Cooking device and control method thereof, and computer-readable storage medium
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Solution Overview
Problem
Existing cooking devices cannot accurately monitor the internal temperature of food without damaging its surface and lack intelligent control to adapt to smart home appliance design concepts.
Innovation Solution
A control method for a cooking device that involves monitoring surface temperature, weight, and chamber temperature, using a preset regression model to predict internal food temperature, and adjusting the cooking device's operating status accordingly to optimize cooking results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a probe is inserted into the food to detect internal temperature, then the user can know whether the food is cooked through, but the integrity of the surface of the food is destroyed and the appearance of the final product is affected
Solution Approach 1:
The patent replaces the mechanical probe insertion method with a non-contact thermal imaging system. The thermal imaging device captures thermal radiation from the food surface, and a regression model predicts the internal temperature based on surface temperature distribution patterns, eliminating the need for physical contact with the food
Solution Approach 2:
The patent introduces a regression model as an intermediary that translates surface temperature measurements (obtained via thermal imaging) into internal temperature predictions. This intermediary enables indirect measurement of internal temperature without direct contact, resolving the contradiction between accurate measurement and food integrity
2Ease of operation
If the cooking device mechanically heats food according to preset time and temperature, then the cooking process is simple to operate, but the device is not intelligent enough to adapt to current smart home appliance design concepts
Solution Approach 1:
The patent implements a closed-loop feedback system where the thermal imaging device continuously monitors the food's surface temperature distribution during cooking, the regression model predicts internal temperature in real-time, and the control system automatically adjusts heating parameters based on the predicted internal temperature to achieve the target cooking state
Solution Approach 2:
The cooking device performs self-diagnosis and self-adjustment by using its own thermal imaging and regression model capabilities to monitor its own cooking process, eliminating the need for external probes or manual temperature checking by the user
3Device complexity
If the cooking device monitors only chamber temperature and surface temperature of food, then the monitoring system is simple, but the user cannot intuitively know the actual internal temperature of the food
Solution Approach 1:
The patent transitions from direct measurement (inserting a probe into the food) to indirect measurement by observing the thermal radiation dimension emitted from the food surface. The thermal imaging device captures two-dimensional thermal distribution patterns that contain information about internal temperature states
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables non-invasive, accurate monitoring of internal food temperature, ensuring better cooking results both inside and on the surface of the food, while maintaining the food's appearance intact and implementing intelligent control for optimized cooking.
Implementation Method 1
a thermal imaging device, configured to acquire the monitoring data
Implementation Method 2
a preset regression model is used for representing a correlation between an internal temperature of the cooked object and the monitoring data
Data Source
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AI summary
A cooking device and a control method thereof, and a computer-readable storage medium are provided. The control method includes: performing monitoring during operation of a cooking device, to obtain monitoring data, where a dimension of the monitoring data includes at least one of a surface temperature of a cooked object, a weight of the cooked object, or a chamber temperature of the cooking device; inputting the monitoring data to a preset regression model, to obtain a predicted internal temperature of the cooked object, where the preset regression model is used for representing a correlation between an internal temperature of the cooked object and the monitoring data; and adjusting an operating status of the cooking device according to at least the predicted internal temperature of the cooked object. According to the solution of the present invention, intelligent control of a cooking device can be implemented, and an internal temperature of food is obtained by using a non-invasive method, to accurately measure an actual cooking state of the food, so that an operating status of the cooking device is automatically adjusted during cooking, to optimize a cooking result.