Identification of Abnormal Rotor Dynamic Stiffness Using Measured Vibration Information and Analytical Modeling

Abstract

It is a relatively common practice to address the problem of unacceptable synchronous (1X) vibration levels (like unbalance) by applying corrective balance weights after a thorough review of vibration measurements, available engineering information, and prior balancing history of a unit if available. The balance history might include balance plane weight maps and/or balancing influence data. On occasion, other vibration malfunctions and symptoms within measured vibration data, such as misalignment, a rub, or proximity probe journal target area slow roll (sometimes called “runout” or “glitch”) can also appear to be “unbalance” but are not. A principal requirement when performing any corrective balancing of a rotor is that the fundamental synchronous rotor response of the unit should always be linear and time invariant. The fundamental synchronous rotor response is directly proportional to dynamic forces and inversely proportional to dynamic stiffness. If the principle requirements cannot be met while balancing, any further balancing of the rotor should be terminated and other root causes for the unacceptable synchronous vibration levels should be investigated. This paper will discuss a case history involving a steam turbine generator unit where excessive synchronous vibration levels were measured at the LP turbine bearings during transient and steady state operation. The initial concern was a steady increase in vibration levels at the LP turbine under steady state conditions. Prior balancing history and balancing information was reviewed and initial corrective balancing was performed. Initial correction of the unbalance proved to be inadequate, and the unit exhibited a significant change in balance influence. Since the response of the rotor to balance correction was not predictable and inconsistent with prior balancing data, alternative root causes for the unbalance symptoms were investigated. Integration of measured vibration data and numerical modeling were essential with proper identification of the root cause of the unbalance symptoms.