Application Of On-line Detection Research Articles

Research and Development of NDIR Sensor and Its Application In On-Line Detection of CF4 Gas

Due to the excellent insulation and arc extinguishing properties of SF6 gas, it is widely used in the production and use of high voltage GIS. However, due to the breakdown of discharge and overheat, SF6 gas decomposes and produces a variety of low fluorine sulfides. Therefore, the concentration of CF4 gas in the high-voltage switch state can be effectively determined by detecting high-voltage GIS. This paper puts forward a kind of semiconductor laser based gas detection (NDIR) technology, the flange fixed installation in high voltage switch, optical fiber sensing structure can realize remote, real-time online monitoring of CF4 gas content. The experiment shows that the flange fiber optic sensor on-line monitoring device can realize the effective measurement of CF4 gas. The research results show that maximum field intensity on the surface of basin insulator is 10.788kV/mm, which is lower than the control field strength of 20kV/mm under the SF6 gas insulation condition, therefore the E-field near the basin insulator does not affect the operation of the optical fiber sensor. In the case of 1m light path, the detection limit of CF4 gas near 1312nm is less than 0.5ppm. The results of this study can provide an entirely new scheme for on-line monitoring of high-pressure open-light SF6 gas decomposition products, which can realize real-time on-line monitoring of the internal gas of the high voltage GIS equipment.

Electrochemical and Infrared Absorption Spectroscopy Detection of SF₆ Decomposition Products.

Sulfur hexafluoride (SF6) gas-insulated electrical equipment is widely used in high-voltage (HV) and extra-high-voltage (EHV) power systems. Partial discharge (PD) and local heating can occur in the electrical equipment because of insulation faults, which results in SF6 decomposition and ultimately generates several types of decomposition products. These SF6 decomposition products can be qualitatively and quantitatively detected with relevant detection methods, and such detection contributes to diagnosing the internal faults and evaluating the security risks of the equipment. At present, multiple detection methods exist for analyzing the SF6 decomposition products, and electrochemical sensing (ES) and infrared (IR) spectroscopy are well suited for application in online detection. In this study, the combination of ES with IR spectroscopy is used to detect SF6 gas decomposition. First, the characteristics of these two detection methods are studied, and the data analysis matrix is established. Then, a qualitative and quantitative analysis ES-IR model is established by adopting a two-step approach. A SF6 decomposition detector is designed and manufactured by combining an electrochemical sensor and IR spectroscopy technology. The detector is used to detect SF6 gas decomposition and is verified to reliably and accurately detect the gas components and concentrations.

An online outlier detection method based on wavelet technique and robust RBF network

We focus on the issue of outlier detection for time-series data in a process control system (PCS), since outlier detection is a critical step before performing data-based system analysis. Several published articles have proved that a wavelet transform (WT) technique can be used to detect outliers in time-series data, but the standard WT detection method, as well as any other univariate outlier detection technique, does not distinguish between the sudden change caused by the changes of inputs and the fluctuations caused by outliers in PCS. In order to improve this shortcoming of the conventional WT method for the data in a PCS, a new algorithm combining the wavelet technique with a robust radial basis function (RBF) network is proposed here. In this method, a robust RBF network (RBFN) training algorithm is proposed, which can train the RBFN online using the original data as a training set without the need of clean data and thus fits the application of online detection. Furthermore, a hidden Markov model is adopted as an analysis tool to accomplish online automatic detection without pre-selecting the threshold. We compare the performance of our proposed method with the conventional wavelet method and the AR model method to demonstrate its validity through simulation and experimental applications to the data pretreatment process in an electric arc furnace electrode regulator system.

Surface-Enhanced Raman Spectroscopy as a Detection Method in Gas Chromatography

The use of surface-enhanced Raman scattering (SERS) as a detection method in gas chromatography (GC) was investigated by two different approaches; GC eluates were trapped either in liquid silver sol or on solid thin-layer chromatography (TLC) plates, previously coated with silver colloidal solution. Subsequently, the trapped analytes were monitored by their SERS spectrum. Pyridine was successfully used as probe molecule for both interfaces. The extension of this static system for application in on-line detection of GC eluates is discussed.

High-performance liquid chromatography and photoaffinity crosslinking to explore the binding environment of nevirapine to reverse transcriptase of human immunodeficiency virus type-1

Nevirapine (BI-RG-587) is a potent inhibitor of the polymerase activity of reverse transcriptase of human immunodeficiency virus type-1. Nevirapine, as well as several other non-nucleoside compounds of various structural classes, bind strongly at a site which includes tyrosines 181 and 188 of the p66 subunit of reverse transcriptase. The chromatography which was utilized to explore this binding site is described. BI-RH-448 and BI-RJ-70, two tritiated photoaffinity azido analogues of nevirapine, are each crosslinked to reverse transcriptase. The use of several HPLC-based techniques employing different modes of detection makes it possible to demonstrate a dramatic difference between the two azido analogues in crosslinking behavior. In particular, by comparing HPLC tryptic peptide maps of the photoadducts formed between reverse transcriptase and each azido analogue, it can be shown that crosslinking with BI-RJ-70 but not with BI-RH-448 is more localized, stable, and hence exploitable for the identification of the specifically bonded amino acid residue(s). In addition, comparison of the tryptic maps also makes it feasible to assess which rings of the nevirapine structure are proximal or distal to amino acid side chains of reverse transcriptase. Finally, another feature of the HPLC peptide maps is the application of on-line detection by second order derivative UV absorbance spectroscopy to identify the crosslinked amino acid residue.