Optimization　techniques　have　been　applied　to　structural　health　monitoring　and　damage　detection　of　civil　infrastructures　for　two　decades.　The　standard　particle　swarm　optimization　(PSO)　is　easy　to　fall　into　the　local　optimum　and　such　deficiency　also　exists　in　the　multiparticle　swarm　coevolution　optimization　(MPSCO).　This　paper　presents　an　improved　MPSCO　algorithm　(IMPSCO)　firstly　and　then　integrates　it　with　Newmark＇s　algorithm　to　localize　and　quantify　the　structural　damage　by　using　the　damage　threshold　proposed.　To　validate　the　proposed　method,　a　numerical　simulation　and　an　experimental　study　of　a　seven-story　steel　frame　were　employed　finally,　and　a　comparison　was　made　between　the　proposed　method　and　the　genetic　algorithm　(GA).　The　results　show　threefold:　(1)　the　proposed　method　not　only　is　capable　of　localization　and　quantification　of　damage,　but　also　has　good　noise-tolerance;　(2)　the　damage　location　can　be　accurately　detected　using　the　damage　threshold　proposed　in　this　paper;　and　(3)　compared　with　the　GA,　the　IMPSCO　algorithm　is　more　efficient　and　accurate　for　damage　detection　problems　in　general.　This　implies　that　the　proposed　method　is　applicable　and　effective　in　the　community　of　damage　detection　and　structural　health　monitoring.