The invention relates to the technical field of
sewage treatment quality monitoring, and provides a
sewage treatment process monitoring method based on KPLS and RWFCM. The method comprises the steps that firstly, collecting
sewage treatment process data samples containing normal working conditions and abnormal working conditions wherein data of
sewage treatment operation variables and data of
effluent quality variables serve as an input
data matrix and an output
data matrix respectively, and the two matrixes are standardized; constructing a KPLS model, and solving a
score matrix; then, based on an RWFCM
algorithm, clustering the
score matrix to obtain a membership matrix, and according to the membership matrix, carrying out abnormal working
condition monitoring on the
sewage treatment process; and finally, establishing a
linear regression model of the membership matrix and the sample variables, solving a variable contribution matrix, and performing abnormal condition identification onthe
sewage treatment process according to the variable contribution matrix. According to the invention,
dimensionality reduction can be carried out on high-dimensional data, nonlinear data can be processed, the method is insensitive to outliers, and timeliness and accuracy of monitoring and identification in a sewage treatment process can be improved.