60 results about "Industrial systems" patented technology

The application relates to a fault detection method and device. Multidimensional monitoring data of a target industrial system is acquired, which contains multi-source sensor monitoring data and target monitoring index data at different time points. A training data set is constructed using the multidimensional monitoring data, the multi-source sensor monitoring data is used as a training sample, the corresponding target monitoring index data is used as a training label, a preset model is trained to obtain a fault recognition model. In detection, the multi-source sensor monitoring data to be detected is input into the fault recognition model to obtain target monitoring index prediction data. Whether the data is abnormal is determined by comparing the prediction data and the actual second target monitoring index data, and the fault detection result of the target industrial system is determined, so that more comprehensive and accurate detection of system faults is realized, and the probability of misjudgment and missed judgment is effectively reduced.

The application relates to an industrial process state monitoring method based on robust space-time joint projection, which comprises the following steps: data preprocessing and standardization; data space manifold structure and time dynamic information capturing: calculating the similarity degree between samples according to neighborhood overlapping order similarity, obtaining a data similarity matrix, and thus obtaining the overall space manifold information of process data; subsequently, calculating a data time derivative matrix, extracting slow change characteristics in the data, and obtaining key dynamic information; feature extraction and monitoring model building based on robust space-time joint projection: comprehensively integrating space-time information, performing dimension reduction projection on the data, obtaining key low-dimensional characteristics for retaining the representation of system operation states, constructing monitoring statistics and monitoring thresholds based on the key low-dimensional characteristics, and building an offline process monitoring model; real-time online monitoring of the state of an industrial system.

The disclosure provides a multi-dimensional time series anomaly detection method based on decoupled representation learning. For the multi-dimensional time series collected by multiple sensors in an industrial system, the multi-dimensional time series is input into a multi-dimensional time series anomaly detection model based on decoupled representation learning, and a judgment result for an abnormal device is output. The implementation mode of the multi-dimensional time series anomaly detection model based on decoupled representation learning is that, for input data, first, a heterogeneous hybrid expert network is used for multi-scale feature extraction to adaptively capture global and local patterns; then, a decoupled double-decoder architecture is designed to separate normal representation learning and abnormal discrimination tasks; finally, a special training method is designed to dynamically generate pseudo abnormal samples adapted to the training progress during the training process, and an abnormal sensitivity enhancement strategy based on data disturbance is introduced to gradually introduce a data disturbance mechanism to dynamically enhance abnormal sensitivity. The problem that single-scale modeling cannot comprehensively describe time series features is solved.

The present disclosure relates to ionic copolymers and terpolymers derived from monomers such as 1-alkyl-3-vinylimidazolium halides, 1-vinylimidazole, acrylamide, n-vinylpyrrolidone, and poly(ethylene glycol) methyl ether methacrylate, and their use as corrosion inhibitors in process streams in industrial systems, more specifically in oil refinery streams. The corrosion inhibitors function at concentrations below 100 ppm, temperatures up to 60° C., and in the presence of congenital waters or synthetic brines.

The application belongs to the technical field of industrial system information, and provides an industrial target recognition and accurate positioning method based on an improved Hough algorithm, which comprises the following steps: adjusting parameters of an industrial camera to obtain clear image data of a workpiece, and pre-processing the image data; performing edge detection on the pre-processed image based on a morphological processing algorithm and a Canny edge detection algorithm, obtaining edge information, and judging whether there is edge loss; for the edge loss condition, performing target recognition and positioning based on an improved Hough algorithm or a template matching algorithm, and obtaining the center point coordinates of the target object; the application can more accurately and effectively detect the features of the target boundary, accurately deduce the boundary loss condition, and then realize accurate positioning of the detection target.

This invention relates to the field of industrial big data technology, specifically to an emergency response plan simulation method and system based on digital twins. The invention first acquires the node runtime sequence data, system load time sequence data, and historical emergency response plan simulation data for each node in the industrial system. Then, based on the time sequence mutual information between nodes and between nodes and the system load, node correlation coefficients are obtained, and the importance coefficient of each node is comprehensively evaluated. Furthermore, based on historical emergency response plan simulation data, the accident transmission index of each node is obtained, and then the data synchronization frequency of each node is comprehensively determined and synchronized to the digital twin system for emergency response plan simulation. This invention derives the data synchronization frequency based on node importance, reducing the synchronous transmission of redundant data while meeting the basic requirements of emergency simulation, thus improving the operational efficiency and stability of emergency response plan simulation.

This invention provides a method for safety alignment assessment of large industrial models, belonging to the technical field of large industrial models. This invention collects multi-dimensional parameter time-series data of industrial systems and establishes a physical constraint rule base. It combines Gaussian process regression and Bayesian optimization to search for a dynamic safety boundary point set, establishes a structural causal model, performs do-of-fact calculus and counterfactual reasoning to extract causal inference chains, and inputs the boundary robustness index and causal inference chains into a spiral progressive network structure safety boundary alignment model to output an alignment score. Through temporal continuity analysis, alignment spikes are detected, and a reverse alignment correction process is initiated to adjust the physical constraint weight coefficients. This solves the technical problem of unstable alignment assessment in large industrial models due to the lack of physical mechanism constraints and causal reasoning capabilities during safety boundary identification.

An edge device may include transmitter circuitry and receiver circuitry. The transmitter circuitry may receive process data associated with an industrial system from a control system of the industrial system, and may transmit the process data to receiver circuitry via a first data diode. The receiver circuitry may receive the process data from the transmitter circuitry, transmit an acknowledgement packet to the transmitter circuitry via a second data diode, and transmit the process data to a computing device.

This invention is dedicated to providing a method for automatic planning and optimization of oil product transportation in oil product pipeline networks. Using a color state space model expressed as a linear variable model with parameters and economic predictive control, this method enables real-time management of the sequence of injection of packages. The proposed structure defines an economic objective function, taking into account pumping costs, product interference, and tracking product delivery targets in specific time intervals, which is iteratively optimized over a sliding forecast horizon. The proposed model, using online data, is capable of identifying potential disturbances such as equipment failure or changes in demand, and ensures stable system performance by quickly revising the schedule. The proposed method also avoids the computational complexity of conventional methods and enables real-time implementation with optimization algorithms such as branch and bound. This invention has applications in industrial systems of petroleum product transmission lines and reduces costs, increases productivity, and improves operational flexibility.

The disclosure of this method is intended for the predictive maintenance market, presenting an innovative method for detecting faults in hydraulic couplings, crucial components in power transmission systems across various industrial sectors. Slippage in hydraulic couplings, which is a loss of efficiency in torque transmission, can indicate wear, insufficient / excessive lubricant, or other problems, resulting in unplanned downtime and maintenance costs. The method uses metrics extracted from vibration signals to identify slippage, such as SFI (Slipping Frequency Indicator) and SNR (Signal-to-Noise Ratio). The combination of these metrics and other signal processing allows for accurate and reliable slippage detection, preventing catastrophic failures in industrial systems.

This application relates to the field of seawater electrolysis technology, and more particularly to a chlorine-resistant MOF anode material for seawater electrolysis and its preparation method. The chlorine-resistant MOF anode material comprises a porous conductive substrate and a metal-organic framework (MOF) catalyst layer grown in situ on the surface of the porous conductive substrate. The MOF catalyst layer includes a transition metal center and a ternary ligand system coordinated to the transition metal center. The ternary ligand system includes 2,5-thiophene dicarboxylic acid as a bridging ligand, and ferrocene carboxylic acid derivatives and pyridine carboxylic acid derivatives as non-bridging ligands. Through the synergistic co-assembly of the ternary ligands, a dense three-dimensional physical protective barrier is constructed on the surface of the catalyst material, enabling the catalyst to exhibit excellent stability in natural seawater media without any desalination or purification pretreatment. This reduces the stringent requirements on the quality of the reaction feed water and eliminates the need for complex seawater desalination pretreatment processes in industrial systems.

This invention discloses a linear scaling quantum chemistry calculation method, its applications, and related products based on pre-constrained energy. Belonging to the field of quantum chemistry calculation technology, it solves the core technical pain points of existing technologies, such as the irreconcilable trade-off between computational complexity and accuracy, lack of underlying physical consistency guarantees, and poor adaptability to complex systems. This invention uses the inherent kinetic-potential coupling relationship derived from the generalized virial theorem as a pre-priority hard constraint. Through a core process involving pre-determining inherent constraint parameters, pre-locking physical orbits, effective particle pair screening calculations, and direct calculation of total energy, it completely abandons self-consistent field iteration and Hamiltonian matrix diagonalization operations, achieving a fundamentally rigorous O(N) linear scaling. The calculation results of this invention naturally conform to the basic rules of quantum mechanics, have no approximate truncation error, and are universally applicable to all systems and quantum states. It can perform high-throughput quantum chemistry calculations for large-scale industrial systems on ordinary consumer-grade hardware, and can be widely applied in fields such as drug development, new material design, semiconductor simulation, and superconducting material screening.

The application relates to the technical field of industrial system protection, and discloses an industrial control system safety isolation protection device and method, which comprises an outer cabinet, the inner wall of the outer cabinet is rotationally connected with an inner cabinet driven by a rotation motor, an opening is arranged on the inner cabinet, the upper and lower ends of the inner cabinet are fixedly connected with rotating guide cylinders, the back surface of the outer cabinet is respectively provided with a direct-current ventilation component and a negative pressure isolation component communicated with the rotating guide cylinders, a mounting frame is arranged on the inner cabinet, an industrial computer is arranged on the mounting frame, and a single-computer detection and isolation component matched with the industrial computer is arranged in the inner cabinet. When the industrial control system in the industrial computer generates abnormal signal feedback, the isolation protection device can realize the whole-machine isolation of the device, and can also realize the single-computer isolation of the industrial computer when the single industrial computer generates abnormal signal feedback; and the device can realize power-off isolation when isolating the industrial control system.

A method for testing code coverage of a software program executed by a machine in an industrial system, comprising: obtaining a control flow model of a first version of the software program as a first control flow model; obtaining a control flow model of a second version of the software program as a second control flow model, wherein the second version is a modified version of the first version; comparing the first control flow model with the second control flow model, to identify one or more code changes of the second version compared to the first version; preparing a set of codes to be tested based on the identified one or more code changes; preparing test data for testing the coverage of the set of codes to be tested; compiling the second version into an assembly code or a binary machine code to be executed by a runtime environment of the machine; adding a check point into the assembly code or the binary machine code at a position corresponding to each code in the set of codes to be tested, wherein the check point is an instruction added into the assembly code or the binary machine code that enables the runtime environment to indicate, when the instruction of the check point is executed, that the code in the set of codes to be tested corresponding to the check point is executed; starting the execution of the assembly code or the binary machine code in the runtime environment using the test data; and determining whether each code in the set of codes to be tested is covered according to the indication from the runtime environment.

This invention discloses a fully integrated large-scale model-driven industrial intelligent agent interaction system and its implementation method, relating to the field of industrial internet technology. It includes: a fully integrated large-scale model training and inference module for modeling, training, lightweight output, and low-latency inference; a super memory storage module for storing industrial scenario data; an intelligent retrieval engine module for outputting optimized adjustment schemes; four core functional pillar modules: a carbon energy intelligent control optimization submodule, a holographic digital twin collaboration submodule, a hyperdimensional knowledge insight and decision-making submodule, and a process AI autonomous evolution submodule; a multimodal interaction portal module supporting multimodal interaction; and a data acquisition and execution control module for acquiring data, issuing commands, and providing feedback. This invention provides a fully integrated large-scale model-driven industrial intelligent agent interaction system and its implementation method, solving the problems of shortcomings in traditional large-scale models, isolated modules in industrial systems, biases in digital twins, and the lack of autonomous system evolution.

The application relates to the technical field of digital twin optimization, and discloses a dynamic compensation method and system for digital twin optimization. The method comprises the following steps: acquiring historical full-amount data of a digital twin body, and screening abnormal entity object data; constructing a compensation control strategy and deducing first compensation target data; calculating a compensation target difference value of adjacent stages, and calculating a main compensator compensation parameter in combination with the characteristics of the abnormal entity object data when the compensation target difference value reaches a preset threshold; collecting state residual data of a sub-compensator, generating a compensation distribution instruction, and enabling the sub-compensator to perform basic compensation adjustment; supplementing the latest operation data to acquire second compensation target data, comparing the generated result, and correcting and adjusting the operation. The system comprises an acquisition unit, a deduction unit, a measurement unit, a collection unit, a distribution unit, an updating and judging module, and the like. The application enhances the response capability of the system to dynamic changes, ensures high matching between a digital twin model and a physical entity, and improves the reliability and efficiency of industrial system operation.

This invention belongs to the field of information processing and discloses a semantic alignment method for industrial multimodal data based on vector space and topological constraints. It aims to solve the problem of semantic fragmentation and difficulty in unifying and associating multimodal data in industrial scenarios. By extracting features and performing structured parsing on each modality of data, and mapping them to a unified semantic vector space through a projection layer, the method introduces topological constraints derived from process drawings, etc., to verify neighbor relationships of candidate entities based on vector similarity matching. Furthermore, it combines a large model for contextual logic verification, thereby significantly improving the accuracy of cross-source entity alignment. An efficient vector database index is established to support hybrid retrieval, and a large model is used to assist in reasoning and rule base verification to achieve incremental updates of the knowledge graph. This invention effectively integrates vector semantics with the structural dependencies unique to industrial systems, achieving high-precision, evolvable cross-modal semantic alignment and intelligent association analysis.

The utility model discloses an anti -interference communication system and industrial system, include: control chip, 485 conversion chip is provided with first A line port and first B line port, and 485 communication chip is connected with control chip electricity, first communication connection module, including first resistance, first switch, connector, first transient voltage suppression tube, second transient voltage suppression tube, second resistance and first electric capacity, and the connector is provided with second A line port, second B line port and upper position port, and first A line port and first resistance are connected with first switch respectively, and first resistance is connected with first B line port, and one end of second resistance is grounded, and the other end of second resistance and second A line port are connected with both ends of first transient suppression tube respectively, and the other end of second resistance and second B line port are connected with both ends of second transient suppression tube respectively, and first electric capacity is connected in parallel with second resistance, the utility model provides an anti -interference communication system can promote the quality of communication.

This invention relates to the field of industrial system condition monitoring and intelligent early warning technology, specifically disclosing a risk early warning method and system for the cooling circuit of a liquid-cooled charging cable. The method involves collecting and preprocessing multi-dimensional time-series data composed of liquid circuit, electrical, and environmental parameters. Based on a combination of K-means clustering and rule-based judgment, five operating conditions are identified: standby, low power, high-power fast charging, peak overcharging, and derating operation. A Kalman filter-ARX model or a TCN-Transformer fusion model is then applied according to the operating condition for time-series prediction. Based on the predicted residual sequence, four trend features are extracted: cumulative residual value, growth rate, multivariate consistency, and confidence interval deviation. The final risk score is obtained by dynamically weighting the data according to the operating condition and combining it with the confidence coefficient of the abnormal duration. Finally, early warning levels are classified, and graded charging power linkage control commands are output.

The application relates to the technical field of fault diagnosis, in particular to a distributed industrial fault diagnosis system and method, which comprises edge terminals and edge servers arranged in various industrial components. The edge terminal is provided with a rapid diagnosis module, a high-level diagnosis module and a dual-mode trigger communication module. The dual-mode trigger communication module independently and in parallel controls uploading of deep feature data according to event triggering and periodic triggering conditions. The edge server is provided with a synchronous sampling module, a feature fusion module and a global diagnosis module, which are used for aligning and fusing multi-source heterogeneous data on a unified time axis, and performing system-level fault diagnosis. The application guarantees real-time response to sudden faults and continuous monitoring of system states through dual-mode triggering, realizes efficient resource utilization and accurate identification of cross-component implicit faults through a hierarchical collaborative architecture, and significantly improves the comprehensive performance of fault diagnosis of complex industrial systems.

A system for condition monitoring and predictive maintenance of in-motion components within an industrial system is disclosed. A centralized controller receives image data from vision sensors and operational data from telemetry sensors. An indexing module detects each component at a trigger location, assigns a sequential index during a full system revolution, and associates acquired data with corresponding subcomponents. A measurement module analyzes images to determine characteristics such as wear, deformation, or misalignment, while a predictive model evaluates the measurement data and historical maintenance information to estimate future wear and replacement intervals. An alarm manager compares the measurements to threshold values and generates multi-level condition alarms. The system produces a consolidated report identifying component-specific wear conditions, predicted maintenance timing, and recommended actions. This architecture enables proactive maintenance, reduces downtime, and improves operational reliability in large-scale automated systems by providing continuous or scheduled monitoring and automated assessment of subcomponent health.

The application discloses a kind of based on knowledge guide's quick reinforcement learning PID parameter self-tuning method and system, it is related to automation control technical field, it solves the problems of low training efficiency, poor initial strategy reliability, insufficient adaptability to industrial system time lag of existing reinforcement learning PID self-tuning scheme.It is based on TD3 algorithm to construct PID closed-loop control framework, decouples Actor network into sub-networks;PID parameter setting prior knowledge is concretized as correlation function, and a supervised data set is generated to pretrain sub-network to embed prior knowledge;Introduce action-state alignment mechanism to compensate system time lag, complete network joint training optimization based on designed reward function, and finally output optimal PID parameters from trained Actor network.The application greatly improves training efficiency and convergence reliability, adapts to industrial time lag system, realizes PID parameter adaptive optimization control.

This invention relates to the field of intelligent control technology for industrial coating testing, specifically an intelligent analysis system for coating consistency measurement in industrial control systems. The system includes modules for signal acquisition, signal conversion and transmission, intelligent analysis and calculation, and decision output. Through embedded rheological sensors in pipelines and mixing tanks, it continuously collects multiaxial stress and strain rate time-series data streams under coating shear action. After analog-to-digital conversion, the data is uploaded in real-time to a workshop intelligent analysis server via an industrial communication network. An improved particle swarm optimization algorithm is used to initialize the weights of the consistency analysis neural network, and accurate consistency quantification values ​​are calculated based on the model. The quantified values ​​are compared with the acceptable consistency range in the process, automatically generating instructions for adjusting the batching valve and stirring speed, or abnormal warning signals. This system enables continuous online consistency detection, improves calculation accuracy and data stability, and achieves real-time closed-loop control in industrial systems.

This invention discloses an integrated automated processing method and system for sales settlement across all scenarios, featuring AI-based pre-parameter verification, belonging to the field of financial settlement technology for industrial ERP / MES systems. Based on a unified stored procedure architecture, this invention incorporates an AI-based pre-parameter verification module, supporting settlement of spot and futures contracts, as well as real-time price locking and post-pricing modes. It achieves batch parameter transmission through table-valued parameters, combined with automatic settlement number generation, transaction-level atomicity guarantees, multi-table automatic updates, financial auditing and access control, automatic generation and printing of settlement documents, and full-link operation tracking, realizing automated and standardized management of the entire sales settlement process. This invention solves the problems of traditional settlement systems, such as limited scenario adaptability, fragmented operations, low efficiency, data error susceptibility, lack of traceability, and inability to integrate with AI. It adopts standard SQL syntax to adapt to multiple database platforms such as SQL Server and GaussDB, possessing cross-database compatibility and independent controllability. This invention has been fully implemented in actual industrial MES systems and can operate stably in real production environments for a long time, demonstrating mature engineering value and industrial-scale promotion capabilities.

An industrial extract, transform, and load (ETL) system extracts and transfers data from proprietary industrial systems and devices to cloud-level systems or other higher level applications. The industrial ETL system uses application connectors that are designed to interface with various types commonly used or proprietary industrial systems and devices—including but not limited to industrial controllers, open platform communications (OPC) servers, databases, MQ telemetry transport (MQTT) brokers, motor drives, telemetry devices, etc.—and to extract data from those systems in a manner that reduces the impact on those systems' core functionalities relative to conventional ETL approaches. The system's application connectors use the same technology stack to communicate with multiple different devices and systems that are commonly found in industrial software architectures.

The present disclosure provides an industrial control device that performs authentication based on a dynamic authentication code and a method using the same. The industrial control device according to the present disclosure includes a communication module that communicates with a user terminal and a central server, and a CPU (Central Processing Unit) that transmits a dynamic authentication code generated by the user terminal to the central server via the communication module to request authentication of the dynamic authentication code and changes an operation mode based on a result of the authentication.

The application discloses an industrial system simulation deduction method and device, electronic equipment and medium. The method comprises the following steps: obtaining simulation deduction scene information of an industrial system; determining an industrial simulation deduction template matched with the simulation deduction scene information; performing simulation parameter configuration on the industrial simulation deduction template to obtain a simulation model; generating dynamic strategy information for driving the simulation model according to the simulation deduction scene information; performing iterative simulation deduction on the simulation model according to the dynamic strategy information to obtain a simulation deduction result; in response to the simulation deduction result meeting a preset condition, saving and publishing the industrial simulation deduction template; and in response to the simulation deduction result not meeting the preset condition, adjusting a digital twin node and a topological layout in the industrial simulation deduction template until the simulation deduction result of the adjusted industrial simulation deduction template meets the preset condition. Thus, the reusability and adaptability of the simulation deduction template are improved, the problem solving efficiency of the industrial system is improved, and the loss of the industrial equipment is reduced.