摘要
基于时序分析理论,提取并优化选择表征20钢不同时效组织形态超声回波信号的自回归(AR)模型参数,用于超声无损评价。结果表明:利用AR模型参数无损评价20钢的时效组织形态是可行的,对五种组织的识别率可达84％;此外,对Cr5Mo钢高温时效组织形态和30Mn2SiV结构钢的热处理组织形态的识别率分别达到80％和88％。
Based on the time series theory, the autoregressive （AR） model parameters which had been extracted and optimized were applied to the ultrasonic nondestructive evaluation of 20 steel aging microstructure at high temperature. The results showd that it was {easible to evaluate 20 steel aging microstructure at high temperature using auto-regression model parameters, and the recognizing ratio was 84% for fire sorts of aging microstructure at high temperature. In addition, the recognizing ratios for aging microstructure of CrSMo at high temperature and heat treatment microstructure of 30Mn2SiV were 80% and 88%, respectively.
出处
《机械工程材料》
CAS
CSCD
北大核心
2006年第8期25-27,60,共4页
Materials For Mechanical Engineering
关键词
AR模型参数
时效组织
超声无损评价
AR model parameter
aging microstructure
ultrasonic nondestructive evaluation
