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A strategy for increasing the accuracy rate of internal combustion engine (ICE) fault diagnosis based on the probabilistic graphical model is proposed. In this method, a three-layer network with inference of probability is constructed, and both the material conditions and the signals collected from different engine parts are considered as the inputs of the system. Machine signals measured by sensors were processed in order to diagnose potential faults, which were presented as probabilitiesdoi:10.1155/2019/8156450 fatcat:yn6tn62tuvbszng7er6kswx2qq