This　paper　takes　on　the　central　heating　secondary　network　and　establishes　a　two-level　diagnosis　model　of　leakage　fault　of　heating　pipe　network　based　on　deep　belief　network　(DBN)　under　the　condition　of　constant　and　small　supply　flow　quality　regulation.　Firstly,　a　leakage　condition　hydraulic　calculation　model　of　the　heating　pipe　network　is　established　with　graph　theory,　which　provides　the　pressure　changes　of　the　pressure　monitoring　points　in　the　pipe　network.　Then,　the　first-level　diagnostic　model　for　the　leakage　of　the　heating　pipe　network　is　designed　to　diagnose　the　leaky　pipe　segment　by　using　a　deep　belief　network.　Based　on　the　results　of　the　first-level　diagnostic　model,　each　leaky　pipe　segment　is　treated　as　a　unit　and　a　second-level　diagnosis　model　is　then　developed　to　predict　the　specific　leak　location.　Finally,　the　model　is　verified　with　a　branch-pipe　network　and　a　loop-pipe　network.　Experimental　results　showed　that　the　first-level　diagnostic　model　had　a　high　accuracy　rate　in　the　prediction　of　leaky　pipe　segments,　which　was　superior　to　traditional　fault　diagnosis　methods　such　as　BP　(Back　Propagation　Neural　Network)　and　SVM　(Support　Vector　Machines).　The　second-level　diagnostic　model　can　detect　the　leak　location　of　the　leaky　pipe　with　satisfactory　results.