Weak fault feature extraction method based on selective integration and improved local feature decomposition
The invention discloses a weak fault feature extraction method based on selective integration and improved local feature decomposition. The method specifically comprises the steps that collecting vibration signals and carrying out normalization processing; adopting a boundary continuation method bas...
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| creator | PAN JIANHAN TANG XIAN REN SHIJIN WEI MINGSHENG |
| description | The invention discloses a weak fault feature extraction method based on selective integration and improved local feature decomposition. The method specifically comprises the steps that collecting vibration signals and carrying out normalization processing; adopting a boundary continuation method based on mirror image continuation symmetric points to carry out continuation on two ends of the normalized signal; decomposing the extended signal into a plurality of ISC components by adopting an SEILCD method; estimating the energy of each ISC component at the confidence of 95% and 99%; judging whether each ISC component belongs to noise or not, if yes, denoising the ISC by adopting a minmax threshold denoising method, and otherwise, denoising the ISC by adopting an AWOGS method; and normalizingand orthogonalizing the denoised ISC and carrying out time-frequency analysis. According to the method, the LCD interpolation mean value curve and the adaptive signal denoising can be adaptively selected, the complex vibrati |
| format | Patent |
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The method specifically comprises the steps that collecting vibration signals and carrying out normalization processing; adopting a boundary continuation method based on mirror image continuation symmetric points to carry out continuation on two ends of the normalized signal; decomposing the extended signal into a plurality of ISC components by adopting an SEILCD method; estimating the energy of each ISC component at the confidence of 95% and 99%; judging whether each ISC component belongs to noise or not, if yes, denoising the ISC by adopting a minmax threshold denoising method, and otherwise, denoising the ISC by adopting an AWOGS method; and normalizingand orthogonalizing the denoised ISC and carrying out time-frequency analysis. 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The method specifically comprises the steps that collecting vibration signals and carrying out normalization processing; adopting a boundary continuation method based on mirror image continuation symmetric points to carry out continuation on two ends of the normalized signal; decomposing the extended signal into a plurality of ISC components by adopting an SEILCD method; estimating the energy of each ISC component at the confidence of 95% and 99%; judging whether each ISC component belongs to noise or not, if yes, denoising the ISC by adopting a minmax threshold denoising method, and otherwise, denoising the ISC by adopting an AWOGS method; and normalizingand orthogonalizing the denoised ISC and carrying out time-frequency analysis. 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The method specifically comprises the steps that collecting vibration signals and carrying out normalization processing; adopting a boundary continuation method based on mirror image continuation symmetric points to carry out continuation on two ends of the normalized signal; decomposing the extended signal into a plurality of ISC components by adopting an SEILCD method; estimating the energy of each ISC component at the confidence of 95% and 99%; judging whether each ISC component belongs to noise or not, if yes, denoising the ISC by adopting a minmax threshold denoising method, and otherwise, denoising the ISC by adopting an AWOGS method; and normalizingand orthogonalizing the denoised ISC and carrying out time-frequency analysis. According to the method, the LCD interpolation mean value curve and the adaptive signal denoising can be adaptively selected, the complex vibrati</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING HANDLING RECORD CARRIERS MEASURING PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS TESTING TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR |
| title | Weak fault feature extraction method based on selective integration and improved local feature decomposition |
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