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To solve the problem of transformer condition recognition, this paper propose a transformer condition recognition method based on acoustic signal and One-dimensional Convolutional Neural Networks(1D-CNN). In order to verify the effectiveness of 1D-CNN algorithm in the field of transformer condition recognition, a platform for acquisition of acoustic signals from a 500 kV transformer is built to carry out the acoustic signal acquisition test for four conditions of the transformer. The acoustic signal data sets are also made, and the 1D-CNN algorithm is used to calculate the recognition accuracy of the transformer conditions. According to test results, 1D-CNN algorithm, as a new structure of deep-learning algorithm, can properly classify acoustic signals of the transformer, and its classification accuracy is higher than those of FFT-BP, SVM, FFT-SAE and other algorithms. In order to explore the internal mechanism of 1D-CNN algorithm, in this paper, a t-SNE visual analysis is also conducted to reveal the performance of 1D-CNN algorithm.

Endophytic Streptomyces sp. SSD49 inhibited eight pathogens, including the human opportunistic pathogenic microorganisms, the plant pathogenic fungi and bacteria. The growth of soybeans, tomatoes, peppers and Populus tomentosa seedings inoculated with SSD49 are remarkably promoted. Here, we constructed two P. tomentosa seedling microRNA (miRNA) libraries inoculated with (PS30d) and without SSD49 (PC30d) to explore the molecular regulatory roles in the plant response to the beneficial bacteria. Totals of 314 known and 144 novel miRNAs were identified, among which 27 known and 11 novel miRNA had significantly different expression. The targets of up-regulated miR160, miR156, ptc114 and down-regulated miR319 and other differential expressed miRNAs primarily regulated genes encoding transcription factors (auxin response factor, small auxin-up RNA, and GRAS proteins), disease resistance proteins, phytohormone oxidase, and response regulators, which could promote plant growth, influence disease resistance and miRNA biosynthesis in P. tomentosa. This is the first report on the genome-wide identification of biocontrol endophytic Streptomyces inoculation-responsive miRNAs using small RNA sequencing in P. tomentosa and these findings provide new insight into understanding the biocontrol effects of endophytic Streptomyces.

As a light-weight and ultra-thin artificial material, acoustic metamaterial have more different attributes than natural material. The study of sound insulation for acoustic metamaterial is hot, and the membrane-type acoustic metamaterials supplement the deficiency of linear sound insulation materials. The physical material parameters (young modulus and loss factors)of base material of membrane-type acoustic metamaterials (PVC) is obtained by cantilever beam dynamic measurement method. The acoustic metamaterial sound insulation analysis is simulated by CAE method based on the material parameters that measured. The configuration of the simulation accuracy is measured on impedance tube, and the design work of the acoustic metamaterial sound insulation for transformer is provided. The relationship between sound insulation and the mass on membrane-type acoustic metamaterial at the different frequencies (100Hz to 500Hz) provides the reference to set sound insulation frequency.

The problem of vibration of the buildings and transformers in the urban substation has becoming more and more socially concerned. The urban substation and its associated building are taken as the research object. the vibration tests and modal shapes of the building and each floor slab were carried out. The transformer vibration and its noise were transmitted with obvious attenuation in the structural floor slab. The vibration transmission into the lower floor slab was higher than that of into the higher one. The further away from the transformer room, the vibration characteristics are weak, and the attenuation is no longer significant. At last, the finite element model was established for the urban substation. The transformer and floor slab vibration went through the simulated analysis and the consistent analysis results were obtained.

Polyphenol from fruits and vegetables have been proved that can lower the risk of many chronic disease. However, most studies are only focus on the extractable polyphenols right now. Non-extractable polyphenols may also have many important biological effects. The objective of this study was to find the difference between the extractable polyphenol and non-extractable by alkaline hydrolysis, acid hydrolysis and enzyme hydrolysis, compare the total phenolic content, flavonoid content and tannin content, and study their anti-inflammation effect, anti-cancer effect and antioxidant effect. The results showed that NEP alkaline hydrolysis was the best way to extract mango polyphenol. It had the highest total phenolic content and tannin content. The ORAC data also showed NEP alkaline hydrolysis had the best antioxidant effect. NEP alkaline also showed the dose-dependent inhibition manner. The extractable polyphenol showed better anti-inflammation effect then non-extractable polyphenol. Overall, we can conclude the secondary extraction did in fact yield more polyphenol from residue and non-extractable polyphenol have very similar effects as the extractable polyphenol.

Abundant damage information is implicated in the bilinear time-frequency distribution of structural dynamic signals, which could provide effective support for structural damage identification. Signal time-frequency analysis methods are reviewed, and the characters of linear time-frequency distribution and bilinear time-frequency distribution typically represented by the Wigner-Ville distribution are compared. The existence of the cross-term and its application in structural damage detection are demonstrated. A method of extracting the dominant term is proposed, which combines the short-time Fourier spectrum and Wigner-Ville distribution; then two-dimensional time-frequency transformation matrix is constructed and the complete cross-term is extracted finally. The distribution character of which could be applied to the structural damage identification. Through theoretical analysis, model experiment and numerical simulation of the girder structure, the change rate of cross-term amplitude is validated to identify the damage location and degree. The effectiveness of the cross-term of bilinear time-frequency distribution for damage detection is confirmed and the analytical method of damage identification used in structural engineering is available.

Structural vibration and noise of indoor substation is getting more and more extensive attention. The 110kV urban indoor substation and its associated building are taken as the research object. The vibration and noise signal of testing points are acquired in the building and transformer room. Time domain analysis and frequency analysis for the test data are carried out. By test and analysis, vibration and noise characteristics are obtained. The transformer vibration and its noise were transmitted with obvious attenuation in the structural floor slab. The vibration transmission into the lower floor slab is higher than that of into the higher one. If the floor is far from the transformer room, the vibration and noise and the low frequency characteristic are weak and thus the attenuation is no longer significant. It is necessary that indoor substation equipment of vibration and noise transmission can be controlled.