Discrete Wavelet Multitone Modulation for ADSL &amp; Equalization Techniques

Baig, Shams Ali; Farrukh, Fasih Ud Din; Mughal, Muhammad Junaid

doi:10.5772/15936

Cited by 1 publication

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Following the decomposition process, the original signal S can be reconstructed in the following manner: 𝑆(𝑡) = 𝑎 1 + 𝑑 1 = (𝑎 2 + 𝑑 2 ) + 𝑑 1 = (𝑎 3 + 𝑑 3 ) + 𝑑 2 + 𝑑 1 (10) or more generally, 𝑆(𝑡) = 𝑎 𝑛 + 𝑑 𝑛 + 𝑑 (𝑛−1) + ⋯ 𝑑 2 + 𝑑 1 (11) There are many types of wavelets, such as Haar, Daubechies, Symlet, etc. Proper selection of the mother wavelet type and the number of decomposition levels is crucial prior to applying the DWT [16].…”

Section: Discrete Wavelet Transformmentioning

confidence: 99%

“…The discrete wavelet transform (DWT) algorithm is well-established in various signal processing research areas because it provides a time-frequency representation for non-stationary time-varying signals [10]. The Discrete Wavelet Transform (DWT) was implemented to solve the resolution problem associated with the Short-Time Fourier Transform (STFT)'s fixed window size.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fault detection in robots based on discrete wavelet transformation and eigenvalue of energy

Ouarhlent,

Terki,

Hamiane

et al. 2023

Diagnostyka

View full text Add to dashboard Cite

This article addresses the problem of fault detection in robot manipulator systems. In the production field, online detection and prevention of unexpected robot stops avoids disruption to the entire manufacturing line. A number of researchers have proposed fault diagnosis architectures for electrical systems such as induction motor, DC motor, etc..., utilising the technique of discrete wavelet transform. The results obtained from the use of this technique in the field of diagnosis are very encouraging. Inspired by previous work, The objective of this paper is to present a methodology that enables accurate fault detection in the actuator of a two-degree of freedom robot arm to avoid system performance degradation. A partial reduction in joint torque constitutes the actuator fault, resulting in a deviation from the desired end-effector motion. The actuator fault detection is carried out by analysing the torques signals using the wavelet transform. The stored energy at each level of the transform contains information which can be used as a fault indicator. A Matlab/Simulink simulation of the manipulator robot demonstrates the effectiveness of the proposed technique.

show abstract

Section: Discrete Wavelet Transformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%