WO2022126564A1

WO2022126564A1 - High-reliability anti-arc light interference welding polymorphic data intelligent agent and processing method

Info

Publication number: WO2022126564A1
Application number: PCT/CN2020/137415
Authority: WO
Inventors: 冯消冰; 刘文龙
Original assignee: 南京水木自动化科技有限公司
Priority date: 2020-12-18
Filing date: 2020-12-18
Publication date: 2022-06-23

Abstract

A high-reliability anti-arc light interference welding polymorphic data intelligent agent and a processing method, the intelligent agent comprising: a master controller (101), which is used for collecting data in real time from various types of sensing devices of a crawling welding robot (100); a communication controller (102), which is communicatively connected to a cloud state monitoring device (106); a physical anti-interference isolation layer (103), which is provided between the master controller (101) and the communication controller (102), the physical anti-interference isolation layer (103) being used for outer layer isolation; an application layer (104), which is communicatively connected to the master controller (101), the application layer (104) comprising an application layer intelligent main node (114) and an application layer intelligent standby node (124) which are communicatively connected to one another; and a physical entity storage layer (105), which is communicatively connected to the application layer (104), the physical entity storage layer (105) comprising a physical layer storage entity main node (115) and a physical layer storage entity standby node (125) which are communicatively connected to one another, and the physical layer storage entity main node (115) being communicatively connected to the application layer intelligent main node (114).

Description

High-reliability and anti-arc interference welding polymorphic data agent and processing method

technical field

The invention relates to the technical field of welding robots, in particular to a highly reliable and anti-arc interference welding polymorphic data intelligent body and a processing method.

Background technique

Welding robots are industrial robots engaged in welding, and have had an important impact on various fields of modern high-tech industries and even people's lives. When the welding robot is in working state, the main body of the robot travels to the surface of a large steel structure for welding, and is located on the ground or scaffolding. The control device on the robot controls the main body of the robot to complete the welding work. The inventor found that the data generated in the welding process can be used to feedback the product quality defects in the welding robot, and the performance optimization of the welding robot can be fed back through the data to further ensure the welding quality, and finally optimize and iterate a high-quality welding robot. However, since there are many types of data involved in the welding process, how to manage them effectively is a complicated problem. The information disclosed in this Background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person of ordinary skill in the art. The information disclosed in this Background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person of ordinary skill in the art.

technical problem

The purpose of the present invention is to provide a highly reliable anti-arc interference welding polymorphic data agent and processing method, which can process the original welding data of various forms to form usable data that is conducive to analysis, thereby abstracting product quality. question.

technical solutions

In order to achieve the above purpose, the present invention provides a welding polymorphic data intelligent body with high reliability and anti-arc interference, including: a main controller, which is used to collect data in real time from various sensing devices of the crawling welding robot, and provides Multiple data interfaces; communication controller, which is connected to the cloud status monitoring device; physical anti-interference isolation layer, which is set between the main controller and the communication controller, and the physical anti-interference isolation layer is used for outer isolation; application layer , which is communicatively connected to the main controller, and the application layer includes an application-layer intelligent master node and an application-layer intelligent standby node that are connected in communication, wherein, when the application-layer intelligent master node fails, the application-layer intelligent master node and the application-layer intelligent standby node State switching is possible, and both the application layer intelligent master node and the application layer intelligent standby node include a composite intelligent body module with a plurality of intelligent algorithms; and a physical entity storage layer, which is communicatively connected to the application layer, and the physical entity storage layer includes a communication connection The master node of the physical layer storage entity and the backup node of the physical layer storage entity, the master node of the physical layer storage entity and the intelligent master node of the application layer are connected in communication, wherein, when the master node of the physical layer storage entity fails, the master node of the physical layer storage entity and the intelligent master node of the application layer are connected in communication. The physical layer storage entity standby node can make the physical entity storage layer work normally through state switching.

In a preferred embodiment, in the process of entering the cloud synchronization, the state switch is changed to the off state. If the crawling welding robot is in the running state at this time, the time consistency verification algorithm will logically verify the normalized morphological data. It is sent to the slice stack backup queue; when the cloud synchronization is completed, the slice stack backup queue is merged into the slice stack queue, and the status switch is changed to the ON state.

In a preferred embodiment, transforming the image data of the weld through the image feature characterization algorithm includes the following steps: first, the RGB image is subjected to binarization grayscale processing, and then scanned through a plurality of neural nuclei, and the convolution calculation is performed. Low-dimensional data, through multiple low-dimensional processing, finally output several 1*N-dimensional data, and then intercept different segments to represent each data, so that effective features can be extracted from the weld image according to the time dimension and represented as structured multi-dimensional data .

In a preferred embodiment, the abnormal screening and processing of the original data of the welding machine data and the main push data includes the following steps: filtering the abnormal time series data on the original data of the welding machine data and the main push data, and then finding out all problematic data. A collection of time points, and all data in this collection are eliminated to obtain normalized morphological data.

In a preferred embodiment, the data collected by the main controller includes image data, welding machine data and machine body motion data.

beneficial effect

Compared with the prior art, the beneficial effects of the highly reliable anti-arc interference welding polymorphic data agent and the processing method of the present invention are as follows: the present invention configures the application layer to include an application layer intelligent master node and an application layer intelligent backup node. Active and standby dual node management, the physical entity storage layer is set to include the physical layer storage entity master node and the physical layer storage entity standby node. The welding data is not lost to the greatest extent, and the welding quality data, welding machine data and robot body motion data generated by welding are recorded.

By setting up a composite intelligent body with a combination of multiple artificial intelligence algorithms, the readability and availability of the multi-modal robot operating state data is effectively guaranteed, and the bottleneck of centralized management and processing of welding data is broken; by setting a physical anti-interference isolation layer , which can effectively shield arc light and electromagnetic waves in special frequency bands, thus ensuring the authenticity of welding sequence data. By setting up a physical anti-interference isolation layer, the interference of arc light and some electromagnetic fields can be avoided, the high-quality transmission of original ecological data to the cloud can be ensured, and a reliable hardware base framework can be established for truly reflecting the running state of robots on a scale of tens of millions.

Description of drawings

Figure 1 is the structure of the highly reliable anti-arc interference welding polymorphic data agent of the preferred embodiment of the present invention

block diagram.

FIG. 2 is a flow chart of a method for intelligent processing of welding polymorphic data with high reliability and anti-arc interference according to a preferred embodiment of the present invention.

Embodiments of the present invention

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. The embodiments of the present invention, and all other embodiments obtained by those of ordinary skill in the art without creative work, fall within the protection scope of the present invention.

Unless expressly stated otherwise, throughout the specification and claims, the term "comprising" or its conjugations such as "comprising" or "comprising" and the like will be understood to include the stated elements or components, and Other elements or other components are not excluded.

Example 1

As shown in Figures 1-2, the highly reliable anti-arc interference welding polymorphic data agent according to a preferred embodiment of the present invention includes: a main controller 101, a communication controller 102, a physical anti-interference isolation layer 103, and an application layer 104 and the physical physical storage layer 105. Among them, the main controller 101 is used to collect data in real time from various sensing devices of the crawling welding robot 100, and provides multiple data interfaces. The communication controller 102 is in communication connection with the cloud state monitoring device 106 . The physical anti-interference isolation layer 103 is arranged between the main controller 101 and the communication controller 102, and the physical anti-interference isolation layer 103 is used for outer layer isolation. The application layer 104 is in communication connection with the main controller 101, and the application layer 104 includes an application layer intelligent master node 114 and an application layer intelligent standby node 124 that are communicatively connected. When the application layer intelligent master node 114 fails, the application layer intelligent master node 114 and the application layer intelligent standby node 124 can perform state switching, thereby quickly realizing the time series data processing and response capabilities of the agent. The application layer intelligent master node 114 and the application layer intelligent standby node 124 each include a composite agent module 134 having a plurality of intelligent algorithms. The physical entity storage layer 105 is in communication connection with the application layer 104. The physical entity storage layer 105 includes a physical layer storage entity master node 115 and a physical layer storage entity backup node 125 that are communicatively connected, and the physical layer storage entity master node 115 and the application layer intelligent master node. 114 Communication connection. Wherein, when the physical layer storage entity master node 115 fails, the physical layer storage entity master node 115 and the physical layer storage entity backup node 125 can make the physical entity storage layer 105 work normally through state switching.

In a preferred embodiment, a composite agent with multiple intelligent algorithms includes a polymorphic time series data queue, an image feature representation intelligent algorithm body, an anomaly detection intelligent algorithm body, a time check consistency intelligent algorithm body, and an active and standby slice heap processing. body.

In a preferred embodiment, the physical entity storage layer includes an I/O read/write function and a storage function, and the I/O read/write function requires that the read/write speed is not lower than the frequency of commands issued by the main controller. The storage function satisfies the ability to report twice the failure period in the extreme case of data failure in the cloud, that is, the locally reserved free storage space resources must be guaranteed by 2 times.

In a preferred embodiment, the physical anti-interference isolation layer is a carbon nanotube (CNT) fiber material, which is used to absorb the electromagnetic radiation of the arc light.

In a preferred embodiment, the data collected by the main controller includes image data, welding machine data and machine body motion data, and the multiple data interfaces include a time series image data interface, a main push time series data interface, a welding time series data interface and a slider time series. The data interface is used to transmit time series images, main push data, welding machine data and slider data respectively.

Example 2

As shown in FIG. 2 , the present invention also discloses a highly reliable anti-arc interference intelligent processing method for welding polymorphic data, including the following steps: constructing a main controller 101, a physical anti-interference isolation layer 103, an application layer 104, a physical entity The storage layer 105 and the communication controller 102 ; the main controller 101 collects data in real time from multiple sensing devices of the crawling welding robot 100 .

The main controller 101 transmits the collected data to the composite intelligent body module with multiple intelligent algorithms of the intelligent master node of the application layer through multiple data interfaces. Among them, the multiple data interfaces include a time series image data interface, a main push time series data interface, a welding time series data interface and a slider time series data interface, which are respectively used to transmit time series images 201, main push data 202, welding machine data 203 and slider data 204.

When the composite agent module receives the time series image 201, the main push data 202, the welding machine data 203 and the slider data 204, the time series image 201, the main push data 202, the welding machine data 203 and the slider data 204 enter the time series queue 211.

The image feature characterization intelligent algorithm body 212 converts the image data of the weld through the image feature characterization algorithm, outputs the parameters of the unwelded weld, and outputs the welding quality data that has been welded.

The abnormality detection intelligent algorithm body 213 performs abnormality discrimination on the transformed data through the abnormality detection intelligent algorithm, and performs abnormality discrimination and processing on the welding machine data and the original data of the main push data, and obtains normalized morphological data.

The temporal consistency checking algorithm body 214 performs logical checking on the normalized morphological data through the temporal consistency checking algorithm, and obtains time-series single morphological data.

When the state switch 217 is turned on, the time series single morphological data is subjected to heap processing to form extractable time axis playback data. The time axis playback data is subjected to slice stack processing in the slice stack queue 215 and stored in the physical entity storage layer. 105.

The cloud state monitoring device 106 periodically obtains the data stored in the physical entity storage layer 105 through the communication controller 102 synchronously. Among them, both the application layer and the physical entity storage layer have the dual-node disaster recovery and backup switching function of the active and standby nodes. When the application layer intelligent master node fails, the application layer intelligent master node and the application layer intelligent standby node perform state switching; and when the physical layer storage entity master node fails, the physical layer storage entity master node and the physical layer storage entity standby node. The physical physical storage layer works normally through state switching.

Example 3

In a preferred embodiment, in the process of entering the cloud synchronization, the state switch 217 is changed to the off state. If the crawling welding robot 100 is in the running state at this time, the time consistency check algorithm normalizes the logic check. The morphological data is sent to the slice stack backup queue 216; when the cloud synchronization is completed, the slice stack backup queue 216 is merged into the slice stack queue 215, and the state switch 217 is changed to the ON state.

In a preferred embodiment, transforming the image data of the weld through an image feature characterization algorithm includes:

The following steps: first perform binary grayscale processing on the RGB image, then scan through multiple neural nuclei, calculate low-dimensional data by convolution, and finally output several 1*N-dimensional data through multiple low-dimensional processing, and then separately Different segments are intercepted to represent each data, so that effective features can be extracted from the weld image according to the time dimension and represented as structured multi-dimensional data.

In a preferred embodiment, abnormal screening and processing are performed on the original data of the welding machine data and the main push data to obtain normalized morphological data, including the following steps: the original data of the welding machine data and the main push data are processed as abnormal time series data. Filter, and then find out all problematic time point sets, and remove all data in this set to obtain normalized morphological data. For example, the welding machine data (such as current and voltage) has a certain reasonable value range, but when it is transmitted through the controller, due to various reasons, there will be abnormal conditions, which exceed reasonable expectations, and obvious error data will appear, so abnormal The detection algorithm will ensure that reasonable data is retained and unreasonable data is deleted through several means:

1. Pre-set the value range such as [100, 250], delete it if it exceeds.

2. The values of two adjacent time points vibrate violently, with large-span jumps, and they will also be deleted if they exceed a reasonable range. 3. The value of the continuous time period is close to the reasonable upper and lower thresholds. It is necessary to add logical judgment and conditional detection and deletion. The normalized morphological data means that the types of data from different welding machine bodies are inconsistent, and the upper and lower limit value ranges are different, which needs to be unified here. Flatten to 0~1 range, such as voltage/current/main thrust speed, etc.

In a preferred embodiment, the time consistency check algorithm is based on the data in the interval 0~1 at all the above time points. For example, the result from the image algorithm at 0:01 shows that welding is in progress, but the speed of the main pusher is normal. The normalization value is close to 0. It may be that the time information returned by a certain welding machine component is incorrect, resulting in a time misalignment problem. Therefore, it is necessary to perform time correction again and do a feedback process. The output of the time consistency check algorithm is managed separately according to the dimensions of the different bodies of the welding machine robot. For example, the welding machine has a set of 0~1 data, the main pusher has a set of 0~1 data, and the slider has a set of 0~1 data, all of which are in chronological order. The heap processing is sorted according to the time dimension and regularly compressed (such as every minute) to form a bag. document.

The invention ensures the effective management and feedback of the polymorphic data of tens of millions of welding robots in end-testing through the excellent advanced technology of software and hardware, and finally can form the product portrait of the real product of the welding robot, which is used to guide the R&D iteration and precise optimization of the robot.

As will be appreciated by those skilled in the art, the embodiments of the present application may be provided as a method, a system, or a computer program product.

Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, and substitutions can be made in these embodiments without departing from the principle and spirit of the invention and modifications, the scope of the present invention is defined by the appended claims and their equivalents.

Claims

A welding polymorphic data intelligent body with high reliability and anti-arc interference is characterized in that: the welding polymorphic data intelligent body includes: a main controller, which is used to collect data in real time from various sensing devices of crawling welding robots , and provides multiple data interfaces;

a communication controller, which is connected in communication with the cloud state monitoring device; a physical anti-interference isolation layer, which is arranged between the main controller and the communication controller, and the physical anti-interference isolation layer is used for outer layer isolation; an application layer, It is connected to the main controller in communication, and the application layer includes an application layer intelligent master node and an application layer intelligent backup node that are connected in communication, wherein when the application layer intelligent master node fails, the application layer intelligent master node The node and the application layer intelligent standby node can perform state switching, and both the application layer intelligent master node and the application layer intelligent standby node include a composite intelligent body module with a plurality of intelligent algorithms; and a physical entity storage layer, which is related to all the application layer communication connection, the physical entity storage layer includes a physical layer storage entity master node and a physical layer storage entity backup node that are communicatively connected, and the physical layer storage entity master node is communicatively connected to the application layer intelligent master node, wherein , when the primary node of the physical layer storage entity fails, the primary node of the physical layer storage entity and the backup node of the physical layer storage entity can make the physical entity storage layer work normally through state switching.
The welding polymorphic data agent according to claim 1, wherein the composite agent with multiple intelligent algorithms includes a polymorphic time series data queue, an image feature representation intelligent algorithm, an anomaly detection intelligent algorithm, a time series Check the consistency intelligent algorithm body and the active and standby slice heap processing body.
The welding polymorphic data agent according to claim 1, wherein the physical entity storage layer includes an I/O read and write function and a storage function, and the I/O read and write function requires a read and write speed not lower than The frequency of commands issued by the main controller.
The welding polymorphic data agent according to claim 1, wherein the physical anti-interference isolation layer is made of carbon nanotube fiber material, which is used to absorb electromagnetic radiation of arc light.
The welding polymorphic data agent according to claim 1, wherein the data collected by the main controller includes image data, welding machine data and machine body motion data, and a plurality of the data interfaces include time-series image data The interface, the main push timing data interface, the welding timing data interface and the slider timing data interface are respectively used to transmit the timing image, the main push data, the welding machine data and the slider data.
An intelligent processing method for welding polymorphic data with high reliability and anti-arc interference is characterized in that: the intelligent processing method for welding polymorphic data comprises the following steps:

Build a main controller, a physical anti-interference isolation layer, an application layer, a physical physical storage layer and a communication controller; the main controller collects data in real time from multiple sensing devices of the crawling welding robot;

The master controller transmits the collected data to the composite intelligent body module with multiple intelligent algorithms of the application layer intelligent master node through multiple data interfaces, wherein the multiple data interfaces include a time series image data interface, a main push time series Data interface, welding timing data interface and slider timing data interface, which are used to transmit timing images, main push data, welding machine data and slider data respectively;

When the time series image, main push data, welding machine data and slider data received by the composite agent module, the time series image, main push data, welding machine data and slider data enter the processing queue;

The image feature characterization intelligent algorithm body converts the image data of the weld through the image feature characterization algorithm, outputs the parameters of the unwelded weld, and outputs the welding quality data that has been welded;

The abnormality detection intelligent algorithm body uses the abnormality detection intelligent algorithm to discriminate the abnormality of the transformed data, and discriminates and processes the original data of the welding machine data and the main data, and obtains the normalized morphological data;

The temporal consistency checking algorithm body performs logical checking on the normalized morphological data through a temporal consistency checking algorithm, and obtains time-series single morphological data;

When the state switch is on, the time-series single morphological data is subjected to heap processing to form extractable timeline playback data. The timeline playback data is stacked in the slice stack queue and stored in the physical entity storage layer. ;

The cloud state monitoring device periodically and synchronously obtains the data stored in the physical entity storage layer through the communication controller;

Wherein, when the application layer intelligent master node fails, the application layer intelligent master node and the application layer intelligent standby node perform state switching; and when the physical layer storage entity master node fails, the physical layer storage entity master node and The physical layer storage entity standby node enables the physical entity storage layer to work normally through state switching.
The intelligent processing method for welding polymorphic data according to claim 6, further comprising the following steps: in the process of entering the cloud synchronization, the state switch is changed to an off state, and if the crawling welding robot is in a running state at this time, The time consistency check algorithm transfers the normalized morphological data after logical check to the slice stack backup queue;

After the cloud synchronization is complete, the slice stack backup queue is merged into the slice stack queue, and the status switch is changed to the ON state.
The intelligent processing method for welding polymorphic data according to claim 6, characterized in that: transforming the image data of the welding seam through an image feature representation algorithm comprises the following steps: firstly performing binarization grayscale processing on the RGB image, and then Scanning through multiple neural nuclei, calculating low-dimensional data by convolution, and finally outputting several 1*N-dimensional data through multiple low-dimensional processing, and then intercepting different segments to represent each data, so that the weld image can be divided according to the time dimension. Effective features are extracted and represented as structured multidimensional data.
The intelligent processing method for welding polymorphic data according to claim 6, wherein: abnormal screening and processing of the original data of the welding machine data and the main push data comprises the following steps: making the original data of the welding machine data and the main push data abnormal Filter the time series data, then find out all the problematic time point sets, and remove all the data under the set to obtain normalized morphological data.
The intelligent processing method for welding polymorphic data according to claim 6, wherein the data collected by the main controller includes image data, welding machine data and machine body motion data.