This　paper　proposes　a　method　that　uses　adaptive　decision-making　of　wavelet　level　for　detecting　high-voltage　direct　current　(HVDC)　discharge　in　wavelet　transform.　Identification　and　detection　of　HVDC　discharge　are　essential　study　subjects　for　pipeline　safety　and　optimal　operation　of　electrical　power　systems.　This　method　overcomes　the　disadvantage　that　wavelet　packet　transform　needs　to　determine　the　level　in　advance.　The　decomposition　level　of　wavelet　packet　transform　is　controlled　by　calculating　relatively　wavelet　energy　change　to　decide　its　wavelet　level.　Our　proposal　extracts　richer　features　of　HVDC　discharge　by　comparing　other　feature　extraction　algorithms.　The　second　primary　discovery　is　that　a　wavelet-based　application　framework　is　designed　to　detect　the　HVDC　discharge　and　further　protect　the　energy　pipeline.　These　discoveries　have　application　value　in　the　protection　of　power　systems　and　provide　opportunities　and　brighter　perspectives　along　with　valuable　studies　in　the　detection　and　classification　of　time-series　data.