Coastal coverage of ESA’ Sentinel 2 mission

Climatologic and anthropogenic pressures in coastal areas affect the coastal zone at different scales. With the development of new missions in open-access, satellites now represent an attractive solution for a broad public to capture local-scale coastal impacts at large scales. Here, the capability of the Sentinel 2 constellation to cover coastal areas and measure coastal processes –physical and biological. We show that Sentinel 2 enables high-frequency measurements across the globe. Cloud coverage at higher latitudes is overcome by decrease revisit time-intervals. Only around the equator, the longest revisit intervals and high cloud cover probability limits coastal measurements there. Sentinel 2 based methods are capable of estimating Digital Elevation Models for mid- to high-latitude coastal zones and sporadic spots for lower latitudes where 2 orbit swaths overlap. For the majority of the world’s coastal bathymetries can be obtained with the Sentinel 2 imagery surpassing the depth of closure (beyond this offshore limit sediment transport is limited). Only in sheltered areas, wave-based bathymetry inversion is limited but at these areas inversion through colouring (light penetration) prevails. This works shows that Sentinel 2 enables coastal monitoring as never before, large spatial scale with revisits of a few days at most of the world.     

Some additional results in the regular balloon monitoring of cosmic rays in the Earth’s atmosphere

The different types of the data recorded in the experiment of the regular balloon monitoring of cosmic rays (carried out since 1957 by Lebedev Physical Institute, Moscow, Russia, in several locations) are described. So called detailed information (the form of each pulse detected by the ground-based receiver) recorded during the last 12 years is discussed in more details. The use of these data both for getting and correcting the standard results of the experiment and for obtaining some additional information on the cosmic rays in the Earth’s atmosphere is considered.     

基于无线通信的城市路灯监控系统

通过多种通信技术和计算机对城市路灯实现集中监控，监督级、监控级与现场控制级形成三级分布式计算机控制系统。监督级与监控级之间通过Intranet／Internet交互；监控级与现场控制级之间采用无线电台、GPRS及SMS等多种通信技术。     

Real-time coseismic wave retrieving by integrated Kalman filter with observations of GPS,Glonass and strong-motion sensor

A method of real-time coseismic wave retrieving was proposed based on the tight integration of GPS, Glonass and strong-motion sensor observations, the validation and precision analysis have been made by an experimental data. The series of results have been shown that: by the integrated Kalman filter and multi-sensors, the coseismic waves can be optimally recovered by complement the advantages of each other, especially when the observation conditions are very bad. In additional, the results are not significantly effected by different receiver clock error processes for the integration solution.     

An assessment of semi-analytical models based on the absorption coefficient in retrieving the chlorophyll-a concentration from a reservoir

Monitoring chlorophyll-a (Chl-a) concentrations in inland waters is crucial for water quality management, since Chl-a is a proxy for phytoplankton biomass and, thus, for ecological health of a water environment. Chl-a concentration can be retrieved through the inherent optical properties (IOPs) of a water system, which, in turn, can be remotely sensed obtained. Quasi-analytical algorithm (QAA), originally developed for ocean waters, can also retrieve IOPs for inland waters after re-parameterizations. This study is aimed at assessing the performance of sixteen schemes composed by QAA original and re-parameterized versions followed by models that use absorption coefficients as inputs for estimating Chl-a concentration in Ibitinga reservoir, located at Tietê River cascading system, São Paulo State, Brazil. It was verified that only QAA_V5 based schemes were able to obtain reasonable estimates for image data and that by four models tested presented similar and acceptable results for QAA_V5 outputs. The best model were applied to a Ocean and Land Colour Instrument (OLCI) image. Light absorption in the reservoir showed to be dominated by colored dissolved organic matter (CDOM), and wide spatial and temporal variability of optical and water quality properties was observed.     

空客A330飞机CBMU数据库客户化及其工程管理的实现

CBMU是A330飞机电源系统中一个关键组件，负责监控电子、机械多个章节系统的跳开关状态。对于CBMU数据库软件构型的管理，通常是根据具体的硬件改装工作，由相关专业系统工程师自行控制。该方式容易导致CBMU数据库软件构型变更管理失控，严重时会影响到飞行安全。本文旨在分析梳理传统管理模式的基础上，结合实际经验，探讨构建一种新的管理模式，以达到有效管理CBMU数据库软件构型的目的。     

A data-driven health indicator extraction method for aircraft air conditioning system health monitoring

Prognostics and Health Management (PHM) has become a very important tool in modern commercial aircraft. Considering limited built-in sensing devices on the legacy aircraft model, one of the challenges for airborne system health monitoring is to find an appropriate health indicator that is highly related to the actual degradation state of the system. This paper proposed a novel health indicator extraction method based on the available sensor parameters for the health monitoring of Air Conditioning System (ACS) of a legacy commercial aircraft model. Firstly, a specific Airplane Condition Monitoring System (ACMS) report for ACS health monitoring is defined. Then a non-parametric modeling technique is adopted to calculate the health indicator based on the raw ACMS report data. The proposed method is validated on a single-aisle commercial aircraft widely used for short and medium-haul routes, using more than 6000 ACMS reports collected from a fleet of aircraft during one year. The case study result shows that the proposed health indicator can effectively characterize the degradation state of the ACS, which can provide valuable information for proactive maintenance plan in advance.     

直9涡轴8发动机的历程记录仪

本文简要介绍了适合直9涡轴8系列发动机使用的历程记录仪的硬件结构及软件设计原则。通过100多台的外场改装使用证明,记录仪改装简单、工作可靠,取得了满意的效果。     

复合材料钻削刀具状态集成学习分类技术

刀具状态监测关系到工件加工质量,因此实时掌握刀具的磨损状态具有重要的意义。针对单一模式识别分类器的局限性,提出了基于异态集成学习模型的刀具状态监测系统。在该系统中,根据集成学习基分类器选择原则,选取了支持向量机(SVM)、隐马尔科夫模型(HMM)以及径向基神经网络(RBF)这3个单分类器作为基分类器。为了验证监测系统的有效性,进行了复合材料钻削实验,提取了加工过程中的钻削力信号、振动信号的时域特征并利用局部保持法(LPP)进行了特征选择。通过与单分类器和集成学习分类效果的对比,表明了集成学习模型相比于单一基分类器具有更高的分类精度和更好的稳定性。     

基于数据挖掘的航空发动机状态参数离群点分析

利用机载数据采集系统和传感器获得的发动机状态参数往往存在粗大误差，影响故障诊断的准确性。采用数据挖掘算法中基于统计学的离群点分析，并与厂家系统的分析结果相比较，结果表明，该方法能够有效地剔除粗大误差且不会误删有用数据。