Adaptive Aeration Control for Agricultural Storage Bins
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Solution Overview
Problem
Existing agricultural product storage systems with aeration fans lack adaptive control strategies that account for changing storage conditions and product states, leading to inefficient operation and potential over-drying or spoilage.
Innovation Solution
An agricultural product storage system with a controller that selects among multiple control functions based on sensed conditions and storage states, using a condition sensor and conditioning device to adjust fan operation dynamically, including parameters like moisture content, temperature, and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a simple control algorithm is used to operate the aeration fan, then the system is easy to operate and energy consumption is reduced, but the product moisture content cannot be precisely controlled leading to over-drying or spoilage
Solution Approach 1:
The control system dynamically transitions between different control modes (first control mode and second control mode) based on real-time product state conditions. The controller automatically adjusts which algorithm governs fan operation, enabling the system to adapt its complexity and control strategy according to the current storage conditions, thus achieving both ease of operation and precise moisture control.
Solution Approach 2:
The system changes control parameters by switching between different control modes defined by distinct algorithms. Each control mode has specific parameter settings for fan operation that are selected based on product state conditions such as temperature and moisture content thresholds, allowing precise adjustment of aeration intensity to maintain optimal moisture levels.
2Manufacturing precision
If a complex control algorithm is used to precisely control aeration, then product quality is improved, but the device complexity and operational difficulty increase
Solution Approach 1:
The complex control problem is segmented into multiple distinct control modes, each governed by a specific algorithm suited for particular product states. Rather than implementing one monolithic complex algorithm, the system divides control into manageable segments (first control mode for certain conditions, second control mode for other conditions), reducing overall system complexity while maintaining precision.
Solution Approach 2:
The controller automatically determines which control mode to apply based on sensed product conditions, eliminating the need for manual intervention or complex user configuration. The system self-adjusts its control strategy by evaluating current state parameters and selecting the appropriate algorithm, thereby reducing operational difficulty despite the sophistication of the underlying control logic.
3Device complexity
If manual adjustment of fan operation settings is required, then the control system is simple, but the storage efficiency is reduced due to delayed response to changing conditions
Solution Approach 1:
The control system continuously monitors product state parameters (temperature, moisture content) and uses this feedback to automatically adjust fan operation. The controller receives real-time data from sensors and dynamically selects control modes based on current conditions, enabling rapid response to changing storage conditions without manual intervention, thus maintaining storage efficiency while keeping the interface simple.
Solution Approach 2:
The system performs self-adjustment by automatically selecting appropriate control modes based on sensed conditions, eliminating the need for manual settings changes. The controller autonomously responds to product state changes by switching between control algorithms, thereby maintaining optimal aeration without user involvement and maximizing storage efficiency.
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
The system ensures optimal storage conditions by adapting fan control strategies in real-time, maintaining product quality and market value by adjusting operations according to changing storage conditions and product states.
Implementation Method 1
a condition sensor associated with the storage bin so as to be arranged to sense a condition of the agricultural product in the storage bin
Implementation Method 2
a conditioning device operatively associated with the storage bin for conditioning the agricultural product in the storage bin when activated
Data Source
AI summary
In an agricultural product storage system, product is stored in a bin having a condition sensor associated therewith and a conditioning device for conditioning the stored product when activated, for example an aeration fan. A controller in communication with the sensor and the conditioning device, operates the condition device in response to the sensed condition of the product according a selected one of a plurality of different control functions defining different control parameters of the conditioning device. The controller selects among the different control functions based upon the changing state of the of the storage bin.