Analysis of Total Hydrocarbon Exceeding Standard in Oil Chromatogram of a 500kV Main Transformer

Oil chromatographic analysis is widely used in transformer fault diagnosis However, the problem of excessive total hydrocarbons in the oil chromatogram caused by the failure of the transformer submersible pump is different from the failure of the transformer body. Technicians need to be able to accurately identify these two types of failure. For this problem, this article proposes a method of judging by manually starting and stopping the submersible pump and monitoring the change law of the transformer chromatographic data. This article first finds out suspicious submersible pumps through current data. Subsequently, the operator starts and stops the submersible pump and monitors the change law of the transformer chromatographic data. From this, the correlation between the start or stop of the submersible pump and the chromatographic data was found. Finally, the effectiveness of this method is verified by the submersible pump disassembly inspection and simulated live test.

Method for estimating mass content of paraffins in Achimov condensates based on chromatographic data

The paraffin content in production well streams must be monitored to assess the risks of wax formation during the production, transportation, and treatment of hydrocarbons. This is especially important when operating Achimov reservoirs containing fluids with a high content of heavy paraffin-type hydrocarbons. The standard approach for determining the paraffin content in oil using certified methods involves a long process of sample preparation and separation in selective columns followed by freezing out of paraffin from toluene extract. An urgent task is to find methods for the rapid assessment of paraffin content in condensates. The article considers a method for estimating the mass content of paraffins in condensates based on chromatographic data on the component-fractional and component-group composition of degassed condensate. The authors provide a comparison of the mass fraction of paraffins obtained by the proposed method and measured by the standard certified method.

Chromatographic Applications in the Multi-Way Calibration Field

In this review, recent advances and applications using multi-way calibration protocols based on the processing of multi-dimensional chromatographic data are discussed. We first describe the various modes in which multi-way chromatographic data sets can be generated, including some important characteristics that should be taken into account for the selection of an adequate data processing model. We then discuss the different manners in which the collected instrumental data can be arranged, and the most usually applied models and algorithms for the decomposition of the data arrays. The latter activity leads to the estimation of surrogate variables (scores), useful for analyte quantitation in the presence of uncalibrated interferences, achieving the second-order advantage. Recent experimental reports based on multi-way liquid and gas chromatographic data are then reviewed. Finally, analytical figures of merit that should always accompany quantitative calibration reports are described.

Multivariate Curve Resolution Alternating Least Squares applied to Chromatographic Data: From the Basics to the Recent Advances

This revision presents applications of multivariate curve resolution alternating least squares (MCR-ALS) applied to chromatographic data. Initially, the fundamentals and recent advances of the MCR-ALS method will be presented. Several critical issues such as data organization, advantages of the modelling, constraints, evaluation of ambiguity and the use for mathematical separation is discussed. An extensive revision of the papers on MCR-ALS applied to chromatographic data reported up to 2020 is presented. A practical example of an innovative application of cholesterol lowering drugs using supercritical fluid chromatography (SFC) is described highlighting important aspects of the method. At the end, a list of links to MCR-ALS algorithms and graphical interfaces developed in Matlab, R and Python 3 is provided.