IIR Filter design with Craziness based Particle Swarm Optimization Technique

This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.

Transmit Sub-aperture Optimization in MSTA Ultrasound Imaging Method

The paper presents the optimization problem for the multi-element synthetic transmit aperture method (MSTA) in ultrasound imaging applications. The optimal choice of the transmit aperture size is performed as a trade-off between the lateral resolution, penetration depth and the frame rate. Results of the analysis obtained by a developed optimization algorithm are presented. Maximum penetration depth and the best lateral resolution at given depths are chosen as the optimization criteria. The optimization algorithm was tested using synthetic aperture data of point reflectors simulated by Filed II program for MatlabĀ® for the case of 5MHz 128-element linear transducer array with 0.48 mm pitch are presented. The visualization of experimentally obtained synthetic aperture data of a tissue mimicking phantom and in vitro measurements of the beef liver are also shown. The data were obtained using the SonixTOUCH Research systemequipped with a linear 4MHz 128 element transducerwith 0.3 mm element pitch, 0.28 mm element width and 70% fractional bandwidth was excited by one sine cycle pulse burst of transducer's center frequency.

Drying of Papaya (Carica papaya L.) Using a Microwave-vacuum Dryer

In present work, drying characteristics of fresh papaya (Carica papaya L.) was studied to understand the dehydration process and its behavior. Drying experiments were carried out by a laboratory scaled microwave-vacuum oven. The parameters affecting drying characteristics including operating modes (continuous, pulsed), microwave power (400 and 800 W), and vacuum pressure (20, 30, and 40 cmHg) were investigated. For pulsed mode, two levels of power-off time (60 and 120 s) were used while the power-on time was fixed at 60 s and the vacuum pressure was fixed at 40 cmHg. For both operating modes, the effects of drying conditions on drying time, drying rate, and effective diffusivity were investigated. The results showed high microwave power, high vacuum, and pulsed mode of 60 s-on/60 s-off favored drying rate as shown by the shorten drying time and increased effective diffusivity. The drying characteristics were then described by Page-s model, which showed a good agreement with experimental data.

Acoustic Noise Reduction in Single Phase SRM Drives by Random Switching Technique

It is known that if harmonic spectra are decreased, then acoustic noise also decreased. Hence, this paper deals with a new random switching strategy using DSP TMS320F2812 to decrease the harmonics spectra of single phase switched reluctance motor. The proposed method which combines random turn-on, turn-off angle technique and random pulse width modulation technique is shown. A harmonic spread factor (HSF) is used to evaluate the random modulation scheme. In order to confirm the effectiveness of the new method, the experimental results show that the harmonic intensity of output voltage for the proposed method is better than that for conventional methods.

Anisotropic Constitutive Model and its Application in Simulation of Thermal Shock Wave Propagation for Cylinder Shell Composite

In this paper, a plane-strain orthotropic elasto-plastic dynamic constitutive model is established, and with this constitutive model, the thermal shock wave induced by intense pulsed X-ray radiation in cylinder shell composite is simulated by the finite element code, then the properties of thermal shock wave propagation are discussed. The results show that the thermal shock wave exhibit different shapes under the radiation of soft and hard X-ray, and while the composite is radiated along different principal axes, great differences exist in some aspects, such as attenuation of the peak stress value, spallation and so on.

Multipurpose Three Dimensional Finite Element Procedure for Thermal Analysis in Pulsed Current Gas Tungsten Arc Welding of AZ 31B Magnesium Alloy Sheets

This paper presents the results of a study aimed at establishing the temperature distribution during the welding of magnesium alloy sheets by Pulsed Current Gas Tungsten Arc Welding (PCGTAW) and Constant Current Gas Tungsten Arc Welding (CCGTAW) processes. Pulsing of the GTAW welding current influences the dimensions and solidification rate of the fused zone, it also reduces the weld pool volume hence a narrower bead. In this investigation, the base material considered was 2mm thin AZ 31 B magnesium alloy, which is finding use in aircraft, automobile and high-speed train components. A finite element analysis was carried out using ANSYS, and the results of the FEA were compared with the experimental results. It is evident from this study that the finite element analysis using ANSYS can be effectively used to model PCGTAW process for finding temperature distribution.

A Neural-Network-Based Fault Diagnosis Approach for Analog Circuits by Using Wavelet Transformation and Fractal Dimension as a Preprocessor

This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with [1] and [6], which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.

Multi-stage Directional Median Filter

Median filter is widely used to remove impulse noise without blurring sharp edges. However, when noise level increased, or with thin edges, median filter may work poorly. This paper proposes a new filter, which will detect edges along four possible directions, and then replace noise corrupted pixel with estimated noise-free edge median value. Simulations show that the proposed multi-stage directional median filter can provide excellent performance of suppressing impulse noise in all situations.