SPECTROMETRIC OIL ANALYSIS Detecting Engine Failures Before They Occur It has been estimated that in the U.S. economy the damage done by wear alone represents about 6% of the gross national product (1). Thus, the development of effective techniques for the reliable analysis of wear metal debris is of substantial interest to analytical chemists. Traditionally, spectrometric oil analysis has been performed in a manner that is generally unsuitable for the reliable detection of severe wear. The analyst simply takes a sample of lube oil from the equipment to a spectrometer and runs it.
The analytical data obtained in this manner may not reflect the extent of internal wear within the oil-wetted system being monitored, particularly when a component is undergoing extensive wear that will soon lead to catastrophic failure. These errors in analyses are especially critical when the equipment being monitored is an aircraft, particularly a single-engine aircraft whose engine is about to fail inflight, catastrophically, with the potential loss of both aircraft and crew. Undetected failures both of aircraft
1086 A · ANALYTICAL CHEMISTRY, VOL. 56, NO. 9, AUGUST 1984
and ground equipment can also result in substantial cost outlays and unplanned downtime once the equipment fails. Most analysts are not aware of the multitude of factors that affect the quality of data obtained in wear metal determinations. In this article we will discuss several of these factors and summarize the results of recent research that bear directly on the quality of the analytical data obtained, in the hope that it will be of value in the numerous applications of wear metal determinations. 0003-2700/84/A351 -1086$01.50/0 © 1984 American Chemical Society
The Analytical Approach Kent J. Eisentraut Rebecca W. Newman Air Force Wright Aeronautical Laboratories United States Air Force Wright-Patterson Air Force Base, Ohio 45433
Costandy S. Saba Robert E. Kauffman Wendell E. Rhine University of Dayton Research Institute Dayton, Ohio 45469
Spectrometric oil analysis was first applied by the railroads in the early 1940s in an effort to detect wear in diesel locomotive engines. The technique was later adopted by the U.S. military. In the early 1960s spectrometric oil analysis was applied successfully to the detection of wear in turbojet aircraft engines by the U.S. Air Force. Considering the tremendous cost savings to be achieved in reduced maintenance and repair activities, as well as improved operational reliability of weapon systems, the Air Force has maintained a continued interest in research to improve the capability to detect and identify the extent of aircraft engine internal wear. Currently, the U.S. military services use rotating-disk electrode atomic emission spectrometry (RDE-AES) and, to a much lesser extent, flame atomic absorption spectrophotometry (AAS) as primary analytical techniques for wear metal determinations. Both of these techniques as currently applied have limitations in providing accurate data for wear metal content of engine oil samples (2-8).
Interferences Emission spectrometry may suffer from interelement and matrix interferences. Interelement interferences cause enhancement or suppression of the analytical signal due to the presence of concomitant elements in the sample or standard. The normal procedure is to calibrate the spectrometer with a multielement standard and then analyze samples that may contain one or more of these elements. This procedure can lead to errors, as depicted in Table I. Matrix interferences may be caused by differences in chemical composition between the standard and the sample to be analyzed, as shown in Figure 1. The data
Figure 1. Concentration of Fe determined by RDE-AES in different lubricating oil matrices
shown in this figure represent the RDE-AES readout in ppm Fe for the same 20-element Conostan standard in different lubricating oil matrices. When the instrument is standardized with the 20-element standard in Conostan 245 base oil, 100 ppm of Fe reads 100 ppm. When the same concentration of iron is determined using the same 20-element standard in different oil matrices, the concentration of Fe indicated on the spectrometer readout increases. For example, with MIL-L-23699 lubricating oil as the
20-element standard matrix, the 100ppm Fe standard reads approximately 200 ppm Fe.
Wear Particle Detection A further limitation of AES and AAS for wear metal determinations is that both techniques are affected by the particle size of the wear metal. In actual oil samples the wear metal can be present as dissolved species or range to millimeter-sized particles. The detection and identification of metallic particles in the lubricant are
ANALYTICAL CHEMISTRY, VOL. 56, NO. 9, AUGUST 1984 · 1087 A
Table I. Effect of Concomitant Elements on RDE-AES a Element
Wavelength (A)
Cone, (ppm)
Element
Ag AI Ba Be Cd Cr Cu Fe Mg
3281 3028 4554 2651 2265 4254 3274 2599 2803
137
Mn Mo Na Ni Pb
97
166 95 210 85 185 134 106
Si
Sn Ti V
Wavelength (A)
2576 2816 5896 3415 2833 2516 3175 3349 4379
Cone, (ppm)
131 170 191 142 133 107 126 148 94
a RDE-AES readout of single-element standard of 100 ppm in MIL-L-7808H synthetic oil Instrument calibrated with 20-element standard in MIL-L-7808H synthetic oil at 100 ppm.
of critical importance because their presence is indicative of engine oilwetted component wear. Another crit ical factor is that the presence of me tallic wear particles can in turn fur ther degrade component surfaces. The
inability to detect large wear particles has led to engine component failure without prior indication by spectrometric methods. Several cases have been documented where large metallic wear particles produced by severe-
wear mechanisms have not been quan titatively determined by the spectrometric techniques employed (6,8-11). Both AES and flame AAS techniques are limited in their ability to quantita tively determine metal particles in oil samples when the particle size is larg er than ~ l - 8 fim, depending on the specific metal. The limitations for iron metal pow der are shown in Figure 2. In this fig ure the concentrations of iron detect ed directly with various spectrometric techniques are plotted against the particle size of iron present in the sample. These data should be com pared with the actual concentration present as determined by acid dissolu tion of the Fe particles using the parti cle-size-independent method (PSIM) (6). The only analysis technique capa ble of directly determining iron parti cles of submicrometer to ~20-30-μιη size (unfiltered) is graphite furnace atomic absorption (HGA). Flame AAS using nitrous oxide-acetylene and in ductively coupled plasma atomic emission spectrometry (using the FAS-2PL spectrometer) both deviate from the PSIM curve as the Fe parti cle size exceeds ~ 1 μηι. The rotatingdisk electrode atomic emission spec trometers (A/E35U-3 and A/E35U-1) are intermediate in capability and the dc argon plasma spectrometer (SMIIII) is slightly more efficient. The par ticle size detection limitation poses the serious potential problem that an aircraft engine undergoing severe wear may not be identified. Sample Introduction Systems
Figure 2. Comparison of the detection of Fe particles by various spectrometers with the acid dissolution method (PSIM) 1088 A · ANALYTICAL CHEMISTRY, VOL. 56, NO. 9, AUGUST 1984
One of the major reasons for parti cle size detection limitations of these analytical spectroscopic techniques is the inefficiency of the sample intro duction systems used in many flame AA and plasma atomic emission spec trometers (7). Many of these sample introduction systems incorporate neb ulizer-spray chamber systems, which were designed for transporting homo geneous samples and are quite ineffi cient when applied to samples that contain suspended metal particulates. The larger wear particles collect on the walls of the spray chamber and are washed into the sample drain or waste container. Only the relatively small particles find their way into the sam ple excitation region. The rotatingdisk electrode is also an inefficient particle transport system because its efficiency depends on the settling rate of particles (12). The settling rate of particles depends on the lubricant's viscosity as well as the particle's den sity. Therefore, heavy metal particles, such as Ag and Mo, settle rapidly and are not transported to the source, whereas ΙΟ-20-μπι particles of the
Figure 3. Comparison of percent recovery of metal particles with and without acid
lighter elements, such as Mg and Al, are transported to the source where they can be detected. In addition, the power of the spark-arc source is not sufficient to vaporize metal particles in the oil matrix (12). AAS
Flame AAS as currently employed by the Air Force for wear metal deter minations is accomplished in a se quential manner and is not well suited to heavy sample workloads. Further more, the present instrumentation is not rugged enough to be transported easily and requires shipment and han dling of flammable gases. These fac tors, along with the severe particle size dependency of flame AAS, render the technique unreliable for accurate analysis of wear metal particles of the sizes expected from severe wear. One technique, the electrothermal analyzer as applied in graphite fur nace AAS, permits the physical intro duction of the sample directly into the
furnace by means of a micropipet. This technique has been found to be capable of determining metal particles of sizes in the 20-30-μηι range (13). Because of the deficiencies of flame AAS, the Air Force is currently sup porting the development of a rugged simultaneous multielement AA spec trophotometer based on electrother mal atomization for use as a portable wear metal analyzer (14,15). This de vice is used primarily for oil sample analysis of aircraft deployed at loca tions away from fixed laboratory spec trometers. Particle-Size-Independent Techniques
Inasmuch as severe wear can pro duce metal particles of sizes that can not be detected by these spectrome ters, alternate approaches are re quired. One approach to this problem has been the development of particlesize-independent techniques for wear metal analysis by flame AAS and AES
1090 A · ANALYTICAL CHEMISTRY, VOL. 56, NO. 9, AUGUST 1984
(4-6, 8). These methods simply re quire shaking a small amount of an acid solution with the used oil sample prior to spectrochemical analysis. Initial requirements for particlesize-independent analysis surfaced ap proximately 10 years ago when several fighter aircraft experienced gas tur bine engine failures that were unde tected by oil analysis. The reason for these engine failures was abnormal wear of Ti components within the oilwetted system of the engines. It was soon discovered that direct flame AA analysis of the oil samples from these engines was not capable of detecting this severe Ti wear situation. A simple procedure was developed whereby a diluted oil sample containing Ti wear particles is shaken for 10 s with a small quantity of a mixture containing HC1 and HF (4). The acid contact re sults in dissolution of the Ti particles. Only 0.15 mL of acid is required for a 15-g diluted oil sample, and no phase separation is apparent. The oil sample containing the dissolved Ti and excess acid can then be analyzed directly with reliable results by flame AAS for Ti using a nitrous oxide-acetylene flame. A similar procedure was later developed for Mo determinations (5). It soon became evident that wear par ticle detection was a general problem that was not specific to Ti or Mo and that a more universal procedure was required. The most widely used of these ap proaches (8) has application to air craft, automobile, and diesel truck en gine oils as well as aircraft hydraulic fluids for the particle-size-indepen dent analyses of 12 common wear met als. Figure 3 demonstrates the effec tiveness of this multielement acid dis solution method (MADM) by compar ing the percent recoveries of suspen sions that contain 13 metal powders by direct analysis of the suspensions (no acid) and by MADM analysis. The suspensions were prepared using 325mesh (44-μπι) or 200-mesh (74-μιη) metal powders. All data were obtained using the direct current plasma (DCP) spectrometer. The results represent triplicate analyses of the suspensions. The shaded area represents the stan dard deviation of the analyses. Table II compares data for two air craft engine oil samples obtained di rectly (without acid dissolution of the wear particles) using flame AA, DCP, and RDE atomic emission with the re sults obtained on the same samples using MADM and DCP. In the table, the RDE values are artificially higher because they include the influence of the previously described interelement and matrix effects. A specific embodiment of the acid dissolution approach is found in a por-
Table II. Comparison of Direct Analysis vs. Multielement Acid Dissolution Method (MADM) for Authentic Aircraft Engine Oil Samples Direct analysis
Direct analysis
Ag AI Cu Fe Mg
AA
DCP
RDE
DCP
1.3 1.6 5.6 21.2 9.8
1.8 2.1 7.0 28.9 11.5
1.0 4.3 15.6 61.3 31.0
4.9 8.0 21.0 81.3 25.3
Engine: T56 Aircraft: C-130E Hours since overhaul: 1123 Hours since oil change: 400
table, easy-to-operate, low-cost colorimetric Fe kit (16-18). This kit, which provides a readout directly in ppm of Fe, was developed and tested to provide a go/no-go flight decision based on iron wear metal content of the lubricating oil of aircraft deployed at remote locations. Standard Selection
Another factor of primary concern in spectrometric oil analysis is the selection of a standard. Traditionally, metalloorganic compounds have been used as standards for spectrometric wear metal analysis. Care should be taken to match the standard oil matrix with that of the sample to reduce matrix effects on the analysis. Problems can occur particularly in plasma spectrochemical analysis when metalloorganic standards are used. Although the viewing position of the plasma is normally fixed, it has been
AA
DCP
RDE
Ag 4.2 5.7 Cr 14.4 27.3 Cu 136.8 271.0 Fe 105 286 Mo 0.1 1.6 Si 48.9 50.9 Engine: J-85 Aircraft: T-38 Hours since overhaul: 2208 Hours since oil change: 1
6.5 21.5 314 361 7.5 69.9
found that the maximum emission position of the DCP can be quite different for a given metal when comparing the emission from a metalloorganic compound with, for example, a powdered form of the same metal, as seen in Figure 4 for the case of Fe and Al (2). Even when using high-purity metal powders as standards, the maximum emission region of the DCP is at a higher position for larger particles relative to smaller particles of the same metal (2). These factors also contribute to difficulty in achieving accuracy when determining wear metals of unknown size distribution in a used oil sample. This can be a no-win situation for the analyst. Does the operator optimize the plasma height for the metalloorganic standard or for each sample, which may contain different particle size distributions of different metals? Even when using high-purity, small-particle-size metal
Figure 4. Effect of dc plasma observation height on metal particle detection 1092 A · ANALYTICAL CHEMISTRY, VOL. 56, NO. 9, AUGUST 1984
MADM DCP
10.0 38.1 546 394 17.7 71.6
powders suspended in oil as standards, the viewing position for maximum emission of a sample may be different depending on the particle size distribution of that sample (2). Unless the acid dissolution method is used, great care must be taken in the selection of any standard. All of these factors substantially reduce the appeal of direct sample analysis. Sampling
It is imperative that proper sampling techniques be used when an oil sample is taken, to ensure that the sample removed is representative of the total quantity of lubricant and wear in the system. The best analysis is worthless unless the sample has been removed from the engine in the proper manner. Once the sampling is complete, it is essential that the integrity of the original sample be maintained until all analyses are complete.
It has been observed that agglomera tion of wear debris occurs when the oil sample stands in the sample bottle. It is essentially impossible to redistri bute this material in suspension in the oil by hand-shaking once agglomera tion takes place. Agglomeration can occur between the time the oil sample is removed from the engine and the time an aliquot of the oil sample is taken for analysis. To ensure that the first sample removed from the con tainer is identical to the last, particu larly if sampling occurs over a pro longed period of time, it is necessary that the agglomerated material be redistributed upon each sampling. Re distribution may be accomplished by placing the oil sample container in an ultrasonic bath for 20-30 min. If ag glomeration occurs and ultrasonic agi tation is not used, the resulting analy sis will not reflect the actual wear of the engine, because the agglomerated material will remain in the sampling container and not be present in the al iquot taken for analysis. Other techniques have also been ap plied to wear metal determinations. Particle counting, scanning electron microscopy, and ferrography, for ex ample, all contribute useful informa tion on the extent of wear in lubricat ed equipment. Particle counting can provide a reliable indication of the ex tent of particulate contamination by defining the particle size distribution in a used oil sample (19). Unfortu nately, particle counting alone cannot distinguish between metallic and nonmetallic debris. In some cases, how ever, the particle count can be very helpful in detecting nonmetallic seal deterioration in gas turbine engines when combined with determination of wear metals in the oil sample (20). Ferrography (21) and scanning elec tron microscopy (21,22) can be useful techniques for determining wear par ticle morphology and in relating it to the specific type of wear that is occur ring. Ferrography is a technique that magnetically deposits particles ac cording to their size. The particles de posited form a dark band and their size distribution can be determined by measuring the optical density at vari ous points of the band. Qualitative de termination of the nature of wear metal debris can be made when the ferrogram is examined using a bichromatic microscope. It is possible to dis tinguish among metal particles, metal oxides, and other compounds present. Significant information about the composition of wear particles can be obtained by progressively heating the ferrogram and observing the changes in the appearance of the particle. These changes are characteristic of the type of particles being heated (23). Although information may be ob
tained with an optical microscope, ex amining the particles with a scanning electron microscope (SEM) provides a better study of particle morphology because of the SEM's greater depth of focus. If the SEM is equipped with X-ray energy analysis, the particle composition can be determined. This additional capability allows the identi fication of the wearing components.
Chemical Nature of Wear Debris Perhaps one of the most exciting re cent developments in wear metal anal ysis is the ability to obtain useful in formation on the chemical form of metal in the wear debris of used oil samples (24). A procedure has been developed that employs solvent ex traction and spectrometric analysis to determine the concentration of metal lic species in used lubricating oils. Using this technique, one can obtain important information on the cause of the presence of a given metal in the oil, as well as the approximate particle size distribution of the wear species present. For example, the form of wear metal present may be the metal (mechanical wear), the metal oxide (oxidative corrosion), dissolved or par ticulate organometallic compounds (chemical corrosion), or a combination of any of these. For the first time, using this technique, information can be obtained that permits an inside view about what may be happening within the engine's oil-wetted system and about what corrective action may be taken. The preceding discussion represents the state-of-the-art technology, which in large part can be applied to present wear metal analysis problems. To meet the needs of the Department of Defense oil analysis laboratories in the future, the Air Force is sponsoring a feasibility study to identify the opti mal instrumentation to upgrade fixed laboratory spectrometers currently used for analyzing aircraft engine oil samples. Desirable features of this in strumentation include simultaneous multielement capability, rapid sample turnaround time (19 elements/min), direct analysis capability (i.e., particle size independence and elimination of a requirement for sample pretreatment), and adaptability to a wide dy namic range (for application to oils of varying origin, from aircraft to ground equipment). In addition to lower costs associated with procurement and sub sequent maintenance of these instru ments, goals for the new generation of spectrometer emphasize elimination of manual operation through micro processor control and reduced depen dency on operator skill, for example through automatic alignment and cali bration procedures. Moreover, a high degree of instrumental reliability in
1094 A · ANALYTICAL CHEMISTRY, VOL. 56, NO. 9, AUGUST 1984
conjunction with ease of data handling (via automated interfacing with cen tral data banks) is required for accu rate trend analyses and early predic tion of oil-wetted component failures in turbine engines.
References (1) Rabinowicz, E. Lubr. Eng. 1982,39, 738. (2) Eisentraut, K. J. et al. In "Proceedings International Symposium on Oil Analy sis"; Bundesakademie fur Wehrverwaltung und Wehrtechnik: Mannheim, F.R.G., 1978; p. 95a.09.02. (3) Lukas, M.; Giering, L. P. In "Proceed ings International Symposium on Oil Analysis"; Bundesakademie fur Wehrverwaltung und Wehrtechnik: Mannheim, F.R.G., 1978; p. 95a.01.02. (4) Saba, C. S.; Eisentraut, K. J. Anal. Chem. 1977,49,454. (5) Saba, C. S.; Eisentraut, K. J. Anal. Chem. 1979,51,1927. (6) Brown, J. R. et al. Anal. Chem. 1980, 52 2365 (7) Saba, C. S.; Rhine, W. E.; Eisentraut, K. J. Anal. Chem. 1981,53,1099. (8) Kauffman, R. E. et al. Anal. Chem. 1982,54,975. (9) Lee, R., JOAP Technical Support Cen ter, Naval Air Station, Pensacola, Pla.; personal communication, 1979. (10) Kagler, S. H.; Jantzen, E. Fresenius Z. Anal. Chem. 1982,310,401. (11) Westcott, V. C; Seifert, W. W. Wear 1973 23 239 (12) Rhine, W.E.; Saba, C. S.; Kauffman, R. E. In "Proceedings International JOAP Symposium"; Pensacola, Fla., May 1983; p. 379. (13) Saba, C. S. et al., presented at the Pittsburgh Conference on Analytical Chemistry and Applied Spectroscopy, Cleveland, Ohio, 1979; Paper 62. (14) Newman, R. W.; Niu, W. H.; O'Con nor, J. J., presented at the International Oil Analysis Symposium, Pensacola, Fla., May 1983. (15) Niu, W. H.; O'Conner, J. J. AFWALTR-83-2087, Air Force Wright Aeronau tical Laboratories, AFWAL/POSL, Wright-Patterson AFB, Ohio, 1983. (16) Eisentraut, K. J.; Thornton, T. J. AFWAL-TR-80-4022, Air Force Wright Aeronautical Laboratories, AFWAL/ MLBT, Wright-Patterson AFB, Ohio, 1980. (17) Hillan, W. J.; Ross, W. D.; Eisentraut, K. J. In "Proceedings of the 33rd Meet ing of the Mechanical Failures Preven tion Group," NBS Special Publication 640; National Bureau of Standards: Washington, D.C., 1982. (18) Eisentraut, K. J. et al. U.S. Patent 4 238 197,1980; U.S. Patent 4 324 758, 1982. (19) Bierlein, J. Α.; Eisentraut, K. J., pre sented at the Pittsburgh Conference on Analytical Chemistry and Applied Spec troscopy, Cleveland, Ohio, 1979; Paper 610. (20) Bierlein, J. A. AFML-TR-79-4215, Air Force Wright Aeronautical Laboratories, AFWAL/MLBT, Wright-Patterson AFB, Ohio, 1980. (21) Anderson, D. P. Report NAEC-92163; Naval Air Engineering Center: Lakehurst, N.J., 1982. (22) Scott, D.; Mills, G. H. NEL Report No. 574; Dept. of Industry, National En gineering Lab.: Glasgow, U.K., 1974. (2$) Barwell, F. T. et al. Wear 1977,44, 163. (24) Saba, C. S. et al., presented at the 9th Annual FACSS Meeting, Philadelphia, Pa., 1982; Paper 313.
