… different bearing faults studied in this paper followed by the mathematical background of
fractal … Thereafter, the proposed time domain bearing detection and diagnosis framework is …

… There are various techniques that can be used for bearing fault detection and these techniques
can … The HFTR is the most popular for bearing fault detection and diagnosis [5]. The dis…

… Marwala T, Mahola U, Nelwamondo FV (2006) Hidden Markov models and Gaussian mixture
models for bearing fault detection using fractals. In: Proceedings of the IEEE international …

… the standard hidden Markov model (HMM) for fault detection by … First, the de-noised time-scale
signatures are extracted using … to perform fault detection on the bearings supporting the …

… robust new hidden Markov modeling (BRNHMM) for bearing fault detection and diagnosis
based … [6] used HMM combined with the use of Mel-frequency cepstral coefficient, fractal and …

… In this paper, a new fault diagnosis approach is introduced to distinguish the two major
faults namely bearing fault and unbalanced rotor bar from the healthy condition in synchronous …

… the nonlinear feature of bearing fault. To realize more accurate fault diagnosis, multiple
nonlinear features such as box-counting dimension, multiscale fractal dimension [10], [11], and …

… fault detection and diagnosis (FDD), based on a combined approach of data and process
knowledge driven techniques. The Hidden Markov Model (… area of bearing fault classification. A …

… from vibration signals using long-path … bearings, utilizing GMM and the hidden Markov
model. They employed measures like multi-scale fractal dimension and kurtosis for bearing failure …

… this work presents a novel technique to improve fault recognition rate in time-series condition
… A new bearing fault detection and diagnosis scheme based on hidden Markov modeling of …