Abstract
The life prediction is crucial to guarantee the reliability and safety of the mechanical system. The current prediction methods predict the life only based on the historical usage pattern of the mechanical system, and do not consider the mission profile of the future working process. To realize the life prediction with considering the switching of mission profile, which is composed of different operating conditions, this paper proposes a new prediction scheme on the base of the similarity trajectory method (STM). Two main improvements are employed. First, the reference degradation models are constructed according to the predicted trend of each constant operating condition obtained by the relevance vector machine (RVM). Secondly, the life under specific mission profile is calculated through weighted aggregating the life of each constant operating condition. The proposed method is validated by a turbofan engine simulation data. The results show that the proposed method achieves an excellent predicted result, in which the predicted result is close to the actual result. In addition, the proposed method can deal with the problem of mission profile switching.
Highlights
Prognostics and health management (PHM) is very crucial in modern industries, as the mechanical system is becoming larger, more complicated, and more automated
Motivated by the abovementioned problems, this paper proposes a new life prediction scheme for the mechanical system with considering the mission profile switching in the prediction process
In order to solve the switching of the mission profile with variable operating conditions, in the method, two main improvements on the base of the similarity trajectory method (STM) are proposed: (1)
Summary
Prognostics and health management (PHM) is very crucial in modern industries, as the mechanical system is becoming larger, more complicated, and more automated. The similarity trajectory method (STM) [17,18,19,20,21], which is simpler to calculate, was widely used to predict the RUL of the mechanical system under variable operating conditions [22,23,24,25,26]. The precondition of all the methods mentioned above is that the operating condition in the prediction process should be consistent with that of the training samples This means that the life of mechanical systems is an extrapolation of the current state. Motivated by the abovementioned problems, this paper proposes a new life prediction scheme for the mechanical system with considering the mission profile switching in the prediction process. In order to solve the switching of the mission profile with variable operating conditions, in the method, two main improvements on the base of the STM are proposed:.
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