ADAPTIVE MODULE FOR MONITORING WELDING PROCESSES IN MANUAL WELDING WITH LIGHTOPTIC-HAPTIC ACTUATORS

Abstract

The invention relates to an adaptive module for monitoring welding processes in manual welding with optical sensors, wherein the adaptive module comprises at least one energy unit, a computer unit with at least one actuator unit. Furthermore, the invention relates to a use of the adaptive module.

Description

[0001] The invention relates to a device as an adaptive module for monitoring welding processes during manual welding using light-optical and / or haptic actuators. The device relates to an adaptive module that can be attached to a respective welding helmet or worn on the body, which has at least one actuator system and, in particular, displays process deviations, welding defects, and the like in real time.

[0002] Process parameter analyses using machine learning models are used to evaluate and analyze the data collected by a sensor system in the digital process mapping.

[0003] According to the invention, an adaptive module for monitoring welding processes during manual welding with light-optical-haptic actuators (AMLOH) is understood to be a device for light-optical and / or haptic feedback in the identification of process anomalies, including the possibility of compensating the detected anomaly by means of an actuator, during manual welding / cutting or related thermal processes.

[0004] Machine learning is understood to be a sub-area of ​​AI (artificial intelligence) that can carry out algorithmic processes using data processing models. The core processes here include the model's ability to learn from data, understand logical relationships, and self-correct through adaptation. This enables the digital generation of knowledge and experience. A model learns from examples using training models, enabling identification and expanded interpretation of input data. For this purpose, machine learning algorithms generate approaches to relationships based on the training data, which are then tested against the resulting data. In this way, patterns and regularities are recognized in the learning data. This enables the system to evaluate even unknown data. The most striking feature of this method is the lack of provision of solution approaches.The system generates a solution based only on input and output data and checks it for accuracy.

[0005] One approach for processing serial process data is to mathematically classify, weight, evaluate and assign the recorded data sets to a result space using artificial neural networks (CNN - Convolutional Neural Network) with classifiers of numerical measurement results.

[0006] The adaptive module consists of connectable housing units that together form a separate system, whereby different components with different properties are considered as a common whole due to defined relationships with each other, which solve the given task.

[0007] In a first embodiment, the AMLOH comprises housing units that can be detachably connected to one another and which consist, for example, of an energy unit, a computing unit and an actuator unit.

[0008] The power unit comprises at least one housing housing a charger with a battery management system and accumulators. Power is transferred to the consuming units using spring contact pins (pogo pins). The connection to the computing unit is established via a magnetic connection for easy replacement.

[0009] The computer unit comprises at least one housing in which a sufficiently compact computer module for digitally processing the recorded data (e.g., a single-board computer) is installed, with shielding against process-related electromagnetic interference (e.g., ferrite foil). Furthermore, the computer unit includes external connections for communication with external devices, in particular IoT (Internet of Things)-capable devices. A module for communication with a standardized, wireless or wired data transmission, such as Bluetooth and Wi-Fi, is provided for this purpose. In the case of wireless transmission, an antenna designed according to the data transmission requirements is also provided. The computer unit includes at least one LED display for displaying setting modes and checking the wireless data connection.

[0010] The design allows for the expansion of additional sensors and actuators, such as light-optical or haptic signals. The computer unit includes a multi-pin connector for this purpose. Its size allows it to be comfortably worn on the body, for example, on a belt or battery pack for ventilated safety shields. The computer unit includes a belt clip for this purpose, but can also be supplemented with alternative mounting devices, such as a screw connection directly to the welding helmet.

[0011] The actuator unit comprises at least one housing in which an actuator and a multi-pin plug connection are installed. The actuator unit can be accommodated within a welder's protective shield or goggles due to its size. The actuator unit determines the functional scope of the AMLOH and its specific type of feedback and interaction. Light-optical and haptic actuators can be used for this purpose, which map process deviations or errors detected by the machine learning model into signals that can be interpreted by the user. Furthermore, the actuator unit can be expanded to almost any level of complexity, for example,

[0012] Connections of so-called “smart” welding helmets can be controlled in order to map the identified deviations and errors into an augmented reality, or, for example, to use optical sensors to operate the AMLOH by eye tracking and control.

[0013] The simple design of the AMLOH enables the replacement of damaged individual components and / or housing units, such as the energy unit, computer unit, actuator unit or the individual components in the possibly separate housing units, such as charger, batteries, switches, display, single-board computer, sensors, actuators and the fastening.

[0014] The housing units are preferably manufactured according to applicable industry standards and are designed to be heat-resistant, especially for welding conditions, so they can be used even in closed welding cells or exceptionally tight work spaces. To increase heat resistance, additives such as fillers or stabilizers are added to the housing materials, which are preferably made of plastic. The housing units are designed for additive manufacturing. State of the art

[0015] A number of publications are known from the state of the art that deal with the topic in general terms without showing concrete solutions: Journal of Manufacturing Systems; Volume 57, October 2020, Pages 1-18: Application of sensing techniques and artificial intelligence-based methods to laser welding real-time monitoring: A critical review of recent literature; Wang Cai, JianZhuang Wang, Ping Jiang , LongChao Cao, GaoYang Mi, Qi Zhou; https: / / doi.org / 10.1 016 / j.jmsy.2020.07.021.

[0016] DE 10 2011 016 124 A1 shows a spot welding system and post-processing determination method, wherein the spot welding system, a welding gun with an openable or closable electrode pair and a post-processing determination device determines the quality of a forming process applied to an electrode of the electrode pair.The post-processing determining device includes an optical sensor that obtains an image of the electrode, identifies a base and a tip of the electrode in the image, and measures a distance between the base and the tip in the image by image processing, an optical sensor control section that has the optical sensor measure the distance immediately before and after performing the forming process, a removal amount calculating section that calculates a difference between the distances measured by the optical sensor immediately before and after performing the forming process as a removal amount of the electrode, and a removal amount judging section that judges whether the calculated removal amount is within a predetermined acceptable range.

[0017] EP 3 010 677 B1 discloses a system and method for determining a welding speed, while EP 2 986 419 B1 discloses a power tool with, among other things, integrated sensors and evaluation devices. Both documents are examples of the wide range of integrated systems.

[0018] This is where the invention comes in, as the inventive AMLOH eliminates the deficiencies of integrated systems by: - The possibility of easily upgrading all commercially available welding systems for manual processes. This is not possible with integrated solutions, as these require the development of specific solutions for each system type. - easy installation on the device without any further specialist knowledge; - modularity of all AMLOH components and fastening, which requires minimal effort in the event of necessary repairs / replacement of damaged components (standard components); - easy service and maintenance; - system-independent handling, i.e. in the event of a failure of the AMLOH, the welding / cutting process is not affected or interrupted, as there is no direct system integration and no interface to the welding system; - an independent power supply; - an adjustment that can be carried out easily and requires only minimal effort; - non-slip installation by clamping during fastening. Tasks

[0019] A first object of the invention is to provide a technically simple device that can be manufactured as a modular product and is easily adaptable to known systems in order to transmit process analyses and predictions from machine learning models into interpretable signals directly to the operator / welding specialist, thereby representing the interface from the model (digital analysis level) to the operator (manual process environment).

[0020] A further task is to adjust the sensitivity of the response to the incoming error signals in order to adapt the application to welding specialists with different experience levels. This plays a particularly important role in potential applications as an assistance system for training purposes. The analysis model provides feedback via a percentage value indicating the probability of a process deviation or error. The sensitivity of the AMLOH can be adjusted based on this value, so that, for example, the signal is only triggered at a probability of 85%. Furthermore, signal patterns can be graded as an extension of the interpretation of predicted probabilities, for example, a flashing LED for ranges of 50-80% and a continuously lit LED for 80-100%.

[0021] A preferred exemplary embodiment is the use of a light-optical actuator unit with binary feedback on the process sequence or weld seam quality (LED on = error, LED off = process OK). This represents the simplest form of interpreting the model analysis. The computer unit and energy unit are worn on the belt with a clamp holder and connected via a cable connection or wirelessly to the actuator unit in / on the welding shield or goggles.

[0022] Another embodiment, for example, provides more complex feedback through actuators with haptic or projecting functions. The interpretation options extend into the real world and allow, for example, the display of defective areas by projecting them directly onto the weld seam. The computer unit and power unit can also be integrated directly into the welding shield, and the cable connection to the actuator unit can be realized by extending it with a self-contained power unit via Bluetooth.

[0023] This task or tasks are solved with an adaptive module for monitoring welding processes during manual welding with light-optical sensors according to the main claim.

[0024] Further advantageous embodiments can be found in the subclaims.

[0025] The adaptive module for monitoring welding processes during manual welding with light-optical sensors, the adaptive module has at least one energy unit, a computer unit with at least one actuator unit.

[0026] It is further advantageous if the respective energy unit comprises at least a housing, a charger with a battery management system and an accumulator.

[0027] In a preferred embodiment, the respective computer unit comprises at least a housing, a computer module, a display and a built-in multi-pin plug connection and fastening, in particular or for example a belt clip.

[0028] Furthermore, the respective actuator unit can preferably have at least one housing, an actuator module, which is designed, for example, to be light-optical, haptic, or projecting, and a built-in multi-pin plug connection.

[0029] Furthermore, the invention provides for the use of the previously claimed adaptive module with a welding shield / helmet or goggles of any standard design.

[0030] The invention is described below with reference to the accompanying figures in the figure description, which are intended to explain the invention and are not to be considered limiting.

[0031] They show: Fig. an exemplary adaptive module for monitoring welding processes during manual welding with a light-optical actuator in a perspective view; Fig. an exemplary adaptive module for monitoring welding processes during manual welding in a front view; Fig. an exemplary adaptive module for monitoring welding processes during manual welding in a side view; Fig. an exemplary adaptive module for monitoring welding processes during manual welding in a rear view; Fig. an exemplary energy unit in a perspective view; Fig. an exemplary energy unit in a side view; Fig. an exemplary energy unit in a top view; Fig. an example energy unit in a bottom view; Fig. an exemplary computer unit in a perspective view; Fig. an exemplary computer unit in a front view; Fig. an exemplary computer unit in a side view; Fig. an exemplary actuator unit as a light-optical variant in perspective view; Fig. an exemplary actuator unit as a light-optical variant in front view; Fig. an exemplary actuator unit as a light-optical variant in side view; Fig. an exemplary actuator unit as a light-optical variant in rear view; Fig. an exemplary adaptive module with light-optical actuators for monitoring welding processes during manual welding in an installation variant on the harness and helmet; Fig. an exemplary adaptive module with light-optical actuators for monitoring welding processes in manual welding and joining technology and Fig. an example schematic structure of an AMLOH. List of reference symbols 1 Adaptive module for monitoring welding processes during manual welding with light-optical-haptic actuators (AMLOH) 2 energy units 3 Computer unit 4 Actuator unit 5 connecting cables 6 Energy unit housing shell 7 Energy unit housing cover 8 Computer unit housing shell 9 Computer unit housing cover 1 10 Computer unit housing cover 2 11 Actuator unit housing shell 12 Actuator unit housing cover 13 Charger with battery management system 14 accumulators 15 spring contact pins (magnetic pogo pin connection) 16 switches 17 Display 18 single-board computers 19 Light-optical actuator (built-in LED) 20 antenna 21 Belt clip 22 multi-pin panel connector (female) 23 multi-pin connector (m / male) 24 welding specialists 25 Welding shield / helmet 26 Cover screw 27 Belt clamp screw 28 Interface (Micro USB) 29 Energy level display 30 Shielding

[0032] Fig. shows an exemplary adaptive module for monitoring welding processes during manual welding with a light-optical actuator in a perspective view.

[0033] Fig. shows an exemplary adaptive module for monitoring welding processes during manual welding in a front view.

[0034] Fig. shows an exemplary adaptive module for monitoring welding processes during manual welding in a side view.

[0035] Fig. shows an exemplary adaptive module for monitoring welding processes during manual welding in a rear view.

[0036] Fig. shows an example energy unit in a perspective view.

[0037] Fig. shows an example energy unit in a side view.

[0038] Fig. shows an example energy unit in a top view.

[0039] Fig. shows an example energy unit in a bottom view.

[0040] Fig. shows an example computer unit in a perspective view.

[0041] Fig. shows an example computer unit in a front view.

[0042] Fig. shows an example computer unit in a side view.

[0043] Fig. shows an exemplary actuator unit as a light-optical variant in perspective view.

[0044] Fig. shows an exemplary actuator unit as a light-optical variant in front view.

[0045] Fig. shows an exemplary actuator unit as a light-optical variant in side view.

[0046] Fig. shows an exemplary actuator unit as a light-optical variant in rear view.

[0047] Fig. This example shows an adaptive module with light-optical actuators for monitoring welding processes during manual welding, installed on a harness and helmet, and corresponds to the preferred exemplary design. The computer unit and power unit are worn on the body via a belt clip (belt or battery belt for ventilated welding protection systems). A cable connection running along the back connects the computer unit to the actuator unit mounted in the welding shield. This is screwed or glued into the shield and is located within the welder's peripheral field of vision.

[0048] Fig. shows an exemplary adaptive module with light-optical actuators for monitoring welding processes in manual welding and joining technology.

[0049] Fig. shows an example schematic structure of an AMLOH. QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] DE 10 2011 016 124 A1

[0016] EP 3 010 677 B1

[0017] EP 2 986 419 B1

[0017] Cited non-patent literature

[0000] Journal of Manufacturing Systems; Volume 57, October 2020, Pages 1-18: Application of sensing techniques and artificial intelligence-based methods to laser welding real-time monitoring: A critical review of recent literature

[0015] Wang Cai, JianZhuang Wang, Ping Jiang, LongChao Cao, GaoYang Mi, Qi Zhou; https: / / doi.org / 10.1 016 / j.jmsy.2020.07.021

[0015]

Claims

[1] Adaptive module for monitoring welding processes during manual welding with light-optical sensors, wherein the adaptive module has at least one energy unit, a computer unit with at least one actuator unit. [2] Adaptive module according to claim 1, characterized by that the respective energy unit comprises at least a housing, a charger with a battery management system and an accumulator. [3] Adaptive module according to one of the preceding claims, characterized by that the respective computer unit comprises at least a housing, a computer module, a display and a built-in multi-pin plug connection. [4] Adaptive module according to one of the preceding claims, characterized by that the respective actuator unit has at least a housing, an actuator module and a built-in multi-pin plug connection. [5] Use of the adaptive module according to any one of the preceding claims with a welding shield / helmet or goggles of any standard design.

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