Mathematical models of magnetite desliming for automated quality control systems

Author(s):  
Yu. Olevska ◽  
V. Mishchenko ◽  
V. Olevskyi
2011 ◽  
Vol 28 (1) ◽  
pp. 74-84 ◽  
Author(s):  
Vesa Hasu ◽  
Ari Aaltonen

Abstract Automated quality control is a necessity for meteorological measurement networks because of an ever-increasing number of measurements. One of the basic quality control tests is to check that the observations fall into a range of acceptable values. This paper proposes an algorithm for the automatic determination of maximum and minimum thresholds for such a test. The automated algorithm results in more statistically justified thresholds compared to the operator-fed values, which some quality control systems normally use. The suggested algorithm is a tuning-free method for the determination of daily minimum and maximum limits. The basis of the algorithm is, first, to collect the essential statistics of observations during their annual cycle and, second, to use these statistics to determine the acceptable observation range. This paper introduces a semirecursive version with lower computational requirements and discusses additional algorithmic details. The algorithm is demonstrated through numerical examples, which show that limits converge to satisfactory values in a few years.


2019 ◽  
pp. 40-46 ◽  
Author(s):  
V.V. Savchenko ◽  
A.V. Savchenko

We consider the task of automated quality control of sound recordings containing voice samples of individuals. It is shown that in this task the most acute is the small sample size. In order to overcome this problem, we propose the novel method of acoustic measurements based on relative stability of the pitch frequency within a voice sample of short duration. An example of its practical implementation using aninter-periodic accumulation of a speech signal is considered. An experimental study with specially developed software provides statistical estimates of the effectiveness of the proposed method in noisy environments. It is shown that this method rejects the audio recording as unsuitable for a voice biometric identification with a probability of 0,95 or more for a signal to noise ratio below 15 dB. The obtained results are intended for use in the development of new and modifying existing systems of collecting and automated quality control of biometric personal data. The article is intended for a wide range of specialists in the field of acoustic measurements and digital processing of speech signals, as well as for practitioners who organize the work of authorized organizations in preparing for registration samples of biometric personal data.


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2017 ◽  
pp. btw766 ◽  
Author(s):  
Peter J. van der Most ◽  
Leanne K. Küpers ◽  
Harold Snieder ◽  
Ilja Nolte

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