Optimal Configuration and Performance of Heat Engines with Heat Leak and Finite Heat Capacity

The optimal configuration of a class of two-heat-reservoir heat engine cycles in which the maximum work output can be obtained under a given cycle time is determined with the considerations of heat leak, finite heat capacity high-temperature source and infinite heat capacity low-temperature heat sink. The heat engine cycles considered in this paper include: (1) infinite low- and high-temperature reservoirs without heat leak, (2) infinite low- and high-temperature reservoirs with heat leak, (3) finite high-temperature source and infinite low-temperature sink without heat leak, and (4) finite high-temperature source and infinite low-temperature sink with heat leak. It is assumed that the heat transfer between the working fluid and the reservoirs obeys Newton's law. It is shown that the existence of heat leak doesn't affect the configuration of a cycle with an infinite high-temperature source. The finite heat capacity of a high temperature source without heat leak makes the cycle a generalized Carnot heat engine cycle. There exists a great difference of the cycle configurations for the finite high-temperature source with heat leak and the former three cases. Moreover, the relations between the optimal power output and the efficiency of the former three configurations are derived, and they show that the heat leak affects the power versus efficiency characteristics of the heat engine cycles.     

气体泄漏传热模型及其有限元分析

对气体发生泄漏时漏孔处的流动与传热耦合特性进行研究。分析泄漏流动状态并考虑摩擦力影响,推导气体泄漏描述方程,利用焦耳-汤姆逊系数计算泄漏节流温差并采用压缩因子进行修正。基于有限元方法建立传热模型,对泄漏稳态流与热传导的耦合场进行仿真分析,进而通过红外热成像方式实现泄漏点定位。仿真与实验结果表明,该传热模型较好地表征了泄漏发生时漏孔处的热特性,为利用红外成像技术的泄漏定位方法奠定了基础。     

漆包机烘炉热能平衡模糊控制系统设计与实现

漆包机烘炉温度系统的实时性和稳定性,关系到漆包线产品质量。针对漆包机烘炉热能系统特点,提出了一种的漆包机烘炉的热能平衡模糊控制系统,该系统提出了模糊热能平衡控制、PID温度控制结合的漆包机温度控制系统的设计思路。针对漆包机烘炉结构和系统特性进行研究,根据热能平衡方程建立漆包机烘炉系统的温度模型;利用热力学相关理论知识分析热能的输入输出的主要组成部分,计算烘炉的总热量;并提出热能平衡模糊控制系统原理流程图,设计相关的软、硬件模块加以实现。试验与测试表明,该热平衡系统为烘炉内各加热区域的温度调节提供了可靠保障;使烘炉的温控能够自适应环境温度的变化;热平衡系统以节约电能为准则,最大限度地减少电能消耗,提高产能比。     

基于飞腾处理器的瘦客户机散热结构设计

基于目前国产处理器的瘦客户机整机功耗相对较高,利用常用的无风扇散热的被动散热方式在整机散热性能方面稍显不足,尤其是存在散热死区,从而设计了一种基于飞腾四核处理器的瘦客户机。该瘦客户机采用双散热模组设计,采用4个进风道和2个出风道设计,使得机体内部无散热死区,实现整机超强的散热性能。温度测试数据表明：在25℃环境中,机器满负荷工况运行时,机体内各测试点的温度均在52℃以内,满足所有元器件的工作温度要求;同时,机器箱体外表面温度低于36℃,用户体验感良好。     

嵌入式Email发送平台的设计和实现

随着现代计算机技术和互联网技术的飞速发展,嵌入式系统成为当前IT行业最热门的焦点之一.本文设计了一种基于嵌入式的Email发送平台.利用此平台,无人值守的嵌入式Internet设备可以使用Email把特定事件和异常信息直接发送到设备管理员信箱.与远程在线监控方式相比,用Email方式传送报警信息可以降低系统总体成本.     

基于热负荷变化的后混合饮料机温度控制参数优化整定

介绍后混合饮料机的工作原理,分析CCDX型后混合饮料机温控参数设置的固有缺陷,通过改变糖浆的冷却方式,并利用NTC测得的温度和时间的比值(即升/降温速度)来反映热负荷的变化,从而设定不同的压缩机开/关机温度值.测试结果表明,本文所提的温度参数优化整定方法能有效地解决不能同时满足为了得到合格的饮料所需要的狭窄的温控范围和...     

数控铣齿机主轴系统温度场有限元分析

热误差是影响机床加工精度的主要因素之一。主轴的热变形是机床总的热变形的重要组成部分。因此本文在分析数控铣齿机主轴热源的基础上,计算发热量,确定边界条件,并利用有限元软件abaqus建立主轴系统的温度场模型并进行了数字模拟仿真,为主轴系统的进一步热变形控制提供了基础。     

双PLC主从站通讯在热整理机中的应用

双PLC主从站通讯方式应用于热整理机,使得原有的复杂系统得以分割并功能化为简单模块,实现了热整理机温度在控制上的灵活性与实时性。     

一个可证明安全的短环签密方案

签密能在一个逻辑步骤内实现签名和加密2项功能。环签名允许一个群体内某成员匿名地泄露秘密。结合签密和环签名提出环签密概念。环签密既有保密性,又具认证功能。基于双线性对构造一个高效的短环签密方案。该方案允许发送者以匿名方式发送消息,使消息具有保密性和认证性。在随机预言模型下,证明该方案具有保密性和不可伪造性。     

C程序内存泄漏智能化检测方法

内存泄漏在采用显式内存管理机制的C语言中是一种常见的代码缺陷,内存泄漏的检测方法目前主要是静态分析与动态检测.动态检测开销大,且高度依赖测试用例;静态分析目前被学术界和工业界广泛应用,但是存在大量误报,需要人工对检测结果进行确认.内存泄漏静态分析的误报通常是由于对指针、分支语句和全局变量分析的不准确性导致的.提出了一种内存泄漏的智能化检测方法,通过使用机器学习算法学习程序特征与内存泄漏之间的相关性,构建机器学习分类器,并应用机器学习分类器进一步提高内存泄漏静态分析的准确性.首先构建机器学习分类器,然后通过静态分析方法构建从内存分配点开始的Sparse Value Flow Graph（SVFG）,并从中提取内存泄漏相关特征,再使用规则和机器学习分类器进行内存泄漏的检测.实验结果显示,该方法在分析指针、分支语句和全局变量时是有效的,能够提高内存泄漏检测的准确性,降低内存泄漏检测结果的误报.最后,对未来研究的可行性以及面临的挑战进行了展望.     

高空气球加强带热合温度数值仿真

为了合理地设计高空气球加强带热合机的加热辊,达到提高气球承载力,对加强带的热合过程进行了数值仿真。对该热合过程进行了简化,建立了热合过程的传热模型,采用ANSYS是的命令流编制了瞬态热分析的参数化程序,建立了动态热流密度表并通过移动热源的加载,实现了热合过程的数值仿真。对热合面上的温度场进行分析,得到热源功率和热合速度之间的线性关系,拟合出热合最佳位置落后于热源中心距离L与热合速度V之间的数值关系。结果表明可用来指导加强带热合机的加热部件设计,得出加热功率和结构设计应遵循的原则,为设计提供了依据。     

Leak detection of pipeline: An integrated approach of rough set theory and artificial bee colony trained SVM

The generation of leak along the pipeline carrying crude oils and liquid fuels results enormous financial loss to the industry and also affects the public health. Hence, the leak detection and localization problem has always been a major concern for the companies. In spite of the various techniques developed, accuracy and time involved in the prediction is still a matter of concern. In this paper, a novel leak detection scheme based on rough set theory and support vector machine (SVM) is proposed to overcome the problem of false leak detection. In this approach, ‘rough set theory’ is explored to reduce the length of experimental data as well as generate rules. It is embedded to enhance the decision making process. Further, SVM classifier is employed to inspect the cases that could not be detected by applied rules. For the computational training of SVM, this paper uses swarm intelligence technique: artificial bee colony (ABC) algorithm, which imitates intelligent food searching behavior of honey bees. The results of proposed leak detection scheme with ABC are compared with those obtained by using particle swarm optimization (PSO) and one of its variants, so-called enhanced particle swarm optimization (EPSO). The experimental results advocate the use of propounded method for detecting leaks with maximum accuracy.     

The application of ANFIS prediction models for thermal error compensation on CNC machine tools

Thermal errors can have significant effects on CNC machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon the accuracy and robustness of the thermal error model and its input measurements. This paper first reviews different methods of designing thermal error models, before concentrating on employing an adaptive neuro fuzzy inference system (ANFIS) to design two thermal prediction models: ANFIS by dividing the data space into rectangular sub-spaces (ANFIS-Grid model) and ANFIS by using the fuzzy c-means clustering method (ANFIS-FCM model). Grey system theory is used to obtain the influence ranking of all possible temperature sensors on the thermal response of the machine structure. All the influence weightings of the thermal sensors are clustered into groups using the fuzzy c-means (FCM) clustering method, the groups then being further reduced by correlation analysis.A study of a small CNC milling machine is used to provide training data for the proposed models and then to provide independent testing data sets. The results of the study show that the ANFIS-FCM model is superior in terms of the accuracy of its predictive ability with the benefit of fewer rules. The residual value of the proposed model is smaller than ±4 μm. This combined methodology can provide improved accuracy and robustness of a thermal error compensation system.     

基于MSP413单片机的热量表检测系统的研制与开发

以MSP413单片机为核心,研制开发了一种热量表检测系统。该检测系统的硬件部分主要由CPU主控芯片、按键模块、驱动显示模块、温度参数检测模块、流量参数检测模块以及光电隔离模块构成。该检测系统用来检测热量表的流量、进水温度、出水温度、瞬时流量、累计流量温度、流量等参数是否准确。实例表明,该测试系统在检测热量表参数过程中具有操作简单、检测精度高、速度快等特点,并能实时显示检测结果。     

柔性印刷线路板LED贴片质量视觉检测方法

柔性印刷线路板中LED的粘贴需经过点银、贴片、封胶等工艺,其中贴片过程中会产生漏粘、异物、粘斜、偏移等一系列质量问题;提出了一套基于机器视觉的贴片质量在线检测方法:通过最小外接矩形获取有效区域的范围,利用基于轮廓特征的模板匹配对贴片所在连接盘进行定位;利用动态模板匹配检测漏粘缺陷;通过平均灰度值比较法检测LED上的异物缺陷;采用有效区域与LED区域的交集与差集对粘斜与偏移缺陷进行检测;该方案已应用于工业生产线,并且具有较高的检测准确率。     

Android应用程序中的内存泄漏与规避方法

Android应用程序的主体采用Java编程语言实现,Java语言的一个显著特点是它通过Java虚拟机和垃圾回收机制管理大部分的内存事务,但是在Java程序中不可避免地存在着内存泄漏的问题。本文从造成Android应用程序内存泄漏的原因入手,对内存泄漏进行检测和定位。阐述了在编写应用程序时规避内存泄漏的方法,并分别介绍了一种内存监测工具和一种内存分析工具的使用方法。     

Steels classification by machine learning and Calphad methods

Steels of different classes (austenitic, martensitic, pearlitic, etc.) have different applications and characteristic areas of properties. In the present work two methods are used to predict steel class, based on the composition and heat treatment parameters: the physically-based Calphad method and data-driven machine learning method. They are applied to the same dataset, collected from open sources (mostly steels for high-temperature applications). Classification accuracy of 93.6% is achieved by machine learning model, trained on the concentration of three elements (C, Cr, Ni) and heat treatment parameters (heating temperatures). Calphad method gives 76% accuracy, based on the temperature and cooling rate. The reasons for misclassification by both methods are discussed, and it is shown that the part of them caused by ambiguity/inaccuracy in the data or limitations of the models used. For the rest of cases reasonable classification accuracy is demonstrated. We suggest that the reason of the supremacy of machine learning classifier is the small variation in the data used, which indeed does not change the steel class: the properties of steel should be insensitive to the details of the manufacturing process.     

基于动态压力变送器的输油管道泄漏检测与定位系统

设计了一套基于动态压力变送器的输油管道泄漏检测与定位系统,阐述了其系统组成和检测原理.通过动态压力变送器获取管道的动态压力信号,采用基于经验模态分解的方法提取信号的特征向量,再利用支持向量机实现对管道泄漏的识别.最后采用相关时延估计算法获得管道泄漏点的位置.通过现场应用实例表明,动态压力变送器具有更高的检测灵敏度和泄漏分辨力.该系统能够对管道泄漏进行正确识别,可以有效地降低误报警率,并提高了泄漏检测的灵敏度和定位精度.     

Using a cool spot to improve the thermal comfort of glassmakers

Glassmakers monitoring a rolled plate process suffered discomfort from the high temperature environment. This was caused by the radiant heat emitted by the furnaces and associated equipment surrounding the glassmakers' working area, combined with a high air temperature. The glassmakers are responsible for monitoring the glass rolling machine to ensure that the product is manufactured to specification, and to prevent the molten glass sticking to the rollers. This study improved their thermal comfort by the construction of a cool area. They were also brought nearer to the rolling machine. This, with the addition of a cooler environment, improved their monitoring performance. The cool spot was constructed using glass and aluminium radiant heat shields, air curtains and low velocity cooling air.     

Quantum correlations responsible for remote state creation: strong and weak control parameters

We study the quantum correlations between the two remote qubits (sender and receiver) connected by the transmission line (homogeneous spin-1/2 chain) depending on the parameters of the sender’s and receiver’s initial states (control parameters). We consider two different measures of quantum correlations: the entanglement (a traditional measure) and the informational correlation (based on the parameter exchange between the sender and receiver). We find the domain in the control parameter space yielding (i) zero entanglement between the sender and receiver during the whole evolution period and (ii) non-vanishing informational correlation between the sender and receiver, thus showing that the informational correlation is responsible for the remote state creation. Among the control parameters, there are the strong parameters (which strongly effect the values of studied measures) and the weak ones (whose effect is negligible), therewith the eigenvalues of the initial state are given a privileged role. We also show that the problem of small entanglement (concurrence) in quantum information processing is similar (in certain sense) to the problem of small determinants in linear algebra. A particular model of 40-node spin-1/2 communication line is presented.