The invention discloses an
oil tank liquid level real-time monitoring method and
system based on an
intelligent sensor, and the method comprises the following steps: S1, collecting and preprocessing
oil tank liquid
level data, and constructing a liquid level
time sequence; s2, extracting a
time sequence fragment in a sliding manner, analyzing a trend, calculating a change rate and an amplitude, and generating a trend
feature vector; s3, constructing a prediction model for reasoning, performing transformation, gating and mapping on a result, and generating a
trend prediction and abnormal probability sequence; s4, fusing the sequence to calculate a mean value and a standard deviation, and constructing a threshold value based on Z-
score to identify an abnormal
time step; s5, calculating an error between a predicted value and a reference value, and dynamically adjusting PID parameters to generate a control instruction; and S6, comparing predicted data with real-
time data before control, and updating
model parameters according to deviation. According to the method,
intelligent sensor collection, BEMD
decomposition,
deep learning trend prediction and a PID control feedback mechanism are fused, and the prediction precision and the regulation response capability of
oil tank liquid level monitoring are improved.