Research On The Composite Measurement System For Fluid Flow Rate And Temperature Inside A Closed Pipeline Based On Fiber Bragg Grating

This thesis aims to solve the problems of single measurement parameters,large volume,installation limitations,inconvenient networking,and susceptibility to electromagnetic interference in the current nuclear power industry’s nuclear cooling system flow and temperature measurement instruments.To achieve safe and stable monitoring of cooling water flow and temperature inside the nuclear cooling pipeline,a composite measurement system for fluid flow and temperature inside a closed pipeline based on fiber Bragg grating was studied using a combination of theory,simulation,and experimentation.The research object was a differential structure of square tube FBG flow and temperature composite measurement sensor.Starting from the FBG sensing principle and combining it with the arrangement method of the differential structure of square tube FBG,the mechanism of the sensor’s flow and temperature composite measurement was derived,the overall structure of the sensor was designed,and the sensor’s performance testing experiment system was constructed.The composite measurement performance of the sensor for flow and temperature was verified through simulation and experimentation,and a neural network algorithm decoupling model was constructed for FBG sensing signal decoupling.The specific research content of the thesis is as follows:(1)Based on the FBG sensing principle,the principles of FBG strain and temperature measurement were revealed,and the reasons for coupling interference in FBG sensing signals were analyzed.The mechanism for decoupling strain and temperature was studied.Based on the differential structure decoupling method and combining fluid mechanics and elasticity theory,a composite measurement mechanism model for flow and temperature of the differential structure of square tube FBG was constructed,and the regular features of the center wavelength drift of the differential structure of square tube FBG with changes in flow and temperature were elucidated.(2)Based on the composite measurement mechanism of the differential structure of square tube FBG for flow and temperature and the safety measurement requirements of the nuclear cooling pipeline,the overall structure of the sensor was designed,and sensor components that are corrosion-resistant and can withstand high temperatures were selected.The sensor’s sensitive unit structure dimensions were designed using theoretical and numerical analyses,combined with cooling water flow and temperature measurement range requirements.The optimal FBG attachment position was determined through simulation analysis,and the sensor and flow and temperature measurement characteristics were verified.The development of the sensor prototype was completed.(3)To verify the measurement performance of the sensor,a closed pipeline fluid flow and temperature composite measurement experimental system was constructed to simulate the fluid environment of the nuclear cooling pipeline.A hardware experimental platform composed of a power platform,a measurement platform,and a data acquisition platform was constructed.Using the Python language,a software experimental platform was designed,consisting of modules such as data acquisition,FBG sensing signal processing,flow and temperature data processing,FBG sensing signal decoupling,data storage,and system parameter setting and query.The combination of the hardware and software experimental platforms formed the closed pipeline fluid flow and temperature composite measurement experimental system.(4)Based on the designed and fabricated prototype sensor,experiments were conducted on the sensor’s temperature characteristics,flow-temperature composite measurement,and FBG sensing signal algorithm decoupling using the built measurement system.The temperature characteristic experiment results showed that the repeatability errors of FBG1 and FBG2 were 3.07%and 4.40%,respectively,with hysteresis errors of7.44%and 12.15%,and an average temperature sensitivity of 21.35pm/℃and temperature resolution of 0.04℃in the range of 0℃～100℃.The flow-temperature composite measurement experiment results showed that within the range of 25℃～65℃and 5m~3/h～30m~3/h,the sensing signal and flow exhibited a quadratic relationship with a quadratic polynomial fitting goodness of 0.937,and a linear relationship with a linear fitting goodness of 0.986 with a dynamic measurement flow root mean square error of0.237m~3/h and maximum error of 1.15m~3/h,and temperature root mean square error of0.045℃and maximum error of 0.50℃.The FBG sensing signal algorithm decoupling experiment results showed that the established Harris Hawks Optimizer algorithm Optimized Kernel Extreme Learning Machine algorithm model had good decoupling effects,effectively reducing the mutual influence of flow and temperature signals,and the flow root mean square error and maximum error of the sensor were reduced by 67.09%and 55.78%,respectively,while the temperature root mean square error and maximum error were reduced by 73.33%and 50.00%,respectively.