Review on Intelligent Diagnosis Technology of Electronically Controlled Fuel Injection System of ME Diesel Engine
DOI:
https://doi.org/10.54097/ajst.v1i2.351Keywords:
Fuel injection system, Feature extraction, Fault diagnosis, Health management.Abstract
ME diesel engine plays an important role in realizing energy conservation and environmental protection and improving the intelligent level of ship engine room. Because of its high technical content and high added value, using intelligent diagnosis technology to ensure safe and reliable work is an important means to realize intelligent engine room. Taking the ship electronic fuel injection system as an example, this paper introduces its working principle and common faults, analyzes and summarizes the research status of intelligent diagnosis technology at home and abroad in four aspects: fault mechanism, data measurement and feature extraction, fault mode classification and residual life prediction. Then, it analyzes the problems and future development trend of intelligent diagnosis technology, and points out that developing a health management system integrating weak fault signal extraction, multi-source data analysis, quantitative judgment of fault mode, remaining life prediction and maintenance suggestions is an important development goal in the future.
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References
Gao Zongying, Zhu Jianming Diesel fuel supply and regulation [M] .Beijing: China Machine Press, 2009
Peiyong Ni, Xiangli Wang,Hu Li. A review on regulations ,current status, effects and reduction strategies of emissions for marine diesel engines[J]. Fuel,2020(279).
Bai yun. Study on fluctuation characteristics of circulating fuel injection quantity in high pressure common rail fuel system [D].Harbin: Harbin Engineering University, 2017
Fu Yuhui, Weng Yubo Market analysis of marine low-speed machine brand [J] China ship inspection, 2018,72-75
Zeng Dingjun Design analysis and Research on electronic control system of me diesel engine [D]. Harbin: Harbin Engineering University, 2011
Yu Yonghua, marine diesel engine health assessment based on instantaneous speed and machine learning[J], internal combustion engine engineering.
Chai Yanyou Research on fault diagnosis of marine diesel engine based on nuclear learning theory [D] Harbin: Harbin Engineering University, 2012.
The State Council of the people's Republic of China Outline of building a transportation power [EB / OL]. 2019-09-19, http://www.gov.cn/zhengce/2019-09/19/content_5431432.htm
The State Council of the people's Republic of China Smart ship development action plan (2019-2021) [EB / OL]. December 30, 2018, http://www.gov.cn/xinwen/2018-12/30/content_5353550.htm
Ministry of transport of the people's Republic of China Guidance on Intelligent shipping simulation [EB / OL]. 2019-11-19, https://xxgk.mot.gov.cn/jigou/haishi/201911/t20191119_3298977.html
The State Council of the people's Republic of China Digital transportation development planning outline [EB / OL]. 2019-07-28 http://www.gov.cn/xinwen/2019-07/28/content_5415971.htm
JIANG J W, HU Y H, CAI D L. Fault diagnosis expert system of marine propulsion system based on Access database[C]//Proceedings SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, International Society. Shanghai: SPIE,2018
Hu Yihuai Analysis and safety assessment of ship engine damage accident [M] Beijing: People's Communications Press, 2013:12
LI B, CHEN M Y, WANG R R, et al. Fault diagnosis for the ship electric propulsion system[C]//Proceedings of 2015 11th International Conference on Natural Computation. Zhangjiajie，China: IEEE, 2015: 714-718
Yang Yongdong Common problems and management points of me marine EFI main engine - control system [J] World shipping, 2016,39 (8): 24-30
Xue Yongzhang Typical fault analysis and treatment of man B & W me two-stroke EFI diesel engine [J] World shipping, 2019,42 (2): 39-41
Liu Binghai This paper briefly describes the working principle of man me / me-c marine EFI diesel engine [J] Tianjin navigation. 2018 (4): 28-31
Huang Lin, Cheng Gang, Zhu Guoguo Optimization prediction and Simulation of diesel engine thermodynamic system fault [J] Computer simulation, 2019,36 (3): 426-431
Zhu Tingting, Zuo Chengji Thermodynamic modeling and Simulation of diesel engine high pressure common rail fuel system [J] Internal combustion engine and power plant, 2016,33 (3): 46-49,55
Zhao Zhiqiang, Zhang Jiarui, Luo Chiheng, et al Typical fault simulation and data analysis of marine diesel engine based on AVL BOOST [J] Chinese ship research, DOI: 10.19693/j.issn 1673-3185.01883
Y.Bai,L.Y.Fan,X.Z.Ma,et al. Effect of Injector Parameters On The Injection Quantity of Common Rail Injection Sytem for Diesel Engines. International Journal of Automotive Technology[J]. International Journal of Automotive Technology,2016,17(4):567-579
Baiyun, fan Liyun, Matthew, et al Study on fuel injection stability of high pressure common rail system based on state matrix [J] Internal combustion engine engineering, 2016,37 (6): 156-163
Fei Hongzi, Qu Chao, Wei Yunpeng, et al Simulation Research on prediction model of circulating fuel injection quantity of high pressure common rail diesel engine, Journal of Harbin Engineering University [J], https://kns.cnki.net/kcms/detail/23.1390.u.20201112.1117.006.html
Ling Jian, fuel injection quantity observation method of common rail diesel engine based on instantaneous rail pressure waveform characteristic parameters [J], internal combustion engine engineering, 2017,38 (1): 63:69
Liu Xuelong, Su Wanhua, Zhan Qiang Study on the influence of high pressure oil pipe on the performance of common rail system [J] Internal combustion engine engineering, 2010,31 (5): 47-51,57
Su Haifeng, Zhang Youtong, Luo Xu, et al Test on water hammer pressure fluctuation of high pressure common rail system [J] Journal of internal combustion engines, 2011,29 (2): 163-168
Su Haifeng, Zhang Youtong, Luo Xu, et al Vibration elimination of water hammer pressure fluctuation in high pressure common rail system [J] Journal of internal combustion engines, 2013,31 (4): 379-383
G. Chiatti, O. Chiavola,E. Recco. Combustion diagnosis via block vibration signal in common rail diesel engine[J].2014 ,15(6):654-663.
W. Xi, Z. Li, Z. Tian, et al. A Feature Extraction and Visualization Method for Fault Detection of Marine Diesel Engines[J]. Measurement (2017), DOI: https://doi.org/10.1016/j.measurement.2017.11.035
Liu Jiameng, Ma Bo, Jiang Zhinong Misfire probability diagnosis of diesel engine based on noisy Max model and adjacent and opposite cylinder vibration signals [J] Journal of internal combustion engines, 2020,38 (6): 560-568
Zhang Yufei, Yao Ziyun, Tang Songlin, et al An engine fault diagnosis method based on principal component analysis and support vector machine [J] Chinese Journal of mechanical engineering, 2016,27 (24): 3307-3311
Li Fengming, Design and implementation of fault diagnosis of diesel engine fuel system based on wavelet neural network [D] Shandong University, 2010
F. Jia, Y. Lei, J.Lin, et al.Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data[J]. Mechanical system and signal processing,(2015),DOI: http://dx.doi.org/10.1016/j.ymssp.2015.10.025
Jiang Jiawei, Hu Yihuai, Li Fangyu, et al Condition monitoring method of marine low-speed diesel engine based on aakr model [J] Ship science and technology, 2021,43 (2): 158:162
Jia Baozhu, Jia Zhitao, Yu Peiwen, et al Data driven intelligent fault diagnosis method for ships [J], control engineering, 2019,26 (10), 1892-1898
Qin Ciwei Research on fault diagnosis of marine high pressure oil pump based on common rail pressure storage signal [D] China Ship Research Institute, 2019
Li Xiaopeng, Ni he, Jin Jiashan Research on Fault Simulation of fuel system of marine power plant [J] Computer simulation, 2019,36 (6): 26-31Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, “Electron spectroscopy studies on magneto-optical media and plastic substrate interfaces (Translation Journals style),” IEEE Transl. J. Magn. Jpn., vol. 2, Aug. 1987, pp. 740–741 [Dig. 9th Annu. Conf. Magnetics Japan, 1982, p. 301].
J. Porteiro，J. Collazo, D. Patino, et al. Diesel engine condition monitoring using a multi-net neural network system with nonintrusive sensors[J].Applied Thermal Engineering,31(2011)4097-4105
K. Nikzadfar, A. H. Shamekhi. Investigating the relative contribution of operational parameters on performance and emissions of a common-rail diesel engine using neural network[J].Fuel,125(2014)116-128.
Niu Xiaoxiao, Wang Hechun, Li Xu, et al Optimization of diesel engine performance prediction model based on neural network [J] Journal of internal combustion engines, 2018,36 (6): 561-568
Liu Yifan, Huang Lianzhong, sun Peiting, et al Performance evaluation method of marine main diesel engine in real ship data environment [J] Journal of internal combustion engines, 2018362 (2): 182-191
Yao Xiaoshan, Zhang Weidong, Zhou Ping, et al Research on fault prediction and health management technology of marine diesel engine based on oil monitoring [J] Journal of Wuhan University of Technology (traffic science and Engineering Edition), 2014,4:874-877
Hountalas D T. Prediction of Marine Diesel Engine Performance Under Fault Condition[J]. Applied Thermal Engineering,2000,20(18):1753-1783.
Basurko O C,Uriondo Z. Conditon-based Maintenance for medium speed diesel engines used in vessels in operation[J]. Applied Thermal Engineering,2015,80;404-412.
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