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To develop a cost-effective condition-based maintenance strategy, accurate prediction of remaining useful life (RUL) is the key. It is known that many failure mechanisms in engineering can be traced back to some underlying degradation processes. In this paper, we propose a two-stage prognostic framework for individual units subject to hard failure, based on(More)
Failure prognosis plays an important role in effective condition-based maintenance. In this paper, we evaluate and compare the hard failure prediction accuracy of three types of prognostic methods that are based on mixed effect models: the degradation-signal based prognostic model with deterministic threshold (DSPM), with random threshold (RDSPM), and the(More)
In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is(More)
Asthma is a very common chronic disease that affects a large portion of population in many nations. Driven by the fast development in sensor and mobile communication technology, a smart asthma management system has become available to continuously monitor the key health indicators of asthma patients. Such data provides opportunities for healthcare(More)
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