大型数控磨床磨削颤振在线监测理论与试验方法研究

Chatter is a sef-excited vibration that occurs during machining operations and becomes a common limitation to productivity and part quality.Chatter occurrence also has several negative effects, such as excessive noise, machine tool damage, disproportionate tool wear, damage of the tooling structure and the spindle bearing.For these reasons, chatter avoidance is a topic of enormous interest for many researchers who have focused on the solution to the problem of chatter. Based on researching the vibration of the grinding processing,according to the feature of the vibration signals in the grinding processing, the appropriate sensors and signal acquisition system are chose to build the platform for grinder chatter test. By changing the grinding parameters, the signals of different mode are collected to supply the data for subsequent research. The new method-BEMD is introduced to analysis the non-stationary vibration signals and extracted the grinding chatter feature for KD4020X16 CNC grinding machine. Least square support vector machine (LSSVM) is seen as recognition classifier to indentify the relationship between chatter feature and grinding states, which develops a chatter online detection methods and provids theoretical basis for the development of engineering applications.Vibration signals collected by grinding test is used to verify the grinding chatter identification method based on HHT and LSSVM can be used as the basis for judgment and identification grinder chatter occurs. This project will solve three key problems:(1)CNC grinding machine chatter model considering multi-nonlinear factor.(2)Endpoint effect solve method of two-dimensional signal processing-BEMD.(3)Chatter feature extraction method.

磨削颤振是磨床主机故障的主要表现形式，若这种振动故障不能及时排除，将进而导致传动噪声和运行阻力变大、工作效率下降、刀具损耗加剧等问题，严重时还可能损害磨头和机床主轴，使加工无法进行下去。 本项目拟以KD4020X16型数控动梁龙门导轨磨床为对象，以机械动力学、二维经验模态分解和最小二乘支持向量机为理论基础，从振动信号的测量、磨削过程动态分析、颤振机理研究、颤振特征量提取技术及磨削颤振检测与颤振控制几个方面，开展基于二维经验模态分解和最小二乘支持向量机的龙门式平面/导轨磨床磨削颤振在线监测与抑制技术研究，对于深刻揭示磨削颤振过渡过程的本质特征、保证产品加工精度、提高生产率将会有着重要的学术价值和工程应用前景。 本项目拟解决的关键科学问题：（1）考虑多种非线性因素的数控磨床颤振模型的建立；（2）BEMD信号处理方法的端点效应问题；（3）能反映颤振征兆的颤振特征量的提取。

根据项目研究计划，项目组在项目执行期内针对数控磨床磨削颤状态监测、检测与预测方法进行了深入的研究。迄今，项目研究进展顺利，各项研究任务均已圆满成功，并达到了预期的研究目标。现将项目研究成果总结如下：.（1）从振动信号的采集、磨床动静态特性分析、颤振机理研究、颤振特征量提取、分类识别等多个方面，成功开发了大型数控导轨磨床磨削颤振在线检测与颤振预测技术；.（2）针对大型数控导轨磨床磨削信号的非平稳、非线性特性，开发了能快速准确分析非平稳、非线性信号特征的信号分析及颤振特征量提取方法，提取出了对颤振敏感的特征量。.（3）以智能理论与技术、多传感器信息融合理论为主，构建了数控磨床磨削颤振辨识模型，并在此基础之上成功开发了适用于数控磨床的颤振检测技术，并开发了相应的计算机软件包和工具。该技术被列为可推广项目1。.（4）针对磨床信号非线性、多维性和非平稳性的特点，根据揭示磨削颤振过渡过程的本质特征，在使用BEMD处理试验信号的基础上，开发了基于控制图与ARIMA模型结合的磨削颤振预测方法。该技术被列为可推广项目2。. 在项目的整个执行期内，项目组各研究人员精诚团结，勤奋工作，通过理论研究、数学模型仿真和现场测试等多种手段，积累了大量可供研究使用的数控磨床磨削状态监测数据库。作为研究成果的具体体现，项目组在国际国内学术期刊上公开发表学术论文10篇，国际会议论文2篇，申请发明专利4项，软件著作权1项。其中SCI、EI收录7篇。按照项目研究计划，开发大型数控磨床磨削颤振检测与预测软件包1套，开发可推广项目2项。