EP0824735B1 - Device and process for processing sheet articles such as bank notes - Google Patents

Device and process for processing sheet articles such as bank notes Download PDF

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Publication number
EP0824735B1
EP0824735B1 EP96919717A EP96919717A EP0824735B1 EP 0824735 B1 EP0824735 B1 EP 0824735B1 EP 96919717 A EP96919717 A EP 96919717A EP 96919717 A EP96919717 A EP 96919717A EP 0824735 B1 EP0824735 B1 EP 0824735B1
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EP
European Patent Office
Prior art keywords
unit
data
sheet
class
sensor
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.)
Expired - Lifetime
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EP96919717A
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German (de)
French (fr)
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EP0824735A2 (en
Inventor
Paul Dr. Smith
Walter Herrmann
Bernd Dr. Wunderer
Dieter Stein
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.)
Giesecke and Devrient GmbH
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Giesecke and Devrient GmbH
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Publication date
Application filed by Giesecke and Devrient GmbH filed Critical Giesecke and Devrient GmbH
Priority to EP01120428A priority Critical patent/EP1168252A3/en
Publication of EP0824735A2 publication Critical patent/EP0824735A2/en
Application granted granted Critical
Publication of EP0824735B1 publication Critical patent/EP0824735B1/en
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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
    • B07C5/36—Sorting apparatus characterised by the means used for distribution
    • B07C5/361—Processing or control devices therefor, e.g. escort memory
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D11/00—Devices accepting coins; Devices accepting, dispensing, sorting or counting valuable papers
    • G07D11/20—Controlling or monitoring the operation of devices; Data handling
    • G07D11/22—Means for sensing or detection
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D11/00—Devices accepting coins; Devices accepting, dispensing, sorting or counting valuable papers
    • G07D11/20—Controlling or monitoring the operation of devices; Data handling
    • G07D11/22—Means for sensing or detection
    • G07D11/235—Means for sensing or detection for monitoring or indicating operating conditions; for detecting malfunctions
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D11/00—Devices accepting coins; Devices accepting, dispensing, sorting or counting valuable papers
    • G07D11/20—Controlling or monitoring the operation of devices; Data handling
    • G07D11/22—Means for sensing or detection
    • G07D11/235—Means for sensing or detection for monitoring or indicating operating conditions; for detecting malfunctions
    • G07D11/237—Means for sensing or detection for monitoring or indicating operating conditions; for detecting malfunctions for detecting transport malfunctions, e.g. jams or misfeeds
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D11/00—Devices accepting coins; Devices accepting, dispensing, sorting or counting valuable papers
    • G07D11/40—Device architecture, e.g. modular construction
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D11/00—Devices accepting coins; Devices accepting, dispensing, sorting or counting valuable papers
    • G07D11/50—Sorting or counting valuable papers
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S209/00—Classifying, separating, and assorting solids
    • Y10S209/938—Illuminating means facilitating visual inspection

Definitions

  • the invention relates to a device and a method for processing of sheet material, such as. B. banknotes.
  • DE 27 60166 shows such a device, which consists of different units is constructed. In a separator, this is in a stack Sheet by sheet, sheet by sheet, and transferred to a transport route, which transports the separated sheet material through the device.
  • Each sensor unit detects and records certain features of the sheet material summarizes a measurement result.
  • the structure of the sensor units used here is shown in DE-PS 27 60 165.
  • Each sensor unit has one Sensor that detects certain characteristics of the sheet material and converted into an electrical signal. This signal is in a signal processing stage reshaped. In general, the implementation takes place here of the mostly analog signal in digital measurement data instead.
  • the measurement data are then finally in an evaluation unit of the sensor unit Changed yes / no statement. This then forms the measurement result of the sensor unit and is stored in a central memory.
  • the central memory is used as a connection for data exchange between the Units of the device used. All units can access it and write or read the data necessary to process the sheet material are. There is one for several sheets in the central memory Record saved.
  • the target units can, for example, stackers for stacking the sheet material or shredder to destroy the sheet material.
  • the destinations for that Corresponding sheet material is stored in the central store. Based The stored target unit is the sheet material from the transport unit appropriately managed and filed. After the sheet material has been transported the transport unit writes positive or negative information to the target unit via the processing exit to the central memory.
  • the machining process in the device is carried out by means of a control unit controlled.
  • This also has access to the central memory and can be based on the information stored there monitor the machining process and log.
  • the control unit also serves the units of the device depending on one set by the operator Initialize operating mode. This includes, for example, storage the correct decision table for the selected operating mode in the central evaluation unit.
  • each sensor unit can only measure its result derive from the measurement data of the sheet material recorded by her.
  • the object of the invention is a device and to propose a method for processing sheet material which enables the To improve the quality of the derivation of a measurement result of the sensor units.
  • the basic idea of the invention consists essentially in that Deriving a measurement result from a sensor unit data from other sensor units to use on the appropriate sheet material.
  • At least one sensor unit is provided with a memory in which data records multiple sheets can be managed.
  • Areas are provided in which data from at least one other sensor unit can be saved.
  • the advantage of the invention is that the sensor unit has data from other sensor units which they have when deriving their own measurement result can take into account. Knowing this data is the sensor unit able to get your measurement result faster and more accurately from this Derive data.
  • the sensor unit preferably has a measuring unit and an evaluation unit , with the memory of the sensor unit in the evaluation unit is provided. Furthermore, the measurement results of the sensor unit are not limited to a yes / no statement, but with a higher information content fitted.
  • the measurement results can be, for example, the length or the width of the sheet in mm, a measure of the pollution or the correspondence of the printed image with a reference image, the distance of a metal thread from the leading edge of the sheet, an identification number for the type or location of the sheet material or the like.
  • Fig. 1 shows a schematic diagram of an embodiment of the invention.
  • the sheet material is separated from a stack of sheets in a separating unit Sheet isolated and passed to a transport route that the sheets transported by the device and controlled by a transport unit 30 becomes.
  • the transport route is divided into individual sections, the decentralized sub-units 30.1 - 30.M of the transport unit 30 can be controlled.
  • each sheet is assigned an identification ID, on the basis of which the sheet is clearly recognized by the units of the device becomes.
  • the data required to process a sheet are used the identification ID of the sheet exchanged via a connection 100.
  • the connection 100 connects both the subunits 30.1 - 30.M, as well as a central evaluation unit 10, several sensor units 20.1 - 20.N and a control unit 40 with each other.
  • the sensor units 20.1 - 20.N each consist of a measuring unit 21.1 - 21.N and an evaluation unit 22.1 - 22.N together.
  • Each measuring unit 21.n has a transducer, the certain characteristics of the sheet detected and converted into electrical signals. These electrical signals will be then converted into digital measurement data and can optionally before Further processing can be standardized and / or transformed.
  • the evaluation unit 22.n of the sensor 20.n receives the measurement data of the measuring unit 21.n and derives a measurement result using the measurement data.
  • a memory is provided in at least one evaluation unit 22n Content is shown in Fig. 2.
  • the evaluation unit was used here as an example 22.2 chosen.
  • Several data records can be stored in the memory of the evaluation unit 22.2 to get managed.
  • Each record is a sheet of a particular one Identification ID assigned.
  • the memory shown here is in the Able to manage a number L of records.
  • Each data record has an area for external data ED. Be in it either measurement data MD or measurement results ME of other sensor units saved. 2 shows, for example, the measurement data MD of the sensor unit 20.3 and the measurement results of the sensor unit 20.1 in each data set saved.
  • the name proceed analogously.
  • the evaluation unit 22.2 In the memory of the evaluation unit 22.2, those of the measurement data MD supplied to the measuring unit 21.2 are stored for each sheet. From the own measurement data MD and the external data ED of a data record leads the evaluation unit 22.2 a corresponding measurement result for each sheet ME, which is optionally saved in the corresponding data record can be.
  • the measurement result is compared with the corresponding Identification ID of the sheet written on the data line 100.
  • the measurement result can now be read and read by other sensor units if required be stored in the memory of the evaluation unit of this sensor unit. Is the knowledge of certain measurement data of a sensor for deriving the measurement result another sensor unit necessary, this must also be the write the corresponding measurement data on the data line 100 so that they are the other sensor unit can read. Alternatively, writing the Measurement data only after receiving a corresponding signal from another sensor unit.
  • the device has a central evaluation unit 10 with a Memory whose content is shown in Fig. 3.
  • the central evaluation unit 10 reads the measurement results of all sensor units 20.1 - 20.N from the data line 100 and stores this under the identification ID of the corresponding Leaf.
  • the central evaluation unit 10 guides from the measurement results a sorting class KL for the corresponding sheet material and writes the Identification ID and the associated sorting class KL on the data line 100.
  • the sorting class KL can be stored in the memory under the corresponding Identification of the sheet can be saved.
  • the sorting class KL is evaluated by the subunits of the transport unit, that control the transport of the sheet to the target unit. Is the corresponding one Subunit 30.m not responsible for processing the sheet, this is forwarded to the subsequent subunit 30.m + 1. in the otherwise the sheet becomes the corresponding manipulators of the subunit 30.m directed and edited.
  • the processing unit After processing the sheet material the processing unit makes a corresponding positive or negative Information about the completion of the processing on the data line 100 written. This information is, for example, from the control unit 40 read and used in the logging of the machining process.
  • each subunit 30.m error messages on the data line write if, for example, there is a sheet jam in the transport system the subunit 30.m comes.
  • These error messages can be from others Units of the device interpreted and appropriate measures be initiated.
  • the sub-units 30.m are designed so that they the electrical and control mechanical functions of the transport route. For this count among other things the drive of the transport route, the switching of the Turnouts within the transport route, measuring the position of the sheet material by means of light barriers etc. Furthermore, the sub-units 30.m but also the control of special electrical or mechanical manipulators perform within the units of the device. That counts for example the control of the singling components, the stacking wheels and the shredder rollers etc.
  • the control unit 40 serves to control and log the machining processes of leaves. It is able to communicate via data line 100 Send control information by the individual units accordingly be interpreted. By means of such control information for example, the device in a processing status selected by the operator to be brought.
  • the control unit 40 can also store the data special programs or reference data from the control unit 40 in initiate the other units of the device via data line 100. For this purpose, 40 mass memories are available on the control unit, in which this data is managed.
  • Control unit 40 monitor the processing of each sheet and log. During the actual processing of the sheet material is the function of the control unit only on listening to the data line 100 limited.
  • the data line 100 is designed as a data bus.
  • A is preferred CAN bus used. This is for so-called real-time applications such as they are mainly present here, particularly well suited.
  • data lines 101 and 102 are provided parallel to data line 100 be so that the data line 100 is relieved.
  • the data line 101 can also be implemented using a CAN bus and serves to exchange data between the sensor units 20.1 - 20.N as well as the central evaluation unit 10. This is particularly so then makes sense if there are many between the sensor units 20.n. Measurement data are exchanged, which often have a high data volume.
  • the data line 102 is specifically used by the control unit 40 for so-called Non-real-time applications used. You can use this, for example, at Initialization of the device in a certain operating state programs or larger-scale reference data in the sensor units 20 or the central evaluation unit 10 can be written. On a connection to the sub-units 30.m can also be dispensed with, since the amounts of data transferred there are generally small.
  • Deriving the sorting class of a sheet from the measurement results of the Sensor units can be freely configurable, for example Tables and / or matrices are performed in a memory the central evaluation unit 10 are managed.
  • Tables and / or matrices are performed in a memory the central evaluation unit 10 are managed.
  • continuous measurement results are mapped to classes. discrete Measurement results are assigned directly to a class. Individual classes become a property of the sheet with different characteristics summarized.
  • a rule matrix can be used to select any, but fixed Combinations of different forms of a set of properties be assigned to a sort class.
  • Fig. 4 shows a flow chart of a first embodiment of the Method according to the invention for processing sheet material, here specifically Paper money.
  • the measurement data MD of the banknote are from the sensors 20.n detected. Using these measurement data MD, measurement results ME derived from the banknote and stored in the evaluation unit 10 according to FIG. 3.
  • the measurement results ME are initially mapped to discrete classes.
  • An example of such a mapping is shown in FIG. 5.
  • the measurement result should represent the area of the banknote in mm 2 which is covered by spots. If, for example, 140 mm 2 is determined as the measurement result in a first measurement M 1 , this measurement result is mapped to the class with the class identifier 4.
  • the number of classes and the location of the class boundaries can be configured as desired.
  • Classes 0 to 5 can be summarized as "stains”. Each class thus represents an expression of the property "stains”.
  • the individual classes are often also provided with verbal markings, such as "very little", “little", “much” etc.
  • a property vector is first formed from the classes of all properties. 6 four class vectors V 1 to V 4 are shown by way of example. In each property the class is marked that corresponds to the measurement result of the banknote. With the property "stains” the measurement result of the leaf material belonging to the class vector V 1 is z. B. in the class "little", while the measurement result of the property "dog ears” in the class "very little". The class vector thus classifies the characteristics of all the properties of a banknote.
  • the rule matrix consists of a number of rules, here with the digits 1 to 5 are designated.
  • Each rule consists of a rule vector, the is formed from the classes of all properties analogously to the class vector. In contrast to the class vector, it is possible that several classes of a property, such as the property "pollution" in rules 1 to 5.
  • Each of rules 1 to 5 is a sort class assigned here with the respective sorting destination "Stacker 1", “Stacker 2", etc. is designated. In general, there can also be several rules the same sort class can be assigned.
  • the markings of the class vector e.g. B. V 1
  • the sorting class which is assigned to the first rule vector, which is marked in all classes of the class vector, is assigned to the sheet material as a sorting class. If the markings of none of the rule vectors match all the markings of the class vector, the sheet material is assigned any, but firmly selected sorting class.
  • the sheet material for class vector V 2 is given the sorting class "stacker 4".
  • the sorting class "shredder” is assigned to the sheet material for class vector V 3 . Since the marking of no rule vector matches all the markings of the class vector V 4 , this sheet material is assigned any, but firmly selected sorting class which is to be referred to as "reject".
  • the sorting class "Reject" After assigning the sorting class to the sheet material, this is based on the sorting class is transported to the corresponding target unit.
  • the leaves with the sorting class "Reject" are generally in a so-called Reject compartment stacked, where they are then removed from the device by the operator and can be viewed.
  • a security level SL is assigned to each class.
  • each class Hereby can be specified which users are allowed to make changes in this class.
  • the value 3 for the developer, 2 for the supervisor and 1 stand for the operator of the device. So here it is Device operators can use the classes of property “Denomination the banknote "while changing the properties of the group "Security features of the banknote” only changed by the supervisor may be.
  • weights G are explained.
  • security features of the banknote are explained.
  • security thread there are generally a number of others Properties in this group that are here for the sake of clarity not be mentioned.
  • One of the weights of the property "Denomination” is supposed to be here specified minimum weight for the security of a fit banknote be determined.
  • the specified minimum weight of a rule in the "Banknote security features" group for fit banknotes is the maximum of the weights of the marked classes Usually in the "Denomination” property. For rule 1, 2, 4 and 5 results thus a minimum weight for the security of an unfit banknote of 8 and for rule 3 of 3.
  • the sorting class determined with the aid of the rule matrix can in retrospect, again optionally depending on a specific one Condition to be changed. Such a subsequent change can, for example, in the maintenance of the device or in the design the rule matrix can be helpful.
  • the conditions can be derived from the rule matrix, for example the minimum weight MG for a rule in the group "safety features the banknote ". Furthermore, the conditions of Measurement results of the sensors or the class identification of a certain one Depend on the measurement result. In general, all of the evaluation device available data in any combination in one Condition.
  • RND Redirect banknotes statistically.
  • 20% of the banknotes are sorted by the "Shredder" sorting class redirected the sorting class "Reject".
  • Such an approach allows for example, to continuously check the sorting quality of banknotes, by the operator of the device having the sorting class "Reject" redirects banknotes personally. Possibly he can then inspect the class boundaries based on the inspection change certain classes appropriately.
  • FIG. 8 A second embodiment of the inventive method for Processing sheet material is shown in Fig. 8. Again, how already explained for the first embodiment, first measurement data from the sensors 20.n and using these measurement data MD Measurement results derived from ME.
  • the measurement results are here ME mapped to overlapping classes or fuzzified.
  • An example for such a mapping is shown in Fig. 9.
  • the measurement results of the sheet material can have values between Accept 0 and 1.
  • Each property has three overlapping classes assigned. These are the classes for the property “pollution” “strong” with measurement results in the interval from 0 to 0.5, “medium” in the interval from 0 to 1 and “low” in the interval from 0.5 to 1.
  • the classes “strong”, “Medium”, “low” are used as fuzzy classes in the following.
  • Each fuzzy class is assigned a membership function shown in FIG. 9.
  • the number of overlapping fuzzy classes and the shape of the various membership functions can be set arbitrarily.
  • the functionality of the process can be optimized for the respective application.
  • FIG. 9 shows the measurement results of two measurements, M 1 and M 2 , with the membership values resulting from the membership functions.
  • Measurement M 1 is a banknote with little contamination, a relatively large number of dog ears and few stains.
  • the measurement M 2 is more dirty than the measurement M 1 and it has more dog ears. Furthermore, it shows fewer spots than the measurement M 1 .
  • a rule matrix is defined by means of the fuzzy classes, which is shown in FIG. 10.
  • the possible combinations of the individual classes of the properties "pollution”, “dog-ear” and “stains” are plotted in the columns of the rule matrix.
  • the last column of the rule matrix forms a "Sorting" property with three fuzzy classes, which are called “Stacker”, “Shredder” and "Reject”.
  • a rule 1 to 8 is plotted in the rows of the rule matrix, each of which assigns a possible combination of fuzzy classes of the three properties of a fuzzy class to the "sorting" property. Under the respective designation of the fuzzy class, the membership value determined in FIG. 9 to the measurements M 1 and M 2 is given. The determination of the values specified for the fuzzy classes of the "sorting" property is explained below.
  • Rule 1 says, for example, that a banknote with little soiling, many dog ears and little stains of the fuzzy class "Reject" should be assigned to a "Sorting" property.
  • rule 2 a banknote with medium soiling, many dog ears and few stains is assigned to the "sorting" property of the "shredder” fuzzy class, etc.
  • the rule matrix is limited to 8 rules here, since the measurements M 1 and M 2 do not contain any other useful combinations occur. In principle, however, it is not necessary for the rule matrix to contain rules for all possible combinations. It is sufficient if it only contains rules for relevant combinations.
  • each fuzzy class of the "Sorting" property has a corresponding one Membership function assigned.
  • the fuzzy classes of the property resulting from the rules are obtained "Sort" by first, as shown in Fig. 10, the appropriate Membership values of the measurement results within one rule linked and assigns the result of the linking to the sorting.
  • the selection of the lowest membership value selected (framed in each case).
  • 12 shows, for example, the fuzzy class "shredder” of the "sorting” property resulting from the corresponding rules.
  • the membership function of the fuzzy class "Shredder” is usually cut off at the corresponding height according to the result of the link.
  • 12a and 12b show this process for the results of the measurement M 2 of rule 4.
  • rule 4 supplies the value for the measurement M 2 and the fuzzy class "shredder” of the "sorting” property 0.2.
  • the membership function of the fuzzy class "Shredder” is cut off at the value 0.2.
  • the parts of the individual rules thus obtained are linked to one another. For the sake of simplicity, the maximum covered area of the individual partial areas was chosen here as a link.
  • the result of the link is shown in Fig. 12c.
  • a discrete sorting class In a final step, a discrete sorting class must be derived from the resulting fuzzy classes of the "sorting" property or the "sorting” property must be defuzzified.
  • a simple possibility for such a derivation is to assign the sorting class to the sheet material whose fuzzy class has the largest area. In the case of the measurement results M 1 , the sorting class "Reject” would be assigned to the sheet material and the sorting class "Shredder" would be assigned to the sheet material with the measured values M 2 .
  • a more elaborate method for deriving the sorting class from the resulting ones For example, there are fuzzy classes of the "Sorting" property first of all the individual resulting fuzzy classes “stacker", For example, “Shredder”, “Reject” of the "Sorting” property to link by union and from the resulting area the To calculate the location of the center of gravity. By rounding this value up a discrete Sorfier class can be mapped.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Inspection Of Paper Currency And Valuable Securities (AREA)
  • Controlling Sheets Or Webs (AREA)
  • Manufacture Of Macromolecular Shaped Articles (AREA)
  • Treatments Of Macromolecular Shaped Articles (AREA)
  • Basic Packing Technique (AREA)
  • Sheets, Magazines, And Separation Thereof (AREA)
  • Control Of Vending Devices And Auxiliary Devices For Vending Devices (AREA)
  • Making Paper Articles (AREA)

Abstract

The appts. includes a note separating unit, a transport unit, several sensor units, a central processing unit, several target units and a control unit. The sensor units contain both measurement devices (21.n) and processing devices (22.n) for providing measurements for each sheet. Connections are provided between the units for exchange of data. At least one of the sensor units (20.n) contains memory in which a data set is stored. There is a region in the data set in which data from at least one other sensor unit can be stored.

Description

Die Erfindung betrifft eine Vorrichtung und ein Verfahren zur Bearbeitung von Blattgut, wie z. B. Banknoten.The invention relates to a device and a method for processing of sheet material, such as. B. banknotes.

Die DE 27 60166 zeigt eine solche Vorrichtung, die aus verschiedenen Einheiten aufgebaut ist. In einem Vereinzeler wird das in einem Stapel vorliegende Blattgut Blatt für Blatt vereinzelt und an eine Transportstrecke übergeben, die das vereinzelte Blattgut durch die Vorrichtung transportiert.DE 27 60166 shows such a device, which consists of different units is constructed. In a separator, this is in a stack Sheet by sheet, sheet by sheet, and transferred to a transport route, which transports the separated sheet material through the device.

Entlang des Transportweges sind mehrere Sensoreinheiten angebracht, wobei jede Sensoreinheit bestimmte Merkmale des Blattguts detektiert und zu einem Meßergebnis zusammenfaßt. Der Aufbau der hier verwendeten Sensoreinheiten ist in der DE-PS 27 60 165 gezeigt. Jede Sensoreinheit weist einen Meßwertaufnehmer auf, der bestimmte Merkmale des Blattguts erfaßt und in ein elektrisches Signal umwandelt. Dieses Signal wird in einer Signalaufbereitungsstufe umgeformt. Im allgemeinen findet hier die Umsetzung des meist analogen Signals in digitale Meßdaten statt. Die Meßdaten werden dann schließlich in einer Auswerteeinheit der Sensoreinheit zu einer Ja/ Nein-Aussage umgeformt. Diese bildet dann das Meßergebnis der Sensoreinheit und wird in einem Zentralspeicher gespeichert.Several sensor units are attached along the transport path, whereby Each sensor unit detects and records certain features of the sheet material summarizes a measurement result. The structure of the sensor units used here is shown in DE-PS 27 60 165. Each sensor unit has one Sensor that detects certain characteristics of the sheet material and converted into an electrical signal. This signal is in a signal processing stage reshaped. In general, the implementation takes place here of the mostly analog signal in digital measurement data instead. The measurement data are then finally in an evaluation unit of the sensor unit Changed yes / no statement. This then forms the measurement result of the sensor unit and is stored in a central memory.

Der Zentralspeicher wird als Verbindung zum Datenaustausch zwischen den Einheiten der Vorrichtung genutzt. Auf ihn können alle Einheiten zugreifen und die Daten schreiben oder lesen, die zur Bearbeitung des Blattguts notwendig sind. Auf dem Zentralspeicher ist zu mehreren Blättern jeweils ein Datensatz gespeichert.The central memory is used as a connection for data exchange between the Units of the device used. All units can access it and write or read the data necessary to process the sheet material are. There is one for several sheets in the central memory Record saved.

Aus den auf dem Zentralspeicher gespeicherten Meßergebnissen der Sensoreinheiten zu jedem Blattgut wird in einer zentralen Auswerteeinheit zunächst eine Auswerteinformation erstellt. Mittels einer in der Auswerteeinheit gespeicherten Entscheidungstabelle werden aus den Auswerteinformationen die Zieleinheiten für das betreffende Blattgut ermittelt.From the measurement results of the sensor units stored in the central memory for each sheet material is first in a central evaluation unit created an evaluation information. By means of one in the evaluation unit saved decision table are from the evaluation information determined the target units for the sheet material in question.

Die Zieleinheiten können beispielsweise Stapler zur Stapelung des Blattguts oder Shredder zur Vernichtung des Blattguts sein. Die Zieleinheiten für das entsprechende Blattgut werden auf dem Zentralspeicher gespeichert. Anhand der gespeicherten Zieleinheit wird das Blattgut von der Transporteinheit entsprechend geleitet und abgelegt. Nach dem Transport des Blattguts zur Zieleinheit schreibt die Transporteinheit eine positive oder negative Information über den Ausgang der Bearbeitung auf den Zentralspeicher.The target units can, for example, stackers for stacking the sheet material or shredder to destroy the sheet material. The destinations for that Corresponding sheet material is stored in the central store. Based The stored target unit is the sheet material from the transport unit appropriately managed and filed. After the sheet material has been transported the transport unit writes positive or negative information to the target unit via the processing exit to the central memory.

Der Bearbeitungsvorgang in der Vorrichtung wird mittels einer Steuereinheit gesteuert. Auch diese hat Zugriff auf den Zentralspeicher und kann anhand der dort abgelegten Informationen den Bearbeitungsvorgang überwachen und protokollieren. Weiterhin dient die Steuereinheit dazu, die Einheiten der Vorrichtung abhängig von einem durch den Bediener eingestellten Betriebsmodus zu initialisieren. Hierzu gehört beispielsweise die Speicherung der für den gewählten Betriebsmodus korrekten Entscheidungstabelle in der zentralen Auswerteeinheit.The machining process in the device is carried out by means of a control unit controlled. This also has access to the central memory and can be based on the information stored there monitor the machining process and log. The control unit also serves the units of the device depending on one set by the operator Initialize operating mode. This includes, for example, storage the correct decision table for the selected operating mode in the central evaluation unit.

Bei dem bekannten System kann jede Sensoreinheit ihr Meßergebnis lediglich aus den von ihr aufgenommenen Meßdaten des Blattgutes ableiten.In the known system, each sensor unit can only measure its result derive from the measurement data of the sheet material recorded by her.

Ausgehend davon liegt der Erfindung die Aufgabe zugrunde, eine Vorrichtung und ein Verfahren zur Bearbeitung von Blattgut vorzuschlagen, die es ermöglichen, die Qualität der Ableitung eines Meßergebnisses der Sensoreinheiten zu verbessern.Proceeding from this, the object of the invention is a device and to propose a method for processing sheet material which enables the To improve the quality of the derivation of a measurement result of the sensor units.

Diese Aufgabe wird durch die Merkmale der Ansprüche 1 und 16 gelöst. This object is solved by the features of claims 1 and 16.

Der Grundgedanke der Erfindung besteht im wesentlichen darin, bei der Ableitung eines Meßergebnisses einer Sensoreinheit Daten anderer Sensoreinheiten über das entsprechende Blattgut zu verwenden. Hierzu wird in wenigstens einer Sensoreinheit ein Speicher vorgesehen, in dem Datensätze mehrerer Blätter verwaltet werden können. In jedem dieser Datensätze sind Bereiche vorgesehen, in denen Daten von wenigstens einer anderen Sensorcinheit gespeichert werden können.The basic idea of the invention consists essentially in that Deriving a measurement result from a sensor unit data from other sensor units to use on the appropriate sheet material. For this, in At least one sensor unit is provided with a memory in which data records multiple sheets can be managed. In each of these records are Areas are provided in which data from at least one other sensor unit can be saved.

Vorteil der Erfindung ist es, daß die Sensoreinheit Daten anderer Sensoreinheiten zur Verfügung hat, die sie bei der Ableitung ihres eigenen Meßergebnisses berücksichtigen kann. Durch die Kenntnis dieser Daten ist die Sensoreinheit in der Lage, ihr Meßergebnis schneller und genauer aus diesen Daten abzuleiten.The advantage of the invention is that the sensor unit has data from other sensor units which they have when deriving their own measurement result can take into account. Knowing this data is the sensor unit able to get your measurement result faster and more accurately from this Derive data.

Vorzugsweise weist die Sensoreinheit eine Meßeinheit und eine Auswerteeinheit auf, wobei der Speicher der Sensoreinheit in der Auswerteeinheit vorgesehen wird. Ferner werden die Meßergebnisse der Sensoreinheit nicht auf eine Ja/Nein-Aussage beschränkt, sondern mit einem höheren Informationsgehalt ausgestattet. Die Meßergebnisse können beispielsweise die Länge oder die Breite des Blattguts in mm, eine Maßzahl für die Verschmutzung oder die Übereinstimmung des Druckbilds mit einem Referenzbild, der Abstand eines Metallfadens von der Blattgutvorderkante, eine Identifikationsnummer für die Art oder Lage des Blattguts o. ä. sein.The sensor unit preferably has a measuring unit and an evaluation unit , with the memory of the sensor unit in the evaluation unit is provided. Furthermore, the measurement results of the sensor unit are not limited to a yes / no statement, but with a higher information content fitted. The measurement results can be, for example, the length or the width of the sheet in mm, a measure of the pollution or the correspondence of the printed image with a reference image, the distance of a metal thread from the leading edge of the sheet, an identification number for the type or location of the sheet material or the like.

Weitere Merkmale und Vorteile der Erfindung ergeben sich aus den Unteransprüchen und der Beschreibung von Ausführungsbeispielen der Erfindung anhand der Figuren. Es zeigen:

Fig. 1
Prinzipskizze eines Ausführungsbeispiels der Erfindung,
Fig. 2
Darstellung des Speicherinhalts in der Auswerteeinheit eines Sensors,
Fig. 3
Darstellung des Speicherinhalts in der zentralen Auswerteeinheit,
Fig. 4
Flußdiagramm eines ersten Ausführungsbeispiels des erfindungsgemäßen Verfahrens,
Fig. 5
Darstellung der Abbildung der Meßergebnisse in diskrete Klassen,
Fig. 6
Darstellung der Regelmatrix des ersten Ausführungsbeispiels,
Fig. 7
Darstellung der Änderungsbedingungen für Sortierklassen,
Fig. 8
Flußdiagramm eines zweiten Ausführungsbeispiels des erfindungsgemäßen Verfahrens,
Fig. 9
Darstellung der Abbildung der Meßergebnisse in überlappende Klassen mit Zugehörigkeitsfunktion,
Fig. 10
Darstellung der Regelmatrix des zweiten Ausführungsbeispiels,
Fig. 11
Darstellung der Zugehörigkeitsfunktionen der Sortierklassen,
Fig. 12
Grafische Ableitung einer resultierenden Zugehörigkeitsfunktion einer Sortierklasse,
Fig. 13
Darstellung der resultierenden Zugehörigkeitsfunktionen.
Further features and advantages of the invention result from the subclaims and the description of exemplary embodiments of the invention with reference to the figures. Show it:
Fig. 1
Schematic diagram of an embodiment of the invention,
Fig. 2
Representation of the memory content in the evaluation unit of a sensor,
Fig. 3
Representation of the memory content in the central evaluation unit,
Fig. 4
Flow chart of a first embodiment of the method according to the invention,
Fig. 5
Representation of the representation of the measurement results in discrete classes,
Fig. 6
Representation of the control matrix of the first exemplary embodiment,
Fig. 7
Representation of the change conditions for sorting classes,
Fig. 8
Flow chart of a second embodiment of the method according to the invention,
Fig. 9
Representation of the mapping of the measurement results in overlapping classes with membership function,
Fig. 10
Representation of the control matrix of the second exemplary embodiment,
Fig. 11
Representation of the membership functions of the sorting classes,
Fig. 12
Graphical derivation of a resulting membership function of a sort class,
Fig. 13
Representation of the resulting membership functions.

Fig. 1 zeigt eine Prinzipskizze eines Ausführungsbeispiels der Erfindung. Das Blattgut wird in einer Vereinzelungseinheit aus einem Stapel Blatt für Blatt vereinzelt und an eine Transportstrecke übergeben, die die Blätter durch die Vorrichtung transportiert und durch eine Transporteinheit 30 gesteuert wird. Die Transportstrecke ist in einzelne Teilabschnitte aufgeteilt, die jeweils von dezentral arbeitenden Untereinheiten 30.1 - 30.M der Transporteinheit 30 gesteuert werden.Fig. 1 shows a schematic diagram of an embodiment of the invention. The sheet material is separated from a stack of sheets in a separating unit Sheet isolated and passed to a transport route that the sheets transported by the device and controlled by a transport unit 30 becomes. The transport route is divided into individual sections, the decentralized sub-units 30.1 - 30.M of the transport unit 30 can be controlled.

Bei der Vereinzelung wird jedem Blatt eine Identifikation ID zugeordnet, anhand derer das Blatt von den Einheiten der Vorrichtung eindeutig erkannt wird. Die zur Bearbeitung eines Blattes benötigten Daten werden unter Verwendung der Identifikation ID des Blattes über eine Verbindung 100 ausgetauscht. Die Verbindung 100 verbindet sowohl die Untereinheiten 30.1 - 30.M, als auch eine zentrale Auswerteeinheit 10, mehrere Sensoreinheiten 20.1 - 20.N und eine Steuereinheit 40 miteinander.With the separation, each sheet is assigned an identification ID, on the basis of which the sheet is clearly recognized by the units of the device becomes. The data required to process a sheet are used the identification ID of the sheet exchanged via a connection 100. The connection 100 connects both the subunits 30.1 - 30.M, as well as a central evaluation unit 10, several sensor units 20.1 - 20.N and a control unit 40 with each other.

Die Sensoreinheiten 20.1 - 20.N setzen sich jeweils aus einer Meßeinheit 21.1 - 21.N und einer Auswerteeinheit 22.1 - 22.N zusammen. Jede Meßeinheit 21.n weist einen Meßwertaufnehmer auf, der bestimmte Merkmale des Blattguts erfaßt und in elektrische Signale umwandelt. Diese elektrischen Signale werden dann in digitale Meßdaten umgewandelt und können optional vor der Weiterverarbeitung normiert und/oder transformiert werden. Die Auswerteeinheit 22.n des Sensors 20.n empfängt die Meßdaten der Meßeinheit 21.n und leitet unter Verwendung der Meßdaten ein Meßergebnis ab.The sensor units 20.1 - 20.N each consist of a measuring unit 21.1 - 21.N and an evaluation unit 22.1 - 22.N together. Each measuring unit 21.n has a transducer, the certain characteristics of the sheet detected and converted into electrical signals. These electrical signals will be then converted into digital measurement data and can optionally before Further processing can be standardized and / or transformed. The evaluation unit 22.n of the sensor 20.n receives the measurement data of the measuring unit 21.n and derives a measurement result using the measurement data.

In mindestens einer Auswerteeinheit 22.n ist ein Speicher vorgesehen, dessen Inhalt in Fig. 2 dargestellt ist. Als Beispiel wurde hier die Auswerteeinheit 22.2 gewählt. Im Speicher der Auswerteeinheit 22.2 können mehrere Datensätze verwaltet werden. Jeder Datensatz ist jeweils einem Blatt einer bestimmten Identifikation ID zugeordnet. Der hier gezeigte Speicher ist in der Lage, eine Anzahl L von Datensätzen zu verwalten.A memory is provided in at least one evaluation unit 22n Content is shown in Fig. 2. The evaluation unit was used here as an example 22.2 chosen. Several data records can be stored in the memory of the evaluation unit 22.2 to get managed. Each record is a sheet of a particular one Identification ID assigned. The memory shown here is in the Able to manage a number L of records.

Jeder Datensatz weist einen Bereich für externe Daten ED auf. In ihm werden entweder Meßdaten MD oder Meßergebnisse ME anderer Sensoreneinheiten gespeichert. In Fig. 2 sind beispielsweise die Meßdaten MD der Sensoreinheit 20.3 und die Meßergebnisse der Sensoreinheit 20.1 in jedem Datensatz gespeichert. Beisielsweise die Meßdaten der Sensoreinheit 20.3 für das Blatt mit der Identifikation ID = 2 sind hier mit MD.23 bezeichnet, wobei der erste Index der Identifikation ID der Banknote = 2 und der zweite Index dem Index der Sensoreinheit = 3 entspricht. Für die anderen Daten wird bei der Bezeichnung analog verfahren.Each data record has an area for external data ED. Be in it either measurement data MD or measurement results ME of other sensor units saved. 2 shows, for example, the measurement data MD of the sensor unit 20.3 and the measurement results of the sensor unit 20.1 in each data set saved. For example, the measurement data of the sensor unit 20.3 for the sheet with the identification ID = 2 are designated here with MD.23, the first Index of the ID ID of the banknote = 2 and the second index of the index corresponds to the sensor unit = 3. For the other data, the name proceed analogously.

Vorzugsweise werden im Speicher der Auswerteeinheit 22.2 auch die von der Meßeinheit 21.2 gelieferten Meßdaten MD für jedes Blatt gespeichert. Aus den eigenen Meßdaten MD und den externen Daten ED eines Datensatzes leitet die Auswerteeinheit 22.2 für jedes Blatt ein entsprechendes Meßergebnis ME ab, welches optional in dem entsprechenden Datensatz gespeichert werden kann.In the memory of the evaluation unit 22.2, those of the measurement data MD supplied to the measuring unit 21.2 are stored for each sheet. From the own measurement data MD and the external data ED of a data record leads the evaluation unit 22.2 a corresponding measurement result for each sheet ME, which is optionally saved in the corresponding data record can be.

Ist das Meßergebnis für ein Blatt ermittelt, wird dieses mit der entsprechenden Indentifikation ID des Blattes auf die Datenleitung 100 geschrieben. Das Meßergebnis kann nun bei Bedarf von anderen Sensoreinheiten gelesen und im Speicher der Auswerteeinheit dieser Sensoreinheit gespeichert werden. Ist die Kenntnis bestimmter Meßdaten eines Sensors zur Ableitung des Meßergebnisses einer anderen Sensoreinheit notwendig, so muß diese auch die entsprechenden Meßdaten auf die Datenleitung 100 schreiben, so daß sie die andere Sensoreinheit lesen kann. Alternativ dazu kann das Schreiben der Meßdaten auch erst nach dem Empfang eines entsprechenden Signals der anderen Sensoreinheit erfolgen. Once the measurement result has been determined for a sheet, it is compared with the corresponding Identification ID of the sheet written on the data line 100. The The measurement result can now be read and read by other sensor units if required be stored in the memory of the evaluation unit of this sensor unit. Is the knowledge of certain measurement data of a sensor for deriving the measurement result another sensor unit necessary, this must also be the write the corresponding measurement data on the data line 100 so that they are the other sensor unit can read. Alternatively, writing the Measurement data only after receiving a corresponding signal from another sensor unit.

Weiterhin weist die Vorrichtung eine zentrale Auswerteeinheit 10 mit einem Speicher auf, deren Inhalt in Fig. 3 gezeigt ist. Die zentrale Auswerteeinheit 10 liest die Meßergebnisse aller Sensoreinheiten 20.1 - 20.N von der Datenleitung 100 und speichert diese unter der Identifikation ID des entsprechenden Blattes ab. Sind zu einer Identifikation ID die Meßergebnisse aller Sensoreinheiten bekannt, leitet die zentrale Auswerteeinheit 10 aus den Meßergebnissen eine Sortierklasse KL für das entsprechende Blattgut ab und schreibt die Identifikation ID und die zugehörige Sortierklasse KL auf die Datenleitung 100. Optional kann die Sortierklasse KL im Speicher unter der entsprechenden Identifikation des Blattes gespeichert werden.Furthermore, the device has a central evaluation unit 10 with a Memory whose content is shown in Fig. 3. The central evaluation unit 10 reads the measurement results of all sensor units 20.1 - 20.N from the data line 100 and stores this under the identification ID of the corresponding Leaf. Are the measurement results of all sensor units for an identification ID known, the central evaluation unit 10 guides from the measurement results a sorting class KL for the corresponding sheet material and writes the Identification ID and the associated sorting class KL on the data line 100. Optionally, the sorting class KL can be stored in the memory under the corresponding Identification of the sheet can be saved.

Die Sortierklasse KL wird von den Untereinheiten der Transporteinheit ausgewertet, die den Transport des Blattes in die Zieleinheit steuern. Ist die entsprechende Untereinheit 30.m nicht für die Bearbeitung des Blattes zuständig, wird dieses an die nachfolgende Untereinheit 30.m+1 weitergeleitet. Im anderen Fall wird das Blatt zu den entsprechenden Manipulatoren der Untereinheit 30.m geleitet und bearbeitet. Nach der Bearbeitung des Blattguts wird von der Verarbeitungseinheit eine entsprechende positive oder negative Information über den Abschluß der Bearbeitung auf die Datenleitung 100 geschrieben. Diese Information wird bespielsweise von der Steuereinheit 40 gelesen und bei der Protokollierung des Bearbeitungsvorgangs verwendet.The sorting class KL is evaluated by the subunits of the transport unit, that control the transport of the sheet to the target unit. Is the corresponding one Subunit 30.m not responsible for processing the sheet, this is forwarded to the subsequent subunit 30.m + 1. in the otherwise the sheet becomes the corresponding manipulators of the subunit 30.m directed and edited. After processing the sheet material the processing unit makes a corresponding positive or negative Information about the completion of the processing on the data line 100 written. This information is, for example, from the control unit 40 read and used in the logging of the machining process.

Weiterhin kann jede Untereinheit 30.m Fehlermeldungen auf die Datenleitung schreiben, falls es beispielsweise zu einem Blattstau im Transportsystem der Untereinheit 30.m kommt. Diese Fehlermeldungen können von anderen Einheiten der Vorrichtung interpretiert und entsprechende Maßnahmen eingeleitet werden.Furthermore, each subunit 30.m error messages on the data line write if, for example, there is a sheet jam in the transport system the subunit 30.m comes. These error messages can be from others Units of the device interpreted and appropriate measures be initiated.

Vorzugsweise sind die Untereinheiten 30.m so ausgelegt, daß sie die elektrischen und mechanischen Funktionen der Transportstrecke steuern. Hierzu zählen unter anderem der Antrieb der Transportstrecke, die Schaltung der Weichen innerhalb der Transportstrecke, das Messen der Position des Blattguts mittels Lichtschranken usw. Weiterhin können die Untereinheiten 30.m aber auch die Steuerung spezieller elektrischer bzw. mechanischer Manipulatoren innerhalb der Einheiten der Vorrichtung durchführen. Hierzu zählt beispielsweise die Steuerung der Vereinzelerkomponenten, der Stapelräder und der Shredderwalzen usw.Preferably, the sub-units 30.m are designed so that they the electrical and control mechanical functions of the transport route. For this count among other things the drive of the transport route, the switching of the Turnouts within the transport route, measuring the position of the sheet material by means of light barriers etc. Furthermore, the sub-units 30.m but also the control of special electrical or mechanical manipulators perform within the units of the device. That counts for example the control of the singling components, the stacking wheels and the shredder rollers etc.

Die Steuereinheit 40 dient zur Steuerung und zur Protokollierung der Bearbeitungsvorgänge der Blätter. Sie ist in der Lage, über die Datenleitung 100 Steuerinformationen zu senden, die von den einzelnen Einheiten entsprechend interpretiert werden. Mittels solcher Steuerungsinformationen kann beispielsweise die Vorrichtung in einen vom Bediener ausgewählten Bearbeitungsstatus gebracht werden. Ferner kann die Steuereinheit 40 die Speicherung spezieller Programme oder Referenzdaten von der Steuereinheit 40 in die anderen Einheiten der Vorrichtung über die Datenleitung 100 veranlassen. Zu diesem Zweck sind auf der Steuereinheit 40 Massenspeicher vorhanden, in denen diese Daten verwaltet werden.The control unit 40 serves to control and log the machining processes of leaves. It is able to communicate via data line 100 Send control information by the individual units accordingly be interpreted. By means of such control information for example, the device in a processing status selected by the operator to be brought. The control unit 40 can also store the data special programs or reference data from the control unit 40 in initiate the other units of the device via data line 100. For this purpose, 40 mass memories are available on the control unit, in which this data is managed.

Anhand der Daten der Untereinheiten 30.1 - 30.M, der Sensoreinheiten 20.1 - 20.N und der Sortierklasse KL der zentralen Auswerteeinheit 10 kann die Steuereinheit 40 den Bearbeitungsvorgang jedes einzelnen Blattes überwachen und protokollieren. Während der eigentlichen Bearbeitung des Blattguts ist die Funktion der Steuereinheit lediglich auf das Abhören der Datenleitung 100 beschränkt.Based on the data of the sub-units 30.1 - 30.M, the sensor units 20.1 - 20.N and the sorting class KL of the central evaluation unit 10 can Control unit 40 monitor the processing of each sheet and log. During the actual processing of the sheet material is the function of the control unit only on listening to the data line 100 limited.

Die Datenleitung 100 wird als Datenbus ausgeführt. Bevorzugt wird ein CAN-Bus verwendet. Dieser ist für sogenannte Echtzeitanwendungen, wie sie hier hauptsächlich vorliegen, besonders gut geeignet. Optional können weitere Datenleitungen 101 bzw. 102 parallel zur Datenleitung 100 vorgesehen werden, so daß die Datenleitung 100 entlastet wird.The data line 100 is designed as a data bus. A is preferred CAN bus used. This is for so-called real-time applications such as they are mainly present here, particularly well suited. Optionally can further data lines 101 and 102 are provided parallel to data line 100 be so that the data line 100 is relieved.

Die Datenleitung 101 kann auch mittels eines CAN-Busses realisiert werden und dient dazu, den Datenaustausch zwischen den Sensoreinheiten 20.1 - 20.N sowie der zentralen Auswerteeinheit 10 zu verbessern. Dies ist insbesondere dann sinnvoll, wenn zwischen den Sensoreinheiten 20.n viele Meßdaten ausgetauscht werden, die oft ein hohes Datenvolumen aufweisen.The data line 101 can also be implemented using a CAN bus and serves to exchange data between the sensor units 20.1 - 20.N as well as the central evaluation unit 10. This is particularly so then makes sense if there are many between the sensor units 20.n. Measurement data are exchanged, which often have a high data volume.

Die Datenleitung 102 wird speziell von der Steuereinheit 40 für sogenannte Nichtechtzeitanwendungen genutzt. Hierüber können beispielsweise bei der Initialisierung der Vorrichtung in einen bestimmten Betriebszustand Programme oder Referenzdaten größeren Umfangs in die Sensoreinheiten 20 oder die zentrale Auswerteeinheit 10 geschrieben werden. Auf eine Verbindung zu den Untereinheiten 30.m kann auch verzichtet werden, da die dorthin übertragenen Datenmengen im allgemeinen gering sind.The data line 102 is specifically used by the control unit 40 for so-called Non-real-time applications used. You can use this, for example, at Initialization of the device in a certain operating state programs or larger-scale reference data in the sensor units 20 or the central evaluation unit 10 can be written. On a connection to the sub-units 30.m can also be dispensed with, since the amounts of data transferred there are generally small.

Die Ableitung der Sortierklasse eines Blatts aus den Meßergebnissen der Sensoreinheiten kann beispielsweise unter Verwendung frei konfigurierbarer Tabellen und/oder Matrizen durchgeführt werden, die in einem Speicher der zentralen Auswerteeinheit 10 verwaltet werden. Bei der Ableitung werden zunächst kontinuierliche Meßergebnisse auf Klassen abgebildet. Diskrete Meßergebnisse werden direkt einer Klasse zugeordnet. Einzelne Klassen werden zu einer Eigenschaft des Blattes mit verschiedenen Ausprägungen zusammengefaßt. Mittels einer Regelmatrix können beliebige, aber festgewählte Kombinationen verschiedener Ausprägungen einer Menge von Eigenschaften einer Sortierklasse zugeordnet werden.Deriving the sorting class of a sheet from the measurement results of the Sensor units can be freely configurable, for example Tables and / or matrices are performed in a memory the central evaluation unit 10 are managed. When deriving First, continuous measurement results are mapped to classes. discrete Measurement results are assigned directly to a class. Individual classes become a property of the sheet with different characteristics summarized. A rule matrix can be used to select any, but fixed Combinations of different forms of a set of properties be assigned to a sort class.

Die Fig. 4 zeigt ein Flußdiagramm eines ersten Ausführungsbeispiels des erfindungsgemäßen Verfahrens zur Bearbeitung von Blattgut, hier speziell Banknoten. Die Meßdaten MD der Banknote werden von den Sensoren 20.n erfaßt. Unter Verwendung dieser Meßdaten MD werden Meßergebnisse ME der Banknote abgeleitet und in der Auswerteeinheit 10 gemäß Fig. 3 gespeichert.Fig. 4 shows a flow chart of a first embodiment of the Method according to the invention for processing sheet material, here specifically Paper money. The measurement data MD of the banknote are from the sensors 20.n detected. Using these measurement data MD, measurement results ME derived from the banknote and stored in the evaluation unit 10 according to FIG. 3.

Im ersten Ausführungsbeispiel werden die Meßergebnisse ME zunächst auf diskrete Klassen abgebildet. Ein Beispiel für eine solche Abbildung ist in Fig. 5 gezeigt. Das Meßergebnis soll in diesem Fall die Fläche der Banknote in mm2 darstellen, die von Flecken bedeckt ist. Wird in einer ersten Messung M1 beispielsweise als Meßergebnis 140 mm2 ermittelt, so wird dieses Meßergebnis auf die Klasse mit dem Klassenkennzeichen 4 abgebildet. Die Anzahl der Klassen sowie die Lage der Klassengrenzen kann beliebig konfiguriert werden. Die Klassen 0 bis 5 lassen sich zur Eigenschaft "Flecken" zusammenfassen. Jede Klasse stellt somit eine Ausprägung der Eigenschaft "Flecken" dar. Zur besseren Übersicht werden die einzelnen Klassen auch oft mit verbalen Kennzeichnungen, wie "sehr wenig", "wenig", "viel" usw. belegt.In the first embodiment, the measurement results ME are initially mapped to discrete classes. An example of such a mapping is shown in FIG. 5. In this case, the measurement result should represent the area of the banknote in mm 2 which is covered by spots. If, for example, 140 mm 2 is determined as the measurement result in a first measurement M 1 , this measurement result is mapped to the class with the class identifier 4. The number of classes and the location of the class boundaries can be configured as desired. Classes 0 to 5 can be summarized as "stains". Each class thus represents an expression of the property "stains". For a better overview, the individual classes are often also provided with verbal markings, such as "very little", "little", "much" etc.

In Fig. 6 ist die Regelmatrix des ersten Ausführungsbeispiels dargestellt. Zu den einzelnen Eigenschaften "Doppelabzug", "Störung", usw. sind jeweils die zugehörigen Klassen mit den verbalen und den Klassenkennzeichen angegeben. Zur besseren Übersicht sind verschiedene Eigenschaften nochmals zu einer übergeordneten Gruppe zusammengefaßt.6 shows the control matrix of the first exemplary embodiment. To the individual properties "double deduction", "malfunction", etc. are each the associated classes are given with the verbal and class identifiers. For a better overview, various properties are again combined into a superordinate group.

Zur Ableitung der Sortierklasse der Banknote wird zunächst aus den Klassen aller Eigenschaften ein Eigenschaftsvektor gebildet. In der Fig. 6 sind beispielhaft vier Klassenvektoren V1 bis V4 dargestellt. In jeder Eigenschaft ist jeweils genau die Klasse markiert, die dem jeweiligen Meßergebnis der Banknote entspricht. Bei der Eigenschaft "Flecken" liegt das Meßergebnis des zum Klassenvektor V1 gehörenden Blattguts z. B. in der Klasse "wenig", während das Meßergebnis der Eigenschaft "Eselsohren" in der Klasse "sehr wenig" liegt. Der Klassenvektor klassifiziert somit die Ausprägung aller Eigenschaften einer Banknote.To derive the sorting class of the banknote, a property vector is first formed from the classes of all properties. 6 four class vectors V 1 to V 4 are shown by way of example. In each property the class is marked that corresponds to the measurement result of the banknote. With the property "stains" the measurement result of the leaf material belonging to the class vector V 1 is z. B. in the class "little", while the measurement result of the property "dog ears" in the class "very little". The class vector thus classifies the characteristics of all the properties of a banknote.

Die Regelmatrix besteht aus einer Anzahl von Regeln, die hier mit den Ziffern 1 bis 5 bezeichnet sind. Jede Regel besteht aus einem Regelvektor, der analog zum Klassenvektor aus den Klassen aller Eigenschaften gebildet ist. Im Gegensatz zum Klassenvektor ist es jedoch möglich, daß mehrere Klassen einer Eigenschaft markiert sind, wie beispielsweise zur Eigenschaft "Verschmutzung" in den Regeln 1 bis 5. Jeder der Regeln 1 bis 5 ist eine Sortierklasse zugeordnet, die hier mit dem jeweiligen Sortierziel "Stapler 1", "Stapler 2" usw. bezeichnet ist. Im allgemeinen kann auch mehreren Regeln die gleiche Sortierklasse zugeordnet werden.The rule matrix consists of a number of rules, here with the digits 1 to 5 are designated. Each rule consists of a rule vector, the is formed from the classes of all properties analogously to the class vector. In contrast to the class vector, it is possible that several classes of a property, such as the property "pollution" in rules 1 to 5. Each of rules 1 to 5 is a sort class assigned here with the respective sorting destination "Stacker 1", "Stacker 2", etc. is designated. In general, there can also be several rules the same sort class can be assigned.

Die Aussagen der einzelnen Regeln lassen sich verbal in etwa wie folgt formulieren. Gemäß Regel 1 werden denjenigen Banknoten die Sortierklasse "Stapler 1" zugewiesen, deren Denomination 50 $ ist, die nach oben orientiert sind, alle Sicherheitsmerkmale aufweisen, die sauber sind und die sehr wenig Defekte aufweisen. Gemäß Regel 2 werden diejenigen Banknoten, deren Orientierung nach unten gerichtet ist und die ansonsten die gleichen Eigenschaften wie die Banknoten nach Regel 1 haben, der Sortierklasse "Stapler 2" zugewiesen. Der Sortierklasse "Stapler 3" werden alle 1 $- und 2 $-Banknoten zugewiesen, die zumindest einen korrekten Sicherheitsfaden aufweisen, die sauber sind und wenig Defekte aufweisen. Die Sortierklasse "Stapler 4" wird denjenigen Banknoten zugewiesen, die unabhängig von der Denomination sauber sind, wenig Defekte aufweisen und bei denen weder die Eigenschaft "Wasserzeichen" noch die Eigenschaft "Sicherheitsfaden" korrekt ist. Der Sortierklasse "Shredder" werden alle Banknoten zugewiesen, die unabhängig von ihrer Denomination und ihren Defekten korrekte Sicherheitsmerkmale aufweisen und schmutzig sind. The statements of the individual rules can be formulated verbally as follows. According to rule 1, those banknotes become the sorting class Assigned "Stacker 1", whose denomination is $ 50, which is oriented upwards have all the security features that are clean and that very have few defects. According to rule 2, those banknotes whose Orientation is downward and otherwise has the same characteristics like the banknotes according to rule 1, the sorting class "Stacker 2" assigned. The sorting class "Stacker 3" will be $ 1 and 2nd $ Banknotes assigned at least one correct security thread have clean and few defects. The sort class "Stacker 4" is assigned to those banknotes that are independent of the Denomination are clean, have few defects and neither the property "watermark" or the property "security thread" correct is. All banknotes are assigned to the "Shredder" sorting class the correct security features regardless of their denomination and defects have and are dirty.

Zur Ableitung der Sortierklassen werden nun die Markierungen des Klassenvektors, z. B. V1, mit den entsprechenden Markierungen der Regelvektoren 1, 2, 3, 4, 5 in ihrer Reihenfolge nacheinander verglichen. Die Sortierklasse, die dem ersten Regelvektor zugeordnet ist, der in allen Klassen des Klassenvektors markiert ist, wird dem Blattgut als Sortierklasse zugewiesen. Stimmen die Markierungen keines Regelvektors mit allen Markierungen des Klassenvektors überein, so wird dem Blattgut eine beliebige, aber fest gewählte Sortierklasse zugewiesen.To derive the sorting classes, the markings of the class vector, e.g. B. V 1 , compared with the corresponding markings of the control vectors 1, 2, 3, 4, 5 in sequence. The sorting class, which is assigned to the first rule vector, which is marked in all classes of the class vector, is assigned to the sheet material as a sorting class. If the markings of none of the rule vectors match all the markings of the class vector, the sheet material is assigned any, but firmly selected sorting class.

Für die Beispiele in Fig. 6 bedeutet das, daß dem Blattgut zum Klassenvektor V1 die Sortierklasse "Stapler 2" zugewiesen wird. Das Blattgut zum Klassenvektor V2 erhält die Sortierklasse "Stapler 4". Dem Blattgut zum Klassenvektor V3 wird die Sortierklasse "Shredder" zugewiesen. Da die Markierung keines Regelvektors mit allen Markierungen des Klassenvektors V4 übereinstimmen, wird diesem Blattgut eine beliebige, aber fest gewähle Sortierklasse zugewiesen, die mit "Reject" bezeichnet werden soll.For the examples in FIG. 6, this means that the sorting class "stacker 2" is assigned to the sheet material for class vector V 1 . The sheet material for class vector V 2 is given the sorting class "stacker 4". The sorting class "shredder" is assigned to the sheet material for class vector V 3 . Since the marking of no rule vector matches all the markings of the class vector V 4 , this sheet material is assigned any, but firmly selected sorting class which is to be referred to as "reject".

Nach der Zuweisung der Sortierklasse an das Blattgut, wird dieses anhand der Sortierklasse in die entsprechende Zieleinheit transportiert. Die Blätter mit der Sortierklasse "Reject" werden im allgemeinen in ein sogenanntes Rejectfach gestapelt, wo sie dann vom Bediener aus der Vorrichtung entnommen und in Augenschein genommen werden können.After assigning the sorting class to the sheet material, this is based on the sorting class is transported to the corresponding target unit. The leaves with the sorting class "Reject" are generally in a so-called Reject compartment stacked, where they are then removed from the device by the operator and can be viewed.

Um eine unbefugte Änderung in den Regeln der Regelmatrix zu verhindern, ist jeder Klasse ein Sicherheitslevel SL zugewiesen. Hiermit kann spezifiziert werden, welche Benutzer Änderungen in dieser Klasse vornehmen dürfen. Hier sollen beispielsweise der Wert 3 für den Entwickler, 2 für den Supervisor und 1 für den Bediener der Vorrichtung stehen. Somit ist es hier dem Bediener der Vorrichtung möglich, die Klassen der Eigenschaft "Denomination der Banknote" zu verändern, während die Eigenschaften der Gruppe "Sicherheitsmerkmale der Banknote" lediglich vom Supervisor geändert werden dürfen.In order to prevent an unauthorized change in the rules of the rule matrix, a security level SL is assigned to each class. Hereby can be specified which users are allowed to make changes in this class. Here, for example, the value 3 for the developer, 2 for the supervisor and 1 stand for the operator of the device. So here it is Device operators can use the classes of property "Denomination the banknote "while changing the properties of the group "Security features of the banknote" only changed by the supervisor may be.

Weiterhin ist es möglich, zumindest bestimmten Klassen ein Gewicht G zuzuordnen. Mittels dieser Gewichte G können beispielsweise die Regeln der Regelmatrix auf Konsistenz überprüft werden oder die durch die Regelmatrix abgeleitete Sortierklasse bei Bedarf geändert werden.It is also possible to assign a weight G to at least certain classes. By means of these weights G, the rules of Rule matrix to be checked for consistency or by the rule matrix derived sort class can be changed if necessary.

Beispielhaft soll hier lediglich eine mögliche Bedeutung für die Gewichte G der Klassen der Gruppe "Sicherheitsmerkmale der Banknote" erläutert werden. Neben den hier dargestellten beiden Eigenschaften "Wasserzeichen" und "Sicherheitsfaden" gibt es im allgemeinen noch eine Anzahl weiterer Eigenschaften in dieser Gruppe, die hier aus Gründen der Übersichtlichkeit nicht genannt werden.By way of example, only a possible meaning for the weights G is intended here the classes of the group "security features of the banknote" are explained. In addition to the two properties "watermark" shown here and "security thread" there are generally a number of others Properties in this group that are here for the sake of clarity not be mentioned.

Für die Beurteilung einer Banknote kann es von Interesse sein, nicht nur die einzelnen Eigenschaften der Sicherheitsmerkmale zu überprüfen, sondern zudem noch eine Gewichtung der einzelnen Eigenschaften zueinander vorzunehmen, um beispielsweise aussagekräftige Eigenschaften von weniger aussagekräftigen zu unterscheiden. Hier wird beispielsweise die Korrektheit der Eigenschaft "Sicherheitsfaden" mit 5 höher bewertet als die Korrektheit der Eigenschaft "Wasserzeichen" mit 3. Bei einer Vielzahl solcher Eigenschaften kann durch entsprechende Gewichte eine Feinabstufung der einzelnen Eigenschaften gegeneinander vorgenommen werden.It may be of interest to assess a banknote, not just that to check individual properties of the security features, but in addition to weighting the individual properties to each other, for example meaningful properties of less to distinguish meaningful. Here, for example, the correctness the property "security thread" with 5 higher than the correctness the property "Watermark" with 3. With a large number of such properties can be fine-tuned by individual weights Properties are made against each other.

Aus den Gewichten der einzelnen Klassen in der Gruppe "Sicherheitsmerkmale der Banknote" kann nun für jede Regel ein Mindestgewicht bestimmt werden, indem die Gewichte der einzelnen Klassen jeder Eigenschaft der Gruppe mit dem jeweils geringsten markierten Gewicht der Regel aufsummiert werden. Das bedeutet für das Beispiel in Fig. 6, daß der Regel 1, 2 und 5 in der Gruppe "Sicherheitsmerkmale der Banknote" jeweils ein Mindestgewicht von 8 zugeordnet ist. Für die Regel 3 ist das Mindestgewicht 5 und für die Regel 4 ist das Mindestgewicht 0.From the weights of the individual classes in the group "Security features the banknote "can now determine a minimum weight for each rule be by the weights of each class of each property the group with the lowest marked weight of the rule become. For the example in FIG. 6, this means that rule 1, 2 and 5 in the "Security features of the banknote" group each have a minimum weight of 8 is assigned. For rule 3, the minimum weight is 5 and for rule 4 the minimum weight is 0.

Das so ermittelte Mindestgewicht für jede Regel in der Gruppe "Sicherheitsmerkmale der Banknote" gibt somit ein Maß für die Sicherheit der Banknote an. Ein hohes Mindestgewicht steht für hohe Sicherheit und ein niedriges Mindestgewicht für eine geringe Sicherheit. Für eine umlauffähige Banknote kann die gewünschte Sicherheit somit durch ein vorgegebenes Mindestgewicht in der Gruppe "Sicherheitsmerkmale der Banknote" definiert werden.The minimum weight determined in this way for each rule in the group "Safety features The banknote "thus gives a measure of the security of the Banknote. A high minimum weight stands for high security and a low minimum weight for low security. For a fit Banknote can thus provide the desired security through a given Minimum weight defined in the group "Security features of the banknote" become.

Aus den Gewichten der Eigenschaft "Denomination" soll hier ein solches vorgegebenes Mindestgewicht für die Sicherheit einer umlauffähigen Banknote bestimmt werden. Das vorgegebene Mindestgewicht einer Regel in der Gruppe "Sicherheitsmerkmale der Banknote" für umlauffähige Banknoten ergibt sich hierbei als Maximum der Gewichte der markierten Klassen der Regel in der Eigenschaft "Denomination". Für die Regel 1, 2, 4 und 5 ergibt sich somit ein Mindestgewicht für die Sicherheit einer unlauffähigen Banknote von 8 und für die Regel 3 von 3.One of the weights of the property "Denomination" is supposed to be here specified minimum weight for the security of a fit banknote be determined. The specified minimum weight of a rule in the "Banknote security features" group for fit banknotes is the maximum of the weights of the marked classes Usually in the "Denomination" property. For rule 1, 2, 4 and 5 results thus a minimum weight for the security of an unfit banknote of 8 and for rule 3 of 3.

Durch einen Vergleich des vorgegebenen Mindestgewichts für die Sicherheit einer umlauffähigen Banknote gemäß der Eigenschaft "Denomination" mit dem Gewicht in der Gruppe "Sicherheitsmerkmale der Banknote" für jede Regel ergibt sich, daß die Mindestgewichte für die Sicherheit einer umlauffähigen Banknote bei den Regeln 1, 2, 3 und 5 größer sind als die Mindestgewichte in der Gruppe "Sicherheitsmerkmale der Banknote". Die Relation und somit das Kriterium für eine umlauffähige Banknote ist lediglich in Regel 4 nicht erfüllt. Anhand dieser Kriterien kann beispielsweise die Konsistenz einer jeden Regel geprüft werden. By comparing the specified minimum weight for safety a fit banknote according to the "Denomination" property the weight in the banknote security features group for each As a rule, it follows that the minimum weights for the safety of a fit Banknote rules 1, 2, 3 and 5 are larger than the minimum weights in the group "Security features of the banknote". The relation and thus the criterion for an fit banknote is only normal 4 not met. For example, consistency can be based on these criteria of every rule.

Durch die Einführung eines Mindestgewichts für jede Regel in der Gruppe "Sicherheitsmerkmale der Banknote" ist ein Kriterium geschaffen, mit dem auch Banknoten mit unterschiedlichen Sicherheitsmerkmalen miteinander verglichen werden können. Bei Bedarf sind selbstverständlich auch andere Auswerte-Algorithmen für die einzelnen Gewichte der Klassen denkbar.By introducing a minimum weight for each rule in the group "Security features of the banknote" is a criterion created with the also banknotes with different security features with each other can be compared. If necessary, there are of course others Evaluation algorithms for the individual weights of the classes are conceivable.

Wie in Fig. 7 dargestellt, kann die mit Hilfe der Regelmatrix bestimmte Sortierklasse im Nachhinein nochmals optional in Abhängigkeit von einer bestimmten Bedingung verändert werden. Eine solche nachträgliche Änderung kann beispielsweise bei der Wartung der Vorrichtung oder beim Entwurf der Regelmatrix hilfreich sein.As shown in FIG. 7, the sorting class determined with the aid of the rule matrix can in retrospect, again optionally depending on a specific one Condition to be changed. Such a subsequent change can, for example, in the maintenance of the device or in the design the rule matrix can be helpful.

Die Bedingungen können aus der Regelmatrix abgeleitet werden, wie beispielsweise das Mindestgewicht MG für eine Regel in der Gruppe "Sicherheitsmerkmale der Banknote". Weiterhin können die Bedingungen auch von Meßergebnissen der Sensoren oder der Klassenkennzeichnung eines bestimmten Meßergebnisses abhängen. Generell können alle der Auswerteeinrichtung zur Verfügung stehenden Daten in beliebiger Kombination in einer Bedingung genutzt werden.The conditions can be derived from the rule matrix, for example the minimum weight MG for a rule in the group "safety features the banknote ". Furthermore, the conditions of Measurement results of the sensors or the class identification of a certain one Depend on the measurement result. In general, all of the evaluation device available data in any combination in one Condition.

Weiterhin ist es möglich, mittels eines Zufallsgenerators RND bestimmte Banknoten statistisch verteilt umzuleiten. In dem in Fig. 7 gezeigten Beispiel werden statistisch 20 % der Banknoten von der Sortierklasse "Shredder" in die Sortierklasse "Reject" umgelenkt. Eine solche Vorgehensweise gestattet es beispielsweise, die Sortierqualität der Banknoten kontinuierlich zu überprüfen, indem der Bediener der Vorrichtung die mit der Sortierklasse "Reject" umgeleiteten Banknoten persönlich in Augenschein nimmt. Gegebenenfalls kann dieser anhand der Inaugenscheinnahme dann die Klassengrenzen bestimmter Klassen geeignet verändern. It is also possible to use a random number generator RND Redirect banknotes statistically. In the example shown in FIG. 7 statistically 20% of the banknotes are sorted by the "Shredder" sorting class redirected the sorting class "Reject". Such an approach allows for example, to continuously check the sorting quality of banknotes, by the operator of the device having the sorting class "Reject" redirects banknotes personally. Possibly he can then inspect the class boundaries based on the inspection change certain classes appropriately.

Weiterhin ist es durch eine nachträglich Änderung der Sortierklasse einfach möglich, im Fall einer Störung die entsprechenden Banknoten umzuleiten, ohne große Änderungen in der Regelmatrix vornehmen zu müssen.Furthermore, it is easy to change the sorting class afterwards possible to divert the relevant banknotes in the event of a malfunction, without having to make major changes in the rule matrix.

Ein zweites Ausführungsbeispiel des erfindungsgemäßen Verfahrens zur Bearbeitung von Blattgut ist in Fig. 8 dargestellt. Auch hier werden, wie schon zum ersten Ausführungsbeispiel erläutert, zunächst Meßdaten von den Sensoren 20.n erfaßt und unter Verwendung dieser Meßdaten MD Meßergebnisse ME abgeleitet.A second embodiment of the inventive method for Processing sheet material is shown in Fig. 8. Again, how already explained for the first embodiment, first measurement data from the sensors 20.n and using these measurement data MD Measurement results derived from ME.

Im Gegensatz zum ersten Ausführungsbeispiel werden hier die Meßergebnisse ME auf überlappende Klassen abgebildet bzw. fuzzifiziert. Ein Beispiel für eine solche Abbildung ist in Fig. 9 gezeigt. Der Übersichtlichkeit halber wurden aus den Eigenschaften des ersten Ausführungsbeispiels lediglich die Eigenschaften "Verschmutzung", "Eselsohren" und "Flecken" verwendet. In diesem Beispiel können die Meßergebnisse des Blattguts jeweils Werte zwischen 0 und 1 annehmen. Jeder Eigenschaft sind drei überlappende Klassen zugeordnet. Für die Eigenschaft "Verschmutzung" sind das die Klassen "stark" mit Meßergebnissen im Intervall von 0 bis 0.5, "mittel" im Intervall von 0 bis 1 und "gering" im Intervall von 0.5 bis 1. Die Klassen "stark", "mittel", "gering" werden im folgenden als Fuzzyklassen benutzt.In contrast to the first embodiment, the measurement results are here ME mapped to overlapping classes or fuzzified. An example for such a mapping is shown in Fig. 9. For the sake of clarity were only the properties of the first embodiment Properties "pollution", "dog ears" and "stains" used. In In this example, the measurement results of the sheet material can have values between Accept 0 and 1. Each property has three overlapping classes assigned. These are the classes for the property "pollution" "strong" with measurement results in the interval from 0 to 0.5, "medium" in the interval from 0 to 1 and "low" in the interval from 0.5 to 1. The classes "strong", "Medium", "low" are used as fuzzy classes in the following.

Jeder Fuzzyklasse ist eine in Fig. 9 dargestellte Zugehörigkeitsfunktion zugewiesen. Die Anzahl der überlappenden Fuzzyklassen sowie die Form der verschiedenen Zugehörigkeitsfunktionen kann beliebig festgelegt werden. Durch eine geeignete Wahl der Zugehörigkeitsfunktionen kann die Funktionalität des Verfahrens für die jeweilige Anwendung optimiert werden.Each fuzzy class is assigned a membership function shown in FIG. 9. The number of overlapping fuzzy classes and the shape of the various membership functions can be set arbitrarily. By a suitable choice of membership functions, the functionality of the process can be optimized for the respective application.

In die Fig. 9 sind jeweils die Meßergebnisse zweier Messungen, M1 und M2, mit den aus den Zugehörigkeitsfunktionen resultierenden Zugehörigkeitswerten eingetragen. Bei der Messung M1 handelt es sich um eine Banknote mit geringer Verschmutzung, relativ vielen Eselsohren und wenig Flecken. Bei der Messung M2 ist die Verschmutzung stärker als bei der Messung M1 und sie weist mehr Eselsohren auf. Weiterhin zeigt sie weniger Flecken als die Messung M1.FIG. 9 shows the measurement results of two measurements, M 1 and M 2 , with the membership values resulting from the membership functions. Measurement M 1 is a banknote with little contamination, a relatively large number of dog ears and few stains. The measurement M 2 is more dirty than the measurement M 1 and it has more dog ears. Furthermore, it shows fewer spots than the measurement M 1 .

Mittels der Fuzzyklassen wird eine Regelmatrix definiert, die in der Fig. 10. dargestellt ist. In den Spalten der Regelmatrix sind die möglichen Kombinationen der einzelnen Klassen der Eigenschaften "Verschmutzung", "Eselsohr" und "Flecken" aufgetragen. Die letzte Spalte der Regelmatrix bildet eine Eigenschaft "Sortierung" mit drei Fuzzyklassen, die mit "Stapler", "Shredder" und "Reject" bezeichnet werden. In den Zeilen der Regelmatrix ist jeweils eine Regel 1 bis 8 aufgetragen, die jeweils einer möglichen Kombination von Fuzzyklassen der drei Eigenschaften einer Fuzzyklasse der Eigenschaft "Sortierung" zuordnet. Unter der jeweiligen Bezeichnung der Fuzzyklasse ist jeweils der in Fig. 9 ermittelte Zugehörigkeitswert zu den Messungen M1 und M2 angegeben. Die Ermittlung der zu den Fuzzyklassen der Eigenschaft "Sortierung" angegebenen Werte wird im folgenden noch erläutert.A rule matrix is defined by means of the fuzzy classes, which is shown in FIG. 10. The possible combinations of the individual classes of the properties "pollution", "dog-ear" and "stains" are plotted in the columns of the rule matrix. The last column of the rule matrix forms a "Sorting" property with three fuzzy classes, which are called "Stacker", "Shredder" and "Reject". A rule 1 to 8 is plotted in the rows of the rule matrix, each of which assigns a possible combination of fuzzy classes of the three properties of a fuzzy class to the "sorting" property. Under the respective designation of the fuzzy class, the membership value determined in FIG. 9 to the measurements M 1 and M 2 is given. The determination of the values specified for the fuzzy classes of the "sorting" property is explained below.

Verbal lassen sich die Regeln der Regelmatrix wie folgt darstellen. Die Regel 1 sagt beispielsweise, daß eine Banknote mit geringer Verschmutzung, vielen Eselsohren und wenig Flecken der Fuzzyklasse "Reject" einer Eigenschaft "Sortierung" zugewiesen werden soll. Gemäß Regel 2 wird einer Banknote mit mittlerer Verschmutzung, vielen Eselsohren und wenig Flecken der Fuzzyklasse "Shredder" der Eigenschaft "Sortierung" zugewiesen usw. Die Regelmatrix ist hier auf 8 Regeln begrenzt, da bei den Messungen M1 und M2 keine weiteren sinnvollen Kombinationen auftreten. Prinzipiell ist es jedoch nicht notwendig, daß die Regelmatrix Regeln für alle möglichen Kombinationen enthält. Es genügt, wenn diese lediglich Regeln für relevante Kombinationen enthält.The rules of the rule matrix can be represented verbally as follows. Rule 1 says, for example, that a banknote with little soiling, many dog ears and little stains of the fuzzy class "Reject" should be assigned to a "Sorting" property. According to rule 2, a banknote with medium soiling, many dog ears and few stains is assigned to the "sorting" property of the "shredder" fuzzy class, etc. The rule matrix is limited to 8 rules here, since the measurements M 1 and M 2 do not contain any other useful combinations occur. In principle, however, it is not necessary for the rule matrix to contain rules for all possible combinations. It is sufficient if it only contains rules for relevant combinations.

Zur Ableitung einer Sortierklasse einer Banknote wird, wie in Fig. 11 dargestellt, zunächst auch jeder Fuzzyklasse der Eigenschaft "Sortierung" eine entsprechende Zugehörigkeitsfunktion zugeordnet.To derive a sorting class of a banknote, as shown in FIG. 11, First, each fuzzy class of the "Sorting" property has a corresponding one Membership function assigned.

Aus den Fuzzyklassen mit ihren Zugehörigkeitsfunktionen und der Regelmatrix werden zunächst mittels einer sogenannten Inferenzmaschine die resultierenden Fuzzyklassen "Stapler", "Shredder", "Reject" der Sortierung abgeleitet.From the fuzzy classes with their membership functions and the rule matrix the resulting are first of all using a so-called inference machine Fuzzy classes "Stacker", "Shredder", "Reject" of the sorting derived.

Man erhält die aus den Regeln resultierenden Fuzzyklassen der Eigenschaft "Sortierung", indem man zunächst, wie in Fig. 10 gezeigt, die entsprechenden Zugehörigkeitswerte der Meßergebnisse innerhalb einer Regel miteinander verknüpft und das Ergebnis der Verknüpfung der Sortierung zuordnet. Hier wurde als einfacher Fall für eine Verknüpfung die Auswahl des kleinsten Zugehörigkeitswertes gewählt (jeweils eingerahmt).The fuzzy classes of the property resulting from the rules are obtained "Sort" by first, as shown in Fig. 10, the appropriate Membership values of the measurement results within one rule linked and assigns the result of the linking to the sorting. Here, as a simple case for a link, the selection of the lowest membership value selected (framed in each case).

In Fig. 12 ist beispielsweise die aus den entsprechenden Regeln resultierende Fuzzyklasse "Shredder" der Eigenschaft "Sortierung" dargestellt. Die Zugehörigkeitsfunktion der Fuzzyklasse "Shredder" wird gemäß dem Ergebnis der Verknüpfung in der Regel in der entsprechenden Höhe abgeschnitten. Die Fig. 12a und 12b zeigen diesen Vorgang für die Ergebnisse der Messung M2 der Regel 4. Gemäß der in Fig. 10 dargestellten Regelmatrix liefert die Regel 4 für die Messung M2 und die Fuzzyklasse "Shredder" der Eigenschaft "Sortierung" den Wert 0.2. Folglich wird die Zugehörigkeitsfunktion der Fuzzyklasse "Shredder" bei dem Wert 0.2 abgeschnitten. Die so erhaltenen Anteile der einzelnen Regeln werden miteinander verknüpft. Hier wurde der Einfachheit halber als Verknüpfung die maximal abgedeckte Fläche der einzelnen Teilflächen gewählt. Das Resultat der Verknüpfung ist in Fig. 12c dargestellt.12 shows, for example, the fuzzy class "shredder" of the "sorting" property resulting from the corresponding rules. The membership function of the fuzzy class "Shredder" is usually cut off at the corresponding height according to the result of the link. 12a and 12b show this process for the results of the measurement M 2 of rule 4. According to the rule matrix shown in FIG. 10, rule 4 supplies the value for the measurement M 2 and the fuzzy class "shredder" of the "sorting" property 0.2. As a result, the membership function of the fuzzy class "Shredder" is cut off at the value 0.2. The parts of the individual rules thus obtained are linked to one another. For the sake of simplicity, the maximum covered area of the individual partial areas was chosen here as a link. The result of the link is shown in Fig. 12c.

Führt man das analoge Verfahren für alle Fuzzyklassen der Eigenschaft "Sortierung" und alle Regeln durch, erhält man für die Messung M1 und die Messung M2 die in Fig. 13a und 13b dargestellten resultierenden Fuzzyklassen der Eigenschaft "Sortierung" mit ihren Zugehörigkeitsfunktionen. Das in Fig. 12c beispielsweise ermittelte Ergebnis findet sich hier in der Fig. 13b wieder.If the analogous method is carried out for all fuzzy classes of the “sorting” property and all rules, the resulting fuzzy classes of the “sorting” property with their membership functions are shown for the measurement M 1 and the measurement M 2 . The result determined in FIG. 12c, for example, can be found here in FIG. 13b.

In einem letzten Schritt muß aus den resultierenden Fuzzyklassen der Eigenschaft "Sortierung" eine diskrete Sortierklasse abgeleitet bzw. die Eigenschaft "Sortierung" defuzzifiziert werden. Eine einfache Möglichkeit für eine solche Ableitung ist es, dem Blattgut die Sortierklasse zuzuordnen, dessen Fuzzyklasse die größte Fläche aufweist. Für den Fall der Meßergebnisse M1 würde dem Blattgut somit die Sortierklasse "Reject" zugeordnet und dem Blattgut mit den Meßwerten M2 die Sortierklasse "Shredder".In a final step, a discrete sorting class must be derived from the resulting fuzzy classes of the "sorting" property or the "sorting" property must be defuzzified. A simple possibility for such a derivation is to assign the sorting class to the sheet material whose fuzzy class has the largest area. In the case of the measurement results M 1 , the sorting class "Reject" would be assigned to the sheet material and the sorting class "Shredder" would be assigned to the sheet material with the measured values M 2 .

Eine aufwendigere Methode zur Ableitung der Sortierklasse aus den resultierenden Fuzzyklassen der Eigenschaft "Sortierung" besteht beispielsweise darin, zunächst jeweils die einzelnen resultierenden Fuzzyklassen "Stapler", "Shredder", "Reject" der Eigenschaft "Sortierung" miteinander beispielsweise durch Vereinigung zu verknüpfen und aus der resultierenden Fläche die Lage des Schwerpunkts zu berechnen. Durch Rundung kann dieser Wert auf eine diskrete Sorfierklasse abgebildet werden.A more elaborate method for deriving the sorting class from the resulting ones For example, there are fuzzy classes of the "Sorting" property first of all the individual resulting fuzzy classes "stacker", For example, "Shredder", "Reject" of the "Sorting" property to link by union and from the resulting area the To calculate the location of the center of gravity. By rounding this value up a discrete Sorfier class can be mapped.

Selbstverständlich ist es möglich, weitere bereits aus dem Stand der Technik bekannten Möglichkeiten im Umgang mit Fuzzylogik auf das Problem der Bearbeitung von Blattgut im oben beschriebenen Sinne zu übertragen. Of course, it is possible to have more from the prior art Known ways of dealing with fuzzy logic on the problem of Processing of sheet material in the sense described above.

Analog zum ersten Ausführungsbeispiel des Verfahrens ist es auch hier möglich, die einzelnen Regeln mit Sicherheitsleveln zu versehen. Auch die Nutzung von Gewichten für eine jede Klasse ist möglich, indem man beispielsweise die jeweilige Zugehörigkeitsfunktion einer Fuzzyklasse mit dem entsprechenden Gewicht, beispielsweise durch Multiplikation, verknüpft. Die Behandlung des Sicherheitslevels und der Gewichte kann analog zum ersten Ausführungsbeispiel erfolgen.It is analogous to the first exemplary embodiment of the method possible to provide the individual rules with security levels. Also the Use of weights for each class is possible, for example, by the respective membership function of a fuzzy class with the corresponding weight, for example by multiplication. The treatment of the safety level and the weights can be analogous to first embodiment.

Claims (16)

  1. An apparatus for processing sheet material such as bank notes having
    a singler unit for singling the sheet material from a stack sheet for sheet,
    a transport unit (30) for transporting the singled sheets through the apparatus,
    a plurality of sensor units (20.1 - 20.N) each having a measuring unit (21.1 - 21.N) and an evaluation unit (22.1 - 22.N) for determining measuring results for each sheet,
    a central evaluation unit (10) for assigning a certain destination unit to each sheet using the measuring results from the sensor units,
    a plurality of destination units in which sheets are stacked or destroyed,
    a control unit (40) for controlling and/or logging the processing operation on the sheets, and
    a connection for data exchange between the units,
       characterized in that
    at least one sensor unit (20.n) is provided with a memory in which at least one data record is managed,
    said data record being provided with at least one area (ED) in which data from at least one other sensor unit can be stored.
  2. The apparatus of claim 1, characterized in that data records of a plurality of sheets are managed in the memory of at least one sensor unit (20.n).
  3. The apparatus of claim 1, characterized in that the memory of the sensor unit (20.n) is provided in the evaluation unit (22.n) of the sensor unit (20.n).
  4. The apparatus of claim 1, characterized in that each data record is provided with areas (MD, ME) in which the measuring data determined by the measuring unit of the sensor unit (20.n) and/or the measuring results determined by the evaluation unit of the sensor unit (20.n) can be stored.
  5. The apparatus of claim 1, characterized in that the central evaluation unit (10) is provided with a memory in which data records of a plurality of sheets are managed, each data record being provided with areas (ME) in which the measuring results of the sensor units (20.1 - 20.N) for a certain sheet can be stored.
  6. The apparatus of claim 5, characterized in that the central evaluation unit is provided with a memory in which freely configurable tables and/or matrixes are managed which are used for deriving a sort class of a sheet.
  7. The apparatus of claim 5 or 6, characterized in that means are provided for deriving a sort class for a certain sheet from the measuring results of the sensor units for this sheet.
  8. The apparatus of claim 5, characterized in that each data record is provided with an area (SK) in which a sort class of the sheet can be stored.
  9. The apparatus of claim 1, characterized in that the transport unit (30) has a plurality of decentralized subunits (30.1 - 30.M).
  10. The apparatus of claim 9, characterized in that each subunit (30.1 - 30.M) controls a partial portion of a transport path of the transport unit (30).
  11. The apparatus of claim 9, characterized in that each subunit (30.1 - 30.M) controls a certain unit of the apparatus.
  12. The apparatus of claim 1, characterized in that the connection for data exchange (100) is a data bus.
  13. The apparatus of claim 12, characterized in that the data bus is a CAN bus.
  14. The apparatus of claim 12, characterized in that further connections (101, 102) at least partly connecting the units are disposed in parallel to the connection for data exchange (100).
  15. The apparatus of claim 14, characterized in that the further connections (101, 102) are data buses.
  16. A method for processing sheet material such as bank notes, characterized in that data from at least one other sensor unit are stored in at least one sensor unit, and the derivation of at least one measuring result of the sensor unit is performed using the stored data from the at least one other sensor unit.
EP96919717A 1995-05-11 1996-05-08 Device and process for processing sheet articles such as bank notes Expired - Lifetime EP0824735B1 (en)

Priority Applications (1)

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EP01120428A EP1168252A3 (en) 1995-05-11 1996-05-08 Device and method for handling sheets, in particular banknotes

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DE19517347 1995-05-11
DE19517347 1995-05-11
PCT/EP1996/001930 WO1996036931A2 (en) 1995-05-11 1996-05-08 Device and process for processing sheet articles such as bank notes

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EP01120428A Division EP1168252A3 (en) 1995-05-11 1996-05-08 Device and method for handling sheets, in particular banknotes

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EP0824735B1 true EP0824735B1 (en) 2002-03-06

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EP96919717A Expired - Lifetime EP0824735B1 (en) 1995-05-11 1996-05-08 Device and process for processing sheet articles such as bank notes

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EP (2) EP1168252A3 (en)
JP (1) JPH11506555A (en)
CN (1) CN1078724C (en)
AT (1) ATE214182T1 (en)
AU (1) AU5815896A (en)
DE (2) DE59608844D1 (en)
ES (1) ES2171685T3 (en)
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EP0824735A2 (en) 1998-02-25
US6074081A (en) 2000-06-13
DE59608844D1 (en) 2002-04-11
RU2168210C2 (en) 2001-05-27
WO1996036931A3 (en) 1997-02-20
ES2171685T3 (en) 2002-09-16
EP1168252A3 (en) 2004-12-29
WO1996036931A2 (en) 1996-11-21
CN1078724C (en) 2002-01-30
AU5815896A (en) 1996-11-29
CN1187894A (en) 1998-07-15
DE19618541A1 (en) 1996-11-14
ATE214182T1 (en) 2002-03-15
JPH11506555A (en) 1999-06-08
US6151534A (en) 2000-11-21
EP1168252A2 (en) 2002-01-02

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