This　article　presents　a　new　method　for　effective　detection　of　ac　series　arc　fault　(AF)　(SAF)　and　extraction　of　SAF　characteristics　in　residential　buildings,　which　addresses　the　challenges　with　conventional　current　detection　methods　in　discriminating　arcing　and　nonarcing　current　due　to　their　similarity.　Different　from　the　traditional　method,　in　the　proposed　method,　the　differential　magnetic　flux　is　coupled　to　obtain　highfrequency　signals　by　putting　the　live　line　and　the　neutral　line　through　the　current　transformer,　which　can　effectively　solve　the　problem　of　SAF　features　disappearing　in　the　trunk-line　current.　However,　similar　to　the　traditional　method,　the　effectiveness　of　the　proposed　coupling　method　could　also　be　compromised　when　being　used　in　cases　with　dimmer　load　and　load　starting　process.　This　is　found　to　be　caused　by　the　presence　of　high-amplitude　pulse　phenomenon　in　the　nonarcing　signals　in　these　scenarios,　which　are　incorrectly　detected　as　arcing　signals　in　other　loads.　To　address　this　issue,　a　short-observation-window　singular　value　decomposition　and　reconstruction　algorithm　(SOW-SVDR)　is　used　to　enhance　the　capability　to　identify　SAFs　by　the　coupling　method.　The　proposed　method　has　been　implemented　and　validated　according　to　the　UL1699　standard　with　different　types　of　loads　connected　to　the　system　and　also　tested　under　their　starting　processes.　The　experimental　results　show　that　the　proposed　approach　is　more　effective　in　detecting　AFs　compared　with　existing　methods.