A method of implementing repairable board test of a repairable board detection device , the method comprising the steps of: obtaining, by the repairable board detection device , repair-relevant information of a plurality of sample repairable boards ; extracting, by the repairable board detection device , predetermined features from the repair-relevant information of the plurality of the sample repairable boards ; analyzing, by the repairable board detection device , the predetermined features to obtain one or more training features; establishing and training, by the repairable board detection device , a board detection model based on the training features; and receiving, by the repairable board detection device , repair-relevant information of a repairable board and transmitting, by the repairable board detection device , the repair-relevant information of the repairable board to the board detection model to obtain a detection result of the repairable board ; wherein the step of analyzing the predetermined features to obtain one or more training features comprises: obtaining a features list which comprises the predetermined features; encoding a value of each feature of the features list and converting feature values of the predetermined features to truth-values based on a predetermined converting rule to establish a features truth-value list; and applying the features truth-value list and detection results of the plurality of the sample repairable boards as the training features; and wherein each feature value is trained to obtain a weighted value, and the board detection model calculates the detection result of the repairable board according to the weighted value of each feature value. obtaining, by the repairable board detection device , repair-relevant information of a plurality of sample repairable boards ; extracting, by the repairable board detection device , predetermined features from the repair-relevant information of the plurality of the sample repairable boards ; analyzing, by the repairable board detection device , the predetermined features to obtain one or more training features; establishing and training, by the repairable board detection device , a board detection model based on the training features; and receiving, by the repairable board detection device , repair-relevant information of a repairable board and transmitting, by the repairable board detection device , the repair-relevant information of the repairable board to the board detection model to obtain a detection result of the repairable board ; wherein the step of analyzing the predetermined features to obtain one or more training features comprises: obtaining a features list which comprises the predetermined features; encoding a value of each feature of the features list and converting feature values of the predetermined features to truth-values based on a predetermined converting rule to establish a features truth-value list; and applying the features truth-value list and detection results of the plurality of the sample repairable boards as the training features; and wherein each feature value is trained to obtain a weighted value, and the board detection model calculates the detection result of the repairable board according to the weighted value of each feature value. obtaining a features list which comprises the predetermined features; encoding a value of each feature of the features list and converting feature values of the predetermined features to truth-values based on a predetermined converting rule to establish a features truth-value list; and applying the features truth-value list and detection results of the plurality of the sample repairable boards as the training features; and wherein each feature value is trained to obtain a weighted value, and the board detection model calculates the detection result of the repairable board according to the weighted value of each feature value. <EOS>