喷嘴
磨料
声学
快速傅里叶变换
参数统计
自回归模型
自回归滑动平均模型
信号(编程语言)
材料科学
直线(几何图形)
振幅
机械工程
计算机科学
工程类
光学
数学
物理
算法
几何学
统计
程序设计语言
计量经济学
作者
Radovan Kovacevic,L Wang,Y M Zhang
标识
DOI:10.1243/pime_proc_1994_208_076_02
摘要
The abrasive waterjet nozzle is one of the most critical parts that influences the technical and economical performance of an abrasive waterjet system. In order to control the uniformity of cutting results in milling and cutting, it is necessary to devise a sensing system that can sense on-line the nozzle wear. This paper presents an on-line technique for monitoring the nozzle wear which is based on monitoring the acoustic signals generated by the abrasive waterjet. The autoregressive moving average (ARMA) spectra are used to estimate the nozzle wear. It has been shown that the ARMA spectra can reveal more features of the nozzle wear than the conventional fast Fourier transform (FFT) method. It was found that the amplitude of the spectra and the frequency of the spectra peaks of ARMA models have a high sensitivity to a small variation of the nozzle exit geometry. A method based on on-line acoustic signals is proposed for identification of the nozzle inside diameter.
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