Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory

In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and cu...

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Detalles Bibliográficos
Autores principales: Si, Lei, Wang, Zhongbin, Liu, Xinhua, Tan, Chao, Xu, Jing, Zheng, Kehong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4701307/
https://www.ncbi.nlm.nih.gov/pubmed/26580620
http://dx.doi.org/10.3390/s151128772

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4701307/
https://www.ncbi.nlm.nih.gov/pubmed/26580620
http://dx.doi.org/10.3390/s151128772

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