Digital Signal Processing for ultrasonic Testing INTRODUCTION DSP techniques have been proven successful in radar, aeronautics, communications, acoustics, seismology, speech/image restoration and recognition, energy generation/distribution systems, and financial prediction. This is inspite of the fact that compared to analog signal processing systems, digital systems have the following advantages: 1. Greater Signal Transmission Fidelity 2. Large Non-volatile Storage capabilities 3. Processing/calculation/classification capabilities and 4. More sophisticated filtering and signal analysis methods

2. DIGITAL SIGNALS AND SYSTEMS 2.1 General Architechture And Methods A DSP-based UNDE (ultrasonic non-destructive evaluation)system will have many components shared by its analog counterpart, as shown in below figure.

It will have an ultrasonic pulser, a receiver and several piezo-electric transducers (PZTs) situated near or coupled to the part or material under test. Because a DSP-based system is under some kind of CPU control, it inherently has the ability to automate several test functions, in addition to its DSP capabilities that would include filtering, signal conditioning, and signal classification. The continuously varying received analog output, x(t), is sampled to create a discrete digital sequence, x[n], that is sent to the digital signal processor for manipulation. DSP-specific chips used for these various signal conditioning and classification functions are either fixed or floating-point processor. However, because we are dealing with discrete time samples, care must still be taken when converting from the analog, x(t), to the digital, x[n], domain.

2.3 Digitizing Signal Amplitude A continuous time analog signal xa(t) has to be converted into a sequence of discrete time signals. x[n] = xa(nT) The sampling frequency, WS = (1/T), has to be greater than the bandwidth WN of the signal being sampled. According to the Nyquist Sampling Theorem, for a correct representation of a digitized signal, the sampling frequency WS has to be at least twice as high as the bandwidth WN. WS = 2p/T > WN The A/D converter in Figure 1 performs the initial amplitude discretization for the input analog ultrasonic signal prior to further conversion needed during processing by either a fixed or floating-point signal processor.

3. DIGITAL FILTERS Digital filters can be designed for precise purposes and are not restricted by the availability and characteristics of hardware components. Two classes of such filters, Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) filters, is possible-the latter being selected most often for ultrasonic testing. Averaging the ultrasonic signal is a common method of enhancing the signal-to-noise (S/N) ratio. This method slows down data acquisition, because the pulse repetition rate of ultrasonic instruments is orders of magnitudes slower than the processing time needed to perform averaging. In addition, the efficiency of averaging is limited and the method can be insufficient, as demonstrated in the following example. Figure 5 illustrates the pulse-echo signal from a 4 MHz transducer applied to a 200-mm thick steel plate. All spikes represent noise.

Filterd signal (using FIR filtered) Unfiltered signal Averaging in resulted in a lowering of the amplitude from 100% to 60 and 30 %. The 1.5-mm flat bottom hole present in the specimen does not show up as a signal. The power of a correlation FIR filter for 4 MHz is demonstrated on the same set-up as used. Averaging did not lower the amplitudes from these signals, but it did reduce the noise between them.

This demonstrates the possibility of detecting flaws in steel of at least 1m thickness using the FIR filter. 6. SUMMARY Whether the application is a general purpose NDE situation, as depicted in Figures 5 through 8, or a very product-specific test scenario, as illustrated above in Figure 9, none of these would have been possible without the use of highly sophisticated DSP algorithms. DSP is the enabling technology furthering NDE science in the new millennium.

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