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A research approach of crack detection of rotating shafts based on acoustic emission (AE) signals and machine learning is proposed in this paper. The relationship between crack intensity and domain features are investigated, and the features which could well indicate the crack condition are selected for modelling and crack prediction. Multiple Linear Regression (MLR), Artificial Neural Networks (ANN)...
In metal cutting processes, tool condition monitoring (TCM) plays an important role in maintaining the quality of surface finishing. Monitoring of tool wear in order to prevent surface damage is one of the difficult tasks in the context of TCM. Through early detection, high quality surface finishing and near-zero loss for potential failures can be ensured. Real-time/online tool degradation detection...
A novel methodology for generating fuzzy reinforcement learning systems without a prior knowledge and expert effect named as dynamic self-generated fuzzy Q-learning (DSGFQL) has been proposed in this paper. Compared with authors' previous work on dynamic fuzzy Q-learning (DFQL), DSGFQL offers an automatical generation method for fuzzy reinforcement learning with capabilities of creating as well as...
Deployment of large population of sensors for sophisticated sensing and control in the industrial and commercial infrastructures is a challenging research area. The use of wireless sensor network (WSN) for industrial applications has attracted a great deal of interests today. Unlike the office networks, the industrial environment for wireless sensor networks are harsher due to the unpredictable variations...
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