Determination of data matrix dimensions for subspace-based parameter estimation algorithms

2002 ◽  
Author(s):  
Yinong Ding ◽  
R.J. Vaccaro
Keyword(s):  
Parameter Estimation ◽  
Data Matrix ◽  
Estimation Algorithms

scholarly journals Application of Multidimensional Statistical Analysis in Tribotechnical Diagnostics of Hydraulic Fluids in Woodworking Equipment

Materials ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4628
Author(s):  
Michaela Hnilicová ◽  
Ján Turis ◽  
Richard Hnilica
Keyword(s):  
Data Matrix ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Machine Maintenance ◽  
Hydraulic Fluids ◽  
Quantitative Characteristics ◽  
Friction Surfaces ◽  
Qualitative And Quantitative Characteristics

The article dealt with the assessment of the quality of hydraulic oil and determination of the mode of wear of the friction surfaces of Baljer & Zembrod manipulating lines through the information traces in the oils by applying tribotechnical diagnostics. We presented the assessment of the level of degradation of the oils. In addition, we presented the mode of wear of the friction surfaces washed in oil through evaluation of the qualitative and quantitative characteristics of the particles found in the oil. In detail, we focused on the application of suitable multivariate statistical methods on the data matrix. The article also presents predictive models that can sort oils into groups based on the assessment of quality of the oil and the state of the friction couples. The models can be used in research and in solving practical tasks in tribotechnical diagnostics of hydraulic fluids in woodworking equipment. Our results showed that the manipulation lines were greatly thermically stressed due to inadequate oil and machine maintenance. By correlative integration of all methods used, we could determine the real mode of the wear of the tribologic nodes of the machine. The experiment enabled the early detection of an undesirable process in the tribological node and implementation of corrective measures before the machine would break down.

Development and Validation of Chemometric-Assisted Spectrophotometric Methods for Simultaneous Determination of Phenylephrine Hydrochloride and Ketorolac Tromethamine in Binary Combinations

2016 ◽  
Vol 99 (5) ◽  
pp. 1247-1251 ◽  
Author(s):  
Hamed M Elfatatry ◽  
Mokhtar M Mabrouk ◽  
Sherin F Hammad ◽  
Fotouh R Mansour ◽  
Amira H Kamal ◽  
...  
Keyword(s):  
Least Squares ◽  
Simultaneous Determination ◽  
Principal Component Regression ◽  
Principal Component ◽  
Data Matrix ◽  
Ketorolac Tromethamine ◽  
Concentration Data ◽  
Phenylephrine Hydrochloride ◽  
Spectrophotometric Methods

Abstract The present work describes new spectrophotometric methods for the simultaneous determination of phenylephrine hydrochloride and ketorolac tromethamine in their synthetic mixtures. The applied chemometric techniques are multivariate methods including classical least squares, principal component regression, and partial least squares. In these techniques, the concentration data matrix was prepared by using the synthetic mixtures containing these drugs dissolved in distilled water. The absorbance data matrix corresponding to the concentration data was obtained by measuring the absorbances at 16 wavelengths in the range 244–274 nm at 2 nm intervals in the zero-order spectra. The spectrophotometric procedures do not require any separation steps. The accuracy, precision, and linearity ranges of the methods have been determined, and analyzing synthetic mixtures containing the studied drugs has validated them. The developed methods were successfully applied to the synthetic mixtures and the results were compared to those obtained by a reported HPLC method.

Model Verification of Mixed Dynamic Systems

1978 ◽  
Vol 100 (2) ◽  
pp. 266-273 ◽  
Author(s):  
J. D. Chrostowski ◽  
D. A. Evensen ◽  
T. K. Hasselman
Keyword(s):  
Experimental Data ◽  
Parameter Estimation ◽  
Dynamic Systems ◽  
Statistical Parameter ◽  
Model Verification ◽  
Passive Networks ◽  
Parameter Values ◽  
Basic Configuration ◽  
General Method

A general method is presented for using experimental data to verify math models of “mixed” dynamic systems. The term “mixed” is used to suggest applicability to combined systems which may include interactive mechanical, hydraulic, electrical, and conceivably other types of components. Automatic matrix generating procedures are employed to facilitate the modeling of passive networks (e.g., hydraulic, electrical). These procedures are augmented by direct matrix input which can be used to complement the network model. The problem of model verification is treated in two parts; verification of the basic configuration of the model and determination of the parameter values associated with that configuration are addressed sequentially. Statistical parameter estimation is employed to identify selected parameter values, recognizing varying degrees of uncertainty with regard to both experimental data and analytical results. An example problem, involving a coupled hydraulic-mechanical system, is included to demonstrate application of the method.

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