In　the　tension　measurement　by　using　magneto-elastic　tension　sensor,　generally　the　changes　of　hysteresis　loop　with　tension　is　applied.　But　due　to　the　changes　in　environment　temperature,　the　changes　of　hysteresis　loop　contain　not　only　the　tension　information　but　also　the　temperature　influence.　In　order　to　eliminate　the　influence　of　temperature　change,　a　temperature　compensation　method　used　in　rod-like　structure　tension　measurement　is　proposed　in　this　paper.　The　proposed　method　involves　three　key　steps.　First,　a　curve　of　hysteresis　loop　change　(CHLC)　is　defined　to　reflect　the　influence　of　temperature　and　tension.　It　contains　two　components:　1)　the　tension　component　of　CHLC　and　2)　the　temperature　component　of　CHLC　which　is　an　unknown　nonlinear　curve　related　to　the　temperature　changes.　Second,　a　prediction　model　of　temperature　component　of　CHLC　based　on　the　neural　network　is　proposed.　Finally,　the　temperature　influence　on　CHLC　is　eliminated　by　calculating　the　difference　between　the　CHLC　and　predicted　temperature　component　of　CHLC,　and　the　predicted　tension　component　of　CHLC　is　obtained.　The　experimental　results　show　that　the　CHLC　can　be　used　as　the　basis　of　the　temperature　compensation　method.　Moreover,　the　temperature　influence　can　be　analyzed　by　CHLC　when　the　tension　is　invariable,　whereas　the　tension　influence　can　also　be　analyzed　when　the　temperature　is　invariable.　The　temperature　component　of　CHLC　can　be　obtained　rapidly　and　accurately　by　the　neural　network-based　prediction　model　with　a　prediction　error　less　than　10(-5).　The　degree　of　CHLC　distortion　caused　by　temperature　change　is　reduced　from　10(-2)　to　10(-5)　with　the　proposed　temperature　compensation　method.