硕士学位毕业论文

硕士研究生：陈敏

指导教师：沈斌 教授

答辩时间：2012.06

摘要

电动助力转向系统近年来得到了迅速发展，随着被越来越广泛地应用在轿车上，人们对EPS系统的安全性和可靠性也提出了更高的要求。电动助力转向由电机来提供助力，作为一项新技术，和液压动力转向相比，EPS存在不同的故障模式，而作为EPS最重要的部件，传感器的故障研究，及其故障诊断技术就显得十分重要。本论文对EPS中最主要的扭矩传感器和车速传感器的各种故障进行研究和分析，建立了一套基于LM神经网络的传感器故障诊断系统。

本论文工作主要包括以下几个方面的内容：

首先，基于扭矩传感器和车速传感器的结构和工作原理的深入分析，应用故障树分析，建立了传感器的故障树模型，得出了故障原因；应用失效模式与影响分析得到了传感器故障的相关重要度，找出传感器故障诊断的最优诊断模式。

其次，通过对人工神经网络和传感器故障原因和特点的研究，在Matlab平台上设计了基于LM神经网络的EPS传感器故障诊断系统，且具有很强的兼容性。

最后，通过台架实验得到相关故障模式数据作为样本数据，对设计的传感器故障诊断系统进行试验论证。结果表明LM神经网络收敛快，其精度和准确度达到了正确诊断的要求，可以用于EPS传感器的实时故障诊断。

本文设计的EPS传感器故障诊断系统，切实有效，对其他传感器的故障诊断具有指导意义，有很大的实用价值。

关键词：电动助力转向，故障诊断，故障树，失效模式与影响分析，神经网络，Matlab

ABSTRACT

    The electric power steering system has been developing rapidly in recent years. As more and more widely applied in the automobile industry, people put forward higher requirements to the safety and reliability of the EPS system. As a new technology, the EPS is provided the impetus by an electric motor. Compared with the hydraulic power steering, the EPS existences of different failure modes. Because the EPS is the most important component in the auto, so that the sensors' failure research and their fault diagnosis technologies in EPS ,are particularly important. This thesis researches with the faults of the torque sensor and speed sensor，which are the most important components in the EPS, and has established a sensor fault diagnosis system，which is based on the LM neural network.

    The principal contents studied in this thesis are as follows:

First, based on in-depth analysis of the structure and working principles of the torque sensor and speed sensor, the thesis constructs the sensor fault tree models and identifies the causes of the malfunction, which are with the application of fault tree analysis. And then through the failure mode and effects analysis determines the several importances of the sensor failure, which can identify the optimal diagnostic mode of the sensor fault diagnosis.

    Second, with the research on the the artificial neural network and the causes and characteristics of the sensor failure, the thesis designs a EPS sensor fault diagnosis system on the Matlab platform, which is based on the LM neural network and has a strong compatibility.

    Finally, demonstrate the sensor fault diagnosis system with the sample data of failure modes from the bench test. The results show that the LM neural network convergence fast, and its precision and accuracy can meet the requirements of the correct diagnosis. So that it can be used for real-time fault diagnosis of EPS sensors.

The design of the EPS sensor fault diagnosis system is effectively .It has a guiding significance for the other sensor fault diagnosis and great practical value.

    Keywords: Electric power steering, fault diagnosis, fault tree, failure mode and effects analysis, neural networks, Matlab