Identification of misalignment and bow parameters in rotating machinery models

Author(s)

Lucas Ward Franco de Camargo

• Document type: Master's Dissertation
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Mecânica
• Defense date: 2010-03-29

Examining board members

Katia Lucchesi Cavalca Dedini; Alberto Luiz Serpa; Domingos Alves Rade

• Advisor: Katia Lucchesi Cavalca Dedini; Hélio Fiori de Castro

Abstract

The study of rotating machinery occupies an outstanding position in the study of machinery and structures due to the significant amount of phenomena that occur in the operation of these equipments. This work is focused on the study of rotating systems supported by hydrodynamic bearings (with or without a flexible coupling connecting the driving motor and the driven shaft), mainly considering faults that can commonly occur in these systems (misalignment, bow and unbalance) as the presence of multiple faults in a real machine is a common situation. The perfect balance and alignment of the machine cannot be achieved in practical applications. Consequently excitation forces are generated at these systems, which significantly affect the operation of the machines. In this way, the influence of the unbalance, bow and misalignment on the vibration amplitude is an important consideration, specially the effect of the harmonic components that can rise when a machine is misaligned. To mathematically represent the system, a finite element model is used and the analysis is held in the frequency domain. The coupling is also modeled as a finite element and the misalignment, bow and unbalance forces are included in the fault model. Noise is added to the simulated results to build a possible experimental result and, in order to identify the fault unknown parameters, the multi-objective genetic algorithm is proposed. The individual analysis of each objective function (difference between simulated and adjusted results) allows the identification of an optimal set of solutions resulting in the identification the fault parameters (AU)