环境减灾卫星影像森林火灾监测技术方法研究

森林火灾是世界性的、频繁发生的重大自然灾害。随着国内外航天科技的迅猛发展,卫星遥感技术特别是红外卫星遥感已成为森林火灾监测的一种有效手段。我国的环境一号卫星A、B星(简称HJ-1A卫星、1B卫星)于2008年9月成功发射,其中的HJ-1B卫星搭载了红外多光谱相机,在森林火灾监测方面具有得天独厚的优势,可在早期的火灾发现、中期的灾害跟踪、后期的灾害损失评估中发挥重要作用。本文主要分析了环境减灾卫星在森林火灾监测方面的优势,对环境减灾卫星森林火灾监测技术和方法进行了研究。     

Operational active fire mapping and burnt area identification applicable to Mexican Nature Protection Areas using MODIS and NOAA-AVHRR direct readout data

Since 1999, the National Commission for the Knowledge and Use of the Biodiversity (CONABIO) in Mexico has been developing and managing the “Operational program for the detection of hot-spots using remote sensing techniques”. This program uses images from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites and from the Advanced Very High Resolution Radiometer of the National Oceanic and Atmospheric Administration (NOAA-AVHRR), which are operationally received through the Direct Readout station (DR) at CONABIO. This allows the near-real time monitoring of fire events in Mexico and Central America. In addition to the detection of active fires, the location of hot spots are classified with respect to vegetation types, accessibility, and risk to Nature Protection Areas (NPA). Besides the fast detection of fires, further analysis is necessary due to the considerable effects of forest fires on biodiversity and human life. This fire impact assessment is crucial to support the needs of resource managers and policy makers for adequate fire recovery and restoration actions. CONABIO attempts to meet these requirements, providing post-fire assessment products as part of the management system in particular for satellite-based burnt area mapping. This paper provides an overview of the main components of the operational system and will present an outlook to future activities and system improvements, especially the development of a burnt area product. A special focus will also be placed on the fire occurrence within NPAs of Mexico.     

EST3火灾报警系统的应用层通信协议剖析

给出通信协议剖析的一般方法和步骤,介绍GE爱德华EST3火灾报警系统的组成。对该系统串行通信协议的结构以及数据链路层和应用层的帧格式进行剖析。举例说明其应用层的基本分组格式,包括命令服务帧格式、报告服务帧格式和日期／时间通告服务帧格式。     

基于可拓神经网络的火灾探测算法

为解决传统单一传感器式的火灾探测器容易造成火灾报警的漏报和误报的问题,采用多传感器信息融合技术,将温度、烟雾浓度和CO浓度等多个参数相结合,进行综合分析,对火灾进行早期预测。采用可拓神经网络作为数据融合算法,以温度、烟雾浓度、CO气体浓度三个物理参量作为输入,以三种火灾预警等级作为输出。通过仿真分析结果表明：火灾正确识别率很高,达到93.9%以上。同时通过与传统BP神经网络的对比,表明可拓神经网络在数据融合的速度和可靠性上有突出的优势,从而使可拓神经网络实际应用于火灾早期预测成为可能。     

一种机载火控系统自动测试平台的设计及实现

针对一般典型机载火控系统的测试需求,提出了一种基于PXI总线和ini配置文件的自动测试平台的设计及实现方法。用户可以在该自动测试平台上"零编程"搭建自动测试系统。     

A fuzzy reasoning and fuzzy-analytical hierarchy process based approach to the process of railway risk information: A railway risk management system

Risk management is becoming increasingly important for railway companies in order to safeguard their passengers and employees while improving safety and reducing maintenance costs. However, in many circumstances, the application of probabilistic risk analysis tools may not give satisfactory results because the risk data are incomplete or there is a high level of uncertainty involved in the risk data. This article presents the development of a risk management system for railway risk analysis using fuzzy reasoning approach and fuzzy analytical hierarchy decision making process. In the system, fuzzy reasoning approach (FRA) is employed to estimate the risk level of each hazardous event in terms of failure frequency, consequence severity and consequence probability. This allows imprecision or approximate information in the risk analysis process. Fuzzy analytical hierarchy process (fuzzy-AHP) technique is then incorporated into the risk model to use its advantage in determining the relative importance of the risk contributions so that the risk assessment can be progressed from hazardous event level to hazard group level and finally to railway system level. This risk assessment system can evaluate both qualitative and quantitative risk data and information associated with a railway system effectively and efficiently, which will provide railway risk analysts, managers and engineers with a method and tool to improve their safety management of railway systems and set safety standards. A case study on risk assessment of shunting at Hammersmith depot is used to illustrate the application of the proposed risk assessment system.     

A mobility constraint model to infer sensor behaviour in forest fire risk monitoring

Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.     

面向火灾救援的室内定位与逃生路径规划系统

在发生火灾等紧急情况时,由于高层楼宇空间小、出口少的结构特性,受困人员逃生往往很困难。针对传统的被动引导逃生方式中信息获取有限、易产生人群聚集等缺点,该文提出主动式逃生导航的概念,设计了一种改进的K-Means室内定位方法,结合人群密度检测与环境信息采集,进行路径导航,实现了一套基于传感器网络与智能手机的定位导航系统。实验表明,该系统能较好地提高定位精度,避开火灾点,增大每个人的逃生几率,该文为室内逃生导航方案提供了新的思路。     

火焰的红色饱和度-亮度模型

通过研究不同的火焰图像,发现了火焰图像亮度的空间分布规律及不同像素之间红色饱和度随亮度的变化规律,提出了火焰图像的红色饱和度亮度（RL）模型。该模型描述了火焰图像的像素参数在不同像素间的变化规律。在在火灾探测应用中,可通过图像分割将疑似火焰图像从摄像头拍摄的视频中提取出,通过RL模型判定是否发生了火灾。