Tool Wear State Recognition Based on One-Dimensional Convolutional Channel Attention.

Tool wear state recognition is an important part of tool condition monitoring (TCM). Online tool wear monitoring can avoid wasteful early tool changes and degraded workpiece quality due to later tool changes. This study incorporated an attention mechanism implemented by one-dimensional convolution in a convolutional neural network for improving the performance of the tool wear recognition model (1DCCA-CNN). The raw multichannel cutting signals were first preprocessed and three time-domain features were extracted to form a new time-domain sequence. CNN was used for deep feature extraction of temporal sequences. A novel 1DCNN-based channel attention mechanism was proposed to weigh the channel dimensions of deep features to enhance important feature channels and capture key features. Compared with the traditional squeeze excitation attention mechanism, 1DCNN can enhance the information interaction between channels. The performance of the model was validated on the PHM2010 public cutting dataset. The excellent performance of the proposed 1DCCA-CNN was verified by the improvement of 4% and 5% compared to the highest level of existing research results on T1 and T3 datasets, respectively.

Oxidative stress responses in the respiratory tree and the body wall of sea cucumber Apostichopus japonicus (Selenka) to high temperature.

Sea cucumber Apostichopus japonicas (Selenka) is one of the important aquaculture species distributed in northern China. In recent years, global warming caused frequent high temperature weather in summer in northern China, resulting in dramatic losses of the sea cucumber aquaculture industry. In the present study, we focused on the effect of oxidative stress in Apostichopus japonicus (Selenka) subjected to high temperature stress. Sea cumbers were exposed to the control (16 °C), and high temperature treatments (20 °C, 24 °C, and 28 °C) for 7 days. Then, reactive oxygen species (ROS) level, superoxide dismutase (SOD) activity, catalase (CAT) activity, peroxidase (POD) activity, reduced glutathione (GSH) content, malondialdehyde (MDA) content and 8-hydroxy-2'-deoxyguanosine (8-OHdG) level in the respiratory tree and body wall were detected, respectively. Results showed that 24 °C and 28 °C acute exposure induced the elevation of ROS level, SOD, CAT, POD activities, GSH content, MDA content and 8-OHdG level in the respiratory tree of sea cucumber. In contrast, no significant changes were observed for ROS and 8-OHdG levels in the body wall of sea cucumber, while the antioxidants including SOD, CAT, POD, and GSH decreased to some extent. Moreover, MDA content exhibited a noticeable increase in the body wall, similarly to that in the respiratory tree, indicating that high temperature could induce severe lipid peroxidation in two tissues. Considering the differences in various biomarkers measured in two tissues, respiratory tree might be more susceptible to the high temperature changes compared to the body wall. Our findings may help understand the oxidative stress response to high temperature in the respiratory tree and the body wall in A. japonicus.