基于分时段规范变量残差分析的高速自动机动态特性监测

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摘要

针对高速自动机运动形态的多行程特点，提出一种分时段规范变量残差分析（phase-partitioned canonical variate dissimilarity analysis, PCVDA）方法用于高速自动机的动态特性监测。通过建立整个行程与短时瞬态冲击信号的对应关系，将冲击信号划分为多个时段。采用正弦波辅助经验模态分解（sinusoid-assisted empirical mode decomposition, SEMD）将每个时段的冲击信号分解为高频和低频成分，分别计算两种成分的过去和未来数据的规范变量的残差，建立基于高低频成分的PCVDA模型监测高速自动机在不同时段的动态特性。对某12.7mm高速自动机的监测结果验证了PCVDA模型的有效性。

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关键词 ：时段划分')" href="#">

时段划分, 规范变量残差分析, 正弦辅助经验模态分解, 动态监测, 高速自动机

Abstract：

Aiming at monitoring the dynamic characteristics of high-speed automata with multi-stroke features, a phase-partitioned canonical variate dissimilarity analysis (PCVDA) method was proposed.The short-term transient shock signals were firstly partitioned into multiple phases through establishing the matching relationship between the whole strokes and the signals, the sinusoid-assisted empirical mode decomposition (SEMD) was then employed to transform each phase into high-frequency and low-frequency components, and by calculating the departure between the past-and future-projected canonical variables, the PCVDA models on those two components were built to monitor the dynamic characteristics of high-speed automata at different phases, respectively.Dynamic performance monitoring of a 12.7mm high-speed automata validates the efficiency of the proposed work.

Key words： phase partition')" href="#">

phase partition canonical variate dissimilarity analysis sinusoid-assisted

收稿日期: 2018-04-20 出版日期: 2019-10-15

引用本文:

王宝祥1,2，潘宏侠1. 基于分时段规范变量残差分析的高速自动机动态特性监测[J]. 振动与冲击, 2019, 38(20): 90-96.
WANG Baoxiang，PAN Hongxia. Dynamic performance monitoring of high-speed automata based on phase-partitioned canonical variate dissimilarity analysis. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(20): 90-96.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2019/V38/I20/90

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