Dynamic pressure analysis as a tool for determination of sharkskin instability by extrusion of molten polymers

2012 ◽  
Vol 32 (6-7) ◽  
pp. 335-341 ◽  
Author(s):  
Mateusz Barczewski ◽  
Roman Barczewski ◽  
Tomasz Sterzynski
Keyword(s):  
Autocorrelation Function ◽  
Dynamic Pressure ◽  
Pressure Fluctuations ◽  
Extrusion Process ◽  
Processing Technique ◽  
Considerable Effect ◽  
Visual Observation ◽  
Fast Fourier Transformation ◽  
Signal Acquisition ◽  
Signal Processing Technique

Abstract Increasing requirements which extruded polymeric products should accomplish are imposed to quantitatively characterize the factors which have a considerable effect on extrusion stability. Investigation has been realized by means of a rheological measurement device including a single screw extruder, as well as a rheological die, signal acquisition and analysis system. Due to a specially designed measurement track and modern signal processing technique, the separation of cyclic instabilities from received signals (representing the course of melt pressure) and the definition of the influence on the extrusion process were feasible. This paper demonstrates an example of the application of two new methods which facilitate the detection of sharkskin instability, irrespective of visual observation of the extrudate. Autocorrelation function and frequency analysis based on a fast Fourier transformation (FFT) were used as numeric tools applied to register and control the extrusion process. The flow of molten polymer was studied under various processing conditions, giving an opportunity to split high frequency pressure fluctuations by means of the autocorrelation function and fast Fourier transform, and to create, in the future, a catalogue of data which can be used to define particular distortions in technological investigations.

scholarly journals A Remote Sensor System Based on TDLAS Technique for Ammonia Leakage Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2448
Author(s):  
Hongbin Lu ◽  
Chuantao Zheng ◽  
Lei Zhang ◽  
Zhiwei Liu ◽  
Fang Song ◽  
...  
Keyword(s):  
Signal Processing ◽  
Limit Of Detection ◽  
Processing Technique ◽  
Tunable Diode Laser ◽  
Sensor System ◽  
Signal Processing Technique ◽  
Suppression Effect ◽  
Output Wavelength ◽  
Deviation Analysis ◽  
Remote Sensor

The development of an efficient, portable, real-time, and high-precision ammonia (NH3) remote sensor system is of great significance for environmental protection and citizens’ health. We developed a NH3 remote sensor system based on tunable diode laser absorption spectroscopy (TDLAS) technique to measure the NH3 leakage. In order to eliminate the interference of water vapor on NH3 detection, the wavelength-locked wavelength modulation spectroscopy technique was adopted to stabilize the output wavelength of the laser at 6612.7 cm−1, which significantly increased the sampling frequency of the sensor system. To solve the problem in that the light intensity received by the detector keeps changing, the 2f/1f signal processing technique was adopted. The practical application results proved that the 2f/1f signal processing technique had a satisfactory suppression effect on the signal fluctuation caused by distance changing. Using Allan deviation analysis, we determined the stability and limit of detection (LoD). The system could reach a LoD of 16.6 ppm·m at an average time of 2.8 s, and a LoD of 0.5 ppm·m at an optimum averaging time of 778.4 s. Finally, the measurement result of simulated ammonia leakage verified that the ammonia remote sensor system could meet the need for ammonia leakage detection in the industrial production process.

scholarly journals Application of UAV in Search and Rescue Actions in Underground Mine—A Specific Sound Detection in Noisy Acoustic Signal

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3725
Author(s):  
Paweł Zimroz ◽  
Paweł Trybała ◽  
Adam Wróblewski ◽  
Mateusz Góralczyk ◽  
Jarosław Szrek ◽  
...  
Keyword(s):  
Signal Processing ◽  
Acoustic Signal ◽  
Processing Technique ◽  
Underground Mine ◽  
Search And Rescue ◽  
Reference Spectrum ◽  
Signal Processing Technique ◽  
Time Frequency ◽  
Communication Device ◽  
Frequency Representation

The possibility of the application of an unmanned aerial vehicle (UAV) in search and rescue activities in a deep underground mine has been investigated. In the presented case study, a UAV is searching for a lost or injured human who is able to call for help but is not able to move or use any communication device. A UAV capturing acoustic data while flying through underground corridors is used. The acoustic signal is very noisy since during the flight the UAV contributes high-energetic emission. The main goal of the paper is to present an automatic signal processing procedure for detection of a specific sound (supposed to contain voice activity) in presence of heavy, time-varying noise from UAV. The proposed acoustic signal processing technique is based on time-frequency representation and Euclidean distance measurement between reference spectrum (UAV noise only) and captured data. As both the UAV and “injured” person were equipped with synchronized microphones during the experiment, validation has been performed. Two experiments carried out in lab conditions, as well as one in an underground mine, provided very satisfactory results.

EXPRESS: The effect of low frequency equalisation on preference and sensorimotor synchronisation in music

2021 ◽  
pp. 174702182110371
Author(s):  
Scott Beveridge ◽  
Estefanía Cano ◽  
Steffen A. Herff
Keyword(s):  
Body Movement ◽  
Low Frequency ◽  
Empirical Support ◽  
Processing Technique ◽  
Original Version ◽  
Upper Body ◽  
Signal Processing Technique ◽  
Band Energy ◽  
Sensorimotor Synchronisation ◽  
Specific Frequency

Equalisation, a signal processing technique commonly used to shape the sound of music, is defined as the adjustment of the energy in specific frequency components of a signal. In this work we investigate the effects of equalisation on preference and sensorimotor synchronisation in music. Twenty-one participants engaged in a goal-directed upper body movement in synchrony with stimuli equalised in three low-frequency sub-bands (0 - 50 Hz, 50 - 100 Hz, 100 - 200 Hz). To quantify the effect of equalisation, music features including spectral flux, pulse clarity, and beat confidence were extracted from seven differently equalised versions of music tracks - one original and six manipulated versions for each music track. These music tracks were then used in a movement synchronisation task. Bayesian mixed effects models revealed different synchronisation behaviours in response to the three sub-bands considered. Boosting energy in the 100 - 200 Hz sub-band reduced synchronisation performance irrespective of the sub-band energy of the original version. An energy boost in the 0 - 50 Hz band resulted in increased synchronisation performance only when the sub-band energy of the original version was high. An energy boost in the 50 - 100 Hz band increased synchronisation performance only when the sub-band energy of the original version was low. Boosting the energy in any of the three subbands increased preference regardless of the energy of the original version. Our results provide empirical support for the importance of low-frequency information for sensorimotor synchronisation and suggest that the effect of equalisation on preference and synchronisation are largely independent of one another.

scholarly journals Thermal Modulation of a High-Bandwidth Gas Sensor Array in Real-Time for Application on a Mobile Robot

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 858 ◽  
Author(s):  
Timothy A. Vincent ◽  
Yuxin Xing ◽  
Marina Cole ◽  
Julian W. Gardner
Keyword(s):  
Signal Processing ◽  
Mobile Robot ◽  
Real Time ◽  
Low Cost ◽  
Processing Technique ◽  
Signal Processing Technique ◽  
Baseline Drift ◽  
Gas Sensor Array ◽  
Sensor Module ◽  
High Bandwidth

A new signal processing technique has been developed for resistive metal oxide (MOX) gas sensors to enable high-bandwidth measurements and enhanced selectivity at PPM levels (<50 PPM VOCs). An embedded micro-heater is thermally pulsed from 225 to 350 °C, which enables the chemical reactions in the sensor film (e.g., SnO2, WO3, NiO) to be extracted using a fast Fourier transform. Signal processing is performed in real-time using a low-cost microcontroller integrated into a sensor module. The approach enables the remove of baseline drift and is resilient to environmental temperature changes. Bench-top experimental results are presented for 50 to 200 ppm of ethanol and CO, which demonstrate our sensor system can be used within a mobile robot.

Toward a noninvasive subject-specific estimation of abdominal aortic pressure

2008 ◽  
Vol 295 (3) ◽  
pp. H1156-H1164 ◽  
Author(s):  
Carl-Johan Thore ◽  
Jonas Stålhand ◽  
Matts Karlsson
Keyword(s):  
Aortic Pressure ◽  
Processing Technique ◽  
Distributed Model ◽  
Specific Information ◽  
Peripheral Artery ◽  
Tree Model ◽  
Signal Processing Technique ◽  
Arterial Tree ◽  
One Dimensional ◽  
Abdominal Aortic

A method for estimation of central arterial pressure based on linear one-dimensional wave propagation theory is presented in this paper. The equations are applied to a distributed model of the arterial tree, truncated by three-element windkessels. To reflect individual differences in the properties of the arterial trees, we pose a minimization problem from which individual parameters are identified. The idea is to take a measured waveform in a peripheral artery and use it as input to the model. The model subsequently predicts the corresponding waveform in another peripheral artery in which a measurement has also been made, and the arterial tree model is then calibrated in such a way that the computed waveform matches its measured counterpart. For the purpose of validation, invasively recorded abdominal aortic, brachial, and femoral pressures in nine healthy subjects are used. The results show that the proposed method estimates the abdominal aortic pressure wave with good accuracy. The root mean square error (RMSE) of the estimated waveforms was 1.61 ± 0.73 mmHg, whereas the errors in systolic and pulse pressure were 2.32 ± 1.74 and 3.73 ± 2.04 mmHg, respectively. These results are compared with another recently proposed method based on a signal processing technique, and it is shown that our method yields a significantly ( P < 0.01) lower RMSE. With more extensive validation, the method may eventually be used in clinical practice to provide detailed, almost individual, specific information as a valuable basis for decision making.

Identification of the State of a Magneto-Fluidized Bed by Pressure Fluctuations

2006 ◽  
Vol 4 (1) ◽  
Author(s):  
Sachin Dahikar ◽  
Ram Sonolikar
Keyword(s):  
Fluidized Bed ◽  
Autocorrelation Function ◽  
Pressure Fluctuations ◽  
Spectral Density Function ◽  
Functional Relationships ◽  
Power Spectral ◽  
Data Points ◽  
Instantaneous Pressure ◽  
Conventional Signal ◽  
Mutual Information Function

Local instantaneous pressure signals obtained through a magneto-fluidized bed have been analyzed using both classical and advanced signal analysis methods, which can deliver the necessary information about the presence of the bubbling and turbulent flow pattern. The conventional signal processing tool such as autocorrelation and cross correlation were used as preliminary tools to analyze the data. Evaluation of the dominant bubble frequency was completed using the autocorrelation function and power spectral density function. Mutual information function was used to identify the periodicity and the predictability of the local instantaneous pressure signals. Since it does not demand any particular functional relationships between the data points, it is a better method (compared to autocorrelation function) for measuring the predictability of nonlinear systems.

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