Health monitoring of in-cylinder sensors and fuel injectors using an external accelerometer

被引:3
作者
Jeon, Woongsun [1 ]
Georgiou, Anastasis [2 ]
Sun, Zongxuan [2 ]
Rothamer, David A. [3 ]
Kim, Kenneth [4 ]
Kweon, Chol-Bum [4 ]
Rajamani, Rajesh [2 ,5 ]
机构
[1] Chung Ang Univ, Sch Elect & Elect Engn, Seoul, South Korea
[2] Univ Minnesota, Dept Mech Engn, Minneapolis, MN USA
[3] Univ Wisconsin Madison, Dept Mech Engn, Madison, WI USA
[4] US Army, DEVCOM, Res Lab, Aberdeen Proving Ground, MD USA
[5] Univ Minnesota, Dept Mech Engn, 111 Church St SE, Minneapolis, MN 55455 USA
来源
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL | 2025年 / 24卷 / 01期
关键词
Engine health monitoring; sensor fault; combustion estimation; accelerometer; in-cylinder pressure; DIESEL-ENGINE; FAULT-DETECTION; PRESSURE RECONSTRUCTION; WAVELET TRANSFORM; VIBRATION; DIAGNOSIS; SIGNAL; MISFIRE;
D O I
10.1177/14759217241232257
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper focuses on the development of a methodology to monitor the health of an engine by detecting any failures in the fuel injectors or in-cylinder pressure sensors using an accelerometer that is non-intrusively mounted on the engine block. A multi-cylinder engine with each cylinder having its own pressure sensor and injector is considered. First, a model relating the combustion component of the measured acceleration signal to the combustion component of in-cylinder pressure is proposed. Then, gains of the model are tuned to reduce the cycle-to-cycle estimation error by analyzing cycle-to-cycle variations with respect to the combustion pressure peak and engine vibration peak. Using the developed model, cylinder combustion pressures are estimated from engine vibration signals with small cycle-to-cycle estimation errors. Subsequently, a health monitoring system that can detect faults in pressure sensors, fuel injectors, and the accelerometers is proposed based on residues obtained from the difference between estimated combustion pressure and measured pressure signals. The source of the failed component can be identified uniquely by analyzing the pattern of residues. The proposed combustion pressure estimation algorithms are validated by extensive evaluation with experimental data obtained by operating a four-cylinder compression-ignition direct-injection engine with a range of experimental data. Finally, the developed health monitoring system is evaluated with various failure scenarios involving faults in the in-cylinder pressure sensor, fuel injector, and accelerometer.
引用
收藏
页码:164 / 184
页数:21
相关论文
共 43 条
[1]   Determination of specific heat ratio and error analysis for engine heat release calculations [J].
Abbaszadehmosayebi, G. ;
Ganippa, Lionel .
APPLIED ENERGY, 2014, 122 :143-150
[2]  
Amezcua E., 2020, SAE TECHNICAL PAPER, P1
[3]   Classification-Based Fuel Injection Fault Detection of a Trainset Diesel Engine Using Vibration Signature Analysis [J].
Ayati, Moosa ;
Shirazi, Farzad A. ;
Ansari-Rad, Saeed ;
Zabihihesari, Alireza .
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 2020, 142 (05)
[4]  
Bizon K., 2011, SAE Technical Paper (2011-24-0161
[5]  
Bohn C, 2005, 2005 International Conference on Control and Automation (ICCA), Vols 1 and 2, P239
[6]  
Brunt M.F. J., 1999, SAE Technical Paper No. 1999-01-0187
[7]   Fault detection and diagnostic method of diesel engine by combining rule-based algorithm and BNs/BPNNs [J].
Cai, Baoping ;
Sun, Xiutao ;
Wang, Jiaxing ;
Yang, Chao ;
Wang, Zhengda ;
Kong, Xiangdi ;
Liu, Zengkai ;
Liu, Yonghong .
JOURNAL OF MANUFACTURING SYSTEMS, 2020, 57 :148-157
[8]   Reconstructing cylinder pressure from vibration signals based on radial basis function networks [J].
Du, H ;
Zhang, L ;
Shi, X .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2001, 215 (D6) :761-767
[9]   Acoustic emission characteristics of a single cylinder diesel generator at various loads and with a failing injector [J].
Dykas, Brian ;
Harris, James .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 93 :397-414
[10]   The development of automated pattern recognition and statistical feature isolation techniques for the diagnosis of reciprocating machinery faults using acoustic emission [J].
El-Ghamry, MH ;
Reuben, RL ;
Steel, JA .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2003, 17 (04) :805-823