Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significa...Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing costs.Recently,an innovative TCM approach based on sensor data modelling and model frequency analysis has been proposed.Different from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process model.Then,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health conditions.In order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency analysis.The feature dimension is reduced by principal component analysis first.Then the moving average strategy is exploited to generate monitoring variables and overcome the effects of noises.The milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end mills.The results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.展开更多
因特殊工况要求,5G基站的空调设备多常年开启以维持基站内的正常工作温度,从而保障主通讯设备的正常运行。据统计,移动通信基站中空调设备能耗约占总能耗的46%,5G基站空调的高能耗问题亟待解决。本文基于NB-IoT(Narrow Band Internet of...因特殊工况要求,5G基站的空调设备多常年开启以维持基站内的正常工作温度,从而保障主通讯设备的正常运行。据统计,移动通信基站中空调设备能耗约占总能耗的46%,5G基站空调的高能耗问题亟待解决。本文基于NB-IoT(Narrow Band Internet of Things,窄带物联网)技术设计了远程控制系统,实现了对5G基站空调的实时监控和运维;再通过设计智能温控系统,利用室内温度与室内外温差双参数决策、PID控制来实现5G基站空调的智能调节。通过Simulink仿真与实验测试验证了控制系统的有效性。展开更多
文摘Tool condition monitoring(TCM)is a key technology for intelligent manufacturing.The objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing costs.Recently,an innovative TCM approach based on sensor data modelling and model frequency analysis has been proposed.Different from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process model.Then,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health conditions.In order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency analysis.The feature dimension is reduced by principal component analysis first.Then the moving average strategy is exploited to generate monitoring variables and overcome the effects of noises.The milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end mills.The results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.
文摘因特殊工况要求,5G基站的空调设备多常年开启以维持基站内的正常工作温度,从而保障主通讯设备的正常运行。据统计,移动通信基站中空调设备能耗约占总能耗的46%,5G基站空调的高能耗问题亟待解决。本文基于NB-IoT(Narrow Band Internet of Things,窄带物联网)技术设计了远程控制系统,实现了对5G基站空调的实时监控和运维;再通过设计智能温控系统,利用室内温度与室内外温差双参数决策、PID控制来实现5G基站空调的智能调节。通过Simulink仿真与实验测试验证了控制系统的有效性。
