Search Results (4)

This paper aims to conduct an acoustic analysis through noise measurements of a hybrid propulsion system intended for implementation on a drone, from which the main noise sources can be identified for further research on noise reduction techniques. Additionally, the noise was characterized by performing spectral analysis and identifying the tonal components that contribute to the overall noise. The propelling force system consists of a micro-turboshaft coupled with a gearbox connected to an electric generator. The propulsion system consists of a micro-turboshaft coupled with a gearbox connected to an electric generator. The electric current produced by the generator powers an electric ducted fan (EDF). The engineturbo-engine was tested in free-field conditions for noise generation at different speeds, and for this, an array of microphones was installed, positioned polarly around the system and near the intake and exhaust. Consequently, based on the test results, the acoustic directivity was plotted, revealing that the highest noise levels are at the front and rear of the engine. The noise level at a distance of 1.5 m from the turboengine exceeds 90 dBA at all tested speeds. Spectral analyses of both the far-field acoustic signals (measured with a polar microphone array) and the near-field signals (microphones positioned near the intake and exhaust) revealed that the primary contributors to the overall noise are the micromotor’s compressor, specifically the gas dynamic phenomena in the fan (BPF and 2× BPF). Thus, it was determined that at the intake level, the main noise contribution comes from the high-frequency components of the compressor, while at the exhaust level, the noise mainly originates from the combustion chamber, characterized by low-frequency components (up to 2 kHz). The findings from this study have practical applications in the design and development of quieter drone propulsion systems. By identifying and targeting the primary noise sources, engineers can implement effective noise reduction strategies, leading to drones that are less disruptive in urban environments and other noise-sensitive areas. This can enhance the acceptance and deployment of drone technology in various sectors, including logistics, surveillance, and environmental monitoring. Full article

The acoustic performance of automotive micro-motors directly impacts the comfort and driving experience of both drivers and passengers. However, various motor production and testing uncertainties can lead to noise fluctuations during operation. Thus, predicting the operational noise range of motors on the production line in advance becomes crucial for timely adjustments to production parameters and process optimization. This paper introduces a prediction model based on a Multi-Branch Channel–Spatial Adaptive Weighting Strategy (MCSAWS). The model includes a multi-branch feature extraction (MFE) network and a channel–spatial attention module (CSAM). It uses the vibration and noise data from micro-motors’ idle operations on the production line as input to efficiently predict the operational noise uncertainty interval of automotive micro-motors. The model employs the VAE-GAN approach for data augmentation (DA) and uses Gammatone filters to emphasize the noise at the commutation frequency of the motor. The model was compared with Convolutional Neural Networks (CNNs) and Multilayer Perceptrons (MLPs). Experimental results demonstrate that the MCSAWS method is superior to conventional methods in prediction accuracy and reliability, confirming the feasibility of the proposed approach. This research can help control noise uncertainty in micro-motors’ production and manufacturing processes in advance. Full article

By leveraging the benefits of a high energy density, miniaturization and integration, acoustic-wave-driven micromotors have recently emerged as powerful tools for microfluidic actuation. In this study, a Lamb-wave-driven micromotor is proposed for the first time. This motor consists of a ring-shaped Lamb wave actuator array with a rotor and a fluid coupling layer in between. On a driving mechanism level, high-frequency Lamb waves of 380 MHz generate strong acoustic streaming effects over an extremely short distance; on a mechanical design level, each Lamb wave actuator incorporates a reflector on one side of the actuator, while an acoustic opening is incorporated on the other side to limit wave energy leakage; and on electrical design level, the electrodes placed on the two sides of the film enhance the capacitance in the vertical direction, which facilitates impedance matching within a smaller area. As a result, the Lamb-wave-driven solution features a much lower driving voltage and a smaller size compared with conventional surface acoustic-wave-driven solutions. For an improved motor performance, actuator array configurations, rotor sizes, and liquid coupling layer thicknesses are examined via simulations and experiments. The results show the micromotor with a rotor with a diameter of 5 mm can achieve a maximum angular velocity of 250 rpm with an input voltage of 6 V. The proposed micromotor is a new prototype for acoustic-wave-driven actuators and demonstrates potential for lab-on-a-chip applications. Full article

Intravenous delivery is the fastest conventional method of delivering drugs to their targets in seconds, whereas intramuscular and subcutaneous injections provide a slower continuous delivery of drugs. In recent years, nanoparticle-based drug-delivery systems have gained considerable attention. During the progression of nanoparticles into the blood, the sound waves generated by the particles create acoustic pressure that affects the movement of nanoparticles. To overcome this issue, the impact of sound pressure levels on the development of nanoparticles was studied herein. In addition, a composite nanostructure was developed using different types of nanoscale substances to overcome the effect of sound pressure levels in the drug-delivery process. The results demonstrate the efficacy of the proposed nanostructure based on a group of different nanoparticles. This study suggests five materials, namely, polyimide, acrylic plastic, Aluminum 3003-H18, Magnesium AZ31B, and polysilicon for the design of the proposed structure. The best results were obtained in the case of the movement of these molecules at lower frequencies. The performance of acrylic plastic is better than other materials; the sound pressure levels reached minimum values at frequencies of 1, 10, 20, and 60 nHz. Furthermore, an experimental setup was designed to validate the proposed idea using advanced biomedical imaging technologies. The experimental results demonstrate the possibilities of detecting, tracking, and evaluating the movement behaviors of nanoparticles. The experimental results also demonstrate that the lowest sound pressure levels were observed at lower frequency levels, thus proving the validity of the proposed computational model assumptions. The outcome of this study will pave the way to understand the interaction behaviors of nanoparticles with the surrounding biological environments, including the sound pressure effect, which could lead to the useof such an effect in facilitating directional and tactic movements of the micro- and nano-motors. Full article