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首页> 外文期刊>Mechanical systems and signal processing >Extraction of angle deterministic signals in the presence of stationary speed fluctuations with cyclostationary blind source separation
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Extraction of angle deterministic signals in the presence of stationary speed fluctuations with cyclostationary blind source separation

机译:存在平稳速度波动且具有循环平稳盲源分离的角度确定性信号的提取

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摘要

This paper addresses the use of a cyclostationary blind source separation algorithm (namely RRCR) to extract angle deterministic signals from mechanical rotating machines in presence of stationary speed fluctuations. This means that only phase fluctuations while machine is running in steady-state conditions are considered while run-up or run-down speed variations are not taken into account. The machine is also supposed to run in idle conditions so non-stationary phenomena due to the load are not considered. It is theoretically assessed that in such operating conditions the determi nistic (periodic) signal in the angle domain becomes cyclostationary at first and second orders in the time domain. This fact justifies the use of the RRCR algorithm, which is able to directly extract the angle deterministic signal from the time domain without performing any kind of interpolation. This is particularly valuable when angular resampling fails because of uncontrolled speed fluctuations. The capability of the proposed approach is verified by means of simulated and actual vibration signals captured on a pneumatic screwdriver handle. In this particular case not only the extraction of the angle deterministic part can be performed but also the separation of the main sources of excitation (i.e. motor shaft imbalance, epyciloidal gear meshing and air pressure forces) affecting the user hand during operations.
机译:本文讨论了使用循环平稳盲源分离算法(即RRCR)从存在固定速度波动的机械旋转机器中提取角度确定性信号的方法。这意味着仅考虑机器在稳态条件下运行时的相位波动,而不考虑加速或减速速度的变化。机器也应该在空转条件下运行,因此不考虑由于负载引起的非平稳现象。从理论上评估,在这种工作条件下,角度域中的确定性(周期性)信号在时域中以一阶和二阶变为循环平稳。这个事实证明了使用RRCR算法是正确的,该算法能够从时域直接提取角度确定性信号,而无需执行任何类型的内插。当由于速度波动不受控制而导致角度重采样失败时,这特别有价值。通过在气动螺丝刀手柄上捕获的模拟和实际振动信号验证了所提出方法的功能。在这种特殊情况下,不仅可以进行角度确定部分的提取,而且可以分离影响操作过程中用户手的主要激励源(即,电动机轴不平衡,十字齿轮啮合和空气压力)。

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