Journal of Dynamics, Monitoring and Diagnostics

Aims & Scope

Sponsored by Chongqing Sino-German Future Factory Research Institute and Chongqing University of Technology.

The Journal of Dynamics, Monitoring and Diagnostics is a Gold Open Access, peer reviewed journal that publishes articles on the theoretical, technological, and experimental aspects of fault diagnostics, monitoring and related dynamics.

The journal aspires to be a high-level international academic journal that provides a prestigious platform for both researchers and practitioners in the fault diagnostic community.

The Journal of Dynamics, Monitoring and Diagnostics welcomes submissions on the following topics, but are not limited to: -New techniques in measurement and sensing -Fault dynamic modeling and analysis of failure mechanisms -Feature extraction, fault detection and severity assessment -Fault diagnostics, prognostics and health management -Developments of signal processing for machine condition monitoring

View Aims & Scope

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Metrics & Ranking

SJR (SCImago Journal Rank)

Year	Value
2024	1.939

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	17

Journal Rank

Year	Value
2024	1533

Journal Citation Indicator

Year	Value
2024	493

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Engineering, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Inter-shaft Bearing Fault Diagnosis Based on Aero-engine System: A Benchmarking Dataset Study

  Citation: 66

  Authors: Lei, Haiming, Yuhong, Min, Lianzheng, Jianwei, Yushu

• Residual Convolution Long Short-Term Memory Network for Machines Remaining Useful Life Prediction and Uncertainty Quantification

  Citation: 43

  Authors: Wenting, Yaguo, Tao, Naipeng, Asoke

• Compound Fault Diagnosis for Rotating Machinery: State-of-the-Art, Challenges, and Opportunities

  Citation: 40

  Authors: Ruyi, Jingyan, Bin, Zhuyun, Weihua

• Physics-Informed Deep Neural Network for Bearing Prognosis with Multisensory Signals

  Citation: 35

  Authors: Xuefeng, Meng, Zhibin, Zhi, Zhu

• Orthogonal On-Rotor Sensing Vibrations for Condition Monitoring of Rotating Machines

  Citation: 30

  Authors: Yuandong, Xiaoli, Guojin, Dong, Craig, Fengshou, Andrew

• Prognostics and Remaining Useful Life Prediction of Machinery: Advances, Opportunities and Challenges

  Citation: 26

  Authors: Nagi, Yaguo, Naipeng, Xiaosheng, Enrico

• Short-time Fourier Transform Using Odd Symmetric Window Function

  Citation: 26

  Authors: Miaofen, Youmin, Shaodan, Tianyang, Fulei

• Long-range Dependencies Learning Based on Non-Local 1D-Convolutional Neural Network for Rolling Bearing Fault Diagnosis

  Citation: 20

  Authors: Huan, Zhiliang, Ting

• The Effect of Signal Propagation Delay on the Measured Vibration in Planetary Gearboxes

  Citation: 19

  Authors: Marc

• RMA-CNN: A Residual Mixed-Domain Attention CNN for Bearings Fault Diagnosis and its Time-Frequency Domain Interpretability

  Citation: 15

  Authors: Dandan, Huan, Wim, Konstantinos

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