研究论文
Enhancing the accuracy of machinery fault diagnosis through fault source isolation of complex mixture of industrial sound signals
Ayantha Senanayaka, Philku Lee, Nayeon Lee, Charles Dickerson, Anton D. Netchaev, Sungkwang Mun
Mississippi State University Korea Automotive Technology Institute United States Army U.S. Army Engineer Research and Development Center
来源The International Journal of Advanced Manufacturing Technology
年份2024
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工程Machine Fault Diagnosis Techniques
Vehicle Noise and Vibration Control · Speech and Audio Processing
参考文献 56
Single-channel speech separation using sparse non-negative matrix factorization
被引 379Mikkel Nørgaard Schmidt, Rasmus Kongsgaard Olsson · 2006
Deep neural network based instrument extraction from music
被引 112Stefan Uhlich, Franck Giron, Yuki Mitsufuji · 2015
Multi-view Face Detection Using Deep Convolutional Neural Networks
被引 600Sachin Farfade, Mohammad Javad Saberian, Li-Jia Li · 2015
此处列出前 3 条
引用本文 13
Phoneme-inspired acoustic frame embedded lightweight transformer for rolling bearing fault diagnosis
被引 28Linhao Peng, Fang Liu, Zhongliang Lv · Mechanical Systems and Signal Processing · 2026
A unified Cross-Modal adaptive contrastive learning framework for acoustic fault diagnosis of rolling bearing under limited & imbalanced data
被引 23Linhao Peng, Fang Liu, Ang Lu · Mechanical Systems and Signal Processing · 2025
A novel framework for multi-sensor data fusion in bearing fault diagnosis using continuous wavelet transform and transfer learning
被引 18Iman Makrouf, Mourad Zegrari, Khalid Dahi · e-Prime - Advances in Electrical Engineering Electronics and Energy · 2025
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