Abstract: According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status were confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information and online testing information were established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information was 94%. The evaluation model could evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.