Evaluating Grease Degradation through Contact Angle Approach

Grease is highly susceptible to degradation due to regular usage and the severity of the operating conditions. Degradation can negatively impact the performance of grease-lubricated machinery, demanding frequent maintenance to avoid premature failure of machine elements. Quantification of grease degradation has proven to be a formidable task, for which no accepted standards are currently available. In this paper, we extend the results of a novel approach developed recently for the evaluation of the water-resistant property in grease to quantify degradation. The methodology is based on measurements of the contact angle of a water droplet on the surface of a sample of grease. We report the results of extensive tests performed on different grades of lithium complex greases to evaluate the variation of contact angle values with the composition of grease. The measurements were compared with penetrometer readings to quantify a relationship between the grease consistency and contact angle. Detailed study results are also presented on three types of greases sheared in a grease worker for a different number of strokes: contact angle and the yield stress values were measured and compared. Finally, the tribological characteristics were determined for two greases that exhibited a low or high change in their contact angles.

Hybrid Model for Wind Turbine Main Bearing Fatigue with Uncertainty in Grease Observations

Available historical field data shows that wind turbine main bearing failure can lead to major operation and maintenance costs due to unscheduled downtime. For legacy turbines, fa- tigue is one of the major failure modes and, to a degree, can be partially modeled with physics-based formulations. Unfor- tunately, existing bearing fatigue models can potentially be inaccurate due to lack of understanding of the lubricant degra- dation. One way to enhance these models is to track the grease damage along with the bearing fatigue damage. However, the need of grease degradation data can become an impedi- ment for such strategy. In this paper, we will demonstrate that it is possible to calibrate grease degradation models with cost-efficient periodic visual inspections. Knowing that such inspections introduce observation uncertainty to the model, we will use a hybrid physics-informed deep neural networks to quantify such uncertainties within our models. We built a hybrid model that fuses the physics-based understanding of the bearing fatigue failure with the ability of data-driven layers to compensate the missing physics, with respect to the grease degradation. The proposed hybrid model is also ca- pable of decoding uncertain visual grease inspections with a custom designed classifier. We illustrate the merits of the model with the support of case studies, where we test inspec- tion with different levels of conservatism to train the model and compare the predictions of these models on an artificial wind park. Results from the case studies indicate the success- ful prognostic performance of the trained with limited and noisy observations. While grease damage is predicted with 0.3% root mean square error as a result of baseline inspection campaign, bearing life is prediction is conservatively off only by months for aggressive turbines that have 10 years of life.

Bearing Grease Degradation Related to Water and Roller Bluing

Bearing degradation and defects can result in a premature failure. Water ingress into the bearing is a factor for premature degradation, as water may corrupt internal parts and degrade the bearing grease. This paper presents the investigation of the properties of grease degradation from bearings with water-related degradations. This research provides insight into the internal state of bearings that have been replaced due to grease degradation as a result of water ingress. Separately, the railroad industry has observed bearing roller “bluing” or “lube staining.” This discoloration may be a harmless surface effect, or it may be similar to heat bluing. Determining true metallurgical effects may lead to the understanding between these two different types of “bluing”. To study bearings with water-related lubrication degradation, grease samples were collected from two populations of bearing lubrication at bearing service locations. One population contains bearings identified with water-related damage, and a second population is a control set of bearings. Primary grease analysis was done per ASTM 7918, providing metrics of wear, contamination, consistency, and oxidative properties. Additional testing was performed where results indicated utility; including measurements of anti-oxidant remaining in grease and microscopic analysis of wear particles in the grease. “Bluing” or “lube stain” bearing components were examined through analysis of lubrication and metallurgical metrics. Collections of samples from bearing shops included representative small amounts of grease and “blued” steel parts from bearings exhibiting surface discoloration. A second sample set included steel parts and grease samples from a control set of bearings. A third set of rollers were heat blued in the lab. Lube stained rollers and control set rollers were tested for metallurgical changes. Analysis of the bearing steel consisted of hardness and micro-hardness testing of polished samples, examination to compare microstructural features, and residual stress tests. The tests conducted in the investigation of water-related bearing grease degradation indicate a difference between bearings with “Water-Etch” and “Non-Verified” degradation modes based on ferrous debris levels in the grease. This difference is due to wear of the bearing material deposited in the grease. The tests conducted in the investigation of lube stain in bearings show lube stain does not affect any tested metallurgical material properties, other than surface discoloration.

Nuotekų ir vamzdynų, užterštų riebalais, valymo, naudojant bakterinį preparatą, technologija / Технология очистки сточных вод и трубопроводов, загрязнённых липидами,с использованием бактериального препарата

The complex, effective and innovative cleaning technology for lipid-rich wastewater and pipelines contaminated by lipids, was developed. For this purpose, laboratory experiments were performed to verify the efficiency of bacterial preparation (Enterobacter aerogenes E13, Arthrobacter sp. N3 and Bacillus coagulans S1) to degrade the grease in water and in drainpipes. The results showed that selected microorganisms intensively degrade grease to light odourless precipitate, water and CO2, thus could be applied in industry. For optimization of technological cleaning processes, the response surface methodology was used. The optimal parameters for biological model wastewater treatment were determined: concentration of grease − 4.5–6.0 g/l, amount of bacterial preparation −5.5–6.0%, pH – 8–9. Due to optimization, the grease degradation rate increased by 20–30%. The optimization of drainpipe cleaning technology was achieved in two stages. During the first stage, the experiments were performed in laboratory flasks; during the second stage, optimized cleaning process was tested in a pilot plant. The following optimal parameters were set: pH – 8, amount of bacterial preparation –1.25 l/m2 and harness of water – 0.0 mmol/l. In water of medium hardness, the rate of biodegradation process is 15–20% less. A satisfactory efficiency of grease biodegradation was achieved in the pilot plant: the 86.7% of grease were digested in 21 days. Besides, living microorganisms were detected inside the clean drainpipe. Santrauka Sukurta kompleksinė, efektyvi ir inovacinė nuotekų bei vamzdynų, užterštų riebalais, valymo technologija. Atlikti laboratoriniai eksperimentai, siekiant nustatyti biopreparato, sudaryto iš Enterobacter aerogenes E13, Arthrobacter sp. N3 ir Bacillus coagulans S1, riebalų skaidymo efektyvumą kiek vandenyje, tiek vamzdyje. Gauti rezultatai parodė, kad atrinkti mikroorganizmai intensyviai skaido riebalus iki lengvų, neturinčių nemalonaus kvapo nuosėdų, vandens ir CO2, todėl gali būti taikomi pramonėje. Technologiniam valymo procesui optimizuoti taikyta reakcijos paviršiaus metodologija. Nustatyti optimalūs nuotekų, užterštų riebalais, valymo technologiniai parametrai: riebalų koncentracija – 4,5–6,0 g/l, biopreparato kiekis – 5,5–6,0%, pH – 8–9. Optimizavus procesą, riebalų skaidymo greitis padidėja 20–30 %. Vamzdžių, užterštų riebalais, valymo technologijos optimizavimas atliktas dviem etapais. Pirmajame etape eksperimentiniai tyrimai atlikti kolbose, antrajame etape optimizuotas procesas testuotas valant riebalinius teršalus bandomajame įrenginyje. Nustatyti optimalūs valymo parametrai: pH – 9, biopreparato kiekis – 1,25 l/m2 ir vandens kietis – 0,0 mmol/l. Esant vidutiniam vandens kiečiui biodagradacijos proceso greitis sumažėja 15–20%. Geras riebalų skaidymo efektyvumas pasiektas bandomajame įrenginyje, po 21 paros suskaidyta 86,7 % riebalų. Taip pat ant švaraus vamzdžio sienelių rasta gyvų mikroorganizmų. Резюме Создана комплексная, эффективная и инновационная технология очистки сточных вод и трубопроводов, загрязнённых липидами. С целью проверки эффективности бактериального состава (Enterobacter aerogenes E13, Arthrobacter sp. N3 и Bacillus coagulans S1) для расщепления жиров в воде и водосточной трубе были выполненылабораторные эксперименты. Полученные результаты показали, что отобранные микроорганизмы интенсивнорасщепляют жир до лёгкого осадка без побочного запаха воды и CO2 и могут быть применены в промышленности. Для оптимизации технологических процессов очистки использовался метод математического моделирования.Были определены оптимальные параметры для биологической обработки сточных вод: концентрация жира – 4,5– 6,0 г/л, количество бактериального состава – 5,5–6,0%, pH фактор – 8–9. После оптимизации скорость деградации жира увеличилась на 20–30%. Оптимизация технологии по очистке водосточных труб была выполнена на двухстадиях. На первой стадии эксперименты были выполнены в лабораторных колбах. На второй стадии оптимизационный процесс очистки был проведен в пилотной установке. Были установлены оптимальные параметры: pH фактор – 8, количество бактериального состава – 1,25 л/м2 и жёсткость воды – 0,0 ммол/л. В среднежёсткой водескорость процесса биологического распада была на 15–20% меньше. Хорошая биодеградация жира была установлена в пилотной установке. 86,7% жира было расщеплено за 21 день. Также в чистой водосточной трубе были обнаружены живые микроорганизмы.