Research on health assessment method of information communication system based on cloud model

Traditional failure-based reactive maintenance strategies for information and communication systems present considerable operational risks, as unexpected system failures can lead to critical communication disruptions and severely compromise system support capabilities. To overcome these limitations, this study proposes a cloud model-based health assessment methodology tailored for condition-based maintenance. The approach introduces two key technical innovations. First, a hybrid weighting strategy is developed by integrating the Analytic Hierarchy Process, which captures the relative importance of individual components, with entropy weighting, which reflects the influence of performance parameters. This dual-weighting mechanism effectively accounts for the varying impact of subsystems on overall system health. Second, the methodology incorporates a cloud model transformation, enabling bidirectional conversion between quantitative performance metrics and qualitative health assessments. This feature addresses inherent uncertainties and fuzziness in system evaluation while providing intuitive visual outputs to support informed maintenance decision-making. Simulation results demonstrate that the proposed method offers enhanced performance compared to conventional evaluation approaches, particularly in early fault detection and the prioritization of maintenance tasks.