| 光谱学与光谱分析 |
|
|
|
|
|
| A Fast Method to Measure TAN and TBN of Used Lubricant Oil Based on Portable Infrared Spectrometer |
| YANG Kun1, 2, WU Tong1, ZOU Mao1, SHI Li-jie3 |
1. Reliability Engineering Institute, School of Energy and Power Engineering，Wuhan University of Technology, Wuhan 430063，China
2. National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063，China
3. Spectro Scientific (Beijing) Inc.，Beijing 100176，China |
|
|
|
|
Abstract TAN and TBN which provide information about the degree of lubricating oil oxidation and the properties of alkali reserve is usually used in measurement of aging degree of lubricant, and its value can determine whether the amount of certain acid additives added is enough. It can avoid the problems such as, the abnormal wearing, corruption, deposit, filter blocking. The TAN and TBN of Lubricating oil is measured by the standard based on acid-base titration, in which potentiometric titration is used more. However it has to face the problems of complicated operation, expensive consuming material, and large quantity of sample oil, well trained operator and difficulty in handling reagent. Due to the oxidation of lubricating oil products and alkaline additives in the infrared spectrum has strong structural information, therefore, the TAN and TBN of lubricating oil can be monitored by infrared spectra. The quantification of TAN and TBN based on neutralization reaction was built up through the measurement of portable infrared spectroscopy. The reliable quantification of TAN and TBN can be archived by three procedures of lubricant type classification, building up lubricant library and multi-parameters regression. This method is supported by recent ASTM D7889 standard. Compared with the other standard, this method has a high speed of analysis, and it can read out measurement result directly without any solvent. The accuracy of measurement is relatively high, operation is relatively simple, and improve the detection speed at a certain degree. The method can be used widely in industry field, including in laboratory offline measurement and in situ online measurement.
|
|
Received: 2015-09-28
Accepted: 2016-02-02
|
|
|
|
Corresponding Authors:
YANG Kun
E-mail: kunyangwhut@163.com
|
|
[1] Fr V D V, Sedman J, Yaylayan V, et al. Applied Spectroscopy , 2003, 57(11): 1425
[2] Sedman J. Tribology Transactions, 2006, 49(3): 410.
[3] LIU Wei, FAN Ke-qing, BAO Yan-chun, et al(刘 伟，范可青，包艳春，等). Chinese Journal of Pharmaceutical Analysis(药物分析杂志)，2009，29(1)：125.
[4] LEI De-qing, FENG Yan-chun, HU Chang-qin(雷德卿，冯艳春，胡昌勤). Chinese Pharmaceutical Journal(中国药学杂志)，2010，45(4)：1097.
[5] Wu D, He Y, Feng S, et al. Journal of Food Engineering, 2008, 84(1): 124. |
| [1] |
LI Jie, ZHOU Qu*, JIA Lu-fen, CUI Xiao-sen. Comparative Study on Detection Methods of Furfural in Transformer Oil Based on IR and Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 125-133. |
| [2] |
XING Hai-bo1, ZHENG Bo-wen1, LI Xin-yue1, HUANG Bo-tao2, XIANG Xiao2, HU Xiao-jun1*. Colorimetric and SERS Dual-Channel Sensing Detection of Pyrene in
Water[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 95-102. |
| [3] |
LEI Hong-jun1, YANG Guang1, PAN Hong-wei1*, WANG Yi-fei1, YI Jun2, WANG Ke-ke2, WANG Guo-hao2, TONG Wen-bin1, SHI Li-li1. Influence of Hydrochemical Ions on Three-Dimensional Fluorescence
Spectrum of Dissolved Organic Matter in the Water Environment
and the Proposed Classification Pretreatment Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 134-140. |
| [4] |
LI Yu1, ZHANG Ke-can1, PENG Li-juan2*, ZHU Zheng-liang1, HE Liang1*. Simultaneous Detection of Glucose and Xylose in Tobacco by Using Partial Least Squares Assisted UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 103-110. |
| [5] |
WANG Xin-qiang1, 3, CHU Pei-zhu1, 3, XIONG Wei2, 4, YE Song1, 3, GAN Yong-ying1, 3, ZHANG Wen-tao1, 3, LI Shu1, 3, WANG Fang-yuan1, 3*. Study on Monomer Simulation of Cellulose Raman Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 164-168. |
| [6] |
LIANG Ye-heng1, DENG Ru-ru1, 2*, LIANG Yu-jie1, LIU Yong-ming3, WU Yi4, YUAN Yu-heng5, AI Xian-jun6. Spectral Characteristics of Sediment Reflectance Under the Background of Heavy Metal Polluted Water and Analysis of Its Contribution to
Water-Leaving Reflectance[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 111-117. |
| [7] |
LIU Jia1, 2, GUO Fei-fei2, YU Lei2, CUI Fei-peng2, ZHAO Ying2, HAN Bing2, SHEN Xue-jing1, 2, WANG Hai-zhou1, 2*. Quantitative Characterization of Components in Neodymium Iron Boron Permanent Magnets by Laser Induced Breakdown Spectroscopy （LIBS）[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 141-147. |
| [8] |
XIA Ming-ming1, 2, LIU Jia3, WU Meng1, 2, FAN Jian-bo1, 2, LIU Xiao-li1, 2, CHEN Ling1, 2, MA Xin-ling1, 2, LI Zhong-pei1, 2, LIU Ming1, 2*. Three Dimensional Fluorescence Characteristics of Soluble Organic Matter From Different Straw Decomposition Products Treated With Calcium Containing Additives[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 118-124. |
| [9] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [10] |
LAN Yan1，WANG Wu1，XU Wen2，CHAI Qin-qin1*，LI Yu-rong1，ZHANG Xun2. Discrimination of Planting and Tissue-Cultured Anoectochilus Roxburghii Based on SMOTE and Inception-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 158-163. |
| [11] |
HE Qing-yuan1, 2, REN Yi1, 2, LIU Jing-hua1, 2, LIU Li1, 2, YANG Hao1, 2, LI Zheng-peng1, 2, ZHAN Qiu-wen1, 2*. Study on Rapid Determination of Qualities of Alfalfa Hay Based on NIRS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3753-3757. |
| [12] |
SONG Yi-ming1, 2, SHEN Jian1, 2, LIU Chuan-yang1, 2, XIONG Qiu-ran1, 2, CHENG Cheng1, 2, CHAI Yi-di2, WANG Shi-feng2，WU Jing1, 2*. Fluorescence Quantum Yield and Fluorescence Lifetime of Indole, 3-Methylindole and L-Tryptophan[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3758-3762. |
| [13] |
LI Wei1, TAN Feng2*, ZHANG Wei1, GAO Lu-si3, LI Jin-shan4. Application of Improved Random Frog Algorithm in Fast Identification of Soybean Varieties[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3763-3769. |
| [14] |
WANG Zhi-qiang1, CHENG Yan-xin1, ZHANG Rui-ting1, MA Lin1, GAO Peng1, LIN Ke1, 2*. Rapid Detection and Analysis of Chinese Liquor Quality by Raman
Spectroscopy Combined With Fluorescence Background[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3770-3774. |
| [15] |
YI Min-na1, 2, 3, CAO Hui-min1, 2, 3*, LI Shuang-na-si1, 2, 3, ZHANG Zhu-shan-ying1, 2, 3, ZHU Chun-nan1, 2, 3. A Novel Dual Emission Carbon Point Ratio Fluorescent Probe for Rapid Detection of Lead Ions[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3788-3793. |
|
|
|
|
