动物行为异常与地震灾害预警

地震前地壳中的应力变化会引起在一定区域范围内的地球物理场与地球化学场变化。动物有感受这种变化的能力,在地震发生前数天或数小时,动物可能会不安、抑郁或狂躁、迁徙或逃亡。动物的这种能力是在长期进化过程中形成的,动物在自我保护的同时有可能为人类提供地震预警信号。本文概述了动物感受地震灾害的机制,分析了从基因遗传水平上解释动物地震灾害避险能力的途径,阐述了找出可能作为灾害预警信号的特有动物异常反应的意义,讨论了建立试验性地震灾害动物行为异常预警系统的方法。     

关于城市应急供水系统建设的思考

从城市应急供水系统建设的紧迫性和重要性出发,分析了目前我国城市应急供水系统存在的问题和造成城市非常供水的原因。构建了城市应急供水系统的框架,将其分成工程措施和非工程措施两部分,并阐述了工程措施的类型和实施方法,以及非工程措施的各项应急机制,对建立、健全城市应急供水系统进行了探讨。     

基于ISO 16750-2的汽车电源异常现象分析

本文通过研究汽车电源异常现象的来源,结合ISO 16750-2及各大车厂的要求,对各种汽车电源异常现象进行了分类和全面的阐述,使大家对ISO 16750-2有更加深入的理解。同时对ISO 16750-2:2010中出现的几个标误进行了分析说明,可供实验室和相关产品的供需双方参考。     

基于监督局部映射的煤矿井下人员身份鉴别方法

为提高煤矿井下人员身份识别率,在局部保持投影(LPP)算法的基础上,提出监督局部映射(SLP)算法。该方法充分利用数据的局部和非局部信息及类别信息,对数据进行维数约简,使特征空间同类数据间的距离更小,不同类数据间的距离更大。该方法能够克服煤矿井下艰苦、空间受限环境中人脸、虹膜和指纹识别率不高的问题。在真实步态数据库上的实验结果表明,基于步态的煤矿井下人员身份鉴别是可行的。     

重型自卸汽车车架横梁异常断裂原因分析

针对无副车架的重型自卸汽车在使用过程中出现的车架横梁异常断裂问题,建立了以板壳单元为基本单元的自卸汽车车架有限元分析模型,采用NASTRAN有限元分析软件对车架强度进行分析.有限元分析结果表明,车架横梁异常断裂现象是横梁连接部位应力值大于材料的屈服强度引起的,这与实车车架断裂结果吻合.根据实际工艺要求,改造车架结构,将连接第2根横梁和纵梁的L板厚度变大,并将平衡悬架推力杆支座由整体式支撑改为分体式支撑,从而使两处的最大应力值分别比原结构下降20.4%和51.7%.改进后车架断裂区的强度明显提高,这表明改造方法有效.     

模式识别在火灾调查中的汽油分类问题的应用研究

在火灾调查中,检测汽油成分并对其进行正确分类尤为重要.运用GC-MS对90#和93#两种普通汽油的共50个样本进行检测,所得的GC-MS原始数据通过PCA方法进行处理,以提取有用信息,避免冗余变量进入后续计算.在此基础上应用KNN方法对这两种汽油助燃剂进行分类.结果表明, KNN方法对这两种汽油的分类准确率达到100%,且当初始数据未经标准化预处理时也能达到同样准确的分类效果.研究表明:将模式识别方法正确地运用到助燃剂鉴定和分类工作中有助于火灾调查.     

Discrimination of different social companions in spectacled parrotlets (Forpus conspicillatus): evidence for individual vocal recognition

Individual recognition is generally assumed to be a prerequisite for establishing and maintaining a complex social system. Indeed, there is good evidence that highly social species have complex systems of vocal communication with individual recognition by acoustic cues. In this study, we provide experimental evidence that vocal class and individual recognition is present in a non-passerine bird, the spectacled parrotlet (Forpus conspicillatus). Spectacled parrotlets live in a complex system of social relationships. Soon after fledging, the young establish close sibling relationships which are important for successful socialization, pairing and reproduction. In a series of playback experiments we tested if spectacled parrotlets use contact calls for vocal recognition. The results showed that spectacled parrotlets discriminate between the contact calls of different social categories. Adult birds preferred to respond to the contact calls of their mates. Subadult individuals recognized the contact calls of their siblings. During the period of pair bond formation, the affiliative contacts to the siblings decrease, but the parrotlets continue to respond to the calls of their siblings. This is the first evidence that vocal sibling recognition might outlast the period of strong sibling interaction and extends into the period of pair bond formation. In cases of mate loss or divorce, the acoustic contact to their siblings might facilitate the re-establishment of close sibling relationships. Received: 29 October 1997 / Accepted after revision: 5 April 1998     

虹膜识别在肉类食品安全追溯系统中的应用及关键技术研究

为了提高大型动物肉类食品的安全性,在研究肉类食品供应链的安全管理的基础上,将大型动物的虹膜识别技术引入食品供应链管理中,构建基于虹膜识别的大型动物肉类食品安全可追溯系统,达到肉类食品安全信息查询及出现安全问题后的个体溯源的目的。借鉴人眼虹膜识别的相关技术,以牛眼为例对大型动物虹膜识别的相关算法和虹膜定位等关键技术进行研究,运用改进的Sobel算子对图像进行边缘检测;引入二次B样条曲线算法实现了牛眼虹膜的精确定位;分析牛虹膜纹理特征的分布特点,实现了虹膜特征区域的提取及归一化处理。研究成果对大型动物的虹膜识别研究和肉类食品供应链安全管理具有一定的参考意义。     

基于FTA-SVM的车辆发动机故障识别方法

发动机结构日益复杂,其故障具有多样性和频发性的特点,收集大量故障样本存在很多实施障碍。为了提高车辆发动机的故障识别的效率和准确性,提出了一种新的结合故障树(FTA)和支持向量机(SVM)各自特点,从故障模式分析到故障类型识别的FTA-SVM故障识别方法。首先利用故障树在复杂系统故障模式分析中的优势,找出系统的故障模式,建立故障树模型,通过对故障树模型中各故障事件的分析,采集与故障事件状态相关的数据,建立数据与故障树底事件的映射模型,最后利用支持向量机在小样本数据处理中的优势,进行故障类型的识别。以发动机的失火故障为例建立了发动机失火故障树模型及故障数据与故障模式映射模型,验证了FTA-SVM方法的有效性和适用性。     

A dual-sensor-based method to recognize pipeline leakage and interference signals

During the detection of pipeline leakages, false alarms of leak detection could be markedly reduced if the interference signals resulting from pressure regulating, pump regulating or valve movements could be accurately distinguished. A digital recognition method for interference signals and leakage signals based on a dual-sensor system is proposed in this paper. It is demonstrated that the direction of the signal can be recognized by a cross-correlation calculation between two signals from the dual-sensor, one of which undergoes forward linear interpolation and backward linear interpolation. Based on this theory, the interference signal and the leak signal can be discriminated exactly, and the distance between the two sensors in the dual-sensor system can be considerably reduced without needing to increase the sampling frequency. The monotonicity of the cross-correlation function is demonstrated, and a fast discrimination algorithm based on a binary extreme search method, which decreases the computational load and maintains global optimization, is also proposed. A pre-processing method of the actual signal is proposed to decrease the identity requirement for the two sensors in a dual-sensor system. In the experiment based on artificial signals, the proposed discrimination algorithm could achieve accurate recognition of the abnormal signal, and as such, the theory and application of pipeline leak detection based on dual-sensor systems are extended.