基于新型谱聚类算法的提升机故障监测研究

Study on Fault Monitoring in Hoister Based on New Spectral Clustering Algorithm

针对经典的谱聚类算法运算效率较低,鲁棒性较差等缺点,设计一种新型的谱聚类算法,引入数据场模型,用于剔除孤立数据以及初始聚类中心点的确定,最后通过UCI数据集和提升机轴承故障数据验证了算法的优越性,能够有效提升矿井提升机故障检测系统性能。

Aiming at the shortage of low calculating efficiency and poor robustness of classical spectral clustering algorithm,a new spectral clustering algorithm has been designed and introduced in data field mode to eliminate isolated data and determine initial cluster centers,finally the calculating advantage has been tested and verified by UCI dataset and fault data of hoist bearings,which can effectively improve the performance of fault detection system of mine hoister.