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。     

离散型智能制造切削单元智能监控系统的开发

以典型离散型智能制造切削单元为载体,分析智能制造切削单元工艺系统、生产流程、在线测量系统、射频识别系统、仓储物流系统、工艺装备等在产品生产过程中需要监控的数据和对象,由此开发基于第五代移动通信工业互联网技术的离散型智能制造切削单元智能监控系统。介绍了离散型智能制造切削单元智能监控系统的基本框架,分析了数据采集与智能控制模块、数据处理服务模块、可视化监控模块、第五代移动通信+工业互联网通信模块等组成模块,给出了离散型智能制造切削单元智能监控系统的主要功能。这一智能监控系统可以为离散型制造企业的智能化管理、生产调度、优化资源配置、绿色制造提供数据和技术支持。     

大型机组润滑安全在线监控与智能预警系统研究

石化行业中的大型机组实时润滑数据是设备在线监测、智能诊断和预警的关键信息.为实现石化行业大型机组润滑状态的在线监测、智能诊断和预警,融合传感技术、网络通信、大数据和故障诊断技术,设计基于机电液一体化的油液在线安全监控与智能预警系统;应用多传感器采集的润滑油温度、水分、黏度、介电常数和污染度等实时数据,实现润滑系统的在线...     

基于小波分析刀具破损检测

刀具切削状态的在线监测是自动化加工技术中的难题,国内外已有许多专家和学者进行了深入研究。针对目前刀具切削状态在线监测中出现的问题,提出了一种利用小波分析技术提取刀具状态信号特征量,对刀具的破损进行预报的监测系统。经大量试验和使用,验证了其可行性和实用性。     

城市轨道交通牵引变电所在线监测方案研究

随着城市轨道交通网络化发展,供电系统的设备运维面临巨大挑战,因此通过引入在线监测系统对变电所一次设备运行状态进行实时监测。轨道交通在线监测系统主要从中央级在线监测系统、站级管理系统、所内机器人巡检及软件框架等方面进行系统性设计,利用智能传感装置、机器人、大数据等技术进行供电系统智慧化建设,以全面提升运维检修效率,改善设备监测能力及设备管控方式,使系统运行更加稳定、更加安全。     

智能刀具研究综述

智能刀具根据加工中具体用途的不同,可实现对切削状态在线监测、数据处理、切削过程优化控制等功能,通过智能刀具的使用可改善加工过程,提高加工质量与效率,到目前为止学者们对于智能刀具的研究已取得大量研究成果。对智能刀具切削状态监测和切削过程控制两个方面的研究进展进行论述,梳理了学者们应用智能刀具对切削力、切削温度、刀具振动进行监测与控制的研究成果,对刀具结构、监测方式、控制原理、缺点不足、发展方向进行了总结与讨论。对智能刀具涉及的关键技术进行探讨,由于智能刀具涉及多学科交叉,实现的功能及采用的原理各不相同,关键技术多样,需进行多学科交叉融合,并通过产学研协同合作,推进智能刀具关键技术的深入研究及实际应用。     

基于分布式光纤的电力电缆健康状态监测与可视化技术研究

进行分布式光纤传感技术机理分析及监测系统网络拓扑的建立,设计了分布式监测、集中管理和实时分析的电力电缆状态在线监测系统架构;同时,运用先进的计算机技术和可视化技术将监测结果直观地显示在人机平台上,供运行人员参考,实现对电力电缆当前和历史的健康状态的监控、分析、故障定位和预警,最后通过相应的案例进行了展示和验证,为建设坚强智能电网迈出了有力的一步。     

基于多源参量感知的航空工装定位器在线监测方法与系统研究

航空工装定位器作为飞机部件装配的定位基准，其全局力位状态直接影响装配精度。因此，赋予工装力位状态自检能力对保障装配精度与效率具有重要意义。提出一种基于多源参量感知的航空工装定位器在线监测方法，可实现严重遮挡、受限测量空间下工装定位器全局位移与应变状态的在线监测。提出可见区域视觉测量-近封闭空间涡流传感的局部位移在线采集方法，拓展工装复杂结构的位移在线监测能力；研究定位器受载状态下应变敏感区域，综合系统敏感性与测量空间可达性，建立光纤内嵌传感的工装应变高性能监测方法；同时，构建定位器在不同工况下力位数据集，并以此数据为基础，提出工装定位器“离散在线监测-全局实时感知”的力位信息全局预测方法，最终形成了基于多源参量感知的航空工装定位器在线监测系统。仿真试验及现场应用验证结果表明，所提方法与系统可赋予航空工装多源状态在线监测能力，实现工装在线自检，推进智能工装的发展。     

智能轴承在钻削加工中的应用

在组合机床及自动化生产中,由于切削加工的自动化,要求对切削状态与刀具状态进行在线检测。介绍用于切削加工的刀具状态监控系统－智能轴承监控系统,该系统在大量实验的基础上,根据切削力与磨损之间的关系,制定了刀具状态监控策略,采用多级报警的方式,实现了民具不同状态的在线检测。     

支持物联网的智能切削刀具视觉在线监测系统

针对国内数控加工中心刀具管理混乱、刀具损耗严重进而导致加工工件次品率急剧上升等实际问题,结合国内外智能切削刀具的研究现状和发展水平,提出一种支持物联网的智能切削刀具视觉在线监测系统。该系统构建支持物联网的机器视觉刀具磨损在线监测,采用Zig Bee技术组建无线传感器网络,通过机床关键部位安装的传感器,实现数据的实时传输。通过以太网传输到智能管理系统,并对在线视觉监控和实时传输数据进行分析与整理,完成对刀具生命全周期的在线监测和管理,在保证加工质量的同时提高加工效率和降低成本。     

Real‐Time Monitoring of Tool Fracture in Turning Using Sensor Fusion

The sensor fusion method using both an acoustic emission (AE) sensor and a built-in force sensor is introduced for on-line tool condition monitoring during turning. The cutting force was measured by a built-in piezoelectric force sensor, which was inserted in the tool turret housing of an NC lathe. FEM analysis was carried out to locate the most sensitive position for the sensor. A burst of AE signal was used as a triggering signal to inspect the cutting force. A significant drop in cutting force indicated tool breakage. The algorithm was implemented in a DSP board and the monitoring system was installed on a CNC lathe in an FMS line for in-process tool-breakage detection. The proposed system showed an excellent monitoring capability.     

An intelligent sensor fusion system for tool monitoring on a machining centre

The objective of this paper is to construct an intelligent sensor fusion monitoring system for tool breakage on a machining centre. Since none of the sensing and diagnosis techniques have proved to be completely reliable in practice, an intelligent tool-monitoring system consisting of a neural-network-based algorithm and a sensor fusion system is proposed. The dual sensing signals of cutting force and acoustic emission are used simultaneously in the proposed system owing to good correlation existing between them, and, a self-learning neural-network algorithm is used to integrate multiple sensing information to make a proper decision about tool condition. The results show good performance in tool-breakage detection by the proposed monitoring system, especially where there is high interference.     

刀具磨损识别方法的分析与研究

在对刀具磨损理论研究的基础上,提出了多种刀具磨损识别方法,为刀具磨损识别及切削过程在线监测提供理论依据。     

ESPRIT- and HMM-based real-time monitoring and suppression of machining chatter in smart CNC milling system

Suppression of machining chatter during milling processes is of great significance for surface finish and tool life. In this paper, a smart CNC milling system integrating the function of signal processing, monitoring, and intelligent control is presented with the aim of real-time chatter monitoring and suppression. The algorithm of estimation of signal parameters via rotational invariance techniques (ESPRIT) is adopted to extract the frequency characteristics of acceleration signals, and then, cutting state is categorized as stable state, chatter germination state, and chatter state based on amplitude-frequency characteristics of identified acceleration signals. The model of chatter identification is acquired by training a hidden Markov model (HMM), which combines acceleration signals and labeled cutting state. To implement real-time chatter suppression, the algorithm of fuzzy control is integrated into a smart CNC kernel to determine the relationship between cutting force and spindle speed. Furthermore, spindle speed of machine tool could be adjusted timely in the presented system once the chatter is identified. Finally, the effectiveness of the proposed real-time chatter monitoring and suppression system is experimentally validated.     

智能刀具状态监测系统及其应用

探讨了智能刀具状态监测系统的设计思想,提出了一种智能刀具状态监测系统的基本结构框图,并进行了试验分析,结果表明,通过人工神经网络估算刀磨损值与实例值基本一致,系统取得了９０％的刀具磨损识别成功率。     

面向铣削加工过程在线监测的智能测振刀柄系统

智能化的切削过程监测技术已逐渐成为提升生产效率和产品质量的重要手段。为克服传统有线式振动采集系统振动衰减、安装不便和移植性差等缺陷,开发了面向铣削加工过程在线监测的智能测振刀柄系统,并开展了锤击法模态试验和不同刀具状态下的铣削加工试验,验证了该系统的实用性、可靠性和有效性。     

多传感器刀具状态监控系统

介绍一个多传感器、多特征量的刀具状态监控系统。以声发射、功率监控和改进的神经网络技术，借助刀具监控软件，识别刀具切削工作的正常和失效状态。软件有信号采集、特征提取、网络训练回忆以及监控等功能，可实现离线和在线监控。并以离线控制试验为实例，考核该系统识别刀具状态的可靠性。     

The design of a single-chip tool monitoring system for on-line turning operation

Tool condition monitoring systems play an important role in a FMS system. By changing the worn tool before or just at the time it fails, the loss caused by defect product can be reduced greatly and thus product quality and reliability is improved. To achieve this, an on-line tool condition monitoring system using a single-chip microcomputer for detecting tool breakage during cutting process is discussed in this paper. Conventionally, PC-based monitoring systems are used in most research works. The major shortcoming of PC-based monitoring systems is the incurred cost. To reduce costs, the tool condition monitoring system was built with an Intel 8051 single-chip microprocessor and the design is described in this paper. The 8051 tool monitoring system uses a strain gauge for measuring cutting force; according to the force feature, the tool monitoring system can easily recognize the breakage of the cutting tool with its tool breakage algorithm. The experimental results show that the low-cost 8051 tool monitoring board can detect tool breakage in three successive products successfully.