Department of Biomechtronics Engineering, National Pingtung University of Science & Technology, Pingtung, 91207 Taiwan.
Sensors (Basel). 2010;10(8):7157-69. doi: 10.3390/s100807157. Epub 2010 Jul 29.
The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves.
柴油机是大多数农业车辆的主要动力源。柴油机排放的控制是一个重要的全球性问题。燃油喷射控制系统直接影响柴油机的燃油效率和排放。齿条变形、电磁阀故障和齿条行程传感器故障等恶化故障可能存在于电子柴油控制（EDC）系统的燃油喷射模块中。在这些故障中，电磁阀故障最有可能发生在使用中的柴油机上。根据以往的研究，这种故障是由于柱塞和套筒的磨损，长期使用、润滑剂降解或发动机过热造成的。由于难以识别电磁阀的劣化，本研究旨在为使用中的农业车辆开发一种传感器识别算法，无需拆卸 EDC 系统的燃油泵，即可清楚地分类电磁阀的可用性。提出了一种诊断算法，包括反馈控制器、参数识别器、线性可变差动变压器（LVDT）传感器和神经网络分类器。实验结果表明，所提出的算法可以准确识别电磁阀的可用性。
