塔式起重机机群故障检测与诊断系统的设计与研究

发布时间：2018-08-12 20:26

【摘要】：随着经济的迅速发展和城市建设规模的扩大化、快速化,塔式起重机的重要作用日益突出,且机群协同作业的情况越来越普遍。与此同时,塔机事故随着机群规模的扩大而频繁发生,严重者甚至造成人员的伤亡。因此,为使整个机群有效运行、协调工作、减少因事故造成的经济损失和人员伤亡,及时、准确的检测诊断出塔机的故障将具有重大的经济效益和学术研究价值。首先,塔式起重机机群拥有巨大的工作数据,如何利用这些数据来反映塔机的工作状态并使相关人员及时掌握情况是故障检测与诊断的关键。本文通过研究塔式起重机组成机构的工作及检测原理,总结出塔式起重机机群故障特点,为机群故障检测与诊断方法的研究和系统设计奠定了基础。其次,研究了基于神经网络专家系统的塔式起重机故障检测与诊断方法。该方法融合了神经网络的学习能力、自适应能力、并行推理能力及联想记忆能力和专家系统知识经验的丰富性和权威性优势,确保了故障检测诊断的准确、快速性。文中以机群中最重要的四种工况为实例对神经网络专家系统在故障检测与诊断中的应用进行了验证。最后,设计了基于塔机监控仪和监控中心计算机通过GPRS网络构成的塔机机群故障检测与诊断系统。论文介绍了塔机监控仪的硬件部分和软件部分的设计原理,监控仪以单片机为核心,通过GPRS方式实现远程数据通信。硬件采用了模块化结构设计,包括输入模块、输出模块、报警模块、液晶显示模块和数据存储模块。在监控中心软件部分,采用MATLAB编制了故障检测与诊断程序,采用Visual Basic设计了数据库处理和人机界面,编制MATLAB与VB的接口、VB与SQL的接口程序,实现了机群故障检测与诊断。论文的创新之处在于,将神经网络专家系统应用于塔机机群故障检测与诊断中;塔机监控仪采用三个单片机协同工作的设计方案,增强了系统的实时性和可靠性。
[Abstract]:With the rapid development of economy and the expansion of urban construction scale, the important role of tower crane is becoming more and more prominent, and the cooperative operation of cluster is becoming more and more common. At the same time, tower crane accidents occur frequently with the expansion of fleet size, and even cause casualties. Therefore, in order to make the whole cluster run effectively, coordinate the work, reduce the economic losses and casualties caused by the accident, timely and accurately detect and diagnose the tower crane fault will have great economic benefits and academic research value. First of all, the tower cranes have huge working data. How to use these data to reflect the working status of tower cranes and make relevant personnel know the situation in time is the key to fault detection and diagnosis. In this paper, the fault characteristics of tower crane cluster are summarized by studying the work and detection principle of the tower crane, which lays a foundation for the research of the fault detection and diagnosis method of tower crane and the design of the system. Secondly, the fault detection and diagnosis method of tower crane based on neural network expert system is studied. This method combines the learning ability, adaptive ability, parallel reasoning ability, associative memory ability and expert system knowledge and authoritative advantages of neural network, and ensures the accuracy and rapidity of fault detection and diagnosis. In this paper, the application of neural network expert system in fault detection and diagnosis is verified by taking the four most important working conditions in the cluster as examples. Finally, the fault detection and diagnosis system of tower crane group is designed based on tower crane monitor and monitor center computer through GPRS network. This paper introduces the design principle of the hardware and software parts of the tower crane monitoring instrument. The monitoring instrument takes the single chip computer as the core and realizes the remote data communication through GPRS mode. The hardware adopts modular structure design, including input module, output module, alarm module, LCD module and data storage module. In the software part of the monitoring center, the program of fault detection and diagnosis is programmed by MATLAB, the database processing and man-machine interface are designed by Visual Basic, and the interface program between VB and MATLAB and SQL is compiled, which realizes the fault detection and diagnosis of cluster. The innovation of this paper is that the neural network expert system is applied to the fault detection and diagnosis of tower crane cluster, and the tower crane monitor adopts the design scheme of three single chip computers to work together, which enhances the real-time and reliability of the system.
【学位授予单位】：沈阳理工大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：TH213.3;TP277

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