USE OF THE LIDAR MEASUREMENT PRINCIPLE IN PROCESS TECHNOLOGY

Abstract

The present disclosure relates to a method for operating a measuring point in process engineering, wherein at least one Lidar (light detection and transmission) system is used at the measuring point, comprising: acquiring spatial information from the surroundings of the measuring point by means of the Lidar system; extracting object information from the spatial information; and reconstructing and identifying objects on the basis of the object information and associating the object information with the reconstructed and identified objects.

Claims

1. A method for operating a measuring point in process engineering, wherein a Lidar (light detection and transmission) system is used at the measuring point, the method comprising: acquiring spatial information from surroundings of the measuring point using the Lidar system; extracting object information from the spatial information; reconstructing and identifying objects on the basis of the object information; and associating the object information with the reconstructed and identified objects.

2. The method according to claim 1, further comprising: repeating the aforementioned method steps at predetermined time intervals and recording a time curve of the object information for each of the reconstructed and identified objects, including a change in spatial position, quantity, shape, and/or size over time; analyzing the time curve of the object information; and determining a prediction based on the analysis of the time curve of the object information and/or determining and carrying out an action based on the analysis of the time curve of the object information and/or the prediction.

3. The method according to claim 2, wherein an AI algorithm is used for reconstructing and identifying the objects, for analyzing the time curve of the object information, and/or for determining the action or the prediction.

4. The method according to claim 1, further comprising: enriching the object information with information from at least one further sensor system, including a camera or a radar system.

5. The method according to claim 2, wherein the measuring point is a measuring point used in aquaculture, wherein the objects are aquatic organisms, and wherein the object information includes the size and/or the number and/or an average value of the size or of the number of aquatic organisms.

6. The method according to claim 5, wherein the prediction contains information about the increase or decrease in the number of aquatic organisms or about the average value of the number of aquatic organisms.

7. The method according to claim 2, wherein the measuring point is a measuring point used in precision farming, wherein the objects are agricultural products, and wherein the object information includes the size and/or the number of agricultural products.

8. The method according to claim 7, wherein the prediction contains information about the increase or decrease in the number of agricultural products or about the average value of the number of agricultural products.

9. The method according to claim 2, wherein the measuring point is located in a process plant with at least one plant component, and wherein the objects are phase boundaries of at least two different media or of at least two media having different optical densities, and wherein the object information is a content of gas bubbles or solids.

10. The method according to claim 9, wherein the prediction contains a degree of change in a process quality.

11. The method according to claim 2, wherein the measuring point is used in a conveyor system, and wherein the objects are anomalies in bulk materials, including defective bulk material or foreign objects.

12. The method according to claim 11, wherein as the measure a distance of the anomaly is determined and carried out, wherein the position of the anomaly is indicated.

13. The method according to claim 5, wherein the predetermined time interval is in the order of magnitude of one hour to several days.

14. The method according to claim 9, wherein the prespecified time interval is in the order of magnitude of 0.1 ms to 10 s.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present disclosure is explained in greater detail with reference to the following figures. These show:

[0040] FIG. 1 shows a first exemplary embodiment of the method according to the present disclosure; and

[0041] FIG. 2 shows a second exemplary embodiment of the method according to the present disclosure.

DETAILED DESCRIPTION

[0042] Nowadays, Lidar systems 11, 11′ have become affordable and miniaturizable so that they can also be used advantageously as sensor technology for process engineering. Due to the substantially greater information content in comparison to single-point measurements, new applications can be opened up in process engineering.

[0043] A non-conclusive list of such application examples follows:

[0044] FIG. 1, left side, shows an application at a measuring point 1 in an aquacultural installation. Specifically, it is a tank in a fish farm in which a plurality of fish a, b, c, d, e are located underwater so that they can only be seen with difficulty and counted by operator personnel. For this reason, a Lidar system 11 in the form of a probe is placed centrally in the tank.

[0045] The Lidar system 11 is designed in such a way that it can detect its surroundings all round. For this purpose, the Lidar system emits a laser beam which is reflected at the surroundings and back to the Lidar system 11. On the basis of the reflection R, the Lidar system 11 can determine the distance from the surroundings. The Lidar system 11 can move the laser beam in a 360° circular movement to the starting position, for example by means of a movable mirror mechanism. The intensity of the reflections within the circular movement is recorded and referred to as spatial information 12. FIG. 1, bottom left, presents an example of such spatial information 12. It shows the intensity of the reflections R at the respective angle φ in the circular path. For the sake of simplicity, it is assumed here that the height of the laser beam remains the same and that the laser beam is moved in a horizontal 360° circular path. In reality however the height is also varied so that the entire surroundings of the Lidar system are ideally captured in a spherical shape.

[0046] Via a wired or wireless network, for example a LAN or the internet, the Lidar system 11 is in communication with an external unit 2, for example a cloud, and is designed to transmit the acquired spatial information 12 via the established communication link to the external unit 2. A logic controller implemented in the external unit, for example an AI algorithm, analyzes the spatial information 12 and extracts object information a′, b′, c′, d′, e′. This object information a′, . . . , e′ can be seen in the diagram in the form of dips in the measurement curve of the reflections R. The logic controller then recognizes or identifies the fish a, . . . , e as objects, on the basis of empirical values, for example. On the basis of the properties of the object information a′, . . . , e′, the logic controller can make a statement not only about the quantity of fish a, . . . , e but also about size or weight. Alternatively, the logic controller is implemented in the Lidar system 11 such that the Lidar system 11 carries out the aforementioned steps. For this purpose, however, sufficient resources in the form of computing power (CPU/GPU), memory space, and working memory must be present.

[0047] The object information a′, . . . , e′ and the statements made regarding the objects a, . . . , e are stored in the external unit 2 or in a memory unit of the Lidar system 11. Measurement is repeated at regular time intervals, for example in a range of several hours to several days. The time curve of the object information is recorded and analyzed by the logic controller in particular with regard to changes. For example, an analysis is made as to whether the fish stock has changed or whether the (mean) size and/or the weight of the fish has changed. Furthermore, the logic controller can calculate a prediction of increase or decrease in the fish stock. Moreover, the logic controller can recommend carrying out an action in the event that the prediction or change does not behave as desired. The operator can then carry out a suitable measure, for example the relevant change in water temperature or the variation in the frequency of the nutrient supply.

[0048] In the event that a large number of fish are located in the basin (see FIG. 1 on the right), interpretation of the spatial information 12 can be more difficult, for example, when two or more fish are located close to one another. In order to improve the analysis, the spatial information can be enriched with data from another sensor system. For example, an integrated or external camera can be used, which captures a photo or a video of the surroundings of the Lidar system 11.

[0049] In a modified exemplary embodiment, the Lidar system is used in a so-called precision farming (German: “Prazisionslandwirtschaft”) application. Instead of detecting aquatic life forms as objects, agricultural products, for example fruits or animals, are detected and their stock or change in size is tracked over time. Depending on the change over time, the logic controller can suggest that water and nutrient supplies be decreased or increased for optimal development of the agricultural products.

[0050] FIG. 2 shows that the Lidar system 11′ is to be installed in or attached to a plant component 13—in this case a pipe—of a measuring point 1′ of a process plant. A fluid measurement medium flows through the pipe 13. Alternatively, several different measurement media with different optical densities are located in the plant component, for example a tank. Phase boundaries f in the flowing measurement medium are identified as objects on the basis of the spatial information obtained by the reflections R. These phase boundaries f, which are, for example, gas bubbles (in the case of a flowing measurement medium) or suspended solids (in measurement media of different optical densities), or which are produced on account of different aggregation states (e.g., in the case of ice water as a fluid measurement medium), can be detected by the logic controller implemented in the external unit 2 in terms of quantity, shape, magnitude and/or local movement and observed over time. The measurement frequency must be selected to be very high for this purpose.

[0051] The logic controller can also execute other functions. For example, the latent energy can be deduced from the ratio of ice to water in a measured volume. It may, for example, also be provided to supply the operator of the process plant with information that an action for maintaining or influencing the process is to be carried out, for example cleaning a plant component 12, when gas bubbles, for example, are increasingly occurring.

[0052] Alternatively, the plant component 12 can be a conveyor belt on which bulk material (e.g., a harvested crop) is conveyed. By evaluating the spatial or object information, anomalies and foreign objects can be identified.