WO2024121320A1 - Detection of variation in a noodle package - Google Patents

Detection of variation in a noodle package Download PDF

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Publication number
WO2024121320A1
WO2024121320A1 PCT/EP2023/084734 EP2023084734W WO2024121320A1 WO 2024121320 A1 WO2024121320 A1 WO 2024121320A1 EP 2023084734 W EP2023084734 W EP 2023084734W WO 2024121320 A1 WO2024121320 A1 WO 2024121320A1
Authority
WO
WIPO (PCT)
Prior art keywords
package
articles
noodle
article
sachet
Prior art date
Application number
PCT/EP2023/084734
Other languages
French (fr)
Inventor
Ayan Chattopadhyay
Nayandeep BANERJEE
Original Assignee
Société des Produits Nestlé S.A.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Société des Produits Nestlé S.A. filed Critical Société des Produits Nestlé S.A.
Publication of WO2024121320A1 publication Critical patent/WO2024121320A1/en

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/90—Investigating the presence of flaws or contamination in a container or its contents
    • G01N21/9018—Dirt detection in containers
    • G01N21/9027—Dirt detection in containers in containers after filling
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
    • B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
    • B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
    • B07C5/34—Sorting according to other particular properties
    • B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/1702—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
    • G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/90—Investigating the presence of flaws or contamination in a container or its contents
    • G01N21/909—Investigating the presence of flaws or contamination in a container or its contents in opaque containers or opaque container parts, e.g. cans, tins, caps, labels
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/22—Details, e.g. general constructional or apparatus details
    • G01N29/24—Probes
    • G01N29/2418—Probes using optoacoustic interaction with the material, e.g. laser radiation, photoacoustics
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/4409—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison
    • G01N29/4427—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison with stored values, e.g. threshold values
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/1702—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids
    • G01N2021/1706—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids in solids
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00—Indexing codes associated with group G01N29/00
    • G01N2291/26—Scanned objects
    • G01N2291/269—Various geometry objects
    • G01N2291/2698—Other discrete objects, e.g. bricks

Definitions

  • the present invention generally relates to packaging of articles .
  • the present invention relates to automated mechanism for detection of variation in articles of a noodle package .
  • assembly and packaging lines are automated, such as noodle packages are automatically filled with predefined articles such as a taste maker sachet , a liquid sachet or a combination thereof and after filling of the predef ined articles the noodle packages are sealed .
  • predefined articles such as a taste maker sachet , a liquid sachet or a combination thereof
  • the noodle packages are sealed .
  • a package type and quantity of the articles are signi ficant and are predefined in automated packaging lines .
  • an automated system for detecting variation of articles in a noodle package includes one light source to illuminate light on a noodle package and one photoelectric sensor configured to capture signals based on the light absorbed and reflected by one of : the one or more articles in the noodle package and inner walls of the noodle package .
  • the automated system also includes an article detection engine to correlate the captured signals with pre-stored data to detect a variation in at least one of : type of article and number of articles in the noodle package .
  • the variation is from a predefined type and number of the article intended to be in the noodle package .
  • the article detection engine is also configured to facilitate rej ection of the noodle package upon finding a variation in the at least one of : type of the article and number of the article in the noodle package .
  • the noodle package is a sealed noodle package covering the articles .
  • the light source radiate light in range of near infrared wavelength .
  • the pre-stored data provides a correlation between intensity and strength of signals and at least one of : type of articles and number of articles in the noodle package .
  • 3D Photo acoustic imaging is employed for the correlation of the captured signals .
  • the photoelectric sensor is a 3D Photo acoustic sensor .
  • the article detection engine facilitates approval of the noodle package upon a match between the pre-stored data and the captured signals .
  • the articles comprise a taste maker sachet , a liquid sachet or a combination thereof , preferably a taste maker sachet and a liquid sachet .
  • the liquid sachet is a lipid sachet , preferably an oil sachet .
  • An embodiment of the present invention discloses an automatic method for detecting variation of articles in a noodle package .
  • the automatic method includes illuminating light on a noodle package , capturing signals based on the light absorbed and reflected by one of : one or more articles in the noodle package and inner walls of the noodle package and correlating the captured signals with pre-stored data to detect a variation in at least one of : type of article and number of articles in the noodle package .
  • the variation is from a predefined type and number of the article intended to be in the noodle package . Further, facilitating rej ection of the noodle package upon finding a variation in the at least one of : type of the article and number of the article in the noodle package .
  • the noodle package is a sealed noodle package covering the articles .
  • the illuminated light is in range of near infrared wavelength .
  • the pre-stored data provides a correlation between : intensity and strength of signals and at least one of : type of articles and number of articles in the noodle package .
  • 3D Photo acoustic imaging is employed for the correlation of the captured audio-visual signals .
  • the automatic method also includes facilitating approval of the noodle package upon a match between the pre-stored data and the captured signals .
  • Figures 1 ( a ) and 1 (b ) illustrate schematic drawings of an automated system for detecting variation of articles in a noodle package in accordance with an embodiment of the present invention
  • Figure 2 illustrates an exemplary embodiment of operation of the present invention with respect to a noodle package ;
  • Figure 3 illustrates a flowchart of an automatic method for detecting variation of articles in a noodle package in accordance with an embodiment of the present invention .
  • the present invention relates to detection of variation of articles in a noodle package .
  • the variation may be with respect to type of the article and number of articles in the noodle package .
  • the noodle package may be understood as an enclosure housing of one or more articles . Further, the articles may be smaller packages , obj ects or a combination thereof .
  • the enclosure may, without any limitation, be a sheet or a box .
  • light of predefined wavelength may be irradiated on the noodle package .
  • the noodle package and the articles in the noodle package may absorb some of the irradiated light and may reflect the remaining .
  • the absorption and reflection of the light is dependent on properties of the material in contact with the light . Accordingly, a correlation of the light absorbed and reflected may give an indication of the number and type of articles in the noodle package without manual inspection of the noodle package itsel f .
  • Figures 1 ( a ) and 1 (b ) illustrate schematic drawings of an automated system 100 for detecting variation of articles 104 in a noodle package 102 in accordance with an embodiment of the present invention .
  • the automated system 100 may be implemented in both high speed lines with machine speed of 300-350 Packages /min and medium speed lines with machine speed of 160-240 Packages/min .
  • the automated system 100 include one light source 106 , one photoelectric sensor 108 and an article detection engine 110 .
  • the light source 106 and photoelectric sensor 108 may be arranged on top of the noodle package 102 , such that noodle package 102 may be analyzed for accurate detection of the variation of articles 104 in the noodle package 102 .
  • the light source 106 , the photoelectric sensor 108 and the article detection engine 110 may be arranged along a conveyor belt 112 carrying the noodle packages 102 .
  • the automated system 100 may be communicatively coupled to a memory and a processor .
  • the processor may be configured to control the operations of the one light source 106 , the one photoelectric sensor 108 and the article detection engine 110 .
  • the processor and the memory may form a part of a chipset installed in the automated system 100 .
  • the memory may be implemented as a static memory or a dynamic memory .
  • the memory may be internal to the automated system 100 .
  • the memory may be implemented as an external memory for the automated system 100.
  • the memory may be a cloud-based storage or onsite based storage.
  • the processor may be implemented as one or more microprocessors, microcomputers, microcontrollers, central processing units, state machines, logic circuitries, or any devices that manipulate signals, based on operational instructions .
  • the one light source 106 may be configured to illuminate light on a package 102.
  • the light source 106 may radiate light in range of near infrared wavelength.
  • the wavelength may be in range of 750nm - lOOOnm, preferably in the range of 750nm - 900nm.
  • the automated system (100) for detecting variation of articles (104) in a noodle package (102) has achieved the best results in case the light source 106 radiate light in range of near infrared wavelength in range of 750nm - lOOOnm, preferably in the range of 750nm - 900nm.
  • a plastic packaging material preferably a polypropylene packaging material, or a paper packaging material can be penetrated through and hit the sachet (s) , which are placed on top of the noodle cake and reflect back a particular filtered wavelength to a single hyper spectral imaging device.
  • This hyper spectral imaging device collects incoming or reflecting signals from the noodle packaging including the sachet (s) and generates a 3D Photo acoustic imaging. At higher wavelength above lOOOnm, the accuracy in detection is getting lower.
  • the photoelectric sensor 108 may be configured to capture signals based on the light absorbed and reflected by the one or more articles 104 in the noodle package 102 or inner wal ls of the noodle package 102 .
  • the captured signals would correspond to the article 104 in the noodle package 102 .
  • the captured signal corresponds to inner walls of the noodle package 102 .
  • the one photoelectric sensor 108 may be a hyper spectral camera .
  • the article detection engine 110 may be configured to correlate the captured signals with pre-stored data to detect a variation in type of article 104 , number of articles 104 in the noodle package 102 or a combination thereof .
  • the variation may be from a predefined type and number of the article 104 intended to be in the noodle package 102 . Accordingly, the variation may be understood as absence of desired number of articles 104 , absence of the articles 104 or presence of wrong type of articles 104 .
  • the pre-stored data provides a correlation between intensity and strength of signals and at least one of : type of articles 104 and number of articles 104 in the noodle package 102 .
  • the noodle package 102 may include one sachet made of metallic reflective sheet with powdered components, preferably taste maker, another sachet made of transparent sheet with lipid and a noodle cake non-covered by any sheet.
  • the light absorbed by the powdered components, the lipid and the noodle cake would be different not only because of their own densities and composition, but also because of the type of sheet covering each of these components. Accordingly, the intensity and strength of signals captured from each of the component would be different.
  • the light absorbed and reflected by a single quantity of any of these components would be different, compared to that absorbed and reflected by plurality. For example, two noodle cakes placed on top of each other, would absorb more light compared to a single noodle cake.
  • the article detection engine 110 may facilitate rejection of the noodle package 102 upon finding a variation in the type of article 104, the number of articles 104 in the noodle package 102 or a combination thereof.
  • the rejection may indicate that the either the type of article 104 (s) in the noodle package 102 or quantity of the articles 104 in the noodle package 102 or any combination thereof is mismatched to desired type and quantity.
  • the noodle package 102 may be rejected if either type or quantity is mismatched.
  • the article detection engine 110 may facilitate approval of the noodle package 102 upon a match between the prestored data and the captured signals . It may be understood that the match between the pre-stored data and the captured signals would indicate that both the type and quantity of articles 104 in the noodle package 102 as desired .
  • the automated system 100 may implement signal threshold stored in the memory related to capture time and a particular reference point for the correlation and detection of the variation .
  • image of the noodle package 102 at three di f ferent positions may be captured and reflective infra-red spectral signatures may be recorded at each point .
  • the recorded reflective infra-red spectral signatures may be plotted to determine averagemaximum threshold .
  • data analytics such as Machine leaning model , the noodle package 102 may be accepted or rej ected .
  • the article detection engine 110 may employ a sel f-learning mechanism such as a machine learning model , computer vision and fuz zy logic-based model for correlation of the captured audio-visual signals to facilitate approval of the noodle package 102 and rej ection of the noodle package 102 .
  • a sel f-learning mechanism such as a machine learning model , computer vision and fuz zy logic-based model for correlation of the captured audio-visual signals to facilitate approval of the noodle package 102 and rej ection of the noodle package 102 .
  • the automated system 100 may include one or more audio-visual prompting mechanisms .
  • the visual prompting mechanisms may include one or more LEDs or buz zers of di f ferent color, such that a first colored LED may glow upon rej ection of the noodle package 102 and a second colored LED may glow upon acceptance of the noodle package 102 .
  • the visual prompting mechanisms may also include a LCD display configured to di splay corresponding digital alerts upon either rej ection or acceptance of the noodle package 102 or both .
  • the audio prompting mechanism may include a speaker configured to output an audio message or a sound to indicate either rej ection or acceptance of the noodle package 102 or both .
  • the automated system 100 may include a pneumatic ej ection system 114 for automatically transporting the rej ected noodle package 102 to a rej ection bin .
  • the pneumatic ej ection system 114 may include pneumatic cylinder device 116 for ej ection .
  • the pneumatic cylinder may be configured to produce required force by using energy from pressuri zed air .
  • pneumatic pressure of 5 Bar may be applied to move the rej ected noodle package 102 to the rej ection bin .
  • the rej ected noodle package 102 may be manually moved by an operator to a rej ection bin . Further, the approved noodle package 102 may be forwarded for circulation .
  • the noodle package 102 may be a sealed noodle package 102 with the articles 104 .
  • the sealed noodle package 102 the variation of the articles 104 is detected after complete sealing off the noodle package 102 .
  • 3D Photo acoustic imaging may be employed for the correlation of the captured signals .
  • the photoelectric sensor 108 may be a 3D Photo acoustic sensor .
  • the noodle package 102 may be a noodle noodle package 102 and the articles 104 may be taste maker sachet , a liquid sachet or a combination thereof .
  • the articles 104 may, without any limitation, include taste maker sachet , oil sachet , chilli flakes sachet , seasoning sachet or a combination thereof .
  • a noodle noodle package 102 should include a noodle cake , sachet A of seasoning, sachet B of onion and chilli flakes , sachet C of spiced oil or a combination thereof .
  • the noodle cake is placed in the noodle package 102 without any covering sheet
  • the sachet A and sachet B are made of di f ferent reflective sheets
  • the sachet C is made of transparent sheet .
  • the noodle noodle package 102 may be illuminated by one light source 106 in range of Near- Infrared (NIR) .
  • NIR Near- Infrared
  • One 3D Photo acoustic sensor may be configured to capture signals based on the light absorbed and reflected by either the sachets and the noodle cake in the noodle noodle package 102 or the inner walls of the noodle noodle package 102 .
  • the article detection engine 110 may correlate the captured signals with pre-stored data to detect a variation in at least one of: type of articles 104 i.e. type of sachets and noodle cake and number of articles 104 i.e.
  • the article detection engine 110 may also facilitate rejection of the noodle noodle package 102 upon finding a variation in the at least one of: type of the article 104 and number of the articles 104 in the noodle noodle package 102.
  • the pre-stored data provides a correlation between intensity and strength of signals and at least one of: type of articles 104 and number of articles 104 in the noodle noodle package 102.
  • the absorption and reflection are higher for denser material .
  • the intensity of the captured signal is 40.10kHZ, at scan speed of 8kHz. Further, in a scenario with no sachet and only noodle cake in the noodle noodle package 102, the intensity of the captured signal is 40.43kKz at the scan speed of 8kHz. Thus, with the decrease in the number of sachets, the intensity of the captured signal increases.
  • Figure 3 illustrates a flowchart of an automatic method for detecting variation of articles in a noodle package in accordance with an embodiment of the present invention.
  • the noodle package may be a sealed noodle package covering the articles .
  • light may be illuminated on the noodle package .
  • the illuminated light may be in range of near infrared wavelength .
  • signals based on the light absorbed and reflected by one or more articles in the noodle package or inner walls of the noodle package may be captured .
  • the signals may be captured by hyper spectral cameras .
  • the captured signals are correlated with pre-stored data to detect a variation in type of article , number of article in the noodle package or a combination thereof .
  • the variation is from a predefined type and number of the article intended to be in the noodle package .
  • the pre-stored data may provide a correlation between intensity and strength of signals and type of articles , number of articles in the noodle package or a combination thereof .
  • 3D Photo acoustic imaging may be employed for the correlation of the captured audio-visual signals .
  • rej ection of the noodle package may be facilitated upon finding a variation in the type of the article , number of the article in the noodle package or a combination thereof .
  • approval of the noodle package may be facilitated upon a match between the pre-stored data and the captured signals .
  • the articles may include a taste maker sachet , a liquid sachet or a combination therof .
  • the articles may, without any limitation, include taste maker sachet , oil sachet , chilli flakes sachet , seasoning sachet or a combination thereof .
  • the automated system and method for detection of variation in articles of a package disclosed by the present invention is a non-destructive automated standalone mechanism to detect and ej ect noodle packages having variation in type of articles or number of articles or both post wrapping irrespective of type of packaging material .
  • the automated system of the present invention has a compact design and is capable of detecting sachet of any primary packaging or si ze in single article pack or a multiple article pack .
  • the present invention is flexible to upgrade and generates less carbon foot-prints .

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  • Physics & Mathematics (AREA)
  • Analytical Chemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
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  • Pathology (AREA)
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  • General Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
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  • Engineering & Computer Science (AREA)
  • Optics & Photonics (AREA)
  • Packages (AREA)

Abstract

An automated system (100) for detecting variation of articles (104) in a noodle package (102) is disclosed. The automated system (100) includes a light source (106) to illuminate light on a noodle package (102), photoelectric sensor (108) configured to capture signals based on the light absorbed and reflected by one of: the articles (104) in the noodle package (102) and inner walls of the noodle package (102) and an article detection engine (110) to: correlate the captured signals with pre-stored data to detect a variation in at least one of: type of article (104) and number of articles (104) in the package (102), wherein the variation is from a predefined type and number of the article (104) intended to be in the noodle package (102) and rejection of the noodle package (102) upon finding a variation in the at least one of: type of the article (104) and number of the article (104) in the noodle package (102).

Description

DETECTION OF VARIATION IN A NOODLE PACKAGE
FIELD OF THE INVENTION
[ 0001 ] The present invention generally relates to packaging of articles . In particular, the present invention relates to automated mechanism for detection of variation in articles of a noodle package .
BACKGROUND OF THE INVENTION
[ 0002 ] Generally, assembly and packaging lines are automated, such as noodle packages are automatically filled with predefined articles such as a taste maker sachet , a liquid sachet or a combination thereof and after filling of the predef ined articles the noodle packages are sealed . In a package type and quantity of the articles are signi ficant and are predefined in automated packaging lines .
[ 0003 ] Manual inspection of sealed noodle packages by an operator to check i f the type and quantity of articles is correct is not practically feasible , as it would require opening of the seal of the noodle package , amounting to destruction of the package . Accordingly, techniques like X-ray based inspection and metal detector-based inspection are conventionally implemented to inspect the articles in the sealed packages . However, the X-ray based inspection mechanism is bulky and costly . Further, X-ray based inspection mechanism fails when similar type of articles are placed upon each other in the noodle package , as the X-ray based inspection mechanism considers such articles as a single unit and do not provide any distinction between di f ferent types of the articles . Also , the metal detector-based inspection mechanism is only able to detect metallic articles or articles having metallic covering sheets . However, the metal detector-based inspection mechanism fails to disclose articles with transparent or non- metallic covering sheets .
[ 0004 ] Thus , in the light of the above , there is a need for an automated mechanism to detect variation of type and number of articles in a noodle package , irrespective of the material of the article or material of the covering sheet of the article and which is not bulky and is cost ef ficient .
SUMMARY OF THE INVENTION
[ 0005 ] In an embodiment to the present invention an automated system for detecting variation of articles in a noodle package is disclosed . The automated system includes one light source to illuminate light on a noodle package and one photoelectric sensor configured to capture signals based on the light absorbed and reflected by one of : the one or more articles in the noodle package and inner walls of the noodle package . The automated system also includes an article detection engine to correlate the captured signals with pre-stored data to detect a variation in at least one of : type of article and number of articles in the noodle package . The variation is from a predefined type and number of the article intended to be in the noodle package . The article detection engine is also configured to facilitate rej ection of the noodle package upon finding a variation in the at least one of : type of the article and number of the article in the noodle package . [ 0006 ] In an embodiment of the present invention, the noodle package is a sealed noodle package covering the articles .
[ 0007 ] In an embodiment of the present invention, the light source radiate light in range of near infrared wavelength .
[ 0008 ] In an embodiment of the present invention, the pre-stored data provides a correlation between intensity and strength of signals and at least one of : type of articles and number of articles in the noodle package .
[ 0009 ] In an embodiment of the present invention, 3D Photo acoustic imaging is employed for the correlation of the captured signals . Further, the photoelectric sensor is a 3D Photo acoustic sensor .
[ 0010 ] In an embodiment of the present invention, the article detection engine facilitates approval of the noodle package upon a match between the pre-stored data and the captured signals .
[ 0011 ] In an embodiment of the present invention, the articles comprise a taste maker sachet , a liquid sachet or a combination thereof , preferably a taste maker sachet and a liquid sachet . In an embodiment the liquid sachet is a lipid sachet , preferably an oil sachet .
[ 0012 ] An embodiment of the present invention discloses an automatic method for detecting variation of articles in a noodle package . The automatic method includes illuminating light on a noodle package , capturing signals based on the light absorbed and reflected by one of : one or more articles in the noodle package and inner walls of the noodle package and correlating the captured signals with pre-stored data to detect a variation in at least one of : type of article and number of articles in the noodle package . The variation is from a predefined type and number of the article intended to be in the noodle package . Further, facilitating rej ection of the noodle package upon finding a variation in the at least one of : type of the article and number of the article in the noodle package .
[ 0013 ] In an embodiment of the present invention, the noodle package is a sealed noodle package covering the articles .
[ 0014 ] In an embodiment of the present invention, the illuminated light is in range of near infrared wavelength .
[ 0015 ] In an embodiment of the present invention, the pre-stored data provides a correlation between : intensity and strength of signals and at least one of : type of articles and number of articles in the noodle package .
[ 0016 ] In an embodiment of the present invention, 3D Photo acoustic imaging is employed for the correlation of the captured audio-visual signals .
[ 0017 ] In an embodiment of the present invention, the automatic method also includes facilitating approval of the noodle package upon a match between the pre-stored data and the captured signals .
[ 0018 ] Other aspects , advantages , and salient features of the present invention will become apparent to those skilled in the art from the following detailed description read in conj unction with the drawings . BRIEF DESCRIPTION OF DRAWINGS
[ 0019 ] The following drawings are illustrative of preferred embodiments for enabling the present invention and are not intended to limit the scope of the invention . The drawings are not to scale (unless so stated) and are intended for use in conj unction with the explanations in the following detailed description .
[ 0020 ] Figures 1 ( a ) and 1 (b ) illustrate schematic drawings of an automated system for detecting variation of articles in a noodle package in accordance with an embodiment of the present invention;
[ 0021 ] Figure 2 illustrates an exemplary embodiment of operation of the present invention with respect to a noodle package ; and
[ 0022 ] Figure 3 illustrates a flowchart of an automatic method for detecting variation of articles in a noodle package in accordance with an embodiment of the present invention .
DETAILED DESCRIPTION OF DRAWINGS
[ 0023 ] The following disclosure is provided in order to enable a person having ordinary skill in the art to practice the invention . Exemplary embodiments are provided only for illustrative purposes and various modi fications will be readily apparent to persons skilled in the art . The general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the invention . Also , the terminology and phraseology used is for the purpose of describing exemplary embodiments and should not be considered limiting . Thus , the present invention is to be accorded the widest scope encompassing numerous alternatives , modi fications and equivalents consistent with the principles and features disclosed . For the purpose of clarity, details relating to technical material that is known in the technical fields related to the invention have not been described in detail so as not to unnecessarily obscure the present invention .
[ 0024 ] The present invention relates to detection of variation of articles in a noodle package . The variation may be with respect to type of the article and number of articles in the noodle package . The noodle package may be understood as an enclosure housing of one or more articles . Further, the articles may be smaller packages , obj ects or a combination thereof . The enclosure may, without any limitation, be a sheet or a box .
[ 0025 ] Once the articles may be enclosed in the noodle package , light of predefined wavelength may be irradiated on the noodle package . The noodle package and the articles in the noodle package may absorb some of the irradiated light and may reflect the remaining . The absorption and reflection of the light is dependent on properties of the material in contact with the light . Accordingly, a correlation of the light absorbed and reflected may give an indication of the number and type of articles in the noodle package without manual inspection of the noodle package itsel f .
[ 0026 ] Figures 1 ( a ) and 1 (b ) illustrate schematic drawings of an automated system 100 for detecting variation of articles 104 in a noodle package 102 in accordance with an embodiment of the present invention . For the sake of brevity description of Figures 1 ( a ) and 1 (b ) has been provided together . The automated system 100 may be implemented in both high speed lines with machine speed of 300-350 Packages /min and medium speed lines with machine speed of 160-240 Packages/min .
[ 0027 ] In an embodiment of the present invention, the automated system 100 include one light source 106 , one photoelectric sensor 108 and an article detection engine 110 . The light source 106 and photoelectric sensor 108 may be arranged on top of the noodle package 102 , such that noodle package 102 may be analyzed for accurate detection of the variation of articles 104 in the noodle package 102 .
[ 0028 ] In an exemplary embodiment of the present invention, the light source 106 , the photoelectric sensor 108 and the article detection engine 110 may be arranged along a conveyor belt 112 carrying the noodle packages 102 .
[ 0029 ] The automated system 100 may be communicatively coupled to a memory and a processor . The processor may be configured to control the operations of the one light source 106 , the one photoelectric sensor 108 and the article detection engine 110 .
[ 0030 ] In an embodiment of the present invention, the processor and the memory may form a part of a chipset installed in the automated system 100 . In another embodiment of the present invention, the memory may be implemented as a static memory or a dynamic memory . In an example , the memory may be internal to the automated system 100 . In another example , the memory may be implemented as an external memory for the automated system 100. The memory may be a cloud-based storage or onsite based storage. Further, the processor may be implemented as one or more microprocessors, microcomputers, microcontrollers, central processing units, state machines, logic circuitries, or any devices that manipulate signals, based on operational instructions .
[0031] The one light source 106 may be configured to illuminate light on a package 102. In an embodiment of the present invention, the light source 106 may radiate light in range of near infrared wavelength. Specifically, the wavelength may be in range of 750nm - lOOOnm, preferably in the range of 750nm - 900nm. Surprisingly, it has been found by the inventors, that the automated system (100) for detecting variation of articles (104) in a noodle package (102) has achieved the best results in case the light source 106 radiate light in range of near infrared wavelength in range of 750nm - lOOOnm, preferably in the range of 750nm - 900nm. Within this wavelength a plastic packaging material, preferably a polypropylene packaging material, or a paper packaging material can be penetrated through and hit the sachet (s) , which are placed on top of the noodle cake and reflect back a particular filtered wavelength to a single hyper spectral imaging device. This hyper spectral imaging device collects incoming or reflecting signals from the noodle packaging including the sachet (s) and generates a 3D Photo acoustic imaging. At higher wavelength above lOOOnm, the accuracy in detection is getting lower. In addition, by using a wavelength in range of 750nm - lOOOnm, preferably in the range of 750nm - 900nm, no heating ef fect occur, which will occur in case a wavelength above l O O Onm is used . Even a short heating might af fect some ingredients of the food product like an oil sachet containing flavorings and can influence the shel f-life . The photoelectric sensor 108 may be configured to capture signals based on the light absorbed and reflected by the one or more articles 104 in the noodle package 102 or inner wal ls of the noodle package 102 . It may be understood that when at least one article 104 may be present in the noodle package 102 , the captured signals would correspond to the article 104 in the noodle package 102 . On the other hand, i f the noodle package 102 does not include any article 104 , then the captured signal corresponds to inner walls of the noodle package 102 . In an exemplary embodiment of the present invention, the one photoelectric sensor 108 may be a hyper spectral camera .
[ 0032 ] Further , the article detection engine 110 may be configured to correlate the captured signals with pre-stored data to detect a variation in type of article 104 , number of articles 104 in the noodle package 102 or a combination thereof . The variation may be from a predefined type and number of the article 104 intended to be in the noodle package 102 . Accordingly, the variation may be understood as absence of desired number of articles 104 , absence of the articles 104 or presence of wrong type of articles 104 . In an embodiment of the present invention, the pre-stored data provides a correlation between intensity and strength of signals and at least one of : type of articles 104 and number of articles 104 in the noodle package 102 . Since di f ferent material have different densities and spectral profiles, the light absorbed and reflected by different type of article 104 would be different. For example, the noodle package 102 may include one sachet made of metallic reflective sheet with powdered components, preferably taste maker, another sachet made of transparent sheet with lipid and a noodle cake non-covered by any sheet. Here, the light absorbed by the powdered components, the lipid and the noodle cake would be different not only because of their own densities and composition, but also because of the type of sheet covering each of these components. Accordingly, the intensity and strength of signals captured from each of the component would be different. Further, the light absorbed and reflected by a single quantity of any of these components would be different, compared to that absorbed and reflected by plurality. For example, two noodle cakes placed on top of each other, would absorb more light compared to a single noodle cake.
[0033] The article detection engine 110 may facilitate rejection of the noodle package 102 upon finding a variation in the type of article 104, the number of articles 104 in the noodle package 102 or a combination thereof. Thus, the rejection may indicate that the either the type of article 104 (s) in the noodle package 102 or quantity of the articles 104 in the noodle package 102 or any combination thereof is mismatched to desired type and quantity. Accordingly, the noodle package 102 may be rejected if either type or quantity is mismatched. In an embodiment of the present invention, the article detection engine 110 may facilitate approval of the noodle package 102 upon a match between the prestored data and the captured signals . It may be understood that the match between the pre-stored data and the captured signals would indicate that both the type and quantity of articles 104 in the noodle package 102 as desired .
[ 0034 ] In an exemplary embodiment of the present invention, the automated system 100 may implement signal threshold stored in the memory related to capture time and a particular reference point for the correlation and detection of the variation . In an exemplary embodiment of the present invention, image of the noodle package 102 at three di f ferent positions may be captured and reflective infra-red spectral signatures may be recorded at each point . The recorded reflective infra-red spectral signatures may be plotted to determine averagemaximum threshold . Further, using data analytics , such as Machine leaning model , the noodle package 102 may be accepted or rej ected .
[ 0035 ] In an embodiment of the present invention, the article detection engine 110 may employ a sel f-learning mechanism such as a machine learning model , computer vision and fuz zy logic-based model for correlation of the captured audio-visual signals to facilitate approval of the noodle package 102 and rej ection of the noodle package 102 .
[ 0036 ] In an exemplary embodiment of the present invention, the automated system 100 may include one or more audio-visual prompting mechanisms . The visual prompting mechanisms may include one or more LEDs or buz zers of di f ferent color, such that a first colored LED may glow upon rej ection of the noodle package 102 and a second colored LED may glow upon acceptance of the noodle package 102 . The visual prompting mechanisms may also include a LCD display configured to di splay corresponding digital alerts upon either rej ection or acceptance of the noodle package 102 or both . The audio prompting mechanism may include a speaker configured to output an audio message or a sound to indicate either rej ection or acceptance of the noodle package 102 or both .
[ 0037 ] In an embodiment of the present invention, the automated system 100 may include a pneumatic ej ection system 114 for automatically transporting the rej ected noodle package 102 to a rej ection bin . The pneumatic ej ection system 114 may include pneumatic cylinder device 116 for ej ection . The pneumatic cylinder may be configured to produce required force by using energy from pressuri zed air . In an exemplary embodiment of the present invention, pneumatic pressure of 5 Bar may be applied to move the rej ected noodle package 102 to the rej ection bin .
[ 0038 ] In another embodiment of the present invention, the rej ected noodle package 102 may be manually moved by an operator to a rej ection bin . Further, the approved noodle package 102 may be forwarded for circulation .
[ 0039 ] In an embodiment of the present invention, the noodle package 102 may be a sealed noodle package 102 with the articles 104 . In such a case , the sealed noodle package 102 , the variation of the articles 104 is detected after complete sealing off the noodle package 102 .
[ 0040 ] In an exemplary embodiment of the present invention, 3D Photo acoustic imaging may be employed for the correlation of the captured signals . Further, the photoelectric sensor 108 may be a 3D Photo acoustic sensor .
[ 0041 ] In an exemplary embodiment of the present invention, the noodle package 102 may be a noodle noodle package 102 and the articles 104 may be taste maker sachet , a liquid sachet or a combination thereof . In an embodiment of the present invention, the articles 104 may, without any limitation, include taste maker sachet , oil sachet , chilli flakes sachet , seasoning sachet or a combination thereof .
[ 0042 ] As illustrated, it is desirable that a noodle noodle package 102 should include a noodle cake , sachet A of seasoning, sachet B of onion and chilli flakes , sachet C of spiced oil or a combination thereof . As may be observed the noodle cake is placed in the noodle package 102 without any covering sheet , the sachet A and sachet B are made of di f ferent reflective sheets and the sachet C is made of transparent sheet .
[ 0043 ] In operation, the noodle noodle package 102 may be illuminated by one light source 106 in range of Near- Infrared (NIR) . One 3D Photo acoustic sensor may be configured to capture signals based on the light absorbed and reflected by either the sachets and the noodle cake in the noodle noodle package 102 or the inner walls of the noodle noodle package 102 . Further, the article detection engine 110 may correlate the captured signals with pre-stored data to detect a variation in at least one of: type of articles 104 i.e. type of sachets and noodle cake and number of articles 104 i.e. number of each type of sachet and noodle cake in the noodle noodle package 102. The variation is from a predefined type and number of the sachets and noodle cake intended to be in the noodle noodle package 102. The article detection engine 110 may also facilitate rejection of the noodle noodle package 102 upon finding a variation in the at least one of: type of the article 104 and number of the articles 104 in the noodle noodle package 102.
[0044] The pre-stored data provides a correlation between intensity and strength of signals and at least one of: type of articles 104 and number of articles 104 in the noodle noodle package 102. As a principle, the absorption and reflection are higher for denser material .
[0045] In an exemplary embodiment, in a scenario when all three sachets and noodle cake are present in the noodle noodle package 102, the intensity of the captured signal is 40.10kHZ, at scan speed of 8kHz. Further, in a scenario with no sachet and only noodle cake in the noodle noodle package 102, the intensity of the captured signal is 40.43kKz at the scan speed of 8kHz. Thus, with the decrease in the number of sachets, the intensity of the captured signal increases.
[0046] Figure 3 illustrates a flowchart of an automatic method for detecting variation of articles in a noodle package in accordance with an embodiment of the present invention. In an embodiment of the present invention, the noodle package may be a sealed noodle package covering the articles .
[ 0047 ] At step 302 , light may be illuminated on the noodle package . In an embodiment of the present invention, the illuminated light may be in range of near infrared wavelength .
[ 0048 ] At step 304 , signals based on the light absorbed and reflected by one or more articles in the noodle package or inner walls of the noodle package may be captured . In an exemplary embodiment of the present invention, the signals may be captured by hyper spectral cameras .
[ 0049 ] At step 306 , the captured signals are correlated with pre-stored data to detect a variation in type of article , number of article in the noodle package or a combination thereof . The variation is from a predefined type and number of the article intended to be in the noodle package . In an exemplary embodiment of the present invention, the pre-stored data may provide a correlation between intensity and strength of signals and type of articles , number of articles in the noodle package or a combination thereof . Further, 3D Photo acoustic imaging may be employed for the correlation of the captured audio-visual signals .
[ 0050 ] At step 308 , rej ection of the noodle package may be facilitated upon finding a variation in the type of the article , number of the article in the noodle package or a combination thereof . In an embodiment of the present invention, approval of the noodle package may be facilitated upon a match between the pre-stored data and the captured signals .
[ 0051 ] In an exemplary embodiment of the present invention, the articles may include a taste maker sachet , a liquid sachet or a combination therof . In an embodiment of the present invention, the articles may, without any limitation, include taste maker sachet , oil sachet , chilli flakes sachet , seasoning sachet or a combination thereof .
[ 0052 ] The automated system and method for detection of variation in articles of a package disclosed by the present invention is a non-destructive automated standalone mechanism to detect and ej ect noodle packages having variation in type of articles or number of articles or both post wrapping irrespective of type of packaging material . The automated system of the present invention has a compact design and is capable of detecting sachet of any primary packaging or si ze in single article pack or a multiple article pack . The present invention is flexible to upgrade and generates less carbon foot-prints .
[ 0053 ] While the exemplary embodiments of the present invention are described and illustrated herein, it will be appreciated that they are merely illustrative . It will be understood by those skil led in the art that various modi fications in form and detail may be made therein without departing from or of fending the spirit and scope of the invention as defined by the appended claims .

Claims

We claim:
1. An automated system (100) for detecting variation of articles (104) in a noodle package (102) , the automated system (100) comprising: one light source (106) to illuminate light on a noodle package (102) ; one photoelectric sensor (108) configured to capture signals based on the light absorbed and reflected by one of: the one or more articles (104) in the noodle package (102) and inner walls of the noodle package (102) ; an article detection engine (110) to: correlate the captured signals with pre-stored data to detect a variation in at least one of: type of article (104) and number of articles (104) in the noodle package (102) , wherein the variation is from a predefined type and number of the article (104) intended to be in the noodle package (102) ; facilitate rejection of the noodle package (102) upon finding a variation in the at least one of: type of the article (104) and number of the article (104) in the noodle package (102) ; wherein the articles comprise a taste maker sachet, a liquid sachet or a combination thereof and wherein the photoelectric sensor (108) is a 3D Photo acoustic sensor and wherein a 3D Photo acoustic imaging is employed for the correlation of the captured signals.
2. The automated system (100) as claimed in claim 1, wherein the noodle package (102) is a sealed noodle package (102) covering the articles (104) .
3. The automated system (100) as claimed in claim 1, wherein the light source (106) radiate light in range of near infrared wavelength in the range of 750 to lOOOnm.
4. The automated system (100) as claimed in claim 1, wherein the pre-stored data provides a correlation between : intensity and strength of signals; and at least one of: type of articles (104) and number of articles (104) in the noodle package (102) .
5. The automated system (100) as claimed in claim 1, wherein the article detection engine (110) facilitates approval of the noodle package (102) upon a match between the pre-stored data and the captured signals.
6. The automated system (100) as claimed in claim 1, wherein the articles are a taste maker sachet and a liquid sachet.
7. The automated system (100) as claimed in claim 1, wherein the articles are selected from the group of taste maker sachet, oil sachet, chilli flakes sachet, seasoning sachet or a combination thereof.
8 . An automatic method for detecting variation of articles in a noodle package , the automatic method comprising : illuminating light on a package ; capturing signals based on the light absorbed and reflected by one of : one or more articles in the package and inner walls of the package ; correlating the captured signals with pre-stored data to detect a variation in at least one of : type of article and number of article in the package , wherein the variation is from a predefined type and number of the article intended to be in the package ; and facilitating rej ection of the package upon finding a variation in the at least one of : type of the article and number of the article in the package ; wherein the article comprise a taste maker sachet , a liquid sachet or a combination thereof and wherein 3D Photo acoustic imaging is employed for the correlation of the captured audio-visual signals .
9 . The automatic method as claimed in claim 8 , wherein the package is a sealed package covering the articles .
10 . The automatic method as claimed in claim 8 , wherein the illuminated light is in range of near infrared wavelength in the range of 750 to l O O Onm .
11. The automatic method as claimed in claim 8, wherein the pre-stored data provides a correlation between: intensity and strength of signals; and at least one of: type of articles and number of articles in the package.
12. The automatic method as claimed in claim 8, further comprising facilitating approval of the package upon a match between the pre-stored data and the captured signals.
13. The automatic method as claimed in claim 8, wherein the articles are a taste maker sachet and a liquid sachet .
PCT/EP2023/084734 2022-12-07 2023-12-07 Detection of variation in a noodle package WO2024121320A1 (en)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
IN202211070560 2022-12-07
IN202211070560 2022-12-07
EP23153215 2023-01-25
EP23153215.1 2023-01-25

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US20040207842A1 (en) * 2002-03-12 2004-10-21 Rzasa David M. System and method for pharmacy validation and inspection
US20080289427A1 (en) * 2005-05-04 2008-11-27 Robert Kurt Brandt Method and Apparatus of Detecting an Object
CN101531258A (en) * 2009-04-17 2009-09-16 天津普达软件技术有限公司 Machine vision-based instant noodle seasoning packet automatic detection instrument and method
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