Incremental cluster analysis for batch drilling-quality based on improved InDBSCAN algorithm

Aiming at monitor and analysis on batch drilling-quality,an acoustic emission sensor was used to collect the acoustic emission signal,extract statistic characteristics and then construct the signal characteristic vector.An improved incremental density based spatial clustering algorithm of time-domain applications with noise(InDBSCAN) was put forward to analyze the distribution law of batch drilling-quality indirectly.Take new data insertion into consideration.Because some of the original clusters could be remerged when the new cluster was created,and so the InDBSCAN algorithm was modified.The results show that the conclusion of incremental cluster analysis is more reasonable by the improved InDBSCAN algorithm and the detection accuracy of batch drilling-quality is up to 84.3%.