A multi-resolution filtered-x LMS algorithm based on discrete wavelet transform for active noise control

Qiu, Zhi; Lee, C.-M.; Wang, Chao; Sui, L.N.

doi:10.1016/j.ymssp.2015.05.024

Cited by 50 publications

(23 citation statements)

References 24 publications

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“…Because the original wavelet transform is too complicated, fast discrete wavelet transform methods such as Mallat [33] are proposed. The Mallat algorithm adopts the hierarchical decomposition method.…”

Section: Sleep Biosignals Detection Using Wavelet Analysis Eemd mentioning

confidence: 99%

Detection of Sleep Biosignals Using an Intelligent Mattress Based on Piezoelectric Ceramic Sensors

Peng

Ding

Wang

et al. 2019

Sensors

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Physiological information such as respiratory rate and heart rate in the sleep state can be used to evaluate the health condition of the sleeper. Traditional sleep monitoring systems need body contact and are intrusive, which limits their applicability. Thus, a comfortable sleep biosignals detection system with both high accuracy and low cost is important for health care. In this paper, we design a sleep biosignals detection system based on low-cost piezoelectric ceramic sensors. 18 piezoelectric ceramic sensors are deployed under the mattress to capture the pressure data. The appropriate sensor that captures respiration and heartbeat sensitively is selected by the proposed channel-selection algorithm. Then, we propose a dynamic smoothing algorithm to extract respiratory rate and heart rate using the selected data. The dynamic smoothing can separate heartbeat signals from respiratory signals with low complexity by dynamically choosing the smooth window, and it is suitable for real-time implementation in low-cost embedded systems. For comparison, wavelet analysis and ensemble empirical mode decomposition (EEMD) are performed in a personal computer (PC). Experimental results show that data collected by piezoelectric ceramic sensors can be used for respiratory-rate and heart-rate detection with high accuracy. In addition, the dynamic smoothing can achieve high accuracy close to wavelet analysis and EEMD, while it has much lower complexity.

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Section: Sleep Biosignals Detection Using Wavelet Analysis Eemd mentioning

confidence: 99%

Detection of Sleep Biosignals Using an Intelligent Mattress Based on Piezoelectric Ceramic Sensors

Peng

Ding

Wang

et al. 2019

Sensors

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“…The wavelet transform can be used by a discrete wavelet transform (DWT) [32] or a continuous wavelet transform (CWT) [31]. The aim of this wavelet transform is to decompose the global topographic signal through a series of highpass and low-pass filters to analyze the high and low frequencies [34][35][36][37][38][39]. Since the high frequencies correspond to the micro-roughness and the low frequencies correspond to the waviness, the wavelet transform can quantify the surface morphology at different scale levels.…”

Section: Summary Of the Multiscale Approachmentioning

confidence: 99%

New Multiscale Approach for Machining Analysis of Natural Fiber ReinforcedBio-Composites

Chegdani

Mansori

2018

Journal of Manufacturing Science and Engineering

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. This is an author-deposited version published in: https://sam.ensam.eu Handle ID ABSTRACTNatural fibers are emerging in many industrial sectors to perform eco-friendly materials such as bio-composites. However, machining of natural fiber reinforced polymer (NFRP)composites remains a complex manufacturing process and the machinability of industrial components underlies a specific approach that involves the multiscale structure of natural fibers. This paper presents first a multiscale method used in machinability rating of NFRP.The fundamentals of the multiscale method are hence applied to experimentally assess the machinability of a complete industrial bio-composite part. Results show that machining NFRP composites requires specific analysis scales that are intimately linked to the natural fibrous structure. The multiscale method can be used to improve the experimental design of NFRP machining and, above all, to determine the optimum process parameters that reflect the multiscale machining characteristics of these bio-based materials.

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“…The FxLMS algorithm is one of the most popular algorithms which has been employed in many other active vibration control studies [23][24][25][26]. The FxLMS algorithm control law is utilized for the sake of achieving the high-performance control effect.…”

Section: Fxlms Control Algorithmmentioning

confidence: 99%

A Comparative Study Based on Different Control Algorithms for Suppressing Multistage Gear Transmission System Vibrations

Sun

Zhang

Zhu

et al. 2018

Shock and Vibration

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A modal analysis (MA) was preconsidered to determine a novel active vibration control (AVC) structure of multistage gear transmission system (MGTS) and an appropriate actuating position for the piezoelectric actuator (PZT); the results of the calculating method and the finite element method (FEM) were compared to validate the reliability of MA. The controllers based on different control algorithms were designed to drive the PZTs to output the control force for suppressing the host structure vibrations. To analyze the feasibility of the applied control schemes and discuss the control effects dominated by the different control algorithms, a series of active vibration control numerical simulations were studied. The cosimulation results validate the practicability of the proposed control schemes and provide a forcible guidance for the further experimental works.

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A multi-resolution filtered-x LMS algorithm based on discrete wavelet transform for active noise control

Cited by 50 publications

References 24 publications

Detection of Sleep Biosignals Using an Intelligent Mattress Based on Piezoelectric Ceramic Sensors

Detection of Sleep Biosignals Using an Intelligent Mattress Based on Piezoelectric Ceramic Sensors

New Multiscale Approach for Machining Analysis of Natural Fiber ReinforcedBio-Composites

A Comparative Study Based on Different Control Algorithms for Suppressing Multistage Gear Transmission System Vibrations

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