Data Center Cooling Region Mapping via Automated Sensor Analysis
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Solution Overview
Problem
The commissioning process for determining the regions of influence of cooling resources in data centers is time-consuming and laborious, requiring manual manipulation of cooling devices and lengthy measurements.
Innovation Solution
A method and analyzer that use cluster analysis on physical and correlation metrics-based relationships between fluid moving devices and sensors to automatically determine regions of influence, reducing the time required and minimizing disruption to infrastructure operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the commissioning process is used to determine regions of influence by manually varying cooling resources and measuring temperature changes, then accurate region determination is achieved, but the process becomes time-consuming and laborious
Solution Approach 1:
The patent replaces the manual mechanical commissioning process with an automated system that uses temperature sensors, processors, and algorithms to determine regions of influence. The system automatically collects temperature data from multiple sensors, processes the data to identify which cooling resources affect which locations, and generates region mappings without human intervention, thereby eliminating the time-consuming manual manipulation while maintaining measurement accuracy.
Solution Approach 2:
The system performs self-commissioning by automatically determining its own regions of influence through embedded processors that analyze temperature sensor data. The cooling infrastructure essentially commissions itself by having the system autonomously identify relationships between cooling resources and temperature changes at various locations, eliminating the need for external manual commissioning processes.
2Measurement precision
If manual commissioning is performed to identify regions of influence, then accurate cooling resource mapping is achieved, but infrastructure operations are disrupted
Solution Approach 1:
The patent replaces manual commissioning operations with an automated data collection and processing system that continuously monitors temperature without requiring human operators to physically manipulate cooling resources. This substitution allows the system to maintain accurate cooling resource mapping while infrastructure operations continue uninterrupted, as the automated system works alongside normal operations rather than requiring shutdowns or manual interventions.
Solution Approach 2:
The system enables continuous temperature monitoring and region determination without interrupting the normal operation of the cooling infrastructure. Temperature sensors continuously collect data, and the processor continuously analyzes this data to maintain accurate region mappings, ensuring that both the commissioning process and infrastructure operations proceed continuously without disruption.
3Measurement precision
If traditional commissioning methods are used to determine regions of influence, then sensitivity metrics are accurately computed, but the process is laborious and requires manual intervention
Solution Approach 1:
The patent replaces manual sensitivity metric computation with an automated processing system that uses processors and algorithms to calculate sensitivity metrics from temperature sensor data. The system automatically determines how temperature changes at various locations respond to cooling resource actuation by analyzing collected data through computational algorithms, achieving accurate sensitivity metric computation without manual intervention.
Solution Approach 2:
The system autonomously computes sensitivity metrics by having the processor automatically analyze temperature data and calculate the relationship between cooling resource actuation levels and temperature changes at different locations. This self-service computation eliminates the need for manual sensitivity analysis while maintaining computational accuracy through systematic data processing.
Data Source
AI summary
A method for determining regions of influence of a plurality of fluid moving devices in an infrastructure is provided. In the method, a plurality of clusters are generated, with each of the plurality of clusters containing a representation of fluid supply data pertaining to a fluid moving device and one or more of the plurality of sensors based upon collected sensor and fluid supply data. In addition, regions of influence of each of the plurality of fluid moving devices are identified from an analysis of the generated clusters.