On-Line Fuel Identification Using Digital Signal Processing and Fuzzy Inference Techniques

2004 ◽  
Vol 53 (4) ◽  
pp. 1316-1320 ◽  
Author(s):  
L. Xu ◽  
Y. Yan ◽  
S. Cornwell ◽  
G. Riley
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Fuzzy Inference ◽  
Digital Signal ◽  
On Line ◽  
Inference Techniques

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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