Intelligent Squid Cutting System Using Laser Point Cloud Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The aquatic processing industry faces challenges in achieving automatic and intelligent processing of aquatic products, particularly in cutting squid white slices, due to the reliance on manual labor, resulting in low production efficiency and high defective product rates.
Innovation Solution
A method and system for intelligent cutting of squid white slices using laser point cloud data processing, which involves optimizing the data, determining cutting points and angles, and adjusting parameters to ensure quality requirements are met, implemented through a system comprising a point cloud data reading module, data optimizing module, area extraction module, zero point determination module, area determination module, and cutting adjustment module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual labor is used for cutting squid white slices, then flexibility and adaptability are maintained, but production efficiency is low and defective product rates are high
Solution Approach 1:
The patent replaces manual mechanical cutting operations with an automated intelligent cutting system that uses laser point cloud scanning to capture the 3D topography of squid white slices, processes the data to determine optimal cutting parameters, and executes automated cutting operations. This substitution of manual mechanical systems with automated optical-mechanical systems directly resolves the contradiction by achieving both high productivity through automation and high quality through precise digital measurement and control.
Solution Approach 2:
The patent transforms the cutting process from manual parameter estimation to automated parameter optimization by using laser point cloud data to precisely measure the 3D geometry of each squid white slice, then calculating optimal cutting positions and angles based on the actual measured parameters. This parameter transformation from approximate manual values to precise measured and calculated values enables both high automation and high product quality.
2Productivity
If automated cutting is implemented, then production efficiency improves, but manufacturing precision may deteriorate without proper optimization
Solution Approach 1:
The patent performs preliminary actions by scanning the 3D topography of squid white slices with laser point cloud technology before cutting, capturing the actual geometry and dimensions. This preliminary measurement and data processing enable the system to pre-calculate optimal cutting parameters based on the specific characteristics of each slice, ensuring that when automated cutting occurs, both high productivity and high precision are achieved because the cutting parameters are optimized in advance for each individual piece.
Solution Approach 2:
The patent implements a feedback mechanism where laser point cloud scanning continuously measures the actual 3D geometry of squid white slices, and this measured data feeds back to the control system which adjusts cutting parameters accordingly. This closed-loop feedback ensures that automated cutting maintains high precision by constantly comparing actual dimensions with target specifications and making real-time adjustments, while simultaneously maintaining high productivity through automated operation.
3Productivity
If intelligent manufacturing devices are used, then labor costs are reduced and productivity improves, but device complexity increases
Solution Approach 1:
The patent employs a multi-functional intelligent cutting device that integrates laser point cloud scanning, 3D topography measurement, data processing, parameter calculation, and automated cutting execution into a single unified system. This universal device performs multiple functions (measurement, analysis, control, and execution) that would otherwise require separate systems, thereby reducing overall system complexity while maintaining high productivity and enabling automated operation to reduce labor costs.
4Manufacturing precision
If manual cutting is used, then device complexity remains low, but product quality and consistency deteriorate
Solution Approach 1:
The patent replaces simple manual cutting tools with an intelligent automated cutting system that uses laser point cloud scanning and digital processing. This substitution introduces optical sensing and computational elements that enable precise measurement and control of cutting parameters, dramatically improving product quality and consistency. The increased device complexity is justified by the substantial improvement in manufacturing precision and the elimination of manual operation variability.
Solution Approach 2:
The patent performs preliminary 3D scanning and data processing to determine optimal cutting parameters before the actual cutting operation. This preliminary action enables the system to account for the specific geometry and characteristics of each squid white slice, ensuring high cutting precision and consistent product quality. The additional complexity of preliminary measurement and calculation is offset by the significant improvement in cutting accuracy and the ability to handle variability in raw material dimensions.
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 significantly reduces labor costs, improves production efficiency, and enhances product quality by ensuring precise cutting based on optimized cutting point positions and angles, suitable for large-scale continuous production.
Implementation Method 1
reading a laser point cloud data of a three-dimensional (3D) topography of the squid white slices
Data Source
AI summary
The present disclosure involves a calculation method and device for intelligent cutting squid white slices, the calculation method being implemented on the device for intelligent cutting squid white slices. The calculation method may be implemented on a calculation device, the calculation device may have at least one processor and at least one storage medium including an instruction set used for intelligent cutting the squid white slices, the calculation method including: reading a laser point cloud data of a three-dimensional (3D) topography of the squid white slices; optimizing the laser point cloud data; extracting an effective area of the squid white slices; determining a cutting zero point; determining a cutting process area; and determining optimization of a cutting point position and a cutting angle. The one or more embodiments provided by the present disclosure may satisfy the needs of large-scale continuous production in factories, reduce labor costs, and improve production efficiency.