Enabling Condition Based Maintenance Strategy for Radar Systems – Data Driven Approach

Abstract

Systems of a radar could encounter major failures that lead to a complete stop of functions. There exist warning signs before that event, and with learning algorithms, a developed model can predict that occurrence and give the opportunity to prevent it or to plan maintenance before. The challenge is to understand systems and define rights features in order to create the best predictive model possible with available data.

In this paper, we will address the concept of a condition-based maintenance strategy in the context of an electromechanical system based on a data-driven approach. Technically speaking, we will address the block function presented in Figure 1 and show some promising results regarding anomaly detection (Figure 2).