With the increasingly common use of industrial automation for mass production, there are\nmany computer numerical control (CNC) machine tools that require the collection of data from\nintelligent sensors in order to analyze their processing quality. In general, for high speed rotating\nmachines, an accelerometer can be attached on the spindle to collect the data from the detected\nvibration of the CNC. However, due to their cost, accelerometers have not been widely adopted\nfor use with typical CNC machine tools. This study sought to develop an embedded miniature\nMEMS microphone array system (Radius 5.25 cm, 8 channels) to discover the vibration source of\nthe CNC from spatial phase array processing. The proposed method utilizes voice activity detection\n(VAD) to distinguish between the presence and absence of abnormal noise in the pre-stage, and\nutilizes the traditional direction of arrival method (DOA) via multiple signal classification (MUSIC)\nto isolate the spatial orientation of the noise source in post-processing. In the numerical simulation,\nthe non-interfering noise source location is calibrated in the anechoic chamber, and is tested with\nreal milling processing in the milling machine. As this results in a high background noise level,\nthe vibration sound source is more accurate in the presented energy gradation graphs as compared to\nthe traditional MUSIC method.
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