摘要
本文通过实测近十年来出现的木工机床噪声声压级数据,利用k-means聚类算法,对13类共65台木工机床噪声声压级测试数据进行数据清洗及聚类分析,并采用降维的方法提高效率及准确度,聚类结果直观明确,限值分类合理,为木工机床限值标准提供数据处理方法参考。
The noise sound pressure level test data of 65 woodworking machine tools in 13 categories are cleaned and clustered by using k-means clustering algorithm based on the data measured over the past ten years in this paper. The dimension reduction method is used to improve the efficiency and accuracy of the algorithm,the clustering results are intuitive and clear,and the limits are classified reasonably. It provides a reference for data processing methods for limit standards of woodworking machine tools.
出处
《木工机床》
2022年第2期5-7,11,共4页
Woodworking Machinery
关键词
木工机床
噪声声压级
聚类分析
K-MEANS
woodworking machine tools
noise sound pressure level
cluster analysis
k-means
