ric constant or impedance of the oil, but these types of parameters are never found in any oil analysis report and are therefore very difficult to interpret without having expert knowledge. In general, these sensors work well in controlled environments. In real world applications where the oil undergoes many changes in parallel (base number reduction, oxidation, water, soot, additive depletion etc) and not to forget temperature changes, all these individual parameters will have an influence on the sensor output, and it is impossible to extract the root cause of the observed sensor changes. Aus Wissenschaft und Forschung 4 1 Introduction Oils and lubricants play a critical role in industry and in the operation of plant equipment such as gas engines, and turbines (steam, gas, hydro) for power generation, large gas compressors, gearboxes (on wind turbines for example), hydraulic systems, steel and metal working applications and industrial automotive engines like excavators, diggers and large trucks. Oil condition monitoring forms a critical part of the lubrication management and maintenance programme and it provides important information to ensure that the asset is operated correctly. Conventionally, plant engineers operating and maintaining high value assets rely on taking oil samples periodically and sending them to a laboratory for analysis. It can take up to 5 days from sampling to receiving the oil report and introduces a large time lag in the reporting of the oil condition. This process is shown in figure 1. The benefit of having real-time monitoring of the oil condition is vast. Customers will not only have the satisfaction of being in complete control of their asset, but the Cost of Ownership (COO) will also decrease as: • potential failure modes can be spotted in the data and can be corrected immediately. • a more effective maintenance and service process can be established as the status of the oil/ engine will be known at the time of sending out an engineer. • oil change intervals can be confidently extended and moved from time based to condition-based intervals. Obviously, real time oil condition monitoring is not new and over recent years a number of different sensor technologies have been used and tested, namely inline dielectric or impedance sensors. These sensors measure physical properties of the oil sample, such as the dielect- DOI 10.24053/ TuS-2022-0025 Tribologie + Schmierungstechnik · 69. Jahrgang · eOnly Sonderausgabe 1/ 2022 How to get Lab Equivalent Oil Analysis 24/ 7 Neil Conway, Carsten Giebeler, Benjamin Wiesent* The established process for oil condition monitoring is to periodically take a sample and have it analysed in an oil laboratory. These laboratory measurements are governed by various technical standards (ASTM,DIN etc) and customers rely on this periodic data to react to oil condition trends and/ or step functions, to plan servicing and maintenance and to reduce asset downtime from failure. Real-time oil condition monitoring systems based on dielectric or impedance analysis of the oil have been available for some time but they only provide summary parameters that are hard to interpretate as they do not correlate with the laboratory oil analysis. In this paper we discuss the development of Spectrolytic’s Oil Condition Monitoring systems (Fluid- InspectIR ® ) and how, by working closely with our customers, we have developed a robust and affordable range of oil condition monitoring systems that gives our clients meaningful and understandable real time data of the same parameters and in the same units as they are commonly receive it from their oil laboratory analysis. These systems provide the customer the comfort of having quantitative and accurate key oil condition data at the touch of a button, while still utilising their standard practices through oil laboratory measurement to validate the predicted key oil parameters by the inline system. Keywords oil condition monitoring, technical standards, Realtime oil condition monitoring, FluidInspectIR ® , laboratory measurements Abstract * Neil Conway Dr. Carsten Giebeler Spectrolytic, Edinburgh, Scotland, UK. Dr.-Ing. Benjamin Wiesent Spectrolytic, Wackersdorf, Germany Based on customer feedback and the clear need for a real time sensor that provides meaningful data, Spectrolytic developed a unique range of oil analysers that measures the most relevant oil degradation and contamination parameters like oxidation, nitration, sulphation, water, soot, additives. The systems also use advanced chemometrics to extract TAN (total Acid Number), TBN (Total Base Number), ipH, viscosity and other chemical changes from the data. For the inline analyser additional modules can be added to house a particle or wear sensor or any sensor that the customer wishes to use to merge with the data stream. A short overview of the next generation of FluidInspectIR ® inline and portable analysers are shown in figure 2. 2 Oil Condition Sensor Platform The sensor platform developed by Spectrolytic utilises the powerful analytical technique of mid-infrared spectroscopy to measure a variety of relevant degradation parameters in an oil sample. With each measurement the sensor determines the changes of the oil at a molecular level using the same analytical technique and data extraction as employed by oil laboratories around the world. The laboratories carry out an oil analysis on customer samples by applying various ASTM and/ or DIN standards to determine Oxidation, Nitration, Sulphation, additive changes and contamination levels of the oil. This common baseline of using mid-infrared spectroscopy as the analytical tool not only allows our sensor to provide real time data with the same units and accuracy as the oil laboratories, but it also provides the option, by employing sophisticated mathematical algorithms, to predict more complex oil parameters such as Total Acid Numbers (TAN), Total Base numbers (TBN) or ipH. Another factor that should not be underestimated is the simplicity of generating calibration files for any given oil/ application. We have developed and designed the systems in such a way that allows the customer to monitor most parametric data from the day of install. There is no need for having old oil samples, shipping oil samples around the world or having to artificially age the oils. 3 Analyser Hardware Spectrolytic’s FluidInspectIR ® Inline oil condition monitoring system allows seamless inline installation. The Aus Wissenschaft und Forschung 5 Tribologie + Schmierungstechnik · 69. Jahrgang · eOnly Sonderausgabe 1/ 2022 DOI 10.24053/ TuS-2022-0025 Figure 1: Typical oil analysis process in an industrial environment and the positive effects of at-line or real time oil analysis Figure 2: FluidInspectIR ® Inline and Portable Oil Condition Analysers ratio. Typically the SNR ratios for these system are 10000: 1 but it all depends on the sample type, film thickness etc. 4 Application Analysis The sensor extracts, in real time, multiple parameters from the chemical changes in the oils’ infra-red absorption using the same analytical technique as employed in an oil laboratory. The sensor is configured and set-up in such a way that it applies ASTM and DIN standards to determine oxidation, nitration, sulphation etc in real time so that the sensor output is directly proportional to these oil degradation parameters. The table in figure 5 provides a good summary of the parameters that have been measured and analysis with our oil analyser systems. The table not only lists the parameters but also provides the units in which the parameters are reported which correspond exactly to those reported by the oil analysis laboratories. Field Application Engineers are well versed in analysing and interpreting reference reports of oil samples and having the sensor data presented in the same format as in the oil reference report significantly lowers the barrier for adapting real time and/ or at line oil condition monitoring sensor technologies. Today’s oil formulations are complex and depend largely on the application (engine, hydraulic, gearbox etc) as regards to the base oil and additive package. Base oils from Group I-III are predominately mineral oils (some Group III base oils are classed in terminology as ‘synthetic’) and Group IV (PolyAlphaOelfins) and Group V (PolyAlkyGylcol, Polyolesters, Phosphate Ester, siloxanes) are classed as synthetic oils. Aus Wissenschaft und Forschung 6 Tribologie + Schmierungstechnik · 69. Jahrgang · eOnly Sonderausgabe 1/ 2022 DOI 10.24053/ TuS-2022-0025 kit installation is plug and play and can be carried out remotely with the support of our Field Service Engineers. The Inline Analyser can be integrated into the main oil flow of the asset via a bypass or alternatively oil can be extracted from an oil sump or oil tank using an integrated pump. If required for the application the analyser can be configured to include particle and wear sensors, viscosity sensors or other sensor that might provide additional information. The generation 2 system as seen in figure 3 has a much smaller footprint and has functionality improvements. Housed inside the kit, amongst other hardware, is an innovative inline mid infrared (MIRS8-T) sensor that extracts the relevant oil condition information from chemical changes in the oils’ infra-red absorbance signature. The MIRS device contains a multi-level array of infrared emitters, sensors and a transmission flow-cell ( see figure 4). The customer can choose the number of pay-load channels depending on the number of parameters that need to be measured. The emitters and sensors are orientated in such a way to avoid any undesired interference effects caused by certain microcavity effects but at the same time to provide the best possible Signal to Noise Figure 3: Installations of Generation 1 Inline Analyser on gas engines Figure 4: MIRS8-T sensor used for inline oil measurements in transmission mode Recent advancements in the sensor technology has opened up the industrial markets for disruptive measurements. The inline systems can measure the chemical degradation involved in polyolester and phosphate ester oils and key parameters in steel plants and metal working industry (aluminium sheet milling). 5 Sensor Accuracy There is an excellent agreement between predicted sensor data and reference analysis as shown in plot below. The plot also displays ‘rogue’ measurements from reference analysis that the sensor does not display. This is likely some error in sample taking or sample measurement. The sensor therefore removes all human involvement from the oil analysis process as there is no sample taking process, no storage/ shipment required Aus Wissenschaft und Forschung 7 Tribologie + Schmierungstechnik · 69. Jahrgang · eOnly Sonderausgabe 1/ 2022 DOI 10.24053/ TuS-2022-0025 Figure 5: Summary of relevant oil degradation parameters that have been measured with our in-line or at-line oil analysers Figure 6: Sensor vrs Oil Lab data for gas engine installation The user can define and set the limits for each parameter to flag any trends or step changes in the behaviour of the oil condition. 7 Conclusion In this paper we have outlined the working principles and the benefits of a real time oil condition monitoring sensor that provides customers with easy to understand and meaningful data. The sensor output data are presented to the user in the same, familiar units that they know from laboratory oil analysis reports and are therefore easy to understand and to interpret. Moreover, our virtual sensor enables the customer to first test the device performance and the usefulness of the sensor in their specific application without having to spend any money on hardware or design-in activities. The sensors can be customised for oil type and application and easily installed with several options for streaming data. Aus Wissenschaft und Forschung 8 Tribologie + Schmierungstechnik · 69. Jahrgang · eOnly Sonderausgabe 1/ 2022 DOI 10.24053/ TuS-2022-0025 or no lab technician carrying out measurements. The results are reliable and consistent reference analysis with minimum effort. The sensor provides customers with accurate , understandable and actionable oil analysis data 24/ 7. 6 Real time Sensor Data As we move more and more towards the realms of Industry 4.0, it’s critical that the plant asset user has access to the full data stream at the touch of a button. For the Inline system, the Data can be sent to Spectrolytic’s cloud and there is an option to view/ download data via a dashboard. We support customer’s cloud (Azure, AWS) via MQTT or Web API protocols Direct integration available with on-site controller systems From the cloud web portal (example in figure 7), the user can access the process control charts from all the sensors to get a complete picture of the oil condition. Figure 7: Dashboard viewer example of oil parameters