Design of ultrasonic imaging system is presented. System has a modular structure with main acquisition and front end electronics separated in order to have minimal path for host PC connectivity and shortest path to ultrasonic transducer. Such acquisition modules placement allows reducing the induced EMI and increasing the flexibility of the system. Positioning module is also separate and allows various scanning equipment configurations. Evaluation of excitation and reception electronics parameters is presented. Essential measurement procedures outlined. Signal digitization parameters (sampling frequency, clock jitter and quantisation) were chosen to balance time of flight estimation random errors versus interpolation bias errors.

In this paper the performance of Split-Spectrum Processing algorithms combined with Spread Spectrum excitation for ultrasonic imaging of new composites were analyzed. Glass and carbon fiber reinforced plastic produced by Resin Transfer Molding (RTM) were the analyzed specimens. These materials are strongly affected by structural noise since air bubbles were trapped during RTM process and interlayer gaps were resent in prepreg technology. For such sort of materials, classic criterions for the parameters of Split-Spectrum algorithms are not feasible and should be revised. Furthermore, as attenuation is highly frequency dependent for these materials, Spread Spectrum and Frequency Selective Loss Compensation techniques were used in order to increase the energy and equalize the received signal. Flaw-to-Clutter Ratio Gain, Signal-to-Noise Ratio Gain and Receiver Operating Characteristics were selected as the figures of merit to make the comparisons, and resulting 3D images of the composites are given.

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Ultrasonic imaging of composites was investigated. Glass and carbon fiber reinforced plastic produced by resin transfer molding and prepreg forming were analyzed. In some of the samples air bubbles were trapped during RTM (resin transfer molding) process and interlayer gaps were present in prepreg technology samples. One of the most expected techniques to apply in such case is the Split Spectrum processing. On the other hand such signals require specific processing to reliably reconstruct the temporal position of the defect reflection. Correlation processing can be used for signal compression or Wiener filtering can be applied for spectral content equalisation. Pulse signals are simple to generate, but lack the possibility to alter the signal's spectrum shape. Spread spectrum signals offer a powerful tool for signal energy over frequency band increase and resolution enhancement. CW (continuous wave) burst has high energy but lacks the bandwidth needed for SSP (spread spectrum processing). The aim of the investigation was to compare the performance of the above signals in case of composite imaging, when various Split Spectrum Processing techniques are used with preceding Wiener processing for spectral content compensation. Resulting composite signals and images obtained are presented. Structural noise removal performance was evaluated as Receiver Operating Characteristics (ROC).

A field-programmable-gate-array based time digitizer for the time-of-flight mass spectrometry Rev. Sci. Instrum. 85, 045115 (2014); 10.1063/1.4870922 Digital implementation of linear gammatone filters: Comparison of design methods ARLO 4, 59 (2003);Abstract. Analysis of the time of flight estimation performance when signal digitization is used is presented. The crosscorrelation function peak position was used as time-of-flight estimator. In order to cope with the discrete nature of the cross-correlation the time of flight subsample estimates used interpolation techniques: parabolic peak, derivative's zero crossing, zero crossing of imaginary of Hilbert transform, double zero crossing and frequency domain phase. Noise density component of the Cramer-Rao lower error bound was modified to include the jittering and quantization noise. Basing the real amplifier noise density theoretical analysis concluded that taking the 180 nV/Hz as lowest noise density at ADC input, 10 bit is needed for 100 MHz sampling. Numerical experiments have been conducted using Matlab to investigate the standard deviation of ToF in presence of additive white Gaussian noise and signal's digitization. It has been concluded that systematic errors are related to subsample interpolation and are in cubic relation to sampling frequency and in inverse quadratic relation to carrier. Random errors are in opposite relation: little influence by sampling frequency and direct proportion to carrier frequency. Investigation on the digital filtering influence revealed that digital filtering does not improve the time-of-flight estimation accuracy.

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