Relay　protection　equipment　is　important　to　ensure　the　safe　and　stable　operation　of　power　systems.　The　risks　should　be　evaluated,　which　are　caused　by　the　failure　of　relay　protection.　At　present,　the　fault　data　and　the　fault　status　monitoring　information　are　used　to　evaluate　the　failure　risks　of　relay　protection.　However,　there　is　a　lack　of　attention　to　the　information　value　of　monitoring　information　in　the　normal　operation　condition.　In　order　to　comprehensively　improve　monitoring　information　accuracy　and　reduce,　a　generalized　proportional　hazard　model　(GPHM)　is　established　to　fully　exploit　the　whole　monitoring　condition　information　during　the　whole　operation　process,　not　just　the　monitoring　fault　condition　data,　with　the　maximum　likelihood　estimation　(MLE)　used　to　estimate　the　parameters　of　the　GPHM.　For　solving　the　nonlinear　equation　in　the　process　of　parameter　estimations,　the　adaptive　homotopy　algorithm　is　adopted,　which　could　ensure　the　reversibility　of　the　Jacobi　matrix.　Three　testing　cases　have　been　reviewed,　to　demonstrate　that　the　adaptive　homotopy　algorithm　is　better　than　traditional　algorithms,　such　as　the　Newton　homotopy　algorithm,　regarding　the　calculation　speed　and　convergence.　Therefore,　GPHM　could　not　only　reflect　the　real　time　state　of　the　equipment,　but　also　provide　a　sound　theoretical　basis　for　the　selection　of　equipment　maintenance　types.