Air Density Measuring Device - Innovative Design, Calibration and Exemplary Results

2020 ◽  
Vol 19 (6) ◽  
pp. 413-419
Author(s):  
Jakub Szymiczek

Air density is a parameter used in numerous applications. Its correct determination can have a key impact on the outcome of an experiment. In calculation of the drag coefficient or pneumatic piping energy loss air density value is crucial for obtaining accurate results. In order to precisely measure this parameter, the electronic air density measuring device was designed and built. The following article presents design, construction, calibration and tests of the mentioned device. The device was designed with a target of reaching set assumptions. It was constructed with open-source programming environment and easily accessible components. Calibration of the device’s sensors was performed in order to ensure high accuracy of results. Calibration of the humidity sensor was performed with use of saturated salt solutions. Exemplary measurement was made to ensure device performance. Created tool provides excellent and cheap fulfillment of the assumptions set in the article.

1995 ◽  
Vol 382 ◽  
Author(s):  
Andrew R.K. Ralston ◽  
Paul E. Thoma ◽  
Carl F. Klein ◽  
Denice D. Denton

ABSTRACTA capacitance relative humidity (RH) sensor is described that has a design, construction, and material composition that result in an inexpensive and robust sensor. This sensor has a multilayer, free-standing film construction. It consists of a humidity sensitive polyimide (PI) dielectric core and conductive layers consisting of carbon filled polysulfone on each side of the polyirnide film to form a capacitor. The polyimide used is a BPDA-ODA type, and replaces a PMDA-ODA type polyimide used in a previous version of this sensor. The BPDA-ODA sensor has a nominal capacitance of 200 pF and a nominal sensitivity of 13% at 100% RH. The characteristics of this humidity sensor are discussed and compared to the characteristics of the PMDA-ODA type sensor. Characteristics considered include the PI film moisture uptake and water vapor transmission, and the sensors' sensitivity to relative humidity, frequency response, and aging at 85°C/85% RH. The dual-state sorption model and free volume calculations are used to demonstrate that observed differences in the film are due to differences in chemical composition between the films.


An electrocardiogram (ECG) can be dependablyused as a measuring device to monitor cardiovascular function. The abnormal heartbeat appears in the ECG pattern and these abnormal signals are called arrhythmias. Classification and automatic arrhythmia signals can provide a faster and more accurate result. Several machine learning approaches have been applied to enhance the accuracy of results and increase the speed and robustness of models. This paper proposes a method based on Time-series Classification using deep Convolutional -LSTM neural networks and Discrete Wavelet Transform to classify 4 different types of Arrhythmia in the MIT-BIH Database. According to the results, the suggested method gives predictions with an average accuracy of 97% without needing to do feature extraction or data augmentation.


2017 ◽  
Vol 5 (2) ◽  
pp. 123-140
Author(s):  
Badhan Saha ◽  
Mazharul Islam ◽  
Abu Torab ◽  
Dewan Hasan Ahmed

Wave energy is the most available energy associated in deep water seas and oceans. Therefore, many attempts have been applied to capture these energies. This paper describes the design, construction and testing of water wave flume. The water wave flume contains an electromechanically driven rotor type wave maker to generate water wave powers. The waves are constructed by different sizes and arrangements of blades which are connected to the rotor. The rotor is driven by an ac motor to generate wave. At the end of the tank a force measuring device is attached opposite to the rotor to measure the thrust of the wave. Experimental results are validated with available literature and wave theory. The results also show that the width of the blade play major role in generating wave sizes including frequency, amplitude and the power. Wider blade displaces much water to generate wave but reduces the blade speed.


1988 ◽  
Vol 31 (1) ◽  
pp. 36-38
Author(s):  
V. T. Neumerzhitskii ◽  
S. P. Toropin ◽  
O. L. Chernikova

2021 ◽  
Author(s):  
Anna S. Kazmina ◽  
Alina V. Rekhovskaya ◽  
Konstantin A. Metsler ◽  
Anton V. Yupashevskiy ◽  
Sergey A. Pilenko

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