The reality is that PHM is mostly a matter of the analytic method and process of building tailored and hybrid functional DSS to meet various requirements in field of maintenance and logistics support, not only creating models and algorithms in black box which is philosophical basis of so many PHM universal platforms, especially in the concept and design stage of systems. Some issues under discussions are presented firstly. Then, the critical cases analysis method is described, and the demonstration on the different level of specialized vehicle health management system is shown as human-computer interfaces. Lastly, the preliminary design approach to implement PHM system is presented. In addition, potential difficult points in practice are investigated for R&D of PHM.

This paper mainly studies the recognition issue of blurred alphabet images. If alphabets in an image is blurred, it is difficult t be recognized. To avoid the defect, the paper proposes a computer recognition method for blurred alphabet images based on grayscale class variance algorithm. The algorithm executes non-linear transformation on feature parameters of alphabets images extracted to obtain eigenvector coefficient weights, and then calculates characteristic correlation coefficient through wavelet transform to realize the blurred alphabet recognition. Experiments show that, the proposed method improves the accuracy of the blurred alphabets recognition and achieves satisfactory results.