September 8, 2015 By je-bearing.com
A crucial factor in the proactive maintenance of high-voltage (HV) motors and generators, especially those in critical industrial applications, is the condition assessment and remaining life expectancy of the stator windings. HV motors and generators are typically custom-made and are not quickly replaceable should an unexpected failure occur. This means that corrective maintenance is very time-consuming and the operator can experience extensive periods of costly, unforeseen downtime.
How can such problems be predicted and avoided?
Various tests and inspection methods are used to gather useful intelligence on the condition of stator winding insulation. A DC test for example helps ascertain the cleanliness of the winding based on the IR (insulation resistance) and PI (polarization index) measured. However in practice, it has been seen that contamination could still be observed in a winding in spite of acceptable IR and PI values.
Traditional measurements such as IR/PI and Tan delta measurements depend on measured value trends for drawing out any meaningful information. This implies that periodic measurements need to be done, and the measurement condition needs to be the same at the time of each measurement. Any change in measurement condition, such as quality of power, can change the trend and render it useless.
Large motors and generators of 2 MW rating and up are designed for high power, and they exhibit a relatively higher proportion of winding failures than lower power designs. Based on figures from an IEEE survey, 33 percent of all failures detected during normal operation are related to the stator winding. However, the corresponding figure for failures detected during maintenance or testing is only 8 percent.
This survey clearly highlights the wide gaps in the existing measurements and inspection methods for identifying stator winding insulation problems proactively.
Before attempting to make any assessment on insulation health or its remaining life, it is important to first understand the stresses that influence them. Any measurement method or inspection should be able to cover all stress-related aspects so as to make a correct prediction.
The different type of stress that act of stator winding insulation at any given time can be classified as TEAM – thermal, electrical, ambient and mechanical.
At the heart of any life cycle management approach for motors and generators is the understanding of how TEAM stresses and insulation strength vary over time and their possible effect on device material.
The degradation of stator winding insulation can be described in general terms by using two curves to demonstrate how stress and strength change over time.
Scientifically predicting the residual life of a stator winding insulation involves a number of steps.
Before any analysis of a motor or generator’s future prospects can be made, its present condition has to be determined. This demands knowledge of basic parameters such as operating hours, loading, number of starts, duty cycle, temperatures, maintenance history, etc. All of these factors have an impact on condition assessment/life expectancy and must be collected and included in the analysis.
However, not all data is available from specification sheets and motor or generator logs. A stator winding insulation, at different stages in the aging process, has properties that can only be explored through measurements. Four measurements that are strongly recommended are:
PDCA – Polarization depolarization current analysis
TDCA – Tan delta capacitance analysis
Partial discharge analysis
NLIBA – Nonlinear insulation behavior analysis
PDCA provides considerably more information than the more commonly used insulation resistance (IR) and polarization index (PI) measurements. PDCA is a DC method in which the winding insulation is initially charged and then discharged through a low-current meter to ground.
From these measurements, it is possible to derive a charge storage value for winding insulation and compare it to reference values for normal conditions. This allows more comprehensive analysis than if only PI and IR were utilized and the method can deliver satisfactory values even with highly contaminated windings. PDCA gives an idea of the quantity and location of charge storage within the motor or generator insulation and identifies contamination on the winding surface. It also provides additional insights into the state of the winding insulation, including possible aging and looseness.