Measuring device for process automation in industrial or private environments

Abstract

Measuring device (100), configured for process automation in an industrial or private environment, and for carrying out measurements at preset measurement times within a recurring measurement interval, in particular a daily, weekly or monthly recurring measurement interval, comprising: a control circuit (101), configured for repeatedly changing the preset measurement times in order to also acquire measured values ​​at otherwise measurement-free times; wherein the control circuit (101) is configured to shift some or all of the preset measurement times.

Description

Technical area

[0001] The present invention relates to measuring instrument technology. In particular, the present invention relates to a measuring device configured for process automation in an industrial or private environment, a method for performing measurements at preset, cyclically repeating measurement times within a repeating measurement interval, a program element, and a computer-readable medium. Technical background

[0002] Measuring devices for process automation in industrial or private environments are used to record measured values ​​to monitor processes. Examples of such measuring devices include level measuring devices such as level radar devices, point level sensors, pressure gauges, and flow sensors.

[0003] Especially with battery-operated measuring devices, the power supply is severely limited. To increase the service life of such measuring devices, the number of measurements per unit of time can be reduced. If the measuring device measures the level instead of every five minutes, for example, only once per hour, the service life of the measuring device can be increased twelvefold. However, with long time intervals between individual measurements, certain events or processes may not be detected until late, such as the filling or emptying of a container, a sharp temperature increase, a sharp pressure drop, etc. Summary

[0004] Against this background, it is an object of the present disclosure to provide an alternative measuring device which is characterized by low energy consumption and high measurement accuracy.

[0005] This object is achieved by the features of the independent patent claims. Further developments of the present disclosure emerge from the subclaims and the following description of embodiments.

[0006] A first aspect of the present disclosure relates to a measuring device configured for process automation in an industrial or private environment. The measuring device, which may be, for example, a level measuring device, in particular a radar level measuring device, a point level sensor, a pressure measuring device, or a flow measuring device, is configured to perform measurements at preset measuring times within a repeating measuring interval. Such a repeating measuring interval may, for example, be a calendar day, a calendar week, a calendar month, or a calendar year. However, the measuring interval may also be significantly shorter.

[0007] The measuring device has a control circuit configured to repeatedly change the preset measurement times, particularly after the measurement interval has been completed and before the next measurement interval begins, in order to also record measured values ​​at otherwise non-measurement times. If the measurement times were not changed, one could speak of preset, cyclically repeating measurement times that always occur "at the same time" in consecutive measurement intervals, for example, every Tuesday at 11 a.m. and 5 p.m.

[0008] The measuring device can in particular be a battery-operated, self-sufficient measuring device.

[0009] In particular, the measuring device can be configured to calculate a measured value trend from the recorded measured values, and it can also be designed to decide that if a newly recorded measured value largely agrees with the calculated measured value trend, this measured value should not be transmitted to an external evaluation unit. This can save energy.

[0010] According to a further embodiment of the present disclosure, the preset measurement times are cyclically repeated measurement times on a daily, weekly or monthly basis.

[0011] According to a further embodiment of the present disclosure, the control circuit is configured to shift some or all preset measurement times by the same period of time, for example, after a measurement interval is completed and before the following measurement interval starts.

[0012] According to a further embodiment of the present disclosure, the control circuit is configured to shift some or all of the preset measurement times by different time periods, also for example after a measurement interval has ended and before the following measurement interval begins.

[0013] Optionally, the measuring device or the control circuit can have a neural network or artificial intelligence (Kl), which can, for example, set the second measuring time based on a learning pattern and / or adjust measuring times.

[0014] It should be noted here that the shifting of the measurement times can also occur during the processing of a measurement interval. For example, the control circuit can be configured to shift one or more measurement times in response to one or more trigger events, particularly during the processing of a measurement interval.

[0015] A trigger event could be a measured value that falls outside your predetermined and / or calculated trend. In this case, additional measurements could be taken at shorter intervals, for example, to confirm the first measurement or to detect and correct an erroneous measurement (such as an outlier). Other trigger events, such as a measured value reaching a threshold, are conceivable.

[0016] According to a further embodiment of the present disclosure, the control circuit is configured to infer a cyclically repeating process between the first measurement time and the second measurement time from a change in a measured value between a first measurement at a first measurement time and a subsequent second measurement at a second measurement time, which is above or below a preset threshold value, and then to shift the first measurement time backward in time and the second measurement time forward in time for the following measurement interval, so that the time of the process can be determined more precisely.

[0017] Such a process may, for example, involve filling or emptying a container, a sharp increase or drop in pressure, a sharp increase in temperature, etc.

[0018] According to a further embodiment of the present disclosure, the measuring device is a fill level measuring device, wherein the control circuit is configured to infer a cyclically repeating filling process between the first measurement time and the second measurement time from an increase in a fill level measured value between a first measurement at a first measurement time and a subsequent second measurement at a second measurement time, and then to shift the first measurement time back in time and the second measurement time forward in time for the following week, so that the exact time of the filling process can be determined more precisely. A corresponding procedure can also be performed if a decrease in the fill level measured value by a threshold value is detected between two measurements.

[0019] According to a further embodiment of the present disclosure, the control circuit is configured to determine time intervals in which the measurements provide constant measurement results and to reduce the number of measurements in these time intervals. An example of such a possible time interval is, for example, the weekend or at least Sunday.

[0020] According to a further embodiment of the present disclosure, the control circuit is at least partially arranged in the cloud so that at least some of the subsequent calculations can be outsourced from the measuring device.

[0021] According to a further aspect of the present disclosure, a method for performing measurements at preset times within a repeating measurement interval, in particular daily, weekly, or monthly, is provided, comprising the following steps: performing measurements at preset measurement times within a repeating measurement interval, in particular daily, weekly, or monthly; changing the preset measurement times after passing through the measurement interval in order to also record measured values ​​at otherwise measurement-free times; and performing measurements at the changed measurement times within the following measurement interval.

[0022] According to a further aspect of the present disclosure, a program element is provided which, when executed on a control circuit of a measuring device, instructs the measuring device to perform the steps described above and below.

[0023] According to a further embodiment of the present disclosure, a computer-readable medium is provided on which a program element described above is stored.

[0024] The term "process automation in industrial environments" can be understood as a branch of technology that includes measures for operating machines and systems without human intervention. One goal of process automation is to automate the interaction of individual components of a plant in the chemical, food, pharmaceutical, petroleum, paper, cement, shipping, or mining industries. A variety of sensors can be used for this purpose, which are specifically adapted to the specific requirements of the process industry, such as mechanical stability, insensitivity to contamination, extreme temperatures, and extreme pressures. Measured values ​​from these sensors are usually transmitted to a control room, where process parameters such as fill level, limit level, flow rate, pressure, or density are monitored, and settings for the entire plant can be changed manually or automatically.

[0025] A sub-area of ​​process automation in the industrial environment concerns the logistics automation of plants and the logistics automation of supply chains. With the help of distance and angle sensors, processes inside or outside a building, or within a single logistics facility, are automated in the field of logistics automation. Typical applications for logistics automation systems include baggage and freight handling at airports, traffic monitoring (toll systems), retail, parcel distribution, and building security (access control). What the aforementioned examples have in common is that the respective application requires presence detection in combination with precise measurement of the size and location of an object.For this purpose, sensors based on optical measuring methods using lasers, LEDs, 2D cameras or 3D cameras that measure distances according to the time of flight (ToF) principle can be used.

[0026] Another sub-area of ​​process automation in the industrial environment concerns factory / production automation. Applications for this can be found in a wide variety of industries, such as automotive manufacturing, food production, the pharmaceutical industry, and packaging in general. The goal of factory automation is to automate the production of goods using machines, production lines, and / or robots, i.e., to run it without human intervention. The sensors used here and the specific requirements regarding measurement accuracy for detecting the position and size of an object are comparable to those in the previous example of logistics automation.

[0027] The terms used in the claims should be construed to give them the broadest reasonable interpretation consistent with the foregoing description. For example, the use of the article "a" or "the" in introducing an element should not be construed to exclude a plurality of elements. Similarly, the mention of "or" should be construed to include a plurality of elements, so that the mention of "A or B" does not exclude "A and B" unless it is clear from the context or the preceding description that only one of A and B is intended.Furthermore, the phrase "at least one of A, B, and C" should be understood as one or more elements from a group of elements consisting of A, B, and C, and should not be interpreted as requiring at least one of each of the listed elements A, B, and C, whether A, B, and C are related as categories or otherwise. Furthermore, the mention of "A, B, and / or C" or "at least one of A, B, or C" should be interpreted to include each individual unit of the listed elements, e.g., A, each subset of the listed elements, e.g., A and B, or the entire list of elements A, B, and C.

[0028] Further embodiments of the present disclosure are described below with reference to the figures. The representations in the figures are schematic and not to scale. Where the same reference numerals are used in the following description of the figures, they denote identical or similar elements. Short description of the characters Fig. 1 shows a measuring system with a measuring device according to an embodiment of the present disclosure. Fig. Figure 2 shows the temporal division of measurements into four consecutive measurement intervals, each lasting one week. Fig. 3 shows the measurement intervals of the Fig. 2 with time-delayed measurements. Fig. 4 shows the measurement intervals of the Fig. 2 with a chaotic temporal distribution of the measurements. Fig. 5 shows the measurement intervals of the Fig. 2 with a chaotic temporal distribution of the measurements with adjustment of the measurement times by a control circuit. Fig. 6 shows the measurement intervals of the Fig. 5, where measurements from uneventful times (weekends) are used to improve energy recording. Fig. 7 shows a flowchart of a method according to an embodiment of the present disclosure. Detailed description of embodiments

[0029] Fig. 1 shows a measuring system with a measuring device 100 according to an embodiment of the present disclosure. The measuring device 100 is configured for process automation in an industrial or private environment and is used, for example, for level measurement. For this purpose, it has a control circuit 101, which also generates the radar signals used for the measurement. The control circuit 101 is connected to the antenna 102, which radiates the radar signals toward the product surface and receives the radar signals reflected from there. An antenna 103 is provided to transmit the recorded measured values ​​and / or other data to an external unit. Additionally or alternatively, a wired data interface can also be provided, through which the measuring device can also be supplied with power. The control circuit 101 can be at least partially outsourced to the cloud 104, which can perform trend calculations and measurement time determinations.

[0030] The measuring device 100 - at this point it should be noted that this can also be a measuring device other than a level measuring device, for example a pressure measuring device, a flow measuring device, a point level sensor or a temperature measuring device - is capable of making a "statistically optimized" adjustment of the measuring times of a measuring interval.

[0031] Embodiments of the present disclosure serve to optimize trends / forecasts that can estimate the expected future development of fill levels or pressures based on sensor measurements. These forecasts are particularly important for automated or time-critical replenishment or emptying planning.

[0032] A core aspect of the present disclosure can be considered to be the determination of the most reliable trends / forecasts possible, despite a significant reduction in the frequency of measurements (for energy-saving reasons, particularly with regard to autonomous or battery-operated measurement technology). This optimization is achieved by distributing the available measurements as efficiently as possible over time.

[0033] Thanks to various design options, fixed temporal events can be reliably detected and taken into account in trend determination. Such events can be any time-controlled process or fixedly scheduled deliveries or withdrawals. Such events could also be transmitted from a third-party system (e.g., a delivery planning system) to the sensor, the measuring device 100, or the control circuit 101 in order to sensibly plan measurement times, for example, to confirm the planned delivery.

[0034] In particular, it can be provided that the measurements are not carried out every x hours as usual, but staggered in time so that a measurement profile that is as consistent as possible is created over days and weeks, through which regular processes (events) between two measuring points can be detected and narrowed down more precisely by adjusting the measurement time in the next cycle.

[0035] All of the above-mentioned methods enable better temporal coverage of measurements in order to detect cyclical events as accurately as possible and thus create a better calculation basis for future forecasts.

[0036] By adjusting the times at which a measured value is recorded, the best possible coverage of all times of day or operating times of the measuring device should be achieved in order to record cyclical events such as fillings or emptyings and thus calculate meaningful trends / forecasts as efficiently as possible.

[0037] Fig. Figure 2 shows four consecutive measurement intervals, each spanning one week from Monday to Sunday. The adjacent dots on each day represent the measurement times in four consecutive weeks. The first dots in each row symbolize the measurement times in week 1, the second dots the measurement times in week 2, the third dots the measurement times in week 3, and the last dots the measurement times in week 4. The measurement times are at 12 noon on each weekday and at 4 p.m.

[0038] Fig. Figure 2 shows an example of conventional, cyclical recording of measured values. Typically, the measuring devices are set to take measured values ​​at fixed times or fixed intervals. For measurement times every four hours, this results in Fig. 2 shown measurement profile.

[0039] Assuming the measured container is filled with an additional 1,000 liters every Wednesday at 2 p.m., the configured measurement profile (the configured measurement times) only allows a linear trend between 12 p.m. and 4 p.m., since the exact time and duration of the filling cannot be determined. Thus, the filling process could take four hours or just a few minutes.

[0040] More precise information about the filling enables the Fig. 3 shows the time schedule of the measurements. These are staggered measurements, which are carried out, for example, over eight weeks. If the measurements are carried out as in Fig. 3, carried out a few minutes later each week, this results in a time-shifted measurement profile over several weeks, which makes it possible to determine the filling, which is carried out with reference to Fig. 2, significantly better time-bound. This allows for a much more accurate forecast without increasing the measurement frequency and the associated energy consumption.

[0041] Fig. Figure 4 shows another example, this time with a chaotic temporal distribution of the measurements. Similar to a fixed temporal shift of the measurement times, a chaotic temporal distribution of the measurement times can lead to cyclic events being detected faster and more reliably than with a conventional distribution as in Fig. 2 shown.

[0042] Fig. Figure 5 shows another example of the distribution of measurement times across multiple measurement intervals. This is the chaotic temporal distribution of the measurements, which was already described in Fig. 4, in combination with an adjustment of the measurement times by the control circuit. The basic approach is similar to the chaotic approach of Fig. 4, but is supported by the control / calculation circuit to enable a logical adjustment of the measurement times when changes in state are detected. This allows the time of an event (a filling or emptying, or another process) to be determined much more efficiently and precisely. The blue bar in Fig. Figure 5 outlines the filling event (Wednesday, 2 p.m.), which, after the first detection in week 1 (the left points on each day), can be further restricted in time by adjusting the measurement times in the following weeks.

[0043] The control / computation circuit can be located directly in or on the measuring device. Alternatively, it can be connected decentrally via a wireless or wired network. Alternatively, the control / computation circuit can be located in the cloud. Depending on the design, this control / computation circuit can also handle calculations for multiple sensors and, if necessary, combine the measured values ​​from several sensors.

[0044] To select the measurement times as efficiently as possible, the user simply sets the desired number of measurements (e.g., four measurements per day). The control / calculation circuit then independently determines suitable times.

[0045] Another embodiment can reduce or completely stop measurements on those days by detecting periods without state changes (e.g., weekends) through the control / computing circuit. The energy gained in this way can be used either to extend battery life or to increase the measurement frequency at certain event times to achieve greater measurement accuracy. This is Fig. 6, where it can be seen that no measurements are taken on Saturday and Sunday and instead the measurement density is significantly increased around the filling event on Wednesday at 2 p.m.

[0046] So, one can say that the number of measurements is reduced during uneventful times and the measurements saved are carried out at other times, so that the energy consumption in the measuring device remains constant.

[0047] Fig.7 shows a flowchart of a method according to an embodiment of the present disclosure. In step 701, measurements are carried out at preset measurement times within a repeating measurement interval, in particular daily, weekly, or monthly. In step 702, the preset measurement times are changed after the measurement interval has been completed in order to also record measured values ​​at otherwise measurement-free times. In step 703, the next measurement interval is then run through, during which the measurements are taken at the changed measurement times. In step 704, the preset measurement times are changed again after the second measurement interval has been completed, and in step 705, the third measurement interval is run through, in which measurements are taken at the now repeatedly changed measurement times.

Claims

[1] Measuring device (100), designed for process automation in an industrial or private environment, and for carrying out measurements at preset measuring times within a repeating measuring interval, in particular a daily, weekly or monthly repeating measuring interval, comprising: a control circuit (101) configured to repeatedly change the preset measurement times in order to also record measured values ​​at otherwise measurement-free times. [2] Measuring device (100) according to claim 1, wherein the preset measuring times are cyclically repeated measuring times on a daily, weekly or monthly basis. [3] Measuring device (100) according to claim 1 or 2, wherein the control circuit (101) is arranged to shift some or all of the preset measuring times by the same period of time. [4] Measuring device (100) according to one of the preceding claims, wherein the control circuit (101) is arranged to shift some or all of the preset measuring times by different time periods. [5] Measuring device (100) according to one of the preceding claims, wherein the control circuit (101) is configured to infer a cyclically repeating process between the first measurement time and the second measurement time from a change in a measured value between a first measurement at a first measurement time and a subsequent second measurement at a second measurement time, which is above or below a preset threshold value, and then to shift the first measurement time backward in time and the second measurement time forward in time for the following measurement interval, so that the time of the process can be determined more precisely. [6] Measuring device (100) according to one of the preceding claims, wherein the measuring device is a level measuring device; wherein the control circuit (101) is configured to infer a cyclically repeating filling process between the first measurement time and the second measurement time from an increase in a fill level measurement value between a first measurement at a first measurement time and a subsequent second measurement at a second measurement time, and then to shift the first measurement time backward in time and the second measurement time forward in time for the following week, so that the time of the filling process can be determined more precisely. [7] Measuring device (100) according to one of the preceding claims, wherein the control circuit (101) is arranged to determine time intervals in which the measurements provide constant measurement results; and wherein the control circuit (101) is arranged to reduce the number of measurements in these time intervals. [8] Measuring device (100) according to one of the preceding claims, wherein the control circuit (101) is arranged at least partially in the cloud (104). [9] Method for carrying out measurements at preset measuring times within a measuring interval which is repeated, in particular daily, weekly or monthly, comprising the steps: Carrying out measurements at preset measuring times within a recurring measuring interval, in particular daily, weekly or monthly; Changing the preset measurement times after the measurement interval has been completed in order to also record measured values ​​at times when measurements would otherwise not be taken; Carry out measurements at the changed measurement times within the following measurement interval. [10] Program element which, when executed on a control circuit (101) of a measuring device (100), instructs the measuring device to perform the following steps: Carrying out measurements at preset measuring times within a recurring measuring interval, in particular daily, weekly or monthly; Changing the preset measurement times after the measurement interval has been completed in order to also record measured values ​​at times when measurements would otherwise not be taken; Carry out measurements at the changed measurement times within the following measurement interval. [11] A computer-readable medium on which a program element according to claim 10 is stored.

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