基于Sugeno模糊模型的CNC机床故障诊断方法

通过将Sugeno模糊模型用于数控机床故障诊断系统的方式,实现了对各个诊断专家诊断结果的模糊综合,消除了诊断专家诊断结论的随意性,保证诊断结论的准确.利用此方法基于诊断专家系统技术可以实现对数控机床的自动诊断,诊断结果准确可靠.     

基于遗传算法的孔系加工路线优化

在数控机床上对大量的孔进行加工时,加工路线的优化程度将直接影响机床的使用效率.通过对在数控机床上对孔系进行加工的典型工艺路线的分析,建立了加工路线优化的数学模型,利用遗传算法,对孔系加工路线的排序进行了优化计算,并用一个算例证明了该算法的可行性.     

数控机床加工技术专业教学改革的探索与实践

介绍了数控机床加工技术专业进行高职教学改革的背景、指导思想和目标,总结了数控机床加工技术专业教学改革的实践经验,研究了数控机床加工技术专业教学改革的途径和方向.     

基于多线程技术的网络化数控加工系统

利用VC++多线程技术研制出基于网络的数控机床远程控制系统,可使计算机与数控机床进行远程数控代码接收与发送,为数控机床群的网络化控制与管理奠定了必要技术基础.本系统得到成功应用并取得良好的效果.     

机床设备选择的评价体系研究

对评价机床性能的指标进行了分析归类,建立了机床选择评价的指标体系,并应用层次分析法对数控机床的性能进行了评价。结合对各种数控机床的单个指标的评价得分,得到数控机床的综合得分,从而辅助车间做出科学合理的设备选择决策。     

基于签密的数控机床远程操控安全交互协议

针对目前数控机床远程操控信息传输所存在的安全交互问题,设计了一种基于签密的数控机床远程操控安全交互协议。通过在客户端与数控机床间嵌入签密算法,实现对信息来源的可验证,防止信息泄露,确保信息的安全传输。实验仿真证实,协议具有较高的可行性。     

基于FOCAS协议和指令域的数控机床在线监控系统

针对配备FANUC数控系统的机床加工过程产生的表征机床能耗的动态数据难以获取的问题,基于FOCAS协议利用C#设计了一套指令域数控机床加工过程动态能耗数据监控系统。通过调用FOCAS相关函数实现了对数控机床主轴和伺服轴的负载、进给率、转速、运行程序段等信息的监控。将加工过程动态能耗数据和运行NC程序同步保存到SQL Sever数据库,建立了机床能耗与工作任务的映射关系,实验表明系统满足监控要求。     

基于元结构基本框架概念的床身结构动态设计

提出数控机床大件结构设计元结构和基本框架的概念,把由床身筋板围成的栅格称为筋格,床身的宏观构形为基本框架:筋格的动态特性直接影响机床床身的动态特性.用有限元分析法对床身筋格结构动态特性进行研究,总结出对数控机床床身设计具有普遍指导意义的规律,可用于数控机床床身结构初步设计.     

数控机床热误差的改进型灰色DGM(2,1)模型建模

针对机床热误差补偿的建模问题,提出了基于灰色DGM(2,1)模型对数控机床热误差进行分析、预测的方法.该模型在通过对原始数据序列进行累加、累减处理以减小其随机性,建立微分方程的方式建立动态模型以揭示数据序列的长期发展趋势的基础上,利用函数变换法改善数据序列的光滑性.通过对1台数控机床的实际切削加工实验数据进行建模分析,对该方法进行了验证.结果表明该方法克服了传统灰色GM(1,1)模型的不足,获得了更高的建模和预测精度,且具有计算简单,便于在线补偿应用等优点.     

基于多线程技术的网络化数控加工系统

利用VC 多线程技术研制出基于网络的数控机床远程控制系统，可使计算机与数控机床进行远程数控代码接收与发送，为数控机床群的网络化控制与管理奠定了必要技术基础．本系统得到成功应用并取得良好的效果．     

数控铣床自动加工循环自行中断故障的处理

数控机床出现外部故障,有时诊断过程比较困难、复杂,一旦发现问题所在,解决起来比较轻松。对数控机床外部故障的诊断,首先应熟练掌握机床的工作原理和动作顺序,出现故障时,要搞清故障现象。其次要熟练运用厂方提供的PLC梯形图,充分利用NC系统的状态显示功能,来观察PLC一些状态信息,在故障比较复杂时,最好采用机外编程器,在线监测PLC梯形图运行的状态。而FANUC-0系统可直接通过NC系统DGNOSPARAM功能直接在线观测梯形图的变化。     

Fault diagnosis for wind turbine based on improved extreme learning machine

A fault diagnosis method based on improved extreme learning machine (IELM) is proposed to solve the weakness (weak generalization ability, low diagnostic rate) of traditional fault diagnosis with feedforward neural network algorithm. This method fuses signal feature vectors, extracts six parameters as the principal component analysis (PCA) variables, and calculates correlation coefficient matrix among the variables. The weight values of control parameters in the extreme learning model are dynamically adjusted according to the test samples’ constantly changing. Consequently, the weight fixed drawback in the original model can be remedied. A fault simulation experiment platform for wind turbine drive system is built, eight kinds of fault modes are diagnosed by the improved extreme learning model, and the result is compared with that of other machine learning methods. The experiment indicates that the method can enhance the accuracy and generalization ability of diagnosis, and increase the computing speed. It is convenient for engineering application.     

Reliability analysis of electrical system of computer numerical control machine tool based on bayesian networks

The core of computer numerical control (CNC) machine tool is the electrical system which controls and coordinates every part of CNC machine tool to complete processing tasks, so it is of great significance to strengthen the reliability of the electrical system. However, the electrical system is very complex due to many uncertain factors and dynamic stochastic characteristics when failure occurs. Therefore, the traditional fault tree analysis (FTA) method is not applicable. Bayesian network (BN) not only has a unique advantage to analyze nodes with multiply states in reliability analysis for complex systems, but also can solve the state explosion problem properly caused by Markov model when dealing with dynamic fault tree (DFT). In addition, the forward causal reasoning of BN can get the conditional probability distribution of the system under considering the uncertainty; the backward diagnosis reasoning of BN can recognize the weak links in system, so it is valuable for improving the system reliability.     

一种改进时域同步平均的滚动轴承故障诊断方法研究

复杂结构设备的滚动轴承其振动信号成分复杂,故障信号微弱,信噪比很小,常规诊断方法难以有效消除背景噪声,有效提取故障信息.文中研究了基于相位补偿时域同步平均的滚动轴承故障诊断方法,并根据轴承故障信号存在调制的特点,探讨了同步周期的合理选取.通过对轴承内圈故障的仿真研究,验证了相位补偿时域同步平均方法的有效性,它能够同时提取故障特征频率与调制频率,为精确诊断轴承故障提供了新的途径.经进一步实验研究,证明该方法是有效的.     

齿轮箱故障诊断技术及其发展

综述了机器故障诊技术的重要组成部分－齿轮箱的故障诊断技术及其发展状况，从齿轮和轴承两个方面介绍了各种故障的诊断方法以及作的研究成果。     

Fault Diagnosis and Reliability Analysis Using Fuzzy Logic Method

A new fuzzy logic fault diagnosis method is proposed. In this method, fuzzy equations are employed to estimate the component state of a system based on the measured system performance and the relationship between component state and system performance which is called as “performance-parameter” knowledge base and constructed by expert. Compared with the traditional fault diagnosis method, this fuzzy logic method can use human＇s intuitive knowledge and dose not need a precise mapping between system performance and component state. Simulation proves its effectiveness in fault diagnosis. Then, the reliability analysis is performed based on the fuzzy logic method.     

液压冷拔机液压系统故障相关问题的探讨

阐述了精密液压冷拔机液压系统中液压油泵、液压控制阀和液压缸的主要常见故障类型,及其故障产生的原因,并针对故障的具体原因,提出了具体的维修方法,以期提高维修人员的液压系统故障诊断能力,减少故障维修时间,降低设备故障停机率。