电动轮自卸车事故分析与监控系统研究

电动轮自卸车是集发动机、发电机、电动机、液压系统、电控系统于一体的大型运输车辆,发生安全事故会造成重大损失。笔者对造成事故的人为因素和设备因素进行了研究,并用故障树对电动轮起火事故作了较详细的分析,确定了造成事故的重要因素。在此基础上设计了基于CAN总线的安全监控系统。该系统以单片计算机为核心,采用模块化结构,组成控制器局域网络,进行分布式控制。监控系统由硬件系统和软件系统两部分构成。对发电机、电动机、发动机进行技术状态监测的同时监测驾驶员的疲劳状态和违章操作情况,可以减少由人为因素和设备因素造成的安全生产事故。对大型工矿设备的安全技术保障有一定的借鉴作用。     

机车控制与监视系统冗余控制方法

为解决机车控制系统冗余切换导致非操作端的显示屏出现失联状态的问题,提出整体冗余切换和部分冗余切换相结合的控制方法;分别检测主微机和辅微机自身的电源板卡、控制器局域网络(CAN)板卡和高级数据链路控制(HDLC)板卡是否为失效故障状态,是则进行整体冗余切换,将主系统整体冗余切换至辅系统;否则进入部分冗余切换,将失效板卡冗余切换至另一系统的对应板卡。在软件方面,针对数字量输入或输出类板卡、模拟量输入类板卡、频率量输入板卡,分别提出严格的冗余切换判定条件;在硬件方面,判断主辅2个系统中任一系统是否存在。研究表明:控制方法提高了硬件的冗余度和冗余切换的准确性,使切换无间隙,方法具有可操作性。     

长在心上的树

<正>奶奶的一生竟和一棵树有关。小时候,我经常看到奶奶望着门前的树发呆,这是一棵槐树。我就问奶奶你看啥?奶奶说是看树。我心里就奇怪,这树有啥看的呢?奶奶就说,这不是一棵普通的树,而是长在心里的树,等你长大后,你就明白了。每年春天,槐树就开满了花,树上就像落了一层厚厚的雪,雪花上飞满了嗡嗡叫的小蜜蜂。我发现,每年槐树开花,奶奶的脸上就布满了笑容,看槐树时眼里就多了几丝柔情。一天,奶奶赶集去了。我偷偷爬上树,摘了不少槐花,还弄断了不少树枝,我摘槐花是想让我妈给我做槐花饭吃。下午,奶奶回来了,奶奶见我弄得满地的槐花,非常     

兵头将尾(9)

报社记者的到来,让兵哥班的弟兄们找到了倾诉的对象。他们将兵哥的班组管理法如数家珍地抖落了出来。自从班上的事迹上报后,兵哥班的成员们开始忘乎所以了。兵哥利用跟班组成员喝酒的机会,绵里藏针地将大伙儿教育了一番。巷道凿偏了,队长赫金非说是兵哥班狗子挪了测点。关键时刻,班组原始工作记录为狗子证明了清白。     

相依相偎的恋人

一对年轻的恋人不紧不慢地在街上并肩而行。到了壶山西路与后巷路交界处停了下来。女的在路边等,男的横穿马路到对面去。先在一部面包车边停下并张望着。不久,他钻进车内。五分钟后,面包车的大灯亮了。面包车绕了个弯,将对面马路上的女人带上,然后往北行车。车经过后巷路、莆阳路,到了天九湾后找不到了。此时是2011年5月14日凌晨1时04分。天亮后,城厢分局刑侦队接到了丢     

“逃之夭夭,遑遑其途”

人多了,什么样的品种都有;车多了,什么离奇的事故都有;出了事故后,什么样的处理方式都有。这几年,随着车子数量的猛增,各种各样的车祸层出不穷,令人心生惶恐。本来,出了事故,打个122,等交警来处理,假如有伤者,赶紧打120,先抢救人要紧,这,都是正道。可是,事到临头,就不是这样子了,可以说,考验人的时候到了。     

安监局长[小说连载]

上期回顾:乡镇配备了管安全的副乡镇长,安监站也招聘了安监员,安全生产环境有了较大改观。雯雯暑假回家为父亲带来了介绍国外金矿在井下设立安全庇护所的资料,欧阳山也有了在井下设立安全庇护所的打算。在欧阳山的坚持和黄奇的努力下,红河煤矿设立了安全庇护所,宏阳市所属的大型煤矿也都设立了安全庇护所。事情总也解决不完,大胡子不能被确诊为矽肺病,他来找欧阳山为他主持公道。     

高层建筑消防安全管理创新方法研究

随着高层建筑数量的增加,消防安全管理变得日益重要。本文深入探讨了高层建筑消防安全管理的方法创新。首先,分析了高层建筑消防安全管理现状及面临的挑战,指出了构建智能化消防系统的重要性,并讨论了其优化途径。其次,探索了基于风险评估的预防策略,强调了应急响应和疏散策略的重要性。最后,着重讨论了提升消防安全意识和人员培训的策略。综合这些创新方法,以期为高层建筑消防安全管理提供一套有效的解决方案,切实提高消防安全水平。     

石墨烯环氧树脂复合材料的制备和阻燃性能的研究

合成并表征了石墨烯,然后通过溶剂法制备石墨烯/环氧树脂复合材料,研究了石墨烯对环氧树脂复合材料的热稳定性和燃烧性能的影响。热重分析数据显示,石墨烯可以显著提高环氧树脂的热稳定性。锥形量热仪测试结果表明,石墨烯降低了环氧复合材料热和烟气的释放。炭渣的扫描电镜(SEM)图揭示了石墨烯减少了环氧树脂炭层孔洞的生成,提高了炭层的致密度,从而增强了炭层的阻隔作用。     

安全小故事

寒号鸟有一种小鸟叫寒号鸟。秋天到了,鸟们都各自忙开了,有的结伴飞到南方越冬;有的留下来,整天辛勤忙碌,积聚食物,修理窝巢,做好过冬的准备。只有寒号鸟,既没有飞到南方去的本领,又不愿劳动。冬天终于来了,鸟们都归到自己温暖的窝巢里。到了夜间,寒号鸟只有躲在石缝里,冻得浑身直哆嗦,他不停地叫着:好冷啊,好冷啊,等天亮了我一定造个窝。等到天亮后,太阳出来了,温暖的阳光一照,它又忘记了昨夜的寒冷。最后,他没能度过寒冷的冬天,终于冻死在岩石缝里了。小故事折射出大道理:不能好了伤疤忘了痛。安全生产一定要牢记"安全第一,预防为主"的方针,决不能敷衍了事,得过且过。     

Quantitative risk analysis of urban natural gas pipeline networks using geographical information systems

This paper presents a novel quantitative risk analysis process for urban natural gas pipeline networks using geographical information systems (GIS). The process incorporates an assessment of failure rates of integrated pipeline networks, a quantitative analysis model of accident consequences, and assessments of individual and societal risks. Firstly, the failure rates of the pipeline network are calculated using empirical formulas influenced by parameters such as external interference, corrosion, construction defects, and ground movements. Secondly, the impacts of accidents due to gas leakage, diffusion, fires, and explosions are analyzed by calculating the area influenced by poisoning, burns, and deaths. Lastly, based on the previous analyses, individual risks and social risks are calculated. The application of GIS technology helps strengthen the quantitative risk analysis (QRA) model and allows construction of a QRA system for urban gas pipeline networks that can aid pipeline management staff in demarcating high risk areas requiring more frequent inspections.     

Association analysis of accident factors in petrochemical storage tank farms

In order to identify and clarify the association between the factors leading to accidents in a petrochemical tank area, this study analyzes investigation reports of 212 petrochemical tank farm accidents and combines this with the “association rule” mining and science related to complex networks. The main risk factors are determined and a risk factor data set is constructed; 75 association rules are extracted from the factor data set based on the Apriori algorithm. Then the obtained association rules are used to construct an accident factors network of the petrochemical storage tank area, and the topology characteristics of the network are further analyzed to reveal the importance of factors. Factors with large node degree, betweenness, and clustering coefficients are obtained, such as “violation of operating regulations”, “high concentration of flammable gas in the air”, “lack of experience and professional skills”, etc. These factors play an important role in the formation and development of accidents. The results also show that the accident cause network of the petrochemical storage tank area has a small average shortest path length and a large cluster coefficient, indicating a relatively close connection between the accident factors. The contributions of this study is not only extracting the hidden relationships among contributory factors to tank farm accidents using association analysis, but also revealing which factors are more important for the tank farm safety through the complex network.     

两类新型神经网络及其在安全评价中的应用

详细讨论小波神经网络(WNN)和模糊神经网络(FNN)的构造以及训练学习过程,并针对安全评价问题分别完成算例。典型算例表明:小波神经网络具有很好的逼近与映射能力,并且有很强的泛化能力;模糊神经网络将模糊数学与人工神经网络相互融合起来,有效提升了系统的智能功能。两类新型神经网络使得人-机-环境系统工程中的许多安全评价问题有了更广泛的量化工具,并具有安全评价的量化较准确的特点。     

Automatic estimation of crowd density using texture

This paper considers the role of automatic estimation of crowd density and its importance for the automatic monitoring of areas where crowds are expected to be present. A new technique is proposed which is able to estimate densities ranging from very low to very high concentration of people, which is a difficult problem because in a crowd only parts of people's body appear. The new technique is based on the differences of texture patterns of the images of crowds. Images of low density crowds tend to present coarse textures, while images of dense crowds tend to present fine textures. The image pixels are classified in different texture classes and statistics of such classes are used to estimate the number of people. The texture classification and the estimation of people density are carried out by means of self organising neural networks. Results obtained respectively to the estimation of the number of people in a specific area of Liverpool Street Railway Station in London (UK) are presented.     

采动影响下公路路基路面观测站布设方法研究

随着我国交通事业的快速发展以及煤炭资源消耗量的日益增加,矿区高等级公路网络越来越密集,高等级公路下采煤已成为必然趋势。而近年来由于路下采煤对公路造成破坏的案例频频出现,这不仅给国家造成严重的经济损失,而且也对人民的生命财产安全构成威胁。针对我国公路下压煤量较大,矿区公路破坏现象严重,采动影响下公路路基路面观测站布设方法研究甚少的现状,根据高等级公路路基路面自身的特点,分析了地下开采对矿区公路路基路面造成的破坏形式,并根据预计结果,提出了开采影响下高等级公路路基路面观测站的布设方法,并以某矿区一高等级公路为例,通过FLAC3D数值模拟,提取路基路面上原设计观测点的移动变形值,并将其与实测值进行对比。结果表明:二者的最大下沉值仅相差200mm,在误差允许范围内。这为说明和验证上述提出方法的正确性和合理性提供了依据。此外,为了预防和减少事故的发生、保护劳动者人身财产安全,提出了采动影响下公路路基路面的保护措施。     

石化装置火灾爆炸贝叶斯网络与防护层集成分析

复杂的石油化工装置在运转过程中存在诸多不确定因素,易发生火灾、爆炸等重大事故,给安全生产带来极大威胁。考虑到传统的系统安全分析方法在风险评估中存在一定局限性,引入贝叶斯网络与防护层集成分析模型。应用GeNIe软件将系统故障树转成贝叶斯网络,根据贝叶斯双向推理进行故障预测和诊断,快速识别系统薄弱环节并确定为风险贝叶斯故障节点,结合防护层分析提出相应的独立防护层,确定剩余风险水平。实例应用表明,所构建的贝叶斯网络与防护层集成分析模型对复杂系统进行风险评估是可行的,较传统的事件树、故障树分析方法更加科学、合理。     

Emergency venting into redundant pipelines

The evolution of pressure, temperature, and gas inventory during containment of blowdown from two high pressure gas networks into a third lower pressure relatively large redundant pipeline is followed through a simple lumped parameter model. Numerical solution of the non-linear model equations enabled to study the effects of relevant operating conditions on the system's dynamics. The effects of initial pressure difference between the supply and receiving networks, ratio of discharge orifice to pipe diameters in the supply networks, and heat transfer from the surroundings are investigated. A set of computer generated results are presented to demonstrate vividly the effect of the above variables on the percent of gas recovered in the lower pressure pipeline, the blowdown time, and the minimum temperatures reached in the networks.     

基于人工神经网络的二元液体闪点预测

建立了一个基于人工神经网络的理论模型,用于预测二元混合液体的闪点.根据所研究混合液体的物理性质,选择了相关黏度、表面张力等物理参数来表征闪点,以这些参数作为输入参数,二元混合液体的闪点作为输出值,应用反向传播(BP)人工神经网络方法对两者之间的内在定量关系进行模拟.结果表明,闪点预测值与实验值符合良好,优于传统的计算方...     

Application of Neural Networks in Active Noise Reduction Systems

Active noise reduction systems based on a control unit in the form of a finite impulse response filter assume the linearity of every single component. Neural networks, which have so far been seldom used in this field, are a kind of a filter with the ability to project nonlinear characteristics of an active noise reduction system. This paper presents some simulation research studies of active noise reduction systems based on neural networks. Also presented are results of the operation of systems with different levels of complexity as well as the influence of different parameters of a neural network and of the system itself on those results.