【作者】 屈海峰；

【导师】 李文江；

【作者基本信息】 辽宁工程技术大学 ， 电力电子与电力传动， 2009， 硕士

【摘要】 提升机系统是煤矿的四大系统之一,素有矿山咽喉之称。提升机系统的安全至关重要,从超前防护的思想模式出发,研究提升机系统故障的早期故障预兆与做出预测,目前是个难题。本文对提升机故障诊断做了研究与设计,总体讨论了矿井提升机的组成,对其各个部分进行了故障分析。以ARM S3C2440为核心设计了嵌入式数据采集的硬件系统,并基于linux操作系统对提升机数据采集部分驱动程序进行了开发,具有精度高、速度快的特点。综合现代智能测试与诊断技术,研究开发了一个基于BP神经网络系统的提升机故障诊断系统。应用三层BP神经网络可以实现任意非线性的输入输出逻辑关系,用在故障模式识别时,其结果有收敛解。所以我们引入智能BP网络在诊断过程中,利用发生故障时的各种信息作为样本,应用Matlab工具箱进行仿真,以部分故障为例进行了网络训练,训练好的神经网络经测试达到了诊断的效果,可以进行提升机故障模式的识别。更多还原

【Abstract】 The mine hoist system is one of the mine four systems, known as the throat of the mine, hoist system security is very important. From the protection mode of thinking ahead of departure to study the failure of elevator harbinger of early failures and to make forecasts is currently a challenge.In this paper, researching and designing the fault diagnosis of hoist , general discussion the composition of the mine hoist ,and making the fault analysis of its various parts. The ARM S3C2440 as the core to design of embedded data acquisition hardware system, and is based on linux operating system to enhance the development of the driver of data acquisition part of high accuracy and fast speed.Integrated test and diagnostic techniques of modern intelligence, researched and developed fault diagnosis system of hoist based on BP neural network. Application of three-layer BP neural network can realize an arbitrary non-linear input-output relationship, used in the fault pattern recognition, the results are convergent solution. Therefore, we introduced intelligence BP network in the process of the diagnosis.using a variety of failure information as samples, using Matlab toolbox for simulation, to some failures as an example of the network training, the trained neural network has been tested and reached effects of a diagnosis, can reach the identification of hoist failure mode.更多还原