【作者】 高璎园；

【导师】 张兴周；

【作者基本信息】 哈尔滨工程大学 ， 通信与信息系统， 2010， 硕士

【摘要】 本课题来源于黑龙江省科技计划项目“平轮检测平台研究与开发”,作为项目的重要组成部分,论文对基于DSP的平轮检测系统的总体方案进行了论证,并研究开发了相应的基于DSP的平轮检测算法。车轮扁疤是列车重大行车事故的隐患之一,对它的准确、快速检测在保障列车行车安全方面起着至关重大的作用,因此研制一种在线实时平轮检测系统具有重大的现实意义。论文首先通过分析比较目前国内外采用的各种动态检测方法,选择振动加速度检测法对平轮信号进行检测。然后根据振动加速度检测法的原理和系统设计指标的要求,对设计的基于DSP的平轮检测系统的具体方案作了详细论证。根据DSP平轮检测系统的工作流程,论文提出了基于DSP的平轮检测算法并进行了详细的阐述。在算法开发部分,首先依据由振动加速度传感器采集到的平轮信号具有持续时间短、突变快等非平稳特征,对现有的适用于平轮信号检测的非平稳时频分析方法进行了分析,通过分析对比首次提出采用S变换的时频分析方法对平轮信号进行检测和定位,并通过仿真验证了S变换的方法相对于现有方法的优越性；然后系统地阐述了平轮检测的整体算法,包括信号的预处理、信号特征提取、位置判别三部分算法,其中信号特征提取部分主要采用多种阈值判别方法和S变换检测定位方法,并提出采用短时能量判决的方法对信号进行阈值判别,仿真证明该方法能够较好地排除漏检、误检现象的发生；最后给出了检测算法在DSP上实现的具体方法,其中主要分析了AD采集算法和DSP与ARM通信算法的实现。论文最后完成了基于CCS硬仿真的DSP单板调试和整个检测平台的联调,调试结果表明系统各方面性能指标均达到系统设计指标,同时通过长期大量数据实验验证了平轮检测算法的正确性和系统设计的可靠性与稳定性。更多还原

【Abstract】 As the important part of the project "The Research and Development of Wheel-flat Detection Platform" which comes from Heilongjiang Province Science and Technology Department, this dissertation demonstrated the overall scheme of wheel-flat detection system based on DSP and developed the corresponding algorithm of wheel-flat detection based on DSP.The wheel-flat is one of the hidden dangers of major train operation accidents, it has a great significance to detect the wheel-flat accurately and rapidly for guaranteeing the train’s traffic safety. Thus there is a great practical significance to develop an on-line and real time wheel-flat detection system.Firstly the thesis choosed the vibrational acceleration detection method to detect wheel-flat through analyzing and comparing various existing dynamic detection methods at home and abroad. According to the principle of vibrational acceleration detection method and the requirements of the system design specifications, the thesis demonstrated the scheme of wheel-flat detection system based on DSP in detail. In accordance with the working flow of wheel-flat detection system based on DSP, the algorithm of wheel-flat detection based on DSP was given and expounded detailedly. In the part of algorithm development, the thesis firstly analysed the existing nonstationary time-frequency analysis methods which were applicable to wheel-flat detection, based on the nonstationary characteristics of short lasting time and fast mutation for wheel-flat signal collected by vibration accelerometer. Through analysis and comparation time-frequency analysis method based on S-transform was proposed for the first time to detect and locate vibration signal with wheel-flat, and the superiority of S-transform compared with the presented methods was verified by simulation. Afterward, the thesis systematically expounded the whole algorithm of wheel-flat detection including signal pretreatment, characteristics extraction and location detection. In the part of characteristics extraction algorithm, the thesis mainly used threshold judgement methods and S-transform detection algorithm, and the method of short-time energy estimation was proposed in the threshold judgement. Simulation results showed that by short-time energy estimation the algorithm could prevent undetection and misjudgment efficiently. Finally, the detection algorithm’s realizations on DSP were also provided, mainly including algorithm for AD acquisition and communication between DSP and ARM. In the end, the thesis accomplished the debugging on the board of DSP in the CCS emulator environment and the whole detection platform’s united debugging. The debugging results have manifested that the performance indexes in every respect of the system are all achieved the system design specifications, and the validity of the algorithm and the reliability and stability of the system are all verified through a great deal data experiments for a long time.更多还原