基于形态距离的真空热试验数据相似性度量研究

Data similarity measurement method for shape-based distance in thermal vacuum test

1.
Beijing Institute of Spacecraft Environment Engineering
2.
Science and Technology on Reliability and Environmental Engineering Laboratory

摘要: 针对真空热试验过程中的数据自动化监视需求，利用数据挖掘手段开展数据异常监测方法研究，提出了一种改进DTW-形态距离相似性度量算法，通过调整形态符号的计算方法，避免了数据规范化带来的形态符号计算失真问题。对实际样本数据相似性聚类准确率进行统计分析，获得了相关参数的最佳取值范围，达到了较高的聚类精度。
- 真空热试验；动态时间弯曲距离；数据挖掘；相似性度量；形态距离
Abstract: For data automatic monitoring in the vacuum thermal test, the data abnormity detection method based on data mining is studied, and an improved DTW shape-based distance similarity measurement method is proposed. The algorithm reduces the amount of computation by the wavelet transformation and the search width limit, which avoids the distortion of the shape symbol by adjusting the calculation method. Its parameters are universal for the vacuum thermal test data and the best range of parameters is obtained through the statistical analysis of the actual sample data’s similarity clustering accuracy.
- vacuum thermal test