Wavelet　decomposition　method　is　used　to　analysis　the　low　voltage　circuit　breaker　mechanical　properties　with　its　vibration　signals.　According　to　the　electric　operating　mechanism　of　low　voltage　circuit　breaker　and　its　closing　action　sequence　relations,　driving　motor　current　signal　as　a　time　stamp　is　applied　to　effectively　extract　closing　vibration　signal.　A　novel　low　voltage　circuit　breaker　closing　synchronous　research　is　proposed　with　wavelet　energy　spectrum　analysis　in　this　paper.　Based　on　refine　decomposition　to　closing　vibration　signal　and　feature　extraction　from　its　main　frequency　band　with　wavelet　packet　reconstruction,　the　feature　vector　of　closing　synchronous　is　constructed.　Three　phases　closing　asynchronous　fault　identification　model　is　established　by　back　propagation　neural　network　with　above　feature　vector.　The　vibration　signals　of　a　DW15-1600　low-voltage　circuit　breaker　under　four　specific　closing　synchronous　status　simultaneities　are　recorded　from　a　single　acceleration　sensor　mounted　on　a　cross　beam　of　breaker　base.　The　simulation　results　show　that　the　combination　method　of　wavelet　packet　energy　spectrum　and　neural　network　can　effectively　analysis　the　closing　synchronism　of　a　low　voltage　circuit　breaker.