The　components　in　an　engineering　signal　may　overlap　in　the　frequency　domain,　which　causes　great　inconvenience　and　even　errors　in　traditional　one-dimensional　signal　processing　methods.　To　identify　and　extract　components　in　the　signal　from　the　time-frequency　domain,　this　paper　proposes　a　time-frequency　domain　signal　decomposition　method　based　on　enhanced　seeded　region　growing　(ESRG).　This　paper　extends　the　seeded　region　growing　method　to　adaptive　recognition　of　target　regions　in　the　time-frequency　representation　and　divides　the　time-frequency　representation　into　several　time-frequency　components.　ESRG　can　reduce　the　influence　of　noise,　expand　the　self-adaptability　of　time-frequency　decomposition　and　avoid　errors　caused　by　manually　setting　the　growth　point　and　threshold.　The　results　of　the　numerical　verification　and　decomposition　of　bat　echo　signals　show　that　this　method　can　accurately　decompose　multi-component　non-stationary　signals.　The　decomposition　results　of　rotor　fault　and　rolling　bearing　fault　signals　show　that　this　method　can　be　successfully　applied　to　fault　diagnosis.