Yumiko NAKAMURA*
Kazuhiko SUGIYAMA*
Chikako TAKATOH*
Yusuke MOCHIDA**
Tomohiko KON**
Tomomi HONDA**
*
Technologies, R&D Division
**
University of Fukui
To improve maintenance of machinery and equipment, we studied wear diagnosis technologies for oil lubricated bearings that include condition-based maintenance or proactive maintenance to maintain their soundness at lower cost. To identify friction and wear mechanisms for sliding bearings, we created simulated polluted oil mixed with metal particles with reference to oil collected from an actual machine, and conducted the block on ring test using this oil to examine how metal particles affect sliding surfaces. Studying lubrication diagnostic methods has allowed us to propose a new index that can diagnose lubricant and machine conditions from the ISO cleanness code of the lubricant and the membrane patch color. Furthermore, we have developed a new lubricant analysis method that can be used on site to detect changes in bearing conditions at early stages through periodic inspection.
Keywords: Lubricant, Bearing, Diagnosis, Wear, ISO code, Membrane patch, On-site, Condition-based maintenance, Proactive maintenance
Time-based maintenance (TBM), which is an approach to performing regular inspections and maintenance based on past records of failures etc., has been widely adopted for the maintenance and management of largesize machines/equipment and machines for industrial use. However, because the reduction of failure risks is the matter of highest priority in performing TBM, plans for inspections and maintenance tended to be somewhat redundant. As such, in recent years users have been requesting the reduction of both failure risks and maintenance costs, so TBM is being superseded by condition-based maintenance (CBM), which enables users of machines and equipment to detect the tendencies of abnormalities early while checking the soundness and develop a maintenance plan based on that 1). Furthermore, in recent years, proactive maintenance (PRM) is being espoused, which aims to retard the degradation of machines and equipment and thereby extend their life by proactively locating and removing the root causes of failures of machines and equipment. When PRM is likened to human health management, it means monitoring the blood-cholesterol level, which is one of the causes of adult diseases, and taking action to prevent problems such as serious myocardial infarctions. Machines not only require that the signs of failure, such as machine body vibrations and temperatures, are detected, but also that the tendencies of the fluid characteristics of lubricants and degradation-inducing factors contained in the lubricants (characteristic values, such as oxidation products, solid foreign substances, and water content) are monitored, and that measures are taken against the root causes of degradation 2) .
As indicated by the relationship between the wear degradation curve of a general sliding surface and the diagnosis methods 3) shown in Figure 1, it is said that lubricant analysis is the method that can detect changes earliest as the state of wear of a machine worsens, and this fact indicates how important lubricant diagnosis is for CBM, PRM, and other maintenance approaches.
Fig. 1 Degradation curve and diagnosis methods of mechanical machinery<sup>3）</sup>
With the increasing demand for lubricant diagnosis technology from inside the company and from customers, Ebara Corporation has carried out analysis of the composition of wear particles contained in lubricants but did not have much knowledge regarding “lubricant diagnosis.”
However, the University of Fukui has conducted research into lubricant diagnosis represented by the development of the “membrane patch method,” which diagnoses the state of degradation of lubricants from the filters through which they are filtrated.
The goal of our research and development aligned with the knowledge and technology of the University of Fukui, and we began joint research with the aim of elucidating the wear mechanism of sliding bearings and establishing a means to predict the degradation of oillubricated bearings.
This research aims to establish a means to detect phenomena or factors implying signs of solid contact of oil-lubricated bearings and predict the degradation of oil-lubricated bearings. In this paper, we explain the following three major activities of the research:
①Elucidating the friction and wear mechanisms of sliding bearings
②Establishing lubricant diagnosis indices using ISO cleanness codes and colors
③Developing an on-site analysis method for metal wear components
Detection of the phenomena or factors that imply signs of degradation of oil-lubricated bearings requires the mechanism from boundary lubrication to solid contact to be elucidated as the correlation between degradation of the lubricant and tribology.
Wear is defined as the phenomenon of gradually making a solid surface thinner due to friction 4), and the amount of wear is difficult to predict because wear is a phenomenon resulting from a combination of environmental factors, such as temperature and humidity, material factors, such as the shape and roughness of the surface, and dynamic factors, such as load and sliding speed, which affect one another. Research has been conducted into the wear mechanism, including research by Sasada on the process of generating wear particles with regard to adhesive wear 5) and the steel wear mechanism maps by Lim and Ashby 6). However, this research was conducted under conditions without lubrication or with unused lubricants and did not reproduce sliding states when wear particles were contained in the lubricant in an actual unit, such as a machine for industrial use or an engine, or when a lubricant is oxidized.
The degradation of lubricants is generally classified into two types, “oxidation” of a base oil or additive and “contamination” attributable to the inclusion of wear particles, sand, dust, etc. 7), and in some advanced research focusing on contamination, friction tests are performed with lubricants containing only hard particles or a single kind of particle 8). In fact, however, lubricants in actual units contain a wide variety of particles, such as hard particles and soft particles.
In this research, we first investigated the contaminated states of lubricants in actual units, prepared lubricants containing soft particles, hard particles, and soft and hard particles for simulation purposes, and performed friction tests using these particles. The results of these tests showed that wear patterns depended on the types of contained particles and the size and shape of hard particles 8)-10).
The tests were performed using white metal WJ2, which is a material for bearings, and stainless steel SUS420J1Q, which is a material for shafts, as test pieces assuming sliding bearings and a simulated degraded lubricant mixed with WJ2 and iron particles as wear particles. However, it was found out that it was impossible to identify whether the WJ2 particles deposited on the sliding surfaces were those contained in the lubricant or were from the worn test piece. For this reason, we performed a friction test using a lubricant mixed with aluminum (Al) relatively close to WJ2 particles in hardness, and investigated in depth the mixed state of particles and friction behavior on the contact surface by observing the cross section of the worn surface 11).
For the friction test, a block-on-ring friction test device was used. WJ2, which is a material for sliding bearings, and SUS420J1Q, which is a material for shafts, were used as a block test piece and a ring test piece, respectively. Both test pieces were subjected to mirror polishing by a buff. A schematic diagram of the test method is shown in Figure 2. This test was a single-direction friction test and performed by pressing the block test piece under a constant load against the side face of the ring test piece rotating at a constant speed in a lubricant and causing sliding friction between them. The test was performed with the sliding part immersed in the lubricant in an oil bath. The lubricant was circulated in the oil bath made of acryl by means of a roller pump. The test conditions are show in Table 1.
The contact electric resistance method was used to monitor the change of the lubricated state of the test pieces in connection with the sliding distance between them. A voltage of 91.5 mV was applied because the desired voltage to be applied across the test pieces was 100 mV 12) or below to avoid a dielectric breakdown of the oil film. The electric resistance was 0Ω in complete contact, which means that there was no oil film formed between the two surfaces in contact with each other, or approximately 156 kΩ in an electrically insulated state with a sufficient oil film.
Fig. 2 Schematic view of test pecimens
| Load，N | 50 |
| Sliding velocity，m/s | 1.0 |
| Sliding distance，m | 1000 |
| Lubricating oil | Turbine oil VG46 |
| Oil temperature，℃ | 23±2 |
| Kinematic viscosity，mm2/s @23 ℃ | 104 |
We prepared simulated contaminated oils complying with the degree of contamination of the most degraded lubricant (ISO codes 21/21/19) by referring to the ISO codes of six lubricants actually used for sliding bearings of a pump 13). (The ISO codes are the criteria for determining the degree of contamination of lubricants from the number assigned according to a particle count of the particles contained in 1 ml of lubricant.)
In this process, we counted the number of particles contained in 10 ml of lubricant using an offline particle counter (HIAC/ROYCO Model 8000A) to identify the particle size distribution of the particles contained in the lubricants actually used for sliding bearings and in the simulated contaminated oils. Secondary electron (SE) images of the metal particles used for preparing the simulated contaminated oils are shown in Figure 3. Iron particles A are spherical, and iron particles B, WJ2 particles, and Al particles are irregular. In a container made of polypropylene, 20 ml of unused lubricant and the particles of each kind were mixed, and the mixture was dispersed for 30 minutes using an ultrasonic cleaner and then dripped into the oil bath just before the test began.
Fig. 3 SE images of particles
The results of the worn surface observed with a laser microscope are shown in Figure 4. With the oil containing WJ2 particles, the deposition of WJ2 particles and a concave area caused by adhesive wear were found, and with the oil containing iron particles A, a streak resulting from abrasive wear and a convex area due to embedded iron particles were observed. With the oil containing iron particles A and WJ2 particles, a streak, the deposition of WJ2 particles, and a concave area caused by adhesive wear were found. It was found out that many iron particles A were embedded in WJ2 particles when they penetrated into the worn surface at the same time.
In addition, compared with spherical iron particles A, the embedded amount of iron particles B of an irregular shape was small because they were less likely to get trapped between the sliding surfaces, and marks left by iron particles B that rolled into between the two surfaces were observed (Figure 5).
The EDX analysis results of the concave area caused by the oil containing iron particles A and WJ2 particles are shown in Figure 6. The EDX analysis results led us to the presumption that a true contact point was formed as a result of the deposition of WJ2 particles on the iron particle-embedded area, which existed around the concave area and was higher than the surrounding area as shown in the image recorded by the laser microscope, and delamination occurred due to adhesion. We can infer from these results that WJ2, or the block material, will embed iron particles and running-in will advance when iron particles get trapped between the surfaces of the block and the ring and the lubricated state consequently becomes serious, and that a concave area will be preferentially formed in an iron particleembedded area.
Furthermore, the secondary electron images and EDX analysis results of the cross section of the test piece obtained in the test using the oil containing iron particles and Al particles are shown in Figure 7. The observation of the cross section of the test piece tested with the oil containing iron particles A and Al particles confirmed that a gap was formed due to embedding of iron particles in the surface of the WJ2 block. Al particles also deposited on and penetrated into the surface of the WJ2 block. They probably penetrated into the block while they were plastically deformed with the WJ2 block material by shear force. We infer that when WJ2 particles are mixed, the same mixed state as that proven with Al particles will be observed.
Fig. 4 Laser images of worn surface of WJ2 block
Fig. 5 SE image and laser image of WJ2 block
Fig. 6 SE images and EDX mappings of WJ2 block (Iron particles A + WJ2 oil)
Fig. 7 SE images and EDX mappings of WJ2 block (Iron particles B+aluminum particles oil)
We performed block-on-ring friction tests in simulated contaminated oils prepared by mixing iron particles as hard particles and WJ2 particles and Al particles as soft particles, and obtained the following conclusions by examining the sliding wear mechanism when contaminant particles were mixed:
（1）
Even if the ISO codes of contaminated oils are equivalent, the wear mechanism of WJ2, which is a material for sliding bearings, depends on the type of contaminant particles.
（2）
Iron particles act on wear in the following three ways: ①Iron particles get trapped between the two surfaces like they are sliding and leave streaks on the WJ2 block. ② Iron particles do not slide much and embed in the WJ2 block. ③ Iron particles roll into between the two surfaces. As iron particles are embedded, a gap is formed between the iron particles and the WJ2 block.
（3）
When the mixed-in soft particles are of the same kind of metal as the block material, a shear fracture is likely to occur inside the block in the area where soft particles deposit, and the particles will be detouched with the block material, resulting in the formation of a concave area.
（4）
When the mixed-in soft particles are of a different kind of metal with low mutual solubility, a shear fracture is less likely to occur inside the block in the area where soft particles deposit, and the particles are less likely to be detouched with the block material, resulting in the formation of a small, shallow concave area.
A lubricant analysis is performed to maintain the appropriate operating state of a machine, and achieves two purposes. One is diagnosis of the degraded state of an oil to determine the oil change timing to appropriately maintain the condition of the oil. The other is diagnosis of the condition of a machine to determine the timing for replacing or repairing parts to appropriately maintain the condition of the machine. As described earlier, in recent years the mainstream of maintenance has shifted to CBM (condition-based maintenance), under which the operating state of a machine is monitored in real time and maintenance is performed at the appropriate time.
Under such circumstances, it is desirable that approaches be developed which enable field operators to diagnose the operating state of machines on site. Proposed as one of these approaches is the lubricant diagnosis method, developed through research conducted thus far by Honda et al. 14)-16), that checks the color of a membrane filter (hereinafter designated as a “membrane patch”) after oil has been filtrated using the three primary colors of light, or RGB (red, green, blue). It was clarified that the degree of degradation of a lubricant and the degradation-inducing factor can be estimated from the relationship between the color of the membrane patch and the contaminant contained in the lubricant.
In the present research, we aimed to develop a diagnosis method capable of discerning the degradationinducing factors of lubricants and monitoring and predicting wear of sliding surfaces of machines for the purpose of widely applying the abovementioned diagnosis method to the monitoring of the state of machines and equipment used in an environment of oxidation and contamination. Below is a description of the diagnosis method we developed.
The filtering equipment used for the present test consists of a dustproof cover, a cylinder, a flask, and a vacuum pump. A schematic diagram of the filtering equipment is shown in Figure 8, and the surface and cross section of the membrane filter used for filtration are shown in Figure 9. A membrane filter made of cellulose acetate, with an outside diameter of 25 mm, thickness of 0.125 mm and a pore size of 0.8 μm, was installed between a cylinder and a flask, and 25 ml of sample lubricant was put into the flask.
The cylinder was vacuumed using a vacuum pump to filtrate the sample lubricant through the membrane filter. The filtration area was approximately 227 mm2 , and the filtration area per ml was approximately 9 mm2 /ml. Petroleum ether was flowed from the membrane patch colored by the filtration residue into the cylinder along its inner wall surface of the cylinder. The oil content remaining in the central area of membrane patch was cleared away, and the cylinder was removed. The membrane patch was put on a hot plate set to 50 °C, petroleum ether was dripped again onto the membrane patch, and the membrane patch was dried for 10 minutes.
Fig. 8 Filtering equipment
Fig. 9 Magnified images of the membrane filter
A colorimetric patch analyzer (CPA) was used for quantitative measurement of the color of the membrane patch. The measurement principle of the CPA is shown in Figure 10. The CPA projects white light from the front and back faces of the membrane patch and measures the color difference ΔERGB of the color parameter (RGB value) from the reflected light and the transmitted light 17). The reflected light can provides information about the color of the contaminant collected on the surface of the membrane filter, and the transmitted light can provide information about the color of all contaminants caught on the surface of and inside the membrane filter.
Here, ΔERGB measured with the transmitted light is expressed as T ΔERGB , and ΔERGB measured with the reflected light is expressed as R ΔERGB . R, G, and B of the RGB value are expressed in 256 levels, from 0 to 255, with white (255, 255, 255) and black (0, 0, 0). The maximum color difference (MCD) is the maximum value of the color difference between two colors of the RGB value, and it is a known fact that the MCD has a close bearing mainly on the degradation-inducing factor of the lubricant 14). ΔERGB is the distance from white in the three-dimensional solid of R, G, B, cyan, magenta, yellow, black, and white and expressed by Equation (1). ΔERGB is used to determine the degree of degradation of a lubricant.
ΔERGB＝｛（255−R)2＋（255−G)2＋（255−B)2｝0.5 …………（1）
Fig. 10 Measurement principle of the membrane patch color by the CPA
We counted the number of particles contained in 10 ml of lubricant using an offline particle counter (HIAC/ROYCO Model 8000A) to identify the particle size distribution of the particles contained in the lubricants in actual units and in the simulated degraded oils. The measurement ranges of particle sizes were ≧ 4μm, ≧6μm, ≧14μm, ≧21μm, ≧38μm, and ≧ 70μm. The ISO codes are the criteria for determining the degree of contamination of a lubricant from the numbers assigned according to the particle count contained in 1 ml of lubricant 13). A higher ISO code means a larger number of particles contained in a lubricant, and a lubricant with a high ISO code is expected to accelerate wear.
The ISO codes are, therefore, considered to be important as criteria for controlling the degrees of contamination of lubricants. Since each ISO code is assigned according to the number of particles with a particle size of 4μm, 6μm, 14μm, or over, it is characterized by the nature of enabling users to understand the ratio of each particle size to all particle sizes more easily than NAS grades 18).
To ascertain the degraded state of a lubricant in an actual unit, we selected a pump as the unit, and performed a general oil analysis and a filtration test of 23 samples of lubricants for industrial use, which are used in different environments or for different periods, and measured the numbers of particles in them using an offline particle counter.
We prepared membrane patches for the 23 samples and performed surface and hue analyses using EDX. We consequently found out that the 23 samples were broadly classified into three types. The representative color parameters of the membrane patches and the results of the EDX analyses are shown in Table 2 and Figure 11. The value of T ΔERGB of membrane patch No. 1 was close to the maximum value, showing that the degree of degradation of the lubricant was extremely high. In the EDX analysis of the substances caught on the surface of the membrane patch, the peaks of metal elements, such as Cu, Fe, and Sn, were detected, the substances caught were wear particles, and contamination attributable to the wear particles is the probable cause of degradation.
The values of ΔERGB and MCD of membrane patch No. 2 were approximately 200 and approximately 50, respectively, in both measurements with transmitted light and reflected light. In the EDX analysis of the substances caught on the surface of the membrane patch, the peaks C, O, Cu, and Fe were detected, metal elements and oxidation products coexisted, and both oxidation and contamination are the probable causes of degradation.
The values of both ΔERGB and MCD of membrane patch No. 3 were high. The value of MCD measured with transmitted light was equivalent to the value of membrane patch No. 2. However, when the value of ΔERGB was high, MCD tended to become low, and it can be said that the value of MCD of this sample is relatively high among the samples with a high value of ΔERGB. In the EDX analysis, only the peaks of C and O were detected from the spherical substance on the surface of the membrane patch, and this substance was an oxidation product. Thus, oxidation is the probable cause of degradation.
These analysis results showed that the states of degradation of lubricants used in actual units were broadly classified into three types; oxidation, contamination attributable to wear particles, and coexistence of oxidation and contamination attributable to wear particles. Furthermore, the results of friction tests performed in the past using simulated degraded oils prove that the wear pattern depends on the type of particles contained or the particle size or shape of hard particles, and that oxidation products alone do not accelerate wear 8)-10).
Thus, we considered it necessary to grasp not only the number of particles contained in the lubricant but also the cause of contamination of the lubricant to keep track of wear of the sliding surface of a machine. We also developed new evaluation parameters and attempted to prepare a contamination mode diagram of lubricants using these evaluation parameters.
Where a, b, and c correspond to ISO codes (a/b/c) and the code for the number of particles of ≧4μm, the code for the number of particles of ≧6μm, and the code for the number of particles of ≧14μm are a, b, and c, respectively. For example, when ISO codes are (22/21/17), Ic is 48 from Equation (2).
As proven by this equation, the larger the total number of particles, or the smaller the difference among the numbers of particles with particle sizes of 4μm or larger, 6μm or larger, and 14μm or larger, the larger the value of Ic. That is, from the viewpoint of monitoring the worn state of the sliding surface, the increase of Ic means the increase of the total number of wear particles and the increase of the ratio of largesize particles. In addition, from the viewpoint of the inclusion of contaminant particles, the increase of Ic means the increase of the total number of wear particles and the increase of the ratio of large-size contaminant particles. In both aspects, Ic can be the index of the degree of risk of a machine failure.
The relationship between the maximum color difference measured with reflected light and the index of degree of contamination Ic is shown in Figure 12. The colors of the plots in the figure indicate the colors of the surfaces of the membrane patches. In the past, it was difficult to discriminate between sample lubricants and discern contamination-inducing factors because the ISO codes of respective particle sizes needed to be separately compared.
However, using Ic can express the difference between ISO codes for respective particle sizes with a single parameter and facilitate discerning the degree of contamination between sample lubricants. Besides, combining Ic with the maximum color difference makes it possible to discern from the value of the maximum color difference whether the change of the number of particles resulted from oxidation or from contamination attributable to wear particles, and easily determine the degree of contamination of each lubricant and the contaminationinducing factor.
The relationship of the difference between ΔERGB measured with transmitted light and that measured with reflected light and Ic is shown in Figure 13. Since information about the colors of the contaminant particles caught inside a membrane patch can be ascertained using transmitted light, the effect of particles smaller than 0.8μm, which cannot be discerned with ISO codes that are applicable to measurement of particles of 4μm or over, caught inside a membrane patch can be confirmed. There are many particles that have a large difference of ΔERGB although Ic is equivalent. Even if Ic is small, Ic can show that many fine particles smaller than 0.8μm are contained in a lubricant with a large difference of ΔERGB. By setting an appropriate threshold for Ic, the maximum color difference, and the difference of ΔERGB, we consider it possible to control lubricants in a suitable manner for the target machine or equipment and identify contamination-inducing factors. We also expect that increasing the sophistication of this technology will enable us to predict wear of oillubricated surfaces.
As described thus far, combining ISO codes with the color parameters of membrane patches was proven to be effective in improving the accuracy of lubricant contamination diagnosis.
Table 2 Example of membrane patches in actual degraded oil
Fig. 11 SE images and EDX mappings of membrane patches
Fig. 12 Relation between contamination index and aximum color difference
Fig. 13 Relation between contamination index and the difference of ΔE<sub>RGB</sub>
With the aim of establishing technology for monitoring and predicting wear of sliding surfaces of machines, we first checked the degraded states of lubricants used in actual units and then performed friction tests in simulated degraded oils prepared based on these degraded states to study the relationship between the degradation of lubricants and the phenomenon of wear. Then, we organized the numbers of contaminant particles in lubricants in actual units and in simulated degraded oils based on ISO codes, and studied the relationship between the number of contaminant particles and the color of membrane filters. Below are the obtained results:
①
We studied the degraded states of 23 samples of lubricants for industrial use actually used for sliding bearings for pumps in different environments or for different periods, and found out that the states of degradation of lubricants were broadly classified into three types; oxidation, contamination attributable to wear particles, and coexistence of oxidation and contamination.
②
Based on the findings and knowledge we obtained, we developed the index of degree of contamination Ic, which is a new evaluation parameter using ISO codes, and proposed a contamination mode diagram of lubricants combining Ic and the color parameters of membrane patches. As a result, these means enabled us to discern the degree of contamination between sample lubricants and identify the degrees of contamination of lubricants and contaminationinducing factors more easily.
Lubricant analyses are carried out to maintain the appropriate operating state of machines, and achieves two purposes. One is diagnosis of the degraded state of an oil to determine the timing of the oil exchange. The other is diagnosis of the condition of a machine to determine the timing for replacing or repairing parts of the machines. When it comes to only diagnosis of the state of a machine, quantifying metal wear particles is more important. Although counting the total number of metal wear particles contained in a lubricant is helpful, it is more desired that a damaged area be inferred by grasping the amount of each metal component.
On the other hand, when maintaining and managing the healthiness of machines through lubricant analysis, it is difficult in many cases to achieve this using a single item as a threshold if machines have different structures or are used under different conditions. Thus, an effective approach is to regularly sample and analyze the lubricant of each machine and perform trend control.
We studied a method for analyzing metal wear particle components contained in lubricants, which can be easily carried out by field inspection operators etc. only with a simple tool or device.
We adopted a color reaction as a method for measuring the amount of metal wear particles contained in a lubricant without using a fluorescent X-ray device or another expensive device. To analyze metal particles suspended or precipitated in a lubricant, we followed the procedure shown below.
①Filtrating the lubricant through a filter
②Washing and drying the residue on the filter
③Eluting the residue on the filter with an acid
④Detecting and quantifying metal particles by a color reaction of metal ions
We filtrated the lubricant by attaching a syringe filter to the tip of the syringe containing the lubricant as shown on the left side of Figure 14. In this step, we diluted the viscosity of the lubricant with an organic solvent to reduce pressure loss during filtration. The pore size of the filter can be selected from 0.45μm or 0.8μm etc. according to the purpose.
To wash the filter after filtration, we temporarily detached the syringe, and removed the oil content. In this step, we charged into the syringe an appropriate amount of organic solvent capable of dissolving and washing away the lubricant, and attached the filter used for filtration to the tip of the syringe as shown in Figure 14. After washing, we detached the syringe, drew air into it, attached it to the filter, and allowed air to pass through it to remove the liquid remaining in the filter and dry it.
To elute the metal wear particles contained in the filtrated residue on the filter, we filled the syringe with a diluted hydrochloric acid or diluted nitric acid and diluted the metal. We collected the acid eluate in a container separately from the lubricant and the organic solvent that passed through the filter (right side of Figure 14).
Fig. 14 Pretreatment steps for measurement Filtration of collected oil (Left) Acid elution of metal on the filter (Right)
We adopted the following two methods as means to detect and quantify the metal ions present in the acid eluate:
①Colorimetric method using indicator strips for water quality inspection
We quantified metal particles using semiquantitative ion test strips QUANTROFIX (manufactured by Macherry Nagel) and a colorimetric method.
②Absorption photometry by adding a color reagent
As the iron ion color reagent, we used o-phenanthroline. As the iron copper color reagent, we used bathocuproin. We measured the absorbance of the colored solution by absorption photometry.
The results of the test of the bearing lubricant sampled from machines No. 1 and No. 2 at the time of maintenance of two pumps on a work site are shown below. Judging from the material of the sliding bearings, we considered that the main detectable wear metal components were iron, copper, and tin. As a more simplified method, we used semiquantitative ion test strips for these metal ions. The results of immersing the test strips in the solution just after elution by the abovementioned method are shown in Figure 15. In addition, the results of the same lubricant analyzed by the SOAP method for a cross check are shown in Table 3.
We compared the results of the quantification using the semiquantitative ion test strips with the results of the analysis by the SOPA method, and found out that the test strips were also capable of measuring the amount of metal components to some extent. It was possible to discern the differences of 10 ppm and 20 ppm of iron, in particular. Contrary to it, the differences of 1 ppm and 5 ppm of tin could not be discerned.
These findings revealed that an analysis using ion test strips enables us to identify the components of metal wear particles and the semiquantitative values of the concentrations thereof. Thus, when the lubricant of a bearing etc. is contaminated black, we consider it possible to immediately estimate the cause of it on site, and when a small amount of lubricant is regularly sampled, it is probably possible to detect a sharp increase of the amount of wear on site. On the other hand, however, a semiquantitative analysis using a colorimetric method cannot detect slight changes of metal concentrations, and an analysis method with higher accuracy is, therefore, desired to detect signs of failures.
Fig. 15 Quantification results of metal concentration (indicated by ion test papers)
| No.1 | No.2 | ||||
| Fe | Cu | Sn | Fe | Cu | Sn |
| 10 | 0 | 5 | 20 | 0 | 1 |
As a method for measuring metal concentrations with higher accuracy, we considered a measurement method that measures a metal concentration by absorption photometry after coloring the eluate by adding a color reagent. In the present research, we analyzed iron and copper in a lubricant contaminated black due to a bearing failure during operation.
As the first step, we prepared calibration curves using a standard solution. As color reagents, we used o-phenanthroline for iron ions and bathocuproin for copper ions. Furthermore, coloring iron ions with o-phenanthroline and copper ions with bathocuproin required both pH and the ion valence to be adjusted, and we used ammonium acetate as buffer agent and hydroxylammonium chloride as reducer.
The calibration curve of iron prepared as described above is shown in Figure 16, and that of copper is shown in Figure 17. Both calibration curves offered satisfactory linearity from 0.1 ppm to 10 ppm. The results of the analysis of the sampled lubricant using this method are shown in Table 4. For comparison, the results of measurement by the XRF method are shown. Although a little difference in the value of copper was found between the results, the values of copper of both results were in good agreement. On-site measurement with satisfactory quantitativity is conceivable by using a mobile type compact absorptiometer capable of performing measurement at a wavelength close to 500 nm. A quantitative analysis of tin can also be performed by absorption photometry if hematoxylin is used as color reagent, although it is not stated herein.
Fig. 16 Calibration curve of iron ion
Fig. 17 Calibration curve of copper ion
| Fe | Cu | |
| XRF | 26.1 | 39.8 |
| Absorbance | 18.1 | 39.8 |
We found out that the approach studied in the present research enables us to measure the concentrations of metal components contained in a small amount of lubricant sampled on a work site where a machine or equipment, such as a pump, is installed with the aid of a simple instrument or device.
Using this approach to regularly measure the concentrations of different kinds of metals contained in lubricants, such as iron, copper, and tin, which are used for sliding parts, and keeping track of the worn states of sliding parts may become an effective approach for performing CBM of a machine, whether it is newly installed or an existing machine.
We have obtained the following findings and outcomes through the present research:
①
The analysis results of lubricants sampled from actual unit showed that the states of degradation of the lubricants, which occurred during use, were broadly classified into three types; oxidation, contamination, and coexistence of oxidation and contamination.
②
The results of the friction tests using simulated degraded oils revealed that the important factor in degradation diagnosis of lubricants was the type of contaminant particles contained in the lubricants, not the number-or size of contaminant particles.
③
We developed a new diagnosis method combining ISO cleanness codes and the color parameters of membrane patches. We proved that using this method enables us to discern the degree of contamination between sample lubricants and identify the degrees of contamination of lubricants and contamination-inducing factors more easily and, at the same time, perform more in-depth diagnosis of the degraded states of lubricants.
④
We developed a new approach capable of analyzing the amounts of metal wear particles contained in lubricants on site. Regularly monitoring the type and amount of wear particles on site with the aid of this approach is effective for early detection in the tendency of deterioration in the state of a machine and performing appropriate CBM.
We will conduct machine learning using actual units or test machines and establish a method for diagnosing abnormalities of oil-lubricated bearings assisted by analysis results. We will also continue to elucidate the wear mechanism of bearings to clarify the phenomena and factors that may cause friction and to present scientific backgrounds for the selection of bearing diagnosis parameters. With regard to on-site analyses of metal wear particle components, the development of an analysis kit field operators can handle easily and safely is an issue to deal with.
To provide customers with better after-sale services, we are committed to establishing technology for predicting the degradation of oil-lubricated bearings and putting it to work on efficient and safe maintenance and control of machines and equipment.
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