The invention provides an unsupervised device running track model establishment method. The method comprises the following steps: step S1, establishing a first layer of a model: establishing a Markov jump process for describing the change of a device state, wherein the probability of an initial stage of a device and the possibility of change of the device to the other stage from one stage in a time span need to be calculated; step S2, establishing a second layer of the model: establishing a group of Markov chains used for capturing a relationship between the change of device state stages and the occurrence of abnormal phenomena; and step S3, establishing a third layer of the model: establishing a bidirectional noisy-or Bayesian network for capturing a relationship between the abnormal phenomena of the device and monitored index data. The method can be used for judging whether the device already has certain abnormal phenomena and enters a next stage with a more serious state according to the change of various indexes, so that the pre-control can be performed for preventing the device from being further deteriorated.