Date of Award

January 2019

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mechanical Engineering

First Advisor

Cai Xia Yang

Abstract

Rotating machinery are critical instruments in the manufacturing sectors that are continually operated to fulfill their productivity objective. To reduce the risk of catastrophic failure and unwanted breakdown, it is crucial to ensure that these machines operate within their quality standards. Waste is undesirable to such sectors that directly affect manufacturing price. Maintenance intervention must be efficient, else it is deemed as waste. It is estimated that businesses are losing billions of dollars worldwide due to inadequate maintenance and poor management. It is, therefore, crucial to carry out effective maintenance actions. Since condition-based monitoring method recommends maintenance only when necessary, this approach can avoid unnecessary plan maintenance costs. Condition-based approach, along with the different faults detecting and correcting approach can become handy for the smooth operation of the machine in the industries. Out of various approaches, the vibration parameters-based condition monitoring approach has been proposed in this work. The significance of the proposed method is that it can correctly identify and classify the condition of the equipment as normal, misaligned, unbalanced, and cracked. Using the information of local harmonic acceleration amplitude, instead of harmonic acceleration amplitude, fault detecting, and classifying method is proposed. Then, the phase plane diagram-based fault classification technique is also proposed using the information of all the accelerometer data. Similarly, the Fuzzy Logic method is also used for fault detection and classification purpose. The obtained results signify the effectiveness of these proposed methods.

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