Research on the Construction of an Evaluation Index System for Onboard Equipment Status Based on Real-Time Data Analysis

The research explores methods for onboard real-time data analysis and health status assessment, focusing on the working principles and status assessment theory of onboard equipment in the electronic toll collection (ETC) system. By applying AHP, fuzzy comprehensive evaluation method, entropy method, and Delphi method, a practical health status assessment model for onboard equipment has been established, providing an innovative path for dynamic real-time monitoring of onboard devices. The research first constructs an indicator system and assessment model, combining expert scoring with fuzzy judgment to objectively quantify the status of onboard equipment, ultimately resulting in a health status assessment indicator system for the objects under evaluation. During the assessment process, expert scoring is used to determine the subjective weights via AHP, and the combined weights are derived by incorporating objective weights, with instance results showing that the comprehensive weights of various indicators lie between the subjective and objective weights. The research also utilizes the Weibull distribution to simulate the failure rate of onboard equipment, indicating that the failure modes of the onboard devices are closely related to their operational status, providing a theoretical basis for future technological improvements. Through empirical analysis of the assessment model, the research verifies the superiority of the comprehensive weights and emphasizes its new approach in health status assessment of onboard devices, opening up new avenues for research in related fields.