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By taking the internal leakage faults of the low-pressure heater system of a 600 MW supercritical boiler unit as the object studied, a new approach by combining fault symptom zoom optimization technology based on artificial neural network was proposed. The neural network fault diagnosis model is established by dealing with the typical fault samples with symptom fuzzy calculation method. Real time fault diagnosis simulation tests are further realized by combining the ANN fault diagnosis model with fault symptom zoom optimization technology. It is proved that the proposed method can accurately diagnose the low-pressure heaters’ inner leakage faults of different leakage severity degrees under multiple load points with good engineering practicability.