EP4515506A1 - Verfahren zur gewinnung eines kennungsdatensatzes für eine industrielle anlage - Google Patents
Verfahren zur gewinnung eines kennungsdatensatzes für eine industrielle anlageInfo
- Publication number
- EP4515506A1 EP4515506A1 EP23712157.9A EP23712157A EP4515506A1 EP 4515506 A1 EP4515506 A1 EP 4515506A1 EP 23712157 A EP23712157 A EP 23712157A EP 4515506 A1 EP4515506 A1 EP 4515506A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- objects
- image
- images
- identifier
- sequence
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G43/00—Control devices, e.g. for safety, warning or fault-correcting
- B65G43/02—Control devices, e.g. for safety, warning or fault-correcting detecting dangerous physical condition of load carriers, e.g. for interrupting the drive in the event of overheating
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/776—Validation; Performance evaluation
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/17—Terrestrial scenes taken from planes or by drones
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/06—Recognition of objects for industrial automation
Definitions
- the present invention relates to a method for obtaining an identification data set for a plurality of objects to be inspected that recur along an industrial system based on a sequence of consecutive images recorded along the system.
- the invention further relates to a method for visually inspecting such objects.
- Conveyor belt systems for conveying bulk materials, for example.
- the bulk material such as overburden, ore, fuel or building materials
- Conveyor belt systems can also be referred to as conveyor belt systems or belt conveyor systems.
- the support rollers are usually rotatably mounted in support structures, so-called support roller chairs, which are evenly spaced apart along the conveyor route.
- a support roller chair can have one or more support rollers.
- the support rollers can be arranged in the support roller chair in a rigid or movable manner, for example in the form of a support roller garland. In this sense, support rollers and support roller chairs are understood as recurring objects along the conveyor belt system.
- Conveyor belt systems can have conveyor routes several kilometers long, in which several hundred support rollers are regularly provided per kilometer of conveyor route. For each of these support rollers, operational and/or weather-related wear and tear, such as increased running resistance caused by defective bearings, can lead to increased energy consumption of the system or even damage to the conveyor belt. Due to the size of such systems and the associated high number of location-specific support rollers, an inspection of all support rollers in the system always involves a high level of logistical effort.
- One way to carry out an inspection of conveyor belt systems is to use a drone or other unmanned vehicle to take images along the system and then evaluate them to determine the functional status of the idlers. Such a method is described, for example, in DE 102020206497 A1. The thermal images recorded are used to detect increased heat development in the area of a support roller, which indicates increased running resistance and thus a defect.
- DE 10 2020 206 497 A1 proposes as a solution to this problem a previous measurement of the entire system and the creation of a 3D model in which each role is assigned an exact GPS position.
- the necessary preparatory work on the system to be inspected and the process of creating the 3D model are extremely time-consuming and must be carried out by specialized specialists, which increases the overall cost of an inspection.
- DE 10 2020 206 497 A1 proposes attaching an RFID transponder to each support roller chair and enabling the images to be clearly assigned to the rollers using appropriate readout electronics in the drone. This also involves time-consuming and cost-intensive preparatory work on the system.
- RFID transponders can be damaged by weather or during the operation of the system and then have to be replaced at great expense.
- Conveyor belt systems based on the evaluation of along the system recorded images based.
- the images are recorded with a rail-bound vehicle and put together to form a panoramic image, which is intended to enable better positioning of individual rollers.
- rail-bound vehicles always require a rail guide that extends along the entire system, the installation of which requires a lot of work and money. Many systems are unsuitable for inspection using rail-bound vehicles due to their size or area of application. Rail-bound vehicles are also usually much slower and use more energy than free-moving or flying drones.
- processing into a panoramic image also requires that successive images overlap by more than 50%, which further limits the maximum travel speed of the rail-bound vehicle along the system. Furthermore, such high overlap results in a lot of redundant data having to be recorded and stored.
- the computer-implemented method according to the invention for obtaining an identification data set for a plurality of objects to be inspected, in particular idler rollers and/or idler roller chairs, recurring along an industrial system, in particular a conveyor belt system, on the basis of a sequence of successive images recorded along the system, comprises the following Steps:
- each object recognized in one or more images can be assigned a unique identifier, for example in the form of an identification number or character string, and recorded in an identifier data record.
- the identifier may also be referred to as an identifier or “ID”.
- ID an identifier
- the advantage of an identifier is that it can be assigned automatically or mechanically and initially without taking external information (such as position data, etc.) into account.
- the identifier can be ordered, for example as ascending sequence of numbers can be assigned.
- the identification data set is image-specific, that is, the identification data record shows which identifiers were assigned on the basis of a specific image and which images are the basis for assigning a specific identifier.
- the identifier record may include one or more databases.
- the object recognized in the original image and provided with an identifier is tracked in the subsequent image.
- position and/or movement data from the recording device used to record the sequence of images for example a freely moving or flying drone, can also be used for tracking purposes.
- the tracked object is preferably assigned the same identifier as in the original image.
- the object in the subsequent image can be assigned an identifier that is linked to the identifier of this object in the source image in a way that enables the identifiers to be uniquely assigned.
- a “new” object detected in the subsequent image that is not shown in the original image is assigned a new identifier.
- the method can be applied iteratively to all images of the sequence by selecting the subsequent image as a new initial image and another subsequent image after all identifiers have been assigned and repeating the object recognition and assignment of identifiers.
- the image of the sequence recorded immediately after the initial image is preferably used as the following image.
- the identification of the recognized objects can be recorded as an image-specific identification data set, for example, immediately during the respective assignment or after each iteration step.
- the method according to the invention is therefore particularly suitable for free Image sequences recorded by driving or flying drones, in which the recording perspectives between two images can vary more, both translationally and rotationally.
- the method delivers easily evaluable results even with a relatively small number of images per longitudinal section of the system to be inspected. This means that the duration of an inspection trip, particularly carried out using a drone, can be significantly shortened and the amount of data produced and subsequently evaluated can be reduced.
- the identifier assigned to the objects depicted and recognized in the images is an advantageous auxiliary variable that can be used for more efficient image evaluation and for a more precise assignment to the corresponding real objects in the system.
- the identification data set makes it possible to avoid redundant determinations about the functional status of an object through clever data management by evaluating only a selection or just one of these images instead of all the images on which an object is depicted and ignoring the remaining images or image areas. In this way, the evaluation of the images can be made more efficient.
- the assignment of an ordered identifier based on a specific reference or reference point of the system e.g. in the form of a count of the objects starting from one of the ends of the system, can provide a very simple way of assigning the recognized objects to the real objects of the system.
- such a system-related ordered identifier is preferably assigned.
- a roller determined to be defective through image evaluation is the 42nd roller on the left side in the conveying direction of the system acts.
- Images are the image data recorded with electronic image sensors, such as CCD or CMOS sensors, which can be further processed using electronic data processing systems.
- electronic image sensors such as CCD or CMOS sensors
- these images can be with an or may have been recorded by several cameras on a freely moving or flying drone.
- the images can be light images (RGB images) and/or thermal images (infrared images). Light images are somewhat better suited for object recognition due to the wider color spectrum. Thermal images are particularly suitable for identifying certain defects that are associated with increased heat generation, such as a bearing defect in a support roller.
- the recognition and tracking of objects depicted in the images can be carried out using known, suitable algorithms, in particular trained ones
- Machine learning algorithms from the field of digital image processing For example, “bounding boxes” can be used in object detection.
- the processing of the images can include segmentation, in particular “semantic segmentation”.
- an optically recognizable marker attached to the system is recognized on the initial image and/or the subsequent image and the identifier is assigned depending on the recognized marker.
- the idler roller chairs are provided with numbers or other markings using plates.
- a distance between two neighboring objects depicted in the initial image and/or in the subsequent image is determined, with a warning message about a potentially unrecognized object being recorded in the identification data set if the distance is a predetermined one or based on the sequence of The threshold value determined in the images is exceeded.
- the identification data set can be used to check whether the sequence of images also depicts all of the objects to be inspected and thus a complete inspection of the system can be guaranteed. For example, based on a warning message received, an image recording can be repeated in an area of the system where the potentially overlooked object is expected.
- Position data of the respective image recording position e.g. in the form of GPS (meta) data
- Position data of the respective image recording position of the images is preferably recorded in the identification data set.
- the threshold value for the distance can be set based on previously known information about the system. For example, the specification of a conveyor belt system usually contains the nominal distance between the idler rollers and/or idler roller chairs, which can be taken into account when determining the threshold value.
- the distance between imaged objects can also be determined statistically without previously known information based on the sequence of images and taken into account when determining the threshold value.
- the computer-implemented method according to the invention for the visual inspection of a plurality of objects to be inspected, in particular idler rollers and/or idler roller chairs, recurring along an industrial system, in particular a conveyor belt system, comprises the following steps:
- the functional state of the objects is determined based on the sequence of images.
- the sequence of images can include light images and/or thermal images.
- photographs for object recognition and creation of the identification data set and the thermal image for determining the
- the identification data set can of course also be used advantageously in combination with inspection data other than visual, for example acoustic data, which was recorded during the recording of the sequence of images.
- the functional state of the objects is determined on the basis of a real subset of the sequence of images, with the subset being selected based on the identification data set.
- evaluation of the images can be made more efficient. For example, redundant determinations about the functional status of an object can be avoided by evaluating only a selection or just one of these images instead of all the images on which an object is depicted and ignoring the remaining images or image areas.
- the invention is also directed to a computer program product for carrying out the method according to one of claims 1 to 3 and/or the method according to one of claims 4 to 6 on a computer.
- the step of recording a sequence of successive images along the system can be part of the method according to the invention.
- Fig. 1 is a flow chart of an embodiment of the invention
- Fig. 2 is a flow chart of a control procedure for checking
- FIG. 3 shows an initial image of a sequence of images recorded along a conveyor belt system as can be used in a method according to the invention according to FIG. 1;
- Fig. 4 is a subsequent image of the sequence of images according to Fig. 3;
- Fig. 5 is an image detail of an image along a
- Conveyor belt system the support roller chairs of which are provided with optical markers, recorded sequence of images as can be used in a method according to the invention according to FIG. 1;
- Fig. 6 is a flow chart of an embodiment of the invention
- FIG. 1 shows an embodiment of the method 100 according to the invention for obtaining an identification data set for a plurality of objects to be inspected that recur along an industrial system, based on a sequence of successive images recorded along the system, comprising the following steps:
- step 120 recognizing the object in the source image and assigning an identifier to the object (step 120);
- step 130 receiving a subsequent image of the sequence of images that was recorded from a different perspective than the initial image and on which the object and another object of the plurality of objects not imaged in the initial image are imaged (step 130); recognizing the object in the subsequent image and associating the identifier with the object (step 140);
- step 150 Recognizing the further object and assigning a new identifier to the further object (step 150);
- step 160 Repeat the previous steps with the following image as the new source image (step 160);
- FIG. 3 An exemplary output image 300, as can be used in a method according to FIG. 1 or 2, is shown in FIG. 3.
- An associated follow-up image 400 is shown in FIG. 4.
- a section of the conveyor belt system 2 is shown on the initial image 300.
- the conveyor belt system 2 comprises a closed conveyor belt 4, supported and guided by a plurality of support rollers 10, 11, 12, for transporting bulk goods, for example.
- the support rollers 10, 11, 12 are rotatably mounted in support roller chairs 10', 1T, 12' arranged along the conveyor route (cf. conveyor direction F).
- the support rollers 10, 11, 12 are evenly spaced from one another, with the upper support rollers 10, 12 having a distance D.
- the received subsequent image 400 (FIG. 3) is recorded from a different perspective than the initial image 300, here from a position offset in the conveying direction F.
- the following image 400 shows the support rollers 12, 13, 14.
- the support roller 12 is tracked on the subsequent image 400, that is, it is determined that this support roller is the same support roller as is also shown in the initial image 300.
- the support roller 12 is therefore assigned the same identifier 32 (“17”) as in the initial image 300.
- another identifier can also be assigned, which can be uniquely assigned to the identifier 32 in the initial image 300.
- the other support rollers 13, 14 recognized in the following image 400, which are not already in the initial image 300 have been recognized, new identifiers 33, 34 are assigned, here increasing numbers “18” and “19”.
- Assigning an identifier in this way has many advantages, especially in the area of visual inspection of idlers.
- the identification data set which shows, for example, which images of the sequence a specific idler roller is depicted, makes it possible to avoid redundant determinations about the functional status of a idler roller through clever data management by only selecting a selection or. instead of all the images on which the idler roller is depicted only one of these images is evaluated and the remaining images or image areas are ignored.
- the assignment of an ordered identifier based on a specific reference or reference point of the conveyor belt system, e.g.
- FIG. 3 to 5 in the form of a count of the support rollers starting from one of the ends of the system, can provide a very simple way to record the identified support rollers assign the images to real support rollers at the location of the conveyor belt system.
- a key advantage of an identifier is that it can be assigned automatically and initially without taking external information (such as position data, etc.) into account.
- a distance between two neighboring objects depicted in the initial image and/or in the subsequent image is determined (step 210).
- the distance is then compared with a predetermined threshold (step 220). If the threshold is exceeded, a Warning message recorded about a potentially unrecognized object. For example, with a view to FIG. 3, a distance D between the upper support rollers 10, 11 should remain constant over the entire conveyor path of the conveyor belt system 2. If there are deviations or the threshold value is exceeded, it can be determined that not all support rollers have been recognized.
- the threshold value for the distance can be determined based on previously known information. Alternatively or additionally, the distance between imaged objects can be determined statistically based on the sequence of images and taken into account when determining the threshold value.
- FIG. 6 shows an embodiment of the method 600 according to the invention for the visual inspection of a plurality of objects to be inspected that recur along an industrial system, comprising the following steps:
- step 620 Determination of a functional state of the objects (step 620); Detecting the respective functional state of the objects in the identification data set (step 630).
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Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102022204123.2A DE102022204123A1 (de) | 2022-04-28 | 2022-04-28 | Verfahren zur Gewinnung eines Kennungsdatensatzes für eine industrielle Anlage |
| PCT/DE2023/200050 WO2023208294A1 (de) | 2022-04-28 | 2023-03-09 | Verfahren zur gewinnung eines kennungsdatensatzes für eine industrielle anlage |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4515506A1 true EP4515506A1 (de) | 2025-03-05 |
Family
ID=85706771
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP23712157.9A Pending EP4515506A1 (de) | 2022-04-28 | 2023-03-09 | Verfahren zur gewinnung eines kennungsdatensatzes für eine industrielle anlage |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP4515506A1 (de) |
| DE (1) | DE102022204123A1 (de) |
| WO (1) | WO2023208294A1 (de) |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6809494B2 (ja) | 2017-07-14 | 2021-01-06 | Jfeスチール株式会社 | ベルトコンベアの管理方法および管理システム |
| DE102020206497A1 (de) | 2020-05-25 | 2021-11-25 | Thyssenkrupp Ag | Verfahren zum maschinellen Ermitteln des Funktionszustands von Tragrollen einer Gurtförderanlage, Verfahren zur Identifikation von funktionsbeeinträchtigen Tragrollen einer Gurtförderanlage, Computerprogramm zur Durchführung der Verfahren, maschinenlesbarer Datenträger mit einem darauf gespeicherten Computerprogramm und Einrichtung zum maschinellen Ermitteln des Funktionsstatus von Tragrollen einer Gurtförderanlage |
-
2022
- 2022-04-28 DE DE102022204123.2A patent/DE102022204123A1/de active Pending
-
2023
- 2023-03-09 WO PCT/DE2023/200050 patent/WO2023208294A1/de not_active Ceased
- 2023-03-09 EP EP23712157.9A patent/EP4515506A1/de active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| DE102022204123A1 (de) | 2023-11-02 |
| WO2023208294A1 (de) | 2023-11-02 |
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