Author

Jin-Rui Wang

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Open access Sep 2026

Blind spectrum-guided adaptive cyclic refinement network for bearing fault diagnosis under complex interference

The extraction of weak bearing fault features remains a formidable challenge in the field of mechanical health monitoring, particularly under strong background noise and non-periodic random shocks. Although blind deconvolution methods can effectively eliminate transmission path effects, their reliability is severely re...

Huai-Qian Bao, Xian-Xin Cui, Jian Wang et al. · Measurement science and tech... · 0 citations

#edge computing Open access Sep 2026

An unsupervised micro-anomaly detection method using U-KAN with physical residual decoupling for industrial robots

Industrial robot grasping faces several key challenges, such as subtle anomaly features, scarce abnormal samples, significant domain shifts in training trajectories, and constrained edge computing capacities. To address these issues, this study introduces an unsupervised anomaly detection method, namely the physical re...

Bao-Kun Han, Zi-Han Liu, Jin-Rui Wang et al. · Measurement science and tech... · 0 citations

Open access Aug 2026

Robust bearing fault diagnosis under strong impulsive interference via envelope spectrum harmonic-to-noise ratio guided sparse filtering

Early fault signatures of rolling bearings are typically very weak and are often contaminated by strong background noise and random impulsive interference. Traditional kurtosis-based feature extraction methods are highly sensitive to non-fault-related large random impacts, which may result in incorrect frequency-band s...

Zong-Zhen Zhang, Jing Wang, Jin-Rui Wang et al. · Measurement science and tech... · 0 citations