Method for optimizing the measurement rate of a field device

Abstract

The invention relates to a method for optimizing the measurement rate of a first field device (11) in a measuring system (1). In order to use the method, the measuring system (1) must include at least one second field device (12) in addition to the first field device (11), wherein at least a measured variable (L) of the first field device (11) is correlated with a measured variable (f) of the second field device (12). The method is based on determining a corresponding specific correlation pattern between the first measured variable (L) and the second measured variable (f) on the basis of measured values ​​measured in a learning phase. According to the invention, this makes it possible to check at least the measured values ​​from the second field device (12) for the correlation pattern during normal measuring operation and to change the measurement rate of the first field device (11) during a corresponding time window (Δt). This makes it possible, in particular in the case of battery-powered field devices (11, 12, 13), to extend the service life and / or availability of a process facility, so that downtimes of the process facility can be avoided.

Description

Technical Field

[0001] The invention relates to a method for optimizing the measurement rate of a field device in a measurement system. Background Art

[0002] In automation technology, in particular for process automation, field devices are often used for detecting various measured variables. The measured variables to be determined can be, for example, the level, flow, pressure, temperature, pH value, redox potential, conductivity or dielectric value of a medium in a process plant. In order to detect the corresponding measured values, the field devices each include a suitable sensor or are based on a suitable measuring principle. The Endress+Hauser Group of Companies produces and sells a wide range of such field devices.

[0003] In the corresponding process facilities, each field device is usually connected together to form a measurement system so that the corresponding process variable can be coordinated with a suitable actuator, such as a heating element, agitator, valve or pump for inlet and outlet. Therefore, the measured variables of each field device of the process facility may also be interrelated. For the communication in the measurement system, the field device can be directly or centrally connected to each other via a control unit (such as a process control station). Mainly in the case where the field device is arranged in an inaccessible process facility position, it is preferred to implement a wireless transmission protocol, such as wireless HART or WLAN, for communication in the measurement system. In these cases, the energy supply of these field devices is carried out via a battery accordingly. The potential use duration of a single field device depends on the battery capacity and the measurement rate, i.e. the timing and measurement time of each clock cycle, during which the field device measures the measured value.

[0004] However, in this case, the measurement rate cannot be set too low so that the process can be adequately monitored. Combined with the limited capacity of the batteries, the corresponding field devices must therefore be taken out of operation during regular maintenance cycles to replace the batteries. As a result, during these maintenance cycles, the processes within the process facility must also be stopped, since these processes generally cannot be run in a controlled manner without corresponding monitoring. This is disadvantageous for the plant operator, since any downtime of the process facility impairs its efficiency. Summary of the invention

[0005] It is therefore an object of the present invention to provide a method by means of which the availability of a battery-powered field device can be increased.

[0006] The invention achieves this object by means of a method for optimizing the measurement rate of a first field device in a measuring system. In order to use the method, it is necessary for the measuring system to include at least one second field device in addition to the first field device, wherein the at least two field devices each measure a measured value of a corresponding measured variable at a specific measurement rate and wherein at least the measured variable of the first field device is correlated with the measured variable of the second field device. The method comprises the following method steps:

[0007] - during a defined learning phase, measuring the measured variables of the at least two field devices at a preset measuring rate in each case,

[0008] - determining a correlation pattern between the first measured variable and the second measured variable based on the measured values ​​determined in the learning phase.

[0009] In doing so, during the measuring operation at least the measured value of the second field device is checked for the relevant mode,

[0010] Therein, during a measuring operation, a measuring rate of the first field device is changed at least during a time window in which a relevant pattern is detected in the measured values ​​of the second measured variable.

[0011] The best correlation pattern can be determined with the help of automated machine learning algorithms, such as Pearson or partial correlation.

[0012] The invention is therefore based on checking the correlation of the individual measured variables with one another. If the method identifies a strong correlation between the measured variables, this is evaluated as evidence of the functionality of the measuring system. Otherwise, it is assumed that the measuring system has a malfunction and the measured values ​​are classified as incorrect or at least not credible.

[0013] During the measuring operation, at least during the time window, in which a relevant pattern is identified in the measured values ​​of the second measured variable, the measuring rate of the first field device can be reduced. As a result, the power consumption of the individual devices can be reduced. This is particularly advantageous when the first field device and / or the second field device comprises a battery for energy supply, because this prolongs the battery life and thus enhances the availability in the process facility.

[0014] In order to reduce any computational effort and thus speed up the creation of the correlation patterns, redundant measured values ​​can advantageously be filtered out from the learning phase, for example by means of unsupervised clustering methods, in order to determine the correlation patterns.

[0015] A corresponding measuring system suitable for carrying out the method according to one of the aforementioned design variants must comprise at least the following components:

[0016] a first field device which is designed to measure a first measured variable at an adjustable measuring rate,

[0017] a second field device, which is designed to measure a second measured variable,

[0018] - a control unit designed to

[0019] o determining a correlation pattern between the first measured variable and the second measured variable based on the measured values ​​determined in the learning phase,

[0020] o checking at least a measured value of the second field device for a relevant mode during a measuring operation,

[0021] o During the measuring operation, at least the measuring rate of the first field device is changed at least during a time window in which a relevant pattern is identified in the measured values ​​of the second measured variable.

[0022] In this case, the first field device and / or the second field device can be connected to the control unit by means of a wireless interface, for example.

[0023] In the context of the present invention, the term "unit" refers in principle to any electronic circuit designed to be suitable for the planned intended purpose. Thus, as required, it can be an analog circuit for generating or processing corresponding analog signals. However, it can also be a digital circuit such as an FPGA or a storage medium that interacts with a program. In this case, the program is designed to perform the corresponding method steps or to apply the necessary computing operations of the corresponding unit. In this context, the various electronic units of the level measuring device in the sense of the present invention can also potentially access a common physical memory or operate by means of the same physical digital circuit. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention is explained in more detail with reference to the following drawings. It is shown as follows:

[0025] Figure 1 : A measurement system having three field devices in a process facility, and

[0026] Figure 2 : Correlation between measured variables of field devices. DETAILED DESCRIPTION

[0027] In order to generally understand the method according to the present invention, Figure 1An exemplary measuring system 1 is shown, which is used for monitoring a process facility 2, such as a chemical reactor. To this end, the exemplary measuring system 1 comprises a flow meter 12 at the inlet of the reactor 2, a level measuring device 11 on the reactor 2 itself and a temperature measuring device 13 as a field device at the outlet of the reactor 2. The field devices 11, 12, 13 measure the respective measured values ​​L, f, T in each case at an individually adjustable measuring rate (e.g. between 1 measurement per minute and 1000 measurements per second).

[0028] For example, the reactant may be supplied via the inlet of the reactor 2 , wherein the flow rate f of the supplied reactant is detected by means of the flow meter 12 .

[0029] The fill level measuring device 11 measures the fill level L in the reactor 2 and thus monitors, for example, whether a critical fill level value L is exceeded or fallen below by a reaction or by supplying reactants. The measured value of the fill level measuring device 11 in the exemplary process facility 2 is therefore correlated with the measured value of the flow meter 12, since the fill level L in the reactor 2 increases linearly with time during the time interval Δt, wherein a constant flow f prevails at the inlet. Thus, the exemplary dependence of the fill level L on the flow f can be described as a function, since the fill level is formed by the antiderivative of the flow:

[0030]

[0031] exist Figure 2 This dependence of the measured fill level value on the value of the flow meter 12 is schematically shown in the diagram of FIG.

[0032] For example, in Figure 1 In the exemplary embodiment shown, the temperature measuring device 13 at the outlet of the reactor 2 can in turn be used to measure the temperature T of the reaction products during the emptying of the reactor 2 in order to adjust the subsequent process steps accordingly. If any chemical reaction in the process facility 2 proceeds endothermically and thus leads to cooling in the reactor 2, the temperature measuring device 13 records an at least brief drop in the temperature T during a corresponding time interval Δt2, during which the reactor 2 is emptied, depending on the ambient temperature. Thus, in the case of a (linear) drop in the fill level L (over time), the measured value of the temperature measuring device 13 also correlates with the measured value of the fill level measuring device 11. This exemplary context is also schematically shown in FIG. Figure 2 are shown in the chart.

[0033] exist Figure 1In the design variant shown, the measuring system 1 comprises a control unit 14, to which the field devices 11, 12, 13 are connected. The control unit 14 can be, for example, a process control system of a process facility. For example, "PROFIBUS", "HART", "WirelessHART" or "Ethernet" can be implemented as an interface via the field devices 11, 12, 13 being connected to the control unit 14. In particular, in the case of a wireless design of the interface, the field devices 11, 12, 13 can be operated accordingly by means of a battery, so that no additional cables are required for this purpose.

[0034] The measured values ​​f, L, T measured by the field devices 11, 12, 13 can be transmitted via the interface. By corresponding design, this enables the control unit 14 to determine the aforementioned correlation pattern between the measured fill level value and the measured value f of the flow meter 12 or the measured temperature value and the measured fill level value during a defined learning phase. For example, in order to find a suitable correlation type, such as Pearson or partial correlation, the control unit 14 can apply an automated machine learning algorithm.

[0035] After detecting the relevant pattern, the measuring system 1 or the control unit 14 according to the invention may switch to normal measuring operation.

[0036] This means that during the measuring operation, the control unit 14 checks at least the measured value f of the flow meter 12 for a previously determined correlation pattern. Specifically, it is checked whether a (constant) flow f currently exists. If this is identified, it is derived from this that, due to the previously identified correlation pattern, the fill level L must also change accordingly.

[0037] Since fill level changes due to a correlation of this type are foreseeable, the measuring rate of the fill level measuring device 11 can be reduced during measuring operation, at least during the time window Δt in which a correlation pattern is identified in the measured flow values ​​f, without expecting unpredictable, sudden fill level changes relative to the fill level L. In the case of a battery-powered fill level measuring device 11, its service life and therefore its availability can thereby be optimized.

[0038] Analogously to the measured flow value f of the flow meter 12, the control unit 14 can also check the measured value L of the fill level measuring device 11 during the measuring operation against a previously defined correlation pattern of the temperature measuring device 13 with respect to the measured fill level value L. As soon as a drop in the fill level is detected, this is in turn recognized as the presence of a correlation pattern and a corresponding (brief) drop in the temperature T at the temperature measuring device 13 is expected. Thus, the measuring rate of the temperature measuring device 13 can also be reduced during the measuring operation at least during the time window Δt2 in which the correlation pattern is recognized in the fill level value L, without expecting unexpected temperature changes. In this way, in the case of battery operation, the service life or availability of the temperature measuring device 13 can therefore also be increased.

[0039] In the illustration shown, the control unit 14 is shown as a separate superordinated unit. However, within the scope of the invention, it is also conceivable to design the control unit 14 not as an external device but as a component of one of the field devices 11 , 12 , 13 .

[0040] Reference numerals list

[0041] 1 Measurement system

[0042] 2 Process facilities

[0043] 11 Level measurement equipment

[0044] 12 Flow Meter

[0045] 13 Temperature measurement equipment

[0046] 14 Control Unit

[0047] f Flow

[0048] L Material level

[0049] T Temperature

[0050] Δt time window

Claims

1. A method for optimizing the measurement rate of a first field device (11) in a measurement system (1), wherein: The measuring system (1) comprises, in addition to the first field device (11), at least one second field device (12), wherein the at least two field devices (11-13) both measure measured values ​​of corresponding measured variables (f, L, T) at a specific measurement rate, wherein the first field device (11) is designed to measure a first measured variable (L) and the second field device (12) is designed to measure a second measured variable (f), and wherein at least the first measured variable (L) of the first field device (11) is correlated with the second measured variable (f) of the second field device (12), the method comprising the following method steps: - during a defined learning phase, the measured variables (f, L) of the at least two field devices (11, 12) are measured at a preset measurement rate, - determining a correlation pattern between said first measured variable (L) and said second measured variable (f) based on the measured values ​​determined in said learning phase, wherein at least the measured values ​​of the second field device (12) are checked for the correlation pattern during a measuring operation, and wherein the measuring rate of the first field device (11) is changed during a measuring operation at least during a time window (Δt), wherein the correlation pattern is identified in the measured values ​​of the second measured variable (f), and Therein, a measuring rate of the first field device (11) during the measuring operation is reduced at least during the time window (Δt).

2. The method according to claim 1, wherein: The correlation patterns are determined with the aid of an automated machine learning algorithm.

3. The method according to claim 1 or 2, wherein: Redundant measurements are filtered out from the learning phase by means of unsupervised clustering methods in order to determine the correlation patterns.

4. A measurement system for performing the method according to one of claims 1 to 3, the measurement system comprising: a first field device (11) which is designed to measure the first measured variable (L) at an adjustable measuring rate, a second field device (12) which is designed to measure the second measured variable (f), - a control unit (14) designed to o determining a correlation pattern between the first measured variable (L) and the second measured variable (f) based on the measured values ​​determined in the learning phase, o checking at least the measured values ​​of the second field device (12) for the relevant pattern during the measuring operation, o During the measuring operation, at least the measuring rate of the first field device (11) is reduced, at least during a time window (Δt, Δt2) during which the correlation pattern is identified in the measured values ​​of the second measured variable (f).

5. The measurement system according to claim 4, wherein: The first field device (11) and / or the second field device (12) comprises a battery for energy supply.

6. The measuring system according to claim 4 or 5, wherein: The first field device (11) and / or the second field device (12) are connected to the control unit (14) by means of a wireless interface.

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