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Today’s condition monitoring programs that wish to advance towards true “Reliability Centered Maintenance” (RCM) must incorporate more than one technology into their diagnostic tool kits. No longer can an organization expect to do this while “putting all their eggs into one basket”.
At one time, most industrial condition monitoring programs included only vibration analysis. And, in so doing, these programs were typically at least moderately successful, particularly if their condition monitoring teams received professional training which is vitally needed in order to truly become proficient in the application of vibration analysis technology. Many engineers and managers of that era felt that vibration analysis alone was sufficient to achieve their reliability objectives and every machine type could be effectively evaluated and faults reliably detected on components within these machines by vibration analysis alone. Vibration analysis was eventually proven effective for certain machine types in its capability of evaluating the condition of some of the more complex machinery types including centrifugal air compressors, rotary screw air compressors, roots blowers, multi-stage gearboxes, AC and DC motors, turbine/generators, boiler feed pumps, low-speed agitators, rolling mills, machine tools, etc. However, now it has become conclusive that an integrated approach employing more than one condition monitoring technology has proven to be noticeably more effective.
However, despite the determined efforts by numerous people in the vibration analysis field, certain machine types for the most part still cannot be adequately evaluated by vibration analysis alone (at least to the depth desired). These machines include reciprocating air compressors, diesel engines, internal combustion engines, greased motor operated valves, presses, piston type hydraulic pumps, etc. And, even in the case where vibration analysis can effectively evaluate the condition of the machinery mentioned above, adding oil analysis to condition monitoring programs has given us a much more complete picture. Oil analysis has actually detected certain problems within these machines before they are evident in vibration analysis data - particularly on multi-stage gearboxes, plain bearings, rotary screw air compressors, roots blowers and on certain rolling element bearings which might be located distant from an accelerometer mounting location.
Figure 1 is an important illustration developed by specialists at Noria Corp. (ref. 8). This illustration correlates Oil Analysis observations with the 4 rolling element bearing failure stages detected by vibration analysis. Note that several factors can be observed in the oil analysis photos as the bearing transitions from Failure Stage 1 through Failure Stage 4. First, there is an increase in particle count; likewise in ferrous density and in percent large particles; and a corresponding increase in contact fatigue particles. Importantly, note that while vibration data alone cannot detect problems during Failure Stage 1, Oil Analysis can do so as shown by the text and photos in Figure 1.
Building the case for technology integration
The focus of this paper is on how integration of just one of these tools with vibration analysis has greatly enhanced the reliability and effectiveness of condition monitoring programs - oil analysis. Actually, the oil analysis technology has been around for many years. The problem was that numerous condition monitoring teams were either not aware of oil analysis; or, if plants did have personnel assigned to perform oil analysis, these persons in most cases did not interface with the vibration analysis condition monitoring teams on the same plant site. The decade of the 1990's has fortunately seen a great shift in this trend. At least some plants have seen the wisdom in adding oil analysis to vibration monitoring to enhance their machine condition monitoring programs. Likewise, several vibration condition monitoring vendors have begun to expand their offerings to incorporate oil analysis products, services and data management. Some vendors have upgraded their software to incorporate oil analysis data into their databases to provide the analyst with a much more complete picture of the operating condition of machinery under his watchcare using these combined detection tools. With the combined offering, they are better positioned to make more effective decisions and recommendations.
In fact, one comprehensive study at a nuclear plant beginning in 1994 clearly showed how the integration of oil analysis with vibration analysis could widen the depth and breadth of a plant condition monitoring program (refs. 2 & 3). Table-1 is a meaningful comparison of the relative strengths and weaknesses of oil analysis and vibration analysis. Likewise, it provides insight into how the results of one technology can complement those of the other.
Importantly, please note from Table-1 that when oil analysis and vibration analysis are "married" within a program, the weaknesses in one technology can be overcome by the strengths in the other. For example, while oil analysis cannot detect resonance, vibration analysis is very adept at doing so. Conversely, while vibration analysis has only mixed success in detecting wear of oil lubricated journal bearings, oil analysis is very adept at detecting the wear debris in the lube and assessing the severity, thereby helping the plant make the important decision on whether or not they should continue to operate the machine. Also, when both technologies pinpoint the same problem, the diagnosis and follow-up recommendations are rarely inaccurate. The authors of ref. 2 made the statement: "Our experience shows that a strong, up-to-date vibration program can be improved by closely integrating it with a strong oil analysis program. The combined program becomes more than the sum of the parts".
The complement between the two technologies continues. For example, note from Table-1 that while vibration analysis can pinpoint which gear might have a problem, oil analysis can predict the type of failure mode. Also, Table-1 shows that oil analysis will detect defects on rolling element bearings during Stage 1 as previously discussed whereas vibration analysis typically cannot see the problem until Failure Stage 2.
Having this information in hand from both technologies facilitates the process of determining the root cause of a problem. In doing so, the program is elevated to a more proactive capability. In fact, a condition monitoring program is not truly effective until it has put into place a "Root Cause of Failure" analysis process to continually identify the failure/problem source(s), allowing proper corrective actions to be taken which can prevent the problem(s) from repeatedly occurring.
A review of some of the data available today reveals several important facts about the need to integrate oil analysis and vibration analysis:
• Early Detection of Rolling Element Bearing Problems — Oil analysis is typically more adept in detecting early bearing failure conditions. When both technologies detect faults, problem diagnosis and its assessment is rarely incorrect (ref. 2).
• Effect of Integrating Oil and Vibration Analysis — Integrating oil and vibration analysis can allow early detection and trending of numerous problems to which a machine can be subjected. Ref. 5 states: “Detecting the faults is the first step in the diagnostic process. Early fault detection yields benefits in diagnostic time, avoidance of unplanned down-time, elimination of chain reaction failures, and improved precision of maintenance actions.” Often, stopping a machine and repairing a single component can prevent this problem component from adversely impacting adjacent machine parts, thereby avoiding costly (and potentially catastrophic) failure (ref. 5).
• Root Cause Failure Analysis - Ref. 5 states "Both oil analysis and vibration analysis are required to effectively determine root cause failure. Confidence in maintenance and operations decisions is substantially improved when both methods are employed".
• Condition of Lubricating Fluid - Ref. 4 states "The life of the machinery is in the lube". Oil analysis is required to assess the quality of this "life blood", no matter what the type of machine it might be.
Our experience has led us to make the following conclusions about oil analysis:
1) The leading indicator of gear problems is oil analysis. In fact, in one case, a wear problem initially detected and trended by lube analysis was not detected by vibration analysis for approximately 6 months; it then trended in both technologies for approximately another 18 months until it was decided corrective actions were necessary.
2) Oil analysis is effective on large motors outfitted with plain bearings (particularly on motors greater than approximately 1000 HP). Oil analysis has proven a better and more reliable tool at detecting problems with wear of sleeve bearings on many machine types than has vibration analysis (on the other hand, vibration analysis is still the tool of choice to detect other plain bearing problems including oil whirl and oil whip).
Since adding oil analysis to our “condition monitoring arsenal”, we have attempted to employ the following policy with condition monitoring clients: if a gearbox is considered critical whatsoever, oil analysis should be considered mandatory since it is often difficult with vibration analysis to clearly differentiate between actual gear wear versus gear tooth shape (profile) or tooth orientation problems (i.e., tooth misalignment, eccentricity and/or excessive backlash). Plus, in some gearboxes, oil analysis is able to differentiate wear from gears versus wear coming from bearings within the same machine. Research performed at Monash University in Victoria, Australia unveiled some important findings on condition monitoring evaluation of gears (ref. 6).
Building an Integrated Condition Monitoring Program
The plant can incorporate oil analysis into its program in several ways by collecting oil samples and sending them off-site for analysis, by employing on-site instruments for oil analysis, or by a combination of both strategies.
Certain “in-shop” oil analysis equipment can now provide very rapid answers (in less than one hour) in confirming wear problems (ref. 4). However, on-site analysis does require some investment in hardware, software, and in training. Management should review its options carefully before proceeding. Following is suggested:-
1. The entire condition monitoring team performing all technologies has been brought together in one common area allowing much information transfer and improving the accuracy/reliability of diagnostic calls as well as root cause analysis;
2. All condition monitoring personnel report to a single plant program manager who himself directly reports to plant management (providing him the ear of both maintenance and production plant management);
3. All condition monitoring personnel are "cross trained" in at least one other condition monitoring technology giving them greater confidence and understanding of the other technology;
4. All condition monitoring personnel work full time in their field (they may occasionally assist in performing certain corrective actions, but are not expected to do this on a regular basis);
5. All condition monitoring personnel receive formal training in their areas of expertise at least one week per year in order to keep them up to date and to further advance their knowledge which is of immediate benefit to the plant. Audits through the years have proven there is a direct correlation of program effectiveness to the quantity and quality of continuing training condition monitoring team members receive.
Conclusions
• Is vibration analysis a powerful condition monitoring tool? You'd better believe it!
• Is oil analysis likewise a powerful condition monitoring tool? Ditto.
• Does one technology "fill the gaps" left open by the other? Yes, they do.
• In other cases, does it improve the confidence and credibility of the analyst if both tools diagnose problems on a critical machine? Absolutely.
• Only one question remains - If you have only employed one of these powerful tools in your own program to date, why not significantly enhance the effectiveness of your program by adding its "complementary cousin" to your program? You and your plant management will be glad you did.
References
1. Berry, James E., P.E.; “Tracking of Rolling Element Bearing Failure Stages Using Vibration and High Frequency Enveloping and Demodulation Spectral Techniques”; Analysis II - Concentrated Vibration Signature Analysis and Related Condition Monitoring Techniques (2nd Edition); Technical Associates of Charlotte, P.C.; Charlotte, NC; 1997.
2. “Integration of Lubrication and Vibration Analysis Technologies”; by Bryan Johnson and Howard Maxwell; Pale Verde Nuclear Generating Station.
3. “Vibration and Lube Oil Analysis in an Integrated Predictive Maintenance Program”; by Howard Maxwell and Bryan Johnson; Pale Verde Nuclear Generating Station; Arizona Public Service; Phoenix, AZ; Vibration Institute Proceedings; June 17-19, 1997.
4. “Case Histories and Cost Savings: Using In-Shop Oil Analysis for Industrial Plant Applications”; by Ray Garvey; Application Paper, Computational Systems, Inc.; 1994.
5. “Effective Integration of Vibration Analysis and Oil Analysis”; by Drew D. Troyer; Maintenance Technology Magazine; pages 17-21; November, 1998.
6. “Comparison of Vibration and Direct Reading Ferrographic Techniques in Application to High- Speed Gears Operating Under Steady and Varying Load Conditions”; by J. Mathew and J. S. Stecki; Monash University; Victoria, Australia; Presented at the 41st Annual Meeting of the Society of Tribologists and Lubrication Engineers in Toronto, Ontario, Canada; pages 646-653; May 12-15, 1986.
7. “Integrating Oil Analysis with Entek For Windows”; by Alan Bern; Texas Utilities Electric; Presented at Enteract '97; April 28-30, 1997.
8. “Good Vibes About Oil analysis”; by James E. Berry, P.E.; Practicing Oil Analysis Magazine; pages 31-39; November/December, 1999.
OIL ANALYSIS OBSERVATIONS
Initial Stage
• Slightly increasing particle count, especially at the small particle range.
• Slightly increasing ferrous density (WPC), but no major change in the percent large particles (PLP).
• Slight increase in elemental iron might be seen, especially if the sample is acid / microwave digested.
• Photomicrograph shows presence of small (<30 microns) platelet shaped, contact fatigue particles.
Second Stage
• Increasing particle count.
• Increasing wear density (WPC) and increasing percent large particles (PLP).
• Elemental iron may remain stable unless the sample is acid or microwave digested.
• Presence of platelet-shaped contact fatigue particles with increasing size (say 30-50 microns, depending on filtration) and density.
• Possible presence of spherical particles.
Third Stage
• Substantial increase in particle count
• Substantial increase in ferrous density (WPC) and in present large particles (PLP)
• Minor increase in elemental iron unless the sample is acid or microwave digested.
• Photomicrograph image reveals large particles (above 30 microns) are appearing in great numbers, both platelets and cutting wear. More and more particles are appearing to have three dimensional shape.
Final Stage
• Further increasing particle count.
• Very high ferrous density (WPC), especially the percent large particles (PLP).
• Minor increase in elemental iron unless the sample is acid or microwave digested.
• Photo image reveals large chunky and fatigue particles, some in excess of 75 microns depending on filtration. Low alloy steel particles may appear blue due to the high heat associated with failure in the final stage of the bearing's life. Some particles may become visible to the naked eye just prior to failure. Particles generated from cage material, primarily cutting wear, will begin to appear.
Figure 1: Correlation of oil analysis observations with the 4 bearing failure stages detected by vibration analysis (Ref. 8)
TABLE I: CORRELATION AND INTEGRATION
OF LUBRICATION AND VIBRATION DATA
* Source: Integration of Lubrication and Vibration Analysis Techniques by Bryan Johnson and Howard Maxwell; Pale Verde Nuclear Generating Station (Ref. 2)
Shashank Singhal
S Pola
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