基于超声导波的道岔钢轨轨头损伤实时监测系统设计

发布时间：2018-05-26 00:25

本文选题：超声导波 + 道岔钢轨　；参考：《西安理工大学》2017年硕士论文

【摘要】：铁路作为目前主要的交通运输方式之一,使人们的出行和货运更加快捷便利。然而,长期以来钢轨损伤一直是影响铁路运输安全的关键因素,其严重威胁列车的行车安全,是导致重大安全事故的重要因素之一。道岔是铁路轨道设备中最重要的组成部分,道岔钢轨的结构复杂性使其成为铁路轨道系统中最难维护、最薄弱的部分,且极易产生损伤。因此,对道岔钢轨损伤进行实时监测具有重要的意义。本文基于超声导波检测方法,对道岔钢轨轨头损伤实时监测系统进行研究。首先对系统方案和检测算法进行了设计。为了不影响列车正常运行以及便于探头的安装固定,本文选用了 PZT压电陶瓷的超声波探头并安装于钢轨轨头侧面。同时,为了减小检测盲区,采用发送与接收探头分开的布置方式,并通过实验方式确定超声波发射探头的激励频率为180kHz。系统损伤检测方法采用超声导波回波互相关算法,通过MATLAB仿真验证了算法的可行性。在此基础上,本文完成了系统的软硬件设计,系统以ARM数据处理模块为核心,其主要包括超声导波发射电路、超声导波接收电路、FPGA数据采集电路、LCD显示电路等模块。系统通过发射电路中的信号隔离、驱动以及升压电路激励超声导波探头;通过接收电路中的限幅保护、有源带通滤波电路实现对超声导波信号的调理,从而保证FPGA数据采集电路对信号的正常采集。此外,由ARM控制LCD实现波形的显示、系统参数设置以及系统调试。最后,论文完成了系统的软硬件联调,验证了系统硬件与软件功能的正确性。实验结果表明系统能够正常工作且ARM平台与MATLAB平台下的互相关算法对数据处理的相对误差低于0.4%,符合系统设计要求。同时,通过人为引入轨头损伤的模拟实验,验证了监测系统对钢轨轨头损伤识别的可行性。
[Abstract]:As one of the main modes of transportation, railway makes people's travel and freight more convenient. However, rail damage has long been a key factor affecting the safety of railway transportation, which seriously threatens the safety of trains and is one of the important factors leading to major safety accidents. Turnout is the most important part of railway track equipment. The structural complexity of switch rail makes it the most difficult to maintain the weakest part of the railway track system and easily cause damage. Therefore, it is of great significance to monitor the rail damage in real time. Based on ultrasonic guided wave detection method, the real-time damage monitoring system of turnout rail head is studied in this paper. First, the system scheme and detection algorithm are designed. In order not to affect the normal operation of the train and to facilitate the installation and fixation of the probe, the PZT piezoelectric ceramic ultrasonic probe is selected and installed on the side of the rail head. At the same time, in order to reduce the blind area of detection, a separate arrangement of transmitting and receiving probes is adopted, and the excitation frequency of ultrasonic transmitting probe is determined to be 180 kHz by experiment. The system damage detection method adopts ultrasonic guided echo cross-correlation algorithm, and the feasibility of the algorithm is verified by MATLAB simulation. On this basis, the software and hardware design of the system is completed. The system takes the ARM data processing module as the core, which mainly includes the ultrasonic guided wave transmitting circuit, the ultrasonic guided wave receiving circuit and the ARM data acquisition circuit and the LCD display circuit and so on. The system excites the ultrasonic guided wave probe through the signal isolation, drive and boost circuit in the transmitting circuit, and realizes the modulation of the ultrasonic guided wave signal through the limiting protection in the receiving circuit, and the active bandpass filter circuit. In order to ensure the normal acquisition of FPGA data acquisition circuit. In addition, ARM controls LCD to realize waveform display, system parameter setting and system debugging. Finally, the hardware and software alignment of the system is completed, which verifies the correctness of the system hardware and software functions. The experimental results show that the system can work normally and the relative error of the cross-correlation algorithm based on ARM platform and MATLAB platform is less than 0.4, which conforms to the design requirements of the system. At the same time, the feasibility of the monitoring system for rail head damage identification is verified by the simulation experiment of artificially introducing rail head damage.
【学位授予单位】：西安理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U216.3;TP274

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