Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Time Domain ◽  
Deep Neural Network ◽  
Spectral Imaging ◽  
Burn Injuries ◽  
Neural Network Classification

Classification of journal bearing friction states based on acoustic emission signals

2018 ◽  
Vol 85 (6) ◽  
pp. 434-442 ◽  
Author(s):  
Noushin Mokhtari ◽  
Clemens Gühmann
Keyword(s):  
Acoustic Emission ◽  
Time Domain ◽  
Journal Bearing ◽  
Prediction Method ◽  
Support Vector ◽  
Mechatronic Systems ◽  
Prediction Time ◽  
Ae Signals ◽  
Bearing Friction

Abstract For diagnosis and predictive maintenance of mechatronic systems, monitoring of bearings is essential. An important building block for this is the determination of the bearing friction condition. This paper deals with the possibility of monitoring different journal bearing friction states, such as mixed and fluid friction, and examines a new approach to distinguish between different friction intensities under several speed and load combinations based on feature extraction and feature selection methods applied on acoustic emission (AE) signals. The aim of this work is to identify separation effective features of AE signals to subsequently classify the journal bearing friction states. Furthermore, the acquired features give information about the mixed friction intensity, which is significant for remaining useful lifetime (RUL) prediction. Time domain features as well as features in the frequency domain have been investigated in this work. To increase the sensitivity of the extracted features the AE signals were transformed to the frequency-time-domain using continuous wavelet transform (CWT). Significant frequency bands are determined to separate different friction states more effective. A support vector machine (SVM) is used to classify the signals into three different friction classes. In the end the idea for an RUL prediction method by using the already determined information is given and explained.

scholarly journals Determination of the time origin by 
the maximum entropy method in 
time-domain terahertz emission spectroscopy

2010 ◽  
Vol 18 (15) ◽  
pp. 15853 ◽  
Author(s):  
Takeya Unuma ◽  
Yusuke Ino ◽  
Makoto Kuwata-Gonokami ◽  
Erik M. Vartiainen ◽  
Kai-Erik Peiponen ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Time Domain ◽  
Emission Spectroscopy ◽  
Maximum Entropy Method ◽  
Entropy Method ◽  
Terahertz Emission ◽  
Terahertz Emission Spectroscopy ◽  
Time Origin
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