...Yuewen Su; Chao Yu; Liya Shi; Caixia Guo Purpose Planetary gearboxes (PGBs) are core industrial components, but current fault diagnosis faces high data collection costs, weak early fault signals masked by strong noise and low traditional model fidelity. This study aims to build a high-fidelity...

... and elevates fault frequency. Radial load suppresses frequency deviation under starvation. This study provides the theoretical basis for dynamic monitoring of starved bearings in rotating machinery, enhancing fault diagnosis accuracy. Design/methodology/approach This study models frequency variations...

..., the extracted feature parameters are combined with SSA-PNN for diagnosis recognition to construct the RCMPNDE-SSA-PNN fault diagnosis method. Findings The proposed RCMPNDE-SSA-PNN fault diagnosis method is tested on actual data sets and its outcomes have been compared to those generated by methods built...

...Tan Zhang; Zhanying Huang; Ming Lu; Jiawei Gu; Yanxue Wang Purpose Rotating machinery is a crucial component of large equipment, and detecting faults in it accurately is critical for reliable operation. Although fault diagnosis methods based on deep learning have been significantly developed...

... convolutional network is proposed. Finally, the phase diagrams of different states are used as samples and input into a two-dimensional CNN for learning modeling to construct a PSR-CNN fault diagnosis model. Findings The proposed PSR-CNN model is tested on two data sets and compared with support vector...

...Defeng Lv; Huawei Wang; Changchang Che Purpose The purpose of this study is to achieve an accurate intelligent fault diagnosis of rolling bearing. Design/methodology/approach To extract deep features of the original vibration signal and improve the generalization ability and robustness...

...Changchang Che; Huawei Wang; Xiaomei Ni; Qiang Fu Purpose The purpose of this study is to analyze the intelligent fault diagnosis method of rolling bearing. Design/methodology/approach The vibration signal data of rolling bearing has long time series and strong noise interference, which brings...

...-stationarity of the fault signal. So, the LMD–Teager transform has better analysis accuracy and resolution than the traditional Fourier method, which provides a good alternative for fault diagnosis of the rolling bearing. Jianhua Cai can be contacted at: cjh1021cjh@163.com 21 12 2015 09 09 2016...