A model to determining the remaining useful life of rotating equipment, based on a new approach to determining state of
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A model to determining the remaining useful life of rotating equipment, based on a new approach to determining state of degradation Saeed RAMEZANI1, Alireza MOINI1, Mohamad RIAHI2, Adolfo Crespo MARQUEZ3 1. Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran; 2. Department of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran; 3. Department of Industrial Management, University of Seville, Spain © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020 Abstract: Condition assessment is one of the most significant techniques of the equipment’s health management. Also, in PHM methodology cycle, which is a developed form of CBM, condition assessment is the most important step of this cycle. In this paper, the remaining useful life of the equipment is calculated using the combination of sensor information, determination of degradation state and forecasting the proposed health index. The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method. Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching (ARMRS) method, final health state is determined and the remaining useful life (RUL) is estimated. In order to evaluate the model, sensor data provided by FEMTO-ST Institute have been used. Key words: remaining useful life (RUL); prognostics and health management (PHM); autoregressive markov regime switching (ARMRS); health index (HI); Dempster-Shafer theory; fuzzy c-means (FCM); Kurtosis-entropy; degradation Cite this article as: Saeed RAMEZANI, Alireza MOINI, Mohamad RIAHI, Adolfo Crespo MARQUEZ. A model to determining the remaining useful life of rotating equipment, based on a new approach to determining state of degradation [J]. Journal of Central South University, 2020, 27(8): 2291−2310. DOI: https://doi.org/10.1007/ s11771-020-4450-7.
1 Introduction Prognostics and health management (PHM) concept are retrieved from the well-known maintenance and diagnosis techniques such as preventive maintenance (PM), reliability centered maintenance (RCM) and especially condition-based maintenance (CBM) [1]. CBM consists of data gathering and processing (condition monitoring), so that, based on the analyzed information, maintenance decisions are taken and as a result the unnecessary maintenance measures are prevented. PHM could be considered as a developed form of CBM. CBM techniques can provide the input of prognostic model in PHM. Failure mechanism
analysis in PHM (corrosion, fatigue, overload, etc.) is related to the product life cycle management. Because of the ability to assess health states and forecasting failures, PHM can even be considered the foundation of modern techniques in the field of maintenance [2]. In general, three different approaches to determining the state of equipment degradation are presented by the researchers:
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