基于主成分分析的18CrNiMo7-6材料理化参数无损评估方法
Nondestructive Evaluation Method of Carburized 18CrNiMo7-6 Parameters Based on Principal Component Analysis
摘 要
重载齿轮材料18CrNiMo7-6加工后需经渗碳处理, 齿轮表面及亚表面理化参数通常需通过切割样品进行有损检测来得到, 且产品无法实现全数检查。提出一种基于Barkhausen效应的无损检测方法, 通过提取Barkhausen噪声信号的六个特征值并对其进行主成分分析, 用降维后的主成分评估18CrNiMo7-6材料表面及亚表面马氏体、残余奥氏体含量, 以及有效硬化层深度等参数。对实际产品进行检测验证, 结果表明该方法是一种可对齿轮产品全数检测的有效无损检测与评估方法。
巴克豪森
无损检测与评估
主成分分析
有效硬化层深
Carburization
Barkhausen effect
Nondestructive testing & evaluation
Principal component analysis
Case depth
Abstract
The material of heavy-load gear,18CrNiMo7-6,was carburized after manufacture. Gears could not be tested exhaustively because the physicochemical parameters of surface and sub-surface material were measured by destructive methods. This paper presented a nondestructive method based on Barkhausen effect. The common six features of MBN (Magnetic Barkhausen Noise) signal were extracted for PCA (Principal Component Analysis). The principal components from dimension reduction process were used to evaluate the martensite, residual austenite and case depth in the surface and sub-surface of carburized 18CrNiMo7-6. By evaluating some products from gear faculty, this nondestructive testing and evaluation method was proven effective for gear exhaustive test.
中图分类号 TH878 TG115.28 DOI 10.11973/wsjc201608003
所属栏目 科研成果与学术交流
基金项目 江苏省研究生创新基金资助项目(CXLX11_0184)
收稿日期 2016/3/3
修改稿日期
网络出版日期
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备注丁 松(1977-), 男, 博士研究生, 主要从事电磁无损检测技术研究。
引用该论文: DING Song,WANG Ping,TIAN Gui-yun. Nondestructive Evaluation Method of Carburized 18CrNiMo7-6 Parameters Based on Principal Component Analysis[J]. Nondestructive Testing, 2016, 38(8): 12～16
丁 松,王 平,田贵云. 基于主成分分析的18CrNiMo7-6材料理化参数无损评估方法[J]. 无损检测, 2016, 38(8): 12～16
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参考文献
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【16】张九龙, 邓筱楠, 张志禹. 概率核主成分分析及其应用［J］. 计算机工程与应用, 2011,47(4):165-167.
【2】刘贤焕,叶仲和.大型风力发电机组用齿轮箱优化设计及方案分析［J］.机械设计与研究, 2006(9): 92-94.
【3】吉田秋良,大上佑司. 基于具有动态特性的小波变换的齿轮轮齿表面故障诊断［J］.设备管理与维修,2006(5):45-46.
【4】白亚红,王奉涛.EMD分解和支持向量机技术在风电齿轮箱早期齿轮磨损故障诊断中的应用［J］.工业控制计算机, 2010,23(2): 70-71.
【5】DAVID G L. Gear crack propagation path studies-guidelines for ultra-safe design［J］. Journal of the American Helicopter Society, 2001,47(1):64-72.
【6】GB/T 3480.5-2008 直齿轮和斜齿轮承载能力计算(第5部分): 材料的强度和质量［S］.
【7】TIAN G Y, SOPHIAN A. Defect classification using a new feature for pulsed eddy current sensors［J］. NDT & E Int,2005, 38:77-82.
【8】钟志明. 核电站在役检查无损检测鉴定的现状及发展［J］.无损检测, 2010,32(5):385-389.
【9】JILES D C. Review of magnetic methods for nondestructive evaluation［J］. NDT & E Int,1988,21:311-319.
【10】DOBMANN G, MEYENDORF N, SCHNEIDER E. Nondestructive characterization of materials. A growing demand for describing damage and service-life-relevant aging processes in plant components［J］. Nucl Eng Des,1997, 171:95-112.
【11】MOORTHY V, VAIDYANATHAN S, BALDEV R, et al. Evaluation of microstructures in 2.25Cr-1Mo and 9Cr-1Mo steelweldments using magnetic Barkhausen noise［J］. Materials Science and Engineering A,1997, 231: 98-104.
【12】MOORTHY V, SHAW B A, EVANS J T. Evaluation of tempering induced changes in the hardness profile of case-carburised EN36 steel using magnetic Barkhausen noise analysis［J］. NDT & E Int, 2003, 36: 43-49.
【13】FRANCO F A, GONZLEZ M F R, DE CAMPOS M F, et al. Relation between magnetic barkhausen noise and hardness for jominy quench tests in SAE 4140 and 6150 steels［J］. Journal Nondestruct Eval, 2013,32:93-103.
【14】AKI S, KAUKO L, SUVI S, et al. Quantitative prediction of residual stress and hardness in case-hardenedsteel based on the Barkhausen noise measurement［J］. NDT & E Int,2012,46:100-106.
【15】陆超, 陈捷, 洪荣晶. 采用概率主成分分析的回转支承寿命状态识别［J］. 西安交通大学学报, 2015,49(10): 90-96.
【16】张九龙, 邓筱楠, 张志禹. 概率核主成分分析及其应用［J］. 计算机工程与应用, 2011,47(4):165-167.
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