Abstract
Carbon monoxide (CO) is one of the most important fault characteristic gases dissolved in power transformer oil. With the advantages of high sensitivity and accuracy, long-term stability, and short detection time, photoacoustic spectroscopy (PAS) has been proven to be one promising sensing technology for trace gas recognition. In this investigation, a tunable PAS experimental system based on a distributed-feedback (DFB) diode laser was proposed for recognizing dissolved CO in transformer oil. The molecular spectral line of CO gas detection was selected at 1.567 μm in the whole experiment. Relationships between the photoacoustic (PA) signal and gas pressure, temperature, laser power, and CO gas concentration were measured and discussed in detail, respectively. Finally, based on the least square regression theory, a novel quantitative identification method for CO gas detection with the PAS experimental system was proposed. And a comparative research about the gas detection performances performed by the PAS system and gas chromatography (GC) measurement was presented. All results lay a solid foundation for exploring a portable and tunable CO gas PAS detection device for practical application in future.
Highlights
Large power transformers are costly and essential apparatus in power transmission and distribution system [1, 2], and their running conditions have important influence on the safety and reliability of the whole power system [3, 4]
Gas detection with the photoacoustic spectroscopy (PAS) system mainly depends on the wavelength of the radiation light source; the radiation wavelength of the DFB diode laser should be well-matched with the characteristic spectrum line of the target gas [6]
Crossinterference between Carbon monoxide (CO) gas and the potential interface gases should be avoided or decreased as much as possible
Summary
Large power transformers are costly and essential apparatus in power transmission and distribution system [1, 2], and their running conditions have important influence on the safety and reliability of the whole power system [3, 4]. Carbon monoxide is a critical fault characteristic gas dissolved in oilfilled power transformers, which can timely and effectively reflect the insulation performance of transformer insulating paper and paperboard [5]. It has been widely used in assessing the insulation state of running transformers. Due to the advantages of high sensitivity and accuracy, rapid detection speed, longterm stability, and no gas separation and consumption [12, 13], PAS would be a promising detection technology for dissolved fault characteristic gases in transformer oil, such as hydrogen, carbon monoxide, methane, ethane, ethylene, and acetylene [3]. The least square regression method was applied to quantitatively recognize the gas concentrations from the measured PA signals
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