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Zhiguo Liang, Lijun Zhang and Xizhe Wang
Since failure of steam turbines occurs frequently and can causes huge losses for thermal plants, it is important to identify a fault in advance. A novel clustering fault diagnosis method for steam turbines based on t-distribution stochastic neighborhood ...
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Nengsong Peng, Weiwei Zhang, Hongfei Ling, Yuzhao Zhang and Lixin Zheng
A key issue in wireless sensor network applications is how to accurately detect anomalies in an unstable environment and determine whether an event has occurred. This instability includes the harsh environment, node energy insufficiency, hardware and sof...
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Beibei Yao, Jia Su, Lifeng Wu and Yong Guan
Due to the noise accompanied with rolling element bearing fault signal, it can reduce the accuracy of faulty diagnoses. In order to improve the robustness of a faulty diagnosis, this study proposed a fault diagnosis model based on modified local linear e...
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