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高速电主轴驱动系统性能评价研究

Performance Diagnosis of the Drive Unit forHigh Speed Motorized Spindle
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摘要 目的 提出一种基于隐含状态映射机制高速电主轴驱动系统的性能评价方法,以提高数控机床的加工质量,降低设备故障风险。方法 根据驱动系统动态特性提取系统模型特征参数,依据系统模型参数提取特征,获得对应的隐含状态信息;根据仿真分析结果与实际经验相结合来确定电主轴驱动系统的性能评价等级;以高速电主轴驱动系统中变频器内的IGBT器件发生性能退化现象为例进行实验验证。结果 随着剪断键合线数量不断增加,笔者所提方法的隐含退化量不断增大;当剪断四根键合线时,隐含退化量值为0.218 3,系统出现失效状态。结论 IGBT器件的不同退化程度所对应的辨识参数能够映射为隐含状态特征,用于驱动系统的性能评价,可以验证该方法的合理性和有效性;笔者所提方法可用于驱动单元发生性能失效前的健康状态评价,能够有效地提高电主轴系统的安全性和可靠性,为构建整个高速电主轴系统的运行评价管理框架奠定基础。 As the key component of the motorized spindle system,the performance of drive unit will directly affect the processing quality of CNC machine tools.This paper proposed a performance diagnosis method for the drive unit based on hidden state mapping model to prevent the motorized spindle from failure.The hidden state model was obtained by feature extraction of the parameter vectors identified from the dynamic responses to test input signals.The thresholds of performance degradation were determined by the hidden state to evaluate the performance of the drive unit in the motorized spindle system.A simulation case was carried out to verify the feasibility and effectiveness of the proposed model by taking IGBT degradation failure as an example.The results showed that the model parameters extracted from different degradation degrees of IGBT devices can be mapped to hidden state characteristics and used for performance evaluation of the drive unit.The proposed hidden state mapping model can be used in the framework of monitoring the safety and reliability of the drive unit,and lay the foundation for the prognostic and health management of the motorized spindle system.
作者 范丽婷 贾正伟 司志鹏 刘继智 张珂 FAN Liting;JIA Zhengwei;SI Zhipeng;LIU Jizhi;ZHANG Ke(School of Mechanical Engineering,Shenyang Jianzhu University,Shenyang,China,110168)
出处 《沈阳建筑大学学报(自然科学版)》 CAS 北大核心 2023年第2期363-369,共7页 Journal of Shenyang Jianzhu University:Natural Science
基金 国家自然科学基金项目(52175107) 辽宁省教育厅项目(lnjc201908)。
关键词 高速电主轴 驱动系统 隐含状态映射 性能评价 high speed motorized spindle drive unit hidden state mapping performance diagnosis
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