微弱信号的混沌同步检测机理及地铁车辆轮对故障的早期诊断

Due to the metro vehicle complex work conditions and a large amount of noise, traditional signal detection methods are difficult to achieve early fault diagnosis of metro wheels. This is a security risk to the metro operation. To this end, the project studied a new method of weak signal detection based on chaotic synchronization theory. The method, which has important scientific significance and application value, was used to early fault diagnosis of metro wheels. It was different from the conventional detection principle. The project analyzed characteristics of weak fault signals when the metro vehicle was running, constructed a weak signal chaotic synchronization detection system to detect wheels’ faults. Then, put the parameter identification method and adaptive algorithm, analyzed synchronization detection characteristics of vehicle wheels’ early weak fault signals, tested detection capability and feasibility of the new method to common faults of traction gears and axle box bearings in vehicle wheels. The project has the following innovations: first, the new method has high detection speed and avoid solve complex phase space trajectories, which is needed in the existing chaotic detection methods. Second, has strong anti-interference ability, even in strong noise environment it can be completed accurately detect weak signals. Third, the detection device is easy to implement, which can be build by the existing basic chaotic systems. The project will further promote the study of the mechanism of weak signal detection based on chaotic synchronization. And provide a new theory and a new method for early diagnosis of metro vehicle wheels failure.

地铁车辆运行时工况复杂且噪声干扰严重，传统的信号检测方法难以实现车辆轮对故障的早期诊断，给运营带来安全隐患。为此，本项目基于混沌同步理论，研究微弱信号检测的新方法，应用于轮对故障的早期诊断，具有重要的科学意义和应用价值。与常规检测原理不同，本项目分析地铁车辆运行时轮对故障微弱信号的特征，构建轮对故障微弱信号混沌同步检测系统，提出相应的参数辨识方法和自适应算法，并进行车辆轮对故障早期高精度混沌同步检测特性分析,验证其对车辆轮对中牵引齿轮和轴箱轴承常见故障的检测能力和可行性。项目有如下几个创新之处：一是检测方法实时性强，避免了现有混沌检测方法对相空间轨迹的复杂求解；二是抗干扰能力强，即使在强噪声环境下也能完成准确检测；三是检测装置易于实现，利用现有基本混沌系统即可搭建。本项目研究成果将推动混沌同步检测微弱信号的机理研究，为地铁车辆轮对故障的早期诊断提供一种新理论和新方法。