锻压技术

基于剪切力特征的圆盘剪分切机故障监测方法

英文标题：Condition monitoring method for disc slitting machine based on shearing force characteristics

作者：朱奕玮阎秋生路家斌高伟强吴宇成

单位：广东工业大学

分类号：TG385

出版年,卷(期):页码：2019,44(12):131-138

摘要：

设计了一种能够实时在线检测金属板材圆盘剪分切的三向力测量系统，提供对金属板材圆盘剪三向分切力特性分析的手段和平台，检测过程和剪切力数据稳定可靠。针对圆盘剪分切力信号特征不显著，以及故障状态难以在线远程识别的问题，提出了一种基于本征模态函数(IMF) 能量矩和隐式Markov模型(HMM)相结合的圆盘剪分切机故障诊断方法。使用经验模态分解（EMD)方法将振动信号分解成若干本征模态函数（IMF)，计算本征模态函数（IMF)能量矩作为状态特征信息，构造特征向量，建立隐式Markov模型对圆盘剪分切机进行故障监测识别。实验表明，该方法能有效识别圆盘刀周向跳动、机床空转、机床停机3种故障，可用于圆盘剪分切机故障监测。

A three-dimensional force measuring system was designed to test
disc slitting of metal plate in real time online and provide a way and platform for analyzing the characteristics of the three-dimensional force of disc slitting for metal plate, and the testing process and the shearing force data were both stable and reliable. Then, for the problem of non-significant signal feature of disc slitting force and the difficulty in long-range online identification under malfunction, the fault diagnosis method on disc slitting machine was proposed based on the intrinsic mode function (IMF) energy moment and the hidden Markov model (HMM), and it used empirical mode decomposition (EMD) method to decompose vibration signals into multiple intrinsic mode functions (IMF), constructed the feature vectors by calculating energy moments of IMF as state feature information, and established a hidden Markov model to monitor and identify the malfunctions of the disc slitting machine. The experiment shows that the above method effectively identify the malfunctions such as circular jumping of disc cutter, machine tool idling and machine tool shutdown, and it detects malfunctions of the disc slitting machine.

基金项目：

国家自然科学基金资助项目(51575112)；广东省科技计划项目(2016A050503043)；广州市南沙区科技计划项目(2015CX010)

朱奕玮(1991-)，男，博士研究生 E-mail：731557862@qq.com 通讯作者：阎秋生(1962-)，男，博士，教授 E-mail：qsyan@gdut.edu.cn

参考文献：

［1］刘培锷,吴国彦. 圆盘剪切机剪切力和轴向力的实验研究
［J］. 重型机械,1994，(5):22-26.

Liu P E,Wu G Y. Experimental study on shear and axial forces of disc shear
［J］. Heavy Machinery,1994,(5): 22-26.

［2］张文芹. 电子铜带的精密分切技术及应用现状
［J］. 铜业工程,2017，(1):21-24.

Zhang W Q. Accuracy slitting technology and application status of electronic copper strip
［J］. Copper Engineering,2017，(1):21-24.

［3］赵治国,李航宇,雷丹.干式DCT离合器无刷直流作动电机双卡尔曼滤波故障诊断
［J］. 机械工程学报,2018,54(2):138-149.

Zhao Z G,Li H Y,Lei D.Fault diagnosis based on dual kalman filter of clutch brushless DC actuator motor for dry dual clutch transmission
［J］. Journal of Mechanical Engineering，2018，54(2):138-149.

［4］王轩,王细洋. 面向故障诊断的行星齿轮扭振信号测量与分析
［J］.中国机械工程,2018,29(1):49-56.

Wang X,Wang X Y. Measuremen and analysis of torsional vibration signals for diagnosing planetary gearbox faults
［J］. China Mechanical Engineering,2018,29(1):49-56.

［5］Bin G F，Gao J J，Li X J. Early fault diagnosis of rotating machinery based on wavelet packets-empirical mode decomposition feature extraction and neural network
［J］. Mechanical System and Signal Processing，2012，27：696-711.

［6］刘占军,张卫平.基于小波神经网络信息融合的板材拉深故障诊断研究
［J］.塑性工程学报,2005,12(5):24-27.

Liu Z J,Zhang W P. The defect diagnosis of test die-drawing on the information merge of wavelet neural network
［J］.Journal of Plasticity Engineering,2005,12(5): 24-27.

［7］Zhang C L,Yue X,Li S,et al. Fault diagnosis of rotating machinery base on wavelet packet energy moment and HMM
［J］. Key Engineering Materials,2010,455:558-564.

［8］路家斌,潘嘉强,阎秋生. 不锈钢薄板圆盘剪分切过程有限元仿真研究
［J］. 机械工程学报,2013,49(9):190-198.

Lu J B,Pan J Q,Yan Q S. Finite element simulation of stainless steel sheet metal disc slitting process
［J］. Journal of Mechanical Engineering，2013，49(9):190-198.

［9］Chen J,Wang Z,Sun Y. Real-time capability analysis for switch industrial Ethernet traffic priority-based
［A］. International Conference on Control Applications
［C］. IEEE,2002，1:525-529.

［10］Huang N E,Shen Z,Long S R,et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
［J］. Proceedings of the Royal Society of London. Series A: Mathematical,Physical and Engineering Sciences,1998,454(1971): 903-995.

［11］杨宇. 基于EMD和支持向量机的旋转机械故障诊断方法研究
［D］. 长沙：湖南大学,2005.

Yang Y. Research on Fault Diagnosis Methods for Rotating Machinery Based on Empirical Mode Decomposition and Support Vector Machine
［D］. Changsha: Hunan University,2005.

［12］莫仕勋,王辑祥,吴杰康,等. 组合通信模式下发电机监控系统的设计与实践
［J］. 电力自动化设备,2010,30(11):122-126.

Mo S X,Wang J X,Wu J K,et al. Design and implementation of generator supervisory system with combined communication mode
［J］. Electric Power Automation Equipment,2010,30(11):122-126.

［13］张敏,崔海龙,陈曦晖,等. 基于IMF能量矩和HSMM模型的滚动轴承故障诊断方法
［J］. 组合机床与自动化加工技术,2015,(10):101-103.

Zhang M,Cui H L,Chen X H,et al.Fault diagnosis of rolling bearing based on intrinsic mode function energy moment and hidden semi-Markov model
［J］. Modular Machine Tool ＆ Automatic Manufacturing Technique,2015,(10):101-103.

［14］楚晓艳. 基于HSMM的齿轮故障诊断方法研究
［D］. 重庆：重庆交通大学，2015.

Chu X Y. Gear Fault Diagnosis Method Based on Hidden Semi Markov Model
［D］.Chongqing：Chongqing Jiaotong University,2015.

［15］何树波,丁启全,李志安,等. 基于Wavelet-HMM的旋转机械故障诊断方法研究
［J］. 机械强度,2003,25(5):473-475.

He S B,Ding Q Q,Li Z A,et al. Study of fault diagnosis methods of rotating machines based on Wavelet transform-hidden Markov models
［J］. Journal of Mechanical Strength,2003,25(5):473-475.

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