## 2 Literature Review
### Reassigned and Synchrosqueezed Wavelet Transform  
[PERSON] et al. [30] introduced the theory and applications of a reassigned wavelet transform as advanced processing of a CWT scalogram. They discussed the drawbacks of the CWT and subsequent shortfall of analytical ability to distinguish abnormal signals clearly. The reassigned wavelet transform method originated from the work of [PERSON] et al. [31], who compared four methods of analysing time-varying signals. They found that the modified moving window method captured more energy content in the signal stream and was able to distinguish changes in time variations. [PERSON] and [PERSON] [32] further developed the reassignment method of wavelet transform, visualizing it as scalograms. The objective of the reassignment is to change the geometrical centre of the window to the gravity centre so that the window can capture more energy content of the input signal. The principle of reassigned wavelet transform is to reassign the resolution window of the wavelet, which is the geometrical centre of the window, to be the gravity centre of the complex energy density distribution. Since a scalogram represents the average energy of the resolution window, the scalogram can only reflect poor energy density information at the geometrical centre. Application of the reassigned scalogram method makes the energy density contained in the reassigned scalogram more closely to the original inspected signal [33]. Furthermore, the better time and frequency concentration in the reassigned scalogram, the more the readability of the CWT scalograms improves [34]. Many algorithms have been introduced to improve the readability and the reliability of the conventional scalogram [23; 35]. These algorithms are being pursued in order to increase the frequency and time resolution in the scalogram. Hence, reassigned wavelet transform has a better ability to distinguish characteristics of patterns in a signal stream. Synchronousqueezed wavelet transform is a special case of reassigned wavelet transform but with added ability to re-construct the time domain data [36]. [PERSON] et al. [37] described synchrosqueezed wavelet transform as a wavelet-based time-frequency reallocation method. It works by decomposing a signal into constituent components with time-varying oscillatory. [PERSON] et al. [38] combined reassigned scalogram with synchrosqueezed scalogram methods to find the incipient fault information of the rolling element bearing. [PERSON] et al. [39] showed that synchrosqueezing had a definite advantage in analysing noisy signals due to its robustness to bounded perturbations. [PERSON] et al. [40] proved that a synchrosqueezed CWT scalogram is more robust in rub detection than discrete Fourier transform (DFT) and fast Fourier transform (FFT). [PERSON] et al. [41] combined warping transform and synchrosqueezed transform to extract modal curves in shallow water waveguide. Synchrosqueezed transform was able to sharpen the frequency resolution, hence enabling more accurate characteristics to be identified. The method was applied to invert sea bottom parameters of a shallow water experiment. [PERSON] et al. [42] applied reassigned wavelet transform to mechanomyograms signals of patients. The reassignment wavelet transform improved resolution and readability of the plot of the scalogram. Subsequently, they were able to increase the sample size with a broader variety of muscular diseases. [PERSON] et al. [43] reviewed synchrosqueezing procedure to identify damping of a vibrating system. They found that a frequency shift error existed due to numerical computation. They proposed three compensation strategies and demonstrated better localisation frequency localisation. [PERSON] et al. [44] compared the effectiveness of synchrosqueezed wavelet with nonlinear squeezing time-frequency transform in the rotor rub-impact fault detection. After analysing different time-frequency analysis (TFA) algorithms, [PERSON] et al.