The invention relates to the field of
industrial internet of things, in particular to a
data quality evaluation and abnormal
root cause analysis method and
system based on
the internet of things, a terminal and a medium, and the method comprises the steps: collecting
monitoring data, and calling a dynamic threshold value for preprocessing based on a business scene type; inputting the data into the optimized isolation forest basic model for preliminary screening, and outputting normal and suspected abnormal data sets; constructing an equipment association graph and a node
feature matrix by using the equipment spatio-temporal topological relation and the suspected abnormal
data set, inputting the graph convolutional network enhancement model for secondary
verification, eliminating pseudo anomalies, and outputting a final abnormal
data set; the normal data and the pseudo-abnormal data are merged into an effective normal
data stream, and multi-dimensional quality evaluation is carried out; and constructing a feature mode vector based on the final abnormal
data set, matching the feature mode vector with a
power equipment knowledge base, and determining an equipment fault type. According to the invention,
data quality evaluation and abnormal
root cause positioning are realized, and the
data management operation and maintenance efficiency of
the Internet of Things is improved.