基于模糊神经网络的茶园拖拉机远程故障诊断系统

梁军; 马志怡; 盘朝奉; 陈龙

doi:10.3969/j.issn.1671-7775.2021.05.006

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江苏大学学报（自然科学版） ›› 2021, Vol. 42 ›› Issue (5) : 533-539. DOI: 10.3969/j.issn.1671-7775.2021.05.006

论文

基于模糊神经网络的茶园拖拉机远程故障诊断系统

作者信息 +

Remote fault diagnosis system of tea garden tractor based on fuzzy neural network

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文章历史 +

摘要

针对茶园拖拉机传统故障诊断对故障信息的采集存在严重滞后性的问题，提出一种基于模糊神经网络（fuzzy neural network,FNN）的茶园拖拉机远程故障诊断系统（remote fault diagnosis system,RFDS）.该方法融合模糊算法和神经网络的优点，通过对车辆运行的实时监控，远程处理车辆信息，获取车辆潜在的故障和实时故障信息，避免了传统方式需进行的大量检测，为维修争取到了更多的时间，提高了生产效率.该系统以仿真软件Carsim为基础，利用Carsim实时模拟车辆运行情况，通过训练集和测试集对算法模型进行训练和验证，结果表明：FNN诊断算法满足系统性能要求，准确率可以达到90%以上，可远程准确诊断茶园拖拉机故障.此外，RFDS技术对于车辆的开发也有重要的作用，可以在车辆的研发阶段通过远程故障诊断系统进行车辆性能评估，节省了大量的人力资源.

Abstract

To solve the problem of traditional fault diagnosis for tea garden tractor with serious delay during collecting fault information, a remote fault diagnosis system(RFDS) of tea garden tractor was proposed based on fuzzy neural network(FNN). Combining the advantages of fuzzy algorithm and neural network, through the real-time monitoring of vehicle operation information, the vehicle information was remotely processed to obtain vehicle potential fault and real-time fault information for avoiding a large number of detections in traditional methods, and more time was gained for maintenance and improving production efficiency. Based on the simulation software of Carsim, the vehicle operation was simulated in real time,and the algorithm model was trained and verified by training set and test set. The results show that FNN diagnosis algorithm can meet the performance requirements of the system, and the accuracy can reach more than 90%. The tractor fault in tea garden can be diagnosed remotely. RFDS technology also plays an important role in the development of vehicles. The performance of vehicles can be evaluated through remote fault diagnosis system in the R & D stage of vehicles, which saves a lot of human resources.

导出引用

梁军, 马志怡, 盘朝奉, 等. 基于模糊神经网络的茶园拖拉机远程故障诊断系统[J]. 江苏大学学报（自然科学版）, 2021, 42(5): 533-539 https://doi.org/10.3969/j.issn.1671-7775.2021.05.006

LIANG Jun, MA Zhiyi, PAN Chaofeng, et al. Remote fault diagnosis system of tea garden tractor based on fuzzy neural network[J]. Journal of Jiangsu University(Natural Science Edition), 2021, 42(5): 533-539 https://doi.org/10.3969/j.issn.1671-7775.2021.05.006

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