[HTML][HTML] Feature extraction of impulse faults for vibration signals based on sparse non-negative tensor factorization

L Liang, H Wen, F Liu, G Li, M Li - Applied Sciences, 2019 - mdpi.com
Featured Application The proposed feature extraction method can be typically applied in the
fault diagnosis of rolling bearings and other rotating machinery. Abstract The incipient …

[PDF][PDF] Feature Extraction of Impulse Faults for Vibration Signals Based on Sparse Non-Negative Tensor Factorization

L Liang, H Wen, F Liu, G Li, M Li - scholar.archive.org
The incipient damages of mechanical equipment excite weak impulse vibration, which is
hidden, almost unobservable, in the collected signal, making fault detection and failure …

[PDF][PDF] Feature Extraction of Impulse Faults for Vibration Signals Based on Sparse Non-Negative Tensor Factorization

L Liang, H Wen, F Liu, G Li, M Li - pdfs.semanticscholar.org
The incipient damages of mechanical equipment excite weak impulse vibration, which is
hidden, almost unobservable, in the collected signal, making fault detection and failure …

Feature Extraction of Impulse Faults for Vibration Signals Based on Sparse Non-Negative Tensor Factorization.

L Liang, H Wen, F Liu, G Li, M Li - Applied Sciences (2076 …, 2019 - search.ebscohost.com
Abstract Featured Application: The proposed feature extraction method can be typically
applied in the fault diagnosis of rolling bearings and other rotating machinery. The incipient …

Feature Extraction of Impulse Faults for Vibration Signals Based on Sparse Non-Negative Tensor Factorization

L Lin, H Wen, F Liu, G Li, M Li - Applied Sciences, 2019 - search.proquest.com
The incipient damages of mechanical equipment excite weak impulse vibration, which is
hidden, almost unobservable, in the collected signal, making fault detection and failure …