The invention provides an
electric power meter data real-time analysis and abnormity early warning method based on edge calculation, and belongs to the technical field of
data analysis and early warning, and the method comprises the steps: collecting the multi-
modal data of an
electric power meter based on a multi-channel analog-to-
digital converter, employing a hardware filter circuit to eliminate high-
frequency noise, and obtaining the data of the
electric power meter;
signal gain self-adaptive adjustment is carried out based on a reconfigurable
amplifier; a
digital signal processing accelerator is used to carry out
Fourier transform on a matrix constructed by the standardized
data stream, and a multi-core processor is combined to carry out analysis to generate a
feature vector; the method comprises the following steps: acquiring environmental parameters in real
time based on an
environmental sensor, dynamically adjusting an
anomaly detection threshold in combination with a
machine learning model trained by historical data, and comparing a
feature vector with the dynamic threshold to generate an anomaly
signal; the
relay control circuit triggers sound-light alarm, the physically isolated communication module sends an early warning instruction to the cloud platform, and meanwhile, the redundant power supply module is started to control the electric power meter to operate continuously. And the efficiency and accuracy of subsequent abnormity early warning are improved.