From the vibration analysis generated by biological and mechanical systems, it is possible to determine whether there has been a fundamental change in their time or frequency domain. This analysis can provide information about the internal state of the system and its dynamics without the need for invasive intervention. In addition, the measured data can be used together with advanced signal processing algorithms (neural networks or machine learning) to create a predictive maintenance and diagnostic system. According to the measured data diagnostics, it will be possible to identify a defective component (e.g. a damaged bearing, loose part or worn belt), replace it and prevent possible system failure. This work describes a modular measuring device based on closed acoustic tube. Acoustic tube parameters are measured and optimized for use in remote monitoring, which is part of a project dealing with measurement of vital signs in magnetic resonance.
In this paper, a performance study of VLC communication channel impaired by rain, is presented. Our solution is based on software defined radio (SDR), LabVIEW and commercially available LED car taillights. This work focuses on performance testing of multistate QAM modulation formats throughout variable rain intensity and its influence on basic communication parameters (EVM, BER, transmit speed). This work will present our testing prototype, measured parameters and possible weak spots, which will be adjusted in future iterations.
In this paper, the impact of fog on performance of VLC communication is explored. Highly modular testing system is based on LabVIEW software, modified National Instruments software defined radios (SDR) and commercially available LED car taillights. This work focuses on performance testing of multistate QAM modulations formats impaired by fog. An optional reference laser is used to monitor fog density throughout the whole measurement. This paper will present our testing solution and measured parameters.
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