ZONG Ying, JIANG Xu-feng, YUE Cong-wei, SUN Jing

(Department of Material and Oil, Air Force Logistics College, Xuzhou 221000, China)

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Rapidly determining fuel pollution level of aviation lubricating oil 50-1-4Φ by mid-infrared spectrometry

ZONG Ying, JIANG Xu-feng, YUE Cong-wei, SUN Jing

(DepartmentofMaterialandOil,AirForceLogisticsCollege,Xuzhou221000,China)

A series of aviation lubrication oil 50-1-4Φ samples were prepared with different RP-3 content, and then these samples were analyzed by Fourier transform mid-infrared spectrometer (FTIR). The infrared region of 805-755 cm-1was selected as quantitative area for determining fuel pollution level of aviation lubrication oil. Finally, correlation of the testing peak area and the fuel pollution level of corresponding samples were analyzed, and the regression equation was proposed. The results show that determining jet fuel pollution level of aviation lubricating oil by FTIR is feasible and reliable.

mid-infrared spectrum; aviation lubricating oil; fuel pollution level

Fuel oil may seep into the oil tank in the operation of aviation turbine engine due to various reasons, which will pose some serious safety hazards, e.g. the viscosity and flash point of aviation lubricating oil will decrease or the wear of machine element will increase or even to arouse explosion fire, etc.[1]. In recent years, great research achievements have been obtained in testing physical and chemical properties of oils and monitoring the used oil status by Fourier transform mid-infrared spectrometer (FTIR)[2-8]. However, there is no special method for determining the content of lightweight oil in the lubricating oil domestically and there are fewer reports on testing the pollution level of lubricating oil by using this method.

In this paper, 25 lubricating oil samples with different contents of RP-3 were analyzed by FTIR to provide more experimental data for rapidly determining fuel content in lubricating oil.

1 Experiment

1.1 Instruments

The main instruments used in this experiment include WQF310 FTIR produced by Beijing Ruili Inst-

rument Analysis Co., Ltd; HF-8 fixed liquid pool, with KBr windows with the optical distance of 0.1 mm, produced by Tianjin Tianguang Optical Instruments Co., Ltd.

1.2 Preparation of samples

The polluted lubricating oil samples were prepared with different proportion of RP-3 to 50-1-4Φ new oil. Micro-adjustable pipette was used to transfer different amount of RP-3 into 50-1-4Φ new oil. The volume ratios of RP-3 and 50-1-4Φ new oil in the prepared samples are shown in Table 1.

Table 1 Preparation table of aviation lubricating oil fuel pollution samples

No.VRP-3/V50-1-4ФNo.VRP-3/V50-1-4ФNo.VRP-3/V50-1-4Ф10.010100.412190.71420.020110.444200.76930.048120.474210.83340.091130.500220.90950.167140.526230.95260.231150.556240.98070.286160.588250.99080.333170.62590.375180.667

1.3 Experimental procedure

The above samples were analyzed by FTIR with the resolution ratio of 4.0 cm-1, scanning 32 times in total for every sample.

The correlation and regression of the data in Table 1 and infrared spectra of corresponding samples were analyzed, and then the regression equation was proposed.

2 Results and discussion

2.1 FTIR analysis

Referring to American Society for Testing and Materials (ASTM) standard Table A1.1, E2412-10, the testing peak area in the infrared spectrum ranging from 804.171 cm-1to 755.959 cm-1was used to calculate the fuel pollution level, i.e. volume ratio of RP-3 and 50-1-4Φ new oil. The FTIR spectra of the samples (No.1, 8, 16 and 24) are shown in Fig.1.

Fig.1 Infrared spectra of the samples No.1,8,16 and 24

The testing peak areas of all samples are shown in Table 2.

Table 2 Infrared spectrum peak areas of aviation lubricating oil fuel pollution samples

No.AreaNo.AreaNo.Area10.964100.523190.18320.926110.428200.22230.989120.344210.05140.878130.414220.03550.780140.336230.10960.619150.343240.02270.677160.294250.10480.567170.32490.582180.288

2.2 Correlation analysis of fuel pollution level and testing peak areas of all samples

Correlation coefficient between pollution level of all samples and their testing peak areas of the corresponding FTIR spectrum is 0.976 8, indicating significant correlation of fuel pollution level and the testing peak areas of all samples.

2.3 Regression analysis of fuel pollution level and testing peak areas of all samples

Polynomial regression curve for fuel pollution level of all samples and their testing peak areas in FTIR spectra is shown in Fig.2.

Fig.2 Polynomial regression curve of prepared samples

The curve equation is shown in Eq.(1). After calculating, fitting degree is 0.975 4, indicating that accuracy is 97.54% for the calculated fuel pollution level compared with the true value of samples.

Y=-6.771 8X6+39.637X5-74.175X4+

(1)

3 Conclusion

In this paper, 25 polluted 50-1-4Φ lubricating oil samples with different content of RP-3 were prepared. All samples were analyzed by FTIR technology. Referring to ASTM: E2412-10, the infrared region of 805-755 cm-1was selected as quantitative area for determining fuel pollution level of aviation lubrication oil. The correlation of the fuel pollution level and the testing peak area of corresponding samples was analyzed. The results show that they are highly correlated. Based on this, the regression analysis was made and regression equation was obtained. The fitting effect is good, showing that determining jet fuel pollution level of aviation lubricating oil by FTIR is feasible and reliable.

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中紅外光譜法測(cè)定航空潤(rùn)滑油50-1-4Φ燃油污染水平

宗 營(yíng)， 姜旭峰， 岳聰偉， 孫 靜

(空軍勤務(wù)學(xué)院 航空油料物資系， 江蘇 徐州 221000)

本文對(duì)配制的不同3號(hào)噴氣燃料含量的50-1-4Ф潤(rùn)滑油樣品作為航空潤(rùn)滑油燃料污染水平測(cè)定的標(biāo)準(zhǔn)模擬油樣進(jìn)行紅外光譜分析， 選擇紅外譜圖中805-755 cm-1區(qū)域作為測(cè)定滑油燃料污染水平的定量區(qū)域， 對(duì)此區(qū)域峰面積與相應(yīng)的樣品燃料污染水平的相關(guān)性進(jìn)行分析并給出回歸方程。 結(jié)果表明， 利用傅立葉變換紅外光譜法測(cè)定航空潤(rùn)滑油的噴氣燃料污染水平是可行的， 測(cè)定結(jié)果是可靠的。

中紅外光譜； 航空潤(rùn)滑油； 燃料污染水平

ZONG Ying, JIANG Xu-feng, YUE Cong-wei, et al. Rapidly determining fuel pollution level of aviation lubricating oil 50-1-4Φ by mid-infrared spectrometry. Journal of Measurement Science and Instrumentation, 2015, 6(2)： 190-192.

10.3969/j.issn.1674-8042.2015.02.014

JIANG Xu-feng (jiangziya@163.com)

1674-8042(2015)02-0190-03 doi： 10.3969/j.issn.1674-8042.2015.02.014

Received date： 2015-03-08

CLD number： TP274+.5 Document code： A