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In engineering, working environment and operating state are constantly changing, which decreases the correct rate of equipment fault diagnosis, resulting in the loss of time and cost. The structure of the deep belief network is investigated for the time-varying factors in the mechanical system. In combination with the signal decomposition technology of fixed learning step size, the original characteristics of the sensor data are retained. In addition, the deep key information of the signal is repeatedly extracted layer by layer. The data loss technology is integrated to optimize the network structure to avoid over-fitting problems. Further, considering the domain adaptive method in transfer learning, the memory characteristics of different levels of deep belief networks are solidified. Therefore, a domain adaptive deep belief network with shift-invariant features (SIF-DADBN) is proposed for rolling bearing fault diagnosis. By identifying the characteristic information of similar fault signals with variable working conditions, the accuracy and generalization of bearing intelligent fault diagnosis are both improved. Based on the public data set of rolling bearings, the average correct rate of the fault diagnosis technology is found to be as high as 95.65%. Compared with five other methods, the effectiveness and accuracy of SIF-DADBN under variable working conditions are verified.

Objective: This study aimed to investigate clinical efficacy of a modified coronal approach in treatment of craniomaxillofacial fractures., Methods: Thirty-seven cases of craniomaxillofacial fractures underwent open reduction and rigid internal fixation through modified coronal approach. Clinical follow-up visits were conducted to evaluate facial nerve functional status, temporal shape, appearance restoration, and reduction of fracture and surgical area scars., Results: During follow-up period of 6-36 months, appearance and function of all 37 patients recovered well without facial nerve injury and temporal depression deformity. All cases presented hidden scars, except for one case with hypertrophic scar., Conclusions: Applying modified coronal approach to craniomaxillofacial surgery effectively reduces incidence of temporal depression and facial nerve injury compared with traditional approach. The modified coronal approach produced more subtle scars compared with traditional approach and should be applied to treatment of craniomaxillofacial fractures.