Vibration Monitoring Mathematical Modelling and analysis of Rotating Machinery | Abstract

ISSN ONLINE(2278-8875) PRINT (2320-3765)

Research Article Open Access

Vibration Monitoring Mathematical Modelling and analysis of Rotating Machinery


The four main components of machinery management are monitoring, protection, machinery analysis and proactive machinery control. Themonitoring system implements the role of monitoring and protecting machinery. However due to its many different forms of communication to outside systems, it provides the data to the systems that can analyse the machinery responses and make decisions to assist the machinery management process. Various transducers translate the mechanical energy into electrical and then transmit them to the monitoring system over the field wiring. The monitoring system accepts the signal and processes it, calculating related quantities, such as the variables amplitude, phase. The monitoring systems also provide access points for the data signal to be provided to other devices. The proximity transducer system is used in the project to obtain the voltage signals and the probe calibration values are found both mathematically and through the use of calibration equipment. The various conditions that led to the use of proximity probes, including probe cable length(s), supply voltages, the types of target materials etc are identified. There are three different software packages which are to be used namely the Rack configuration software for the purpose of configuring the data collector modules.The mathematical model of the individual components are elaborated to analyse vibrations. The mathematical model is based on Finite Element Method. After simulating the dynamic behaviour of the rotor-bearing system with the normal operating conditions, it is possible to predict the stability range based on the variation in values of stiffness and damping coefficients. With the help of the SCILAB code all the direct and cross coupled stiffness and damping coefficients are calculated and their dependencies on the Sommerfeld number are observed using various plots.

SadaShiva Bayya, I.S. Rajay Vedaraj .S , K Sivasubramanian

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