EP0775533A2 - Méthode de tri - Google Patents

Méthode de tri Download PDF

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Publication number
EP0775533A2
EP0775533A2 EP96118241A EP96118241A EP0775533A2 EP 0775533 A2 EP0775533 A2 EP 0775533A2 EP 96118241 A EP96118241 A EP 96118241A EP 96118241 A EP96118241 A EP 96118241A EP 0775533 A2 EP0775533 A2 EP 0775533A2
Authority
EP
European Patent Office
Prior art keywords
sorting
measured values
bottles
properties
objects
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Withdrawn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
EP96118241A
Other languages
German (de)
English (en)
Other versions
EP0775533A3 (fr
Inventor
Martin Rosatzin
Fernando Alvarez
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.)
Elpatronic AG
Original Assignee
Elpatronic AG
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 Elpatronic AG filed Critical Elpatronic AG
Publication of EP0775533A2 publication Critical patent/EP0775533A2/fr
Publication of EP0775533A3 publication Critical patent/EP0775533A3/fr
Withdrawn legal-status Critical Current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

Definitions

  • the invention relates to a method for sorting objects in at least two sorting classes on the basis of a plurality of properties determined on the objects by at least one test device.
  • the invention further relates to a device for carrying out the method and an application of the method.
  • the problem can arise in a wide variety of applications that objects have to be sorted based on their properties.
  • objects have to be sorted based on their properties.
  • properties are checked for which the measurement result can vary in a variety of ways, and if the decision on sorting must also be made quickly, e.g. because many items are generated per unit of time, the mechanical effort for checking and sorting is very high.
  • the testing of reusable beverage bottles can be cited when they return. It is determined by test equipment whether there is an impermissible contamination in the bottle, for which purpose the mass spectrum of a gas sample from each bottle is determined. A corresponding method and a device for this are known from EP-A-0 579 952.
  • a detector for polyaromatic hydrocarbons can be used, for example, and the color spectrum of residual liquid in the bottle can also be determined.
  • Other test facilities check, for example, the height of the bottle, the presence of a lid, the presence of a leak, the presence of permissible labels, etc.
  • a large number of measured values are available as spectra or individual measured values.
  • the individual measured values can be integrated into the spectra, for example in order to obtain a uniform measurement format for the evaluation.
  • the sorting decision must now be made as to whether the respective bottle is intended as a "good" bottle for refilling or whether it is to be discarded as a "bad” bottle.
  • more than two sorting criteria are also possible, for example the sorting out of bottles that have to be checked again or further and are therefore not yet definitely sorted as good or bad.
  • the invention has for its object to provide a sorting method of the type mentioned, which can be carried out quickly and with relatively little effort, and which brings good sorting results, i.e. the class of the bad bottle should be recorded as completely as possible, and as few as possible wrong bottles should be wrongly classified as bad.
  • This object is achieved in that the properties of a large number of objects are first determined by a test device before the sorting operation and the measured values determined are classified and stored by an evaluation device according to the frequency of occurrence, and that subsequently in the actual sorting operation by a Testing device the properties of the individual objects to be sorted are determined and the sorting decision is made according to whether or not the properties determined on the respective object have occurred with a large number of objects with a predetermined frequency and resemblance.
  • a "library" which records the properties in an orderly manner.
  • the same test arrangement can be used to determine the properties or the measured values of the objects can be used, which also carries out the sorting later, or another test device can be used, but which records the same measured values as the test device used later for sorting.
  • the library created in this way then provides the basis for the actual sorting of objects.
  • the objects to be sorted are checked during normal operation of the test facility and the measured values or properties of the objects are compared with the library.
  • the sort criterion is then whether the library already has the same entry - or a sufficiently similar entry - and if so, with what frequency. If the entry is present with a predetermined sufficient frequency, the object falls under a first sorting class, otherwise into a second sorting class. Of course, a distinction could also be made between several predetermined frequency ranges, which results in more than two sorting classes.
  • the criterion for the actual sorting is the frequency with which the same or a sufficiently similar combination of measured values has already occurred when the library was created.
  • the library created with the test devices mentioned will contain, with great frequency, measurement values which correspond to a conventional bottle and one of the usual drinks found in the bottle, for example orange juice; measured values or entries will be available with a low frequency, which indicate an impermissible bottle or impermissible contamination, for example the presence of gasoline.
  • the device for performing the method is characterized by the features of claim 4.
  • a preferred application of the method is defined in claim 5.
  • the method is described below using a special type of container, namely using reusable PET bottles, in which the method can be used particularly advantageously, since a large number of measurement values are obtained and in a short time, for example in 100 ms with a bottle throughput of 600 bottles / Minute a sorting decision has to be made.
  • the method can be applied to any other object.
  • EP-A-0 579 952 describes how gas samples are taken from bottles conveyed in rapid cadence on a conveyor and are fed to a mass spectrometer for testing.
  • other tests can also be carried out.
  • the color spectrum of the residual liquid in the container can be determined.
  • container properties such as tightness, container height etc. can be checked. The measurement results obtained in this way by at least one test device are now used as the basis for the assessment in order to sort the containers into several groups, for example into reusable, good bottles, into restrictedly usable and no longer usable, bad bottles.
  • the sorting process is now carried out in the special manner claimed.
  • a collection of the bottle properties is first carried out on a large sample of bottles.
  • This collection can be called a library and it is created before the sorting operation.
  • the library can be created during normal operation of a bottle inspection system, which sorts the bottles based on previous sorting algorithms.
  • the library can also be created in a special bottle run. In any case, the statistics of all bottles, ie the total bottle flow, are mapped with sufficient accuracy from a large sample, which may include 10,000 bottles, for example, by dividing the bottles into different classes with corresponding percentages based on the measurement.
  • FIG. 1 shows a schematic representation of the frequency distribution of the measured value combinations when the sample was taken. The frequency of a specific combination of measured values is plotted on the ordinate. As can be seen in FIG. 1, a curve 1 of the frequency distribution of the measured value combinations results.
  • the different combinations of measured values can be divided into different classes, which is shown in the example shown on the abscissa with classes 1 to 19. In class 10, for example, there may be combinations of measured values whose mass spectrum indicates a drink, for example orange juice and whose color spectrum corresponds to that of orange juice and in which the bottles have no leak and are of the correct height.
  • This library forms the basis for sorting the bottles in the actual sorting operation.
  • the library can be set up while a bottle inspection system is in operation.
  • the library can be periodically or randomly adjusted in operation or continuously adapted to the bottle flow by taking a sample of the current bottle flow, which influences the frequency distribution of the library.
  • the most similar library entry or the most similar class of classes 1 to 19 is now assigned to each set of measurements or each combination of measured values on an object by means of a comparison device, if a class with a sufficiently exact match can be found at all. If such a class is found, the corresponding sorting criterion is assigned to the object or bottle. If, therefore, an intact bottle occurs in the actual sorting operation, the measurement value combination of which points to orange juice, the bottle is assigned to this class if there is sufficient agreement with the measurement value combination of class 10. In this way, the associated sorting criterion "good" is assigned to the bottle, since all bottles whose frequency corresponds to class 10 are to be rated as good.
  • bottles with a frequency of this type occur in returnable returnable bottles.
  • This bottle can, for example, have a combination of measured values that can be found in class 2.
  • This bottle is discarded from the reusable circulation, since the low frequency of the combination of measured values it receives statistically suggests that there is a bottle to be assessed as bad. Bottles that cannot be assigned to any class are also eliminated as bad bottles.
  • reference measurement spectra are stored in a data file and used as a reference library, and together with each measurement spectrum, additional information is also stored that defines the sorting criteria, e.g. "GOOD", "SORT” or "BAD” for good bottles to be sorted and rejected.
  • a reference measurement is also stored in this reference library, which compensates for the changing environmental influences (background signals).
  • the library can remain unchanged, or periodically resp. continuously adapted to the statistics of the object flow (bottle flow). With self-adaptive libraries, avoiding error propagation is of particular importance (library stability).
  • the setup and adaptation of a library is preferably self-learning.
  • the number of possible ingredients in containers is extremely diverse and is additionally increased by a wide variety of environmental influences (freezing, mold, fermentation, foreign substances, etc.). For this reason, the construction of individual measurement spectra is only possible via empirical measurement. Since a large number of measurement spectra is required for representative statistics, which cannot be handled manually, the entire or a defined, limited selection of the entirety of all measurement spectra is stored and arranged according to statistical criteria in order to set up or adapt a library in a self-learning process. Static information and other criteria allow manual or automatic assignment of the measurement spectra to one of the sorting criteria. Known information on the statistical distribution of the various container properties is used for this assignment. Class 3 is assigned to the "BAD" sorting criterion on the basis of such criteria.
  • the measured values must be evaluated during the actual sorting.
  • To characterize a Container or its content its measurement spectrum is compared with the content of the library or offset as required and then assigned to a specific library entry (positive recognition) and assigned to its corresponding sort class. A decision is made about this assignment by a computer and the container is sorted accordingly.
  • the library data can be converted into a "look-up table”.
  • the library content is shown in a multidimensional "map", which shows the statistical distribution of the objects. In this case, not all data need to be checked when accessing the library. Instead, it is sufficient to check the density distribution in the "environment" of the individual measurement to be tested in order to be able to make a relevant statement about the individual object.
  • the advantage is increased speed due to shorter computing times.
  • the "unknown limit” defines the properties of a container as "unknown", which means that different sorting criteria can be applied.
  • FIG. 2 shows a roughly schematic test device for carrying out the method.
  • several test devices are provided, which transmit measured values about the condition of the object to an evaluation device.
  • a first test device 3 is shown, to which the objects 8 to be tested are conveyed past by means of a conveyor system 9.
  • the test device 3 can be, for example, a test device for taking and analyzing gas samples from containers, as is shown in EP-A-0 579 952.
  • FIG. 2 shows only one further test device 4, for example a PAK detector, but of course several test devices can also be provided, as already mentioned above.
  • the test devices 3, 4 deliver their measurement data either as raw data or already in a processed form to a control device 5. This is generally programmed by a corresponding one Calculator formed.
  • containers 8 are the containers of the sample.
  • the control device creates the library with the sorting criteria as an evaluation device and stores it in a storage medium 6.
  • the control device 5 also controls a sorting element 7 which, based on its measured properties, sorts the containers out of the flow or leaves them in the flow.
  • the data for the creation of the individual library can be collected during an operation in which the items are sorted using a standard library.
  • the device can carry out the sorting according to the invention on the basis of this library, which permits a sharper sorting than that with a standard library. This can drastically reduce the false detection of good bottles as bad bottles (incorrect ejection), while the false detection of bad bottles as good bottles is still suppressed.
  • the control device 5 then works as a comparison device for comparing the current measured values with the library.
  • the library is determined either with the same test device which also carries out the later sorting, or the test device for holding the library is a different test device than the subsequent sorting test device. In this case, the library data are transferred from the first test device to the second test device.

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  • Sorting Of Articles (AREA)
  • Testing Or Calibration Of Command Recording Devices (AREA)
EP96118241A 1995-11-24 1996-11-14 Méthode de tri Withdrawn EP0775533A3 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CH3335/95 1995-11-24
CH333595 1995-11-24

Publications (2)

Publication Number Publication Date
EP0775533A2 true EP0775533A2 (fr) 1997-05-28
EP0775533A3 EP0775533A3 (fr) 1998-06-17

Family

ID=4253754

Family Applications (1)

Application Number Title Priority Date Filing Date
EP96118241A Withdrawn EP0775533A3 (fr) 1995-11-24 1996-11-14 Méthode de tri

Country Status (4)

Country Link
EP (1) EP0775533A3 (fr)
AR (1) AR004340A1 (fr)
BR (1) BR9605701A (fr)
CA (1) CA2191120A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101311730B (zh) * 2007-05-25 2013-01-23 先进自动器材有限公司 用于测试和分类电子元件的系统
CN113825709A (zh) * 2019-05-02 2021-12-21 奥卡多创新有限公司 容器成像设备和方法

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0579952A1 (fr) 1992-07-09 1994-01-26 Elpatronic Ag Procédé et dispositif pour contrôler l'état de propieté de bouteilles

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
IT1205622B (it) * 1982-12-21 1989-03-23 Illycaffe Spa Procedimento per effettuare una selezione in un materiale granuliforme e macchina per attuare il procedimento
US5085325A (en) * 1988-03-08 1992-02-04 Simco/Ramic Corporation Color sorting system and method
EP0342354A3 (fr) * 1988-04-15 1992-01-08 Tecnostral S.A. Industria E Tecnologia Dispositif de trí selon la couleur
DE4210157C2 (de) * 1992-03-27 1994-12-22 Bodenseewerk Geraetetech Verfahren zum Sortieren von Glasbruch
DE4345106C2 (de) * 1993-12-28 1995-11-23 Reemtsma H F & Ph Verfahren zum optischen Sortieren von Schüttgut

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0579952A1 (fr) 1992-07-09 1994-01-26 Elpatronic Ag Procédé et dispositif pour contrôler l'état de propieté de bouteilles

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101311730B (zh) * 2007-05-25 2013-01-23 先进自动器材有限公司 用于测试和分类电子元件的系统
CN113825709A (zh) * 2019-05-02 2021-12-21 奥卡多创新有限公司 容器成像设备和方法
CN113825709B (zh) * 2019-05-02 2024-05-28 奥卡多创新有限公司 容器成像设备和方法

Also Published As

Publication number Publication date
BR9605701A (pt) 1998-08-18
CA2191120A1 (fr) 1997-05-25
MX9605774A (es) 1997-10-31
AR004340A1 (es) 1998-11-04
EP0775533A3 (fr) 1998-06-17

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