Cloud-Dust Based Intelligent Maintenance and Check System for Maximum Performance of Power Generation with Solar Energy

• Main Authors: Yang, Sheng-Feng, 楊勝峰
• Other Authors: Huang, Chung-Chi
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/04163939426963537190

碩士 === 遠東科技大學 === 機械工程研究所 === 103 === This thesis proposes the system of cloud-dust based intelligent maintenance and check for maximum performance of power generation with solar. It can effectively reduce maintenance costs and human resources of a solar generating system and reach best-stated energy conversion to elaborate the large-scale capacity through the advantages like on-demand intelligence, expand ease of use, flexibility… etc. The cloud-dust system contains the cloud database, the cloud operation and the intelligent inference engine. We develop a cloud-computing based intelligence inference engine by using artificial neural network method, fuzzy logic, particle swarm optimization, generation on variable solar energy power generation system to build-out system maintenance and check of the relational model. Through the dust system and embedded system and wireless sensors network, the sensing data captured from the dust system is sent to the intelligent inference engine of the cloud system, and the results from the intelligent inference engine present the states of maintenance and check in the solar generating system. Finally, a solar generating equipment located in the building rooftop is considered to be experimented for the purpose of diagnosis, prescription, schedule, and check. Experimental results show the feasibility of the architecture of the cloud-dust based intelligent maintenance and check system. The checking system can process fool proofing for abnormal data and try to repair, even provide a solution to abnormalities to maintain defect-free rate. Hence, this thesis, cloud-dust based intelligent maintenance and check system, can analyze status efficiently with suggestion to provide more useful reference for solar generating system.