WO2021234083A1

WO2021234083A1 - Method for recording and displaying measurement data

Info

Publication number: WO2021234083A1
Application number: PCT/EP2021/063461
Authority: WO
Inventors: Wladimir DEGTJAREW
Original assignee: Elpro Gmbh
Priority date: 2020-05-21
Filing date: 2021-05-20
Publication date: 2021-11-25
Also published as: EP4154077A1; DE102020113786A1

Abstract

The present invention relates to a method for recording and providing measured values and data, in which measured values and times are first of all recorded. The measured values are then stored in a RAW time grid. A first portion of the data of the recorded measured values is then stored in a first time grid, wherein the first portion of the recorded measured values comprises fewer data than the stored recorded measured values.

Description

VE RFA H R E N Z U M E RFA S E N U N D DA RS TE L L E N VO N

M E S S DAT E N

The present invention relates to a method for acquiring and providing measured values and data, in which first measured values and times are acquired. The measured values are then saved in a RAW time grid. A first part of the data of the recorded measured values is then stored in a first time grid, the first part of the recorded measured values comprising less data than the stored recorded measured values.

It is known to acquire, store and aggregate measured values of a system and to provide the measured values in such a way that they can be represented in a time-resolved manner. A user, in particular a monitor of the system, is thus able to quickly and reliably assess the relevance of the recorded measured values, even over a longer period of time.

The data of the measured values are usually stored in such a way that they require little storage space. This is possible, for example, by means of commercially available permanent storage (HDD and / or SSD), often using compression algorithms. However, in order to display the data of the measured values with the least possible time delay, this space-optimized storage is not optimal. The desired data of the measured values must first be localized on the permanent memory, then loaded into a random access memory (RAM) and, if necessary, decompressed. For the display, it makes more sense to store the data of the measured values with optimized access time, for example in a random access memory (RAM) such as is used as a working memory in a commercially available computer. It is therefore the object of the present invention to provide a method for acquiring and providing measured values with which acquired measured values can be displayed quickly and reliably.

The object is achieved by the method according to claim 1. Further advantageous developments of the invention are set out in the subclaims.

The method according to the invention for acquiring and providing measured values and data has four method steps: In the first method step, measured values are acquired. The measured values can, for example, be physical quantities that are attached to the system to be monitored via sensors. The measured values can also be made available via a network that makes processed measured values available. In the second step, the time is recorded. In order to record the measured values in a time-resolved manner, it is necessary to record the time of receipt of each measured value (time stamp). In the third process step, the recorded measured values are saved in a RAW time grid. The measured values are usually recorded and stored at regular intervals, for example every 10 ms, with each measured variable being able to be sampled in a different time pattern. The RAW time grid therefore contains the individual, unadulterated measured values as they were made available in the first process step. In the fourth method step, a first part of the data of the recorded measured values is stored in a uniform time grid. The uniform time grid is so different from the RAW time grid that the uniform time grid is at least equal to or greater than the smallest RAW time grid. This can be, for example, a 15-minute grid, which is particularly suitable for an energy-efficiency-related consideration of the system, because electricity billing usually takes place in a 15-minute grid. Therefore, according to the invention, the first part of the recorded measured values has less data than the stored recorded measured values and occupies less memory space. In the fifth step, step four can be repeated with a different uniform grid and a different time range, adapted to the application. The storage of the RAW measured values does not necessarily have to take place in the same grid and synchronously with the data acquisition. The measured values can be temporarily stored and bundled in a larger grid (e.g. every 30 seconds) on the hard disk. This greatly reduces the number of hard disk accesses, which not only relieves the load on the computing system, but also increases the service life of the hard disk. The decoupling of the write process on the hard disk from the transfer of the aggregated data in a uniform grid to the main memory (RAM) increases the real-time capability of the system. In a further development of the invention, an output is created from the first part of the stored data of the recorded measured values, which can be viewed at any time as required by a user, for example a supervisor of the monitored facility. For this purpose, at least part of the first part of the stored data of the recorded measured values is read out and transmitted to a graphic output device. In an optional development of the invention, this part of the first part of the stored data of the recorded measured values is used to create an output data record that is output on a graphic output device.

In a further aspect of the invention, the output comprises a graphical output which can be viewed at any time as required by a user, e.g. a supervisor of the monitored facility. Based on the graphical representation of the output, a user can quickly and reliably assess the relevance of the part of the data of the recorded measured values displayed in the output, e.g. whether the monitored system is being operated incorrectly, and make predictions about the behavior of the monitored system.

In a further development of the invention, a control command that executes an action is created from the first part of the stored data of the recorded measured values. This action can include the control of a system, the sensors of which supply the measured values, or another system. For example, with the aid of the control command, the system can be operated in an optimized mode that is recorded with the aid of the recorded measured values. Furthermore, the control command can also be a safety command that switches off the system or parts of it if the measured values show that previously defined or determined limit values are exceeded. For this purpose, at least part of the first part of the stored data of the recorded measured values is read out and transmitted to a control device which creates the control command. In an optional development of the invention, a control data record is created from this part of the first part of the stored data of the recorded measured values, from which a control command is in turn generated. After the control command has been created, the control command is executed. The present invention accelerates all of these processes very much, since the measurement values can be read out and processed much more quickly as a result of the technology used in order to generate a control command.

By reducing the amount of data that arises, the system can use mathematical models to create forecasts over a longer period of time in a uniform grid, which is larger than the smallest scanning grid, which can be used to forward an adapting control command to the control device.

In a further embodiment of the invention, the recorded measured values are stored in a RAW data record. The RAW data set has a RAW data volume. The RAW data record contains the individual, unadulterated measured values as recorded by the system to be monitored. The RAW data volume depends on the number and type of measured values recorded.

In a further development of the invention, the RAW data record is stored on a RAW storage device. The RAW storage device is usually an or several hard drives (HDD and / or SSD) and / or one or more corresponding partitions on such a memory. In addition, compression algorithms can be used that reduce the storage requirements of the RAW data set.

In a further aspect of the invention, the RAW storage device has a RAW write / read speed. The stored data must first be localized on the permanent memory, then loaded into a random access memory (RAM) and, if necessary, decompressed.

In a further embodiment of the invention, the RAW time grid is a variable time grid that can change over time during the recording of a measured value. The recorded measured values are stored together with the RAW time grid in a RAW data record and stored on the RAW storage device. The recorded measured values are therefore assigned to a time grid.

In a further embodiment of the invention, the recorded measured values are stored over a RAW time interval. The RAW time interval can, for example, start with the commissioning of the monitored facility and be continued continuously. It is also possible to start the RAW time interval at a certain point in time, e.g. replacement of a component of the monitored device.

In a further embodiment of the invention, the recorded measured values are stored in a space-optimized manner. In particular, one or more permanent memories (HDD and / or SSD) and / or one or more corresponding partitions on such a memory are used. In addition, compression algorithms can be used that reduce the storage requirements of the RAW data set. The requirements of the method according to the invention on the read-only memories are thereby kept as low as possible. In a further embodiment of the invention, the first part of the data of the recorded measured values is stored in a first data record. The data record can be viewed by a user, for example a supervisor of the monitored facility, at any time as required. In a further development of the invention, the first part of the data of the recorded measured values is stored with optimized access time, for example on a read-only memory with fast access time (SSD), usually without the use of compression algorithms.

In a further embodiment of the invention, the first part of the data of the recorded measured values is aggregated and / or calculated from the recorded measured values. In addition to the latest recorded measured value, the first part of the data of the recorded measured values also contains previously recorded measured values that were uniformly aggregated at a specified time interval.

In a further embodiment of the invention, a second part of the data of the recorded measured values is stored. The second part of the data of the recorded measured values differs with regard to the recorded measured values in its time grid (e.g. 10 second grid), time interval (e.g. the data from 1.1.2019 to 3.11.2019), the type of measurement data and / or its data volume from the first part of the data of the recorded measured values. For the purposes of the invention, types of measured values differ in the source of the measured values, in their physical or chemical size, in their unit and / or in other features.

In a further development of the invention, a third part and further parts of the data of the recorded measured values are stored. The third part and the other parts of the data of the recorded measured values differ with regard to the recorded measured values in their Time grid, time interval, the type of measurement data and / or their data volume from the other parts of the data of the recorded measurement values.

In a further embodiment of the invention, the parts of the data of the recorded measured values are stored on a first storage device. The storage device can in particular be arranged remotely from the RAW storage device, e.g. on a remote server and / or a mobile computer (notebook computer).

In a further embodiment of the invention, the data volumes of the data sets of the parts of the data of the recorded measured values are smaller than the data volume of the RAW data set. The parts of the data of the recorded measured values differ from the RAW data set, in particular with regard to their larger time pattern and the smaller time interval, and therefore have a smaller data volume. The requirements of the method according to the invention on the storage devices are thereby kept as low as possible.

In a further embodiment of the invention, the time intervals of the parts of the data of the recorded measured values are less than or equal to the RAW. The parts of the data of the recorded measured values differ from the RAW data set, in particular with regard to their larger time pattern and the smaller time interval, and therefore have a smaller data volume. The requirements of the method according to the invention on the storage devices are thereby kept as low as possible.

In a further embodiment of the invention, the time intervals of the parts of the data of the recorded measured values lie in the future relative to the RAW values. The physical quantities that have been transmitted by a measuring device are still up to the RAW time limit, but the calculated values are in the future and thus represent the prognoses. In a further aspect of the invention, the time grid of the parts of the data of the recorded measured values are different from the RAW time grid. The parts of the data of the recorded measured values differ from the RAW data set, in particular with regard to their larger time pattern and the smaller time interval, and therefore have a smaller data volume. The requirements of the method according to the invention on the storage devices are thereby kept as low as possible.

In a further embodiment of the invention, the access speed of the parts of the data of the recorded measured values from the data records of the parts of the data of the recorded measured values is less than or equal to the access speed of the same data from the RAW data record. This can be achieved, for example, by using compression algorithms for storing the RAW data set, but not for storing the data sets of the parts of the data of the recorded measured values and / or by using different hard drives (HDD, SSD) with different access times. The requirements of the method according to the invention for the storage devices and their costs are thereby kept as low as possible.

In a further embodiment of the invention, a first subset of the first part of the data of the recorded measured values is stored in a first sub-data set. A division of the first part of the data of the recorded measured values into a further partial data set allows a user greater flexibility in the presentation of the part of the data of the recorded measured values, in that the user can select a selection of the data of the recorded measured values for display.

In a further development of the invention, the first subset of the first part of the data of the recorded measured values is aggregated and / or calculated from the first part of the data of the recorded measured values. In addition to the latest recorded measurement value, the first Subset of the first part of the data of the recorded measured values also previously recorded measured values that were recorded in a specified time interval.

In a further aspect of the invention, a second subset of the first part of the data of the recorded measured values is stored in a second partial data set. The second subset of the second part of the data of the recorded measured values differs in its time pattern, time interval, type of measured data and / or its data volume from the first subset of the first part of the data of the recorded measured values.

In a further embodiment of the invention, a third and further subset of the parts of the data of the recorded measured values is stored. The third and further subsets of the parts of the data of the recorded measured values differ from the other subsets of the other parts of the data of the recorded measured values in terms of time grid, time interval, type of measured data and / or their data volume. A division of the first part of the data of the recorded measured values into a further partial data set allows a user greater flexibility in the presentation of the part of the data of the recorded measured values, in that the user can select a selection of the data of the recorded measured values for display. It is therefore easier to assess the relevance of the recorded measured values.

In a further embodiment of the invention, subsets of the parts of the data of the recorded measured values are stored on a second storage device. The storage device can in particular be arranged remotely from the RAW storage device and / or the first storage device, e.g. on a remote server and / or a mobile computer (notebook computer).

In a further development of the invention, the subsets of the parts of the data of the recorded measured values are stored in different partial data sets. In a further aspect of the invention, the data volumes of the data sets of the subsets of the parts of the data of the recorded measured values are smaller than the data volumes of the parts of the data of the recorded measured values. The data records of the subsets of the parts of the data of the recorded measured values differ from the parts of the data of the recorded measured values, in particular with regard to their larger time pattern and the smaller time interval, and therefore each have a smaller data volume. The requirements of the method according to the invention on the storage devices are thereby kept as low as possible.

In a further embodiment of the invention, the time intervals of the subsets of the parts of the data of the recorded measured values are less than or equal to the time intervals of the parts of the data of the recorded measured values. The data records of the subsets of the parts of the data of the recorded measured values differ from the parts of the data of the recorded measured values, in particular with regard to their larger time pattern and the smaller time interval, and therefore each have a smaller data volume. The requirements of the method according to the invention on the storage devices are thereby kept as low as possible.

In a further embodiment of the invention, the time raster of the subsets of the parts of the data of the recorded measured values is greater than or equal to the time raster of the parts of the data of the recorded measured values. The data records of the subsets of the parts of the data of the recorded measured values differ from the parts of the data of the recorded measured values, in particular with regard to their larger time pattern and the smaller time interval, and therefore each have a smaller data volume. The requirements of the method according to the invention on the storage devices are thereby kept as low as possible. In a further embodiment of the invention, the second storage device has a shorter access time than the first storage device and the RAW storage device. The second storage device is therefore very well suited for a quick output of the subsets of the parts of the data of the recorded measured values. The second memory device can be, for example, a random access memory (RAM) such as is used as a working memory in a commercially available computer.

In a further embodiment of the invention, the access time of the second storage device (ZZ2) is related to the access time of the first storage device (ZZ1) and the access time of the RAW storage device (RZZ): ZZ2 / RZZ <= ZZ1 / RZZ <= 1.

In a further embodiment of the invention, the storage requirement size of the second storage device (DTG2) is related to the storage requirement size of the first storage facility (DTG1) and the storage requirement size of the RAW storage facility (RDTG): DTG2 <RDTG and DTG2 <DTG1.

In a further embodiment of the invention, the second storage device is different from the first storage device and / or the RAW storage device. In a further development of the invention, the first storage device is different from the second storage device and / or the RAW storage device

In a further advantageous embodiment of the invention, data are read in from a hand-held data record. The data of the hand data set are recorded from an input. The data of the hand data set can in particular be generated by an input of a user. These can be, for example, parameters for scaling the recorded measured values or substitute values for missing or incorrect recorded values

Readings. In a further development of the invention, the data read in from a manual data set replace the data from the parts of the data of the recorded measured values. The data of the hand data set can in particular be generated by an input of a user. These can be, for example, parameters for scaling the recorded measured values or substitute values for missing or incorrect recorded measured values. The incorrect recorded measured values are then replaced by entering the manual data set.

In a further development of the invention, the manual data records are entered for the future and form a basis for plan values.

In a further embodiment of the invention, the recorded measured values are recorded from several and / or different measurement data sources. The measurement data sources can, for example, be different sensors on the system to be monitored. A network of sensors that collects processed measured values is also possible.

In a further embodiment of the invention, the measured values acquired from several measured data sources have different time rasters. The time raster can be chosen arbitrarily. Certain measured values can be recorded at short intervals, e.g. 10ms, others at longer intervals, e.g. 1h.

In a further advantageous embodiment of the invention, the recorded measured values are (initially) recorded in a measured value pool. The measured value pool acts as an intermediate memory (buffer memory) in which the recorded measured values are temporarily stored before they are distributed to other storage devices. In particular, write / read processes are facilitated or made possible in this way. The writing and reading processes can be decoupled in time. In a further embodiment of the invention, the recorded measured values are assigned a time in the measured value pool. The recorded measured values are therefore assigned to a time stamp in order to be able to understand when each individual measured value was recorded.

In a further embodiment of the invention, the measured value pool distributes the recorded measured values to different storage devices.

In a further development of the invention, parts of the data of the recorded measured values are read out from the RAW data record and the measured value pool.

The method according to the invention is carried out by means of a computer program product that is loaded in the memory of a computing / processing device.

Exemplary embodiments of the method according to the invention are shown in the drawings in a schematically simplified manner and are explained in more detail in the following description.

Show it:

1: An exemplary embodiment of the method according to the invention with three different data records that can be displayed

2: Another exemplary embodiment of the method according to the invention with data records stored in an access time-optimized manner

3: Another exemplary embodiment of the method according to the invention with measured values from five different measured value sources 4: Another exemplary embodiment of the method according to the invention, a manual data record being generated by means of a user input

5: Another embodiment of the method according to the invention with four displayable partial data sets

1 shows the method according to the invention, three data sets DS1, DS2, DS3 being created. The measured values M1, M2, M3 recorded in the data records DS1, DS2, DS3 have different contents. In this exemplary embodiment, measured values X are only acquired from one measured data source. In principle, however, several measured values X can also be recorded from several different measurement data sources, which can have the same or different time rasters.

The recorded measured values RM are stored together with the RAW time grid RZ in a RAW data record RD and stored on the RAW storage device RS. The recorded measured values are therefore assigned to a time grid. The RAW storage device RS is usually one or more permanent memories (HDD and / or SSD) and / or one or more corresponding partitions on such a memory. In addition, compression algorithms can be used that reduce the storage requirements of the RAW data record RD.

The recorded measured values RM are stored over a RAW time interval. The RAW time interval can, for example, start with the commissioning of the monitored facility and be continued continuously. It is also possible to start the RAW time interval at a certain point in time, e.g. replacement of a component of the monitored device.

In this exemplary embodiment, three parts of the data of the recorded measured values M1, M2, M3 are calculated from the RAW data record. In particular, differ the three parts of the data of the recorded measured values M1, M2, M3 in their time grid, the time interval, possibly the type of measurement data and thus also in their data volume. For example, the first part of the data of the recorded measured values M1 can have a series of measurements of the measured value X with a time frame of 10 ms in a time interval of 1 minute, the second part of the data of the recorded measured values M2 can have the same or a different measured value X with a time frame of 100 ms in the time interval of 1h and the third part of the data of the recorded measured values M3 have the same or a different measured value X with a time grid of 1min in a time interval of 1d. The parts of the data of the recorded measured values M1, M2, M3 therefore have less data than the RAW data record RD stored on the RAW storage device RS and therefore individually occupy less storage space than the RAW data record RD.

These three parts of the data of the recorded measured values M1, M2, M3 are each stored in a data record DS1, DS2, DS3. Analogous to the data of the recorded measured values M1, M2, M3 stored in the data records DS1, DS2, DS3, the individual data volumes of the data records DS1, DS2, DS3 are smaller than the data volume of the RAW data record RD and occupy less storage space. The three data sets DS1, DS2, DS3 can be displayed at any time by means of a graphic output. A user, e.g. a supervisor of the monitored facility, is able to reliably determine the actual state, the history and the development of the monitored facility over time at any time due to the method according to the invention.

An exemplary embodiment of the method according to the invention, in which data records are stored with optimized access time, is shown in FIG. 2. In this exemplary embodiment, measured values X are only acquired from one measurement data source. The recorded measured values RM with their different time patterns are transferred to a measured value pool MT and temporarily stored there. In addition, each recorded measured value RM is given a time stamp in order to be able to understand when the individual measured value RM was recorded. The storage of the recorded measured values RM in the measured value pool MT is particularly useful when the scanning raster contains one or more measured values X or recorded measured values RM are small, e.g. less than 100 ms. The recorded measured values RM are stored together with the RAW time grid RZ in a RAW data record RD and stored on the RAW storage device RS.

The RAW data record RD is then aggregated AT. While unadulterated measured values X are stored in the RAW data record RD together with their time stamp, the aggregated data record AT has not only the latest recorded measured value RM but also recorded measured values RM in a specific time grid depending on the time grid of the data records DS1, DS2, DS3. The recorded measurement data are saved in the RS and AT databases in a space-optimized manner. In particular, one or more permanent memories (HDD and / or SSD) and / or one or more corresponding partitions on such a memory are used. In addition, compression algorithms can be used that reduce the storage requirements of the RAW data record RD.

In this exemplary embodiment, three parts of the data of the recorded measured values M1, M2, M3 are calculated from the aggregated data record AT. In particular, the three parts of the data of the recorded measured values M1, M2, M3 differ from one another in their time grid, the time interval, possibly the type of measurement data and thus also in their data volume. For example, the first part of the data of the recorded measured values M1 can have a measured value X with a time pattern of 10 ms in a time interval of 1 min, the second part of the data of the recorded measured values M2 can have the same or a different measured value X with a time pattern of 100 ms in a time interval of 1 hour and the third part of the data of the recorded measured values M3 have the same or a different measured value X with a time pattern of 1 min in the time interval of 1 d. The parts of the data of the recorded measured values M1, M2, M3 therefore have less data than the RAW data set RD stored on the RAW storage device RS and therefore individually occupy less storage space than the RAW data set RD. Due to the time interval of 1d of the data of the recorded measured values M3 selected here as an example, the database AT of the aggregated data has aggregated measured values RM within the last past 24 hours (1d). These three parts of the data of the recorded measured values M1, M2, M3 are each stored in a data record DS1, DS2, DS3. Analogous to the data of the recorded measured values M1, M2, M3 stored in the data records DS1, DS2, DS3, the individual data volumes of the data records DS1, DS2, DS3 are smaller than the data volume of the RAW data record RD and occupy less storage space.

From the data records DS1, DS2, DS3, the subsets of the parts of the data of the recorded measured values TM1, TM2, TM3 are then generated in such a way that the recorded measured values RM are supplemented by, for example, variables calculated thereon and thus for example forecasts or sums or Integrals. But the calculated values always cover the time interval of the data record DSN and do not go beyond the monitored system.

The subsets of the parts of the data of the recorded measured values TM 1, TM2, TM3 are stored in the partial data sets TDS1, TDS2, TDS3. The three partial data records TDS1, TDS2, TDS3 have the same time grid and the same time interval as the data records DS1, DS2, DS3 from which they were generated. The three partial data sets TDS1, TDS2, TDS3 can be displayed at any time by means of a graphic output.

The data records DS1, DS2, DS3 as well as the partial data records TDS1, TDS2, TDS3 are saved with optimized access time in contrast to the RAW data record, e.g. on a permanent storage with fast access time (SSD).

3 shows an exemplary embodiment of the method according to the invention, with measured values X1, X2, X3, X4, X5 being processed from five different measured value sources. In this exemplary embodiment, measured values X1, X2, X3, X4, X5 are recorded from five measurement data sources. The recorded measured values RM with their different time frames RZ are transferred to a measured value pool MT and there cached. In addition, each recorded measured value RM is given a time stamp in order to be able to understand when the individual measured value RM was recorded. From the measured value pool MT, the recorded measured values RM are distributed together with their time stamp to two different storage devices, to the RAW data record RD and the aggregation AT.

The RAW data record RD and the recorded measured values RM are aggregated in the aggregation AT. The recorded measured values RM are also stored together with the RAW time grid RZ in a RAW data record RD and stored on the RAW storage device RS. While unadulterated measured values X are stored in the RAW data record RD together with their time stamp, the aggregated data record AT has not only the latest recorded measured value RM but also recorded measured values RM in a specific time grid depending on the time grid of the data records DS1, DS2, DS3.

In the aggregation module AT, data records are aggregated to the time grid of the data records DS1, DS2, DS3, and so, in this exemplary embodiment, three parts of the data of the recorded measured values M1, M2, M3 are calculated. If the time interval of a data record DSN lies outside the time stamp MN, then these values are ignored by the aggregation module AT and are not generated at all. In particular, the three parts of the data of the recorded measured values M1, M2, M3 differ from one another in their time grid, the time interval, possibly the type of measurement data and thus also in their data volume. For example, the first part of the data of the recorded measured values M1 can have a measured value X with a time pattern of 10 ms in a time interval of 1 min, the second part of the data of the recorded measured values M2 can have the same or a different measured value X with a time pattern of 100 ms in a time interval of 1 hour and the third part of the data of the recorded measured values M3 have the same or a different measured value X with a time pattern of 1 min in the time interval of 1 d. The parts of the data of the recorded measured values M1, M2, M3 therefore have less data than the RAW data record RD stored on the RAW storage device RS and therefore occupy individually less storage space than the RAW data set RD. Due to the time interval of 1d of the data of the recorded measured values M3 selected here as an example, the database AT of the aggregated data has aggregated measured values RM within the last past 24 hours (1d).

These three parts of the data of the recorded measured values M1, M2, M3 are each stored in a data record DS1, DS2, DS3. Analogous to the data of the recorded measured values M1, M2, M3 stored in the data records DS1, DS2, DS3, the individual data volumes of the data records DS1, DS2, DS3 are smaller than the data volume of the RAW data record RD and occupy less storage space. The data records DS1, DS2, DS3 are stored on the storage device S2. In this exemplary embodiment, the storage devices RS and S2 are one or more permanent memories; storage that is optimized in terms of space is preferred, but storage that is optimized for access time is also possible.

From the data records DS1, DS2, DS3 the subsets of the parts of the data of the recorded measured values TM1, TM2, TM3 are then generated in such a way that the recorded measured values RM are supplemented by variables calculated on them using the calculation module CT, for example, and thus the performance of the drives, for example is calculated via the monitored system.

The subsets of the parts of the data of the recorded measured values TM 1, TM2, TM3 are stored in the partial data sets TDS1, TDS2, TDS3. The three partial data records TDS1, TDS2, TDS3 have the same time pattern as the data records DS1, DS2, DS3 from which they were generated. The partial data records TDS1, TDS2, TDS3 are stored in different storage devices in this exemplary embodiment: the partial data record TDS1 is stored in the memory device S1.2, the partial data records TDS2.TDS3 in the memory device S1.1. The storage devices S1.1, S1.2 are in this exemplary embodiment Random Access Memories (RAM) located in different computer systems. It is therefore also possible according to the invention to store the different partial data sets TDS1, TDS2, TDS3 in different computer systems and to have them displayed graphically.

An exemplary embodiment of the method according to the invention, in which a manual data set HDS is integrated, is shown in FIG. 4. In this exemplary embodiment, three different measured values X1, X2, X3 are acquired from three measurement data sources. The recorded measured values RM with their different time rasters RZ are transferred to a measured value pool MT and temporarily stored there. In addition, each recorded measured value RM is given a time stamp in order to be able to understand when the individual measured value RM was recorded. From the measured value pool MT, the recorded measured values RM are distributed together with their time stamp to two different storage devices, to the RAW data record RD and the aggregation AT.

In this exemplary embodiment, three parts of the data of the recorded measured values M1, M2, M3 are calculated from the aggregated data record AT. In particular, the three parts of the data of the recorded measured values M1, M2, M3 differ from one another in their time grid, the time interval, possibly the type of measurement data and thus also in their data volume. For example, the first part of the data can be the recorded measured values M1 have a measured value X with a time pattern of 10 ms in a time interval of 1 min, the second part of the data of the recorded measured values M2 have the same or a different measured value X with a time pattern of 100 ms in a time interval of 1 h and the third part of the data of the recorded measured values M3 have the same or a different measured value X with a time grid of 1min in a time interval of 1d. The parts of the data of the recorded measured values M1, M2, M3 therefore have less data than the RAW data set RD stored on the RAW storage device RS and therefore individually occupy less storage space than the RAW data set RD. Due to the time interval of 1d of the data of the recorded measured values M3 selected here as an example, the database AT of the aggregated data has aggregated measured values RM within the last past 24 hours (1d).

These three parts of the data of the recorded measured values M1, M2, M3 are each stored in a data record DS1, DS2, DS3. Analogous to the data of the recorded measured values M1, M2, M3 stored in the data records DS1, DS2, DS3, the individual data volumes of the data records DS1, DS2, DS3 are smaller than the data volume of the RAW data record RD and occupy less storage space. The data records DS1, DS2, DS3 are stored in the storage device RS like the RAW data record RD.

In this exemplary embodiment, the storage device RS is one or more permanent memories; storage that is optimized in terms of space is preferred, but storage that is optimized for access time is also possible. The storage of the RAW data record RD is expediently space-optimized, and the storage of the data records DS1, DS2, DS3 is optimized in terms of access time. This can be achieved, for example, by using compression algorithms for the storage of the RAW data record RD, but not for the storage of the data records DS1, DS2, DS3 and / or by using different hard drives (HDD, SSD) with different access times. From the data records DS1, DS2, DS3 the subsets of the parts of the data of the recorded measured values TM1, TM2, TM3 are then generated in such a way that the recorded measured values RM are supplemented by, for example, variables calculated thereon and thus, for example, forecasts about the monitored System become possible.

In this exemplary embodiment, the computation module CT is supplemented by a manual data record HDS. The data of the hand data set HDS can in particular be generated by an input I of a user. These can be, for example, parameters for scaling the recorded measured values RM, or substitute values for missing or incorrect recorded measured values RM. The erroneous recorded measured values RM are then replaced by the input I of the manual data record HDS. With the help of the manual data set, values for the future can be entered in order to create forecasts from them, for example.

The subsets of the parts of the data of the recorded measured values TM 1, TM2, TM3 are stored in the partial data sets TDS1, TDS2, TDS3. The three partial data records TDS1, TDS2, TDS3 have the same time pattern as the data records DS1, DS2, DS3 from which they were generated. The partial data sets TDS1, TDS2, TDS3 are stored in a storage device S1 in this exemplary embodiment.

In this exemplary embodiment, the storage device S1 is a random access memory (RAM) which is located in a computer system. It is therefore also possible according to the invention to store the different partial data sets TDS1, TDS2, TDS3 in different computer systems and to have them displayed graphically.

FIG. 5 shows an exemplary embodiment of the method according to the invention in which both a measured value pool MT and a manual data set HDS are used. In this In the exemplary embodiment, measured values X are recorded and provided over a period of one year. In this exemplary embodiment, three measured values X1, X2, X3 are recorded by different measurement data sources, for example sensors on the system to be monitored. The acquisition of the measured values X1, X2, X3 can have any time grid. In this exemplary embodiment, a time grid of the measured values X1, X2, X3 of 10 ms each is taken as a basis; in other words, a new measured value RM is recorded every 10 ms from each measured value source X1, X2, X3.

The recorded measured values RM with their time pattern are transferred to a measured value pool MT and temporarily stored there. In addition, each recorded measured value RM is given a time stamp in order to be able to understand when the individual measured value RM was recorded. The storage of the recorded measured values RM in the measured value pool MT is particularly useful if the scanning raster of one or more measured values X1, X2, X3 or recorded measured values RM are small, e.g. smaller than 100 ms. From the measured value pool MT, the recorded measured values RM are distributed together with their time stamp to two different storage devices, to the RAW data record RD and via the aggregation module AT to existing data records DS1 to DSN, provided that the time interval of the data record covers the time stamp of the recorded measured value XN .

The RAW data record RD and the recorded measured values RM are aggregated in the aggregation AT. The recorded measured values RM are also stored together with the RAW time grid RZ in a RAW data record RD and stored on the RAW storage device RS. While unadulterated measured values X are stored in the RAW data record RD together with their time stamp, the aggregated data record AT has not only the most recent recorded measured value RM but also recorded measured values RM in the time grid of 10 ms. The recorded measured values RM are stored in the RAW data record RD in a space-optimized manner (less than 4 bytes per recorded measured value RM, the recorded measured values RM stored over a year occupy approx. 2TB in the RAW data record RD. This data sets 200 scanned measured values with a time grid of 10ms ahead. In this exemplary embodiment, four parts of the data of the recorded measured values M1, M2, M3, M4 are calculated from the aggregated data record AT. In particular, the four parts of the data of the recorded measured values M1, M2, M3, M4 differ from one another in their time grid, the time interval, possibly the type of measurement data and thus also in their data volume.

In this exemplary embodiment, a time grid of 100 ms to 10 s is selected for the first part of the data of the recorded measured values M1, the recorded measured values RM being continuously updated from the aggregated data record AT. For the second part of the data of the recorded measured values M2, a time interval of the past 1 min to 15 min is selected, also updated by recorded measured values RM from the aggregated data record AT. Any time interval is assumed for the third and fourth part of the data of the recorded measured values M3, M4.

These parts of the data of the recorded measured values M1, M2, M3, M4 are each stored in a data record DS1, DS2, DS3, DS4. Analogous to the data of the recorded measured values M1, M2, M3, M4 stored in the data records DS1, DS2, DS3, DS4, the individual data volumes of the data records DS1, DS2, DS3, DS4 are smaller than the data volume of the RAW data record RD and occupy less storage space . Due to the selection of the recorded measured values RM assumed in this exemplary embodiment, the data record DS1 has a data volume of approx. 600MB, the data record DS2 has a data volume of approx. 720MB, and the data records DS3.DS4 data volumes of between approx. 960MB and 1.2GB each. The data records DS1, DS2, DS3, DS4 are stored on the storage device RS like the RAW data record RD. The storage of the RAW data record RD is space-optimized, the storage of the data records DS1, DS2, DS3, DS4 is access time-optimized. The access time for the data sets DS1, DS2, DS3, DS4 is typically less than 400ms for 1 million recorded measured values RM. From the data records DS1, DS2, DS3, DS4 the subsets of the parts of the data of the recorded measured values TM1, TM2, TM3, TM4 are then generated in such a way that the recorded measured values RM are supplemented by variables calculated on them by means of the calculation module CT and thus, for example, forecasts become possible via the monitored system. In this exemplary embodiment, 1000 calculated variables of the calculation module CT are assumed.

In contrast to the previous exemplary embodiments, the subsets of the parts of the data of the recorded measured values TM1, TM2, TM3, TM4 have different time rasters and time intervals for the data records DS1, DS2, DS3, DS4 that generate them: In this exemplary embodiment, the For the first part of the data of the recorded measured values TDM1, a time grid of 1s and a time interval of 5d were selected, for the second subset of the second part of the data of the recorded measured values TDM2 a time grid of 1min and a time interval of 1a (representation of the history of the recorded measured values RM der to be monitored), for the third subset of the third part of the data of the recorded measured values TDM3 a time grid of 10ms and a time interval of 2h and for the fourth subset of the fourth part of the data of the recorded measured values TDM4 a time grid of 100ms and a time interval of 24h .

The subsets of the parts of the data of the recorded measured values TM1, TM2, TM3, TM4 are stored in the partial data sets TDS1, TDS2, TDS3, TDS4. In this exemplary embodiment, the partial data sets TDS1, TDS2, TDS3, TDS4 are stored in the storage device S1, which in this exemplary embodiment is a random access memory (RAM). The required storage space for the partial data set TDS1 is approx. 1.2 GB, for the partial data set TDS2 approx. 1.7 GB, for the partial data set TDS3 approx. 2 GB and for the partial data set TDS4 approx. 3 GB. With the parameters selected in this exemplary embodiment, the method according to the invention requires a total of approx to be recorded and made available for one year. The method according to the invention advantageously does not place such high demands on the computer hardware that the method according to the invention can be carried out using a commercially available server or PC and / or notebook computer.

In this exemplary embodiment, the data record TDS1 resolves the data very finely in real time. In the representation of the data record TDS2, the course is shown in a rough time grid over a year. It also often (but not always) makes no sense at all. It does not make sense to display the annual course of a measured value on a trend line in a 10 ms grid, since a standard monitor with 1920 pixels does not have a suitable resolution to display this fine temporal gradation. The data records TDS3 and TDS4 can be used to extract finely resolved data from the RAW database over a time interval that is further in the past and to display it more precisely if the 1m time grid of the data record TDS2 is not sufficiently fine.

The process is used, for example, in power plants when starting up a gas-powered engine:

Before the waste heat from the gas engines can be fed into the district heating network, a flow temperature of 115 ° C must be set in the engine cooling circuit when it exits the engine cooling system. Before the temperature is reached, the coolant (in this case cooling water) is circulated. The water is heated on the engine side and then later cooled down to 60 ° C using a roof cooler. It takes 2-3 minutes for the water heated on the engine side to reach the cooler (due to the circulating volume flow). This process goes pretty well Model and predict the temperature development in the cycle. With the forecast and the upcoming temperature development, the roof cooler, which has its own cooling circuit and its own pump, can be controlled very easily because it can then intervene preventively. In this case, the roof cooler pump can be brought to the correct speed before (too) hot water arrives from the engine and so the circulating volume flow in the roof cooler circuit can be brought to the correct volume flow. The same goes in the opposite direction of the cooling circuit. The cooling pump can be switched off slowly at an early stage, before the coolant temperature has reached 115 ° C, because the feed-out time can be precisely determined by the forecast.

For this purpose, the different temperatures are recorded here in a raw data record RD and stored on the RAW storage device RS as measured values RM, in each case together with the respective time stamp RZ. From the parameters of all sensors of the system RM recorded in a time interval of 150 ms, a first part of the recorded parameters M1, namely the temperatures, the volume flow and the speed of the cooling pump, is stored in a stored data record DS1 on a second storage device S2. The second storage device S2 has a faster access time than the RAW storage device RS. Using the computation module CT, a partial data record is now generated from the stored data record DS1, which has a time interval of 2 s. The recorded parameters, for which no corresponding data record was recorded, are extrapolated using the calculation module CT, taking into account the temporally adjacent recorded parameters M1, and stored in a partial data record TDS1 on a first storage device S1.1. The first storage device S1.1 has a faster access time than the second storage device S2 and the RAW storage device RS. This also significantly reduces the size of the partial data record TDS1 compared to the data record DS1 and the RAW data record RD. From the partial data set TDS1, forecasts of the temperature development are now created as a function of the volume flows and the cooling pump speeds and, on the basis of these forecasts, the volume flow and the Controlled cooling pump speed. Due to the reduced number of parameters, the longer time intervals and the faster storage facilities, the forecasts and the resulting system parameters can be determined more quickly and in a more resource-efficient manner.

Another application example is presented below from the gas storage area:

A gas storage tank often has several compressors from different manufacturers, which work particularly effectively in certain work areas, or can be operated particularly cheaply at certain gas or energy prices. Switching from one compressor to another during operation costs time and money because the compressor first has to be started up. Sometimes switching to another compressor is not worthwhile, even though the second compressor would be more effective under the current working conditions because the amount of gas that still has to be fed in is too small. In this case, starting up a second compressor is not economically viable. Such times must be precisely determined and calculated. In this case, when such a state is reached, in which switching to another compressor comes into question, it must be assessed on the basis of forecasts and a decision must be made as to whether an alternating compressor is switched on.

In this application scenario, the different parameters of the working ranges (speed of the pump or pump power) of the compressor are recorded in a raw data record RD and stored on the RAW storage device RS as measured values RM together with the respective time stamp RZ. From the parameters of all sensors of the system RM recorded in a time interval of 100 ms, a first part of the recorded parameters M1, namely the working range parameters of the compressors and their energy consumption, is stored in a stored data record DS1 on a second storage device S2. The second storage device S2 has a faster access time than the RAW storage device RS. About the Calculation module CT, a partial data record TDS1 is now generated from the stored data record DS1, which includes the working parameters, the energy consumption and the current energy prices, which are read from an external data source, and saves them in a time interval of 5s. The recorded parameters M1 are stored in a partial data record TDS1 on a first storage device S1.1. This also significantly reduces the size of the partial data record TDS1 compared to the data record DS1 and the RAW data record RD. The first storage device S1.1 has a faster access time than the second storage device S2 and the RAW storage device RS. From the partial data set TDS1, forecasts of the energy costs depending on the energy consumption and the performance of the compressors in use and those that are still available are created, and the field of application of the individual compressors and the selection of the compressors to be used are controlled on the basis of these forecasts. Due to the reduced number of parameters, the longer time intervals and the faster storage facilities, the forecasts and the resulting system parameters can be determined more quickly and in a more resource-efficient manner.

Another example of the application of the invention from the transport sector:

A battery is installed in a new type of direct current substation to compensate for the load peaks that occur for 15 minutes. The method according to the invention is used to determine the energy requirement for a time range of 15 minutes on the basis of the forecasts, and the battery is preconditioned accordingly. Based on the prognosis, a decision is made as to whether the energy required for accelerating a tram is taken from the network or from the battery. The same applies to braking energy recovery. A forecast is made at short notice as to whether the energy should flow into the battery or whether it should be fed back into the grid via a four-quadrant controller because the battery has sufficient SOC (State of the Charge) for the next 15 Minutes. The method according to the invention also helps here to record the corresponding parameters quickly and in a resource-saving manner, to determine the necessary forecasts from them and to control the GUW accordingly.

REFERENCE LIST

RD RAW data set

X, X1, X2, X3, X4, X5 Measured values and / or measured value sources of the system to be monitored

T time

RM Measured values recorded

RZ Recorded time

M1, M2, M3, M4 Part of the recorded measured values DS1, DS2, DS3, DS4 Stored data records AT aggregation CT calculation module

TDS1, TDS2, TDS3, TDS4 partial data sets TM1, TM2, TM2, TM3 partial set of a part of the recorded measured values S1.1, S1.2, S2 storage devices

RS RAW storage device

HDS hand data set

MT measured value pool

User input

Limit between access time optimization and storage space optimization of the storage of the recorded measured values Limit between the access time optimization of the storage of the recorded measured values and the calculation module

Claims

PAT EN TA NSPRÜ CHE

1. Process for recording and providing measured values and data with the following process steps:

Acquisition of measured values Acquisition of the time

Saving the recorded measured values (RM) in a RAW time grid (RZ) Saving a first part of the data of the recorded measured values (M1) in a first time grid, the first part of the recorded measured values (M1) comprising less data than the stored recorded measured values.

2. The method for acquiring and providing measured values and data according to claim 1, characterized in that an output is created from the first part of the stored data of the acquired measured values.

3. The method for acquiring and providing measured values and data according to claim 2, characterized in that the output comprises a graphic output.

4. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the acquired measured values are stored in a RAW data record (RD), the RAW data record having a RAW data volume (RDV).

5. The method for acquiring and providing measured values and data according to claim 4, characterized in that the RAW data record (RD) is stored on a RAW storage device (RS).

6. The method for acquiring and providing measured values and data according to claim 5, characterized in that the RAW storage device (RS) has a RAW access time (RZZ).

7. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the RAW time grid (RZ) is a change-based time grid.

8. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the acquired measured values are stored over a RAW time interval (RZI).

9. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the acquired measured values are stored in a space-optimized manner.

10. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the first part of the data of the acquired measured values is stored in a first data record (DS1).

11. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the first part of the data of the acquired measured values (M1) is stored with optimized access time.

12. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the first part of the data of the acquired measured values (M1) is aggregated and / or calculated from the acquired measured values (RD).

13. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that a second part of the data of the acquired measured values (M2) is stored, the second part of the data of the acquired measured values (M2) being in its time grid (ZR2), time interval (ZI2), the type of measurement data (AMD2) and / or its data volume (DV2) differs from the first part of the data of the recorded measurement values (M1).

14. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that a third part and further parts of the data of the acquired measured values (M3, M4, M5) are stored, the third part and the further parts of the data of the recorded measured values (M3, M4, M5) in their time grid (ZR3, ZR4, ZR5), time interval (ZI3, ZI4, ZI5), the type of measured data (AMD3, AMD4, AMD5) and / or their Differentiate the data volume (DV3, DV4, DV5) from the other parts of the data of the recorded measured values (M1, M2, M3, M4 M5).

15. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the parts of the data of the acquired measured values (M1, M2, M3, M4, M5) are stored on a first memory device (S1).

16. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the parts of the data of the acquired measured values (M1, M2, M3, M4, M5) are in different data sets (DS1, DS2, DS3 , DS4).

17. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the data volumes (DV1, DV2, DV3, DV4, DV5) of the data sets (DS1, DS2, DS3, DS4, DS5) of the parts the data of the recorded measured values (M1, M2, M3, M4, M5) are smaller than the data volume (RDV) of the RAW data set (RD).

18. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the time intervals (ZU, ZI2, ZI3, ZI4, ZI5) of the parts of the data of the recorded measured values (M1, M2, M3, M4 , M5) are greater than or equal to the RAW time interval (RZI).

19. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the time raster (ZR1, ZR2, ZR3, ZR4, ZR5) of the parts of the data of the acquired measured values (M1, M2, M3, M4 , M5) are greater than or equal to the RAW time grid (RZR).

20. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the access speed of the parts of the data of the recorded measured values (M1, M2, M3, M4, M5) from the data sets of the parts of the data recorded measured values (DS1, DS2, DS3, DS4, DS5) is less than or equal to the access speed of the same data from the RAW data record (RD).

21. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that a first subset of the first part of the data of the acquired measured values (TM1) is stored in a first partial data set (TDS1).

22. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the first subset of the first part of the data of the acquired measured values (TM1) is stored with optimized access time.

23. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the first subset of the first part of the data of the acquired measured values (TM1) is aggregated from the first part of the data of the acquired measured values (M1) and / or is calculated.

24. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that a second subset of the second part of the data of the recorded measured values (TM2) is stored, the second subset of the second part of the data of the recorded measured values (TM2) in its time grid (TZR2), time interval (TZI2), the type of measurement data (TAMD2) and / or their data volume (TDV2) differs from the first subset of the first part of the data of the recorded measured values (TM1).

25. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that a third subset and further subsets of the parts of the data of the acquired measured values (TM3, TM4, TM5) is stored, the third subset being and further subsets of the parts of the data of the recorded measured values (TM3, TM4, TM5) in their time grid (TZR3, TZR4, TZR5), time interval (TZI3, TZI4, TZI5), the type of measured data (TAMD3, TAMD4, TAMD5) and / or their data volume (TDV3, TDV4, TDV5) differs from the other subsets of the parts of the data of the recorded measured values (TM1, TM2, TM3, TM4, TM5).

26. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the subsets of the parts of the data of the acquired measured values (TM1, TM2, TM3, TM4, TM5) are stored on a second storage device (S1) will.

27. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the subsets of the parts of the data of the recorded measured values (TM1, TM2, TM3,

TM4, TM5) in different partial data sets (TDS1, TDS2, TDS3,

TDS4, TDS5) can be saved.

28. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the data volumes (TDV1, TDV2, TDV3, TDV4, TDV5) of the data records (TDS1, TDS2, TDS3, TDS4, TDS5) of the subsets the parts of the data of the recorded measured values (TM1, TM2, TM3, TM4, TM5) are smaller than the data volumes (DV1, DV2, DV3, DV4, DV5) of the parts of the data of the recorded measured values (DS1, DS2, DS3, DS4, DS5).

29. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the time intervals (TZI1, TZI2, TZI3, TZI4, TZI5) of the subsets of the parts of the data of the recorded measured values (TM1, TM2, TM3 , TM4, TM5) are less than or equal to the time intervals (ZU, ZI2, ZI3, ZI4, ZI5) of the parts of the data of the recorded measured values (M1, M2, M3, M4, M5).

30. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the time raster (TZI1, TZI2, TZI3, TZI4, TZI5) of the subsets of the parts of the data of the acquired measured values (TM1, TM2, TM3 , TM4, TM5) are greater than or equal to the time grid (ZU, ZI2, ZI3, ZI4, ZI5) of the parts of the data of the recorded measured values (M1, M2, M3, M4, M5).

31. A method for acquiring and providing measured values and data according to one or more of the preceding claims characterized in that the second storage device (S2) has a shorter access time than the first storage device (S1) and the RAW storage device (RS).

32. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the access time of the second storage device (ZZ2) to the access time of the first storage device (ZZ1) and the access time of the RAW storage device (RZZ) in the relationship:

ZZ2 / RZZ> ZZ1 / RZZ <1.

33. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the data carrier size of the second storage device (DTG2) is related to the data carrier size of the first storage device (DTG1) and the data carrier size of the RAW storage device (RDTG) the relationship:

DTG2 <RDTG and DTG2 <DTG1 stand.

34. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that data are read in from a hand-held data record, the data in the hand-held data record being acquired from an input.

35. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the data read in from a manual data set replace the corresponding data from the parts of the data of the recorded measured values (M1, M2, M3, M4, M5).

36. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the acquired measured values (RM) are acquired from several and / or different measured data sources.

37. The method for acquiring and providing measured values and data according to claim 36, characterized in that the measured values (RM) acquired from a plurality of measured data sources have different time rasters.

38. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that the acquired measured values (RM) are first acquired in a measured value pool (MP).

39. The method for acquiring and providing measured values and data according to claim 38, characterized in that the acquired measured values (RM) are assigned a time in the measured value pool.

40. The method for acquiring and providing measured values and data according to claim 38 or 39, characterized in that the measured value pool distributes the acquired measured values (RM) to different storage devices.

41. The method for acquiring and providing measured values and data according to one or more of the preceding claims, characterized in that

Parts of the data of the recorded measured values (M1, M2, M3, M4, M5) can be read out from the RAW data record (RD) and the measured value pool (MP).

42. A computer program product comprising a computer-readable storage medium on which a program is stored which enables a computing / processing device to carry out the method according to one of claims 1 to 41 after it has been loaded into the memory of the computing / processing device .