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This paper presents a new approach for machine health monitoring based on the C0 complexity, which is an alternative nonlinear statistical measure that can quantify the regularity of a time series. Firstly, we give a brief introduction of C0 complexity and discuss the parameter r. After that, two run-to-failure bearing vibration data are presented to verify the performance of C0 complexity. Comparisons...
In allusion to performance degradation condition recognition issue for rolling bearing, a method based on improved pattern spectrum entropy (abbreviated as IPSE) and fuzzy C-means algorithm (abbreviated as FCM) is proposed in this paper. In the course of performance degradation feature extraction, morphological corrosion operator is introduced and IPSE is proposed as the degradation feature parameter...
This paper describes a unified data-driven prognostic framework that combines failure time data, static parameter data and dynamic (time-series) data. The approach employs Cox proportional hazards model (Cox PHM) and soft dynamic multiple fault diagnosis algorithm (DMFD) for inferring the degraded state trajectories of components and to estimate their remaining useful life (RUL). This framework takes...
The detection of micro-cracks or degradation of strength of materials at the early stage of fracture is of increasing importance in power plants and aviation industry. A methodology of detecting micro-cracks or degradation of material using quasi matrix pencil method is presented in this paper. The damage is represented by small local elastic modulus reduction. Response of axisymmetric longitudinal...
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