Long-distance　high-pressure　oil　and　gas　pipelines　are　threated　by　various　external　forces,　such　as　earthquakes,　landslides,　and　other　third-party　damages.　These　additional　stresses　will　cause　the　pipeline　to　move　and　bend,　which　not　only　causes　the　pipeline　to　undergo　a　large　bending　strain,　but　will　also　causes　the　pipeline　to　fail　in　severe　cases.　In-line　inspection　(ILI)　based　on　strapdown　inertial　navigation　technology　has　become　an　effective　inspection　method　for　long-distance　pipelines　in　recent　years.　However,　the　cups　or　support　wheels　of　the　ILI　tool　encounter　the　pipe　wall,　girth　or　spiral　welds,　and　other　features　that　lead　to　minor　oscillations　and　vibration　during　the　inspection.　The　attitude　information　computed　by　the　inertial　measurement　unit　(IMU)　is　affected　by　these　noises,　and　the　computation　of　pipeline　bending　strain　(PBS)　is　inaccurate.　In　this　paper,　an　efficient　adaptive　combined　filtering　method　based　on　wavelet　transform　with　Savitzky-Golay　(S-G)　is　proposed,　which　is　adaptable　to　the　variation　of　attitude　information　for　the　ILI　tool　during　a　long　distance　and　time　inspection.　Experiments　were　conducted　to　demonstrate　the　effectiveness　of　the　optimization　for　PBS.　The　average　relative　deviation　decreased　from　38.3%　to　18.3%.