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Electro-mechanical actuators (EMAs) are one type of the key components for the next generation aircraft. In order to ensure its safety and reliability, it is critical to predict the remaining useful life (RUL) of EMAs. The data-driven RUL prediction can be implemented by utilizing Gaussian process regression (GPR) due to its uncertainty representation and nonlinear modeling capability. In order to...
Detecting the anomalies timely in the condition monitoring data, which are highly relevant to the potential system faults, has become a research focus in many domains. Among the various detection methods available, the prediction-based algorithms are popular without using prior knowledge and expert labels. Additionally, these methods can take the time-ordered specialty into account which is highly...
Electro-Mechanical Actuator (EMA) is one of the key components of next generation aircraft. In order to ensure the safety of aircraft, it is critical to predict the remaining useful life (RUL) of EMA. And the RUL prediction can be implemented by utilizing Gaussian Process Regression (GPR). However, the GPR algorithm is extremely complex. Hence, a weighted bagging Gaussian Process Regression (WB-GPR)...
This paper presents a data-driven approach based on mutual information (MI) and Gaussian Process Regression (GPR) for sensor anomaly detection and identification for aerospace applications. The proposed method not only detects and identifies the sensor which is anomalous, but also provides the anomaly detection accuracy, including false positive ration and false negative ration. First, the MI between...
Condition monitoring has gradually become the necessary part of the diagnostics and prognostics for the complex systems. Especially, with the rapid development of data acquisition and communication technology, the appearing of large scale data set and data stream brings great challenges to model and process the condition monitoring data As a result, anomaly detection of the streaming monitoring data...
Lithium-ion battery is a promising power source for electric vehicles owing to its high specific energy and power. Through monitoring battery health in effective way such as determining the operating conditions, planning replacement interval could increase the reliability and stability of the whole system. However, due to the reliance on integration, errors in terminal measurement caused by noise,...
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