Machinery Health Prognosis - Data Driven Approach Using Threshold Regression

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H. MURTAZA
A. MANSOOR
A. S. SOOMRO
H. MUSHTAQ

Abstract

: Machinery health data is the backbone of prognostics. Effective prognostic, from the machinery data, leads towards operational reliability, reduced machinery downtime, cost savings, secondary/catastrophic failures etc. Various methodologies have been adopted by the researchers in an effort to precisely forecast/predict machinery health. In this study, Threshold Regression Methodology has been applied to a machinery vibration data to estimate future health state of machinery. The results show that the proposed method is an effective and reliable approach for data driven prognostics.

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How to Cite
H. MURTAZA, A. MANSOOR, A. S. SOOMRO, & H. MUSHTAQ. (2020). Machinery Health Prognosis - Data Driven Approach Using Threshold Regression . Sindh University Research Journal - SURJ (Science Series), 50(1). Retrieved from https://sujo.usindh.edu.pk/index.php/SURJ/article/view/1321
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