Showing papers on "Signal-to-noise ratio published in 2022"

An Improvement of SNR for Simultaneous Wireless Power and Data Transfer System With Full-Duplex Communication Mode

Abstract: The power interference is always inevitable in the simultaneous wireless power and data transfer (SWPDT) system resulting in the lower signal to noise rate (SNR) and may cause the failure of communication. Besides, the interference between bidirectional data source is also the problem during the full-duplex communication. To solve these problems, in this article, an improvement of SNR for SWPDT system with full-duplex communication mode is proposed. In the power transfer channel, the double-sided LCCL compensation topology is selected due to its good performance of blocking the power interference on data transmission. Besides, the constant current characteristic of primary coil could guarantee the stability of power transmission. In the data transfer channel, a novel data transmission based on the dual-resonant structure is proposed to suppress the ipsilateral interference, and the full-duplex communication is achieved by two different frequencies. An optimization method of power and data transfer channel to improve SNR further is proposed after the analysis on interferences of power transmission and ipsilateral data source. Finally, the feasibility of proposed topology and the correctness of the parameter design method are verified by the simulation and experimental results.

Intelligent denoise laser ultrasonic imaging for inspection of selective laser melting components with rough surface

Abstract: The random microdefects are inevitable during the Selective laser melting (SLM) process due to the principle of discrete-stacking. The rough surface induced strong background noise reduces the probability of detection of traditional laser ultrasonic testing system. In this study, an intelligent denoise laser ultrasonic imaging method was developed to inspect the micro defects on the rough surface of SLM components: (1) a non-contact laser ultrasonic scanning setup was established for data acquisition of multiple ultrasonic signals; (2) a denoising algorithm based on unsupervised machine learning was designed and trained by abundant ultrasonic data to enhance the signal to noise ratio (SNR); (3) a signal matching algorithm based on the cross-correlation and self-normalized method was established to match the amplitude and arrival time of Rayleigh waves from different scanning points. The performance of developed method was verified using micro hole defects on the rough surface of a SLM part. The results indicated that the established denoising algorithm could increase the average SNR from 27.0 dB to 35.2 dB. All holes with diameter of 50 μm and 100 μm can be detected and sized based on the high SNR image without removing the rough surface. The conclusion can be drawn that the proposed intelligent denoise laser ultrasonic imaging method is a very potential way for the online inspection of SLM.

DBA-Filter: A Dynamic Background Activity Noise Filtering Algorithm for Event Cameras

Abstract: Newly emerged dynamic vision sensors (DVS) offer a great potential over traditional sensors (e.g. CMOS) since they have a high temporal resolution in the order of \(\mu s\), ultra-low power consumption and high dynamic range up to 140 dB compared to 60 dB in frame cameras. Unlike traditional cameras, the output of DVS cameras is a stream of events that encodes the location of the pixel, time, and polarity of the brightness change. An event is triggered when the change of brightness, i.e. log intensity, of a pixel exceeds a certain threshold. The output of event cameras often contains a significant amount of noise (outlier events) alongside the signal (inlier events). The main cause of that is transistor switch leakage and noise. This paper presents a dynamic background activity filtering, called DBA-filter, for event cameras based on an adaptation of the K-nearest neighbor (KNN) algorithm and the optical flow. Results show that the proposed algorithm is able to achieve a high signal to noise ratio up to 13.64 dB.

A Preprocessing Techniques for Seismocardiogram Signals in Removing Artifacts

Abstract: Seismocardiogram (SCG) is a non-invasive technique for cardiomechanical assessment by analyzing local vibrations on chest surface. SCG signals have numerous clinical and health awareness applications. The SCG signals utilized in this work are obtained from public domain database which are acquired by standard signal acquisition protocol. The acquired SCG signal includes artifacts such as base line wander, random noise, and predictive power line interference. The artifact-free signal helps significantly in analyzing them either in time scale or in frequency domain. In this work, an attempt has been made to remove motion-induced noises and the low frequency noise including respiratory sounds. The artifact removal methods include moving average and median filter and finite impulse response-based smoothing filter named Savitzky Golay filter. The performance of all these methods is compared using the denoising metrics such as mean square error, mean absolute error, signal to noise ratio, peak signal to noise ratio. Results demonstrate that median filter along with Butterworth filter performs better in removing the motion-induced artifact and low frequency and respiratory sounds. The methodology used in this work is helpful further for further annotation of the signals.

Quality Assisted Spectrum Allocation in Cognitive NOMA Networks

Abstract: Future communications are developed with new communication standards for multi access technologies, where spectrum sharing and Non-orthogonal multiple access (NOMA) are the two latest approaches. To transfer the data from one end to another end through this wireless communication medium interference take place, which affects the total system performance. To minimize the interference in these communications the efficient spectrum sharing technique was developed. Cooperative relaying in NOMA system with spectrum sharing using threshold modeling were proposed in past. To improve the resource allocation in NOMA with cooperative relaying, instantaneous signal to noise ratio were used in obtaining higher outage throughput in a spectrum sharing cognitive radio-NOMA (CR-NOMA) system. In the previous methods constant thresholding is considered in the energy detection model and the quality of signaling is not observed, which results in lower throughput. In this work, a Quality Assisted Spectrum Allocation (QASA) based on loss probability is proposed and a dynamic threshold modeling is suggested for spectrum sensing under dynamic channel condition. Here the Rayleigh and Rician fading models are considered and used the Lagrange mathematical concept to calculate the bit error and to minimize the distortion. The throughput of the proposed work performs well when compared with the conventional method of Simultaneous wireless information and power transfer (SWIPT).