基于最小维修的石化安全设备区间截尾寿命数据分析

在石化安全关键设备寿命截尾数据的可靠性评估过程中，为避免传统可靠性评估方法未考虑维修对故障间隔时间的影响，以及中值填充法误差较大的缺点，本文提出了一种逆变换区间截尾数据填充方法。首先，在可修系统基于最小维修的假设下，通过非齐次泊松过程描述系统的故障趋势，利用逆变换填充得到监测区间的缺失数据；随后根据蒙特卡罗期望最大化算法，获得填充数据的参数估计值。通过蜡油加氢装置紧急泄压阀的案例分析，该算法能够很好地融合已有数据，得到的形状参数估计值偏差与中值填充法相比缩小4%以上，从而验证了该算法的有效性；这有助于安全关键设备的定量化完整性管理，保障石化装置平稳运行。     

烟气多污染物协同处理催化陶瓷过滤管的研究进展

燃烧烟气中各污染物的排放是大气污染的最主要来源，针对烟气多污染物的治理意义重大。本文综述了国内外目前关于烟气多污染物脱除的两种技术，即传统串联脱除技术和一体化协同脱除技术。相比于传统串联脱除工艺，多污染物一体化协同脱除技术具有占地面积小、运行费用低、应用领域广的优点，是烟气多污染物治理的发展趋势。而陶瓷过滤管催化剂技术以其独有的非对称、孔径梯度变化的结构特性，成为一种极具应用前景的一体化协同脱除新技术。国内外关于陶瓷过滤管催化剂的研究主要从过滤管元件的选材和负载脱硝催化剂的工艺方法这两方面，围绕过滤管催化剂的催化活性、过滤压降及性能稳定性的进行研究，取得了一定的成果。结合当前陶瓷过滤管催化剂的研究现状，对今后烟气多污染物陶瓷过滤管催化剂技术的发展提出了建议。     

基于深度学习的传感器优化布置方法

针对传感器优化布置(optimal sensor placement,简称OSP)问题,提出了一种新的使用深度神经网络的解决方案,并以简化的桥梁形状的桁架结构中的振动测试传感器优化为例进行了验证。首先,选择一种传统的传感器优化布置方法,对自动化生成的大量不同的桁架结构分别进行传感器优化布置计算,将所得优化布置结果在进行数据预处理后构建出深度学习方法所需要的训练集与验证集;其次,使用Python语言和深度学习框架TensorFlow设计实现与本研究问题适配的深度神经网络模型并训练;然后,随机生成了新的桁架结构参数;最后,将深度神经网络输出的传感器布置结果和传统方法的计算结果进行了比较,验证了本研究方法的有效性以及在速度上、可移植性与可扩展性方面的性能优势。     

A neural network based technique for vibration characterization using Gaussian laser beams

This paper presents a neural network technique combined with an optical measurement system for the characterization of mechanical vibrations in industrial machinery. In the proposed system, the Gaussian beam of a laser source illuminates on an array of photodetectors. If either the laser source or the photodetector array is coupled with a vibrating system, then the optical powers detected by the photodetectors will vary accordingly, and are expected to reflect the magnitude and frequency of the X–Y planar vibrations of the monitored system. The time-varying optical powers are input to an artificial neural network-based vibration monitoring system which maps the power distributions to the X–Y position of the laser beam center. An experimental setup of the system is built and used for training and testing purposes. The obtained experimental results demonstrate the adequacy of combining optical techniques with neural networks to estimate the vibration frequency and magnitude. Estimated frequencies were within 1% of the actual ones, and the estimated magnitudes were within 29% of the actual magnitudes when using a chirp signal in the training phase. The magnitude estimation percentage error was further reduced below 12% when the neural network was trained with a decaying chirp signal.     

中控机房的改造思路

由于我台倒班方式，造成了技术管理分散，不利于人才的培养和电台健康的发展。为进一步提高电台安全播出管理水平，推进电台的自动化建设，充分利用现代化手段，对中控机房进行了改造。新模式的成功实施，能极大地提高我台安全传输发射水平。     

强化矿山救护队员人身安全的措施

通过对矿山救援现状的了解,发现其中存在的问题和隐患,并制定有效且适用的维护救护队员安全的解决措施,提高救援安全性,维护救援队员的人身安全,并为救援及相关人员提供参考和借鉴。     

基于云概率密度分布估计的大坝监测数据分析

大坝运行监测易受自然环境和监测条件影响，存在时间和空间上的变异性，监测数据具有不确定性。以云理论的随机性和不确定性分析方法为基础，并与空间数据辐射思想相结合，建立了云滴概率密度分布估计模型，然后导出云概率密度分布函数，依据样本监测数据推求母体空间数据的分布特征，并设计了基于逆向云算法云变换的计算程序。分析陆浑水库1979~1999年测压管监测数据和位移变形数据的云概率密度分布特征和云数字特征，得出了20 a来大坝的数据分布特征和运行状态。监测数据分析结果表明，云概率密度分布估计不仅能有效合理地分析大坝的运行状态，而且能够依据云数字特征来判断监测状态和监测环境的异常变化。      

Voltage reference architectures for low-supply-voltage low-power applications

This paper presents a voltage reference generator architecture and two different realizations of it that have been fabricated within a standard 0.18 μm CMOS technology. The architecture takes the advantage of utilizing a sampled-data amplifier (SDA) to optimize the power consumption. The circuits achieve output voltages on the order of 190 mV with temperature coefficients of 43 ppm/°C and 52.5 ppm/°C over the temperature range of 0 to 120°C without any trimming with a 0.8 V single supply. The power consumptions of the circuits are less then 500 nW while occupying an area of 0.2 mm² and 0.08 mm², respectively.     

Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

Investigating software testing and maintenance reports: Case study

ContextAlthough many papers have been published on software development and defect prediction techniques, problem reports in real projects quite often differ from those described in the literature. Hence, there is still a need for deeper exploration of case studies from industry.ObjectiveThe aim of this study is to present the impact of fine-grained problem reports on improving evaluation of testing and maintenance processes. It is targeted at projects involving several releases and complex schemes of problem handling. This is based on our experience gained while monitoring several commercial projects.MethodExtracting certain features from detailed problem reports, we derive various measures and present analysis models which characterize and visualize the effectiveness of testing and problem resolution processes. The considered reports describe types of problems (e.g. defects), their locations in project versions and software modules, ways of their resolution, etc. The performed analysis is related to eleven projects developed in the same company. This study is an exploratory research with some explanatory features. Moreover, having identified some drawbacks, we present extensions of problem reports and their analysis which have been verified in another industrial case study project.ResultsFine-grained (accurate) problem handling reports provide a wider scope of possible measures to assess the relevant development processes. This is helpful in controlling single projects (local perspective) as well as in managing these processes in the whole company (global perspective).ConclusionDetailed problem handling reports extend the space and quality of statistical analysis, they provide significant enhancement in evaluation and refinement of software development processes as well as in reliability prediction.