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Traditional sonic crystals (SCs) are based on scatterers or resonators distributed periodically that attenuate sound waves in different bands of frequencies. Recently, we adopted an improved design of SC, namely, the gradient-based sonic crystal (GBSC), designed with a gradient in the geometric parameters using nonuniform resonators and lattices. The finite element (FE) study on the GBSCs indicated that the gradient induces better attenuation than the traditional periodic SCs. This work is an extension of our previous work with experimental and new FE studies on different parameters of the GBSC in an attempt to improve the attenuation of the GBSCs. It was found that the gradient of the geometry enhances the Bragg scattering and resonance in the array, creating a large number of band frequencies. When designed properly by manipulating their gradient, GBSCs were found to target particular frequency bands over other GBSCs of identical filling ratios by coupling the resonant frequencies or the resonant and Bragg frequencies. It was also found that the thickness of the GBSC can be reduced by removing some specific columns from the array without significantly affecting the attenuation by the GBSC. Similarly, it was also found that the relative position of the resonator columns in a GBSC affects the band frequencies, and swapping the columns may also improve the attenuation by the GBSC. [ABSTRACT FROM AUTHOR]

Purpose: It is observed that the motor-running machines that the fluctuation in power supply causes torsional vibration in the rotating systems. Estimation of torque helps in efficient operation of machines with limited sensors. Measurement noise and the effect of exogenous inputs in torque estimation are main problems. Methods: Here, authors have used a Kalman filter-based input estimation technique for indirect estimation of torque variation in a rotating system. Two mathematical models of the rotating system are used in the present work. The estimation becomes unstable when degrees of freedom is more than the number of parameters to be estimated. For such scenario a modified approach, that consists of using a penalty is proposed. Experimental measurements are performed on a drivetrain to verify the proposed technique. Results: Results are presented for different braking torques. It is found that the estimated torque is close to the measured torque. The effect of the penalty on estimation is studied. A stability analysis is performed with different values of penalty values. Finally, a sensitivity analysis is performed to check for the robustness of the algorithm. Conclusions: It is found that the estimated torque converges to the measured torque with a higher penalty value. The estimator is found robust as the estimated torque matches well with the measured torque for different test cases. Sensitivity analysis shows that for more accurate estimation, accuracy of model stiffness is of the essence. [ABSTRACT FROM AUTHOR]

Sonic crystals (SCs) are unique periodic structures designed to attenuate acoustic waves in tunable frequency bands known as bandgaps. Though previous works on conventional uniform SCs show good insertion loss (IL) inside the bandgaps, this work is focused on widening their bandgaps and achieving better IL inside the bandgaps by using a gradient-based sonic crystal (GBSC). The GBSC applies property gradient to the conventional SC array by varying its basic properties, i.e., the distance between the scatterers/resonators (lattice constant), and resonator dimensions between the columns and hence the name GBSC. The design of the GBSC is backed by the results of acoustic beamforming experiments conducted over the uniform SCs of hollow scatterers and Helmholtz resonators (HRs) having two-dimensional (2D) periodicity prepared by using Polyvinyl chloride (PVC) pipes without any property gradient and their respective 2D finite element (FE) studies. The experimental and FE simulation results of the uniform SCs were found to be in good agreement and therefore, the GBSC was modeled and analyzed using FE method considering the viscothermal losses inside the resonators. The results indicated that the property gradient improves both Bragg scattering and Helmholtz resonance compared to that of the uniform SCs and therefore, the GBSC exhibits wider attenuation gaps and higher attenuation levels. An array of 30 microphones was used to conduct acoustic beamforming experiments on the uniform SCs. Beamforming was found to be an advanced and fast method to perform quick measurements on the SCs. [ABSTRACT FROM AUTHOR]

Unbalance is a common machinery fault, which occurs because of uneven distribution of mass of a rotating component about its axis. Vibration-based monitoring techniques have been widely accepted for machinery fault diagnosis. This article presents experimental verification of a recently developed Kalman filter–based method for the identification of unbalance in rotor systems. The method is tested on an experimental test rig for different unbalance configurations and shaft speeds. The proposed technique is a model-based method, which requires a mathematical model of the rotor system along with response measurements. A rigid rotor model is used, and measured accelerations at bearing pedestals are used for unbalance parameter estimation. Bearing stiffnesses are estimated using a frequency domain parameter estimation technique with measured unbalance responses. Sensitivity analysis is also performed by altering the values of these estimated stiffnesses. [ABSTRACT FROM AUTHOR]

Existing engine misfire detection techniques require direct contact with hot vibrating engine component(s). Thus, they need costly sensors and regular maintenance. To overcome this limitation, a novel method is proposed to detect cylinder misfire using sound quality metrics of the radiated sound, measured either near the cylinder block or near the exhaust tailpipe. This method was tested on a four-stroke, four-cylinder spark-ignition engine over a wide range of load torques and speeds. Sound signals were measured near the cylinder block and near the tailpipe. Vibration signals were measured on the cylinder block. Sound quality metrics namely, loudness, roughness, and fluctuation strength of engine and tailpipe sound using a support vector machine classifier correctly predicted misfiring with 94% test accuracy each. Whereas engine vibration statistical features predicted at 82% test accuracy, engine/tailpipe sound pressure level predicted at 85% test accuracy. Thus, sound quality metrics of the radiated sound successfully detect engine misfiring, with higher accuracy than conventional time domain features of sound and vibration signals. The method was shown to be speed and torque independent. Unlike existing techniques, the proposed method makes no direct contact with any engine component, is computationally quick and reliable over wider range of speeds and torques, and can be easily applied to any acoustic sensor placed under-hood, or near tailpipe. [ABSTRACT FROM AUTHOR]

Deterministic techniques are available for force estimation in dynamic systems in time, frequency, and modal domain. But, these techniques are susceptible to measurement noise and require an accurate model of the system, hence, are not suitable for precise force estimation. Some combined deterministic-stochastic approaches are available in the literature for unknown input force estimations, where force estimations are performed by considering the model uncertainty and measurement noise. In the present work, one such technique is extended by incorporating reduced-order model to estimate forces in of plate structures. Kalman filter and a recursive least-squares (KF-RLSE)-based technique which uses displacement and/or velocity measurements for force estimation is used in the present work with a reduced-order model. Time-varying unknown forces acting at single/multiple locations are reconstructed using the measured responses from the plate. Numerical simulation followed by experimental verification is presented. The effect of error in model parameters on the force estimation is presented, and robustness of the input estimation technique is tested for different levels of measurement noise. [ABSTRACT FROM AUTHOR]

In this paper, a study is made to determine the critical dimensions in the design of a family of reactive mufflers which significantly affect the sound quality of the tailpipe radiated noise. The sound quality parameters of the tailpipe noise such as the loudness level, the roughness and the tonality are measured, and a new sound quality metric is developed which can be used as an index to predict the performance of a muffler. The new sound quality metric was based on the evaluations of the synthesized tailpipe noise by a jury consisting of a few undergraduate and postgraduate students at the Indian Institute of Technology Kharagpur. Using the new sound quality metric, the parameters with the most influence on the design of the muffler can be determined. It was found that the length and the open area ratio of a concentric-tube resonator muffler have the highest impact on the tailpipe noise sound quality. [ABSTRACT FROM AUTHOR]

Abstract Today many different natural materials are being effectively used in the acoustics and noise control domain. In this study, the acoustical characterization of three different types of natural jute felt material is performed by an experimental method and by using the Dunn and Davern model, along with an inverse characterization method. There are many empirical models available in the literature which describes the acoustical behavior of specific material accurately, as they are specially developed for that material. In this study, the possibility of using only the air flow resistivity based Delany- Bazley model and the Dunn-Davern model for acoustical performance prediction of jute material is tested. However, these two models do not show good matching with the experimental data throughout the frequency range of interest. Particularly in the low frequency region, the level of mismatch between experimental and model data is high. Therefore the inverse prediction of the coefficients c1 -- c8 in Dunn-Davern model using the particle swarm optimization (PSO) method is conducted, and new coefficients for jute material are found. These new coefficients better predict the acoustical performance of jute felts and reduce the mismatch level in the low-frequency region. [ABSTRACT FROM AUTHOR]