A hybrid clustering multi-source fault diagnosis method for chiller temperature sensors-Reference-Cited by-同舟云学术

A hybrid clustering multi-source fault diagnosis method for chiller temperature sensors

Published:2022-09-26 Issue:2 Volume:16 Page:198-210
ISSN:1940-1493
Container-title:Journal of Building Performance Simulation
language:en
Short-container-title:Journal of Building Performance Simulation

Author:

Yan Xiuying¹,Liu Guangyu¹,Zhang Boyan²,Fan Kaixing³,Li Jun⁴,Du Yifan²

Affiliation:

1. School of Building Services Science and Engineering, Xi’an University of Architecture, and Technology, Xi’an, Shaanxi 710055, People’s Republic of China

2. College of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an, Shaanxi 710055, People’s Republic of China

3. School of Architecture, Xi’an University of Architecture and Technology, Xi’an, Shaanxi 710055, People’s Republic of China

4. LiTian Energy conservation and environmental protection company, Shenzhen, Guangdong 518102, People’s Republic of China

Funder

Shaanxi Provincial Natural Science Basic Research Foundation

Key Research and Development Plan Project of Shaanxi Province

Science and Technology Development Plan Project of Shaanxi Provincial Jian She Department

Publisher

Informa UK Limited

Subject

Computer Science Applications,Modeling and Simulation,Building and Construction,Architecture

Link

https://www.tandfonline.com/doi/pdf/10.1080/19401493.2022.2126011

Reference31 articles.

1. Fault Detection for Systems With Multiple Unknown Modes and Similar Units and Its Application to HVAC

2. Noise filtering using Empirical Mode Decomposition

3. Integrated Unfold-PCA Monitoring Application for Smart Buildings: An AHU Application Example

4. Fault detection and diagnosis for Air Handling Unit based on multiscale convolutional neural networks

5. Smart building creation in large scale HVAC environments through automated fault detection and diagnosis

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