Study On Water Pipeline Leakage Monitoring Based On Active Heating Fiber Optic Temperature Measurement

Leakage of pipeline system for water supply is a common problem which causes huge waste of resources and economic losses to the society.To obtain the real-time operating status of buried water pipeline and ensure the normal operation of social life,a novel leakage detection method was proposed based active heating and distributed fiber optic temperature measurement.A type of heating cable with distributed temperature sensing capability was therefore developed for leakage detection.The study provides new possibility for the real-time leakage detection and accurate localization for buried water pipeline.The main contents of this study are summaried as follow.The feasibility of the active heating and temperature sensing method for pipeline leakage detection was validated through finite element simulation via ANSYS FLUENT.The three dimensional model of the leakage experiment was established.The accuracy of leakage localization of the proposed method was analyzed.Moreover,the influencing factors,such a s the tmepearature of the fluid,flow velocity,soil conditions,on the detection performance were investigated.The finite element simulation validated the efficacy of the active heating and distributed temperature sensing method for leakage detection of water pipeline.Two type of active heating and temperature sensing cable were developed,namely the cable based on DS18B20 tempearture sensing and the one based on Fiber Bragg Grating(FBG)temperature sensing.The pipeline leakage detection platform was setup.In the preliminary tests,these cables were placed in water,soil,and air environments to obtain their temperature responses un der the given heating duration.The reliability and stability of the fabricated cables for leakage detection of water pipeline were verified.Pipeline leakage monitoring tests using the DS18B20 heating cable and FBG heating cable had been carried out.The accurate positioning of leakage along the pipeline was realized.And the influences of flow velocity,soil conditions on the leakage detection results had been studied experimentally.The temperature responses under the environments of sand,water,voids,and seepage conditions were collected and analyzed.The Back Propagation(BP)neural network was adopted to train and classify the test data under different environmental conditions.The accurate identification of ambient environment along the pipeline and leakage detection were realized.