基于切削噪声测试的数控加工颤振识别系统

通过对机床切削过程中产生的噪声进行测量和分析,采用时域与频域相结合的方法判断机床是否产生切削颤振.采用虚拟仪器的思想,开发了"基于切削噪声测试的数控加工颤振识别系统".系统硬件部分采用普通麦克风与计算机声卡进行切削噪声信号的采集;软件部分分为:信号采集,信号分析以及噪声回放三个模块.实验证明,该系统测试方法简单,判断结果准确.     

一种新的切削刚度系数识别方法

在研究机床切削系统稳定性极限预测的过程中，切削刚度系数ke的准确识别是其中最为关键的一项工作。文中在对刀架施加振动激励，变稳态切削为动态切削的基础上．以动态切削力为研究对象，推导切削刚度系数ke的数学模型，并在切削试验中通过对动态切削力信号及其与振动位移信号相位差的测量，准确有效地识别切削刚度系数ke。试验结果表明，文中的切削刚度的识别方法可以为机床切削系统稳定性预测理论分析和试验研究提供更为准确的动力学参数。     

K-means阈值算法下数控车床功率监控系统的研究

为获取机床工作状态信息和及时发现切削异常现象,通过监控机床主轴电动机功率监测机床。以数控车床为研究对象,利用K-means聚类算法实现不同加工状态下的监控阈值设定,借助Lab View平台采集、分析处理功率信息,建立机床加工过程中切削功率信息的实时监测系统,实现机床加工的预警和工艺参数的合理安排。试验表明该监控系统能有效监控机床切削状态,在一定条件下具有较高识别率。     

基于虚拟仪器的数控机床动态特性测试与分析系统研究

采用虚拟仪器技术开发了用于“机床—刀具—工件”切削加工工艺系统的动力学特性测试与分析系统,该系统以LabView为软件开发平台,实现了切削过程时域信号采集、传函分析、模态分析等功能模块,可通过锤击实验获得切削加工工艺系统的频响特性及固有频率、阻尼比、刚度等参数,为切削过程动力学仿真提供动态特性参数。实验证明利用该系统可以方便地进行现场测试与分析,与传统测试仪器相比,大大提高了测试效率和精度,并降低了测试成本。     

基于人工神经网络的变切削条件下钻头磨损监控

基于人工神经网络变切削条件下的钻头磨损监控系统，以机床主轴和进给轴的电机功率（电流）信号的为监控信号，并通过机床的速度向量识别机床的加工状态；通用对监控信号的提取和预处理，得到人工神经网络模型的输入（有效切削功率和切削用量）用３层ＢＰ网络对钻头的磨损量进行预报。     

基于LabVIEW的刀具磨损在线监控系统

自动监测刀具磨损、分析刀具磨损状况是FMS和CIMS中迫切需要解决的词题。文章在LabVIEW技术的基础上，实现了机床主轴电动机电流信号的采集、存储和分析；在线监控电流的变化情况，反映出了刀具的磨损状况，提出了主轴电流与切削参数之间的数学模型。并用试验验证了该系统的有效性和实用性。     

基于LabVIEW的机床声音信号采集与处理系统

机床声音信号包含着丰富的机床运行状态信息,可作为机床运行状态的判断依据。传统的机床声音信号采集设备成本高,功能单一。为提高机床声音信号采集系统的通用性、丰富声音信号采集系统的功能,并降低设备的成本,以机床、传声器、计算机等为硬件平台,基于Lab VIEW2012软件开发了机床声音信号采集与处理系统。通过实验证明该系统可以对机床的声音信号进行采集,并可进行初步的数据处理,证明了系统的可靠性,为机床设备故障诊断及预测系统的研究打下了坚实的基础。     

JD-3P 机床功率变送器的试验研究

为了适应切削过程的多种功率监控要求，监控系统必须获得切削过程的动态功率信号，常规测试仪表只能测量在一段时间内的平均功率，无法输出功率信号的瞬时值。因此必须设计一种能正确测量切削过程动态信号并能提供输出接口的功率变送器。本文介绍了结合上海市重点攻关项目ＦＭＳ中的刀具状态监控系统所研制的机床功率变送器及其试验结果。     

基于STM32单片机的机床数据采集系统设计

车间信息化管理系统往往只需获取机床在某时刻的状态数据，无需分析该状态信号在短时间内的频率信息，而机床故障诊断及健康监测系统则不然，二者的差异要求机床数据采集系统应同时具备低频采集和高频采集的能力。针对上述问题，通过两个独立的低频采集控制模块和高频采集控制模块设计了具备低、高采样频率的分布式机床数据采集系统。该系统将每台机床作为一个分布式数据采集节点，节点中的采集控制通过STM32系列MCU实现，工控机在获取MCU的采集结果后对其进行分类及预处理，并上传至车间服务器。测试结果表明，系统数据采集结果精确且工作稳定。     

JD—30机床功率变送器的试验研究

为了适应切削过程的多种功率监控要求，监控系统必须获得切削过程的动态功率信号，常规测试仪表只能测量在一般时间内的平稳功率，无法输出功率信号的瞬时值。因此必须设计一种能正确测量切削过程动态信号并能提供输出接口的功率变送器。本文介绍了结合上海市重点攻关项目ＦＭＳ中的刀具状态监控系统所研制的机床功率变送器及其试验结果。     

Tool condition monitoring in an end-milling operation based on the vibration signal collected through a microcontroller-based data acquisition system

Machine condition plays an important role in machining performance. A machine condition monitoring system will provide significant economic benefits when applied to machine tools and machining processes. Development of such a system requires reliable machining data that can reflect machining processes. This study demonstrates a tool condition monitoring approach in an end-milling operation based on the vibration signal collected through a low-cost, microcontroller-based data acquisition system. A data acquisition system has been built through interfacing a microcontroller with a signal transducer for collecting cutting vibration. The examination tests of this developed system have been carried out on a CNC milling machine. Experimental studies and data analysis have been performed to validate the proposed system. The onsite tests show the developed system can perform properly as proposed.     

Envelope dynamic analysis: a new approach for milling process monitoring

Vibration analysis has long been used for the detection and identification of the condition of machine tools. This paper proposes a method for vibration analysis in order to monitor online the milling process quality based on synchronous envelope analysis. Adapting envelope spectral analysis to characterize the milling tool is an important contribution for qualitative and quantitative characterization of milling capacity. It is a stage in modeling the three-dimensional cutting process. To determine different parameters, to understand the phenomenon which takes place during the cutting process, and to validate the monitoring algorithm, it was necessary to build and to use a complex analysis system. An experimental protocol was designed and developed for the acquisition, processing, and analyzing the three-dimensional signal. The vibration envelope analysis is proposed to detect the cutting capacity of the tool with the optimization application of cutting parameters. This purpose is reached by a detailed dynamic study of the manufacturing system divided into two parts. The first one concerns the complete analysis of the machine, of the main spindle. A dynamic analysis method is developed to completely characterize the various components of machine tools. The second is concentrated on the cutting process to condition monitoring and diagnosis. The research is focused on fast Fourier transform optimization of vibration analysis and vibration synchronous envelope to evaluate the dynamic behavior of the machine/tool/workpiece.     

带锯床锯切负载检测系统研制

针对金属带锯床对锯切高精度、高效率等方面提出的要求,设计了一种带锯床锯切负载检测系统,提出了一种基于粗糙集数据分析方法(RSDA)的专家系统智能识别策略。该系统实时采集带锯锯切振动信号,经信号处理模块提取特征值,专家系统将提取的特征值暂存于数据库,经过诊断模型的对比分析,对锯切负载进行识别。研究结果表明,该锯切负载检测系统具有识别准确率高、响应速度快等特点,其检测精度可以达到负载检测量程的1‰,可以较好地满足带锯床锯切负载在线识别的需要。     

基于卷曲能的卷曲机实时状态监测系统

根据卷曲机机组运行特点和现场要求，设计并开发出一套实时监测系统。该系统基于IabWindows／CV18．0开发。数据采集模块运用基于库函数NIDAQmx创建任务的技术，与传统的采集方法相比，大大提高了CPU的利用率；数据分析部分提供强大的信号分析功能，包括时域分析、频域分析等；状态监测与报警部分针对卷曲机自身的特点，创新地提出了判断卷曲机的实时状态的一个综合指标，即卷曲能。卷曲能综合了信号的均值、峰峰值和有效值。实际应用结果表明：利用卷曲能判断机械设备的运行状态，卷曲机实时状态监测的水平得到了显著的提高。     

FPGA based failure monitoring system for machining processes

To be adapted in an easy and economical manner to several machining processes is a desired characteristic in any proposed tool condition monitoring system so as to detect or avoid failures in machine tools. Many modern rotating machines have a servodriver which may, without sensors, acquire a current signal which is directly related to the cutting forces and then be correlated to the cutting tool conditions. Most of the reported systems are designed to work only in one machining process; yet the novelty of this paper is the fact of presenting a hardware signal processing unit implemented in a single field-programmable gate array (FPGA) for acquisition, conditioning, and basic signal monitoring in several machining processes. The system has been proven in industrial processes as well as in laboratories with satisfactory results in both cases. This model is reconfigurable and scalable so that it may be adapted to diverse conditions as an economical stand-alone unit since it does not require either computers nor microprocessors.     

高速铣削力测量与研究分析

在高速铣削条件下，利用PCI-1712高速数据采集卡进行数据采集，应用MATLAB软件中信号处理工具箱（SPTOOL）和小波分析工具箱（Wavelet）进行数据处理，从时域和频域两个方面研究原始切削力信号和其不同频率段的重构切削力信号，说明切削力信号的小波系数分析和功率谱分析对于研究切削力有重要意义。     

基于PC机的动平衡机电测系统设计

设计了动平衡机电测系统,由信号处理板、通用数据采集卡和PC机组成.采用软件的方法实现整周期采样和不平衡信号的提取,使得系统不仅具有很高的测量精度和丰富的功能,并且还具有成本低的优点.     

A review of flank wear prediction methods for tool condition monitoring in a turning process

Flank wear is the most commonly observed and unavoidable phenomenon in metal cutting which is also a major source of economic loss resulting due to material loss and machine down time. A wide variety of monitoring techniques have been developed for the online detection of flank wear. In order to provide a broad view of flank wear monitoring techniques and their implementation in tool condition monitoring system (TCMS), this paper reviews three key features of a TCMS, namely (1) signal acquisition, (2) signal processing and feature extraction, and (3) artificial intelligence techniques for decision making.     

机床机电主传动系统服役过程能量效率获取方法

制造系统能效评估及其机床能效评价研究正在国际上迅速兴起,生产现场的机床服役过程(Machine tools’ service process,MTSP)能量效率的方便获取是其关键问题之一。为此,对MTSP中机电主传动系统(Electro-mechanical main driving system,EMDS)能量效率获取方法进行研究。在分析机床能量效率内涵的基础上,基于MTSP中EMDS的时段能量模型,建立基于输入功率检测的和基于输出功率获取的两类4种EMDS能量效率模型;提出对应的能量效率模型中基础数据和基础系数特别是机床载荷损耗系数的获取方法;形成MTSP中EMDS能量效率获取方法。应用该方法,只需现场检测EMDS输入功率,就可获得MTSP中EMDS的现场能量效率。应用案例表明,应用本方法不仅能实现MTSP能量效率现场获取,而且误差较小;可用于机床及制造系统的能效评价、能效监控和能效优化研究中,具有较广阔的应用前景。