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首页> 外文期刊>Research journal of applied science, engineering and technology >The Effect of Number of Microphones to Amplitude Changes for Detect Crack on Rotating Shaft with Blind Source Separation-Independent Component Analysis Method
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The Effect of Number of Microphones to Amplitude Changes for Detect Crack on Rotating Shaft with Blind Source Separation-Independent Component Analysis Method

机译:盲源分离独立分量分析方法对传声器数量的变化对裂纹检测振幅的影响对旋转轴的影响

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This study aims to determine the amplitude change due to the addition of the number of microphones to detect the cracking of the rotating shaft. This study presents the measurement of sound data from the cracked shaft which is one component of a simple transmission system. The sound signal emitted by the cracked shaft is very complex, low frequency and comes from various sources. Statistically, the sound signal is independent and based on this nature; the mixed signal can separate. The method to separate mixed signals is blind source separation without knowing the origin and process of a signal combined with Independent Component Analysis (ICA). One of the conditions that must satisfy in the BSS method is to know the number of source signals, but in practice, what happens is not specific and complicated. This study use variable is the number of microphones and the shaft speed. The results obtained are the use of microphone array of two, three and four can increase the magnitude amplitude of the estimation signal, while the increased of the shaft speed, the magnitude amplitude of the estimation signal also increased. Use of four microphones has of higher amplitude values than a single, two and three microphones. Moreover, the lowest mean square error value increases the microphone sensitivity. Implications of using microphones array to detect a crack that cannot measure by an accelerometer and avoid distortion on the rotating shaft.
机译:这项研究的目的是确定由于增加了用于检测旋转轴破裂的传声器数量而引起的振幅变化。这项研究提出了来自裂纹轴的声音数据的测量,裂纹轴是简单传输系统的一个组成部分。裂纹轴发出的声音信号非常复杂,低频并且来自各种来源。从统计上讲,声音信号是独立的,并基于此性质;混合信号可以分开。分离混合信号的方法是盲源分离,无需结合独立分量分析(ICA)即可知道信号的来源和过程。 BSS方法必须满足的条件之一是知道源信号的数量,但是实际上,发生的事情并不具体且复杂。这项研究使用的变量是麦克风的数量和轴速度。获得的结果是使用两个,三个和四个麦克风阵列可以增加估计信号的幅度,而增加轴速度时,估计信号的幅度也增加。四个麦克风的使用具有比单个,两个和三个麦克风更高的幅度值。此外,最低的均方误差值会提高麦克风灵敏度。使用麦克风阵列检测无法用加速度计测量的裂纹并避免旋转轴变形的含义。

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