Research On Intelligent Monitoring System Of Tissue Engineering Bioreactor

Tissue engineering is one of the greatest concern field in biomedical international research.the micro environment in the human body can be simulated on the platform for the cultivation of a variety of tissue cells.However,the traditional process of tissue engineering bioreactor culture relies on the experience of the experts or the method of add indicator to discriminate the growth of tissue cells and artificial replacement of the culture medium,resulting in tissue cell contamination,growth conditions affected and the culture of waste.This thesis aims to construct the intelligent tissue engineering bioreactor on-line monitoring system based on multi-sensor data fusion,transform thefrom the mode of the traditional tissue engineering bioreactor from artificial control into the whole day sterile intelligent remote monitoring and achieve the discrimination of the growth condition of tissue cells in the bioreactor,promote the overall integration and industrialization of bioreactor.The background and significance of the research on the intelligent monitoring system of tissue engineering bioreactor are analyzed in this thesis,then the research status and detection parameters of bioreactor monitoring technology are expounded,after the basic detection method of micro-current is discussed,the research on development at home and abroad of multi-sensor data fusion technology is introduced.The existing electrochemical detection methods and the micro-current detection mechanism of electrochemical sensor is analyzed in this thesis,the working principle of three-electrode detection system is introduced,the equivalent circuit model of three-electrode sensor is established,the source of the electrode noise and the influencing factors are analyzed,and the specific structure of three-electrode needle sensor is described in detail,and constant potential circuit detection principle based on the three-electrode are analyzed.In order to realize the accurate detection of the parameters in the bioreactor,the micro-current detection system based on the electrochemical sensor is designed.The hardware circuit design and software program design of each part of the system are described in detail.The simulation test of the hardware circuit is carried out by Multisim circuit simulation software to verify the correctness of the circuit design,and analyze the actual test results of the circuit,the system hardware and software anti-jamming design method is given.In order to realize the growth discrimination of tissue cells in the bioreactor,the calibration of the parameters in the bioreactor is carried out by the standard instrument,and the linear relationship between the measured values and the parameters is determined,a data fusion algorithm combining batch estimation algorithm with D-S evidence theory is established,an improved method of evidence combination rule based on evidence similarity coefficient is proposed to realize the identification of growth status of tissue cells in bioreactor,and a simulation example of multi-source data fusion algorithm is established,The results show that the method can achieve identification of the growth status of tissue cells.The intelligent monitoring platform of virtualized tissue engineering bioreactor which is combined with virtual instrument technology is designed,and the multi-sensor data fusion algorithm based on batch estimation and improved D-S evidence theory is proposed in this thesis for multiple parameter data fusion processing to realize the growth status discrimination of the cells in the bioreactor.