scholarly journals Digital Signal Processing–based Dynamic Mass Measurement System for Egg Weighing Process

2017 ◽  
Vol 50 (4) ◽  
pp. 97-102 ◽  
Author(s):  
İsmail Yabanova
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Mass Measurement ◽  
Digital Signal ◽  
Load Cell ◽  
Analog To Digital ◽  
Manufactured Products ◽  
Measurement Signal ◽  
Dynamic Weighing ◽  
To Receive

In this study, an electronic, mechanical and software system, where the weight measurements of eggs can be performed dynamically, is developed. As the speed is an important factor in the production sector, it is of significant importance that the manufactured products be weighed in a rapid and correct manner. For this reason, systems where the products are dynamically weighed are developed. However, as the products are weighed while they are moving in dynamic weighing systems, undesired disturbing effects occur on the measurement signal. The product weights must be measured at required speeds by eliminating this disturbing effect. Dynamic weighing is performed using a load cell. A digital signal processing–based card has been developed to measure the signal received from the load cell and to send it to the computer. The eggs are weighed while they are moving as they roll over the load cell. A program has been developed using the LabVIEW program to receive, filter and analyze the data read and sent to the computer by digital signal processing. In addition, the configuration adjustments of the integrated analog-to-digital converter that reads data from the load cell can also be performed thanks to this program.

scholarly journals TEACHING DELTA-SIGMA SIGNAL CONVERSION IN AN INTERFACING COURSE

2015 ◽  
Author(s):  
Witold Kinsner
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
The Other ◽  
Original Signal ◽  
New Approach ◽  
Analog To Digital ◽  
Signal Conversion ◽  
Delta Sigma ◽  
Low Pass

Conversion of signals is fundamental to theinterfacing of embedded systems. Such signal conversionsinclude (i) analog-to digital (A/D) in order to translate ananalog form of the signal to its sampled and quantized formfor digital signal processing, (ii) digital-to-analog (D/A) inorder to translate the digital samples to a correspondingboxcar signal for further low-pass filtering and recovery ofthe original signal, and (iii) digital-to-digital (D/D) toachieve new desired properties of the data.This paper focuses on teaching the delta-sigma (ΔΣ)A/D conversion that is often omitted from an interfacingcourse because it appears to be a difficult topic tocomprehend and to teach. This new approach links the newΔΣ conversion to the other classes of A/D conversiontechniques explicitly, thus unifying and simplifying theteaching of signal conversions.

Digital Receiving of OQPSK Signals Dedicated for Maritime Mechatronic Systems

2011 ◽  
Vol 180 ◽  
pp. 366-371
Author(s):  
Ryszard Studański
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Wide Spectrum ◽  
Digital Signal ◽  
Mechatronic Systems ◽  
To Receive

In this paper authors present a possible way to receive a narrowband digital signal that was previously registered in a wide spectrum. To begin with a scheme of receiving equipment is shown. Next, the digital signal processing leading to extraction information from narrowband OQPSK signal is described.

The Performance of near Infrared Analysers Can Be Improved by Digital Filtering Techniques

1998 ◽  
Vol 6 (1) ◽  
pp. 97-104 ◽  
Author(s):  
M. Känsäkoski ◽  
O. Voutilainen ◽  
T. Seppänen
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Filters ◽  
Near Infrared ◽  
Matched Filter ◽  
Digital Signal ◽  
Digital Filtering ◽  
Measurement Signal ◽  
On Line ◽  
Filtering Techniques

On-line near infrared (NIR) analysers are used widely for quantitative composition measurements in real-time process control systems. The accuracy and repeatability of the measurements are amongst the most important factors when evaluating the total performance of these analysers, but the lower detection limit is often limited by noise in the measurement signal. There are two major alternatives for reducing noise in an optical analyser: prevention of noise contamination and post-processing of the signal by filtering. In the second alternative, the measurement signal can be post-processed by digital filtering techniques, for example, to enhance the desired signal component. Although digital signal processing (DSP) technology offers many advantages for on-line process measurements, the behaviour of the signal must be understood thoroughly before a successful application of this technology can be developed. A digital filtering technique called matched filter was used in an experimental set-up. The performance of this filter was compared to an analog filtering of a pulse shaped signal. Experimental data were collected and filtered with a novel digital spectrometer which consists of a modulated light source, a spectrograph, a linear array detector and the analog and digital signal processing electronics needed to control and filter the signal. In this case the matched filter gave a clear improvement of 2.2–4.6 dB in the signal-to-noise ratio (SNR) relative to an analog lock-in amplifier. Among the other advantages afforded by digital filters are that they are programmable, easy to design, test and implement on a PC and do not suffer from drift. Also digital filters are extremely stable with respect to both time and temperature and versatile in their ability to process signals in a variety of ways.

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