Research On Data Quality Control Method Of High Precision CTD Sensor

With the advent of the marine century,the development of marine resources and the exploration of the marine environment has gradually deepened,and the importance of marine research has become increasingly prominent.Temperature and salt depth sensors,referred to as CTD(temperature T,conductivity C,depth D),are important tools for studying the physical characteristics of the ocean.Temperature and depth sensors can accurately measure seawater temperature,conductivity,and pressure.Using these parameters,the seawater salinity,depth,density,and other characteristics can be calculated.Since the temperature-salt depth sensor is an electronic component-based observation instrument and is applied in a complex marine environment,the measurement data obtained are often affected by different factors.If in the design process,these interference factors are not properly handled,high-quality observation data will not be obtained,and related ocean research will inevitably be impossible.Therefore,the study of data quality control methods for temperature-salt depth sensors is of great significance.The data quality of temperature and salt depth sensors mainly includes the accuracy of data measurement,sensor response speed,stability and long-term reliability.This article focuses on this topic,and makes targeted analysis and optimization design from the perspectives of improving the original data quality,data processing algorithm research,and system calibration and fitting,and the feasibility and effectiveness of the solution.Verified.The quality improvement of the original data is mainly a hardware-level study.According to the accuracy requirements of the temperature,conductivity,and pressure sensors,a detailed analysis of the selection of key components in the measurement circuit is made.The thermal design,the stability of the Chinese bridge frequency for electrical conductivity measurement,and the heating problem of the system's long-term operation were optimized.In terms of data processing algorithms,a data filtering algorithm after AD sampling was designed,and the accuracy loss of floating-point and fixed-point data representation was studied.Two kinds of conductivity frequency signal collection algorithms were designed and the accuracy of the two algorithms was compared.Finally,a software-level compensation algorithm is proposed for the lag problem of the temperature sensor and the effectiveness of the algorithm is verified.In terms of system fitting,we mainly study the fitting models and calibration test methods for temperature,conductivity,and pressure.With the help of comparative experiments,we have verified the improvement effects of the previous hardware and software levels and the accuracy of the fitted models.Through the analysis of the experimental results,it is verified that the data indicators of the sensor meet the design requirements.