摘要
Conclusion is that the soft threshold de-noising effect is better than hard threshold de-noising though the signal to noise ratio and Root Mean Square error. After analyzing, de-noising and reconstructing signal through wavelet packet from Matlab software, the average value of peak extracted from signal reconstruction is gotten to provide data for dynamic balance. Making use of the influence coefficient method to adjust drum of CTP dynamic balance, the program of Matlab is used to find phase position and weight of the mass block quickly, which can provide evidence for software for dynamic balance developed.
Conclusion is that the soft threshold de-noising effect is better than hard threshold de-noising though the signal to noise ratio and Root Mean Square error. After analyzing, de-noising and reconstructing signal through wavelet packet from Matlab software, the average value of peak extracted from signal reconstruction is gotten to provide data for dynamic balance. Making use of the influence coefficient method to adjust drum of CTP dynamic balance, the program of Matlab is used to find phase position and weight of the mass block quickly, which can provide evidence for software for dynamic balance developed.
