Ultrasonic Testing (UT) is one of the most important technologies in Non-Detective Testing (NDT) methods. Recently, Barker code and Golay code pairs as coded excitation signals have been applied in ultrasound imaging system with improved quality. However, the signal-to-noise ratio (SNR) of existing UT system based on Barker code or Golay code can be influenced under high high attenuation materials or noisy conditions. In this paper, we apply the convolution of Barker and Golay codes as coded excitation signals for low voltage UT devices that combines the advantages of Barker code and Golay code together. There is no need to change the hardware of UT system in this method. The proposed method has been analyzed theoretically and then in extensive simulations. The experimental results demonstrated that the main lobe level of the code produced by convolution of Barker code and Golay code pairs is much higher than the simple pulse and the main lobe of the combined code is higher than the traditional Barker code, sidelobe is the same as the baker code that constitutes this combined code. So the peak sidelobe level (PSL) of the combined code is lower than the traditional Barker code. Equipped with this, UT devices can be applied in low voltage situations.

Pulsed eddy curent (PEC) technique provides a means to inspect structures without surface contact. It is particularly useful when the structure's surface is rough or inaccessible, such as insulated pipes in pipeline. Probe parameters of a PEC system, especially the sensing and excitation coil diameters, can significantly affect the PEC system's performance. Thus, detailed analysis of these parameters is paramount in developing a PEC system. Currently, this is accomplished by establishing the trend of features with respect to the analyzed variables, e.g. sample thicknesses. However, prior to extracting these features, a number of configuration parameters have to be determined. For this reason, analyzing PEC performance over a range of coil diameter values is rather time-consuming as both the sensing and excitation coil diameters significantly affect the received signals. Principal component analysis (PCA) is proposed as an alternative to the feature extraction. The work here analyzes the trends contributed by the PCA scores for different values of sensing and excitation coil parameters. Results from both numerical simulations and experiments suggest that the sensitivity of the PEC probe is highly correlated with the excitation coil diameter, while the excitation-sensing coil distance is not significant in determining the sensitivity of the PEC probe. These findings are consistent with those reported in the literature, suggesting the potential of adopting PCA for an automated PEC performance analysis process.