刀具切削状态的电机电流监测新方法

本文从实时在线监测刀具切削状态的应用出发,研制了一种新型的电机电流拾取方法和传感装置,并分析了刀具在加工过程中切削力,电机电流与刀具切削状态的关系,同时,研究了利用电机电流信号进行刀具切削状态的监测原理,实验证明了其方法的可靠性和实用性。     

关于利用切削功率监控刀具状态的评述

对近年国内外专家关于刀具状态功率监控的各种算法和研究进行了归纳后指出：利用切削功率对刀具实现在线监测是一种方便、实用和有效的监控方法。     

刀具磨损的在线监测──切削功率监测法

针对切削机床的切削刀具磨损，提出一种实时监控方法──切削功率监测法。本法简单易行，无需改动机床结构，是一种较有潜力的监控方法。对该法的理论基础进行论述，建立数学模型，并给出实验验证结果。     

刀具失效状态监测研究综述

在机械加工中,机床刀具的失效状态分为两种:刀具磨损失效和刀具破损失效。刀具失效对加工精度、加工质量和加工效率有十分消极的影响。随着数控机床自动化程度的不断调高,特别是在高速切削加工中,对刀具磨损状态监测提出了更高的要求。刀具的破损存在典型的随机现象,目前学者多在算法上优化刀具破损预测模型,提高刀具破损的预测精度。国内外学者总结刀具失效的一般规律,研发出了多种刀具状态检测手段和方法。根据国内外刀具状态检测相关研究进展,对刀具失效检测相关问题进行评述,并对以后刀具失效检测的研究方向进行了展望。     

刀具极限磨损破损在线实时监测

提出了一种监测刀具极限磨损和破损的新方法－多参量综合监测法。设计了监测线路，对电网电压进行了监测，自动减去首切电流，用声发射ＡＥ，电机电流对刀具极限磨损和破损进行综合判别，拓宽了监测范围。提出了抗干扰能力，系统具有高的判别成功率。钻削加工总体判别成功率达９６。２％，车削加工判别成功率为９６．７％。     

刀具状态的声振多级在线监测模式研究

基于车削过程中刀具磨损声、振信号的时域统计参数分析、相关分析，ＡＲ分析及频谱、倒谱等分析，构建出以主轴转速为第一级判断，信号平均幅值为第二级判断，信号平均幅值与频谱、相关和ＡＲ等特征参数有机组合为第三级判断的多级模式。既具有单一判据模式的快速性，又具有联合判据模式的准确性。     

基于小波神经网络的切削刀具状态监测

提出了一种基于小波神经网络的切削刀具状态监测方法，即提取反映刀具磨损状态的特征参数，利用小波神经网络的非线性模型，实现在线状态监测；同时针对多输入输出问题带来的网络规模大、收敛速度慢等问题，提出了一种网络优化算法，即采用改进的遗传算法寻找最优小波基元，从而简化小波网络并加快收敛。仿真实例证明该方法是有效的。     

加工过程刀具破损的声发射传感监测新技术

主要介绍一种适合加工过程刀具破损的声发射传感监测新技术,论述了新型传感器的结构、工作原理及信号处理方法。同时还介绍了适合自动化加工过程的新型刀具破损实时监控系统及其应用效果。     

加工过程刀具破损监测的声发射传感新技术

主要介绍一种适合加工过程刀具破损监测的声发射传感新技术,论述了新型传感器的结构、工作原理及信号处理方法。同时还介绍了适合自动化加工过程的新型刀具破损实时监控系统及其应用效果。     

AN 'EFFECTIVE CUTTING TOOL THERMAL CONDUCTIVITY' BASED MODEL FOR TOOL-CHIP CONTACT IN MACHINING WITH MULTI-LAYER COATED CUTTING TOOLS

This paper presents a new modeling approach, based on Oxley's predictive model, for predicting the tool-chip contact in 2-D machining of plain carbon steels with advanced, multi-layer coated cutting tools. Oxley's original predictive model is capable of predicting machining parameters for a wide variety of plain carbon steels, however, the tool material properties and their effects are neglected in the analysis. In the present work, the effect of the tool material, more particularly, the effect of multiple coating layers and the individual coating thicknesses on the tool-chip contact length in orthogonal machining is incorporated. The results from the model predict the tool-chip contact length with respect to major cutting parameters such as feed and rake angle, work material parameters such as the carbon content in the steel, and varying thicknesses and combinations of coating layers. This model enables more precise cutting tool selection by predicting the relative tribological impact (in terms of tool-chip contact length) for a variety of multi-layer coated tools.     

智能化系统的知识表达与推理机制

针对智能化系统知识研究中的知识表达、学习,提出基于神经网络、模糊逻辑、专家规则结合的图形化拓扑网络结构知识表达及相应的学习方法,能灵活地表达对象知识,方便、直观地形成知识库,有利于智能化系统的知识学习;根据智能化推理中常用的专家系统、模糊逻辑、神经网络等推理的互补性,结合图形化拓扑网络结构知识表达的通用知识库,提出融合型推理模型,能形成较强的推理功能,有效地应用和处理智能化系统知识。实际应用于设备状态监测诊断取得了令人满意的效果。     

GMAW焊接过程监测Kohonen神经网络系统

实时测量熔化极气体保护焊（ＧＭＡＷ）焊接过程中的电参数，研制自组织特征映射神经网络（Ｋｏｈｏｎｅｎ神经网络），直接依据不同焊接工艺条件下焊接电压的概率密度分布曲线（ＰＤＤ）以及短路过渡时间的频数分布曲线（ＣＦＤ），自动识别出焊接过程中的各种干扰信号。     

A REAL-TIME WEB-ENABLED PLATFORM FOR INFORMATION MONITORING AND FAULT DIAGNOSIS IN A DISTRIBUTED CONTROL SYSTEM

A novel online diagnosis system framework for distributed control system with expert decision support is presented. The online monitoring and maintenance system is a vital tool for the operator and plant engineer to know the status of the distributed control system (DCS). DCS linked by data network as a single system is used in complex process applications where large amounts of input/output and data are required, such as oil refineries or chemical plants. This novel web-based expert service support maintenance has the system of integrated hardware and software which reduces the distributed control system's service maintenance. Real-time on-line diagnosis helps the plant engineer to maximize the plant operation. The key design challenges of internet security and user interface are the focus of this article.     

水下机器人传感器及推进器状态监测系统

为了保障水下机器人作业安全,提高其智能程度,提出了基于RBF(径向基函数)网络和FNN(模糊神经网络)的水下机器人传感器及推进器状态监测系统。根据对预处理后的传感器信号进行分析,传感器监测模型检测传感器的故障,并对出现故障的传感器信号进行恢复,将其作为水下机器人的实际运行状态参数提供给推进器监测模型;推进器监测模型输出与传感器实际输出共同作用,通过评价模型即得到了相关推进器的状态信息,并实现了故障定位。某型水下机器人的真实试验数据的计算机仿真结果验证了提出的监测系统的有效性和可靠性。     

增广传递矩阵算法在机床主轴系统静动态特性分析中的应用

以ＣＹ６１４０型普通车床主轴系统为研究对象，在集中参数模型的基础上，采用增广传递矩阵法，编制了机床主轴部件静动态特性计算的计算机程序，并应用该程序对机床主轴系统进行了静动态特性的分析计算。     

基于多体系统运动学理论的并联机床运动空间分析及仿真研究

结合 3自由度并联机床 ,运用多体系统运动学理论 ,通过程式化的建模方法 ,建立起并联机床工作空间、结构参数及运动控制参数间的关系模型 ,并给出其计算机仿真结果。     

DESIGN AND IMPLEMENTATION OF A WEARABLE,MULTIPARAMETER PHYSIOLOGICAL MONITORING SYSTEM FOR THE STUDY OF HUMAN HEAT STRESS,COLD STRESS,AND THERMAL COMFORT

This article describes the design and implementation of a wearable, multiparameter physiological monitoring system called the Sensing Belt system, which consists of multiple sensors integrated into fabric that communicates with a physiological data acquisition unit (PDAU) that in turn transmits these data to a remote monitoring center (RMC) for analysis. A number of vital signs can be acquired by the system, including electrocardiography (ECG), respiratory inductance plethysmograph (RIP), posture/activity, multipoint skin temperature (T_SK), and rectal temperature (T_RC). The physiological data can be stored on a MicroSD card or transmitted to the RMC, where specialized analysis will be provided to extract parameters such as heart rate (HR), respiratory rate (RR), respiratory sinus arrhythmia (RSA), and human energy expenditure. The RMC can receive physiological data from up to 16 Sensing Belt users simultaneously. A medical validation test was carried out to compare the accuracy of the physiological data obtained from the Sensing Belt system with data obtained concurrently from traditional, calibrated laboratory physiological monitoring instruments. The results showed that most of the variables measured by the Sensing Belt are within acceptable error limits. The mean temperature on two trials (walking and running) showed significantly higher mean differences than on other trials, but the correlation coefficient (r) remained high (0.985 and 0.989, respectively). This study demonstrates the accuracy of the Sensing Belt system for the monitoring of these physiological parameters and suggests that it could be used to provide a complete human physiological monitoring platform for the study of human heat stress, cold stress, and thermal comfort.