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一种基于变频器电流检测机床刀具磨损新方法的研究
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河南省科技攻关计划(B20143384)


Research on New Method of Tool Wear for Machine Tool Based on Frequency Converter Current Detection
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    摘要:

    针对传统机床刀具磨损状态检测方法的局限性和不足等问题,采用间接量来检测刀具磨损状态而提出了一种基于机床变频器三相输入平均有效电流信号来检测刀具磨损状态新方法。首先,介绍了铣床变频器电流检测刀具磨损新方法的工作原理,验证并对比了三相平均有效电流信号计算法优于传统RMS计算法;其次,利用三相平均有效电流(ARMS)计算法和传统RMS计算法来获取计算后的有效电流信号,结合小波降噪和EEMD分解法对信号进行降噪、分解及重构处理,分析重构后其时频域下两种方法计算的有效电流值信号各频带能量和均方差并将其组成特征向量;最后,将特征向量输入CPSOELM和PNN神经网络等分类器进行故障识别和对比。实验结果表明,CPSOELM相比PNN神经网络分类器具有准确的识别效果,验证了所采用的变频器电流来检测铣床刀具磨损新方法的有效性和可行性。

    Abstract:

    Aiming at the limitation and insufficiency of traditional machine tool wear state detection method, a new method based on the threephase input average effective current signal of machine tool inverter is proposed to detect tool wear state by using an indirect quantity. Firstly, the working principle of the new method of tool wear for current detection of lathe inverter was introduced, and the calculation method of threephase average effective current signal was better than that of traditional Root Mean Square(RMS) calculation method by comparison and verification, and secondly, the calculated effective current signal was obtained by using the threephase average effective current calculation method and the traditional RMS calculation method. Combining wavelet noise reduction and Ensemble Empirical Mode Decomposition (EEMD) method to reduce noise, decompose and reconstruct the signal, the energy and mean variance of each frequency band of the effective current value signal calculated by the two methods in the reconstructed timefrequency domain were analyzed and the eigenvectors were composed. Finally, the eigenvectors were input Chaos Particle Swarm OptimizationExtreme Learning Machine(CPSOELM) and Productbased Neural Network (PNN) and other classifiers for fault identification and comparison. The experimental results show that CPSOELM has a fast and accurate recognition effect compared with PNN neural network classifier, which verifies the validity and feasibility of a new method of detecting lathe tool wear by using inverter current.

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张小翠,徐小明.一种基于变频器电流检测机床刀具磨损新方法的研究[J].机床与液压,2019,47(13):213-218.
. Research on New Method of Tool Wear for Machine Tool Based on Frequency Converter Current Detection[J]. Machine Tool & Hydraulics,2019,47(13):213-218

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  • 在线发布日期: 2020-03-12
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