Gross Error Detection and Data Correction in IIoT-Based Data Center Cooling System
Abstract
A data center always require a proper cooling system. This research study a data center with water based cooling system that consists of two chillers and two in-rack coolers. To control the system, an Industrial Internet of Things (IIoT) infrastructures has been deployed. It able to monitors real-time data from various sensors such as temperature (T), pressure (P), water flow (Q). The data were supposed to be used for optimization. However, early assessment showed that there were discrepancies between the sensors. Therefore, data reconciliation method is essential to get the valid data from the sensors. This paper discusses the implementation of gross error detection and correction by using least square method and bias compensation.
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