METHOD AND DEVICE FOR DETECTING A WEB BREAK OF A FIBROUS WEB, INDUSTRIAL PLANT AND COMPUTER PROGRAM PRODUCT

Abstract

A method for monitoring an industrial plant. In a first part of the industrial plant, first parameters are provided. The industrial plant is used to produce and/or process a fibrous material web. Second parameters are provided in a second part. The parameters are stored, preferentially as time series. In the case of a web break in the second part, the second parameters are first analyzed for a second anomaly. If no second anomaly can be detected, the first parameters are analyzed for a first anomaly. During the analysis, the parameters which were stored in a time range before the web break are preferably examined. If a first or second anomaly is detected, these, and optionally measures to avoid such web breaks, are displayed to the user. Optionally, the first parameters and/or the second parameters can be set so as to avoid future web breaks.

Claims

1. A method for monitoring an industrial plant for a web break of a fibrous material web, wherein the industrial plant serves for producing and/or processing the fibrous material web, wherein the industrial plant comprises a first part, in particular a wet part, and a second part, in particular a dry section, wherein the method comprises: determining and storing first parameters of the first part and second parameters of the second part, analyzing the second parameters for a second anomaly, when it is observed that no second anomaly is present in the second parameters, an analysis of the first parameters for a first anomaly is performed; when the first anomaly is observed in the first parameters, the first anomaly is displayed to a user.

2. The method as claimed in claim 1, wherein the analysis of the first parameters and/or of the second parameters is performed after a web break of the fibrous material web.

3. The method as claimed in claim 1, wherein, when a first anomaly of the first parameters or a second anomaly of the second parameters is observed, a change of the second parameters is performed such that a web tension of the fibrous material web is reduced.

4. The method as claimed in claim 1, wherein, when a first anomaly of the first parameters is observed, a change of the first parameters is performed such that a maximum tension assumes a sufficiently high value such that no web break occurs in the case of correct functioning of the second part.

5. The method as claimed in claim 1, wherein the analysis of the second parameters comprises the following steps: calculating the web tension of the material web from the second parameters; comparing the web tension with a maximum tension, wherein the second anomaly is present if the web tension overshoots the maximum tension.

6. The method as claimed in claim 4, wherein the maximum tension is calculated on the basis of the first parameters.

7. The method as claimed in claim 1, wherein the respective first parameter and/or the respective second parameter are stored as a time series.

8. The method as claimed in claim 1, wherein the respective first parameters and/or the respective second parameter are stored as a function of the time and wherein the respective first parameters and/or the respective second parameters are analyzed with the aid of an algorithm based on artificial intelligence.

9. The method as claimed in claim 1, wherein, when the first anomaly and/or the second anomaly are/is observed, a possibility for avoiding the respective anomaly is displayed.

10. The method as claimed in claim 1, wherein the first parameters and/or the second parameters are stored in a data memory and/or a cloud storage, in each case as a function of the time.

11. The method as claimed in claim 1, wherein the stored first parameters and/or the stored second parameters serve for the adaptation of the algorithm that is based on artificial intelligence.

12. The method as claimed in claim 1, wherein, in the event of a web break, the first parameters and/or the second parameters that lie in a time range preceding the web break are analyzed in order to identify a pattern, wherein, in the event of a later occurrence of such a pattern, a warning signal is output to the user.

13. A non-transitory computer readable medium comprising: computer program instructions stored therein for carrying out a method according to claim 1 when the computer program instructions are executed on a processing unit.

14. A device for monitoring an industrial plant, wherein the device comprises: an interface for receiving first parameters and/or second parameters, a processing unit for analyzing first parameters for a first anomaly and/or second parameters for a second anomaly, optionally a display for interaction with a user, and an interface for the provision of settings for the industrial plant, wherein the device is configured for carrying out a method as claimed in claim 1.

15. An industrial plant, comprising: a device as claimed in claim 14.

16. The industrial plant of claim 15, wherein the industrial plant comprises a paper machine.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0119] In the figures:

[0120] FIG. 1 shows an industrial plant,

[0121] FIG. 2 shows sensors, encoders and time series, and

[0122] FIG. 3 shows a possible method.

DETAILED DESCRIPTION OF INVENTION

[0123] FIG. 1 shows an industrial plant 100. The industrial plant comprises a first part 100a and a second part 100b. The first part 100a is configured as a wet part. The first part comprises a vessel 5. The vessel 5 serves for providing a fibrous solution. The fibrous solution is provided via pipes 6 to a multiplicity of nozzles D1, D2, D3. The respective nozzle D1, D2, D3 serves for applying the fibrous solution to a wire section 2. The wire section serves for separating the fibers from the solution. The fibers are provided in the form of a fiber mat to a press section 3. The press section 3 forms the fibrous material web 1. The fibrous material web is provided to the second part 100b of the industrial plant 100.

[0124] The second part 100b is configured as a dry section 4. The dry section comprises a multiplicity of rollers, wherein the respective roller is coupled to a drive M.

[0125] At least some of the drives M are coupled to an encoder G1, . . . , G4. The respective encoder G1, . . . , G4 serves for acquiring the respective rotational speed of the respective drive M.

[0126] The fibrous material web 1 passes through the dry section and is rolled up on a roller 15. A control device SE serves for controlling the respective drive M. The control device SE serves for the open-loop or closed-loop control of the respective torque and/or of the respective rotational speed of the respective drive M.

[0127] The control device advantageously comprises a closed-loop control device RE. The closed-loop control device RE serves for the closed-loop control of first parameters x1, . . . , xn and/or second parameters y1, . . . , yn.

[0128] A first parameter x1, . . . , xn may be the opening of the respective nozzle D1, D2, D3, a temperature of the fibrous solution or the pressure of the fibrous solution in the pipes 6.

[0129] A second parameter y1, . . . , yn is advantageously a temperature in the dry section 4, a torque of a drive M or a rotational speed of a drive M.

[0130] Exemplary functioning of the industrial plant 100: the fibrous solution is sprayed by the respective nozzle D1, D2, D3 onto a fiber mat. The fiber mat with the fibers is fed to a press section 3. The press section 3 serves for forming the fibrous material web 1. The fibrous material web is subsequently dried in the dry section 4. In the dry section 4, the fibrous material web 1 runs over the multiplicity of rollers and is dried further. In the dry section, a web break can occur in the event of a high tensile load, that is to say a high web tension B, of the fibrous material web 1.

[0131] In the event of a web break, the industrial plant is generally stopped, and a fault is eliminated manually.

[0132] In order to avoid further web breaks, an evident reason for the web break is ascertained by means of the following exemplary method (see FIG. 3).

[0133] FIG. 2 shows sensors S1, . . . Sn, encoders G1, . . . , Gn and time series 16a, . . . , 16n, 17a, . . . 17n. The sensors S1, . . . , Sn advantageously provide first parameters x1, . . . , xn. The encoders G1, . . . , Gn are advantageously respectively assigned to a drive M and/or to a roller. The respective encoder G1, . . . , Gn generally provides second parameters y1, . . . , yn.

[0134] The first parameters x1, . . . , xn and the second parameters y1, . . . , yn are stored as a function of the time t. Advantageously, the parameters x1, . . . , xn, y1, . . . , yn are stored in time series 16a, . . . 16n (for first parameters), 17a, . . . , 17n (for second parameters).

[0135] Storage is advantageously performed in a data memory. The data memory is advantageously configured as a cloud.

[0136] FIG. 3 shows a possible method. The possible method comprises a multiplicity of method steps v1, . . . , v8, as discussed below.

[0137] In a first method step v1, the first parameters x1, . . . , xn and/or second parameters y1, . . . , yn are ascertained by sensors S1, . . . , Sn and/or encoders G1, . . . , Gn and are stored. Storage is advantageously performed by storage in a processing unit RE. The processing unit RE may be configured as a so-called edge device and/or as a peripheral server, in particular as a cloud.

[0138] The parameters x1, . . . xn, y1, . . . , yn are advantageously stored as time series 16a, . . . 16n, 17a, . . . , 17n. A timestamp, such as the time of day, advantageously serves for the synchronization of the individual time series 16a, . . . , 17n.

[0139] If a web break F is observed, the second method step V2, and advantageously the further method steps v3, . . . , v8, are performed.

[0140] In the second method step v2, the second parameters y1, . . . , yn are analyzed. It is advantageously the case here that the respective web tension is provided from the rotational speeds and/or the torques of the respective drive M.

[0141] In a third method step v3, the at least one provided web tension is inspected as regards whether a maximum web tension B-max has been overshot. In the event of the maximum web tension B-max being overshot, the reason for the web break F probably lies in the dry section.

[0142] In a fourth method step v4, the overshooting of the maximum web tension B-max is displayed to a user. Furthermore, possibilities can be displayed to the user, by means of which measures web breaks F can be prevented in future.

[0143] Alternatively or in addition, as part of the fourth method step v4, the respective drives M may be controlled in open-loop or closed-loop fashion such that a web break F of said type no longer occurs.

[0144] If the analysis of the second parameters yields that no second anomaly has occurred in the second parameters, then an analysis of the first parameters x1, . . . , xn is performed in a fifth method step v5. Advantageously, in the fifth method step v5, the first parameters x1, . . . , xn are checked for a first anomaly.

[0145] If a first anomaly is observed, the anomaly may be displayed to a user. Measures for eliminating the anomaly may advantageously be displayed to the user. By way of example, such measures may include cleaning a nozzle D1, D2, D3. Alternatively, first parameters x1, . . . , xn may be changed such that the first anomaly is eliminated. A brief temperature increase or a brief pressure increase is for example conceivable here.

[0146] Alternatively or in addition, in the presence of the first anomaly, in a seventh method step v7, the second parameters y1, . . . , yn may be set such that a second anomaly will likely not occur. For example, for this purpose, the rotational speeds and/or the torques of the respective drives are set such that the web tension B is reduced at least in certain regions.

[0147] In an eighth method step v8, it is also possible for a manual analysis of the first parameters x1, . . . , xn and/or of the second parameters y1, . . . , yn to be performed. This analysis is performed for example with the aid of artificial intelligence. By means of such an analysis, it is advantageously possible to identify patterns that arise prior to a web break. By means of the analysis, it is possible to identify factors in the industrial plant 100 for achieving higher operational reliability of the industrial plant.

[0148] In summary, the invention relates to a method for monitoring an industrial plant 100, to a computer program product and to an industrial plant 100. The industrial plant 100 comprises two parts 100a, 100b. The industrial plant 100, configured in particular as a paper machine, serves for producing and/or for processing a fibrous material web 1. In a first part 100a of the industrial plant 100, in particular of a paper machine, first parameters x1, . . . , xn are provided. In a second part 100b, second parameters y1, . . . , yn are provided. The parameters x1, . . . , xn, y1, . . . , yn are advantageously stored as time series 16a, . . . , 16n, 17a, . . . , 17n. In the event of a web break in the second part 100b, it is firstly the case that an analysis of the second parameters y1, . . . , yn for a second anomaly is performed. If no second anomaly can be observed, the first parameters x1, . . . , xn are inspected for a first anomaly. In the analysis, it is advantageously the case that the parameters x1, . . . , yn that were stored in a time range preceding the web break F are inspected. If a first or second anomaly is observed, this, and optionally measures for avoiding such web breaks F, are displayed to the user. The first parameters x1, . . . , xn and/or the second parameters y1, . . . , yn may optionally be set such that web breaks F are avoided in future.