A statistically based fault detection and diagnosis approach for non-residential building water distribution systems
Author:
Funder
Science Foundation Ireland
Publisher
Elsevier BV
Subject
Artificial Intelligence,Information Systems
Reference110 articles.
1. Principal component analysis;Abdi;Wiley Interdiscip. Rev. Comput. Stat.,2010
2. Abdulshaheed, A., Mustapha, F., & Ghavamian, A. (2017). A pressure-based method for monitoring leaks in a pipe distribution system: A Review. Renewable and Sustainable Energy Reviews, 69(May 2015), 902–911. https://doi.org/10.1016/j.rser.2016.08.024.
3. Ahmed, M., Baqqar, M., Gu, F., & Ball, A. D. (2012). Fault detection and diagnosis using Principal Component Analysis of vibration data from a reciprocating compressor. Proceedings of the 2012 UKACC International Conference on Control, CONTROL 2012, (September 2012), 461–466. https://doi.org/10.1109/CONTROL.2012.6334674.
4. On the application of interval PCA to process monitoring: a robust strategy for sensor FDI with new efficient control statistics;Ait-Izem;J. Process Control,2018
5. Statistical indicator for the detection of anomalies in gas, electricity and water consumption: Application of smart monitoring for educational buildings;Akil;Energy Build.,2019
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