This study investigates data mining techniques useful for the health monitoring of spacecraft, focusing on (1) features derived from telemetry parameter time series; (2) derived parameters from auxiliary data sources; (3) Kernel-­‐density estimate (KDE) based data density change detection; (5) Poincaré plot analysis; (6) command effect analysis