Study Of Biofilm Thickness Online Measure System Using Fiber Sensor Based On Absorbance

In the industry exhaust gas processing means, the mean of the biotrickling filter tower is the common biochemical exhaust gas processing mean as it has a characteristic of high efficiency and easily operating. When the biofilter processes the exhaust gas, the biofilm will be produced on the surface of the filling. While the survival condition of the microbe cell is appropriate, the extracellular polymeric substances made the microbe cell form the fibroid entwisting frame by the research.In the process of processing the low concentration organic exhausted gas in the biofilter tower, the biofilm thickness has a direct influence on the exhaust gas processing speed and increasing the processing efficiency. According to the research, the biofilm thickness's changing at all times makes it difficult to analysis the biofilm thickness. So it brings the difficulty to effectively control the exhaust gas processing speed and to increase the processing efficiency. And to settle these problems, it needs a method that can achieve the online real time measuring biofilm thickness. Online and real time measuring the biofilm and making use this measuring results in the biotrickling filter tower, it can largely increase exhaust gas processing speed and the processing efficiency. This means has a wide and sunshiny application foreground.This paper mainly studies on these aspects and gets the research results below:(1) Puts forward a testing method for biofilm thickness based on fiber reflecting energy attenuation technology. Form the law of Lambert-Beer, the optical absorption coefficient is related to biofilm thickness. According to this phenomenon and the theory, relating the receiving optical energy to the significative biofilm thickness and find this two have a function relation of one to one. Based on this function relation, it can get the biofilm thickness by measuring the voltage signals.(2) Based on the measuring mean, the author designs a fiber biofilm thickness online measuring sensor. And analyze the light pathway theory and the structural principle of the sensor. In the end, carry through the experiment of biofilm thickness measuring with this sensor. According to the experiment results and the theory analysis, it shows that using this mean to measure the biofilm is viable. But in the measuring process, the sensor has a certain error because of a member of light not to be received by the fiber sensor.(3) Aimed at the error above, puts forward that using the RBF neural network puts up a forecast model of biofilm thickness measuring. The forecast model shows that RBF neural network has a capability that it can approach on any function with any precision. Especially when the sample is fewer, the RBF neural network has a good function approach capability. This method only takes use a little time and it is real time. With this forecast mode based on RBF neural network, the relative error of the biofilm thickness measuring system can reduce to 3.9%. So this biofilm thickness measuring method with RBF neural network forecast model is very good.