EP0824042A1 - Einrichtung zum Sortieren von Kunststoffflaschen und mit dieser durchgeführtes Verfahren - Google Patents

Einrichtung zum Sortieren von Kunststoffflaschen und mit dieser durchgeführtes Verfahren Download PDF

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Publication number
EP0824042A1
EP0824042A1 EP97401786A EP97401786A EP0824042A1 EP 0824042 A1 EP0824042 A1 EP 0824042A1 EP 97401786 A EP97401786 A EP 97401786A EP 97401786 A EP97401786 A EP 97401786A EP 0824042 A1 EP0824042 A1 EP 0824042A1
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EP
European Patent Office
Prior art keywords
sorting
products
product
machine according
sorting machine
Prior art date
Legal status (The legal status 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 status listed.)
Withdrawn
Application number
EP97401786A
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English (en)
French (fr)
Inventor
Stéphane Vauche
Michel Hauzeur
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
P Vauche SA
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P Vauche SA
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 P Vauche SA filed Critical P Vauche SA
Publication of EP0824042A1 publication Critical patent/EP0824042A1/de
Withdrawn legal-status Critical Current

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Classifications

    • 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
    • B07C5/3404—Sorting according to other particular properties according to properties of containers or receptacles, e.g. rigidity, leaks, fill-level
    • B07C5/3408—Sorting according to other particular properties according to properties of containers or receptacles, e.g. rigidity, leaks, fill-level for bottles, jars or other glassware
    • 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
    • B07C5/04—Sorting according to size
    • B07C5/12—Sorting according to size characterised by the application to particular articles, not otherwise provided for
    • B07C5/122—Sorting according to size characterised by the application to particular articles, not otherwise provided for for bottles, ampoules, jars and other glassware
    • B07C5/126—Sorting according to size characterised by the application to particular articles, not otherwise provided for for bottles, ampoules, jars and other glassware by means of photo-electric sensors, e.g. according to colour
    • 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
    • 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
    • B07C5/3422—Sorting according to other particular properties according to optical properties, e.g. colour using video scanning devices, e.g. TV-cameras

Definitions

  • the present invention relates to a sorting machine in particular for plastic bottles and the process implemented by this machine.
  • Australian patent 662,338 teaches a lamp machine fluorescent and linear camera that receives light from the lamp after this is passed through a polarizing filter.
  • the camera also features a polarizing filter oriented perpendicular to the light source of the lamp polarizing filter.
  • the selection of bottles is made by detection of crossing of threshold representative of the quantity of light transmitted.
  • the camera also has a green filter to perform the distinction between clear HDPE bottles and green bottles of the PET type.
  • patent EP 0 441 012 also teaches the use polarizing filters to detect differences in birefringence of different plastics.
  • This document also teaches the use of a X-ray source as a means of detection.
  • This document teaches two embodiments, one in which the detector is arranged on the other side of the bottle with respect to the light source, the other in which the detector is placed on the same side. But for this last variant, it is specified that it can detect only the opaque bottles. Indeed, in the case of transparent bottles, the beam would pass through the bottle and would not be received by the sensor.
  • Such a device requires the presence of bottle detection sensors at each of stations so as to implement the detection means for each of the posts when each bottle is presented to the post.
  • the number of detection devices increases the cost of the apparatus and the reliability of the detections because the optical presence detectors can be partly blocked by dirt, which can cause machine malfunctions.
  • Another device such as PCT application WO 94/25186 uses a infrared spectroscopy system and a device for detecting position associated with a conveyor speed sensor for, depending the distance between the detection device and the cameras recording, trigger video recording of color and form determined at the time of shooting of these cameras.
  • the detection device detects bottles or objects that are on the carrier, which may cause the device to consider a litter other than a bottle when it passed the sorting systems.
  • a first object of the invention is therefore to overcome the drawbacks of prior art.
  • the product sorting machine plastics comprising a transport system, means for sorting produced according to the signals resulting from at least one detection and memorized by memory means, a system analysis receiving and processing signals from the station detection, characterized in that the transport systems include means of queuing products, means of determining the precise position of the products to trigger the implementation of the station detection at the time of the passage of the same part of each product, the detection station performing sorting according to sorting conditions learned by means of learning the sorting conditions, said station detection consisting of a laser beam polarized by a first filter and a camera receiving a directly incident part of the beam after that it has passed through a second filter and another part of the beam which has passed through each product before reaching the second filter.
  • the means of learning sorting conditions include means of associating with information delivered by the neural analysis system defined in a space multidimensional other information selected by the user when passage of the sample in front of the detection station.
  • a second or third principle of detection consists of a black light source (UV) and a camera recording the signal from the light source through a window, said window defining a determined position with respect to the transport.
  • UV black light source
  • the second or third principle of detection consists of an infrared light source to detect HDPE and a camera allowing spectroscopy of the different product samples.
  • each of the signals delivered by a detection principle is sent to a neural analysis system comparing, in 256-dimensional spaces, the information received with those memorized during a learning phase in the memory of the system, to classify each product analyzed into three categories.
  • each of the categories of classification associated with a sample of products for each station detection is delivered to the memory of a computer which decides to the operation of a sorting means according to the result developed from memorized information and a decision grid requiring either minus two classifications of the first category, a classification of the first category with at least one classification from the second category.
  • the queuing system is made up a strongly inclined conveyor belt with cleats transverse on its conveying surface and supplying the interior of a rotating drum whose internal surface is screened and provided with partitions spaced apart, which feeds through its high point a second conveyor belt in direction of movement parallel to the axis of rotation of the drum while the first conveyor belt is direction perpendicular to the axis of rotation of the drum, the speeds of displacement of the first strip, the drum and the second strip being set between each device so that the second strip delivers to an inclined chute opening above the transport system to pallet, a sample of products per pallet pushing each and file one respective product sample.
  • Another object of the invention is to propose a method implemented works by the machine which makes it possible to deliver the virgin machines and to adapt to the sorting of different samples of products with different characteristics depending on the region.
  • the method uses this couple subject information to determine sorting after the learning phase.
  • the queuing means are constituted by a turntable comprising at its outer periphery a frustoconical surface, the axis of rotation of the plate being inclined so that that the peripheral frustoconical surface of the plate comes at its point the higher tangent to the fixed surface, on which objects are pushed by the pallets driven in movement by a chain, said plate turning being surrounded on the 3 ⁇ 4 of its periphery by a rim parallel to the axis of rotation of the plate, substantially 3 ⁇ 4 of its periphery.
  • FIG. 1E represents a perspective view of a variant of realization of the sorting machine with another setting device
  • the invention will now be described in connection with FIGS. 1A to 1E.
  • the machine according to the invention comprises a hopper (1) in which the samples of products to be sorted are arranged in bulk.
  • a conveyor belt (2) whose the spacing between the bottom of the hopper and the strip makes it possible to deliver lots of products to sort.
  • the products to be sorted are, in this case, plastic bottles made of different materials such as PET (Polyethylene Terephthalate), HDPE (High Density Polyethylene), PVC (Polyvinyl Chloride).
  • PET Polyethylene Terephthalate
  • HDPE High Density Polyethylene
  • PVC Polyvinyl Chloride
  • the upper end of this strongly inclined part of the strip conveyor (20) pours the batches of bottles into a rotating drum (3) provided on its internal surface with pallets (31) spaced apart from one another distance corresponding substantially to the diameter of the bottles to be treated and not having enough space for two bottles, the distance between 2 partitions serving as a screen (32) separates the small parts (plugs, papers, stones, etc.).
  • the inclined conveyor belt (20) has on its transport surface of the cleats (21) which make it possible to block and to train the bottles in batches of two or four.
  • the drum by its rotation, ensures the placement of the bottles one by one in each notch delimited by the pallets (31) which are arranged in planes passing through the axis of rotation of the drum.
  • Drum rotation drives the bottles to the top of the drum.
  • the chute (5) distributes the bottles on a fixed sheet of sliding (64) above which circulate pallets (62) regularly spaced at determined intervals corresponding to the maximum height of the products to be sorted.
  • the pallets (62) are integral with connecting parts (61) with the links of a chain (60) which is driven in motion and stretched between two rotating gear wheels arranged at each of the ends of the sliding plate.
  • One of the gears end, for example (63b) is driven by an electric motor which the speed is adjusted according to the rate of discharge of the bottles in the chute (5).
  • Each of the connecting pieces (61) also includes a device allowing an inductive sensor to detect the passage of the pallet at a determined position and trigger the operation of the detection station (s) in analysis area A in relation to the position of the objects relative to the detection station to analyze the same part of the products.
  • the analysis area is made up, as shown in FIG.
  • a first station for detection comprising a device (82) for lighting the bottles (9) and a camera (81) delivering by a link (873) the signals generated by the passage of each bottle (9) to a neural analysis system (870).
  • the neural analysis system (870) delivers, by a link (872), information to a supervision computer (877), said computer being connected, on the one hand by a link (878) to a monitor (876) and, on the other hand by a link (874) to an interactive device with the computer and the monitor (875) consisting, for example, of a mouse.
  • the first source (82) of light of the first station consists of a black light called "lamp of wood "generating radiation in the ultraviolet range.
  • This first station thus allows lighting to make PVC bottles phosphorescent while PET bottles appear as white.
  • This station allows, by analysis by the camera (81) of the light to make a distinction between, on the one hand, PET bottles or HDPE and secondly PVC bottles.
  • a signal output from the camera (81) will be indicative of the presence of PVC while the absence of a signal will indicate HDPE or PET.
  • the second station consists of a laser beam (84) polarized in a certain direction by a first filter (841, FIG. 1C), part of the beam of which will strike the bottle (9) in an area determined by the lighting window. and the other part of the beam directly strikes a polarized mirror or a polarizing filter (85) in a direction perpendicular to the direction of polarization of the first filter (841).
  • the two beam parts are then recorded by the camera (86) which is itself possibly provided with a third polarizing filter (861) of direction perpendicular to the first filter (841).
  • a third polarizing filter (861) of direction perpendicular to the first filter (841).
  • the laser light source (84), associated with its first filter (841), is arranged on the other side of the fixed support surface (64) on which the bottles or objects slide and vis-à-vis the camera (86) relative to the opening (641).
  • the second polarizing filter (85) is arranged in front of the camera (86), between the camera and the support surface (64), the third filter, in this case, is not necessary.
  • the signal (91) delivered by the bottle and the signal (851) delivered by the beam not having reached the bottle make it possible to distinguish between the three materials which are PVC, PET, HDPE. Indeed, the PET depolarizes the light and the signals delivered by the camera (86) representative of the beams (91, 851) will contain information.
  • the PVC which does not depolarize the light will be detected by the camera (86) by the fact that the signals corresponding to the beam (851) and to the beam (91) will be without information and identical. Finally the HDPE will be detected by the fact that the beam signal (91) will be very strong and the beam signal (851) will be absent.
  • the cameras used are matrix CCD cameras comprising a matrix network of 500 x 700 points and the digital output signals of which will be analyzed by the neural analyzer (870) to define, for each object passing through each analysis station, a set of information after processing defined in a hyperspace with 256 dimensions representative of the object analyzed by the station. With each object analyzed, the neural analyzer will associate an area of influence in this hyperspace.
  • the neural analyzer (870) contains in its memory a table associating, with each of the information recorded by a detection station in the neural analyzer, during a learning phase during the passage of an object, the correspondence with a material name. This table is filled during a learning phase which we will describe later. This information therefore allows the neural analyzer (870) to deliver to the computer (877), via the links (872), an analysis result for each sample passing in front of a station. This analysis result is stored in the computer memory (877) and a decision grid (8772) allows it thereafter to decide whether the sample (n) corresponds to PET, PVC, HDPE, or if it must be ironed in the analysis area.
  • the decision grid (8772) can correspond to the table below in which ST1 identifies the signals supplied by the camera (81), ST2 the signals supplied by the camera (86), ST3 the signals supplied by a third detection station which could be a station using infrared light as a light source and a third camera.
  • Information I stands for Uncertain, V for True and X for Indeterminate.
  • the neural analyzer will therefore define for each sample passing through the successive stations, information which will be transmitted to the computer and analyzed by it to provide a result R according to the decision grid (8772) below.
  • the computer will decide when passing the sample given in front of one of the tanks (7a, 7b, 7c, 7d) of the ejection in the appropriate bin.
  • the container (7a) could be assigned to the PET, the HDPE container (7b), PVC (7c) and ironing (7d) in analysis.
  • the machine thus defined, makes it possible to analyze the bottles with the success rate mentioned above at a rate higher than 3 second bottles.
  • the position of the bottles being defined by the pallets, cameras and light sources are triggered with precision taking into account the speed of movement of the pallets (62), so that the same areas are analyzed on each of the bottles passing in front of each station.
  • the interface software (8771) interpreting the signals from the interactive device (875) associated with application software will allow the display on the monitor (876) of the computer (877) of a menu comprising several codes for defining the materials to be sorted.
  • the first line of the menu (8761) may mention PVC, the second line (8762) PET, the third line (8763) HDPE.
  • the neural analyzer When a product sample (9) is presented in front of a station, for example the first station, the neural analyzer generates a first series of information (INF1).
  • the application program triggers the display of the menu, as soon as it receives a stimulus from the neural analyzer, so that the installer can, through interactive device (875), select, on the screen (876) displaying the menu, one of the components of this menu.
  • the user brings, for example, help mouse (875), a selection rectangle shown in dotted lines (8764) or a highlight on the component to be selected displayed on the screen (876).
  • help mouse 875
  • the user or the installer validates his selection by an action on the device interactive, for example, by pressing the second mouse button (8752) (875).
  • This validation information causes the establishment of a link between the information (INF1) and the code corresponding to the selected subject and memorization in the couple's neural analyzer (8701) information (INF1), material (MAT1).
  • the installer will proceed in the same way and will thus allow memorization in the memory of the neural analyzer of a table (8701) associating a plurality information stored in hyperspace to information concerning the type of material of the product. So the neural analyzer can issue, for each sample passing in front of each station, a information defining if the type of material of the product has been identified with certainty or with some uncertainty or if none of the information stored in one of the hyperspaces does not correspond to the information supplied by the camera of the station concerned.
  • the neural analyzer thanks to its learning system, allows to overcome the need to define predetermined thresholds in advance and to the ability to learn about the actual waste to be sorted.
  • the interactive device (875) can be of any type other than a mouse and the associated programming interface will correspond to the type of device interactive used. So we could just as easily use a touch screen or a luminous pencil or quite simply, a keyboard to allow the selection on the menu of the material corresponding to the products analyzed.
  • FIG. 1E Another embodiment of the queuing system cannot be advantageously constituted, as shown in FIG. 1E, by a rotary plate (12) whose outer periphery is slightly frustoconical (121) and the inclination of the axis of rotation of the assembly is calculated so to make the frustoconical part (121) tangent to the support surface (64) on which objects such as queued bottles are each pushed by a pallet (62).
  • the bottle supply system is completed by a peripheral belt (11) which is fixed relative to the turntable (12) and open to the highest part of the turntable rotating, so as to allow communication with the surface of sliding (64), at the point of tangency between the plate and the surface of slip.
  • the hook-shaped belt (11) is completed for the part located between the plate and the sliding surface (64) in the direction clockwise rotation of the plate, by a plate (111) allowing to plug this space, so as to avoid the fall of the bottles which would not have tilted on the sliding plate (64).
  • the bottles are poured in loose on the turntable and position tangentially along the belt (11) and are entrained by the conical surface (121), which is coated a slightly rough coating, favoring the training of bottles by this part.
  • the speed of rotation corresponds to the speed linear movement of the pallets (62) and thus, a new bottle present each time a new palette arrives at the point of tangency.
  • the bottles, pushed by the pallets (62) are brought to the detection station (87) which is equipped, as we saw previously, by one or more detection devices with neural analysis.
  • the area of sorting allows the bottles to be evacuated to containers as in the variant of Figure 1A.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Sorting Of Articles (AREA)
  • Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)
EP97401786A 1996-08-06 1997-07-24 Einrichtung zum Sortieren von Kunststoffflaschen und mit dieser durchgeführtes Verfahren Withdrawn EP0824042A1 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR9609908A FR2752178B1 (fr) 1996-08-06 1996-08-06 Machine de tri de bouteilles plastiques et procede mis en oeuvre par la machine
FR9609908 1996-08-06

Publications (1)

Publication Number Publication Date
EP0824042A1 true EP0824042A1 (de) 1998-02-18

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EP97401786A Withdrawn EP0824042A1 (de) 1996-08-06 1997-07-24 Einrichtung zum Sortieren von Kunststoffflaschen und mit dieser durchgeführtes Verfahren

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EP (1) EP0824042A1 (de)
JP (1) JPH1085676A (de)
FR (1) FR2752178B1 (de)

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CN102580931A (zh) * 2012-03-30 2012-07-18 山东丽鹏股份有限公司 直筒瓶盖自动分选器
CN103331269A (zh) * 2013-07-03 2013-10-02 青岛农业大学 种子分拣系统
CN106226117A (zh) * 2016-07-19 2016-12-14 中玉金标记（北京）生物技术股份有限公司 采样切割装置及种子自动切片采样设备
CN106217432A (zh) * 2016-07-19 2016-12-14 中玉金标记（北京）生物技术股份有限公司 分拣装置及种子自动切片采样设备
CN107159591A (zh) * 2017-06-26 2017-09-15 宁波华辉磁业有限公司 一种磁铁外观视觉检测装置
WO2019023545A3 (en) * 2017-07-28 2019-03-07 AMP Robotics Corporation SYSTEMS AND METHODS FOR SORTING RECYCLABLE ELEMENTS AND OTHER MATERIALS
WO2019056102A1 (en) * 2017-09-19 2019-03-28 Intuitive Robotics, Inc. SYSTEMS AND METHODS FOR DETECTION AND RECOGNITION OF WASTE ARTICLES
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EP0111877A1 (de) * 1982-12-21 1984-06-27 ILLYCAFFE S.p.A. Verfahren zum Sortieren von körnigem Material und Maschine zur Ausführung dieses Verfahrens
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Cited By (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102580931A (zh) * 2012-03-30 2012-07-18 山东丽鹏股份有限公司 直筒瓶盖自动分选器
CN102580931B (zh) * 2012-03-30 2013-04-24 山东丽鹏股份有限公司 直筒瓶盖自动分选器
CN103331269A (zh) * 2013-07-03 2013-10-02 青岛农业大学 种子分拣系统
CN106226117A (zh) * 2016-07-19 2016-12-14 中玉金标记（北京）生物技术股份有限公司 采样切割装置及种子自动切片采样设备
CN106217432A (zh) * 2016-07-19 2016-12-14 中玉金标记（北京）生物技术股份有限公司 分拣装置及种子自动切片采样设备
CN106217432B (zh) * 2016-07-19 2018-07-17 中玉金标记（北京）生物技术股份有限公司 分拣装置及种子自动切片采样设备
CN106226117B (zh) * 2016-07-19 2018-08-14 中玉金标记（北京）生物技术股份有限公司 采样切割装置及种子自动切片采样设备
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FR2752178A1 (fr) 1998-02-13
FR2752178B1 (fr) 1998-10-09
JPH1085676A (ja) 1998-04-07

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