Predictive maintenance has become a worldwide accepted practice and is being implemented and finely tuned by nearly every industry category.
Locating, defining, and acting on potential problems before they become catastrophic is the main objective of a predictive maintenance program. Routine monitoring is the most effective tactic for locating potential problem areas and can prompt invaluable follow-up inspections. Often, upon a thorough inspection with state-of-the-art equipment, numerous issues can be identified and rectified, thereby avoiding critical unplanned downtime and ensuring a more-efficient operation.
Monitoring motor performance with properly trained technicians using modern equipment allows plant managers to dictate their own downtime, improve plant operations, and quickly identify poorly performing equipment.
What to monitor
When establishing a new PdM program or enhancing an existing one, defining which motors should be monitored must be the first consideration.
Criticality, the number of starts and stops, starting loads, ambient temperature, ease of testing, manpower, and availability of spares are concerns that must be considered. Every situation is different and each requires individual considerations, but the main objectives and basic plans will be similar. Motors that have a history of poor performance should be monitored more often.
It is vital to the success of the predictive maintenance program that motor importance be defined, a routine schedule established and followed, and the indicated repairs and adjustments made in timely manner.
How to monitor
Predicting imminent motor failures requires knowledge, experience, and as many “tools” as are feasible to use. The more tools a technician has and uses properly, the more likely it is that he or she will be able to predict the health and longevity of the assets in use. Motor monitoring has become a vital tool with two facets that must be considered and fully utilized to obtain a successful diagnosis of the motor’s condition: offline testing and online monitoring.
The motor itself has numerous components, including copper winding wire, insulation systems, bearings, and other mechanical and electrical features that must be tested and trended. The insulation system consists of the very thin insulation manufactured onto the winding or magnet wire and the ground-wall insulation that protects the magnet wire in the slots. Off-line testing equipment can effectively assess the condition of these insulation systems, and when the data is properly trended, it will aid in predicting the motor’s ability to remain in service and whether and when repairs and/or adjustments may be indicated.
An effective offline test should consist of winding resistance, meg-ohm, high-potential, or step-voltage tests and surge tests. Winding resistance can locate shorted turns, open leads, and phase imbalance issues. The meg-ohm test will identify grounded and contaminated windings. The high-potential test looks for poor ground-wall insulation, and the surge test locates turn-to-turn or copper-to-copper weaknesses. It should be noted that the surge test is the only test that can identify weakness in the turn insulation long before such weakness becomes a hard-welded fault that will result in rapid winding failure.
Online equipment has become the tool of choice for many maintenance personnel, as it is safe, quick, and not intrusive, and it provides an enormous amount of information in one report. Online testers can locate electrical problems and many mechanical issues that might otherwise go undiagnosed. Often motors fail and are repaired or replaced and returned to service without determining the “root cause” of the failure. Online equipment can identify subtle issues with power quality such as harmonics, low or high voltage, and voltage unbalance situations. Rotor bar problems, bearing issues, misalignment and many other problem areas also can be identified. All of these can affect motor efficiency.
One major domain that is identified and tracked through motor monitoring is efficiency.
Efficiency is defined as the ratio of useful work performed to the energy expended in producing it (output power divided by input power). Efficiency is usually described using one of three metrics: nominal efficiency, operating efficiency, or minimum efficiency.
Nominal efficiency is that value assigned to a set or group of motors by the manufacturer and designated on the motor’s nameplate. Operating efficiency is the true efficiency of the motor as it is operating within its actual and normal environment. Minimum efficiency is the lowest efficiency value any motor within a “test sample” must maintain. Modern test equipment will define the operating efficiency of the motor being tested.
To understand efficiency, we must first understand how the values are derived and what the numbers mean to us. The Institute of Electrical and Electronics Engineers (IEEE) defines how motor manufacturers must measure and assign efficiency values to motors.
Basically, motors are randomly selected off the production or assembly line and tested on a “dyno” within a completely controlled environment. The voltage is clean and perfectly balanced; the load is dynamically controlled; and the test areas are separated from any possible vibration or sound interference.
A series of motors is measured and a mean average is determined. By definition, manufacturers are allowed a 20% window of the losses, which gets added to the mean average, and all motors within that set are designated with that efficiency rating.
Consider a hypothetical situation where 100 motors are being tested to determine nominal efficiency. Let’s say that some will test as high as 95% and the lowest as low as 93%, with a mean of 94.5%. The average losses are 5.5%, so the accepted 20% window would be 1.1%. This value gets added to the average of 94.5%, which brings the nominal efficiency for this set of motors to 95.6%, and that number gets “stamped” into each motor. This hypothetical case may be somewhat extreme, but it’s not an impossibility.
Why is efficiency important?
Why is motor efficiency so important to understand? Worldwide, motors consume between 55% and 63% of all electrical energy being produced. Recent U.S. Department of Energy reports show that energy costs could be cut by at least 18% by utilizing energy-efficient motors. Premium-efficiency motors have saved billions of dollars in energy costs each year, and manufacturers are continually looking for ways to make motors more efficient.
How does efficiency affect the cost of plant operation? Consider a 100-hp motor/load that is operating 24 hours per day and 365 days per year, where energy costs is $0.07 per kilowatt hour (kWh). A motor operating at 85% efficiency will use 795,118 kilowatts in that year at a cost of $55,588. Improving to 90% efficiency will lower the cost by $4,488 and reduce energy demand by 65,118 kWh. A motor operating at 95% efficiency will use just 691,579 kWh and cost $48,411 – a tremendous savings, and that is for just one motor.
Studies further confirm that efficient motors are more reliable and have an extended useful life expectancy.
How can efficiency be improved?
Motors are affected by numerous environmental, mechanical, and electrical issues, many of which can be rectified or improved. Low- or high-voltage issues are generally correctible through transformer taps, and harmonic issues can be mitigated with various reactors, shielded cables, and isolation transformers. Misalignment, imbalance, and other mechanical issues are generally easy fixes. Often, minor adjustments can add years to a motor’s life and result in big savings thanks to improved efficiency.
Additionally, the costs of replacing poorly performing motors with premium-efficiency motors will be quickly offset by the savings in energy costs.
Energy costs are a major portion of any facility’s operating expenditures, and in a plant, motors account for the majority of those expenses. Monitoring motors’ performance and making necessary adjustments will improve reliability, extend the life of the motor, and reduce the facility’s overall operating cost.