计及RSC控制的DFIG短路电流直流分量解析表达

现有文献针对计及转子变流器(RSC)控制的双馈感应风电机组(DFIG)定子短路电流解析表达,将定子磁链当作一阶直流衰减分量或忽略功率外环控制。基于DFIG电压、磁链和RSC控制方程,得到定子电流关于定子电压和定子功率的传递函数,提出定子电流的精确解析表达式。基于RSC内、外环PI参数关系,推导直流分量衰减时间常数和角频率关于PI参数的表达式。分析了RSC内外环PI参数对定子电流直流衰减分量的影响。仿真结果验证了解析表达式的准确性,为PI参数选取和保护装置测量、整定提供依据。     

花椒风味油的制取及品质研究

以花椒果皮为原料,采用大豆油热浸法制取花椒风味油。以花椒风味油的酸价、过氧化值和感官评分为考察指标,通过单因素实验和正交实验优化制取工艺条件。采用顶空固相微萃取-气相色谱-质谱联用技术对花椒风味油和大豆油中挥发性风味成分进行测定。结果表明:制取花椒风味油的最佳工艺条件为浸提温度95℃、浸提时间20 min、花椒果皮添加量15%,在此条件下制取的花椒风味油香气浓郁、麻味足、色泽好且感官评分最高,其酸价(KOH)为0. 40 mg/g,过氧化值为5. 07 mmol/kg,感官评分为9. 1。花椒风味油中维生素E总量为1 869. 86 mg/kg,远高于大豆油中的742. 07 mg/kg;甾醇含量相较于大豆油几乎不变;脂肪酸组成与大豆油的基本相同;花椒风味油中共鉴定出9类83种挥发性风味成分,大豆油中共鉴定出8类25种挥发性风味成分,花椒风味油中挥发性风味成分主要是烯烃类和醇类(相对含量86. 99%),大豆油中主要是烯烃类和醛类(相对含量87. 26%);花椒风味油中醇类18种,占总量的40. 97%,大豆油中醇类仅1种,占总量的1. 74%;花椒风味油中醛类物质含量仅为1. 91%,而大豆油中醛类物质含量为12. 69%。     

多共振分量融合CNN的行星齿轮箱故障诊断

针对行星齿轮箱中各部件所激起的振动成分混叠、早期故障特征经常被较强的各级齿轮谐波成分以及环境噪声所湮没的问题，提出一种多共振分量融合卷积神经网络（multi-resonance component fusion based convolutional neural network，简称MRCF-CNN）的行星齿轮箱故障诊断方法。首先，对振动信号进行共振稀疏分解，得到包含齿轮谐波成分的高共振分量和可能包含轴承故障冲击成分的低共振分量；其次，构建多共振分量融合卷积神经网络，将得到的高、低共振分量和原始振动信号进行自适应的特征级融合，通过有监督的方式训练模型并进行行星齿轮箱故障诊断。对行星齿轮箱实验数据的分析结果表明，该方法能够有效分类行星齿轮箱中滚动轴承和齿轮的故障，成功对行星齿轮箱故障进行诊断，同时能够进一步增强卷积神经网络对振动信号所蕴含的故障信息的辨识能力。     

基于太赫兹光谱的人参和西洋参鉴别

为了快速区分人参和西洋参，依据两者所含的人参皂苷在太赫兹波段具有不同指纹光谱，提出了一种基于人参皂苷的太赫兹光谱鉴别人参和西洋参的方法。采用MATLAB软件识别人参和西洋参的太赫兹光谱，同时根据太赫兹光谱特征并通过标准的主成分分析(PCA)区分出人参、西洋参。实验结果表明，基于太赫兹光谱的主成分分析可精确区分出人参、西洋参，并且还可以应用于其他类似物质的区分中。     

Governance choices and policy outcomes in the Latin American and caribbean electricity sector

The paper first provides, for Latin America and the Caribbean, country-specific synthetic quantitative measures of the degree of adoption of governance reforms in the electricity sector, focusing on four key dimensions (market structure, private sector participation (PSP), regulatory autonomy and operational organization). These measures are then correlated with standard policy performance outcomes measures. The findings suggest that, the reforms, considered jointly, were statistically significantly associated with higher technical and process quality but not with social or service improvements. Considered individually, increased regulatory autonomy enjoyed the highest positive correlation with desirable outcomes, but PSP has no significant correlation with any of the outcomes. In sum, as of 2018, governance reforms, considered jointly, had still not delivered on some promised payoffs, notably in addressing energy poverty, although the sensitivity analysis suggests that, for some indicators, the relationships are stronger for larger than for smaller countries.     

Gender difference in color preference across cultures: An archetypal pattern modulated by a female cultural stereotype

A gender difference in color preference among British participants has been repeatedly reported, in which both males and females show a preference for blue‐green colors, while females express an additional preference for pink‐purple colors. To investigate the robustness of gender difference in color preference in a different culture, we tested 81 young adult Indians from a school of design and compared them to 80 young British students in Psychology. The 35‐item International Personality Item Pool (IPIP) and Bem Sex Role Inventory (BSRI) questionnaires were also administered to explore possible links between personality traits, gender schemata, and color preferences. Results confirmed a gender difference in both cultures; participants collectively expressed a preference for cool over warm colors, while in addition females showed a preference for pink colors, with a warm bias for Indian females and a cool bias for British females. While these results extend gender difference to Indian culture and support the universality of an underlying pattern they also reveal a culture‐specific contribution essentially observed in females. In British participants, color preference was correlated exclusively with BSRI scores in females and overwhelmingly with IPIP scores in males; this gender‐specific pattern of correlation was not replicated in the Indian sample. Results point to an archetypal pattern of gender difference in color preference with a remarkable cross‐cultural similarity in men and a subtle but significant cultural difference in women whose origin is yet to be explained.     

A datamining approach to classify,select and predict the formation enthalpy for intermetallic compound hydrides

In this paper, two techniques of datamining tools were adopted, a principal component analysis (PCA) and artificial neural network (ANN). A PCA to classify, select and identify several combinations between transition element A and B (B = Ti, Zr, Hf, Sc, Y, La and Th) and ANN to predict ΔH for ternary hydrides. Based on the datasets selected from different works, a principal component analysis (PCA) has been applied to select, classify and identify around 76 possible combinations between transition metal elements A and B. The results showed that the clustering of combinations A-B are significantly influenced by the atomic parameters of element A, such atomic radius (R_A), Pauling's electronegativity (χ_A) and atomic electron density (Z_A/R_A³). From 76 combinations, 55 systems which have χ_A ≥ 1.5, Z_A/R_A³>1.28 and R_A < 1.46 Å are categorized as group 1. On the other hand, 21 systems which have χ_A < 1.5, Z_A/R_A³ < 1.28, and R_A > 1.46 Å are categorized as group 2. From the first group, 46 different combinations are identified and have a negative ΔH, within 18 well-known promising binary alloys of hydrogen storage.An (6-15-1) architecture of artificial neural network (ANN) has been developed to estimate the ΔH for the other ternary hydrides selected from different published works. The performance indices such as relative error, coefficient of determination (R²) and mean square error (MSE) were used to control the performance of obtained results. In addition to this, the ΔH obtained from ANN model were compared with those experimental data and theoretical results available in the literature.     

Failure of high power varistor ceramic components

Ceramic varistors are electronic components which have a sharp change (over several orders of magnitude) of their electrical resistance at a well-defined voltage (switching voltage). Starting at low voltages, the resistance is large. But by exceeding the switching voltage the resistance drops dramatically and the component acts as a good conductor. Mounted parallel to a consumer, they are used as protection devices against over voltage loading. In the technical routine yearly billions of varistors are used to protect power lines, transformation stations, electronic devices, microelectronic systems or even LEDs.In service large temperature differences may come into existence, which cause severe mechanical stresses that even may destroy the components. The basic principles of the varistor behaviour are explained and examples of mechanical failure are discussed.     

HPLC-ESI-MS/MS分析黄芪蜜炙前后活性成分差异

建立了HPLC-ESI-MS/MS联用技术分析生黄芪与炙黄芪的成分，并比较两者成分差异。采用Agilent ZORBAX SB-C18色谱柱（4.6 mm×250 mm×5 μm），以0.1%甲酸乙腈溶液-0.1%甲酸水溶液为流动相进行梯度洗脱，流速1 mL/min，检测波长203 nm，柱温25 ℃；使用ESI离子源，分别在正、负离子模式下进行全扫描和二级扫描，质量扫描范围m/z 100~2000。采用该方法鉴定了生黄芪与炙黄芪中的62种成分，并对黄芪蜜炙前后的成分进行了比较，实验结果可为黄芪炮制方法的选择提供参考依据。     

Classification of monovarietal Argentinean white wines by their elemental profile

The possibility of acquire a chemometric model to classify Argentinean white wines according to their provenance through elemental profile was assessed. A simple method for multielement determination in wines by inductively coupled plasma mass spectrometry along with chemometric pattern-recognition techniques is proposed. A total of 57 white wine samples of the main varieties from four winegrowing regions of Argentina: Mendoza, Rio Negro, San Juan, and Salta, were evaluated. The results of principal component analysis explained 95.95% of the variance data total. Linear discriminant analysis allowed correct discrimination according to the four geographical regions evaluated, using only five ultratrace elements (Ba, As, Pb, Mo, and Co). Discrimination rates higher than 96% for prediction and validation data sets were reached. The outcomes emphasize the skillfulness of ICPMS elemental determination in combination with chemometrics, for classification of white wine and show that could be a trustworthy technique to validate the geographical origin, authenticity and quality control of wines.