Resistive-open defects in Static Random Access Memories (SRAMs) represent an important challenge for manufacturing test in submicron technologies as they may be masked by process variations, which in turn increases the number of test escapes. This paper evaluates the effectiveness of a hardware-based test approach that compares the current consumption of neighboring SRAM cells to detect resistive-open defects. The proposed approach is validated and its fault detection capabilities are analyzed for different defect sizes and taking into account process variations effects. Finally, the paper provides an evaluation of the minimum detectable resistive-open defect size for the proposed hardware-based approach under process variations effects. 相似文献
In the present paper, experimental and numerical investigations of the flow around different types and sizes of anemometers are presented and discussed.The measurements of the flow field at different distances upstream of the anemometer are performed with a laser Doppler Anemometer. The computational results are in good agreement with the experimental ones since the observed deviations are of the same order of magnitude. These results show that anemometers may induce a strong distortion of the velocity field, even far upstream of the anemometer. This distortion has to be taken into account in the anemometer calibration field to yield reliable and consistent measurements. 相似文献
Empirical wavelet transform (EWT) based on the scale space method has been widely used in rolling bearing fault diagnosis. However, using the scale space method to divide the frequency band, the redundant components can easily be separated, causing the band to rupture and making it difficult to extract rolling bearing fault characteristic frequency effectively. This paper develops a method for optimizing the frequency band region based on the frequency domain feature parameter set. The frequency domain feature parameter set includes two characteristic parameters: mean and variance. After adaptively dividing the frequency band by the scale space method, the mean and variance of each band are calculated. Sub-bands with mean and variance less than the main frequency band are combined with surrounding bands for subsequent analysis. An adaptive empirical wavelet filter on each frequency band is established to obtain the corresponding empirical mode. The margin factor sensitive to the shock pulse signal is introduced into the screening of empirical modes. The empirical mode with the largest margin factor is selected to envelope spectrum analysis. Simulation and experiment data show this method avoids over-segmentation and redundancy and can extract the fault characteristic frequency easier compared with only scale space methods.