In a drilling process, the power spectrum of the drilling force is related tothe tool wear and is widely applied in the monitoring of tool wear. But the feature extraction andidentification of the power spectrum have ...In a drilling process, the power spectrum of the drilling force is related tothe tool wear and is widely applied in the monitoring of tool wear. But the feature extraction andidentification of the power spectrum have always been an unresolved difficult problem. This papersolves it through decomposition of the power spectrum in multilayers using wavelet transform andextraction of the low frequency decomposition coefficient as the envelope information of the powerspectrum. Intelligent identification of the tool wear status is achieved in the drilling processthrough fusing the wavelet decomposition coefficient of the power spectrum by using a BP (BackPropagation) neural network. The experimental results show that the features of the power spectrumcan be extracted efficiently through this method, and the trained neural networks show highidentification precision and the ability of extension.展开更多
Tool wear state classification has good potential to play a critical role in ensuring the dimensional accuracy of the work piece and prevention of damage to cutting tool in machining process. During machining process,...Tool wear state classification has good potential to play a critical role in ensuring the dimensional accuracy of the work piece and prevention of damage to cutting tool in machining process. During machining process, tool wear is an important factor which contributes to the variation of spindle motor current, speed, feed and depth of cut. In the present work, online tool wear state detecting method with spindle motor current in turning operation for Al/SiC composite material is presented. By analyzing the effects of tool wear as well as the cutting parameters on the current signal, the models on the relationship between the current signals and the cutting parameters are established with partial design taken from experimental data and regression analysis. The fuzzy classification method is used to classify the tool wear states so as to facilitate defective tool replacement at the proper time.展开更多
射频识别(Radio Frequency Identification,RFID)技术是一种利用无线电波进行识别和跟踪的技术,被广泛应用于各种物品和设备的标签中,以实现自动化管理和信息追踪。深入探讨了提高RFID电力标签抗电磁干扰性能的设计方法,包括合理选择材...射频识别(Radio Frequency Identification,RFID)技术是一种利用无线电波进行识别和跟踪的技术,被广泛应用于各种物品和设备的标签中,以实现自动化管理和信息追踪。深入探讨了提高RFID电力标签抗电磁干扰性能的设计方法,包括合理选择材料、优化天线设计及采用先进的信号调制技术等策略。这些技术措施能够显著提升RFID标签在电力工器具应用中的稳定性和可靠性,从而适应复杂的电磁环境并保证电力系统的高效运行。展开更多
文摘In a drilling process, the power spectrum of the drilling force is related tothe tool wear and is widely applied in the monitoring of tool wear. But the feature extraction andidentification of the power spectrum have always been an unresolved difficult problem. This papersolves it through decomposition of the power spectrum in multilayers using wavelet transform andextraction of the low frequency decomposition coefficient as the envelope information of the powerspectrum. Intelligent identification of the tool wear status is achieved in the drilling processthrough fusing the wavelet decomposition coefficient of the power spectrum by using a BP (BackPropagation) neural network. The experimental results show that the features of the power spectrumcan be extracted efficiently through this method, and the trained neural networks show highidentification precision and the ability of extension.
文摘Tool wear state classification has good potential to play a critical role in ensuring the dimensional accuracy of the work piece and prevention of damage to cutting tool in machining process. During machining process, tool wear is an important factor which contributes to the variation of spindle motor current, speed, feed and depth of cut. In the present work, online tool wear state detecting method with spindle motor current in turning operation for Al/SiC composite material is presented. By analyzing the effects of tool wear as well as the cutting parameters on the current signal, the models on the relationship between the current signals and the cutting parameters are established with partial design taken from experimental data and regression analysis. The fuzzy classification method is used to classify the tool wear states so as to facilitate defective tool replacement at the proper time.
文摘射频识别(Radio Frequency Identification,RFID)技术是一种利用无线电波进行识别和跟踪的技术,被广泛应用于各种物品和设备的标签中,以实现自动化管理和信息追踪。深入探讨了提高RFID电力标签抗电磁干扰性能的设计方法,包括合理选择材料、优化天线设计及采用先进的信号调制技术等策略。这些技术措施能够显著提升RFID标签在电力工器具应用中的稳定性和可靠性,从而适应复杂的电磁环境并保证电力系统的高效运行。
