A Fuzzy Neural Network-Based Time Series Analysis Model for Condition Monitoring of Work Equipment
This paper aims to overcome the shortcomings of existing technologies and provide a fuzzy neural network-based time series analysis model for tool status monitoring, which has good thermal insulation effect, long service life of sound insulation materials, and good sound insulation effect. Its basic principle is as follows. Fuzzy neural network (FNN) is a comprehensive combination of fuzzy logic (FL) and neural network (NN), which is based on the principle that fuzzy inference systems can be represented by multi-level feedforward neural networks. Compared with end-to-end neural network deep learning algorithms, it has faster processing speed, lower hardware cost requirements, and more accurate data detection accuracy.
Authors
- Shizhe Chen (ORCID: https://orcid.org/0000-0001-5802-3297)
- Lei Fang (ORCID: https://orcid.org/0000-0003-0826-9154)
- Wei Dong (ORCID: https://orcid.org/0000-0002-8033-7943)
- Weiye Qian (ORCID: https://orcid.org/0009-0005-3274-3575)
Institutions
- Hangzhou Special Equipment Inspection and Research Institute (CN)
Publication Details
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1109/eiecs63941.2024.10800393
- Primary Topic
- Industrial Technology and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00