安增辉｜山东建筑大学｜学者主页

2026

基于时频双分支注意力增强的元学习轴承故障诊断

郑翼虎，安增辉，王鲁彬，张鹏飞，杨蕊

《起重运输机械》

2026

HabitOSR: Research on the Habit‐Formation Mechanism and Method for Prioritized Unknown Fault Identification in Open Set Bearing Diagnosis

Zenghui An, Chuanmeng Wang, Xinpeng Wang, Zhirui Kai, Tongxiao Yang, Yang Rui

Quality and Reliability Engineering International

DOI

2026

Deep energy learning integrating dual-weight adaptive network and adversarial training: An open-set fault diagnosis model for rolling bearings under cross-device conditions

Zenghui An, Lubin Wang, Yihu Zheng, Pengfei Zhang, Chuanmeng Wang, Rui Yang

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science

DOI

2026

Few-shot class-incremental fault diagnosis of bearings via pseudo-incremental learning and dual-model complementarity

Rui Yang, Pengfei Zhang, Zhirui Kai, Lubin Wang, Yihu Zheng, Zenghui An

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science

DOI

2025

基于图谱的塔机结构损伤诊断技术研究

宋世军，徐保壮，杨蕊，安增辉

《自动化应用》

2025

基于加速度信号阈值分段校正的位移测量方法

宋世军，崔兵，杨蕊，安增辉

《起重运输机械》

2025

Transforming Closed-Set to Open-Set Diagnosis: Placeholder Learning for Bearing Faults

Chuanmeng Wang, Tongxiao Yang, Zhirui Kai, Xinpeng Wang, Rui Yang, Zenghui An

Global Reliability and Prognostics and Health Management Conference (PHM)

DOI

2024

非完备数据集下的标准自学习数据增强滚动轴承故障诊断方法

安增辉，江星星，杨蕊，赵磊，朱忠奎，李舜酩

《振动工程学报》

2024

密度峰值聚类在塔机损伤诊断中的应用研究

王胜春，安宏，安增辉，李文豪

《机械设计与制造》

2024

施工升降机传递路径减振方法探讨

徐美，姜昊，姜洪奎，安增辉

《建筑机械》

2024

Dilated dynamic supervised contrastive learning framework for fault diagnosis under imbalanced dataset conditions

Rui Yang, Jia Dong Shi, Houliang Wang, Yinglong Yan, Peng-fei Zhang, Zenghui An

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science

DOI

2024

A dual-weight mechanism-based neural network for partial domain adaptation fault diagnosis of bearings under different working conditions

Zenghui An, Yinglong Yan, Jia Dong Shi, Houliang Wang, Yihu Zheng, Yang Rui

Measurement Science and Technology

DOI

2024

Fault Diagnosis of Few Sample Rolling Bearings Based on SE Attention and Similarity Contrastive Learning

LuBin Wang, Houliang Wang, Yinglong Yan, Peng-fei Zhang, Rui Yang, Zenghui An

Global Reliability and Prognostics and Health Management Conference (PHM)

DOI

2024

Self-Supervised Time-Frequency Alignment with Convolutional Block Attention Module

Pengfei Zhang, Jia Dong Shi, Lubin Wang, Yihu Zheng, Rui Yang, Zenghui An

Global Reliability and Prognostics and Health Management Conference (PHM)

DOI

2024

Contrast learning with hard example mining for few-shot fault diagnosis of rolling bearings

Zenghui An, Houliang Wang, Yinglong Yan, Jia Shi, Lubin Wang, Yang Rui

Measurement Science and Technology

DOI

2023

基于域自适应的塔式起重机结构损伤诊断方法研究

宋世军，朱昆贤，安增辉，宋连玉，杨蕊

《起重运输机械》

2023

Mode-Decoupling Auto-Encoder for Machinery Fault Diagnosis Under Unknown Working Conditions

Zenghui An, Xingxing Jiang, Jie Liu

IEEE Transactions on Industrial Informatics

DOI

2023

Few-shot Fault Diagnosis Based on Supervised Contrast Learning

Houliang Wang, Yinglong Yan, Shi Jia, Zenghui An

Global Reliability and Prognostics and Health Management Conference (PHM)

DOI

2023

A Standard Self-Learning Unsupervised Contrastive Learning Model for Bearing Fault Diagnosis in Imbalanced Datasets

Jia Dong Shi, Houliang Wang, Yinglong Yan, Pengfei Zhang, Rui Yang, Zenghui An

Global Reliability and Prognostics and Health Management Conference (PHM)

DOI

2023

Fault Diagnosis Method Based On Joint Distributional Adaptation For Intelligent Fault Diagnosis Under Different Working Conditions With Imbalanced Data

Yinglong Yan, Jia Shi, Houliang Wang, Yuxi Zhang, Zenghui An, Rui Yang

Global Reliability and Prognostics and Health Management Conference (PHM)

DOI

2023

Imbalanced data based fault diagnosis of the chiller via integrating a new resampling technique with an improved ensemble extreme learning machine

Hanyuan Zhang, Wenxin Yang, Weilin Yi, Jit Bing Lim, Zenghui An, Chengdong Li

Journal of Building Engineering

DOI

2022

基于一维卷积神经网络的塔式起重机结构损伤诊断方法研究

宋世军，刘昂，安增辉，杨蕊，吴月华

《起重运输机械》

2022

基于特征映射平面的塔机塔身钢结构损伤快速识别方法

杨蕊，宋世军，宋连玉，安增辉，臧泓源，张会敏

《振动与冲击》

2022

Actively Imaginative Data Augmentation for Machinery Diagnosis Under Large-Speed-Fluctuation Conditions

Zenghui An, Xingxing Jiang, Rui Yang, Hanyuan Zhang, Jie Liu, Changqing Shen

IEEE Transactions on Industrial Informatics

DOI

2022

Data Augmentation in 2D Feature Space for Intelligent Weak Fault Diagnosis of Planetary Gearbox Bearing

Rui Yang, Zenghui An, Weiling Huang, Rijun Wang

Applied Sciences

DOI

2022

Multilayer Extreme Learning Convolutional Feature Neural Network Model for the Weak Feature Classification and Status Identification of Planetary Bearing

Rui Yang, Zenghui An, Song Shijun

Journal of Sensors

DOI

2021

Self-learning transferable neural network for intelligent fault diagnosis of rotating machinery with unlabeled and imbalanced data

Zenghui An, Xingxing Jiang, Jing Jin Cao, Rui Yang, Xue‐Gang Li

Knowledge-Based Systems

DOI

2021

Hybrid distance-guided adversarial network for intelligent fault diagnosis under different working conditions

Baokun Han, Xiao Zhang, Jinrui Wang, Zenghui An, Sixiang Jia, Guowei Zhang

Measurement

DOI

2020

滚动轴承冲击特征提取的同步挤压S变换方法

潘高元，李舜酩，安增辉，曾宇

《振动工程学报》

DOI

2020

转速大波动下滚动轴承智能故障诊断方法研究

王金瑞，李舜酩，钱巍巍，安增辉，张伟

《振动工程学报》

DOI

安增辉

精选作品

期刊论文

基于时频双分支注意力增强的元学习轴承故障诊断

HabitOSR: Research on the Habit‐Formation Mechanism and Method for Prioritized Unknown Fault Identification in Open Set Bearing Diagnosis

Deep energy learning integrating dual-weight adaptive network and adversarial training: An open-set fault diagnosis model for rolling bearings under cross-device conditions

Few-shot class-incremental fault diagnosis of bearings via pseudo-incremental learning and dual-model complementarity

基于图谱的塔机结构损伤诊断技术研究

基于加速度信号阈值分段校正的位移测量方法

Transforming Closed-Set to Open-Set Diagnosis: Placeholder Learning for Bearing Faults

非完备数据集下的标准自学习数据增强滚动轴承故障诊断方法

密度峰值聚类在塔机损伤诊断中的应用研究

施工升降机传递路径减振方法探讨

Dilated dynamic supervised contrastive learning framework for fault diagnosis under imbalanced dataset conditions

A dual-weight mechanism-based neural network for partial domain adaptation fault diagnosis of bearings under different working conditions

Fault Diagnosis of Few Sample Rolling Bearings Based on SE Attention and Similarity Contrastive Learning

Self-Supervised Time-Frequency Alignment with Convolutional Block Attention Module

Contrast learning with hard example mining for few-shot fault diagnosis of rolling bearings

基于域自适应的塔式起重机结构损伤诊断方法研究

Mode-Decoupling Auto-Encoder for Machinery Fault Diagnosis Under Unknown Working Conditions

Few-shot Fault Diagnosis Based on Supervised Contrast Learning

A Standard Self-Learning Unsupervised Contrastive Learning Model for Bearing Fault Diagnosis in Imbalanced Datasets

Fault Diagnosis Method Based On Joint Distributional Adaptation For Intelligent Fault Diagnosis Under Different Working Conditions With Imbalanced Data

Imbalanced data based fault diagnosis of the chiller via integrating a new resampling technique with an improved ensemble extreme learning machine

基于一维卷积神经网络的塔式起重机结构损伤诊断方法研究

基于特征映射平面的塔机塔身钢结构损伤快速识别方法

Actively Imaginative Data Augmentation for Machinery Diagnosis Under Large-Speed-Fluctuation Conditions

Data Augmentation in 2D Feature Space for Intelligent Weak Fault Diagnosis of Planetary Gearbox Bearing

Multilayer Extreme Learning Convolutional Feature Neural Network Model for the Weak Feature Classification and Status Identification of Planetary Bearing

Self-learning transferable neural network for intelligent fault diagnosis of rotating machinery with unlabeled and imbalanced data

Hybrid distance-guided adversarial network for intelligent fault diagnosis under different working conditions

滚动轴承冲击特征提取的同步挤压S变换方法

转速大波动下滚动轴承智能故障诊断方法研究

研究方向