266 results about "Industrial Facility" patented technology

The invention relates to a pipe network station inspection task execution method and system based on multi-modal fusion, and belongs to the technical field of industrial facility detection. According to the method, multiple types of sensors are carried through an unmanned aerial vehicle and a ground robot, illumination, temperature and humidity, wind speed and rain and fog data are collected in real time, and an optimal sensor combination is dynamically activated; a feature level fusion strategy is adopted, the weight of each modal is adjusted in combination with environmental parameters, and the defect detection accuracy is improved; the system performs digital twinborn simulation verification on an abnormal result, so that the false alarm rate is reduced; an inspection path is adaptively adjusted according to a detection result, and a high-risk area is emphatically scanned; the edge computing nodes realize real-time data processing, and upload key information after compression; the maintainer rechecks the result through the AR glasses and marks a misinformation case; according to the method, the problems of poor environmental adaptability and insufficient utilization of multi-modal data of traditional inspection are solved, and the detection efficiency and reliability are improved.

Systems and methods for recovering emissions from industrial facilities are disclosed herein. The systems can include an emissions recovery system for use in an industrial facility comprising ducting, a first vent, and a second vent at an opening. The ducting can have a first end region fluidically coupled to a baghouse, and a second end region, opposite the first. The ducting can be configured to operate under a vacuum. The first vent and the second vent can each be fluidically coupled to the second end region of the ducting. The first vent can be positionable at a first distance from the opening, and the second vent can also be positionable at a second distance from the opening. Each of the first and the second vents can be configured to collect emissions particles released from at least the opening.

Example techniques to control operations in an industrial facility is described. In an operation, operating parameters of an equipment from amongst a plurality of equipments installed in the industrial facility are monitored. A range of values is predefined for each of the operating parameters of the equipment. An operating parameter of the equipment that deviates from the corresponding predefined range of values is identified. A dataset is queried to identify past instances of deviation in the operating parameter that are within a specified range of deviation to the deviation in the operating parameter of the equipment. A corrective action is selected from amongst at least one corrective action in the dataset. The corrective action is implemented to correct the deviation in the operating parameter of the equipment.

The invention relates to the technical field of computer vision, in particular to an industrial facility autonomous inspection and intelligent diagnosis method based on multi-modal vision fusion, which comprises the following steps of: acquiring a multi-frame seam image to extract a texture dot matrix, analyzing displacement frequency to evaluate stability, calculating angle difference to identify a deformation structure surface, and performing multi-modal vision fusion. And detecting image and point cloud overlapping, screening abnormal blocks to generate a fusion set, identifying a spectrum hopping mapping image, positioning a boundary region, extracting a frequency analysis path repetition rate, identifying an abnormal focusing position, and generating a diagnosis list. According to the invention, through multi-frame image texture dot matrix displacement tracking, the dynamic abnormal region identification precision is improved, micro deformation is captured through three-dimensional point cloud angle difference, the structural anomaly detection is enhanced, the multi-modal anomaly judgment accuracy is improved, the anomaly characteristics, the inspection path frequency and anomaly aggregation analysis are refined, the high-frequency abnormal region is positioned, and the inspection resource configuration is optimized; risk prevention and control are enhanced, and limitation of equipment surface sensing and abnormal positioning is broken through.

The disclosure relates to an emissions detector for monitoring methane emissions at one or more industrial facilities. The emissions detector includes: a pole; an enclosure mounted on the pole, wherein the enclosure houses at least one sensor, wherein the at least one sensor includes a gas sensor configured to measure concentration of methane in atmospheric gas that flows into the enclosure; and means for removably securing the pole to ground without the use of concrete.

The invention relates to the technical field of automatic response, in particular to an industrial fireproof wind-resistant door automatic response system, which comprises an environment monitoring module, a door control analysis module, a door control adjustment module and an abnormity monitoring module, and is characterized in that the environment monitoring module performs data aggregation based on temperature, smoke concentration and wind speed data received in real time; and calculating an average value and a standard deviation of the data, analyzing an environment change prediction trend in a short period, and generating environment baseline data. According to the method, trend prediction and periodic analysis are performed on the environmental data by applying the ARIMA model, so that the closing speed and force of the fireproof and wind-resistant door can be adjusted according to the prediction result before a fire disaster or strong wind occurs, and the response time and efficiency of the door leaf are optimized; the isolation forest algorithm enables the system to effectively identify and analyze the abnormal mode in the sensor data flow, improves the diagnosis accuracy of the equipment fault, improves the reliability, reduces the dependence of the system on manual intervention, and effectively protects the safety and stability of industrial facilities.

An anthropomorphic AI control system including a plurality of sensors configured to collect industrial input data. The control system also includes an artificial intelligence-enabled edge-deployed computing device configured to analyze and fuse multimodal input data and generate an output through anthropomorphic computing. The computing device includes a cognitive module performing real-time decision-making at the sensor edge and a controller to manage industrial process actuators across operational domains. In management of industrial fluid flow, the control system may include AI-enabled fluid characterization modules to calculate the Reynolds number and incorporate compliance with AGA3 and AGA8 standards.

Implementations set forth herein relate to triaging of robots at an industrial facility using generated snapshots that can be based on an operating status of various features of each particular robot. The snapshots can be generated from data generated by each robot and / or data observed for a particular robot, such as images captured of a particular robot. Each snapshot can be utilized to estimate a likelihood or probability that each robot can complete the task without first visiting a service station. When a probability for a particular task is satisfied, the robot predicted to complete the task can be assigned to the particular task. Alternatively, or additionally, when certain estimated probabilities do not satisfy a threshold for completing the task, each robot associated with such an estimated probability can be directed to a service station of the industrial facility.

A cultivation method for Morchella on patterned layer frames is provided. The method includes: (1) preparing and laying a culture substrate, and sowing; (2) supplementing an exogenous nutrient material; (3) mycelium culture; (4) primordium induction; (5) primordium differentiation; (6) management of a young mushroom period; (7) maturity management; and (8) erchao mushroom management. The method adopts a low temperature of (5-9)° C. to promote a transformation of an exogenous nutrition and adopts a low temperature of (2-4)° C. to induce a differentiation of primordium and other measures, to address a bottleneck of industrial development that cannot continuously supply fresh Morchella to the market, which is caused by some problems in the cultivation of Morchella, such as an unstable yield and seasonal limitation in the existing cultivation of Morchella. The method can carry out industrial facility cultivation for Morchella, and can obtain Morchella with stable yield and good quality.

The invention relates to the technical field of intelligent robot inspection, and discloses a digital twinning-based intelligent AI inspection method, which comprises the following steps of: analyzing a multispectral image acquired by a sensor carried by a robot by utilizing a dynamic attention multilayer feature extraction network; generating an industrial facility abnormal coverage degree real-time distribution map; analyzing historical abnormal coverage data by using a space-time sequence contrast learning model, and generating abnormal coverage trend prediction; analyzing an abnormal coverage evolution process by using a physical constraint neural differential equation model, and generating an accurate abnormal evolution prediction result; generating an optimal inspection path by using a multi-objective optimization algorithm; dynamically updating the digital twin system, and generating an industrial facility maintenance optimization suggestion; according to the invention, through the dynamic attention multilayer feature extraction network and the illumination condition adaptive enhancement algorithm, the detection problem in the strong light and high reflection environment is effectively solved.

The invention specifically relates to a facility intelligent operation and maintenance decision-making method based on big data and artificial intelligence, and relates to the technical field of industrial facility operation and maintenance and intelligent decision-making, and the method comprises the steps: simulating the multi-dimensional operation state of a corresponding physical facility in a future preset time period after each candidate decision is executed; according to the method, the dynamic optimization of the operation and maintenance decision is realized by relying on the multi-scheme deduction capability of the digital twin and combining the non-dominated sorting genetic algorithm II and the dynamic weight evaluation system; the maintenance cost, the fault risk and the production efficiency are balanced by generating five types of candidate schemes, simulating the fault probability, the cost and the production efficiency within seven days and dynamically adjusting the weight based on the equipment health index, the production load and the like; a closed-loop feedback mechanism corrects model parameters through actual data, incremental learning and reinforcement learning continuously optimize decision experience, fault shutdown loss is reduced, operation and maintenance requirements in different scenes are met, and practicability and adaptability of the method are enhanced.

The invention relates to the technical field of remote monitoring, in particular to a remote camera and robot linkage patrol system and patrol method. The patrol system comprises a remote camera monitoring module which remotely monitors the patrol robot and the industrial facility through a remote camera; the robot inspection module inspects industrial facilities through an inspection robot; the cooperative control module is used for processing and analyzing data acquired by the remote camera and the inspection robot, and controlling the remote camera monitoring module and the robot inspection module based on an analysis result; the security protection module is used for encrypting and decrypting data transmitted in each module; when the inspection system is detected to have a fault, the safety protection module triggers a corresponding safety protection strategy based on a fault type; and the data analysis and optimization module is used for optimizing the parameters of the patrol system based on the data stored in the database module. According to the invention, the inspection efficiency is improved, the human input is reduced, and the inspection quality and safety are guaranteed.

This disclosure relates to the monitoring and detection of corrosion and / or erosion of pipes, vessels, and other components in an industrial facility. The monitoring system may comprise of an arrangement of guided wave (GW) transducers and a longitudinal wave (LW) transducer affixed to the piping component to collectively measure for localized corrosion of the piping component without necessarily requiring a thickness map. The monitoring system may use an intelligent amplified multiplexer / switch to control the operation of the transducers that may be controlled and operated to generate waves in the kilohertz range and megahertz range with the same hardware.

The disclosure relates to a system for monitoring methane emissions at industrial facilities. The system includes a network of methane emission detectors at different locations within at least one industrial facility; a gateway device operably coupled to the network of methane emission detectors; and a cloud computing environment operably coupled to the gateway device; wherein the network of methane emission detectors is configured to perform time-series measurements at different locations within the at least one industrial facility and wirelessly communicate time-series sensor data representing such measurements to the gateway device; wherein the gateway device is configured to process the time-series sensor data to derive time-series operational data and communicate the time-series operational data to the cloud computing environment; and wherein the cloud computing environment is configured to receive and process the time-series operational data to detect and characterize methane emission at the at least one industrial facility.

The present invention discloses a preparation method of a ZIF-8-based photothermal superhydrophobic anti-corrosion and anti-icing coating, comprising the following steps: S1. Preparation of ZIF-8@PDA particles: Synthesize ZIF-8@PDA particles modified by polydopamine in one step in water; S2. Preparation of the ZIF-8-based photothermal superhydrophobic anti-corrosion and anti-icing coating: Compound and superhydrophobically modify ZIF-8@PDA and carbon materials in a certain proportion, add an adhesive, spray it on the surface of a substrate, and obtain the ZIF-8-based photothermal superhydrophobic anti-corrosion and anti-icing coating after curing. The ZIF-8-based photothermal superhydrophobic anti-corrosion and anti-icing coating material prepared by the present invention exhibits excellent superhydrophobicity, mechanical stability and corrosion resistance. At the same time, the ZIF-8-based photothermal superhydrophobic anti-corrosion coating exhibits excellent passive delayed icing and active photothermal de-icing capabilities on the surface of aluminum alloy. It provides a brand-new strategy for winter de-icing of industrial facilities and equipment.

A system, device, and method for managing connections in an industrial installation are described. The system includes one or more field devices, one or more automation devices, and a self-configurable device. The self-configurable device is adapted to dynamically configure, based on type of the one or more field devices and the one or more automation devices, such that the self-configurable device manages a connection between the one or more field devices and the one or more automation devices. The self-configurable device is adapted to calibrate one or more field devices and manage automation functions in the industrial installation.

Described herein are systems and methods for asset-management decision-making for large industrial facilities. The disclosed systems and methods can be used to determine the current state of components and systems at a facility, and the likelihood of their degradation or failure in the future, and ultimately determine an asset management strategy that optimizes value returns and / or safety constraints.

The present disclosure relates to a technology for achieving carbon neutrality in ESG-based industrial sites. An apparatus for achieving carbon neutrality analyzes energy performance of factories, industrial facilities, and plants, derives energy saving factors and renewable energy production factors, verifies performance of facility materials and facility construction methods to comply with GRI standards, for example, optimizes internal air in accordance with the GRI standards, and quantitatively measures and evaluates environmental, social, and governance (ESG) achievement rates of factories, the industrial facilities, and the plants.

An industrial topology discovery system autonomously discovers and documents industrial automation system topologies using orchestrated discovery agents of various types. The topology discovery system can reside on a cloud platform or another high level network and deploy discovery agents on plant networks and devices within an industrial facility. These discovery agents can implement different strategies for discovering system information, and can include agents configured to monitor and report on communication traffic across respective types of networks, agents configured to probe respective device types for identity and configuration information, and other types of agents. Discovery services executed by the topology discovery system can collect device and network information obtained by the agents and use this information to document the topology of the automation system as well as to orchestrate the discovery behavior of the agents to extract further information about the system based on defined discovery rules.

The invention discloses a preparation method of a ZIF-8-based photo-thermal super-hydrophobic anti-corrosion and anti-icing coating, which comprises the following steps: S1, preparing ZIF-8 (at) PDA particles: synthesizing polydopamine modified ZIF-8 (at) PDA particles in water in one step; S2, preparing the ZIF-8-based photo-thermal super-hydrophobic anti-corrosion and anti-icing coating: carrying out composite super-hydrophobic modification on ZIF-8 (at) PDA and a carbon material according to a certain proportion, adding an adhesive, stirring, and carrying out vacuum drying to obtain the ZIF-8-based photo-thermal super-hydrophobic anti-corrosion and anti-icing coating. And spraying the mixture on the surface of a base material, and curing to obtain the ZIF-8-based photo-thermal super-hydrophobic anti-corrosion and anti-icing coating. The ZIF-8-based photo-thermal super-hydrophobic anti-corrosion and anti-icing coating material prepared by the preparation method disclosed by the invention shows excellent super-hydrophobicity, mechanical stability and corrosion resistance. Meanwhile, the ZIF-8-based photo-thermal super-hydrophobic anticorrosive coating shows excellent passive icing delay and active photo-thermal deicing capabilities on the surface of the aluminum alloy. And a brand-new strategy is provided for deicing of industrial facilities and equipment in winter.

A method of communicating with a microservice in an industrial facility. The method is implemented by a controller and includes obtaining one or more data structure types, wherein the data structure types are generated based on an API definition associated with the microservice, generating one or more variables based on the obtained data structure types, wherein the variables are associated with one or more function blocks of the controller, and transmitting data associated with the variables to the microservice via a proxy component. The controller transmits the data associated with the variables in a serialized binary format associated with the variables to the proxy component. The proxy component is configured to translate to translate the data from the serialized binary data to a first serialization format and transmit the data in the first serialization format to the microservice.

A method includes a twin model management system presenting a video stream captured by a robot in an industrial facility, the video stream presented in a digital twin (DT) of the industrial facility to a user, receiving a user request to select an input device of an industrial machine, the user request provided by the user via the DT when the industrial machine is depicted in the video stream, providing, in the DT responsive to the user request, a list of input devices indicating input device(s) of the industrial machine that are depicted in a video image of the video stream, receiving a user selection provided via the DT that specifies a target input device in the list, generating, responsive to the user selection, control command(s) specifying operation(s) to be performed by the robot to physically interact with the target input device, and transmitting the control command(s) to the robot.

The invention discloses an important target system intelligent monitoring analysis system based on a large model, and the system comprises a data collection module, a data preprocessing module, an intelligent analysis module based on the large model, a result output module, and a system management and configuration module. And efficient, accurate and intelligent monitoring and analysis of key infrastructures, important military targets and high-value industrial facilities are realized. Particularly, the invention provides a large model monitoring analysis method based on domain knowledge enhancement and a large model optimization monitoring analysis scheme based on multi-modal data collaboration, and the monitoring effect and the adaptive capacity of the system are remarkably improved.

Systems and methods for automatically broadcasting a real-time emergency signal to multiple networked devices at an industrial facility include detecting activation of an emergency alert siren, and identifying networked devices specified to receive a secondary alert signal, the networked devices configured for communication using one or more communication networks associated with the industrial facility. For each networked device, a type of broadcast message is identified and generated, in real-time. Generating a broadcast message includes broadcasting, to a radio device, an audible emergency alert message via a radio system; broadcasting a text-based emergency alert message to a cellular device, using short message service (SMS) messages using a cellular network; pushing a pop-up emergency alert message to a local computing device over a local network; and generating an automated telephone call with a pre-recorded voice message for transmitting using a telephone network.

The disclosure relates to an emission detector for monitoring methane emissions at one or more industrial facilities. The emission detector includes: an enclosure that supports a plurality of sensors, wherein the enclosure is configured to permit atmospheric gas to flow by diffusion into space at or near the plurality of sensors, wherein the plurality of sensors include at least one atmospheric sensor configured to measure atmospheric properties of the atmospheric gas that flows into the space at or near the plurality of sensors as well as at least one gas sensor configured to measure concentration of methane in the atmospheric gas that flows into the space at or near the plurality of sensors.

A secure field-data platform captures equipment images and engineering diagrams via mobile devices or autonomous platforms. On-device AI extracts asset nomenclature and nameplate data, prefilling records. A human-in-the-loop interface enables annotation, validation, and manual data entry. Data are encrypted (AES-256 or equivalent) and queued locally, then synchronized to a backend via secure transports. The system supports cryptographic agility, over-the-air AI model updates, and deployment in SaaS, on-premises, or air-gapped environments. Immutable audit logs ensure compliance. This invention enhances asset-management efficiency and security for utilities, industrial facilities, government agencies, and data centers.

Implementations relate to translating between a base map of an industrial facility and robot specific map(s) utilized by robot(s) to navigate about the industrial facility. First translation data is generated based on comparing the base map and a first robot map, and second translation data is generated based on comparing the base map and a second robot map. Using the first and second translation data, a pose of a first environmental feature detected by the first robot in the first robot map can be translated and graphically rendered in a corresponding pose in the base map, and a pose of a second environmental feature in the second robot map can be translated and graphically rendered in a corresponding pose in the base map. Association between industrial data received for industrial components observed in the base map may also be associated with detection of an environmental feature in a robot-specific map.

Devices, systems, and methods for carbon capture optimization in industrial facilities are disclosed herein. An example carbon capture process involves cooling a flue gas stream using at least one gas-to-air heat exchanger disposed upstream of a carbon dioxide (CO2) absorber. Another example carbon capture process involves heating a heat medium for solvent regeneration and CO2 stripping using a fired heater and / or using at least one waste heat recovery unit.

In variants, an ML-based control system for an industrial facility can include a remote control plane, a client, a set of agents, data processing modules, an optional data store, a telemetry module, a learning module, and / or any other suitable components. In variants, the set of agents can include a facility agent, a set of local cooling agents, and / or any other suitable agents. In variants, the set of agents can include system state approximators and decision models learned via reinforcement learning. The ML-based control system can control components of the industrial facility by predicting and / or determining component setpoints based on power load and / or heat load of the industrial facility.

The invention relates to a method for recycling polymer-based synthetic sealing membranes composed of two or more layers laminated to one another and between which a glass or polyester fibre weft is inserted, wherein the membranes undergo the following steps: - mechanical grinding and densimetric separation; - pulsed-power treatment; - drying and densimetric separation. The invention also provides an industrial facility.