Research On Composite Sensing Of Exhaust Pressure And Temperature For Rotary Vane Compressor Based On Fiber Bragg Grating

Compressor stand-alone power consumption in the vehicle refrigeration system accounted for a large proportion of the compressor exhaust pressure accurate monitoring,is conducive to mastering the dynamic power consumption of the compressor impact factors,in order to achieve fine control of power consumption in the compressor industry and reduce carbon emissions.The electric pressure and temperature sensors used in traditional rotary lobe compressor exhaust monitoring are susceptible to electromagnetic signal interference,which affects sensor accuracy and stability;secondly,compressor exhaust monitoring involves a variety of parameters compound measurement,which is difficult to achieve with electric sensors;finally,the electric sensor installation destroys the pipeline structure and increases the failure rate.This thesis adopts Fiber Bragg Grating(FBG)as a sensitive element,and proposes a composite sensor based on Fiber Bragg Grating to improve the discharge pressure and temperature of the pressure relief valve of rotary vane compressor,taking into account the working characteristics of rotary vane compressor,using theoretical analysis,simulation analysis and real machine experiment.The research is carried out by a combination of theoretical analysis,simulation and experiments.Based on the sensing principle and mechanics theory of fiber Bragg grating,we established the theoretical model of pressure-temperature composite sensing,and revealed the mapping relationship between wavelength drift and pressure and temperature changes;through numerical and simulation analysis,we determined the structural parameters of the sensor sensitive element,processed the sensor prototype,and conducted relevant experimental research;in addition,we carried out the research of artificial intelligence algorithm to realize the In addition,the research related to artificial intelligence algorithm was carried out to realize the decoupling of pressure and temperature,which improved the accuracy and stability of sensor measurement.The specific research contents of this thesis are as follows:(1)Based on the principle of fiber Bragg grating sensing,the mechanism of pressure and temperature signal coupling interference is explored,and the temperature compensation method is studied;combined with the diaphragm deformation theory and compressor exhaust characteristics,the pressure-temperature multi-parameter composite sensing theoretical model based on fiber grating to improve the compressor pressure relief valve is proposed,revealing the mapping relationship between the wavelength drift and the pressure and temperature changes.(2)A diaphragm type fiber grating pressure-temperature composite sensor with improved pressure relief valve is designed for the pressure-temperature composite measurement of rotary lobe compressor discharge;through numerical and simulation analysis,the position of fiber grating paste and the structural parameters of the sensor sensitive element are determined,and the feasibility and vibration characteristics of the sensor structural model are verified,the encapsulation mold is designed,and the sensor prototype is developed.(3)The sensor performance test platform was constructed,and experiments on pressure characteristics,temperature characteristics and combined sensing of rotary vane compressor exhaust pressure and temperature were carried out.The pressure characteristic experiment shows that the pressure and wavelength drift have a good linear relationship,and the temperature compensation can effectively improve the sensitivity of the sensor;the temperature characteristic experiment shows that the two FBGs used in the sensor have a good linear relationship with temperature;the rotary vane compressor exhaust pressure-temperature composite sensing experiment shows that the maximum error of pressure 0.0192 MPa,root mean square error 0.002544 MPa,and the maximum error of temperature 0.72℃.Temperature maximum error 0.72℃,root mean square error0.004452℃,indicating that the sensor can effectively achieve pressure and temperature measurement.(4)In order to solve the pressure-temperature signal coupling interference problem,we propose the pressure-temperature decoupling method based on Atomic Orbital Search(AOS)optimized Deep Extreme Learning Machine(DELM),establish the AOS-DELM algorithm decoupling model,and conduct The results show that the maximum errors of pressure and temperature are reduced by 11.37% and 88.62% respectively after AOSDELM decoupling.