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Abstract In the existing domain adaptation-based bearing fault diagnosis methods, the data difference between the source domain and the target domain is not obvious. Besides, parameters of target domain feature extractor gradually approach that of source domain feature extractor to cheat discriminator which results in similar feature distribution of source domain and target domain. These issues make it difficult for the domain adaptation-based bearing fault diagnosis methods to achieve satisfactory performance. An unsupervised domain adaptive bearing fault diagnosis method based on maximum domain discrepancy (UDA-BFD-MDD) is proposed in this paper. In UDA-BFD-MDD, maximum domain discrepancy is exploited to maximize the feature difference between the source domain and target domain, while the output feature of target domain feature extractor can cheat the discriminator. The performance of UDA-BFD-MDD is verified through comprehensive experiments using the bearing dataset of Case Western Reserve University. The experimental results demonstrate that UDA-BFD-MDD is more stable during training process and can achieve higher accuracy rate.

Abstract Wireless sensor nodes in wireless sensor networks are generally battery powered and it is usually hard to change their batteries. Therefore, energy saving has always been the basic critical problem of wireless sensor networks. In recent years, network coding has become a promising technology to improve network throughput, reduce transmission number, and save energy, which has great potential to solve the energy efficiency problem of wireless sensor networks. In addition, some network coding aware routings have been proposed. However, the network coding condition of existing network coding aware routings may experience the problem of false-coding effect in some scenarios, and usually neglect node energy, which greatly influences the energy efficiency performance. Therefore, existing network coding aware routings are not suitable for wireless sensor networks. This paper proposes network coding aware energy efficient routing (NAER) for wireless sensor networks. In NAER, universal network coding condition is presented and proved to avoid false-coding problem. Besides, combined with the coverage control and topology control mechanism at lower layer, cross layer coding opportunity discover mechanism is presented to increase coding opportunities. In addition, a network coding aware energy efficient routing metric (NERM) is presented, which takes coding opportunity, node energy, and link quality into account jointly. Simulation results demonstrate that NAER improves the accuracy of coding discovery mechanism, increases the number of coding opportunities, saves node’s energy consumption, and prolongs network lifetime.