Faulty gear vibration diagnostic and monitoring

Anbualagan, Ruttiran (2022) Faulty gear vibration diagnostic and monitoring. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Vibrations are an inherent part of machinery. If not monitored or lowered to a safe level, the magnitude of this vibration rises over time and becomes damaging to the apparatus. Researchers worldwide are always conducting research on gear vibrations in order to enhance or suggest solutions to difficulties caused by the vibrations. Numerous components, particularly gears, can create these vibrations, which cause the machinery to shake at a specific frequency and might impair the machine's function if left unnoticed and undiagnosed. Vibrations of a high magnitude indicate that the gear is malfunctioning and should be evaluated; if left untreated, they can raise the cost of repairing the failure and shorten the machine's life. Gears typically face an increase in vibration magnitude when they sustain damage over time due to continual motion during operation. When a defective rolling element makes contact with another element's surface, impact force is generated, resulting in an impulsive gear response. Machinery performs poorly as a result of this increase in vibration magnitude. As a result, it is critical to monitor the gear's vibration status at all times and to diagnose any increase in its vibration amplitude immediately. To address this, vibration signal analysis can be used as an effective vibration monitoring technique, as demonstrated in this thesis. This thesis examines spur gear and helical gear vibrations under normal and fault conditions by conducting an experiment at speeds of 500 rpm, 1000 rpm, 1500 rpm, and 2000 rpm under four different gear conditions to determine the vibration levels associated with each condition. Vibration Statistical Analysis (VSA) was then used to examine the vibration of this gear using MATLAB and Excel tools. As a result of the results, there is an increase in the transient components, which increases in lockstep with the running speed. Additionally, the graphs demonstrate that as the speed increases, the vibration with frequency increases in amplitude. By examining the scattering of z-freq data and its coefficient. It is visible that the dots spread throughout the affix and annex frequency, indicating that the scattered data exhibits a distinct pattern when the RMS speed increases for all conditions. To summarise, time domain is less suitable for fault prediction than the R-Squared approach because the graph difference between the defective and excellent situations is similar to the graph difference between the frequency domain graphs. The RMS and R-squared values in this thesis are used to predict the condition that creates the specific vibration.

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