Algorithm 2. HI construction algorithm.

Input: raw life-cycle data; combine (RMS, Std, Peak) features; Sensitive health features selection. 1. Construct a feature space with 3 features referred to in Table 1 by time-domain, from raw life-cycle data. 2. Reduction of the dimension of 3 features by KPCA. 3. Minimize the weights of each input-sensitive health feature by KPCA. 4. The first Two principal component (1–2) represents the maximum variance direction in the data. 5. Find the sensitive health features by the predetermined termination. 6. Construct the optimal one-dimensional HI. Output: HI; sensitive health features.