Machinery fault diagnosis using independent component analysis (ICA) and Instantaneous Frequency (IF)

  title={Machinery fault diagnosis using independent component analysis (ICA) and Instantaneous Frequency (IF)},
  author={Bagus Tris Atmaja and Dhany Arifianto},
  journal={International Conference on Instrumentation, Communication, Information Technology, and Biomedical Engineering 2009},
Machine condition monitoring plays an important role in industry to ensure the continuity of the process. This work presents a simple and yet, fast approach to detect simultaneous machinery faults using sound mixture emitted by machines. We developed a microphone array as the sensor. By exploiting the independency of each individual signal, we estimated the mixture of the signals and compared time-domain independent component analysis (TDICA), frequency-domain independent component analysis… CONTINUE READING


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