Prism Signal Processing of Coriolis meter data for gasoline fuel injection monitoring

Prism Signal Processing is a new recursive FIR technique offering rapid filter design and calculation. It has previously been applied to Coriolis mass flow metering to generate fast (48 kHz) flow measurement updates, facilitating for the first time the direct mass flow measurement of individual fuel pulses injected into a laboratory diesel fuel injection test bench. In this paper we describe an augmented sensor signal filtering scheme which enables rapid tracking of the desired mode of flow tube vibration while notching out undesired modes. The new scheme is applied to a gasoline injection test bench where the vibrational interference is greater than for the previously described diesel system due to increased hydraulic shock. The paper presents experimental findings which illustrate the further challenges to be overcome in order to achieve the goal of traceable direct mass flow measurement of individual fuel injection pulses. For example, when a fuel pulse is shorter than the resonant period of the flow tube, the observed phase difference appears to show dependence on the instantaneous phase of the flow tube vibration.     

基于移动窗口法的城市遥感生态质量评价研究

为进一步提高城市生态监测的精确度，在前人开展的城市生态遥感监测研究的基础上引入“区域尺度”的概念，充分考虑小区域范围内不同地物间的交互作用，并利用移动窗口模型(Moving Window-Remote Sensing Ecology Index, MW-RSEI)对沈阳市浑南区的遥感影像进行逐像元分析。实验结果表明，MW-RSEI模型和生态遥感监测模型（Remote Sensing Ecology Index, RSEI)在整体生态评价趋势上表现出一致性。但MW-RSEI模型对城市生态中的细节区域表征更明显。考虑到建筑及裸地周围植被的影响，其较差生态区域的占比仅为6%，生态评价为优的区域占比为11%。研究区生态评价结果表现得较为连续，并未出现明显的断层现象。该结果具有现实意义且与实际生态分布更为符合。MW-RSEI模型在城市生态监测中更为适用，可为相关部门提供一定的技术参考。     

Automated prediction system of household energy consumption in cities using web crawler and optimized artificial intelligence

The supply of electrical energy is critical to convenient and comfortable living. However, people consume a large amount of energy, contributing to an energy crisis and global warming, and damaging some ecological cycles. Residential electricity consumption has greater elasticity than industrial and business consumption; it therefore has high energy-saving potential. This work establishes an automated platform, which provides information about residential electricity consumption in each city in Taiwan. Machine learning was used to forecast future residential electricity demand. A nature-inspired optimization method was applied to enhance the accuracy of the best machine learner, yielding an even better hybrid ensemble model. Performance measures indicate that the resulting model is accurate and provides effective information for reference. An automatic web-based system based on the model was combined with a web crawler and scheduled to run automatically to provide information on monthly residential electricity consumption in each county and city. By providing energy consumption information across the country, power providers and government can discuss policy and set different goals for energy use. The results of this study can facilitate the early implementation of energy-saving and carbon emission-reducing in cities and aid utility companies in establishing energy conservation guidelines.     

Selection of features from power theories to compose NILM datasets

The load disaggregation concept is gaining attention due to the increasing need for optimized energy utilization and detailed characterization of electricity consumption profiles, especially through Nonintrusive Load Monitoring (NILM) approaches. This occurs since knowledge about individualized consumption per appliance allows to create strategies striving for energy savings, improvement of energy efficiency, and creating energy awareness to consumers. Moreover, by using feature extraction to devise energy disaggregation, one can achieve accurate identification of electric appliances. However, even though several literature works propose distinct features to be utilized, no consensus exists in the literature about the most appropriate set of features that ensure high accuracy on load disaggregation. Thus, beyond presenting a critical analysis of some significant features often selected in the literature, this paper proposes identifying the most relevant ones considering collinearity and machine learning algorithms. The results show that high-performance metrics can be achieved with fewer features than usually adopted in the literature. Moreover, it is demonstrated that the Conservative Power Theory can offer the most representative features for appliance identification, leading to efficient power consumption disaggregation.     

Fast power cycling protocols implemented in an automated test bench dedicated to IGBT module ageing

This paper presents fast test protocols for ageing IGBT modules in power cycling conditions, and a monitoring device that tracks the on-state voltage V_CE and junction temperature T_J of IGBTs during ageing test operations. This device is implemented in an ageing test bench described in previous papers, but which has since been modified to perform fast power cycling tests.The fast test protocols described here use the thermal variations imposed on IGBT modules by a test bench operating under Pulse Width Modulation conditions. This test bench reaches the maximal values of power cycling frequencies attainable with a given module packaging in order to optimize test duration.The measurement device monitors V_CE throughout the ageing test that is needed to detect possible degradations of wire bonds and/or emitter metallization. This requires identifying small V_CE variations (a few dozen mV). In addition, the thermal swing amplitude of power cycling must be adjusted to achieve a given ageing protocol. This requires measuring junction temperature evolution on a power cycle, which is carried out by means of V_CE measurement at a low current level (100 mA).Experimental results demonstrate the flexibility of this test bench with respect to various power cycling conditions, as well as the feasibility of the proposed on-line monitoring methods.     

Topological preservation techniques for nonlinear process monitoring

This work proposes a novel approach for the offline development and online implementation of data-driven process monitoring (PM) using topological preservation techniques, specifically self-organizing maps (SOM). Previous topological preservation PM applications have been restricted due to the lack of monitoring and diagnosis tools. In the proposed approach, the capabilities of SOM are further extended so that all aspects of PM can be performed in a single environment. First for fault detection, using SOM's vector quantization abilities, an SOM-based Gaussian mixture model (GMM) is proposed to define the normal region. For identification, an SOM-based contribution plot is proposed to identify the variables most responsible for the fault. This is done by analyzing the residual of the faulty point and an SOM model of the normal region used in fault detection. The data points are projected on the model by locating the best matching unit (BMU) of the point. Finally, for fault diagnosis a procedure is formulated involving the concept of multiple self-organizing maps (MSOM), creating a map for each fault. This allows the ability to include new faults without directly affecting previously characterized faults. A Tennessee Eastman Process (TEP) application is performed on dynamic faults such as random variations, sticky valves and a slow drift in kinetics. Previous studies of the TEP have considered particular feed-step-change faults. Results indicate an excellent performance when compared to linear and nonlinear distance preservation techniques and standard nonlinear SOM approaches in fault diagnosis and identification.     

基于70年报刊语料的现代汉语历时稳态词抽取与考察

该文基于70年跨度的历时报刊语料库,使用九种统计方法计算了词语历年的使用情况,并通过对稳定性、覆盖度和时间区分性能的考察筛选获得了规模为3 013词的历时稳态词候选词集。该词集中动词与名词各占约三分之一(其余为形容词、副词与虚词),平均词长约1.7字,前密后疏地分布于历时语料库总频序表的前7 609位,覆盖了总语料的近九成。该部分词语中包含大量构造句子结构的核心词语。它们塑造了稳态词在词长和词类上的特性。稳态词的提取可以加深对语言生活底层与基础词汇的认识,对汉语教学、中文信息处理和语言规划都具有重要意义。     

铁岗水库大坝安全监测自动化系统应用分析

为全面了解铁岗水库大坝安全监测自动化系统的运行情况，本文对系统的可靠性、稳定性和准确性等指标进行分析计算，总结系统运行过程中存在的问题，并就进一步提高水库的大坝安全监测自动化水平提出建议，得到了有益于提高水库整体水利信息化水平的结论。     

输送带冷定伸监控系统

正由青岛橡六输送带有限公司申请的专利(公开号CN 102645922B,公开日期2013-12-04)"输送带冷定伸监控系统",涉及一种输送带冷定伸监控系统。包括:(1)检测装置,用于实时检测输送带的拉伸长度,并将检测的拉伸长度转换成电压信号;(2)控制装置,用于接收电压信号并转换成数据信号,并将数据信号转换     

基于可编程逻辑控制器的电镀工艺参数自动化监控

以可编程逻辑控制器(PLC)为控制核心,辅助相关执行元器件,对电镀过程中涉及的部分关键工艺参数实施自动化监控。分模块阐述了监控原理,并结合实验进行效果验证和评定。结果表明:应用PLC控制系统,可实现工艺参数自动化、实时、准确监控,并且可获得较理想的电镀质量。