The application discloses a kind of in-
pipe electrode head
anode body consumption state real-time
monitoring system, it is related to
electrode wear monitoring technical field, the
system includes
data acquisition module,
data processing module, modeling module, life prediction analysis module and risk early warning module;By arranging multiple micro-sensing nodes in
electrode pipeline interior,
current density distribution,
potential gradient and electrode-medium interface sense resistance value are collected;After normalization
processing, loss characteristic map is constructed, and loss mapping matrix is generated;
Supervised learning is carried out using long short-
term memory residual network, and real-time consumption state
weight value is output;Combined with operating condition parameters, the
remaining life of each region is predicted based on Bayesian dynamic model, and critical wear area is labeled;When life is lower than preset threshold and consumption acceleration exceeds set value, output
anode head replacement early warning instruction;The application realizes high-precision,
dynamic monitoring and intelligent early warning of electrode
anode body wear state, with good real-time and adaptability.