Hyperspectral Imaging for Oil Detection in Agricultural Streams
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Solution Overview
Problem
Existing optical scanning and sorting systems fail to detect and reject products contaminated with oils, greases, lubricants, or other non-tobacco-related materials (NTRM) during the manufacturing process, necessitating time-consuming searches to identify and remove these contaminants.
Innovation Solution
An on-line system using hyperspectral imaging and analysis is employed to scan agricultural product streams, generate spectral fingerprints, and compare them to a database to detect foreign matter, with the system removing contaminated portions via gravity or fluid jets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optical scanning and sorting systems are used, then the system structure is simple and easy to operate, but the system cannot detect and reject products contaminated with oils, greases, lubricants, or other non-tobacco-related materials
Solution Approach 1:
The patent changes the detection parameter from conventional optical properties (color, shape) to spectral properties across multiple wavelengths. By using hyperspectral imaging that captures reflectance spectra at numerous wavelength bands, the system can identify foreign matter based on its unique spectral signature, thereby improving detection accuracy while managing the increased complexity through systematic spectral analysis
Solution Approach 2:
The patent transitions from two-dimensional spatial imaging to three-dimensional spectral-spatial imaging by adding the wavelength dimension. This hyperspectral approach creates a spectral cube for each pixel, enabling detection of foreign matter through its spectral characteristics across multiple wavelengths, thus resolving the limitation of conventional systems
2Reliability
If hyperspectral imaging system is implemented, then detection accuracy of foreign matter is improved, but the device complexity and cost increase
Solution Approach 1:
The patent implements preliminary action by collecting and storing spectral reference data for various foreign materials (oils, greases, lubricants, NTRM) before actual detection. This reference library is built in advance through systematic measurement and characterization, enabling rapid and reliable identification during production without requiring complex real-time analysis of every possible contaminant
Solution Approach 2:
The system employs feedback mechanisms where detected spectral signatures are compared against the reference library, and the results feed into automated sorting decisions. This closed-loop approach improves reliability by continuously validating detections against known reference patterns while maintaining systematic control over the increased system complexity
3Productivity
If manual search and removal of lubricants is conducted, then the equipment complexity is low, but the time consumption and productivity are reduced
Solution Approach 1:
The patent replaces manual mechanical search and removal processes with an automated optical-detection-and-sorting system. Hyperspectral imaging automatically identifies foreign matter in real-time, and automated sorting mechanisms immediately remove contaminated products, eliminating the time-consuming manual search process and significantly improving processing speed and productivity
4Measurement precision
If conventional inspection methods are used, then the system is simple to operate, but foreign matter contamination goes undetected
Solution Approach 1:
The patent implements a universal detection system that can identify multiple types of foreign matter (oils, greases, lubricants, NTRM, plant material) using a single hyperspectral imaging platform. This multi-functional approach improves detection capability across diverse contaminants while centralizing control through automated spectral analysis, making the system easier to operate than multiple specialized inspection devices
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 real-time detection and removal of oils, greases, and lubricants from agricultural products like tobacco, ensuring high accuracy and efficiency in the manufacturing process.
Implementation Method 1
one or more objects in a scene or sample are affected in a way, such as excitation by incident electromagnetic radiation supplied by an external source of electromagnetic radiation upon the objects
Implementation Method 2
determining a spectral fingerprint for the agricultural product stream from the hyperspectral images; comparing the spectral fingerprint so obtained to a spectral fingerprint database
Implementation Method 3
removing a portion of the conveyed product stream in response to the signal
Data Source
AI summary
A method for removing foreign matter from an agricultural product stream of a manufacturing process. The method includes conveying a product stream past an inspection station; scanning a region of the agricultural product stream as it passes the inspection station using at least one light source of a single or different wavelengths; generating hyperspectral images from the scanned region; determining a spectral fingerprint for the agricultural product stream from the hyperspectral images; comparing the spectral fingerprint obtained in step (c) to a spectral fingerprint database containing a plurality of fingerprints using a computer processor to determine whether foreign matter is present and, if present, generating a signal in response thereto; and removing a portion of the conveyed product stream in response to the signal. A system for detecting foreign matter within an agricultural product stream is also provided.