三相四线系统PT二次回路N线多点接地对PT二次电压降的影响以及解决办法

通过几起三相四线接线的计量用电压互感器（简称PT）二次回路N线多点接地造成PT二次压降超差现象的分析，讨论和总结了PT二次回路N线多点接地后PT二次电压降的表现特征，并提出了相应的解决办法。     

SEL-311C型保护装置几个问题的分析

对SEL-311C型保护装置现场调试和在系统实际运行中存在的问题进行分析，并提出了相应的对策。     

WBH-100型微机变压器保护中几个问题的探讨

结合现场维护、运行实际，分析了WBH-100系列微机变压器保护装置在应用中遇到的几个问题，并提出了相应看法及解决对策。     

Axial offset control of PWR nuclear reactor core using intelligent techniques

Improved load following capability is one of the main technical performances of advanced PWR (APWR). Controlling the nuclear reactor core during load following operation encounters some difficulties. These difficulties mainly arise from nuclear reactor core limitations in local power peaking, while the core is subject to large and sharp variation of local power density during transients. Axial offset (AO) is the parameter usually used to represent of core power peaking, in form of a practical parameter. This paper, proposes a new intelligent approach to AO control of PWR nuclear reactors core during load following operation. This method uses a neural network model of the core to predict the dynamic behavior of the core and a fuzzy critic based on the operator knowledge and experience for the purpose of decision-making during load following operations. Simulation results show that this method can use optimum control rod groups maneuver with variable overlapping and may improve the reactor load following capability.     

惯性仪表数据采集的一种实现方法

惯性仪表(陀螺仪和加速度计)是惯性导航系统中的核心部件。为便于导航计算机的数字处理．惯性仪表输出的信号通常要经过A／D或V／F转换。本文介绍惯性仪表输出信号经V／F转换后的信号处理方法，即陀螺仪和加速度计的输出经过V／F转换变成频率信号以后利用82C54构成的电路将其转化成具有一定脉冲当量的脉冲信号供计算机处理，按这种方法处理，计算机对惯性仪表的数据采集就转化为对脉冲信号的计数。文中从硬、软件两个方面讨论了这一设计与实现的方法。     

Chemical process fault diagnosis based on enchanted machine‐learning approach

In the chemical industry, fault diagnosis is a challenging task due to the complexity of chemical equipment. This paper proposes a machine learning‐based approach to achieve the goal of fault diagnosis. First, in order to reduce the impact of redundant features, support vector machine recursive feature elimination (SVMRFE) is used to select important features. The trained probabilistic neural network (PNN) is then used for fault diagnosis. Considering that the diagnostic performance is affected by its hidden layer element smoothing factor (σ), the modified bat algorithm (MBA) is used to optimize the PNN to obtain optimal global parameter values. The MBA adopts a better optimization mechanism than the basic algorithm and achieves excellent global convergence. It can globally optimize the smoothing factor, which effectively improves the fault diagnosis ability of the PNN. During the testing of the Tennessee Eastman (TE) process data set, we evaluate the performance of the proposed model by comparing the F₁‐score and accuracy of the different methods. The charts provided describe the fault diagnostic results and classification for the different models. The results indicate that the MBA has a better optimization ability than other traditional optimization algorithms. At the same time, the combination method proposed in this paper is also superior to others and can significantly improve the accuracy of TE process fault diagnosis.     

A process fault diagnosis method using multi-time scale dynamic feature extraction based on convolutional neural network

Unlike many other techniques used in process control, which are widely applied in practice and play significant roles, abnormal situation management (ASM) still relies heavily on human experience, not least because the problem of fault detection and diagnosis (FDD) has not been well addressed. In this paper, a process fault diagnosis method using multi-time scale dynamic feature extraction based on convolutional neural network (CNN) consisting of similarity measurement, variable ranking, and multi-time scale dynamic feature extraction is proposed. The CNN-based model containing the fixed multiple sampling (FMS) layer can extract dynamic characteristics of process data at different time scales. The benchmark Tennessee Eastman (TE) process is used to verify the performance of the proposed method.     

Evaluation of the antioxidant and antiproliferative activities of extracted saponins and flavonols from germinated black beans (Phaseolus vulgaris L.)

Flavonoids and saponins from common beans have been widely studied due to their bioactivity. This research evaluated the effect of germination of black beans (Phaseolus vulgaris L.) on the antioxidant capacity and antiproliferative activity against cancer cell lines of saponins and flavonoids extracted from seed coats, cotyledons and sprouts. Principal component analysis was performed to achieve punctual associations between the black bean saponins and flavonoids concentrations to the antioxidant capacity and the antiproliferative activities. Total phenolic content and antioxidant capacity of extracts were higher when obtained from seed coats, mainly from the 3rd germination day. The extracts obtained from seed coats after 3 and 5 germination days inhibited all cancer cell lines proliferation with no cytotoxicity against control cells. Genistein was related with the activity against mammary cancer cells but flavonols and group B saponins were more related with hepatic and colon cancers. Non-glycosilated flavonols were related with antioxidant capacity.     

配电网半绝缘电磁式PT加装消谐器后损坏原因分析研究

研究了铁磁谐振机理和特点,得出了铁磁谐振简化等效电路和PT承受电压计算方法,分析了半绝缘PT加装一次消谐器后的损坏原因,提出了改进措施。     

Data fusion for PT100 temperature sensing system heating control model

This research examines temperature monitoring and automated heating system control. The temperature sensing module utilizes a wireless ZigBee chip. A terminal interface to the RS232 transmission infrared transmitter module issues a control packet through the infrared transmitter module to the infrared receiver module to control the electromagnetic oven. ZigBee chip wireless transmission is the essential network topology design. The subsequent maintenance advantage uses the terminal interface is a Visual Basic program to design the system monitoring interface. Concrete results are: (1) adaptive weighted fusion algorithm for data fusion computing. (2) Completion of the PT100 temperature sensing modules. (3) ZigBee wireless transmission. (4) The infrared receiver, launch control module developed. (5) The design of the interface in this system covers monitoring, automatic control, manual control functions.