Rapid analysis of wear metals in used oils by automated ICP-OES
Condition monitoring is essential to the efficient operation of large plant and machinery, and is the use of physical and chemical techniques to check engines and machinery for wear, with the objectives of preventing costly equipment failure and optimising maintenance programmes.
SPECTRO Analytical Instruments
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The elemental analysis of used lubricating oil is an integral part of condition monitoring: specialist service laboratories and plant operators will analyse hundreds of lubricant samples a day for a wide range of elements. Many techniques exist for this type of analysis, but only Inductively Coupled Plasma – Optical Emission Spectrometry (ICP-OES) has the speed and sensitivity to succeed in these high throughput applications.
A modern simultaneous ICP-OES instrument, such as the Spectro Arcos, is capable of measuring over 60 samples per hour for a wide range of elements. Direct presentation to the instrument of a simply diluted oil sample is the preferred technique when speed is essential. Even then, however, sample preparation can be the rate limiting step: the sample must be measured (by volume or weight), quantitatively diluted, mixed and presented to the instrument, possibly with the addition of an internal standard or other reagent. With high sample throughput, performed manually, this task is not only costly in manpower terms, it is also repetitive and therefore subject to human error.
A new and revolutionary system developed jointly by Spectro Analytical Instruments and Labiron Systems bv fully automates the complete sample preparation and measurement process and achieves analysis times of less than one minute per sample including sample preparation. This paper examines the analytical requirements, the design and operation of the system.
Condition analysis: introduction
Lubricating oil analysis has been used to monitor the condition of engines and other machinery for over 50 years. It can be used to detect wear in most lubricated mechanical systems, such as engines, gear transmissions and hydraulics, and has wide application in areas such as construction machinery, power generation and transportation, including aviation, fleet operations and public transport. One of the most powerful arguments for condition monitoring is that it can trigger preventive maintenance before component wear leads to potentially catastrophic failure. Early detection of foreign matter in the oil, perhaps due to an air filter failure, can prevent wear and costly repairs.
There are several causes of wear, such as friction between moving surfaces, abrasion by contaminants such as grit, and corrosion, but most give rise to the presence of microscopic metallic particles in the lubricant as components wear away. Quantitative measurement of metallic elements in the oil can therefore be a useful indicator of wear. Furthermore, as different metals are used to manufacture different components, elemental analysis can often provide a clue as to which components are subject to wear. Analysis can also detect the presence and possibly the origin of foreign matter in the oil, such as dust that may have entered an engine via a defective filter. Many other changes can occur in oils under fault conditions, such dilution by fuels, or contamination by substances like water or anti-freeze. Processes such as oxidation can lead to changes in lubricant properties like viscosity, leading to accelerated wear rates. Not all of these processes can be detected by elemental analysis, so several different physical and chemical measurement techniques are necessary for comprehensive condition monitoring, with elemental analysis the essential tool for wear detection.
Interpretation of the analytical results from oil analysis is itself a complex and specialised task. Many lubricating oils contain organo-metallic additives used to improve or extend the lubricant properties of the oil. These additives may be consumed over time. This is known as “additive depletion” and, unless the oil is changed or the additives replenished, it may itself lead to increased wear, so the level of additives needs to be monitored. These same metals may occur in engine components, but the detection of one of these elements clearly does not necessarily indicate wear. Mechanical systems and engines are often subjected to a “running in” period, during which wear can be quite rapid but is actually beneficial. For these reasons, system management decisions are rarely made on the basis of single oil analysis measurements or against predetermined “limit values”, but by following trends established by regular sampling regimes. Software packages designed to assist in the interpretation of measurement data are commercially available.
Table 1 indicates the possible significance of some elements found in used oil; it is by no means exhaustive. Unless wear is severe, metallic wear particles entering the lubricant are usually very finely divided (10 microns or less) and remain largely suspended in the oil without precipitation. Additive elements are usually in solution. Under these circumstances, the oil sample can be regarded as homogeneous and analysed by solution techniques.
Typical concentration levels for wear metals lie in the range from 1 to 500 parts per million (ppm), and some additive elements can be at several thousand ppm. For most elements, these concentrations are well within the scope of ICP-OES, and there are several national and international standard methods that describe or recommend the use of this technique for the analysis of fuels and lubricating oils.
• ASTM D 4951-09
• ASTM D 5708-11
• ASTM D 5185-09
• ASTM 7111-11
• ASTM 7260-06
• ASTM 7691-11.
ICP-OES spectrometers from Spectro Analytical Instruments are widely used for used oil analysis, and the Spectro Arcos in particular, with a capacity of over 60 samples per hour, is ideally suited for high throughput applications. At this speed, however, sample preparation may be the rate limiting step. Manual sample preparation can be costly in manpower terms and, being highly repetitive, it can be prone to human error.
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