The Experts below are selected from a list of 54282 Experts worldwide ranked by ideXlab platform
S. Grainger - One of the best experts on this subject based on the ideXlab platform.
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rolling element bearing faults diagnosis Based on autocorrelation of optimized Wavelet de noising technique
The International Journal of Advanced Manufacturing Technology, 2009Co-Authors: Khalid F Alraheem, K.p. Ramachandran, David Harrison, S. GraingerAbstract:Machinery failure diagnosis is an important component of the condition Based maintenance (CBM) activities for most engineering systems. Rolling element bearings are the most common cause of rotating machinery failure. The existence of the amplitude modulation and noises in the faulty bearing vibration signal present challenges to effective fault detection method. The Wavelet transform has been widely used in signal de-noising, due to its extraordinary time-frequency representation capability. In this paper, a new technique for rolling element bearing fault diagnosis Based on the autocorrelation of Wavelet de-noised vibration signal is applied. The Wavelet Base function has been derived from the bearing impulse response. To enhance the fault detection process the Wavelet shape parameters (damping factor and center frequency) are optimized Based on kurtosis maximization criteria. The results show the effectiveness of the proposed technique in revealing the bearing fault impulses and its periodicity for both simulated and real rolling bearing vibration signals.
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Detection of the Rolling Element Bearing Faults using Optimized--Wavelet De-Noising Technique.
2006 8th international Conference on Signal Processing, 2006Co-Authors: K.f. Al-raheem, K.p. Ramachandran, D.k. Harrison, S. GraingerAbstract:Rolling bearing fault detection approach using Wavelet de-noising technique Based on optimized Wavelet-Base function derived from the impulse response of the bearing system is proposed. The Wavelet parameters are optimized Based on maximization kurtosis criteria to ensure large similarity with the impulse generated by incipient bearing fault. The results show the effectiveness of the proposed Wavelet de-noising to reveal the impulses produced by faulty bearing and estimate its period.
Wouter Serdijn - One of the best experts on this subject based on the ideXlab platform.
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Nanopower sampled data Wavelet filter design using Switched Gain Cell technique
2009 IEEE International Symposium on Circuits and Systems, 2009Co-Authors: Chutham Sawigun, Michiel Grashuis, Ralf Peeters, Wouter SerdijnAbstract:In order to realize a nano-power Wavelet filter for biomedical applications, this paper applies the singular value decomposition approximation to transform the time domain 1st-derivative of a Gaussian (gauss1) Wavelet Base into a 5th-order z-domain transfer function. Consequently, to realize the approximated transfer function in CMOS technology employing circuitry that operates from a low supply voltage, a sampled data circuit technique, coined dasiaswitched gain cell, (SGC),psila is introduced. Using the SGC technique, standard MOS switches, simple subthreshold (nonlinear) transconductors and their associated parasitic capacitances suffice to constitute the filter, while the scale of the filter can be controlled by the clock frequency. This renders the filter architecture to be simple, modular, and area efficient. Simulation results, using 0.13 mum CMOS model parameters, show that the Wavelet filter implements the gauss1 Wavelet Base well, operates from a 1 V supply and consumes less than 0.47 muW quiescent power.
W.a. Serdijn - One of the best experts on this subject based on the ideXlab platform.
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Ultra low-power analog Morlet Wavelet filter in 0.18 /spl mu/m BiCMOS technology
Proceedings of the 31st European Solid-State Circuits Conference 2005. ESSCIRC 2005., 2005Co-Authors: S.a.p. Haddad, J.m.h. Karel, R.l.m. Peelers, R.l. Westra, W.a. SerdijnAbstract:A novel procedure to implement the Wavelet transform using analog circuitry is presented. First, an approximation is used to calculate the transfer function of the filter, whose impulse response is the required Wavelet. Next, to meet low-power low-voltage requirements, we optimize the state-space description of the filter with respect to dynamic range, sensitivity and sparsity. The filter design that follows is Based on an orthonormal ladder structure and employs log-domain integrators as main building blocks. Measurements demonstrate that it approximates the required Wavelet Base (i.e. Morlet) in an excellent way. The tenth-order log-domain filter operates from a 1.5-V supply voltage and a total bias current of 4.3/spl mu/A.
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Log-domain Wavelet Bases
IEEE Transactions on Circuits and Systems I: Regular Papers, 2005Co-Authors: S.a.p. Haddad, S. Bagga, W.a. SerdijnAbstract:A novel procedure to approximate Wavelet Bases using analog circuitry is presented. First, an approximation is used to calculate the transfer function of the filter, whose impulse response is the required Wavelet. Next, for low-power low-voltage applications, we optimize the state-space description of the filter for dynamic range, sensitivity and sparsity requirements. The filter design that follows is Based on an orthonormal ladder structure with log-domain integrators as the main building blocks. Simulations demonstrate that it approximates the required Wavelet Base (i.e., Morlet) in an excellent way. The circuit operates from a 1.2-V supply voltage and a bias current of 1.2 /spl mu/A.
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Log-domain Wavelet Bases
2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), 2004Co-Authors: S.a.p. Haddad, S. Bagga, W.a. SerdijnAbstract:A procedure to approximate Wavelet Bases using analog circuitry is presented. First, an approximation is introduced to calculate the transfer function of the filter, whose impulse response is the required Wavelet. Next, for low-power low-voltage applications, we optimize dynamic range, minimize sensitivity and fulfil sparsity requirements. The filter design that follows is Based on an orthonormal ladder structure with log-domain integrators as main building blocks. Simulations demonstrate an excellent approximation of the required Wavelet Base (i.e. Morlet). The circuit operates from a 1.2-V supply and a bias current of 1.2/spl mu/A.
Wenshan Zhao - One of the best experts on this subject based on the ideXlab platform.
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Realization of Analog Wavelet Filter Using Hybrid Genetic Algorithm for On-Line Epileptic Event Detection
IEEE Access, 2020Co-Authors: Wenshan Zhao, Yuzhen Zhang, Yigang HeAbstract:As the evolution of traditional electroencephalogram (EEG) monitoring unit for epilepsy diagnosis, wearable ambulatory EEG (WAEEG) system transmits EEG data wirelessly, and can be made miniaturized, discrete and social acceptable. To prolong the battery lifetime, analog Wavelet filter is used for epileptic event detection in WAEEG system to achieve on-line data reduction. For mapping continuous Wavelet transform to analog filter implementation with low-power consumption and high approximation accuracy, this paper proposes a novel approximation method to construct the Wavelet Base in analog domain, in which the approximation process in frequency domain is considered as an optimization problem by building a mathematical model with only one term in the numerator. The hybrid genetic algorithm consisting of genetic algorithm and quasi-Newton method is employed to find the globally optimum solution, taking required stability into account. Experiment results show that the proposed method can give a stable analog Wavelet Base with simple structure and higher approximation accuracy compared with existing method, leading to a better spike detection accuracy. The fourth-order Marr Wavelet filter is designed as an example using Gm-C filter structure Based on LC ladder simulation, whose power consumption is only 33.4 pW at 2.1Hz. Simulation results show that the design method can be used to facilitate low power and small volume implementation of on-line epileptic event detector.
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analog realization of Wavelet Base using afsa
International Conference Telecommunications and Communication Engineering, 2018Co-Authors: Wenshan ZhaoAbstract:This paper proposes a novel approximation method to realize Wavelet Base in analog domain. By means of mathematical model construction, the rational fractional approximation of the Wavelet Base is transformed into an optimization problem. And then, the artificial fish swarm algorithm is used to find the optimal solution. The Morlet Wavelet is taken as an example to illustrate the design process of analog Morlet Wavelet Base. The experimental results show that the constructed analog Wavelet Base has higher approximation accuracy than that derived from the existing approximation method while keeping stable characteristic.
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design of complex Wavelet Base in analog domain
International Conference Telecommunications and Communication Engineering, 2018Co-Authors: Wenshan ZhaoAbstract:This paper proposes a method of pole-shared approximation for complex Wavelet Bases using hybrid genetic algorithm. The approximation process mainly includes the rational fraction approximation of the Gaussian envelope and the Laplace transform of the product of the approximation function and the sine or cosine function. According to the principle of pole-shared approximation, the mathematical approximation model is constructed first. And then, the complex Gabor Wavelet is taken as an example to illustrate the approximation process of Gaussian envelope using hybrid genetic algorithm. The experimental results show that the approximation accuracy of the complex Wavelet Base is relatively high, and the approximation functions of the real part and the imaginary part have the same poles.
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Pole-Shared Realization of Complex Wavelet Base Using AFSA
2018 14th IEEE International Conference on Signal Processing (ICSP), 2018Co-Authors: Wenshan ZhaoAbstract:In this paper, the method for pole-shared approximation of complex Wavelet Bases has been proposed, which mainly involves the rational fraction approximation of Gaussian envelope and the Laplace transform of the product of approximation function and sine or cosine function. To enhance the approximation accuracy of Gaussian envelope, the mathematical approximation model has been constructed, and the Artificial Fish Swarm Algorithm is used for the optimization. Finally, the complex Morlet Wavelet is used as an example in this paper to illustrate the construction and optimization procedure of the approximation model for Gaussian envelope. Experimental results show that the approximation functions of the real and the imaginary part of complex Wavelet Base have the same poles, and also the approximation accuracy for modulus and phase is relatively high.
K.p. Ramachandran - One of the best experts on this subject based on the ideXlab platform.
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rolling element bearing faults diagnosis Based on autocorrelation of optimized Wavelet de noising technique
The International Journal of Advanced Manufacturing Technology, 2009Co-Authors: Khalid F Alraheem, K.p. Ramachandran, David Harrison, S. GraingerAbstract:Machinery failure diagnosis is an important component of the condition Based maintenance (CBM) activities for most engineering systems. Rolling element bearings are the most common cause of rotating machinery failure. The existence of the amplitude modulation and noises in the faulty bearing vibration signal present challenges to effective fault detection method. The Wavelet transform has been widely used in signal de-noising, due to its extraordinary time-frequency representation capability. In this paper, a new technique for rolling element bearing fault diagnosis Based on the autocorrelation of Wavelet de-noised vibration signal is applied. The Wavelet Base function has been derived from the bearing impulse response. To enhance the fault detection process the Wavelet shape parameters (damping factor and center frequency) are optimized Based on kurtosis maximization criteria. The results show the effectiveness of the proposed technique in revealing the bearing fault impulses and its periodicity for both simulated and real rolling bearing vibration signals.
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Detection of the Rolling Element Bearing Faults using Optimized--Wavelet De-Noising Technique.
2006 8th international Conference on Signal Processing, 2006Co-Authors: K.f. Al-raheem, K.p. Ramachandran, D.k. Harrison, S. GraingerAbstract:Rolling bearing fault detection approach using Wavelet de-noising technique Based on optimized Wavelet-Base function derived from the impulse response of the bearing system is proposed. The Wavelet parameters are optimized Based on maximization kurtosis criteria to ensure large similarity with the impulse generated by incipient bearing fault. The results show the effectiveness of the proposed Wavelet de-noising to reveal the impulses produced by faulty bearing and estimate its period.
