Research on Circular plot analysis method and gear fault intelligent diagnosis based on time synchronous averaging

XU Yonggang; ZHANG Yifei; SUN Guodong; ZHANG Kun

doi:10.16579/j.issn.1001.9669.2025.06.002

您当前的位置：

首页 >

文章列表页 >

Research on Circular plot analysis method and gear fault intelligent diagnosis based on time synchronous averaging

·Vibration·Noise·Monitoring·Diagnosis· | 更新时间：2025-06-09

- Research on Circular plot analysis method and gear fault intelligent diagnosis based on time synchronous averaging
- Journal of Mechanical Strength Vol. 47, Issue 6, Pages: 11-16(2025)
- 作者机构：
  
  1.北京工业大学先进制造技术北京市重点实验室，北京 100124
  2.山东省科学技术情报研究院，济南 250101
- 作者简介：
  
  ZHANG Kun, E-mail: zkun212@163.com
- 基金信息：
  
  Young Scientists Fund of the National Natural Science Foundation of China(52405083)
- DOI：10.16579/j.issn.1001.9669.2025.06.002
  CLC： TH132
- Received：22 September 2023，
  
  Revised：06 December 2023，
  
  Published：15 June 2025
- 稿件说明：
移动端阅览
胥永刚，张翼飞，孙国栋，等. 基于时域同步平均的Circular图分析方法及齿轮故障智能诊断研究［J］. 机械强度，2025，47（6）：11-16.

XU Yonggang，ZHANG Yifei，SUN Guodong，et al. Research on Circular plot analysis method and gear fault intelligent diagnosis based on time synchronous averaging［J］. Journal of Mechanical Strength，2025，47（6）：11-16.
胥永刚，张翼飞，孙国栋，等. 基于时域同步平均的Circular图分析方法及齿轮故障智能诊断研究［J］. 机械强度，2025，47（6）：11-16. DOI： 10.16579/j.issn.1001.9669.2025.06.002.

XU Yonggang，ZHANG Yifei，SUN Guodong，et al. Research on Circular plot analysis method and gear fault intelligent diagnosis based on time synchronous averaging［J］. Journal of Mechanical Strength，2025，47（6）：11-16. DOI： 10.16579/j.issn.1001.9669.2025.06.002.

摘要

齿轮Circular图是用于与时域同步平均（Time Synchronous Averaging

TSA）相结合的一种结果呈现方法，可以将TSA提取到的齿轮啮合振动波形直观、清晰地展现出来。针对齿轮Circular图绘制参数设置和其缺少量化指标的问题，提出了用于波形边缘识别的

指标和基于Hu氏不变矩的

指标。首先，使用TSA算法提取出齿轮啮合振动信号，通过计算最小

指标确定振动信号波形的上、下边缘；其次，利用上、下边缘参数绘制齿轮Circular图；再次，将齿轮Circular图分割为4个部分，通过计算分割后图片的Hu氏不变矩得到齿轮Circular图的

指标；最后，基于从齿轮Circular图中提取出的

和

指标，使用K最近邻（K-Nearest Neighbor

KNN）分类器对齿轮振动信号进行分类。仿真信号及齿轮断齿、裂纹故障信号的处理结果表明了该方法的有效性。

Abstract

Gear’s Circular plot is a result presentation method which needs to be combine with time synchronous averaging (TSA)

which can clearly display gear meshing vibration waveform extracted by TSA. Aiming at the problem of parameter setting of gear’s Circular plot and lack of the quantitative index

index for waveform edge recognition and

index based on Hu-moments were proposed. Firstly

TSA algorithm was used to extract the gear meshing vibration signal

and the upper and lower edges of the vibration signal waveform were determined by calculating the minimum

index.Secondly

Circular plot of gears were drawn by the upper and lower edge parameters. Then

the Circular plot of the gear was divided into four parts

and

index of the Circular plot was obtained by calculating Hu-moments of the picture after segmentation. Finally

based on the

and

indices extracted from the gear Circular plot

a K-nearest neighbors (KNN) classifier was utilized to classify the gear vibration signals. The results show that there is a significant difference between the

and

indices of the vibration signals of normal gears and those of abnormal gears. By combining with the KNN classifier， it is possible to distinguish between normal and abnormal gear signals， which proves the effectiveness of this method.

关键词

Keywords

references

LIU R N ， YANG B Y ， ZIO E ， et al . Artificial intelligence for fault diagnosis of rotating machinery：a review ［J］. Mechanical Systems & Signal Processing ， 2018 ， 108 ： 33 - 47 .

何雷，刘溯奇 . 强干扰下基于TMD-SVD和POS-BP网络的变速箱状态识别［J］. 机械传动， 2021 ， 45 （ 5 ）： 169 - 176 .

HE Lei ， LIU Suqi . Gearbox status recognition based on TMD-SVD and POS-BP networks under strong interference ［J］. Journal of Mechanical Transmission ， 2021 ， 45 （ 5 ）： 169 - 176 . （In Chinese）

DHAMANDE L S ， CHAUDHARI M B . Compound gear-bearing fault feature extraction using statistical features based on time-frequency method ［J］. Measurement ， 2018 ， 125 ： 63 - 77 .

郭远晶，金晓航，魏燕定，等 . 改进TSA降噪与平方包络谱分析的故障特征提取［J］. 振动工程学报， 2021 ， 34 （ 2 ）： 402 - 410 .

GUO Yuanjing ， JIN Xiaohang ， WEI Yanding ， et al . Fault feature extraction based on improved TSA denoising and squared envelope spectrum ［J］. Journal of Vibration Engineering ， 2021 ， 34 （ 2 ）： 402 - 410 . （In Chinese）

FENG K ， JI J C ， NI Q ， et al . A review of vibration-based gear wear monitoring and prediction techniques ［J］. Mechanical Systems & Signal Processing ， 2023 ， 182 ： 109605 .

陈予恕 . 机械故障诊断的非线性动力学原理［J］. 机械工程学报， 2007 ， 43 （ 1 ）： 25 - 34 .

CHEN Yushu . Nonlinear dynamical principle of mechanical fault diagnosis ［J］. Chinses Journal of Mechanical Engineering ， 2007 ， 43 （ 1 ）： 25 - 34 . （In Chinese）

DUAN L X ， XIE M Y ， WANG J J ， et al . Deep learning enabled intelligent fault diagnosis：overview and applications ［J］. Journal of Intelligent & Fuzzy Systems ， 2018 ， 35 （ 5 ）： 5771 - 5784 .

LEI Y G ， YANG B ， JIANG X W ， et al . Applications of machine learning to machine fault diagnosis：a review and roadmap ［J］. Mechanical Systems & Signal Processing ， 2020 ， 138 ： 106587 .

胥永刚，李凌均，何正嘉 . 近似熵及其在机械设备故障诊断中的应用［J］. 信息与控制， 2002 ， 31 （ 6 ）： 547 - 551 .

XU Yonggang ， LI Lingjun ， HE Zhengjia . Approximate entropy and its applications in mechanical fault diagnosis ［J］. Information and Control ， 2002 ， 31 （ 6 ）： 547 - 551 . （In Chinese）

CUI B D ， WENG Y ， ZHANG N . A feature extraction and machine learning framework for bearing fault diagnosis ［J］. Renewable Energy ， 2022 ， 191 ： 987 - 997 .

HU M K . Visual pattern recognition by moment invariants ［J］. IRE Transactions on Information Theory ， 1962 ， 8 （ 2 ）： 179 - 187 .

WONG R Y ， HALL E L . Scene matching with invariant moments ［J］. Computer Grahpics and Image Processing ， 1978 ， 8 （ 1 ）： 16 - 24 .

丁明跃，常金玲，彭嘉雄 . 不变矩算法研究［J］. 数据采集与处理， 1992 ， 7 （ 1 ）： 1 - 9 .

DING Mingyue ， CHANG Jinling ， PENG Jiaxiong . Research on moment invariants algorithm ［J］. Journal of Data Acquisition & Processing ， 1992 ， 7 （ 1 ）： 1 - 9 . （In Chinese）

何成刚，张燕平，赵姝 . 基于二阶不变矩的弹头痕迹自动比对优化方法研究［J］. 计算机应用研究， 2010 ， 27 （ 8 ）： 2895 - 2898 .

HE Chenggang ， ZHANG Yanping ， ZHAO Shu . Research of bullet engraving automated comparison optimization method based on second moment invariants ［J］. Application Research of Computers ， 2010 ， 27 （ 8 ）： 2895 - 2898 . （In Chinese）

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Semi-supervised gearbox fault diagnosis under variable working conditions based on masked contrastive learning

FAULT DIAGNOSIS OF GEARBOX UNDER VARIABLE WORKING CONDITION BASED ON WEIGHTED SUBDOMAIN ADAPTIVE ADVERSARIAL NETWORK

STATIC AND DYNAMIC CHARACTERISTIC ANALYSIS AND MULTI-OBJECTIVE TOPOLOGY OPTIMIZATION OF GEARBOX

FAULT DIAGNOSIS OF GEARBOX BASED ON ADAPTIVE EEMD AND FAST KURTOGRAM

RESEARCH ON GEAR BOX FAULT DIAGNOSIS BASED ON DCNN AND XGBOOST ALGORITHM

Related Author

YU Xi

LI Hang

ZUO Fangjun

ZHANG Huiyun

YANG Ting

YU Xi

ZHANG Huiyun

HAO Shuai

Related Institution

School of Intelligent Manufacturing, Chengdu Technological University

School of Mechanical Engineering, Sichuan University

College of Mechanical Engineering, Sichuan University

School of Mechanical and Electrical Engineering, Anhui Jianzhu University

Anhui Province Key Laboratory of Critical Friction Pair for Advanced Equipment

⁰