Abstract: The present disclosure describes multi-parameter dynamic sampling methods and systems. An example method includes: configuring two sampling rates for each parameter in a set of sampling parameters; selecting one of the sampling rates for each parameters to sample it; calculating a load for each parameter at the selected sampling rate, sorting the parameters according to the loads, and determining high-loaded parameters according to a sorting result; and determining whether each parameter has data loss, and if at least one of the sampling parameters has data loss, performing down-sampling on the high-loaded sampling parameters within a range of the configured at least two sampling rates.

Abstract: A multi-type industrial robot control system may include: an automation controller; and a programmable logic controller (PLC)-robot bridge. The controller stores a general-purpose robot control function block generated using a unified design standard, calls a corresponding robot control function block for a robot and using robot state data and puts out corresponding first command data to the PLC-robot bridge. The PLC-robot bridge virtualizes robot interfaces of corresponding offline programming functions of different types of robot as a unified virtual interface, calls a corresponding offline programming function via the unified virtual interface according to the first command data, and generates second command data for output to a corresponding robot controller. The corresponding robot controller controls a corresponding robot. At the same time, robot state data from a corresponding type of robot is received via the unified virtual interface and the robot state data is fed back to the automation controller.

Abstract: Examples of the present disclosure include methods and/or systems for fault diagnosis and solution recommendation. A method may include: obtaining original data including fault problem of a target device; analyzing the original data including fault problem to obtain problem description information; analyzing the problem description information to obtain a diagnosis report; and, according to the diagnosis report, obtaining a video and/or document solution for the fault based on a cloud knowledge map, and recommending the solution to a user. The knowledge map comprises: nodes representing the fault, video solution and/or document solution, and multiple edges representing the relationship between nodes.

Abstract: Examples of the present disclosure provide a parameter optimization method, device and computer readable storage medium. The method includes: establishing a one-to-one functional relationship between each parameter and each performance index; determining each current correlation coefficient between the parameter and each performance index based on the one-to-one function relationships; obtaining a current weight of each performance index; according to current weights and current correlation coefficients, obtaining a current influence coefficient of each parameter on a comprehensive performance of the performance indexes; and determining important optimization parameters according to the current influence coefficient; for each two parameters, calculating a current correlation coefficient of the two parameters, and determining an adjustment parameter; and performing parameter optimization based on the important optimization parameters and the adjustment parameters.

Abstract: Various embodiments include methods for intelligently providing recommendation information. For example, the method may include: determining user attribute parameters corresponding to a user identifier; determining a score value corresponding to the user identifier by inputting the user attribute parameters into a scoring model; determining recommendation information corresponding to the user identifier based on the score value and a knowledge graph related to the user; and providing the recommended information.

Abstract: The present disclosure provides a method for remote assistance and device. 1. A method for remote assistance, the method comprising: determining a state of a machine deployed at a working site; adjusting a digital twin of the machine to be in the same state as the machine deployed at the working site; rendering the digital twin at a remote site using a remote rendering device to enable a remote person at the remote site to perform an operation on the digital twin; and mapping an effect of the operation rendered as visual assistance information onto the machine at the working site using a local rendering device deployed at the working site.

Abstract: The present disclosure describes multi-parameter dynamic sampling methods and systems. An example method includes: configuring two sampling rates for each parameter in a set of sampling parameters; selecting one of the sampling rates for each parameters to sample it; calculating a load for each parameter at the selected sampling rate, sorting the parameters according to the loads, and determining high-loaded parameters according to a sorting result; and determining whether each parameter has data loss, and if at least one of the sampling parameters has data loss, performing down-sampling on the high-loaded sampling parameters within a range of the configured at least two sampling rates.

Abstract: Various embodiments of the teachings herein include a method for controlling a plurality of execution mechanisms. The method may include: determining a dependency relationship of synchronous motions among the plurality of execution mechanisms, wherein the dependency relationship represents motions of a second group of execution mechanisms in the plurality of execution mechanisms depending on motions of a first group of execution mechanisms in the plurality of execution mechanisms; determining an execution order of the first group of execution mechanisms and the second group of execution mechanisms according to the dependency relationship; determining rotation angles of joints coupled to corresponding execution mechanisms; and sequentially controlling the joints to respectively rotate by the determined rotation angles according to the determined execution order.

Abstract: Provided are a data acquisition system and method. The system includes: data acquisition units, to acquire a plurality of pieces of data related to a target object within a data acquisition period; and a controller, communicatively connected to the data acquisition units, to set, according to an ith data acquisition period, a sampling interval time of the ith piece of data, and to set a polling interval time according to a minimum data acquisition period of the data acquisition units. Upon the controller starting to perform polling on the data acquisition units through n_1 polling interval times until a condition is satisfied for the first time, the controller performs first polling, for the ith piece of data, on a data acquisition unit of the data acquisition units for acquiring the ith piece of data.

Abstract: Various embodiments include a fault diagnosis method for a rotating motor. The method may include: obtaining a time-domain acceleration signal of the rotating motor along a vibration direction and a rotation period of the rotating motor; converting the time-domain acceleration signal into a time-domain velocity signal, cutting off a plurality of velocity signal segments along the time-domain velocity signal by taking the rotation period as a step size, and arranging the plurality of velocity signal segments in sequence to obtain a velocity signal matrix; converting the velocity signal matrix into an image; and inputting the image into a trained neural network model to obtain a fault diagnosis result.

Abstract: The present disclosure provides a method and an apparatus for adjusting a process control prediction model, and a process controller. In an embodiment, the method includes: determining, based on controlled variable data in process control data obtained through real-time monitoring, whether a prediction performance of the process control prediction model is lower than a reference performance; and when the prediction performance is determined to be lower than the reference performance, using manipulated variable data in the process control data monitored to adjust the process control prediction model. By way of the method, a re-test does not need to be executed to re-identify a model so as to eliminate a mismatch of the process control prediction model, thereby eliminating an influence of fluctuation introduced by addition of an excitation signal during the re-testing.

Abstract: A method, a component, and an electronic device relating to the field of industrial automation technology, particularly relating to the creation of a human machine interface, and are used for automatically creating an HMI of a system. The method for creating an HMI comprises: a first component of a system receives, via an HMI, a first command for creating an HMI for the system; the first component obtains, from each searched and found second component of the system an HMI resource of each of the second components; and the first component creates, on the basis of an HMI resource of the first component and the obtained HMI resource from each of the second components, the HMI for the system. One component of the system collects the HMI resource of another component of the system and creates the HMI for the whole system, providing a method for automatically creating the HMI for the system.

Abstract: In the technical field of industrial automation, a fault diagnosis method and apparatus for a numerical control machine tool are disclosed which can improve the efficiency of diagnosing faults of numerical control machine tools by utilizing feedback information provided by users. In a fault diagnosis method of an embodiment, the fault diagnosis apparatus receives a fault symptom to be diagnosed from a user terminal, diagnoses the fault for the fault symptom to be diagnosed, returns a fault diagnosis result to the user terminal, receives feedback on the fault diagnosis result from the user terminal, and adjusts the diagnosis policy for the fault symptom to be diagnosed according to the fault diagnosis result if the feedback of the user on the fault diagnosis result indicates that the fault has been cleared.

Abstract: A programming method is for a numerical control machine tool system including a mobile terminal, a controller, a robot, and a numerical control machine tool. The mobile terminal is wirelessly connected to the controller configured to control the robot and the numerical control machine tool, and the robot and the numerical control machine tool being configured to work cooperatively to process a workpiece. The method includes: loading, at the mobile terminal, a preset motion model of the robot and the numerical control machine tool, the preset motion model being a plurality of graphical functional modules and a connection between them; receiving a graphical programming instruction for a user to configure the preset motion model using the mobile terminal; and converting the graphical programming instruction into G-code, where the G-code is used by the controller to control the robot and the numerical control machine tool to process the workpiece.

Abstract: The present disclosure relates to a method, device, and system for configuring parameters, a computer device, a medium, and a product. A configuration device for configuring parameter sampling with respect to an edge device includes: one information acquiring unit, configured to acquire information related to the purpose and use environment of the edge device; one transmitting unit, configured to transmit the information to a cloud platform; and one configuration information determining unit, configured to receive configuration information for parameter sampling with respect to the edge device from the cloud platform, where the configuration information is configuration information determined as matching the information by the cloud platform utilizing a configuration model stored thereby.

Abstract: A data processing system and method are provided. The data processing system includes: a data acquisition unit, configured to acquire a plurality pieces of data related to a target object; and a data processing unit, configured to receive the plurality pieces of data and set a plurality of adjacent regions in a two-dimensional spatial representation of the plurality pieces of data according to a tolerable compression error. The plurality of regions include an adjacent first region and second region, respectively covering a plurality pieces of data. The data processing unit is configured to forwardly expand the second region to obtain the expanded second region overlapping the first region, calculate a compression error of data covered by the expanded second region, reset the first region and compress the data covered by the reset first region. The data processing system can reduce or minimize the data compression error.

Abstract: A data processing system and method are provided. The data processing system includes: a data acquisition unit, configured to acquire a plurality pieces of data related to a target object; and a data processing unit, configured to receive the plurality pieces of data and set a plurality of adjacent regions in a two-dimensional spatial representation of the plurality pieces of data according to a tolerable compression error. The plurality of regions include an adjacent first region and second region, respectively covering a plurality pieces of data. The data processing unit is configured to forwardly expand the second region to obtain the expanded second region overlapping the first region, calculate a compression error of data covered by the expanded second region, reset the first region and compress the data covered by the reset first region. The data processing system can reduce or minimize the data compression error.

Abstract: Provided are a data acquisition system and method. The system includes: data acquisition units, to acquire a plurality of pieces of data related to a target object within a data acquisition period; and a controller, communicatively connected to the data acquisition units, to set, according to an ith data acquisition period, a sampling interval time of the ith piece of data, and to set a polling interval time according to a minimum data acquisition period of the data acquisition units. Upon the controller starting to perform polling on the data acquisition units through n_1 polling interval times until a condition is satisfied for the first time, the controller performs first polling, for the ith piece of data, on a data acquisition unit of the data acquisition units for acquiring the ith piece of data.

Abstract: An interconnection device, a communication method, and a system including a robot are disclosed. In an embodiment, the interconnection device includes a first OPC UA interface, configured to establish connection between the interconnection device and an OPC UA device; and an ROS interface, in communication with the first OPC UA interface. The ROS interface includes: at least one ROS node module, configured to perform communication between the OPC UA device and an ROS device; an ROS client library module, configured to provide a function library to be called when the ROS node module performs the communication; and an ROS core module, configured to manage the ROS node module in the ROS interface unit and a node module in the ROS device. Communication between the OPC UA device and the ROS device is achieved via the interconnection device and the communication method.

Abstract: Disclosed are an information providing method and system. In an embodiment, the method includes: acquiring product data and/or historical operation data; determining at least one feature description tag of an industrial product based upon the product data, and taking the at least one feature description tag of the industrial product as a feature of the industrial product; and/or determining at least one feature description tag of a user based upon the historical operation data, and taking the at least one feature description tag of the user as a feature of the user. The method further includes sending the feature of the industrial product and/or the feature of the user to a human-machine interactive device for display on a human-machine interactive interface. An embodiment further provides a reference suggestion for operative control of the industrial product by the user.