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11.
Adesina Fadairo Temitope Ogunkunle Oreoluwa Lana Adebowale Oladepo Lawal Babajide 《Petroleum Science and Technology》2019,37(15):1747-1754
The chemical method has proved to be the most effective mitigating method of wax deposition in petroleum system as it deals with the root cause of wax formation. Most of the commercial chemicals in the industry are very expensive and toxic. This paper aims the use of biodiesel based additives for improving the rheological behavior and pour points of waxy crude from Nigeria field. The biodiesels derived additives gave better performance than the commercial chemical and the seed oils as greatly improvement in rheology and pour point values of the waxy crude were observed 相似文献
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The operational optimisation of coal-fired power units is important for saving energy and reducing losses in the electric power industry. One of the key issues is how to determine the benchmark values of the energy efficiency indexes of the units. Therefore, a new framework for determining these benchmark values is proposed, based on data mining methods. First, the energy efficiency key performance indicators (KPIs) associated with the net coal consumption rate (NCCR) were selected based on the domain knowledge. Second, the decision-making samples with minimal NCCR were acquired with the fuzzy C-means (FCM) clustering algorithm, and the corresponding clustering centres were employed as the benchmark values. Finally, based on the support vector regression (SVR) algorithm, the target values of the NCCR were obtained with the KPIs as input, and the energy saving potential was evaluated by comparing the target values with the historical values of the NCCR. An actual on-duty 1000 MW unit was taken as study unit, and the results show that the energy saving potential is remarkable when the operators adjust the KPIs based on the calculated benchmark values. 相似文献
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《The Electricity Journal》2020,33(7):106816
Using mean value theorem for integrals we show that the well-known LCOE definition is incorrect. 相似文献
14.
针对齿轮故障特征微弱,在强背景噪声下难以有效提取的问题,提出了一种改进奇异谱分解(ISSD)结合奇异值分解(SVD)的齿轮故障特征提取方法。针对奇异谱分解(SSD)算法中模态参数需凭经验选取的缺陷,基于散布熵优化算法对SSD算法进行了改进,在得到既定的一组奇异谱分量的基础上,根据峭度值最大准则筛选出了最佳奇异谱分量并进行了SVD处理,采用奇异值能量标准谱自适应地确定了信号重构阶数以还原信号和提高降噪效果。最后对信号进行包络解调以提取齿轮故障特征,将所提方法运用到仿真信号和齿轮实测信号中,并同传统包络谱、SSD包络谱以及经验模态分解结合SVD(EMD-SVD)方法进行了对比分析,结果表明,所提方法的降噪和特征提取效果更佳,能够更加有效地实现齿轮故障的判别。 相似文献
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The aim of the study was to identify the importance of individual food product attributes (the use of preservatives, processing method, shelf-life period and nutritional value) as well as their relation to the purchase behaviour. To achieve this, consumer preferences were decomposed in conditions of full access to information, and data was compared with actual consumer behaviour related to making purchasing decisions in front of the store shelf. Based on data from 338 respondents, conjoint analysis and repeated ANOVA measurements were carried out, allowing to eliminate individual behavioural patterns. The results showed a dissonance between the consumers attitudes towards the attributes and their shopping behaviour. The processing method was the most important declared attribute for consumers, meanwhile this information was the least searched for during purchase. At the same time, shelf-life period marked as the least important was the main information searched for by consumers when shopping. The results also show a clear dislike towards the use of microwaves as a preservation method, while traditional thermal preservation was marked as the most positive for consumers. In addition, consumers were classified into 3 heterogeneous groups, identifying differences in the preferences of food attributes. The obtained results have practical value relating not only to the preferences of individual attributes, but also to their various variants. The results can be a guide for companies to properly label food products. The indicated dissonance illustrates the educational gap and related insufficient motivation to get to know the product before buying it. This is extremely important in connection with technological development and new food processing methods. 相似文献
16.
摘要:为了研究退火温度对镀锌DP980+Z烘烤硬化值的影响,退火温度控制在760~820℃之间,系统分析退火温度对烘烤硬化值的影响。通过准静态拉伸试验机测量烘烤硬化值及抗拉强度,采用lepara试剂对组织中的马氏体进行着色,利用金相显微镜及图像处理软件测量马氏体的体积分数;采用扫描电镜观察DP980+Z的双相组织特点,并且将组织图片通过CAD转化成有限元图进行网格划分,建立代表性体积单元(RVE),通过有限元分析铁素体、马氏体强度对烘烤硬化值的影响。在同样的变形量情况下,DP980+Z的原始屈服强度越高,烘烤硬化值越高。 相似文献
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ABSTRACTThis paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance. 相似文献
20.
利用风电场历史功率数据预测未来一段时间内的风功率,对保障电网安全稳定运行具有重要的意义。本文提出一种基于奇异谱分析SSA(singular spectrum analysis)和长短时记忆LSTM(long-short term memory net⁃work)网络的时序特征预测框架用于短期风功率的预测。首先通过SSA对历史风功率原始数据进行降噪处理,然后经过数据转换之后,以LSTM网络为基础进行预测模型的训练,最后通过某风电场提供的两个风机的历史功率数据进行验证。实验结果表明,奇异谱分析对风电场的历史数据具有良好的降噪性,SSA+LSTM模型在测试数据上取得了较好的预测性能,能够有效进行短期风功率的预测。 相似文献