A Ventricular Assistive Device (VAD) is a mechanical pump used to assist the functioning of a weak heart. A catastrophic obstruction in the VAD system could cost the patient their life. This thesis presents a set of fault detection techniques using the commercially available Jarvik 2000 Flowmaker® VAD in a closed loop circuit that incorporates the ability to alter common causes of VAD congestion. The first goals of this research is to determine the nominal pressure-low performance of the Jarvik pump, which is a graphical presentation of the static head and guides us about the major and minor losses in the system. Second goal is to characterize the health of the VAD system using frequency analysis of the acoustic signature. Principal Component Analysis, a data compression technique used to discover patterns in data of high dimension, is implemented on the frequency analysis and is followed by a health classification based on Bayes theorem. The classification results indicate that this technique is accurate to a high degree in detecting different levels of obstruction in the VAD system.
Mechanical Engineering (MS)
Department, Program, or Center
Mechanical Engineering (KGCOE)
Rana, Rohit, "Non-‐Invasive Fault Detection in Axial Flow Blood Pump Used As Ventricular Assistive Device" (2014). Thesis. Rochester Institute of Technology. Accessed from
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