| Water resources are the most important factor in all life,and production,and are the basic conditions for human survival.The development of industry and agriculture has caused more and more serious water pollution,and the research of water quality detection technology has always been an important subject of scientific research in science and technology.The core technology of water quality detection is sensors.At present,water quality sensors are developing towards miniaturization and integration.MEMS sensors are widely used in the field of water quality detection due to their small size,easy integration,and good stability.This paper uses electrochemical analysis technology,combined with microelectrode sensors,to achieve the measurement of three water quality parameters: p H,dissolved oxygen and ammonia nitrogen.By analyzing the development status of sensor integration,miniaturization,nano-material electrode surface modification and detection data correction methods,based on analysis of related technologies,using MEMS technology to design a multi-parameter microsensor chip with temperature compensation function,and the sensor chip The matched microfluidic test chamber realizes the independent test of each sensing unit.On the other hand,polyaniline/inorganic composite nanomaterials were used to modify the surface of the sensor's sensitive electrode,and the surface morphology of the sensitive material was characterized and analyzed.The modified electrodes were used to measure the three parameters,and the results showed higher sensitivity and better stability.The use of multiple linear regression analysis technology to calibrate the temperature of each parameter further improves the accuracy of the measurement.The PSO-LM-ANN model is constructed to correct the problem of selectivity variation in simultaneous multi-parameter measurement,which improves the measurement accuracy.This paper focuses on the key technologies such as the structural design of the sensor,the surface modification of the sensor electrode and the correction and processing of the water quality multi-parameter detection data.Multi-parameter sensor chip structure design.Based on the study of the electrochemical diffusion mechanism,it is concluded that the microelectrode has a better electrochemical diffusion effect than the large electrode.Therefore,MEMS technology is used to design and prepare microelectrode sensor chips.From the analysis of electrode structure,ANSYS software was used to compare and analyze the "square" and "circular" electrode structures.The simulation results show that the "circular" electrode structure makes the solution have a more consistent electric field intensity and current density distribution.,So that the analyte on the electrode can receive a more uniform and consistent electrocatalysis.Considering the influence of temperature on the measurement results of various parameters,a micro heater integrated with the microelectrode is designed in the sensor chip structure.Several heater structures are compared and analyzed using ANSYS software to determine the optimal structure,and finally the design has a temperature Multi-parameter sensor electrode array structure with compensation function.Surface modification of sensor electrodes.The surface modification of the sensor electrode can increase the specific surface area of the electrode and enhance the conductivity of the electrode.Different sensitive membranes are selective for different water quality parameters,which can further enhance the detection sensitivity of the sensor.The conductive polymer PANI/inorganic nanomaterials were synthesized by in-situ method and modified on the surface of the sensor electrode.The surface morphology of the sensitive material was characterized and analyzed,and its microscopic morphology showed high activity.By measuring p H,ammonia nitrogen and other parameters,it shows high sensitivity.Sensor signal acquisition and testing methods.Use PMMA plexiglass to prepare a miniaturized microfluidic test chamber with a shunt channel to form a test container that matches the sensor chip.The cavity structure of the shunt channel ensures that each test unit of the sensor chip can work independently,avoiding solution in the test process Interfere with each other internally.In order to realize the sensor signal acquisition,a potentiostat matched with the sensor structure is configured.In the test process,the inlet and outlet of the water quality solution are controlled by a peristaltic pump.Adjusting the operation mode of the peristaltic pump can fully realize the uniform flow of the liquid,and realize experiments such as sensor testing and cleaning.Water quality multi-parameter testing.Through the sensor test platform,water quality parameters such as water temperature,p H,dissolved oxygen and ammonia nitrogen concentration were measured.The experimental results show that the sensors all show higher sensitivity and better linearity.According to the actual situation of the test environment temperature,adjust the heater working mode in the sensor to realize temperature compensation and ensure that the sensor works within the ideal temperature range.The three parameters of p H,dissolved oxygen and ammonia nitrogen are respectively established with temperature and response current to establish multiple linear regression equations to further improve the measurement accuracy of the sensor.In the water quality multi-parameter detection data correction processing.Aiming at the influence of coexisting substances on the catalytic reaction when multi-parameters are measured at the same time,the selectivity of multi-parameter simultaneous measurement is deteriorated and the measurement accuracy is reduced.A PSO-LM-ANN data correction method is proposed to correct the multi-parameter detection data.The three parameters of p H,dissolved oxygen and ammonia nitrogen output by the sensor during simultaneous multi-component measurement are used as network inputs,and the standard values of p H,dissolved oxygen and ammonia nitrogen concentration are used as the three output parameters.Using Matlab to optimize the design of the network model,the optimization results show that when the number of hidden layer nodes is 8,and the network adopts the LevenbergMarquardt algorithm,the prediction accuracy of the network is the best.At the same time,the PSO optimization algorithm is introduced to optimize the weights and sums of the LM-ANN network.Threshold.The verification results show that the PSO-LMANN method has better data correction effect and higher correction accuracy.The research results show that the multi-parameter array sensor chip with temperature compensation based on MEMS technology can achieve high-precision measurement of parameters such as p H,dissolved oxygen,and ammonia nitrogen,and the temperature compensation effect is better.The developed PANI/Cu O nanocomposite material is used for electrode surface modification,which can effectively improve the sensitivity of p H detection and reduce the response time.The PSO-LM-ANN model corrects the detection data when multiple components are measured at the same time.The experimental results show that the model can be used to obtain high-precision correction results. |
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