Determination of the probability of spontaneous fracture of metal from the acoustic emission spectrum at the prefracture stage

Atomic Energy ◽  
2007 ◽  
Vol 102 (6) ◽  
pp. 436-444
Author(s):  
V. A. Krylov
1979 ◽  
Vol 44 ◽  
pp. 349-355
Author(s):  
R.W. Milkey

The focus of discussion in Working Group 3 was on the Thermodynamic Properties as determined spectroscopically, including the observational techniques and the theoretical modeling of physical processes responsible for the emission spectrum. Recent advances in observational techniques and theoretical concepts make this discussion particularly timely. It is wise to remember that the determination of thermodynamic parameters is not an end in itself and that these are interesting chiefly for what they can tell us about the energetics and mass transport in prominences.


2015 ◽  
Vol 44 (7) ◽  
pp. 2497-2506 ◽  
Author(s):  
Pei-Chi Chen ◽  
Yen-Fu Su ◽  
Shin-Yueh Yang ◽  
Steven Y. Liang ◽  
Kuo-Ning Chiang

2018 ◽  
Vol 85 (6) ◽  
pp. 434-442 ◽  
Author(s):  
Noushin Mokhtari ◽  
Clemens Gühmann

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.


1967 ◽  
Vol 45 (11) ◽  
pp. 3663-3666 ◽  
Author(s):  
K. M. Lal ◽  
B. N. Khanna

The emission spectrum of the A–X system of the PbBr molecule in the region 4 600–5 900 Å has been obtained in the second order of a 21-ft concave grating spectrograph (15 000 lines per inch) with a dispersion of 1.25 Å/mm. A rotational analysis of four bands—(3, 2), (2, 2), (3, 1), and (4, 1)—of this system has been done, leading to the determination of the following rotational constants:[Formula: see text]The system appears to be similar to the A-X system of the PbCl molecule in the visible region, and a [Formula: see text] transition has been suggested.


2017 ◽  
Vol 53 (15) ◽  
pp. 1506-1512 ◽  
Author(s):  
I. A. Rastegaev ◽  
D. L. Merson ◽  
A. Yu. Vinogradov ◽  
A. V. Danyuk

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