基于PCI的船舶动力装置监测与故障诊断系统设计

发布时间：2018-03-24 04:29

本文选题：船舶动力装置　切入点：PCI接口　出处：《武汉理工大学》2014年硕士论文

【摘要】：随着航运业的快速发展，，船舶的安全问题越来越受到人们的关注。船舶动力装置是产生、传递和消耗能量的全部机械设备的总和，为船舶的正常航行和其它各项工作开展提供足够的能量，它是船舶上最重要的组成部分。各类船舶故障中约有60%-80%的故障是由动力装置设备部分引起的，传统故障诊断方法较落后、效率低、劳动强度大、维护成本高，因此需要开展船舶动力装置设备的状态监测与故障诊断技术研究。将现代计算机技术和嵌入式技术应用于船舶监测与故障诊断技术研究，提出了一种基于计算机PCI接口的船舶动力装置监测和故障诊断系统设计方案。本文主要讲述了系统的平台设计方法和过程，包括以下内容：介绍了船舶动力装置和故障诊断技术的相关知识，结合当前国内外在该领域的研究现状，分析了船舶动力装置监测与故障诊断系统平台的功能需求，设计了整个系统的总体方案，并对各个单元模块的设计方案进行论证。系统以工控机和cyclone III系列FPGA控制器为核心搭建硬件平台，包括基于PCI9054的PCI接口电路，EEPROM电路，FPGA控制电路，485通信接口电路，基于SJA1000的CAN总线接口电路和基于DM9000A的以太网接口电路。选取合适的传感器设计检测电路测量船舶动力装置设备的温度、压力、转速等重要热力参数，并设计合适的信号采集电路采集这些数据，以实现对船舶动力装置设备运行状态的实时监测。 FPGA控制器上开发基于Nios II软核处理器的SOPC系统，用来控制整个下位机硬件平台的运行。在Quartus II开发环境下编辑FPGA子程序，采用VerilogHDL语言开发自定义IP模块实现与各外设模块之间的实时通信。采用Windows环境下的WDM模型驱动设计了PCI9054驱动程序，实现设备的即插即用，并在VS2008开发环境开发系统的监测与故障诊断应用软件。最后，本文提出了船舶动力装置设备的神经网络故障诊断专家系统设计思路。
[Abstract]:With the rapid development of shipping industry, people pay more and more attention to the safety of ships. Providing sufficient energy for the normal navigation and other work of the ship, which is the most important part of the ship. About 60% to 80% of all kinds of ship faults are caused by power plant equipment, The traditional fault diagnosis method is backward, low efficiency, high labor intensity, high maintenance cost, Therefore, it is necessary to carry out the research on condition monitoring and fault diagnosis of marine power plant equipment, and apply modern computer technology and embedded technology to ship monitoring and fault diagnosis technology. This paper presents a design scheme of marine power plant monitoring and fault diagnosis system based on computer PCI interface. This paper mainly describes the platform design method and process of the system, including the following contents:. This paper introduces the relevant knowledge of ship power plant and fault diagnosis technology, and analyzes the functional requirements of the platform of ship power plant monitoring and fault diagnosis system, combined with the current research situation in this field at home and abroad. The overall scheme of the whole system is designed, and the design scheme of each unit module is demonstrated. The hardware platform of the system is based on the industrial control computer and cyclone III series FPGA controller, including the PCI interface circuit based on PCI9054 and the EEPROM control circuit and the FPGA485 communication interface circuit. The CAN bus interface circuit based on SJA1000 and the Ethernet interface circuit based on DM9000A are selected. The suitable sensor design and detection circuit is selected to measure the important thermodynamic parameters such as temperature, pressure, rotational speed and so on. A suitable signal acquisition circuit is designed to collect these data in order to realize the real-time monitoring of the running state of marine power equipment. The SOPC system based on Nios II soft core processor is developed on FPGA controller, which is used to control the running of the whole hardware platform of the lower computer. In the Quartus II development environment, the FPGA subprogram is edited. The self-defined IP module is developed with VerilogHDL language to realize real-time communication with each peripheral module. The PCI9054 driver is designed by using the WDM model driver under the Windows environment, which realizes the plug and play of the device, and develops the monitoring and fault diagnosis application software of the system in the VS2008 environment. Finally, This paper presents the design idea of neural network fault diagnosis expert system for marine power plant.
【学位授予单位】：武汉理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U664.1

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