Tea Garden Trap Board Replacement via Machine Vision
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing manual trap board replacement methods in tea gardens are labor-intensive, time-consuming, and often result in inefficient insect control due to lack of real-time monitoring, leading to potential waste and environmental pollution.
Innovation Solution
An intelligent replacement device utilizing image channel computation and machine vision to automatically detect trap board failure, replacing it with a new one and removing used stickers, reducing labor costs and improving insect trapping efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual operation is used to replace trap boards, then the replacement can be performed, but it is time-consuming and labor-consuming, increasing labor cost
Solution Approach 1:
The system enables self-service automation where the replacement device autonomously performs trap board replacement operations without human intervention. The machine vision system automatically detects trap board status, identifies replacement needs, and triggers the replacement mechanism, transforming manual labor into an autonomous self-service system that eliminates time consumption and labor costs
Solution Approach 2:
The patent replaces manual mechanical operations with an automated mechanical system. The replacement device uses a mechanical arm or transfer mechanism driven by motors to handle trap board removal and installation, substituting human physical labor with automated mechanical systems that operate faster and more efficiently
2Productivity
If timer-based periodic replacement is used, then labor cost is reduced, but insects cannot be monitored in real time and trap boards may be replaced prematurely or wasted
Solution Approach 1:
The system implements feedback control by using machine vision to continuously monitor trap board status and insect accumulation in real time. The vision system provides feedback information about actual trap board conditions, which is then used to dynamically adjust replacement timing, ensuring boards are replaced only when actually needed rather than following fixed schedules, thus eliminating premature replacement and resource waste
Solution Approach 2:
The machine vision system performs preliminary detection and assessment of trap board status before replacement is actually needed. By continuously monitoring and identifying deteriorating conditions in advance, the system can plan and execute replacements at optimal moments, preventing both premature replacement and failure to replace in time
3Measurement precision
If machine vision is used to determine trap board failure in real-time, then replacement accuracy is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex manual inspection processes with machine vision systems that use optical sensors and image processing algorithms to automatically detect trap board failure conditions. This substitution of mechanical/human inspection with optical detection systems achieves high measurement precision while the added complexity is offset by the elimination of manual labor and improved overall system 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 device automates trap board replacement, reducing labor costs, preventing waste, and enhancing insect trapping efficiency while minimizing chemical usage and environmental pollution, leading to improved tea quality and economic benefits.
Implementation Method 1
intelligent replacement device and method for trap board in tea garden based on image channel computation
Data Source
AI summary
The present disclosure provides an intelligent replacement device and method for a trap board in a tea garden based on image channel computation. The device includes a trap board supply module, a trap board sticker removal module and a machine vision control module fixed on a machine frame, where the machine vision control module is configured to acquire an image of a present trap board in the trap board supply module, determine whether the present trap board fails according to the image, control, in response to failure of the present trap board, the trap board supply module to replace the trap board, and control the trap board sticker removal module to remove a film of a replaced trap board. The present disclosure can replace the trap board in the tea garden automatically, timely and accurately instead of the manual operation.