Search

Mechanical fault diagnosis of Gas Insulated Switchgear (GIS) is a popular research topic in recent years. Inspired by the fact that experienced inspectors can detect the failure of GIS only by sound, this paper proposes a novel framework for mechanical fault diagnosis based on sound classification. We extract the Mel Frequency Cepstral Coefficient (MFCC) features from the input sound signal and make an improvement to adapt to the underlying features of the GIS’s sounds. Using machine learning, we classify the extracted features with a support vector machine (SVM) to obtain a model of mechanical fault diagnosis of GIS based on sound signals. We outperform the traditional MFCC features by a significant margin, especially when the input sound signal is disturbed by noises. The F1-score can be increased by 2.47% to 21.59% with the change of the signal-to-noise (SNR) ratio.

The acidic environment has been confirmed to have significant influence on the biochar products through hydrothermal carbonization. To investigate the effect of H3PO4 on the surface properties and adsorption mechanisms of the biochar, fresh banana peels were used as feedstock and transformed into hydrochars under the catalysis of H3PO4 with concentration ranges from 0% to 50%wt. The addition of H3PO4 greatly impacted the physicochemical properties of the as-obtained hydrochars, such as carbonization degrees, pH values, amount of surface acidic functional groups and then further affected the adsorption mechanisms of lead ions on those hydrochars. Hydrochars catalyzed by H3PO4 with higher concentration showed higher degree of carbonization, lower value of pH and fewer amount of acidic functional groups, while lower content of H3PO4 could not completely catalyze the degradation reactions and resulted in larger quantity of intermolecular locked oxygen containing groups that could not be participated into the adsorption process. Among all six samples, hydrochar generated in 30%wt H3PO4 exhibited the best adsorption property of 241 mg g−1, possibly due to the largest concentration of the acidic functional groups on the surface rather than in the intermolecular structure of the carbon. It had been confirmed that the adsorption mechanisms were the combination of surface complexation, cationic exchange and part of precipitation. Hydrochars derived from fresh banana peel via hydrothermal carbonization catalyzed by phosphoric acid could be excellent adsorbents for lead removal in aqueous environments.

Fresh and dehydrated banana peels were used as biomass feedstock to produce highly effective sorbent biochars through a facile one-step hydrothermal carbonization approach with 20%vol phosphoric acid as the reaction medium. The elemental ratio of oxygen content of the two as-prepared biochars were about 20%, and the FT-IR analysis confirmed the existence of abundant surface functional groups such as hydroxyl and carboxyl which greatly enhanced the adsorption performance. The sorbents showed excellent lead clarification capability of 359mg·g-1 and 193mg·g-1 for dehydrated and fresh banana peels based biochars, respectively. The change of the CO/OCO and the appearance of PbO/PbOC on the surface after adsorption confirmed that the ion exchange might be the dominant mechanism. The dehydration and pulverization pre-treatment and the addition of phosphoric acid can benefit the formation of those functional groups and hydrothermal carbonization can be a promising method to transfer biomass like fruit peels into biochars with excellent adsorption performance.

Porous media are ubiquitous in both nature and engineering applications, thus their modelling and understanding is of vital importance. In contrast to direct acquisition of three-dimensional (3D) images of such medium, obtaining its sub-region (s) like two-dimensional (2D) images or several small areas could be much feasible. Therefore, reconstructing whole images from the limited information is a primary technique in such cases. Specially, in practice the given data cannot generally be determined by users and may be incomplete or partially informed, thus making existing reconstruction methods inaccurate or even ineffective. To overcome this shortcoming, in this study we proposed a deep learning-based framework for reconstructing full image from its much smaller sub-area(s). Particularly, conditional generative adversarial network (CGAN) is utilized to learn the mapping between input (partial image) and output (full image). To preserve the reconstruction accuracy, two simple but effective objective functions are proposed and then coupled with the other two functions to jointly constrain the training procedure. Due to the inherent essence of this ill-posed problem, a Gaussian noise is introduced for producing reconstruction diversity, thus allowing for providing multiple candidate outputs. Extensively tested on a variety of porous materials and demonstrated by both visual inspection and quantitative comparison, the method is shown to be accurate, stable yet fast ($\sim0.08s$ for a $128 \times 128$ image reconstruction). We highlight that the proposed approach can be readily extended, such as incorporating any user-define conditional data and an arbitrary number of object functions into reconstruction, and being coupled with other reconstruction methods.

On the basis of the idea that the injecting energy will improve the conditions for the formation of Cooper pairs, a smart meta-superconductor (SMSC) was prepared by doping inhomogeneous phase of luminescent nanocomposite Y2O3:Eu3+/Ag, which has the strong luminescence characteristic, in MgB2 to improve the superconducting transition temperature (TC) of the MgB2-based superconductor. Two types of Y2O3:Eu3+/Ag with different sizes were prepared and marked as m-Y2O3:Eu3+/Ag and nY2O3:Eu3+/Ag. MgB2 SMSC was prepared through an ex situ process. Results show that when the inhomogeneous phase content was fixed at 2.0 wt.%, the TC of MgB2 SMSC increased initially then decreased with the increase in the Ag content in the dopant. When the Ag content accounted for 5 wt.% of the inhomogeneous phase weight, the TC of MgB2 SMSC was 37.2-38.0 K, which was similar to that of pure MgB2. Meanwhile, the TC of MgB2 SMSC doped with n-Y2O3:Eu3+/Ag increased initially then decreased basically with the increase in the content of n-Y2O3:Eu3+/Ag, in which Ag accounted for 5 wt.% of the inhomogeneous phase. The TC of MgB2 SMSC doped with 0.5 wt.% n-Y2O3:Eu3+/Ag was 37.6-38.4 K, which was 0.4 K higher than that of pure MgB2. It is thought that the doping inhomogeneous phase of luminescent nanocomposite into the superconductor is a new means to improve the TC of SMSC.

In order to understand the influence of 750 kV power transmission and transformation project on electromagnetic radiation of surrounding environment, the data of electric field intensity, magnetic field intensity and noise from 750 kV substation equipment transmission and transformation system in some areas of Gansu Province were monitored and analyzed. The results showed that the areas near circuit breaker, switch and reactance in the power transmission system were the main areas producing high electric field intensity. The electric field intensity near the circuit breaker is the highest in substation equipment, with the average value of 12.40 ± 1.25 kV/m, while the main noise producing area is near the reactor. The study could provide scientific basis for environmental assessment and prevention of ultrahigh voltage power transmission projects.

A new leaf spot disease was observed on leaves of Rheum palmatum (Chinese rhubarb) in Northwest China (Gansu Province) starting in 2005. A Septoria-like fungus was isolated and completion of Koch's postulates confirmed that the fungus was the casual agent of the leaf spot disease. Morphology and molecular methods were combined to identify the pathogen. The fungus produced conidiomata pycnidia and the conidia were 2~5 septate, 61.2~134.1 µm in length and 3.53~5.3 µm in width, which is much larger than the known Spetoria species that infects Polygonaceae species. Phylogenic analysis of the internal transcribed spacer region confirmed that this Spetoria-like fungus is within the Spetoria genus but distinct from known Spetoria species. Together, these morphological and phylogenetic data support that the R. palmatum infecting Spetoria strain is a newly-described plant pathogenic species.