Advantages and Limitations of Using Matrix Pencil Method for the Modal Analysis of Medical Percussion Signals

2013 ◽  
Vol 60 (2) ◽  
pp. 417-426 ◽  
Author(s):  
Moinuddin Bhuiyan ◽  
Eugene V. Malyarenko ◽  
Mircea A. Pantea ◽  
Fedar M. Seviaryn ◽  
Roman Gr. Maev
2021 ◽  
pp. 0309524X2110379
Author(s):  
Yue Wang ◽  
Yonggang Li ◽  
Yinan Yang ◽  
Binyuan Wu ◽  
Qiyu Liu ◽  
...  

This paper presents a gray-box harmonic resonance frequency identification method of multiple-inverter-fed power system, which enables modal analysis oriented to system designers based on only frequency response data provided by diverse vendors or measured by frequency scanning. First, admittance transfer functions of all grid-connected inverters (GCIs) are fitted using Matrix Pencil Method-Vector Fitting (MPM-VF) combined method. Then, node admittance matrix (NAM) is formed according to the topology of whole system. Finally, harmonic resonance frequency along with changes in number of GCIs are identified by NAM-based modal analysis (MA). The proposed gray-box identification method is implemented in a typical multiple-inverter-fed power system. The correctness of harmonic resonance frequency identification results and the effectiveness of the presented method are verified by simulation results obtained in Matlab/Simulink platform and OPAL-RT digital real-time simulation platform. Based on the identification results, a more stable and better power quality multiple-inverter-fed power system can be built by system designers though avoiding the appearance of harmonic sources with corresponding resonance frequency.


Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5065
Author(s):  
Daniel Chaparro-Arce ◽  
Sergio Gutierrez ◽  
Andres Gallego ◽  
Cesar Pedraza ◽  
Felix Vega ◽  
...  

This paper presents a technique, based on the matrix pencil method (MPM), for the compression of underwater acoustic signals produced by boat engines. The compressed signal, represented by its complex resonance expansion, is intended to be sent over a low-bit-rate wireless communication channel. We demonstrate that the method can provide data compression greater than 60%, ensuring a correlation greater than 93% between the reconstructed and the original signal, at a sampling frequency of 2.2 kHz. Once the signal was reconstituted, a localization process was carried out with the time reversal method (TR) using information from four different sensors in a simulation environment. This process sought to achieve the identification of the position of the ship using only passive sensors, considering two different sensor arrangements.


Author(s):  
Sirisak Nongpromma ◽  
Akkarat Boonpoonga ◽  
Prayoot Akkaraekthalin ◽  
Lakkhana Bannawat ◽  
Titipong Lertwiriyaprapa

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