热处理井式回火炉温度波动的分析

回火是金属零件制造加工工艺中非常重要的一道热处理工序，温度控制要求很严格，回火炉的温度波动又是影响热处理质量和重要一环。本对热处理井式回火炉温度波动的原因作了分析，提出了有效的改善措施。     

数据采集系统在热处理设备测温中的研究

通过对热处理设备测温的总结,结合实际工作经验,开发了该数据采集系统.用来满足各种不同热处理设备的炉温均匀性测试.     

热电偶自动检定和热处理炉温现场测试装置建立的方案

本文阐述了由计算机控制实现的热电偶自动检定和热处理炉温现场测试装置的原理,以及测量装置的硬件设计与编程原理,并对测量装置的不确定度进行了分析.     

从温度均匀性测试看HB5425-89的改进方向

介绍了热处理炉温度均匀性检测的要求与方法,总结了实际工作中的经验,从设备分类、传感器要求、测试方法、管理等方面,指出了HB5425-89的不足与改进方向.     

基于模糊支持度的分布式多传感器加权融合算法

针对目前分布式多传感器数据融合算法中鲁棒性和实时性问题,基于充分利用多传感器测量数据中互补和冗余信息的思想,通过局部状态估计精度间支持度函数的建立和支持度矩阵的求解,合理地分配各局部航迹估计在融合中心的权重,进而提出了一种基于模糊支持度的分布式多传感器加权融合算法.最后,通过蒙特卡罗仿真验证了该算法的有效性.     

热处理炉温测量准确性影响因素分析和改进方案

<正>一、热处理炉温测量过程中误差来源分析1.交流谐波及噪声对热处理炉温测量过程的影响在热处理车间,特别是使用高频炉的车间,对热处理炉温的测量具有较大影响。原因是交流谐波及噪声的存在,通常会对电网及现场空间中其他系统造成较为严重的干扰,且干扰具有不确定性。如图1所示,由于在高温环境下,热处理炉体内部绝缘材料及测试支架绝缘强度大幅度降低,并且尽管常见的电测仪器     

热处理炉温控系统测温控制方法探讨

温控系统的测温控制方法精度直接影响热处理产品成品率,如何对热处理炉温控系统的测温精度进行有效的控制,在生产过程中起着关键作用。本文主要介绍了以现场测温来控制热处理炉温控系统的精度,并且阐述了现场测温的同时可能产生的误差分析及处理。     

井式炉温度测量与修正方法

通过对多区控温井式炉温度测量和对温度，垂直温场的修理，水平温场的工艺温度修正等方法，可提高工件热处理一次性合格率达９８％。     

炉温测试仪校准方法的探讨

炉温测试仪主要用于测量波峰焊、回流焊等设备的测温曲线,以便更好的改进制程和工艺。文章简述了炉温测试仪装置的结构和使用,对炉温测试仪的校准方法进行探讨,并通过试验数据和不确定度评定验证方法的可行性以及指出了注意事项。     

模糊PID控制策略在真空热处理炉中的应用

本文阐述了真空热处理炉的温度控制策略,针对热处理炉炉温的控制常采用单一控制策略存在控温精度低、跟随性能差、系统超调高等缺点,提出了基于真空热处理炉温度控制器运行状态的分段式复合控制策略,并针对大误差运行模式下采用包含自适应装置的模糊PID控制策略进行较为详细的解析,通过MATLAB/SIMULINK仿真,验证了模糊PID控制策略在真空热处理炉温度控制方面的有效性及优越性。     

改进的Hough变换在多传感器数据融合中的应用

提出了用一种改进的Ｈｏｕｇｈ变换来解决多传感器数据融合的问题，与多传感器数据融合中常用的统计或几何方法相比，该方法具有计算速度快、存储要求小和容易实施等优点，简要分析了该方法和数据融合的几何方法之间内在的联系。     

A wavelet-based multisensor data fusion algorithm

This paper presents a wavelet transform-based data fusion algorithm for multisensor systems. With this algorithm, the optimum estimate of a measurand can be obtained in terms of minimum mean square error (MMSE). The variance of the optimum estimate is not only smaller than that of each observation sequence but also smaller than the arithmetic average estimate. To implement this algorithm, the variance of each observation sequence is estimated using the wavelet transform, and the optimum weighting factor to each observation is obtained accordingly. Since the variance of each observation sequence is estimated only from its most recent data of a predetermined length, the algorithm is self-adaptive. This algorithm is applicable to both static and dynamic systems including time-invariant and time-varying processes. The effectiveness of the algorithm is demonstrated using a piecewise-smooth signal and an actual time-varying flow signal.     

Optimal fusion of multiple nonlinear sensor data

A framework for the detection of bandlimited signals by optimally fusing the multinonlinear sensor data is developed. Though most sensors used are assumed to be linear, none of them individually or in series gives the truly linear relationship, and errors are inevitable as a result of the assumption of linearity. A new approach, which takes the actual nonlinear characteristics of sensors into account, is advocated. Though the fusion of redundant information can reduce the overall uncertainty and, thus, serves to increase the accuracy of the process measurements, identifying the faulty readings and fusing only the reliable data are very difficult and challenging. An optimal multiple nonlinear sensor data fusion scheme in which multisensor data fusion is done by scheduling the sensor measurements is proposed. The main idea of the multisensor fusion schemes proposed in this paper is to pick only the reliable data for the fusion and disregard the rest. The proposed theoretical framework is supported by illustrative examples and simulation data.     

多传感器机器人的集成开发系统

设计了一个用于多传感器机器人控制的集成开发系统，该系统带有一个智能接口，可以集中采集多个传感器的数据，并进行一部分低层的数据融合处理，系统软件为多传感器的研究提供了必要的仿真工具及其他辅助控制算法，系统通用性好，为基于多感器的智能机器人的研究提供了一个很好的工具。     

Toward a miniature wireless integrated multisensor microsystem for industrial and biomedical applications

This paper presents our work toward the integration of a multisensor microsystem with wireless communication, using system-on-chip (SoC) methodology. Four different forms of microelectronic sensors have been fabricated on two separate 5/spl times/5 mm/sup 2/ silicon chips measuring pH, conductivity, dissolved oxygen concentration, and temperature. The sensors are integrated with a sensor fusion chip comprising analog circuitry for sensor operation and signal amplification prior to digital decoding and transmission. The microsystem prototype will be packaged in a miniature capsule, which measures 16 mm /spl times/55 mm including batteries and dissipates 6.3 mW for a minimal life cycle of 12 h.     

变风量空调房间温度传感器最佳位置预测

空调房间的温控器通常安装在门口附近墙壁上,其测量值并不能完全代表室内温度,以此值为反馈进行房间温度控制常常无法满足房间控制要求。本文通过在空调房间不同垂直、水平位置布设温度和风速测点,获得的测量值计算其有效吹风温度。采用修正误差学习的加权融合算法得到房间融合有效吹风温度,综合研究融合有效吹风温度控制作用下,送风量对室内有效吹风温度、热舒适性及空调系统能耗的影响。结果表明:设计风量为70%时,室内高度为1. 5 m处测点的有效吹风温度为-1. 7～1. 1℃,空气分布特性指标为100%,此点为最佳传感器安装位置。     

Adaptive, integrated sensor processing to compensate for drift and uncertainty: a stochastic 'neural' approach

An adaptive stochastic classifier based on a simple, novel neural architecture--the Continuous Restricted Boltzmann Machine (CRBM) is demonstrated. Together with sensors and signal conditioning circuits, the classifier is capable of measuring and classifying (with high accuracy) the H+ ion concentration, in the presence of both random noise and sensor drift. Training on-line, the stochastic classifier is able to overcome significant drift of real incomplete sensor data dynamically. As analogue hardware, this signal-level sensor fusion scheme is therefore suitable for real-time analysis in a miniaturised multisensor microsystem such as a Lab-in-a-Pill (LIAP).     

多源遥感数据融合的现状

本文总结了当前遥感中多源数据融合的各种方法。首先提出了一些多传感器数据融合的一般问题,在此基础上有重点地对多源遥感数据融合的方法进行了描述,分析和对比,介绍了一些最新的方法,同时也论述存在的主要问题和今后的发展方向。     

Multisensor fusion and integration: approaches, applications, andfuture research directions

Multisensor fusion and integration is a rapidly evolving research area and requires interdisciplinary knowledge in control theory, signal processing, artificial intelligence, probability and statistics, etc. The advantages gained through the use of redundant, complementary, or more timely information in a system can provide more reliable and accurate information. This paper provides an overview of current sensor technologies and describes the paradigm of multisensor fusion and integration as well as fusion techniques at different fusion levels. Applications of multisensor fusion in robotics, biomedical system, equipment monitoring, remote sensing, and transportation system are also discussed. Finally, future research directions of multisensor fusion technology including microsensors, smart sensors, and adaptive fusion techniques are presented     

信息融合技术及其在包装工业中的应用

论述了多传感器信息融合技术(MIF)的结构,从工业应用的角度出发探讨和提出了一种多传感器信息融合的结构模型.将经典的统计理论和估计理论以及现代的信息理论和人工智能理论应用于信息融合,通过学科交叉和边沿化,形成了多传感器信息融合的算法和理论.提出了一种用于包装工业的多传感器信息融合控制系统模型,为多传感器信息融合在包装工业控制中的应用迈出了一步.