1.青岛大学 数据科学与软件工程学院, 山东 青岛 266000
高畅(1993— ),男,河北唐山人,硕士,主要研究方向为工业大数据分析、机器学习、智能制造。
周强(1981— ),男,山东青岛人,博士,副教授,硕士生导师,主要研究方向为计算机软件理论、计算机网络、大数据。
扫 描 看 全 文
高畅,于忠清,周强.GA-ACO优化BP神经网络在行星齿轮箱故障诊断中的应用[J].机械传动,2021,45(03):153-160.
Gao Chang,Yu Zhongqing,Zhou Qiang.Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox[J].Journal of Mechanical Transmission,2021,45(03):153-160.
高畅,于忠清,周强.GA-ACO优化BP神经网络在行星齿轮箱故障诊断中的应用[J].机械传动,2021,45(03):153-160. DOI: 10.16578/j.issn.1004.2539.2021.03.025.
Gao Chang,Yu Zhongqing,Zhou Qiang.Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox[J].Journal of Mechanical Transmission,2021,45(03):153-160. DOI: 10.16578/j.issn.1004.2539.2021.03.025.
针对目前利用优化算法改进的BP神经网络算法对行星齿轮箱进行故障诊断过程中存在的故障识别率低、收敛速度慢和参数选择困难等问题,提出了一种用GA-ACO算法对神经网络参数进行优化的算法。给出GA-ACO-BP算法的基本原理和主要步骤,并将此方法应用到行星齿轮箱的故障诊断中。比较了ACO-BP神经网络算法和GA-ACO-BP算法的性能。结果表明,ACO优化BP神经网络算法对行星齿轮箱的故障诊断收敛速度慢且识别精度不高,而GA-ACO-BP算法能够对行星齿轮箱故障进行准确、快速的诊断和识别。
Aiming at the problems of low fault recognition rate, slow convergence speed and difficult parameter selection in the process of fault diagnosis of planetary gearbox based on BP neural network improved by optimization algorithm, a GA-ACO algorithm is proposed to optimize the parameters of neural network. The basic principle and main steps of GA-ACO-BP algorithm are given. At the same time, this method is applied to the fault diagnosis of planetary gearbox. Comparing the performance of ACO-BP neural network algorithm and GA-ACO-BP algorithm, the results show that the convergence speed of ACO Optimized BP neural network is slow and the recognition accuracy is not high, while GA-ACO-BP algorithm can accurately and quickly diagnose and identify the fault of planetary gearbox.
GA-ACO-BP算法行星齿轮箱故障诊断遗传算法蚁群优化算法BP神经网络
GA-ACO-BP algorithmPlanetary gearboxFault diagnosisGenetic algorithmAnt colony optimization algorithmBP neural network
魏秀业,潘宏侠.齿轮箱故障诊断技术现状及展望[J].测试技术学报,2006(4):368-376.
WEI Xiuye,PAN Hongxia.Review of the gearbox fault diagnosis technology[J].Journal of Test and Measurement Technology,2006(4):368-376.
赵艳丽,刘奇志,白士红.模糊关联方法在齿轮箱故障诊断中的应用[J].沈阳航空工业学院学报,2003(2):21-22.
ZHAO Yanli,LIU Qizhi,BAI Shihong.The application of illegibility associated degree method in diagnosis of gear box failure[J].Journal of Shenyang Aerospace University,2003(2):21-22.
LIU Y,QIN Z,XU Z L,et al.Feature Selection with Particle Swarms[C].Computational and Information Science,2004,3314:425-430.
杜设亮,傅建中,陈子辰,等.基于BP神经网络的齿轮故障诊断系统研究[J].机电工程,1999(5):3-5.
DU Sheliang,FU Jianzhong,CHEN Zichen,et al.Study on gear fault diagnosis system based on BP neural network[J].Journal of Mechanical & Electrical Engineering,1999(5):3-5.
王凯,张永祥,李军.小波神经网络在齿轮故障诊断中的应用[J].煤矿机械,2004(7):126-128.
WANG Kai,ZHANG Yongxiang,LI Jun.The application of wavelet-based neural network for gear fault diagnosis[J].Coal Mine Machinery,2004(7):126-128.
CHEN P,LIANG X,YAMAMOTO T.Rough sets and partially-linearized neural network for structure fault diagnosis of rotating machinery[J].Lecture Notes in Computer Science book series,2004,3174:574-580.
艾莉,程加堂.蚁群算法融合BP神经网络的齿轮故障模式识别[J].机械传动,2012,36(7):86-88.
AI Li,CHENG Jiatang.Mode identification of gear fault based on ant colony algorithm combing with BP neural network[J].Journal of Mechanical Transmission,2012,36(7):86-88.
杨家印.一种BP神经网络的汽车齿轮箱故障诊断方法及实验验证[J].机械传动,2019,43(1):150-153.
YANG Jiayin.A fault diagnosis method and experimental verification of automobile gearbox based on BP neural network[J].Journal of Mechanical Transmission,2019,43(1):150-153.
李华,梅卫江,赵永满,等.齿轮典型故障特征分析及其振动信号处理方法[J].湖南农机,2014,41(3):59-60.
LI Hua,MEI Weijiang,ZHAO Yongman,et al.Analysis on typical gear faults and treatment of its vibration signal[J].Times Agricultural Machinery,2014,41(3):59-60.
LI J M,YAO X F,WANG X D,et al.Multiscale local features learning based on BP neural network for rolling bearing intelligent fault diagnosis[J].Measurement,2020,153:107419.
ZHANG X L,CHEN X F,HE Z J.Fault diagnosis based on support vector machines with parameter optimization by an ant colony algorithm[J].Journal of Mechanical Engineering Science,2010,224(1):217-229.
SAFARVAND D,ALIZADEH M,SAMIPOUR GIRI M,et al.Exergy analysis of NGL recovery plant using a hybrid ACOR‐BP neural network modeling:a case study[J].Asia Pacific Journal of Chemical Engineering,2015,10(1):133-153.
游志勇,苏彦莽,王羿帆,等.基于GA-ACO-BP的WSN数据融合算法实现[J].现代电子技术,2019,42(21):13-17.
YOU Zhiyong,SU Yanmang,WANG Yifan,et al.Implementation of WSN data fusion algorithm based on GA-ACO-BP[J].Modern Electronics Technique,2019,42(21):13-17.
禹迪.基于GA-ACO算法和BP神经网络的语音识别研究[D].湘潭:湘潭大学,2016:24-27.
YU Di.The research of speech recognition based on GA-ACO algorithm and BP neural networks[D].Xiangtan:Xiangtan University,2016:24-27.
LIU Y,CHEN H X.Fault diagnosis of gearbox based on RBF-PF and particle swarm optimization wavelet neural network[J].Neural Computing and Applications,2019,31(9):4463-4478.
吴玉国,宋崇智.蚁群神经网络在齿轮箱故障诊断中的研究与应用[J].机械传动,2007(4):87-89.
WU Yuguo,SONG Chongzhi.Research & application based on ant-neural networks fault diagnosis gear box[J].Journal of Mechanical Transmission,2007(4):87-89.
王敏.基于蚁群优化算法的齿轮箱故障诊断研究[D].太原:中北大学,2010:24-28.
WANG Min.Fault diagnosis of Gear-box based on ant colony optimization[D].Taiyuan:North China University,2010:24-28.
0
浏览量
4
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构