Food waste accounts for 30% - 50% of domestic waste, and its centralized treatment is difficult. For commercial places with large production of food waste, it is a better way to use grinding mill to crush food waste and then discharge it into sewer. The mechanical properties of grinding plate are the decisive factors affecting the performance of grinding mill. In this paper, the static analysis and modal analysis of the grinding plate of commercial grinding mill are carried out. The results show that: under the rated load, the maximum equivalent stress of grinding hammer is 83.4mpa, the maximum equivalent stress of cutter head is 77.6mpa, which meets the design requirements, but the stress is relatively concentrated. The lowest modal vibration frequency of the lapping plate is 456.2hz, and the lapping plate will not have resonance damage under normal conditions.
A fingerprint is an impression left by the friction ridges of a human finger. A fingerprint classification system groups fingerprint according to their characteristics and therefore helps to match a fingerprint against an extensive database of fingerprints. The Henry classification system is widely used among fingerprint classification systems. Some researchers have used traditional machine learning or deep learning for fingerprint classification. Nevertheless, traditional algorithms cannot extract the depth features of the fingerprint, and most deep learning algorithms lack fingerprint image enhancement. So, this paper combined the Gabor Filter and Convolutional Neural Network to extract fingerprint features. The model has two channels, one is a Deep Convolutional Neural Network (DCNN), and the other is a Shallow Convolutional Neural Network (SCNN). The DCNN consists of a neural network with eight layers, which can extract deep features of the fingerprint. The SCNN consists of Gabor Filter and a neural network with two layers that can extract features from clear fingerprint images. This paper uses NIST Special Database 4 for experiments. Experimental results show that the model proposed in this paper has achieved 91.4% accuracy. Compared with other algorithms, this model has higher accuracy than others. It shows that combined with the Gabor Filter and Convolutional Neural Network can better extract the ridge features of fingerprint images.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.