scholarly journals Measurement of Flow Fluctuation in the Flow Standard Facility Based on Singular Value Decomposition

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6850
Author(s):  
Tao Meng ◽  
Huanchang Wei ◽  
Feng Gao ◽  
Huichao Shi
Keyword(s):  
Singular Value Decomposition ◽  
Measuring Method ◽  
Flow Stability ◽  
Singular Value ◽  
Single Frequency ◽  
Standard Facility ◽  
Flow Fluctuation ◽  
Set Up ◽  
Value Decomposition ◽  
The Impact

In order to accurately evaluate the flow stability of the flow standard facility, the flow fluctuation in the standard facility needs to be accurately measured. However, the flow fluctuation signal is always superimposed with the fluctuation signal of the measuring flowmeter or measurement system (mainly noise), which leads to inaccurate measurement of the flow fluctuation and even an unreliable evaluation result of the flow stability. In addition, when there are multiple fluctuation sources, flow fluctuations with different frequencies are superimposed together, which is extremely unfavorable for evaluating the impact of flow fluctuation with different single frequencies. In this paper, a new measuring method was proposed to obtain the fluctuation signal and the flow fluctuation based on singular value decomposition (SVD). Simulation experiments on the fluctuation signal (single frequency and multiple frequencies) under different levels of noise were conducted, and simulation results showed that the proposed method could accurately obtain the fluctuation signal and the flow fluctuation, even under high noise. Finally, an experimental platform was set-up based on a water flow standard facility and a flow fluctuation generator, and experiments on the output signal of a venturi flowmeter were carried out. The experiment results showed that the proposed method could effectively obtain the fluctuation signal and accurately measure the flow fluctuation.

Modeling Research of Background Noise in Low-Voltage Power Line Communication Channel

2012 ◽  
Vol 516-517 ◽  
pp. 1386-1390 ◽  
Author(s):  
Hao Kun Guo ◽  
Jun Ji Wu ◽  
Zhan Feng Ying
Keyword(s):  
Singular Value Decomposition ◽  
Background Noise ◽  
Low Voltage ◽  
Power Line ◽  
Singular Value ◽  
Ar Model ◽  
Recursive Method ◽  
Noise Interference ◽  
Set Up ◽  
Value Decomposition

Background noise interference is one of the most important factors for low-voltage power line communication’s reliability. By analyzing the background noise of low-voltage power line communication’s channel, the background noise’s measuring circuit is set up and the AR model of the measured background noise is established. Both of them are respectively using singular value decomposition and Levinson-Durbin (LD) recursive method to calculate the AR model’s parameters and a comparative analysis of the simulation is made. The results induct: parameters acquired from the methods of singular value decomposition and LD recursive method are feasible, the parameter model from singular value decomposition is relatively complex, but extremely accurate, which is suitable for the off-line calculation and analysis of the low-voltage power line’s background noise; the parameter model from LD recursive method is very simple, but has a greater loss of accuracy, fitting for online quickly generation of the low-voltage power line’s background noise.

scholarly journals Methodology for Assessing the Impact of Aperiodic Phenomena on the Energy Balance of Propulsion Engines in Vehicle Electromobility Systems for Given Areas

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2314
Author(s):  
Piotr Wróblewski ◽  
Wojciech Drożdż ◽  
Wojciech Lewicki ◽  
Paweł Miązek
Keyword(s):  
Energy Balance ◽  
Singular Value Decomposition ◽  
Input Data ◽  
Principal Component ◽  
Singular Value ◽  
Operating Costs ◽  
Model Research ◽  
Observation Matrix ◽  
Value Decomposition ◽  
The Impact

The article presents the methodology of isolating aperiodic phenomena constituting the basis of the energy balance of vehicles for the analysis of electromobility system indicators. The symptom observation matrix (SOM) and experimental input data are used to analyze periodic phenomena symptoms. The multidimensional nature of the engine efficiency shortage has been well defined and analyzed in terms of errors in the general model using neural networks, singular value decomposition, and principal component analysis. A more difficult task is the analysis of a multidimensional decision-making process. The research used a data fusion method and the concept of symptom reliability, which is applied to the generalized failure symptom obtained by applying the singular value decomposition (SVD). The model research has been based on the gray system theory (GST) and GM forecasting models (1,1). Input data were obtained from the assessment of driving cycles and analysis of the failure frequency for 1200 vehicles and mileage of 150,000 km. Based on this analysis, it can be concluded that with the current infrastructure and operating costs and the frequency of failure of PHEV and BEV drives, ICEV vehicles are unrivaled in terms of their operating costs.

scholarly journals Multilag Singular Value Decomposition Analysis of ENSO Convection with Tropical Stratospheric Temperature

2008 ◽  
Vol 21 (24) ◽  
pp. 6556-6568 ◽  
Author(s):  
Bryan C. Weare
Keyword(s):  
Singular Value Decomposition ◽  
Southern Oscillation ◽  
Decomposition Analysis ◽  
Singular Value ◽  
Central Pacific ◽  
Singular Value Decomposition Analysis ◽  
Stratospheric Temperature ◽  
Wide Range ◽  
Value Decomposition ◽  
The Impact

Abstract Multilag singular value decomposition (MLSVD) analysis is developed and applied to diagnosing the impact of interannual variations of outgoing longwave radiation (OLR) on tropical stratospheric temperature changes. MLSVD is designed to analyze simultaneously variations at multiple levels and for a large number of temporal lags and leads. The two dominant MLSVDs are strongly related to El Niño–Southern Oscillation (ENSO). The associated patterns of tropical OLR are similar to the canonical ENSO SST patterns with strong negative sign regions stretching along the equator in the eastern and central Pacific. These dominant modes are strongly linked to temperature perturbations at a wide range of lags. At the lowest analyzed level (200 hPa) and zero lag positive temperatures anomalies are in the region of low OLR. In the lower stratosphere near 100 hPa, strong negative temperature perturbations replace the positive values of the lowest level. Higher in the stratosphere near 20 hPa, equatorial temperature perturbations are again positive, but with a more zonally elongated spatial pattern. Overall, the equatorial temperature anomalies propagate slowly to the east, at a speed strongly related to ocean–atmosphere coupling of less than 1 m s−1, and vertically and westward into the stratosphere by Rossby waves with a speed in the range of 30 m s−1.

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