Current Issue : October-December Volume : 2022 Issue Number : 4 Articles : 5 Articles
The combination of the new perturbed spiral channel and a slanted gold interfingered transducer (IDT) is designed to achieve precise dynamic separation of target particles (20 μm). The offset micropillar array solves the defect that the high-width flow (avoiding the occurrence of channel blockage) channel cannot realize the focusing of small particles (5 μm, 10 μm). The relationship between the maximum design gap of the micropillar (Smax) and the particle radius (a) is given: Smax = 4a, which not only ensures that small particles will not pass through the micropillar gap, but also is compatible with the appropriate flow rates. A non-offset micropillar array was used to remove 20 μm particles in the corner area. The innovation of a spiral channel structure greatly improves the separation efficiency and purity of the separation chip. The separation chip designed by us achieves deflection separation of 20 μm particles at 24.95–41.58 MHz (κ = 1.09–1.81), at a flow rate of 1.2 mL per hour. When f = 33.7 MHz (κ = 1.47), the transverse migration distance of 20 μm particles is the smallest, and the separation purity and efficiency are as high as 92% and 100%, respectively....
This paper presents the implementation of a measurement system that uses a four microphone array and a data-driven algorithm to estimate depth of cut during end milling operations. The audible range acoustic emission signals captured with the microphones are combined using a spectral subtraction and a blind source separation algorithm to reduce the impact of noise and reverberation. Afterwards, a set of features are extracted from these signals which are finally fed into a nonlinear regression algorithm assisted by machine learning techniques for the contactless monitoring of the milling process. The main advantages of this algorithm lie in relatively simple implementation and good accuracy in its results, which reduce the variance of the current noncontact monitoring systems. To validate this method, the results have been compared with the values obtained with a precision dynamometer and a geometric model algorithm obtaining a mean error of 1% while maintaining an STD below 0.2 mm....
Respiration monitoring is vital for human health assessment. Humidity sensing is a promising way to establish a relationship between human respiration and electrical signal. This paper presents a polyimide‐based film bulk acoustic resonator (PI‐FBAR) humidity sensor operating in resonant frequency and reflection coefficient S11 dual‐parameter with high sensitivity and stability, and it is applied in real‐time human respiration monitoring for the first time. Both these two parameters can be used to sense different breathing conditions, such as normal breathing and deep breathing, and breathing with different rates such as normal breathing, slow breathing, apnea, and fast breathing. Experimental results also indicate that the proposed humidity sensor has potential applications in predicting the fitness of individual and in the medical field for detecting body fluids loss and daily water intake warning. The respiratory rates measured by our proposed PI‐FBAR humidity sensor operating in frequency mode and S11 mode have Pearson correlation of up to 0.975 and 0.982 with that measured by the clinical monitor, respectively. Bland–Altman method analysis results further revealed that both S11 and frequency response are in good agreement with clinical monitor. The proposed sensor combines the advantages of non‐invasiveness, high sensitivity and high stability, and it has great potential in human health monitoring....
In an autonomous underwater vehicles– (AUVs–) based optical-acoustic hybrid network, it is critical to achieve ultra high-speed reliable communications, in order to reap the benefits of the complementary systems and perform high-bandwidth and lowlatency operations. However, as the mobile AUVs operate in harsh oceanic environments, it is essential to design an effective switching algorithm to execute flexible hybrid acoustic-optical communications and increase the network throughput. In this paper, we propose a Q-learning-based adaptive switching scheme to maximize the network throughput by capturing the dynamics of the varying channels as well as the mobility of AUVs. In order to address the challenge associated with partial observations of the optical channel and improve the switching efficiency in extreme conditions, a blind optical channel estimation method is designed and implemented with the Extended Kalman Filter (EKF), in which the relationship between the underwater acoustic and optical channels is utilized to improve the channel prediction accuracy. Based on this environmental status, a reinforcement learning approach is leveraged to build a near-optimal switching strategy for the hybrid network. We conduct numerical simulations to verify the performance of the scheme, and the simulation results demonstrate that the proposed switching scheme is effective and robust....
This paper presents an experimental investigation of acoustic emission (AE) time-frequency characteristics of a water-bearing sandstone specimen in a conventional uniaxial compression test. The main achievements are as follows: (1) The violent fluctuation of AE time domain parameters indicates that the water-bearing sandstone specimen is about to be destroyed. This characteristic provides a theoretical basis for predicting the failure of water-bearing rock in engineering practice. (2) In the elastic phase, the AE b value is the lowest but has a sudden increase after falling into the steady crack propagation phase. In the unsteady crack propagation phase, the AE b value is further increased. This characteristic is of great indicative value for predicting the failure of the water-bearing sandstone specimen. (3) The difference of dominant frequency among the three key points is very small, indicating that the crack initiation and propagation of the water-bearing sandstone specimen has a certain stability in the damage and failure process. But, the two-dimensional frequency spectrum structure of AE waveform signals shows that the closer to failure, the more the number of the frequency spectrum structure peaks. (4) The energy of AE signals is mainly concentrated in the first three frequency bands. The closer to failure, the more the energy proportion of the first three frequency bands is reduced; conversely, the energy proportion of the latter five frequency bands is increased, which leads to more complexity of the failure modes of the water-bearing sandstone specimen....
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