Expandable Platform for Dynamic Signal Analysis

1989 ◽  
Vol 61 (12) ◽  
pp. 16-17
Keyword(s):  
Signal Analysis ◽  
Dynamic Signal

Dynamic Signal Analysis of Two Walking Persons in Intra-body Communication

2019 ◽  
Author(s):  
Rikuma Ashizawa ◽  
Hiroki Tada ◽  
Sotaro Sawa ◽  
Mitsuru Shinagawa ◽  
Kyoji Oohashi ◽  
...  
Keyword(s):  
Signal Analysis ◽  
Dynamic Signal

scholarly journals Dynamic signal analysis for speed-varying machinery: A review

2015 ◽  
Vol 45 (7) ◽  
pp. 669-686 ◽  
Author(s):  
Ming ZHAO ◽  
Jing LIN
Keyword(s):  
Signal Analysis ◽  
Dynamic Signal

scholarly journals Accuracy of the dynamic signal analysis approach in respiratory mechanics during noninvasive pressure support ventilation: a bench study

2021 ◽  
Vol 49 (2) ◽  
pp. 030006052199218
Author(s):  
Yuqing Chen ◽  
Yueyang Yuan ◽  
Hai Zhang ◽  
Feng Li ◽  
Xin Zhou
Keyword(s):  
Pressure Support Ventilation ◽  
Signal Analysis ◽  
Airway Pressure ◽  
Pressure Support ◽  
Respiratory Mechanics ◽  
Assisted Ventilation ◽  
Support Ventilation ◽  
Expiratory Resistance ◽  
Ventilator Performance ◽  
Dynamic Signal

Objective To evaluate the accuracy of respiratory mechanics using dynamic signal analysis during noninvasive pressure support ventilation (PSV). Methods A Respironics V60 ventilator was connected to an active lung simulator to model normal, restrictive, obstructive, and mixed obstructive and restrictive profiles. The PSV was adjusted to maintain tidal volumes (VT) that achieved 5.0, 7.0, and 10.0 mL/kg body weight, and the positive end-expiration pressure (PEEP) was set to 5 cmH2O. Ventilator performance was evaluated by measuring the flow, airway pressure, and volume. The system compliance (Crs) and airway resistance (inspiratory and expiratory resistance, Rinsp and Rexp, respectively) were calculated. Results Under active breathing conditions, the Crs was overestimated in the normal and restrictive models, and it decreased with an increasing pressure support (PS) level. The Rinsp calculated error was approximately 10% at 10.0 mL/kg of VT, and similar results were obtained for the calculated Rexp at 7.0 mL/kg of VT. Conclusion Using dynamic signal analysis, appropriate tidal volume was beneficial for Rrs, especially for estimating Rexp during assisted ventilation. The Crs measurement was also relatively accurate in obstructive conditions.

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Diagnostic System of Gravitational Solid Flow Based on Weight and Accelerometer Signal Analysis Using Wireless Data Transmission Technology

2012 ◽  
Vol 17 (4) ◽  
pp. 319-326 ◽  
Author(s):  
Zbigniew Chaniecki ◽  
Krzysztof Grudzień ◽  
Tomasz Jaworski ◽  
Grzegorz Rybak ◽  
Andrzej Romanowski ◽  
...  
Keyword(s):  
Signal Analysis ◽  
Scale Up ◽  
Three Dimensional ◽  
Diagnostic System ◽  
Wireless Data ◽  
Stick Slip ◽  
Wireless Data Transmission ◽  
Accelerometer Signal ◽  
Flow Investigation ◽  
Material Information

Abstract The paper presents results of the scale-up silo flow investigation in based on accelerometer signal analysis and Wi-Fi transmission, performed in distributed laboratory environment. Prepared, by the authors, a set of 8 accelerometers allows to measure a three-dimensional acceleration vector. The accelerometers were located outside silo, on its perimeter. The accelerometers signal changes allowed to analyze dynamic behavior of solid (vibrations/pulsations) at silo wall during discharging process. These dynamic effects are caused by stick-slip friction between the wall and the granular material. Information about the material pulsations and vibrations is crucial for monitoring the interaction between silo construction and particle during flow. Additionally such spatial position of accelerometers sensor allowed to collect information about nonsymmetrical flow inside silo.

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