Please wait a minute...
浙江大学学报(工学版)
环境与能源工程     
应用双树复小波包和NCA-LSSVM检测磁瓦内部缺陷
谢罗峰, 徐慧宁, 黄沁元, 赵越, 殷国富
四川大学 制造科学与工程学院,四川 成都 610065
Application of DTCWPT and NCA-LSSVM to inspect internal defects of magnetic tile
XIE Luo feng, XU Hui ning, HUANG Qin yuan, ZHAO Yue, YIN Guo fu
School of Manufacturing Science and Technology, Sichuan University, Chengdu 610065, China
 全文: PDF(1329 KB)   HTML
摘要:

提出结合双树复小波包变换(DTCWPT)、邻域成分分析法(NCA)、最小二乘支持向量机(LSSVM)的磁瓦内部缺陷检测方法.通过双树复小波包将采集的声音信号分解为6层,得到64个不同频带的子信号;求取特定频带信号的能量、偏度、峭度、模糊熵,并将能量、偏度、峭度、模糊熵作为分类特征|利用邻域成分分析法对分类特征降维|将降维构造的新特征集输入到最小二乘支持向量机,判断磁瓦是否含有内部缺陷.通过实验验证,对提出的检测方法进行可行性分析.3种不同类型磁瓦的内部缺陷识别率均可以达到99%,与以往双谱切片方法相比,提高了检测识别率.试验结果表明,提出的方法具有检测速度快、可靠性高、适应性强等特点,为高效、准确地进行磁瓦内部缺陷检测提供了有效的技术手段.

Abstract:

A novel method was proposed to detect magnetic tile internal defects based on dual-tree complex wavelet packet transform (DTCWPT), neighborhood component analysis (NCA), least squares support vector machines (LSSVM). The impact sound was decomposed up to 6 levels, resulting in 64 sub-signals. Then four statistical features: energy, skewness, kurtosis and fuzzy entropy were calculated to construct feature set. The dimension of feature set was reduced and optimized by NCA. The new feature set was input to LSSVM to judge whether the magnetic tile is with internal defects. The reliability of the proposed method was verified by the experimental results. The classification results showed that the accuracy rates of three kinds of magnetic tiles could reach 99%, higher than the bispectrum method. The experimental results demonstrate that the proposed method is fast, adaptable, efficient and reliable, providing a technical support to detect the internal defects of magnetic tile.

出版日期: 2017-01-01
CLC:  TN 911  
基金资助:

国家自然科学青年基金资助项目(51205265);四川省科技计划资助项目(2015ZR0018).

通讯作者: 徐慧宁,女,讲师. ORCID: 0000-0001-9208-0578.     E-mail: huiningxu@foxmail.com
作者简介: 谢罗峰(1991—),男,硕士生,从事数字化检测的研究. ORCID: 0000-0001-7625-1525. E-mail: xieluofengclark@foxmail.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章  

引用本文:

谢罗峰, 徐慧宁, 黄沁元, 赵越, 殷国富. 应用双树复小波包和NCA-LSSVM检测磁瓦内部缺陷[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2017.01.023.

XIE Luo feng, XU Hui ning, HUANG Qin yuan, ZHAO Yue, YIN Guo fu. Application of DTCWPT and NCA-LSSVM to inspect internal defects of magnetic tile. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2017.01.023.

[1] LI X, JIANG H, YIN G. Detection of surface crack defects on ferrite magnetic tile [J]. NDT&E International, 2014, 62(2): 6-13.
[2] WAGNER R, GONCALVES O, DEMMA A, et al. Guided wave testing performance studies: comparison with ultrasonic and magnetic flux leakage pigs [J]. Insight, 2013, 55(4): 187-196.
[3] MOHAMMAD R, AFZALNIA MR, HAMED F. Heat residual stress measurement of welded areas in steel pipes via magnetic particle testing [J]. Materials Evaluation, 2012, 70(6): 624-630.
[4] SHKATOV P. Combining eddycurrent and magnetic methods for the defectoscopy of ferromagnetic materials [J]. Nondestructive Testing and Evaluation, 2013,28: 155-165.
[5] BAKNOV A S, KUROZAEV V P, KUDRYAVTSEV D A, et al. Increasing the reliability of magneticparticle testing by means of a YMJIK10 automated unit for magnetic fluorescentpenetrant inspection of pipe end faces [J]. Russian Journal of Nondestructive Testing, 2014, 40(5): 311-316.
[6] 黄沁元,殷鹰,赵越,等.基于双谱分析的磁瓦内部缺陷音频检测方法[J].四川大学学报:工程科学版,2014,46(5): 188-194.
HUANG Qinyuan, YIN Ying, ZHAO Yue, et al.Acoustic inspection of internal defect in magnetic tile based on bispectrum analysis [J]. Journal of SichuanUniversity: Engineering Science, 2014, 46(5):188-194.
[7] BAYRAM I, SELESNICK I W. On the dualTree complex wavelet packet and MBand transforms [J]. IEEE Transactions on Signal Processing, 2008, 56(6):22982310.
[8] LO E H S, PICKERING M R, FRATER M R, et al. Image segmentation from scale and rotation invariant texture features from the double dyadic dual-tree complex wavelet transform [J]. Image and Vision Computing, 2011, 9(1): 15-28.
[9] 李辉,郑海起,唐力伟.基于双树复小波包峭度图的轴承故障诊断研究[J].振动与冲击,2012, 31(10): 13-18.
LI Hui, ZHANG Haiqi, TANG Liwei. Bearing fault diagnosis based on kurtogram of dualtree complex wavelet packet transform [J]. Journal of Vibration and Shock, 2012, 31(10): 13-18.
[10] 王娜,郑德忠,刘永红.双树复小波包变换语音增强新算法[J].传感技术学报,2009,22(7):983-987.
WANG Na, ZHENG Dezhong, LIU Yonghong. New method for speech enhancement based on dual tree complex wavelet packet transform [J]. Journal of Sensors and Actuators, 2009, 22(7): 983-987.
[11] ZHOU H, CHEN J, DONG G, et al. Bearing fault recognition method based on neighbourhood component analysis and coupled hidden Markov model [J].Mechanical Systems and Signal Processing, 2016, 6667: 568-581.
[12] XU Q, WONG PK. Hysteresis modeling and compensation of a piezostage using least squares support vector machines [J]. Mechatronics, 2011, 21(7): 12391251.
[13] 杨先勇,周晓军,张文斌,等.基于局域波法和KPCALSSVM的滚动轴承故障诊断[J].浙江大学学报:工学版,2010,44(8): 1519-1524.
YANG Xianyong, ZHOU Xiaojun, ZHANG Wen bin, et al. Rolling bearing fault diagnosis based on local wave method and KPCALSSVM [J]. Journal of Zhejiang University: Engineering Science, 2010, 44(8): 1519-1524.
[14] SELESNICK I W, BARANIUK R G, KINGSBURY N G. The dualtree complex wavelet transform [J]. IEEE Digital Signal Processing Magazine, 2005, 22(6): 123-151.
[15] 胥永刚,孟志鹏,陆明.基于双树复小波包变换的滚动轴承故障诊断[J].农业工程学报,2013, 29(10): 49-56.
XU Yonggang, MENG Zhipeng, LU Ming. Fault diagnosis of rolling bearing based on dualtree complex wavelet packet transform [J]. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(10): 49-56.
[16] 胥永刚,孟志鹏,赵国亮,等.双树复小波包和谱峭度在齿轮故障诊断中的应用[J].北京工业大学学报,2014, 40(4): 488-494.
XU Yonggang, MENG Zhipeng, ZHAO Guoliang, et al. Application of gear fault diagnosis based on dualtree complex wavelet packet transform and spectral kurtosis [J]. Journal of Beijing University of Technology, 2014, 40(4): 488-494.
[17] 郑近德,程军圣,杨宇.基于改进的ITD和模糊熵的滚动轴承故障诊断方法[J].中国机械工程,2012,23(19): 2372-2377.
ZHENG Jinde, CHENG Junsheng, YANG Yu. A rolling bearing fault diagnosis method based on improved ITD and fuzzy entropy [J]. Chinese Mechanical Engineering, 2012,23(19): 2372-2377.
[18] XAVIERDESOUZA S, SUYKENS J A, VANDEWALLE J, et al. Coupled simulated annealing [J]. IEEE Transactions on Systems, Man and Cybernetics: Part B, 2010, 40(2): 320-335.
[19] FAWCETT T. An introduction to ROC analysis [J]. Pattern Recognition Letters, 2006, 27(8): 861-874.

[1] 贾真,董文德,徐贵力,朱士鹏. 基于马尔科夫专家场的泊松噪声图像去噪方法[J]. 浙江大学学报(工学版), 2020, 54(6): 1164-1169.
[2] 冯毅雄,李康杰,高一聪,郑浩,谭建荣. 基于特征与形貌重构的轴件表面缺陷检测方法[J]. 浙江大学学报(工学版), 2020, 54(3): 427-434.
[3] 金列俊,詹建明,陈俊华,王涛. 基于一维卷积神经网络的钻杆故障诊断[J]. 浙江大学学报(工学版), 2020, 54(3): 467-474.
[4] 叶晓杰,崔光茫,于快快,赵巨峰,朱礼尧. 结合编码曝光和运动先验信息的局部模糊图像复原[J]. 浙江大学学报(工学版), 2020, 54(2): 320-330.
[5] 赵祥龙,陈捷,洪荣晶,王华,李媛媛. 基于Wavelet leader和优化的等距映射算法的回转支承自适应特征提取[J]. 浙江大学学报(工学版), 2019, 53(11): 2092-2101.
[6] 胡天中,余建波. 基于多尺度分解和深度学习的锂电池寿命预测[J]. 浙江大学学报(工学版), 2019, 53(10): 1852-1864.
[7] 张亚云,刘家瑞,王志宇,莫炯炯,郁发新. 基于三步旋转坐标旋转数字计算机算法的直接数字频率综合器实现[J]. 浙江大学学报(工学版), 2019, 53(10): 2034-2040.
[8] 吴晨曦, 张旻, 王可人. 基于二级嵌套阵列的宽频段欠定波达方向估计[J]. 浙江大学学报(工学版), 2017, 51(5): 1016-1023.
[9] 王志, 朱世强, 卜琰, 郭振民. 改进导向滤波器立体匹配算法[J]. 浙江大学学报(工学版), 2016, 50(12): 2262-2269.
[10] 陈阔, 冯华君, 徐之海, 李奇, 陈跃庭. 细节保持的快速曝光融合[J]. 浙江大学学报(工学版), 2015, 49(6): 1048-1054.
[11] 于慧敏, 曾雄. 结合排序向量SVM的视频跟踪[J]. 浙江大学学报(工学版), 2015, 49(6): 1015-1021.
[12] 朱株,刘济林. 基于马尔科夫随机场的三维激光雷达路面实时分割[J]. 浙江大学学报(工学版), 2015, 49(3): 464-469.
[13] 江燊煜,陈阔,徐之海,冯华君,李奇,陈跃庭. 基于曝光适度评价的多曝光图像融合方法[J]. 浙江大学学报(工学版), 2015, 49(3): 470-475.
[14] 童基均, 张光磊, 蔡强, 简锦明,郭希山. 阈值随机共振及其在低质量浓度气体检测中的应用[J]. 浙江大学学报(工学版), 2015, 49(1): 15-19.
[15] 李江,赵雅琼,包晔华. 基于混沌和替代数据法的中风病人声音分析[J]. 浙江大学学报(工学版), 2015, 49(1): 36-41.