Research On Multi-sensor Information Fusion Algorithm In Water Quality Detection

The research of information fusion algorithm in water quality detection can describe the water quality grade well,and it is of great significance to the selection and analysis of water quality attributes in water quality and water quality protection.By processing and fusing the water quality information measured by multiple water quality detection sensors.The sensors of the same or heterogeneous type.The water quality information measured by a single water quality detection sensor can be more comprehensive and reliable.The water quality evaluation and analysis are more realistic.The research of multi-sensor information fusion algorithm in water quality detection is particularly important.The paper takes the water quality data in the water quality detection as the research object,and it focuses on the research of the multi-sensor information fusion algorithm.The main research contents include:(1)A brief introduction to the relevant theoretical knowledge of the multi-sensor information fusion algorithm.Taking the water quality data obtained by the water quality detection sensor as the research object.A fuzzy multi-attribute decision-making algorithm based on information entropy under the same level of water quality is proposed.The algorithm combined with the principal component analysis method.Selecting the water quality attributes of KMO>0.5 and Bartlett<0.05 used for algorithm analysis,which it used for improved fuzzy comprehensive evaluation algorithm research.Firstly,the traditional fuzzy comprehensive evaluation method is used to obtain the water quality grade.Secondly,making fuzzy multi-attribute water quality decision-making based on information entropy on the basis of the same level of water quality.Using information entropy to find the relationship between the pros and cons of water quality at the same level,so that the water quality level has a higher degree of discrimination.Finally,combining the advantages of the principal component analysis method to obtain the pros and cons of the relationship to compare the results of the improved algorithm.This algorithm effectively makes up for the shortcomings of the principal component analysis method that cannot divide the water quality grades.And it solves the general ambiguity of the same grade of water quality.On the basis of the same grade of water quality,a higher-precision distinction of water quality can be obtained.(2)In view of the fact that traditional water quality evaluation models cannot reflect the dynamic change characteristics of water quality testing data.A water quality evaluation model based on intuitionistic fuzzy multiple attribute decision-making is constructed.The uncertainty information of the change in the water quality attribute value interval,Which is combined with the degree of membership and non-membership in the intuitionistic fuzzy multi-attribute decision-making to describe this uncertain water quality attribute information.Firstly,using the interval average of water quality to combine with the traditional fuzzy comprehensive evaluation algorithm.It can decide the interval water quality grade.On the basis of the same level of water quality to construct a multi-attribute decision matrix of water quality intuition interval.Normalized to intuitionistic fuzzy multi-attribute matrix to construct the optimal weights of water quality attributes.And it can calculate the comprehensive attribute values of the water samples.Finally,the score value of the water sample is obtained through the score function.This algorithm can describe the fuzzy nature of water quality in more detail.The algorithm fully considers the information that the water quality attribute value changes within a certain range.This algorithm effectively expands the research of interval water quality assessment algorithm.At the same time,combining with the fuzzy comprehensive index method to verify the feasibility of the algorithm.