Search

Hollow structured nanofibers have attracted much attention in diverse domains owing to their unique physicochemical properties and characteristics. Gas sensing is one of the most promising applications. In electrical engineering, the detection of SF6 decomposing gas products is significant to monitor the insulation status online of gas insulated switchgear (GIS). This mini-review presents the developments of hollow structured nanofibers in synthesis strategies and gas sensing application, especially in the detection of SF6 decomposing gas products, including hydrogen disulfide (H2S), sulfur dioxide (SO2), thionyl fluoride (SOF2), and sulfuryl fluoride (SO2F2). In addition, the gas sensing mechanism of metal oxide hollow nanofibers based gas sensor are discussed.

In this study, we reported a successful synthesis of a nanocomposite based on SnO2 nanoneedles anchored to NiO microsphere by a simple two-step hydrothermal route. The results show that the SnO2/NiO nanocomposite-based sensor exhibits more prominent performances than the pristine NiO microsphere to NO2 such as larger responses and more outstanding repeatability. The improved properties are mainly attributed to the p&ndash, n heterojunctions formed at the SnO2&ndash, NiO interface, leading to the change of potential barrier height and the enlargement of the depletion layer. Besides, the novel and unique nanostructure provides large and effective areas for the surface reaction. In addition, a plausible growth mechanism and the enhanced sensing mechanism were proposed to further discuss the special nanostructure which will benefit the exploration of high-performance sensors.

In this work, Cr2O3 nanoparticles and SnO2 nanofibers were fabricated by a sol–gel process and an electrospinning method, respectively. Gas sensitive materials with high sensitivity to C2H2 gas were obtained by coating Cr2O3 nanoparticles on SnO2 nanofibers. The prepared Cr2O3 nanoparticle-coated SnO2 nanofibers (Cr2O3 NPs. coated SnO2 NFs.) were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), X-ray energy dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and the gas sensing behaviors to C2H2 were studied. The Cr2O3 NPs. coated SnO2 NFs. exhibited low optimal operating temperature, high sensing response, excellent response-recovery time and long-term stability to C2H2. The optimal operating temperature of the measured material to 20 ppm C2H2 was about 220℃ and the C2H2 concentration had a good linear relationship with the response value when the concentration was less than 60 ppm. In addition, a reasonable gas sensing mechanism was proposed which may enhance the gas sensing performances for the Cr2O3 NPs. coated SnO2 NFs. to C2H2.

The water content in oil is closely related to the deterioration performance of an insulation system, and accurate prediction of water content in oil is important for the stability and security level of power systems. A novel method of measuring water content in transformer oil using multi frequency ultrasonic with a back propagation neural network that was optimized by principal component analysis and genetic algorithm (PCA-GA-BPNN), is reported in this paper. 160 oil samples of different water content were investigated using the multi frequency ultrasonic detection technology. Then the multi frequency ultrasonic data were preprocessed using principal component analysis (PCA), which was implemented to obtain main principal components containing 95% of original information. After that, a genetic algorithm (GA) was incorporated to optimize the parameters for a back propagation neural network (BPNN), including the weight and threshold. Finally, the BPNN model with the optimized parameters was trained with a random 150 sets of pretreatment data, and the generalization ability of the model was tested with the remaining 10 sets. The mean squared error of the test sets was 8.65 &times, 10&minus, 5, with a correlation coefficient of 0.98. Results show that the developed PCA-GA-BPNN model is robust and enables accurate prediction of a water content in transformer oil using multi frequency ultrasonic technology.

In this study, highly sensitive Ag 2 O-doped ZnO nanorods based sensor was presented and developed to detect CH 4 gas, an extremely significant fault characteristic gas extracted from power transformer oil. Ag 2 O-doped ZnO nanorods sensing materials were synthesized with facile hydrothermal method, and characterized via X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and energy-dispersive X-ray spectroscopy (EDS), respectively. Side heated chemical gas sensor was fabricated and its sensing performances towards CH 4 were systematically investigated. The optimal operating temperature of the Ag 2 O-doped ZnO sensor was 280 °C for CH 4 sensing, and its gas sensing response to 10 ppm CH 4 was measured to be as high as 12.28. In addition, good linearity for low concentration of CH 4 gas was also obtained. The corresponding response-recovery time of the Ag 2 O-doped ZnO sensor was measured to be about 17-10s. All results provide reference and guidance for developing high-performance ZnO based gas sensors for CH 4 detection. All these excellent sensors performances indicate the large potential of the fabricated Ag 2 O decorated ZnO nanorods sensor for practical application of CH 4 detection.

The detection of toxic gas decomposition in gas insulated switchgear is an important technology to predict and judge equipment failure. In this paper, the adsorption model is established by the first principles. It is found that the band gap of Ni-doped ZIF-8 clusters is reduced and the selectivity is enhanced. The key adsorption parameters such as adsorption energy, charge transfer, bond length, bond angle, density of States, charge density difference and electron localization function were calculated and analyzed. The adsorption of SO2, H2S, SOF2 and CF4 was analyzed by Ni-ZIF-8 cluster and overall structure adsorption model, and competitive adsorption was introduced to verify single gas. The calculation results show that ni-zif-8 has the best selective adsorption of SO2, and the order of adsorption priority is SO2 > H2S > SOF2 > CF4. Therefore, it provides a feasible theoretical basis for the design of gas sensor.

By detecting the decomposition gases of sulfur hexafluoride (SF6), the type of internal fault of gas insulated switchgear (GIS) can be determined. In this paper, the scandium atom doped molybdenum sulfide material (Sc-MoS2) was proposed, and the adsorption behaviors of four typical SF6 decomposing gases (H2S, SO2, SOF2, SO2F2) on the surfaces of intrinsic MoS2 and Sc-MoS2 are studied based on density functional theory (DFT) method. The adsorption models were established to calculate the electronic properties and adsorption parameters of the adsorption systems. The results show that Sc-MoS2 has excellent adsorption properties for SO2, SOF2 and SO2F2, but weak adsorption for H2S. Moreover, the adsorption effect for target gases was obviously enhanced by the introduction of Sc atom as the active center of the system. The findings are beneficial to refine the gas sensing mechanism of MoS2 materials and lay a foundation for SF6 decomposition gases detection based on MoS2 sensors.

In this paper, based on density functional theory (DFT), the possibility of intrinsic and Cr doped SnP3 (Cr-SnP3) monolayer as candidate materials for detecting SF6 decomposed gases SO2, SOF2 and SO2F2 was discussed. The adsorption energy, adsorption distance, charge transfer and density of states of adsorption systems were calculated and analyzed. Results reveal that the Cr-SnP3 monolayer has higher chemical affinity to SO2, SOF2 and SO2F2 molecules than intrinsic SnP3. Larger adsorption energy, obvious charge transfer and significant molecular structural deformation can be observed, indicating the strong interaction between gas molecule and Cr-SnP3 caused by chemisorption, which can effectively excite electrical signals for gas detection. Therefore, Cr-SnP3 monolayer gas sensor may be recommended in the field of SF6 decomposition characteristics products detection.

Understanding of turbidity, an indicator of water quality, is of great importance in cities and can have significant implications for human society. Many users are interested in mapping turbidity using remote sensing tools for long-term and large-scale monitoring. This study aims to derive turbidity maps in an urbanizing city and to identify the driving factors for better decision-making and water quality management. Taking Wuhan, the most rapidly urbanizing metropolis in central China, as an instance, the water turbidity is monitored using Landsat observations from 1987 to 2019, and the relationships of turbidity and climatic/human factors are examined. Climatic factors are represented by meteorological conditions (rainfall, wind speed, temperature, and water vapor pressure) and human factors are characterized by the normalized difference vegetation index (NDVI) and impervious surface area (ISA). The results demonstrated that: (1) the seasonal mean turbidity increased from spring to summer (34.28 NTU to 36.27 NTU), decreased in autumn (25.04 NTU), and increased again in winter (37.20 NTU), and the variations were related to changes in rainfall; and (2) the annual mean turbidity was fluctuatingly stable during 1987–2004 and decreased by 1 NTU/yr. since 2005. The decline of water turbidity was highly correlated to the increase of NDVI and ISA with p values

In order to detect the decomposition gas of organic insulator in gas insulated switchgear, Cu doped ZIF-67 material was proposed. In this paper, the gas adsorption process was analyzed by the first principle. The calculation indexes include density of States (DOS), adsorption energy (Eads ), charge transfer quantity (Qt ), Charge density difference (CDD), electron localization function (ELF), the highest occupied molecular orbitals (HOMO) and the lowest unoccupied molecular orbital (LUMO). The results show that the adsorption capacity of Cu-ZIF-67 for CO and CO2 is better than that of CF4 in the single gas adsorption calculation. The adsorption energies of three single gases are -1.306eV, -1.597eV and -0.991eV, respectively. Therefore, this study provides excellent gas sensing materials and scientific theoretical calculation for selective detection and gas adsorption of decomposition gas.

The decomposition gas of SF6 circuit breaker adsorbed on MOF-505 analogue had been analyzed and studied in this paper by using the first principles of density functional theory (DFT) to analyze adsorption mechanism. The adsorption structures of organic ligands and metal sites were established and optimized. Through analyzing the adsorption energy, adsorption distance difference, charge transfer, density of states, Charge density difference and electron localization function, the results show that organic ligands and metal sites have excellent adsorption effect on H2S and SO2, belonging to chemical adsorbent, and the adsorption capacity is far greater than that of SF6. The MOF-505 analogue will be a potential adsorbent for the fault recovery of SF6 circuit breaker.

In order to improve the reliability of the transformer, reduce the maintenance cost of the transformer, online detection technology of transformer oil dissolved gases (H2, C2H2 and CH4) has become more important. Quick and accurate fault location is the research focus of this technology. In this paper, based on first principles density functional theory (DFT), the best Sb doping position was discussed, and adsorption systems of H2, C2H2 and CH4 on intrinsic graphene and Sb-doped graphene were built. The adsorption energy, charge transfer, bandgap, the energy of lowest unoccupied molecular orbital (LUMO), the energy of highest occupied molecular orbital (HOMO) and the total and partial density of states (DOS) of these adsorption systems were analyzed. The results showed that T doping site (Sb-CT) on the surface of graphene is the most stable site. And the intrinsic graphene has better adsorption and gas sensitivity to C2H2. Compared with H2, Sb-CT doped graphene has better sensing properties to C2H2 and CH4. It illustrates that Sb-doped graphene can be used in the overheated fault detection of the transformer.

Air-gap discharge in oil-paper insulation is one of the main types of partial discharge (PD) in power transformer. The discharge development stage for monitoring and diagnosis of transformer potential faults is a significant area of study. The method of wavelet packet energy entropy, which is based on different frequency bands energy distribution of PD signals at different insulation states, is provided to explore the variation characteristics of the whole PD process. In this paper, air-gap discharge model is built in the simulative transformer tank that collects PD signals based on constant voltage method. This model also utilizes wavelet packet decomposition method to partition PD signal bands obtaining signal energy distribution in each frequency band, as well as total signal energy tendency along with PD development process. Wavelet packet energy entropy, which is the new PD feature parameter describing the development process, represents the order degree of PD signals which corresponds to dielectric strength. Finally, because of the cyclic change of this method, the step points of wavelet packet entropy are taken as the way to effectively divide the PD development stage.

In this paper, pure and 1.5, 2.5 and 3.5 at.-% samarium oxide (Sm2O3) doped tin oxide (SnO2) nanorods were successfully synthesised with a facile and environment friendly hydrothermal process. All the as prepared nanostructures were carefully characterised by X-ray diffraction, field emission SEM, TEM, high resolution TEM and X-ray photoelectron spectroscopy respectively. Planar sensors were further fabricated with the as synthesised samples, and their sensing properties towards acetylene gas (C2H2), an extremely significant fault characteristic gas dissolved in oil immersed power transformers, were systematically measured. Interestingly, the sensing properties of the fabricated SnO2 nanorod based sensor to C2H2 gas can be obviously enhanced by adding Sm2O3, and the sensor doped with 3.5 at.-%Sm2O3 displays the most superior sensing characteristics, including operating temperature, sensitivity, response and recovery time, etc., as compared to other three cases. All results indicate that the synthesised Sm...

Two type flower-like SnO2 hierarchical architectures with ultrathin nanosheets as building blocks have been controllably synthesized via tuning the presence or not of PEG under hydrothermal condition. Whether the sparsely assembled flower-like SnO2 hierarchical nanosheets or the closely assembled counterparts, the thickness of an individual nanosheet is about 50 nm, which is less than twice Debye length of bulk SnO2 at 250 °C, resulting in full electron depletion induced by oxygen adsorption. Interestingly, a comparison study reveals that an enhanced gas sensing performance for the sensor made of the closely assembled hierarchical nanosheets towards ethanol occurs over that of the other, which may be mainly attributed to the confined effect provided by numerous nano- or micro-reaction rooms for adequate gas-sensing reactions in closely assembled case.

It is essential to detect the characteristic gas products of SF6 decomposition for fault diagnosis of gas-insulated switchgear (GIS). The model of Rh doped MoS2 was built by Materials Studio software. The micro process of three SF6 partial dissociation products (SO2, SOF2, SO2F2) approaching the Rh–MoS2 surface and reaching a stable state was simulated. The modification effect of Rh doped MoS2 was studied by the key adsorption parameters such as the adsorption structure, bandgap, absorption energy, charge transfer, the total and partial density of states and electron density difference. As a result, the electrical property and chemical activity are significantly improved in comparison with the pristine MoS2 monolayers by selecting the most stable Rh doping site. Simultaneously, it was found that Rh–MoS2 monolayer had good selectivity and gas sensitivity to SO2 and SOF2 with chemical adsorption. It can also be proved by the desorption time. From the adsorption energy, the adsorption reaction of SO2F2 is not strong, but the transferred charge is large.

In this study SO2 adsorption on intrinsic graphene (IG), Ni-doped graphene (NiG) and Pd-doped graphene (PdG) has been analyzed and studied using density functional theory (DFT) based on first principles. By analyzing the adsorption energy, bond length, bond angle, charge transfer, DOS, PDOS and frontier molecular orbitals, it can be proved that NiG and PdG have excellent SO2 adsorption performance than IG. PdG has better SO2 adsorption performance than NiG thanks to the strong overlapping of peaks in PDOS and the obvious reduction of energy gap. In particular, the stable adsorption of double SO2 on NiG and PdG means that Ni or Pd doping has practical value. Therefore, the study in this paper provides a feasible direction to the detection of SO2.

MEMS gas sensor arrays and specially designed pattern recognition systems are the main research directions in the field of modern sensing technology in the engineering, especially in the smart sensing and monitoring of faults in large power equipment such as oil-immersed transformers. In this paper, the MEMS sensor array composed by eight SWCNTs-based (pure, OH functionalized, COOH functionalized, NH2 functionalized by ethylenediamine, NH2 functionalized by aniline, Ni-coated, Pd-doped, ZnO-doped) sensing units was palced in the fault characteristic gases (H2, CO, and C2H2) of oil-immersed transformers, and their gas-sensing characteristics were tested in single and mixed gas atmosphere. Combined with the DBN-DNN pattern recognition method, the qualitative identification and quantitative analysis of the sensor array in a mixed gas atmosphere was realized, and the accuracy and reliability of the results are higher than the traditional BPNN model.

Based on the density functional theory (DFT), the adsorption capabilities and electronic properties of Ag–MoS2 monolayer were discussed to fully discover the gas sensing performance to transformer oil decomposed gases (H2, CO, CH4, C2H6, C2H4 and C2H2). Specifically, the adsorption structure, adsorption energy, Mulliken charge analysis, deformation charge density, density of state (DOS), frontier molecular orbital analysis and band structure were explored. The analysis results illustrate that the adsorption to CO, C2H4 and C2H2 is strong, which is superior to the adsorption of H2, CH4 and C2H6. The narrower band gaps and increased electrical conductivity in all adsorption structures indicate that Ag–MoS2 monolayer is promising for the detection of studied gases. Therefore, the present study proposes an effective gas-sensing material to estimate the working state and insulation level of power transformers.

Two novel hierarchical WO3/NiO microspheres with porous and rough surface have been prepared through a simple one-stop hydrothermal method. Interestingly, it is a surprise that the introduction of different amounts of WO3 plays a critical role in the growth and self-assembly of nanosheets and then the morphology of microsphere. Further gas sensing experiment demonstrates that the sensor based on porous microsphere possesses prominent performance towards 100 ppm ethanol at the optimal working temperature of 300 °C compared with that of rough microsphere. It is believed that the enhanced gas sensing properties benefit from the porous structure on the surface with abundant active sites and gas passages for sufficient gas adsorption and diffusion.

In this work, hierarchical WO3-NiO microflowers have been designed and prepared through a controllable hydrothermal route for high sensitivity detection of H2S produced by SF6 decomposition. The hierarchical flower-like nanostructures assembled with numerous nanosheets were influenced by the introduction of WO3, which is regarded as a significant strategy for improving the gas sensing properties. The synthesized nanostructures were tested by various characterization to investigate the different microstructures of the nanocomposites. The H2S sensing performances of the sensors fabricated with these flower-like nanostructures were measured, which indicated that 3.0 at% WO3-NiO microflower based sensor possessed excellent properties such as higher gas responses and more prominent repeatability compared with those of other fabricated sensors. The enhanced performances might be mainly ascribed to the creation of the heterojunction at n-type WO3 and p-type NiO interface, which caused the improvement of the potential barrier and depletion layer. In addition, the larger specific surface area of flower-like nanostructures also possessed abundant sites for surface reaction.

In the paper, the adsorption of H2S on three modified graphene by doping Pd atom and introducing oxygen–containing functional groups (Pd–G, G–O and G–OH) was studied based on first principles. All the three modification methods improve the adsorption performance of graphene for H2S, among which the introduction of hydroxyl shows the best with the adsorption energy of −1.255eV. Nevertheless, Pd–G, G–O and G–OH exhibited similar adsorption properties for SO2, SO2F2, SOF2 and H2S, with the small difference of adsorption energy values. So the three modified graphene structures show poor selective adsorption performance for H2S. Then, the influence of the combine interaction of Pd atom and oxygen–containing functional group on the performance of graphene (Pd–G–O, Pd–G–OH) adsorbing H2S is further studied. Among them, the structure of Pd–G–O is stable, and the adsorption energy of Pd–G–O adsorbing H2S is −1.623eV. However, the adsorption energies of SO2, SO2F2 and SOF2 adsorbed on Pd–G–OH are −0.751eV, −0.799eV and −0.552eV, respectively. The excellent adsorption capacity of H2S on Pd–G–O is verified from the practical feasibility and selectivity. Therefore, Pd–G–O is a potential gas sensor material for selective adsorption of H2S.

The Moderate-Resolution Wide-Wavelength Imager (MWI), onboard the Tiangong-2 (TG-2) Space Lab, is an experimental satellite sensor designed for the next-generation Chinese ocean color satellites. The MWI imagery is not sufficiently radiometrically calibrated, and therefore, the cross-calibration is urgently needed to provide high quality ocean color products for MWI observations. We proposed a simple and effective cross-calibration scheme for MWI data using well calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) imagery over aquatic environments. The path radiance of the MWI was estimated using the quasi-synchronized MODIS images as well as the MODIS Rayleigh and aerosol look up tables (LUTs) from SeaWiFS Data Analysis System 7.4 (SeaDAS 7.4). The results showed that the coefficients of determination (R2) of the calibration coefficients were larger than 0.97, with sufficient matched areas to perform cross-calibration for MWI. Compared with the simulated Top of Atmosphere (TOA) radiance using synchronized MODIS images, all errors calculated with the calibration coefficients retrieved in this paper were less than 5.2%, and lower than the lab calibrated coefficients. The Rayleigh-corrected reflectance (ρrc), remote sensing reflectance (Rrs) and total suspended matter (TSM) products of MWI, MODIS and the Geostationary Ocean Color Imager (GOCI) images for Taihu Lake in China were compared. The distribution of ρrc of MWI, MODIS and GOCI agreed well, except for band 667 nm of MODIS, which might have been saturated in relatively turbid waters. Besides, the Rrs used to retrieve TSM among MWI, MODIS and GOCI was also consistent. The root mean square errors (RMSE), mean biases (MB) and mean ratios (MR) between MWI Rrs and MODIS Rrs (or GOCI Rrs) were less than 0.20 sr−1, 5.52% and within 1 ± 0.023, respectively. In addition, the derived TSM from MWI and GOCI also agreed with a R2 of 0.90, MB of 13.75%, MR of 0.97 and RMSE of 9.43 mg/L. Cross-calibration coefficients retrieved in this paper will contribute to quantitative applications of MWI. This method can be extended easily to other similar ocean color satellite missions.

Hydrogen sulfide (H2S) is an important decomposition component of sulfur hexafluoride (SF6), which has been extensively used in gas-insulated switchgear (GIS) power equipment as insulating and arc-quenching medium. In this work, electrospun ZnO-SnO2 composite nanofibers as a promising sensing material for SF6 decomposition component H2S were proposed and prepared. The crystal structure and morphology of the electrospun ZnO-SnO2 samples were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM), respectively. The composition of the sensitive materials was analyzed by energy dispersive X-ray spectrometers (EDS) and X-ray photoelectron spectroscopy (XPS). Side heated sensors were fabricated with the electrospun ZnO-SnO2 nanofibers and the gas sensing behaviors to H2S gas were systematically investigated. The proposed ZnO–SnO2 composite nanofibers sensor showed lower optimal operating temperature, enhanced sensing response, quick response/recovery time and good long-term stability against H2S. The measured optimal operating temperature of the ZnO–SnO2 nanofibers sensor to 50 ppm H2S gas was about 250°C with a response of 66.23, which was 6 times larger than pure SnO2 nanofibers sensor. The detection limit of the fabricated ZnO–SnO2 nanofibers sensor toward H2S gas can be as low as 0.5 ppm. Finally, a plausible sensing mechanism for the proposed ZnO–SnO2 composite nanofibers sensor to H2S was also discussed.

SF6 decomposition components detection is a key technology to evaluate and diagnose the insulation status of SF6-insulated equipment online, especially when insulation defects-induced discharge occurs in equipment. In order to detect the type and concentration of SF6 decomposition components, a Ni-modified carbon nanotube (Ni-CNT) gas sensor has been prepared to analyze its gas sensitivity and selectivity to SF6 decomposition components based on an experimental and density functional theory (DFT) theoretical study. Experimental results show that a Ni-CNT gas sensor presents an outstanding gas sensing property according to the significant change of conductivity during the gas molecule adsorption. The conductivity increases in the following order: H2S &gt, SOF2 &gt, SO2 &gt, SO2F2. The limit of detection of the Ni-CNT gas sensor reaches 1 ppm. In addition, the excellent recovery property of the Ni-CNT gas sensor makes it easy to be widely used. A DFT theoretical study was applied to analyze the influence mechanism of Ni modification on SF6 decomposition components detection. In summary, the Ni-CNT gas sensor prepared in this study can be an effective way to evaluate and diagnose the insulation status of SF6-insulated equipment online.

The detection of partial discharge by analyzing the decomposition components of SF6 gas in gas-insulated switchgears plays an important role in the diagnosis and assessment of the operational state of power equipment. Recently, the application of transition metal-modified MoS2 monolayer dioxide in gas detection has received wide attention. In this paper, first-principle density functional theory calculations were adopted to study the gas-sensitive response of Co-MoS2 monolayer to SOF2 and SO2F2. It is found that the conductivity of the Co-MoS2 monolayer has been effectively enhanced after Co atom doping on the MoS2 monolayer. After gas adsorption, electrons transfer from the Co-MoS2 monolayer to the gas molecules, resulting in significant reduction of conductivity of the adsorption system. The calculation results reveal that the Co-MoS2 monolayer is sensitive and selective to SOF2 and SO2F2 gases. This study provides the theoretical possibility of using Co-MoS2 as a gas sensor for SOF2 and SO2F2 gas detection.

Oil-paper insulation has excellent thermal and electrical properties is quite important. Compared with the traditional method of improving the electrical and thermal property of the insulation paper by bulk-doped nanoparticles, it is still necessary to explore new idea and method to improve its thermal and electrical performance. Functional layers of micro- and nano-structures can not only endow the surface or interface with novel properties, but also maintain the good properties of the material itself. Magnetron sputtering is one of the commonly used methods to prepare functional thin films. At here, the Al 2 O 3 /PTFE functional film was deposited on the pressboard surface by the reactive radio frequency (RF) magnetron sputtering. The influence of the Al 2 O 3 /PTFE functional film on the DC breakdown and thermal property of the sputtered pressboard were investigated. Compared with the fresh pressboard, the insulation pressboard coated by Al 2 O 3 /PTFE film had slightly lower $\varepsilon _{\mathrm {r}}^{\prime}$ in the lower frequency region. However, the difference is very small between 1-100HZ. The sputtered pressboard has higher DC pre-pressure breakdown voltage value. The pressboard sputtered PTFE for 30 min shows obvious enhancement of the DC pre-pressure breakdown performance. The thermogravimetric analysis (TGA) show that the Al 2 O 3 /PTFE functional film increase the initial decomposition temperature (IDT) and the temperature at maximum decomposition rate (TMDR) of the sputtered pressboard.

Oil is an important liquid insulating medium in oil-immersed transformer. The water content in oil is closely related to the deterioration of the performance of the insulation system. 160 oil samples that were collected from various transformers, 150 of which were set as training sets and 10 forecast sets. Input variables to the model is 242-dimension multi-frequency ultrasonic testing data, and the output of the model is the water content of the oil sample. Through the experimental method to determine the hidden layer consists of 11 neurons, the nonlinear mapping relationship. Genetic algorithm (GA) was applied to optimize the BP neural network connection weights and threshold of every layer. The results show that the correlation coefficient of water content of oil prediction model is 0.97207. The average absolute percentage error MAPE of the proposed GA-BPNN model is 9.4%. All results provide a new online detection method for water content in transformer oil.

The unique flower-like NiO/ZnO composite with porous nanosheets has been triumphantly manufactured via the one-step hydrothermal method initially. On the basis of morphology observations and ethanol gas measurements, it is considered that the construction of P-N junctions at the interface as well as the sheet-like porous microflowers architecture greatly contribute to the fantastic gas sensing properties of the prepared materials, which exhibit superb gas response value and outstanding repeatability. Furthermore, a possible formation mechanism is proposed, elucidating the process of the oriented-attachment, the self-assembly in addition to the pores-development.

Suspended sediment (SS) is an important water quality indicator of coastal and estuarine ecosystems. Field measurement and satellite remote sensing are the most common approaches for water quality monitoring. However, the efficiency and precision of both methods are typically affected by their sampling strategy (time and interval), especially in highly dynamic coastal and estuarine waters, because only limited measurements are available to analyze the short-term variations or the long-term trends of SS. Dramatic variations of SS were observed, with standard deviation coefficients of 48.9% and 54.1%, at two fixed stations in Deep Bay, China. Therefore, it is crucial to resolve the temporal variations of SS and its main influencing factors, and thus to develop an improved sampling strategy for estuarine ecosystems. Based on two years of continuous high-frequency measurements of SS and concurrent tidal and meteorological data, we demonstrated that the tide is the dominant factor influencing the SS variation among tide, wind (speed and direction), and rainfall in Deep Bay, China. For the monitoring of maximum suspended sediment concentration (SSC), the recommended optimum sampling time coincides with the occurrence of the ebb tides, whereas multiple sampling times are recommended for monitoring of minimum SSC. Although variations of SS are also affected by other factors, the recommended sampling strategy could capture the maximum and minimum SSC variations exactly more than 85% days in a year on average in Deep Bay. This study provides a baseline of SS variation and direct sampling strategy guidance for future SS monitoring and could be extended to other coastal or estuarine waters with similar climatological/tidal exposures.

Pure and Pt-decorated ZnO nanosheets were synthesized via a facile and environment-friendly hydrothermal process, and characterized by X-ray powder diffraction (XRD), field-emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectroscopy (EDS), respectively. Side-heated chemical gas sensors were fabricated with the synthesized ZnO based powders and their sensing properties to methane CH4, an important characteristic hydrocarbon contaminant extracted from power transformer oil with overheating or discharging fault, were systemically investigated. Interestingly, Pt decoration not only obviously increased the gas response of sensor fabricated with the synthesized ZnO nanosheets to CH4, but also effectively reduced its optimum operating temperature. Its highest response to 50 ppm of CH4 was about 63.45 at 240 °C, which was about two times larger when compared with the pure one. Meanwhile, the Pt-decorated ZnO nanosheets sensor exhibited shorter response-recovery characteristic, good linearity in low concentration range and excellent stability towards CH4. Those superior sensing features indicate the synthesized Pt-decorated ZnO nanosheets is a promising candidate for fabricating high-performance CH4 sensor.

A transformer is the most valuable and expensive property for power utility, thus ensuring its reliable operation is a major task for both operators and researchers. Online impulse frequency response analysis has proven to be a promising technique for detecting transformer internal winding mechanical deformation faults when a power transformer is in service. However, as so far, there is still no reliable standard code for frequency response signature interpretation and quantification. This paper tries to utilize a machine learning method, namely the support vector machine, to identify and classify the winding mechanical fault types, based on online impulse frequency response analysis. Actual transformer fault data from a specially manufactured model transformer are collected and analyzed. Two feature vectors are proposed and the diagnostic results are predicted. The diagnostic results indicate the satisfied classifying accuracy by the proposed method.

In this paper, nano Al2O3 was used as a modifier in order to improve the thermal stability of cellulose insulation paper which used in power transformer. The influence and mechanism of nano Al2O3 to the thermal stability of cellulose insulation paper were investigated by molecular simulation and experiment methods. First of all, the mechanism analysis on the surface interaction between of nano Al2O3 and cellulose indicated the easy-doping ability of nano Al2O3 to cellulose, the equation for the binding energy of surface interaction was obtained and the physical meanings of parameters in the equation were revealed. Then, nano Al2O3 with a radius of 5 A was used to modify cellulose in MS software, the variation laws of microscopic parameters were discussed. Meanwhile, thermal ageing experiment on both modified and un-modified cellulose insulation paper was performed in laboratory. The combined analysis showed that, the thermal stability of modified cellulose insulation paper improved a lot. Finally, a deep discussion on the modification mechanism of nano Al2O3 to the thermal stability of cellulose insulation paper were presented, which introduced a theoretical reference for the future research on nano-modification technology of insulation paper.

In this paper, PV module parameters of dust removal equipment are analyzed; the dust removal device model is established by using solidworks software; the motion simulation of removal process is conducted directly in solidworks motion simulation interface; a comparison of dust removal effects is made between the top-down and the left-to-right dust removal device at the same traction speed and brush dust removal brush rotation speed; a conclusion is drawn that brush traction speed, rotation speed, and helix angle have impact on dust removal effect and the two devices are close to each other in terms of dust removal effect, which provides some theoretical evidence for further design.

We successfully synthesised pure and NiO doped SnO2 p–n heterojunction microspheres with different doping levels via a facile and environment friendly hydrothermal route. The crystalline structures, surface morphologies, element components and valences of the as synthesised nanostructures were characterised by means of X-ray powder diffraction, field emission scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy respectively. SnO2 based planar chemical gas sensors were fabricated from the as prepared samples, and their sensing performances towards carbon monoxide (CO) were systematically investigated. Compared with pure SnO2 sensor, NiO doped SnO2 microsphere sensors exhibit obviously enhanced CO sensing properties, such as higher gas response, lower operating temperature etc. It might be attributed to the p–n heterojunctions formed between p-type NiO and n-type SnO2 interfaces, further increasing the amount of absorbed oxygen ions and decreasing the a...

Acetylene C2H2gas is one of the most important fault characteristic hydrocarbon gases dissolved in oil immersed power transformer oil. This paper reports the successful preparation and characterization of samarium oxide Sm2O3decorated tin oxide SnO2based sensors with hierarchical rod structure for C2H2gas detection. Pure and Sm2O3decorated SnO2sensing structures were synthesized by a facile hydrothermal method and characterized by XRD, FESEM, TEM, EDS, and XPS measurements, respectively. Planar chemical gas sensors with the synthesis samples were fabricated, and their sensing performances to C2H2gas were systematically performed and automatically recorded by a CGS-1 TP intelligent gas sensing analysis system. The optimum operating temperature of the Sm2O3decorated SnO2based sensor towards 50 μL/L of C2H2is 260°C, and its corresponding response value is 38.12, which is 6 times larger than the pure one. Its response time is about 8–10 s and 10–13 s for recovery time. Meanwhile good stability and reproducibility of the decorated sensor to C2H2gas are also obtained. Furthermore, the proposed sensor exhibits excellent C2H2selectivity among some potential interface gases, like H2and CO gas. All sensing results indicate the sensor fabricated with oxide Sm2O3decorated SnO2nanorods might be a promising candidate for C2H2detection in practice.

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.

Highly sensitive acetone chemical sensor was fabricated using ZnO nanoballs modified silver electrode. A low temperature, facile, template-free hydrothermal technique was adopted to synthesize the ZnO nanoballs with an average diameter of 80 ± 10 nm. The XRD and UV-Vis. studies confirmed the excellent crystallinity and optical properties of the synthesized ZnO nanoballs. The electrochemical sensing performance of the ZnO nanoballs modified AgE towards the detection of acetone was executed by simple current–voltage (I–V) characteristics. The sensitivity value of ∼472.33 μA·mM−1·cm−2 and linear dynamic range (LDR) of 0.5 mM–3.0 mM with a correlation coefficient (R2) of 0.97064 were obtained from the calibration graph. Experimental limit of detection (LOD) for ZnO nanoballs modified AgE was found to be 0.5 mM.

The detection of partial discharge and analysis of the composition and content of sulfur hexafluoride SF6 gas components are important to evaluate the operating state and insulation level of gas-insulated switchgear (GIS) equipment. This paper reported a novel sensing material made of pure ZnO and NiO-decorated ZnO nanoflowers which were synthesized by a facile and environment friendly hydrothermal process for the detection of SF6 decomposition byproducts. X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) were used to characterize the structural and morphological properties of the prepared gas-sensitive materials. Planar-type chemical gas sensors were fabricated and their gas sensing performances toward the SF6 decomposition byproducts SO2, SO2F2, and SOF2 were systemically investigated. Interestingly, the sensing behaviors of the fabricated ZnO nanoflowers-based sensor to SO2, SO2F2, and SOF2 gases can be obviously enhanced in terms of lower optimal operating temperature, higher gas response and shorter response-recovery time by introducing NiO. Finally, a possible gas sensing mechanism for the formation of the p–n junctions between NiO and ZnO is proposed to explain the enhanced gas response. All results demonstrate a promising approach to fabricate high-performance gas sensors to detect SF6 decomposition byproducts.

A sensitive optical system which can be used to measure accurately the concentrations of fault gases dissolved in samples extracted from transformer oil is described, and some test results are presented.