基于贝叶斯的智能电能表可靠性评估方法

针对具有高可靠、长寿命特点的智能电能表,应用加速退化试验方法进行可靠性评估是一种有效的方法。开展加速退化试验过程中,在高加速应力激发下,一方面可观测到智能电能表的性能退化,也可能出现智能电能表的整表失效。如何融合智能电能表加速寿命试验过程中的整表失效数据、性能退化数据转化得到的伪寿命数据,从而进行智能电能表的综合可靠性评估,是智能电能表可靠性评估急需解决的问题。本文研究提出基于贝叶斯方法的智能电能表可靠性评估方法,给出融合智能电能表的整表失效数据、伪寿命数据的数据处理方法及计算模型,探讨了伪失效数据计算方法、整表失效数据与伪失效寿命数据相容性检验方法等。     

琅琊山景区不同叶绿素条件下树种叶片光谱差异分析

叶绿素含量高低反映植物健康状况,研究景区树种叶片叶绿素绝对值(SPAD)不同的光谱变化规律能为叶绿素高光谱监测波段识别与景区树种管理提供理论支撑。从琅琊山景区灌木和乔木类选取9个常见树种,探讨相同树种叶片SPAD值变化时的光谱差异,同时,横向对比相同SPAD值不同树种叶片的光谱特征,并深入分析不同树种叶片SPAD值与单波段原始光谱、光谱倒数、一阶微分、二阶微分及波段组合差值指数、归一化指数、比值指数、一阶微分归一化指数、一阶微分比值指数之间的关系。结果表明：9个所测树种叶片随着叶绿素SPAD值的升高,光谱变化规律各不相同,在可见光波段区分明显,总体上,光谱反射率最高的样本组SPAD值较低;叶绿素SPAD值相同时,在可见光波段,桂花较其余树种反射率整体较高; 在780~1 350 nm波段,广玉兰叶片反射率始终排前三,其余波段变化规律不明显;原始光谱反射率的二阶微分与海桐叶片SPAD值相关系数最大,一阶微分与其余8种相关性最高;与灌木、落叶乔木叶片SPAD值相关系数最大的光谱指数分别为差值指数、一阶微分归一化指数,与常绿乔木、不分树种相关系数最大的为一阶微分比值指数。     

热敏电阻温度计的设计与制作

本文介绍了设计性实验“热敏电阻的设计与制作”的实施情况。说明了只要选题合适、要求恰当,设计性实验不仅可行,而且对物理实验训练的总结提高十分有效。     

适用于非常规工作环境中热释电型激光能量计的研制

现有的激光能量计传感器灵敏度系数都与其所处环境温度有关,在-50℃～70℃的温度范围内,灵敏度偏差较大,直接影响测量结果。为了达到消除环境温度的影响,采取在不同环境温度下对热释型能量计的灵敏度进行校准的研究方法。该校准方法与普通激光能量计的校准方法的不同之处在于对热释电型能量计进行校准时,温度由室温扩展到-50℃～70℃的温度范围。利用环境试验箱,每隔10℃固定一个温度点,进行激光能量的测量实验,得到各个温度点所对应的灵敏度修正系数,再借助最小二乘法建立起各个温度点上能量计灵敏度系数同环境温度的函数关系,从而实现了-50℃～70℃的温度范围内激光能量的准确计量。研制能直接工作于非常规工作环境下的热释电型激光能量计,对解决激光能量测量的外场需求有一定现实意义。     

对欧姆表测量误差的进一步讨论

从分析姆表测量的全过程出发,导出了电阻测量不确定度的估计公式。     

Dual-modality and dual-energy gamma ray densitometry of petroleum products using an artificial neural network

The prediction of volume fractions in order to measure the multiphase flow rate is a very important issue and is the key parameter of multi-phase flow meters (MPFMs). Currently, the gamma ray attenuation technique is known as one of the most precise methods for obtaining volume fractions. The gamma ray attenuation technique is based on the mass attenuation coefficient, which is sensitive to density changes; density is sensitive in turn to temperature and pressure fluctuations. Therefore, MPFM efficiency depends strongly on environmental conditions. The conventional solution to this problem is the periodical recalibration of MPFMs, which is a demanding task. In this study, a method based on dual-modality densitometry and artificial intelligence (AI) is presented, which offers the advantage of the measurement of the oil–gas–water volume fractions independent of density changes. For this purpose, several experiments were carried out and used to validate simulated dual modality densitometry results. The reference density point was established at a temperature of 20 °C and pressure of 1 bar. To cover the full range of likely density fluctuations, four additional density sets were defined (at changes of ±4% and ±8% from the reference point). An annular regime with different percentages of oil, gas and water at different densities was simulated. Four features were extracted from the transmission and scattered detectors and were applied to the artificial neural network (ANN) as inputs. The input parameters included the ²⁴¹Am full energy peak, ¹³⁷Cs Compton edge, ¹³⁷Cs full energy peak and total scattered count, and the outputs were the oil and air percentages. A multi-layer perceptron (MLP) neural network was used to predict the volume fraction independent of the oil and water density changes. The obtained results show that the proposed ANN model achieved good agreement with the real data, with an estimated root mean square error (RMSE) of less than 3.     

On realistic terrains

We study worst-case complexities of visibility and distance structures on terrains under realistic assumptions on edge length ratios and the angles of the triangles, and a more general low-density assumption. We show that the visibility map of a point for a realistic terrain with n triangles has complexity . We also prove that the shortest path between two points p and q on a realistic terrain passes through triangles, and that the bisector of p and q has complexity . We use these results to show that the shortest path map for any point on a realistic terrain has complexity , and that the Voronoi diagram for any set of m points on a realistic terrain has complexity and . Our results immediately imply more efficient algorithms for computing the various structures on realistic terrains.     

Measurement of microchannel fluidic resistance with a standard voltage meter

A simplified method for measuring the fluidic resistance (R_fluidic) of microfluidic channels is presented, in which the electrical resistance (R_elec) of a channel filled with a conductivity standard solution can be measured and directly correlated to R_fluidic using a simple equation. Although a slight correction factor could be applied in this system to improve accuracy, results showed that a standard voltage meter could be used without calibration to determine R_fluidic to within 12% error. Results accurate to within 2% were obtained when a geometric correction factor was applied using these particular channels. When compared to standard flow rate measurements, such as meniscus tracking in outlet tubing, this approach provided a more straightforward alternative and resulted in lower measurement error. The method was validated using 9 different fluidic resistance values (from ∼40 to 600 kPa s mm⁻³) and over 30 separately fabricated microfluidic devices. Furthermore, since the method is analogous to resistance measurements with a voltage meter in electrical circuits, dynamic R_fluidic measurements were possible in more complex microfluidic designs. Microchannel R_elec was shown to dynamically mimic pressure waveforms applied to a membrane in a variable microfluidic resistor. The variable resistor was then used to dynamically control aqueous-in-oil droplet sizes and spacing, providing a unique and convenient control system for droplet-generating devices. This conductivity-based method for fluidic resistance measurement is thus a useful tool for static or real-time characterization of microfluidic systems.     

轻质石油产品电导率仪检定系统分析

论述研制轻质石油产品电导率仪检定系统的必要性,介绍各级检定标准装置的原理和检定方法。