Health Indicator Construction using the Equipment’s Failure Stage Degradation Function

The Health Indicator (HI) is used to monitor equipment conditions. Supervised HI extraction methods assume a general degradation pattern, ensuring robustness. However, existing degradation functions are often designed assuming monotonic degradation without reflecting actual equipment characteristics. When the assumed pattern deviates from reality, the extracted HI may suffer from performance loss. This study aims to enhance HI extraction by identifying failure stages and designing degradation functions that better reflect real degradation patterns. A change point detection algorithm was used to identify failure stages, which were then used to construct the degradation function. The proposed method was validated using real-world data from a Weapon System. Compared to conventional linear and exponential degradation functions, the proposed approach improved HI performance by up to 29.13% in terms of Monotonicity. As the proposed degradation function can be applied to various equipment types, it is expected to enhance HI extraction in practical applications.