2021/04/21 by Akthem Rehab, Islam Ali, Rehab, Akthem +5
Chemistry · Engineering · #FOS: Computer and information sciences #Fault Detection and Control Systems #Logic in Computer Science (cs.LO) #Machine Fault Diagnosis Techniques #Machine Learning (cs.LG) #Spectroscopy and Chemometric Analyses
paper · pdf · doi:10.48550/arxiv.2104.10519
openalex publication_date 2021/04/21 · openalex created_date 2021/04/26 · openalex updated_date 2026/07/28
Asset health monitoring continues to be of increasing importance on productivity, reliability, and cost reduction. Early Fault detection is a keystone of health management as part of the emerging Prognostics and Health Management (PHM) philosophy. This paper proposes a Hidden Markov Model (HMM) to assess the machine health degradation. using Principal Component Analysis (PCA) to enhance features extracted from vibration signals is considered. The enhanced features capture the second order structure of the data. The experimental results based on a bearing test bed show the plausibility of the proposed method.