Temperature characteristic evaluation method
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Solution Overview
Problem
Existing methods for evaluating temperature characteristics within climate chambers are costly and lack reliability, particularly in maintaining temperature uniformity across the internal space while considering external air influences, as they require multiple sensors and frequent measurements.
Innovation Solution
A method involving a computer-connected climate chamber that uses regression analysis to derive a temperature function from ambient and internal temperature data, allowing for the evaluation of temperature characteristics with reduced sensor usage and cost by calculating differences and approximating functions to assess temperature uniformity and margin levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple temperature sensors are used to monitor temperature at all positions inside the test chamber, then measurement precision and reliability improve, but device complexity and cost increase
Solution Approach 1:
The test chamber is divided into multiple temperature zones, with monitoring sensors strategically placed at representative positions for each zone. This segmentation approach allows comprehensive temperature monitoring across the entire chamber while using a limited number of sensors, as each sensor represents the temperature characteristics of its corresponding zone.
Solution Approach 2:
The patent introduces a temperature distribution simulation model as an intermediary between the physical temperature field and the monitoring system. This model uses data from a limited number of sensors to simulate and predict temperature distribution at all positions within the chamber, thereby achieving comprehensive monitoring without requiring sensors at every location.
2Reliability
If temperature uniformity is measured every fixed period, then reliability of temperature maintenance guarantee improves, but loss of time increases
Solution Approach 1:
The patent performs temperature distribution simulation and establishes temperature characteristic data before the actual preservation period begins. This preliminary action creates a baseline model that can be used to evaluate temperature uniformity without requiring frequent physical measurements during the preservation period, thus reducing time loss while maintaining reliability through the pre-established model.
Solution Approach 2:
The system uses temperature monitoring data and simulation results to provide feedback on temperature uniformity. By comparing actual measurements with simulated temperature distributions, the system can evaluate whether temperature uniformity requirements are met without requiring continuous or frequent measurements, thereby reducing time loss while maintaining evaluation reliability.
Data Source
AI summary
A temperature characteristic evaluation method includes the steps of acquiring temperature data, ambient temperature data, and internal temperature data are acquired. By changing at least one of the set temperature and the ambient temperature, a plurality of combinations of the set temperature data, the ambient temperature data, and the internal temperature data is obtained as a plurality of temperature data groups. A difference between the ambient temperature data and the set temperature data in each of the plurality of temperature data groups is calculated as the first difference. A difference between the internal temperature data and the set temperature data is calculated as the second difference. The combinations of the first and second differences are obtained as difference groups. The plurality of difference groups for the plurality of temperature data groups is approximated in a linear function, and the linear function is obtained as a temperature function.