The　physical　parameters　identification　of　structures　is　a　key　topic　in　structural　damage　detection.　Considering　the　problem　of　low　accuracy　and　computation　efficiency　and　insufficient　computation　resources　in　the　physical　parameters　identification　of　structures,　an　improved　parallel　multi-particle　swarm　cooperative　optimization(IPMPSCO)　algorithm　was　proposed.　Based　on　the　apache　spark　cloud　computing　platform,　the　resilient　distributed　datasets(RDD)　was　introduced　to　parallelly　and　distributedly　improve　the　traditional　multi-particle　swarm　cooperative　optimization　(MPSCO)　algorithm　for　the　identification　of　physical　parameters.　In　order　to　verify　the　accuracy　of　the　proposed　method　and　the　ability　to　deal　with　the　huge　number　of　data,　a　30-story　frame　numerical　simulation　and　a　7-story　steel　frame　test　were　conducted　to　identify　the　physical　parameters　on　the　cloud　computing　cluster　of　8　nodes.　The　results　show　that　the　approach　proposed　has　excellent　precision,　stability,　and　fairly　parallel　ability　in　the　computation　efficiency.　©　2018,　Editorial　Office　of　Journal　of　Vibration　and　Shock.　All　right　reserved.