【摘要】 传统的采样策略会产生大量的数据,为了减少齿轮振动监测中的数据量,在压缩感知的基础上,建立了齿轮振动信号采集和重构模型。首先通过高斯随机矩阵对振动信号进行压缩测量、传输和存储压缩后的信号可以节省成本。信号重构归结为一个最优化问题,应用正交匹配追踪求解信号重构问题。进而得到重构信号的Hilbert解调谱,从Hilbert解调谱中提取特征频率,以特征频率能否识别来评价信号重构的效果。仿真实验和齿轮实验证明了模型的有效性。更多还原

【Abstract】 A lot of data is generated with the traditional sampling strategy. To reduce the data amount in vibration monitor for gear,the model of acquisition and reconstruction of mechanical vibration signal is established based on the principle of compressed sensing. The compressed signal that is transmitted and stored is measured with Gaussian random matrix. Therefore the cost is decreased. The signal reconstruction comes down to optimization question that is solved by Orthogonal Matching Pursuit. And then,the feature frequency is extracted from Hilbert demodulation spectrum of reconstruction signal and is employed to judge the success of signal reconstruction. The effectiveness of the model is verified through simulation signal and gear vibration signal.更多还原