Fault detection and diagnosis of the air handling unit via combining the feature sparse representation based dynamic SFA and the LSTM network
Energy and Buildings（2022）
Abstract
•By infusing sparse restriction, STBDSFA is proposed to improve monitoring effect.•A new dynamic SFA is developed to handle the autocorrelations and dynamics.•To identify the fault, the LSTM is improved to classify sparse slow features.•Detailed experiments are performed to verify the effect of proposed FDD scheme.
MoreTranslated text
Key words
fault detection and diagnosis,air handling unit,feature sparse representation,slow feature analysis,long short-term memory (LSTM) network
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined