Oven with machine learning based algorithm selection strategy
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Solution Overview
Problem
Conventional microwave ovens are limited in their ability to control energy application, leading to inefficient cooking due to indiscriminate energy distribution and poor penetration of radiation, which can result in suboptimal cooking results, especially when trying to brown food.
Innovation Solution
An oven using solid-state components to generate electromagnetic energy, with control electronics that employ adaptive algorithms and machine learning to dynamically adjust energy application based on real-time feedback, allowing for customized and optimized heating of food products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional microwave cooking is used to speed up the cooking process, then cooking time is reduced, but the ability to brown food and control energy application is lost
Solution Approach 1:
The patent implements dynamic control of microwave energy application through multiple algorithms (e.g., Algorithm 1 for initial heating, Algorithm 2 for browning) that can be switched based on cooking progress and detected trigger events. This allows the system to adapt energy application in real-time, achieving both rapid cooking and controlled browning that static conventional microwaves cannot provide.
Solution Approach 2:
The system incorporates feedback mechanisms where the control electronics monitor cooking progress and detect trigger events (such as temperature thresholds or time milestones) to determine when to switch between different energy application algorithms. This feedback loop enables automatic adjustment of energy distribution to achieve desired cooking outcomes including browning, while maintaining operational simplicity for the user.
2Productivity
If microwave energy is applied indiscriminately to cook food faster, then cooking time is reduced, but penetration of radiation into the food product is insufficient
Solution Approach 1:
The patent applies different energy application algorithms to different stages and regions of the cooking process. For example, initial algorithms may apply higher power for rapid heating of accessible surfaces, while subsequent algorithms adjust energy distribution to improve penetration into deeper regions. This localized quality approach ensures both speed and adequate radiation penetration throughout the food product.
Solution Approach 2:
The system employs periodic switching between different energy application algorithms based on detected trigger events during the cooking process. This periodic action allows the microwave energy application to be modulated in cycles, enabling deeper penetration over time while maintaining overall cooking speed through alternating high-power and penetration-optimized phases.
3Adaptability or versatility
If combination of microwave and hot airflow is used for browning, then browning capability is achieved, but the limitations of microwave penetration remain unresolved
Solution Approach 1:
The patent merges microwave energy application with convection heating in a coordinated manner. The control electronics manage both heating modes, using microwave energy for rapid internal heating and convection for surface browning. This combination resolves the penetration limitation by ensuring that while convection handles surface browning, microwave energy simultaneously penetrates deeper regions, achieving both goals synergistically rather than sequentially.
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
This approach enables precise control over electromagnetic energy application, improving cooking performance by ensuring uniform heating and achieving desired cooking outcomes, such as browning, in a shorter time, enhancing the overall cooking experience.
Implementation Method 1
an EM heating system configured to provide EM energy into the cooking chamber using solid state electronic components
Implementation Method 2
The control electronics may be configured to select a first algorithm to direct application of the EM energy to the food product
Data Source
AI summary
An oven may include a cooking chamber configured to receive a food product, an EM heating system configured to provide EM energy into the cooking chamber using solid state electronic components, and control electronics configured to control the EM heating system. The control electronics are configured to enable user selection of a cooking program associated with cooking the food product. The control electronics select a first algorithm to direct application of the EM energy to the food product. The control electronics perform a learning process to receive feedback on execution of the cooking program during execution of the cooking program according to the first algorithm. Responsive to detecting a trigger event during the learning process, the control electronics are configured to select a second algorithm that is different from the first algorithm to direct application of the EM energy to the food product during execution of the cooking program.