METHOD FOR MONITORING AN AUTOMATION SYSTEM

Abstract

The invention relates to a method for monitoring a process automation system, a plurality of measuring points being provided in the system, said method comprising: detecting movements, of people located within the system and/or objects, especially robots, vehicles and/or machines, which are not located at the measuring points; calculating stay data containing moments of the stay and/or the respective duration of the stay, the respective people and/or objects at the individual measuring points on the basis of the detected movements; and evaluating the stay data in terms of defined noticeable problems.

Claims

1-14. (canceled)

15. A method for monitoring a process automation system, wherein a plurality of measuring points is provided in the system, comprising: detecting movements of people located within the system or of objects not located at the measuring points, vehicles, or machines; calculating stay data containing moments of the stay and/or the respective duration of the stay, the respective people, or objects at the individual measuring points on the basis of the detected movements; and evaluating the stay data in terms of defined noticeable problems.

16. The method of claim 15, wherein the stay data is stored in a database.

17. The method of claim 15, wherein the stay data are visualized in the course of the evaluation in a diagram in which the number of moments of stay or the duration of stay of the people or of objects at a respective measuring point, is represented cumulatively.

18. The method of claim 15, wherein the people or the objects are grouped by distinguishing features.

19. The method of claim 18, wherein the people are grouped based on authority or role, wherein the authority or the role is defined in a distinguishing feature which is attached to the respective person.

20. The method of claim 18, wherein the objects are grouped in the system according to the type of component and/or based on the function of the component.

21. The method of claim 15, wherein the stay data is evaluated automatically, wherein the result of the evaluation is output to an operator.

22. The method of claim 21, wherein the stay data is evaluated automatically with respect to at least one of the following noticeable problems: cumulative stay duration of people or at least one specific measuring point; cumulative number of moments of people or objects at least one specific measuring point; or stay of people or objects in a restricted area of the system.

23. The method of claim 15, wherein a prediction with regard to an expected cumulative stay time at least one measuring point is calculated.

24. The method of claim 15, wherein the stay data are filtered before the evaluation or after the evaluation with respect to at least one of the following features: filtering with respect to at least one distinguishing feature; filtering with respect to at least one defined time period; and filtering with respect to at least one measuring point.

25. The method of claim 15, wherein the stay data are linked before the evaluation to at least one data set of the following data: weather data; production data; and financial data.

26. The method of claim 25, wherein the stay data are evaluated with respect to at least one of the following noticeable problems: at least one temperature range or a specific temperature; at least one production date, or a production period of components of the measuring points; and with respect to the maintenance costs of the measuring points.

27. The method of claim 15, wherein movements are detected on the basis of at least one of the following methods: evaluating video images recorded by means of at least one video camera arranged in the system; collecting GPS data, wherein the people or the objects are respectively equipped with at least one GPS module; and detecting movements using at least one infrared motion detector arranged in the system.

28. The method of claim 15, wherein the stay data additionally comprise trajectories of the individual persons or objects.

Description

[0052] The invention is explained in greater detail with reference to the following Figures. The following is shown:

[0053] FIG. 1: an exemplary embodiment of the method according to the invention; and

[0054] FIG. 1 shows an exemplary embodiment of the method according to the invention. Parts of a process automation system A are depicted in this illustration. Specifically, three measuring points MS1, MS2, MS3 are involved. These respectively consist of a tank and a pipeline which discharges from the tank. In order to measure the fill level of the tank, a field device FG, for example a fill level measuring device using radar, is mounted on the tank. In order to measure the flow rate in the pipeline, a respective field device FGis mounted, for example a flow meter according to the Coriolis principle.

[0055] The measuring points MS1, MS2, MS3 and the space located between the measuring points MS1, MS2, MS3 are recorded by at least one video camera VK. The recorded photos/videos are transmitted to a database DB. This exists especially on a cloud platform and can be contacted by an operator by means of the Internet. The database DB is connected to an application AP which evaluates the recordings.

[0056] The purpose of the recording is to collect stay data of people P1, P2, P3 of objects which stay in the system A, and to evaluate the stay data for noticeable problems. In the example shown in FIG. 1, two service technicians P1, P2 as well as a supplier P3 are currently in the system A. The application AP groups these three persons P1, P2, P3 using distinguishing features. Specifically, in this instance this involves the helmets of the people P1, P2, P3. The color of the helmet defines the role of the people P1, P2, P3 in the system A. Black hereby signifies the role of service technician; white hereby stands for the role of supplier.

[0057] The trajectories T1, T2, T3 of the people P1, P2, P3, and the moments of the stay and the duration of the stay by the people P1, P2, P3 at the measuring points MS1, MS2, MS3, are hereby recorded. The service technician P1 is on a routine tour to the individual measuring points MS1, MS2, MS3, wherein the service technician P2 is on the way to the measuring point MS2 where a problem has occurred, and wherein the supplier P3 is on the way to the measuring point MS2 to fill the tank.

[0058] The stay data determined in this way are likewise stored in the database DB. The stay data located in the database DB are evaluated by means of the application AP.

[0059] In a first step, the stay data are filtered. The filtering relates, for example, to a defined time period and/or to a defined role of people P1, P2, P3, and/or to one or more measuring points MS1, MS2, MS3.

[0060] The filtered stay data are then examined for noticeable problems. Such noticeable problems are, for example, a cumulative occurrence of a specific group of people at a measuring point MS1, MS2, MS3. It is also possible to check whether certain groups of people visit the measuring points MS1, MS2, MS3 at regular intervals.

[0061] In this way, it is possible to determine noticeable problems in the system A which cannot be determined by means of diagnostic values of the field devices FG, FG, or in order to clarify diagnostic cases. For example, measured values of a flow meter which outside a defined standard interval could thus be explained in that a pipeline is clogged, for example. The cause can be determined from the stay data. For example, it could be apparent that the service technician P1 is at the respective measuring point MS1, MS2, MS3 at regular intervals, especially within the scope of the maintenance routinefor example in order to knock on the pipe with an object, which removes accretion inside the pipe. From the stay data, it is clear that the service technician P1 had not been to the measuring point MS1, MS2, MS3 for a longer period of time before the fault occurred, as a result of which the accretion in the interior of the pipe had not been loosened.

[0062] Advantageously, the stay data can be linked to further data sets, for example weather data, prognosis data, financial data, and/or to position data of the field devices. In this way, additional findings can be obtained.

LIST OF REFERENCE SYMBOLS

[0063] A System

[0064] AP Application

[0065] DB Database

[0066] EM Distinguishing features

[0067] FG, FG Field devices

[0068] MS1, MS2, MS3 Measuring points

[0069] P1, P2, P3 People

[0070] TJ1, TJ2, TJ3 Trajectories

[0071] VK Video camera