A Comparison of Artificial Neural Networks and Other Statistical Methods for Rotating Machine Condition Classification
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چکیده
Statistical estimates of vibration signals such as the mean and variance can provide indication of faults in rotating machinery. Using these estimates jointly can give a more robust classiication than using each individually. Artiicial neural network architectures and some statistical algorithms are compared with emphasis on training requirements and real-time implementation as well as overall performance.
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تاریخ انتشار 2007