Signal processing methods

Shear Horizontal (SH) waves generated by Electromagnetic Acoustic Transducer (EMAT) have been used for sizing fatigue cracks and machined notches in steels by Time-of-Flight Diffraction (TOED) method. The used EMATs have been Phased Array-Probes and have been operated by State-of-the-art PC based phased array systems. Test and system parameters have been optimised to maximise defect detection and signal processing methods have been applied to improve accuracy in the transit time measurements. 

To restore resolution, we proposed a signal processing method based on Papoulis deconvolution. We implemented this algorithm and tried to operate an improvement from an aluminum rod smaller than the wavelength. 

Using discrimination algorithms, simple signal processing methods can plot response curves such as that shown at the bottom of Figure 9.11. This trace represents the difference in response between the two channels (i.e., the response of the... 

Each signal processing method discussed here involves same function which is either interpolating or smoothing, and is either local or global approximation of the data. This results in the two-way classification of the methods shown in Figure 4.2, where the quadrants of each card list methods of the same family for the particular application. 

Victory, 1993] Victory, C. (1993). Comparison of signal processing methods for passive sonar data. Master s thesis, Department of Electrical Engineering and Computer Science, Naval Post Graduate School. 

The detection and diagnosis tasks can be carried out on the process measurements to obtain critical insights into the performance of not only the process itself but also the automatic control system that is deployed to assure normal operation. Today, the integration of such tasks into the process control software associated with Distributed Control Systems (D-CS) is in progress. The technologies continue to advance, especially in the incorporation of multivariate statistics as well as recent developments in signal processing methods such as wavelets and hidden Markov models. 

Independent Component Analysis (ICA) is a signal processing method for transforming multivariate data into statistically independent components expressed as linear combinations of observed variables [91, 119, 134]. Consider a process with m zero-mean variables x = (xi X2 XmY The... 

Biosensor advancement in the commercial world could also be accelerated by the use of intelligent instrumentation, electronics, and multivariate signal processing methods. Increasing attention must be paid to the engineering of both the basic components and the device as a whole. 

A Novel Bio-inspired Digital Signal Processing Method for Chemical Sensor Arrays... 

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