scholarly journals Application of Neural Network in the Measuring System On-line for Water Content of Crude Oil

2013 ◽  
Vol 5 (3) ◽  
pp. 276-279
Author(s):  
Zengrong Zhao ◽  
Yanju Wang
Keyword(s):  
Neural Network ◽  
Crude Oil ◽  
Water Content ◽  
Measuring System ◽  
On Line

Study on the Method of On-Line Measurement of Water Content in Turbine Oil Based on Resonant Cavity Perturbation

2005 ◽  
Author(s):  
Song-Feng Tian ◽  
Zhong-He Han ◽  
Kun Yang
Keyword(s):  
Water Content ◽  
Resonant Cavity ◽  
Measuring System ◽  
Turbine Oil ◽  
Economy Running ◽  
Line Measurement ◽  
Cavity Perturbation ◽  
On Line ◽  
Cavity Configuration ◽  
Lower Thermal Expansion

The accurate measurement of water content in the turbine oil has great significant for guiding steam turbine safety and economy running. A method of the on-line measurement of the water content in the turbine oil based on microwave resonant cavity perturbation is presented in this paper, The author deduced the formula of the volume proportion of water content in turbine oil, the resonant cavity and the measuring system of this method is simple. The precision of measurement can be improved by selecting work pattern with high quality factor, advancing the measurement precision of the relative frequency deflection and adopting the lower thermal expansion coefficient material and the especial resonant cavity configuration. Ten PPM water content in turbine oil can be distinguished by this method.

scholarly journals Water Content Monitoring in Water-in-Crude-Oil Emulsions Using an Ultrasonic Multiple-Backscattering Sensor

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5088
Author(s):  
Alberto L. Durán ◽  
Ediguer E. Franco ◽  
Carlos A. B. Reyna ◽  
Nicolás Pérez ◽  
Marcos S. G. Tsuzuki ◽  
...  
Keyword(s):  
Crude Oil ◽  
Water Content ◽  
Multiple Scattering ◽  
Propagation Velocity ◽  
Ultrasonic Transducer ◽  
Near Field ◽  
Water Volume ◽  
Signal Energy ◽  
On Line ◽  
Oil Emulsions

This work shows the application of an ultrasonic multiple-scattering sensor for monitoring water-in-petroleum emulsions. The sensor consists of a commercial ultrasonic transducer with an array of cylindrical scatterers placed in the near field. The scatterers are thin metal bars arranged in rows in front of the transducer. The backscattering signals were analyzed by calculating the wave energy and by a cross-correlation between signal segments; they were also used to determine the propagation velocity in the emulsions. The tests performed used emulsions with water volume concentrations from 0 to 50%. The results showed that both the signal energy and propagation velocity strongly depended on the concentration of water in the emulsion. Therefore, the ultrasonic multiple-scattering sensor can be used for on-line and real-time monitoring of the water content in water-in-crude-oil emulsions.

Demulsification of a Water-in-crude Oil Emulsion with a Corn Oil BasedDemulsifier using the Response Surface Methodology: Modelling and Optimization

2021 ◽  
Vol 14 ◽  
Author(s):  
Abed Saad ◽  
Nour Abdurahman ◽  
Rosli Mohd Yunus
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Water Content ◽  
Response Surface ◽  
Separation Efficiency ◽  
Corn Oil ◽  
Oil Emulsion ◽  
Optimal Values ◽  
Input Variables ◽  
Oil Emulsions

: In this study, the Sany-glass test was used to evaluate the performance of a new surfactant prepared from corn oil as a demulsifier for crude oil emulsions. Central composite design (CCD), based on the response surface methodology (RSM), was used to investigate the effect of four variables, including demulsifier dosage, water content, temperature, and pH, on the efficiency of water removal from the emulsion. As well, analysis of variance was applied to examine the precision of the CCD mathematical model. The results indicate that demulsifier dose and emulsion pH are two significant parameters determining demulsification. The maximum separation efficiency of 96% was attained at an alkaline pH and with 3500 ppm demulsifier. According to the RSM analysis, the optimal values for the input variables are 40% water content, 3500 ppm demulsifier, 60 °C, and pH 8.

Water absorption thermodynamics in single wood pellets modelled by multivariate near-infrared spectroscopy

Holzforschung ◽  
2008 ◽  
Vol 62 (4) ◽  
Author(s):  
Torbjörn A. Lestander
Keyword(s):  
Water Content ◽  
Near Infrared ◽  
Calorific Value ◽  
Least Squares Regression ◽  
Wood Pellets ◽  
Differential Heat ◽  
On Line ◽  
Explained Variation ◽  
Test Sets ◽  
Content Range

Abstract Samples of wood pellets were adjusted into six water content classes from 0% to 12%. The water content in single pellets varied between 0.1% and 14.2%. Three equations were constructed to estimate the differential heat of sorption (-ΔH) values from (1) fractal-geometry, (2) isosteric, and (3) calorimetric data. The ranges in calculated -ΔH of single pellets were (1) 133–1475, (2) 315–881, and (3) 195–1188 J g-1 water, respectively, across the studied moisture content range. Partial least squares regression was used to model near-infrared (NIR) spectra from single pellets and to predict -ΔH values and water content. The explained variation in test sets for the different models ranged from 97.1% to 99.9%. The shifts in peak absorbance for two water bands indicated that frequency in overtone vibration of O-H stretching and bending decreased, when water content was raised. Simulations of mixes between pellets of differential heat values showed that released heat was up to 0.03% of the gross calorific value of wood pellets. This heat may be a major contributor to initial temperature increases in pellet stacks during storage. The results indicate that on-line NIR based predictions of differential heat in wood pellets is possible to apply in the pellet industry.

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