Zhengjia He

TL;DR: This paper attempts to survey and summarize the recent research and development of EMD in fault diagnosis of rotating machinery, providing comprehensive references for researchers concerning with this topic and helping them identify further research topics.

TL;DR: This paper aims to review and summarize publications on condition monitoring and fault diagnosis of planetary gearboxes and provide comprehensive references for researchers interested in this topic.

TL;DR: Wang et al. as discussed by the authors proposed a new EEMD-based method for fault diagnosis of rotating machinery, which can reveal the signal characteristic information accurately because of the problem of mode mixing.

TL;DR: The proposed method for fault diagnosis based on empirical mode decomposition (EMD), an improved distance evaluation technique and the combination of multiple adaptive neuro-fuzzy inference systems (ANFISs) show that the multiple ANFIS combination can reliably recognise different fault categories and severities.

TL;DR: In this article, the inner product operation of wavelet transform (WT) is verified by simulation and field experiments and the development process of WT based on inner product is concluded and the applications of major developments in rotating machinery fault diagnosis are also summarized.