158 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.

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.

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.

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 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.

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.

This invention is a method for the production and distribution of compressed air in organized industrial zones (OIZs), specifically involving the centralized production of compressed air using energy-efficient turbo compressors and its transmission to industrial facilities via high-pressure conveying lines. The method aims to produce compressed air more efficiently and minimize energy losses during transport, thanks to the low energy consumption and multi-stage compression mechanism of turbo compressors. This method also ensures fair and accurate billing based on the measurement of compressed air consumption supplied to industrial facilities. Each industrial facility is equipped with high-accuracy meters to precisely measure the amount of compressed air consumed. Data from these meters is collected and processed in real time via a central control system. Billing is then based solely on the amount of air consumed. The system aims to reduce operating costs through energy efficiency and low maintenance costs, as well as to ensure environmental sustainability by reducing carbon emissions. The fact that turbo compressors offer lower energy consumption and maintenance requirements compared to screw compressors increases the overall efficiency of this method and provides economic advantages.

The disclosure relates a wind blade (1) segmented by a cutting contour (2, 9, 12) into an inner segment (3) and an outer segment (4). The cutting contour includes straight and circular portions enabling modular assembly. The outer segment comprises an opening (7) configured to receive the inner segment of another wind blade. A building assembly is formed using three wind blades, where the outer segments align and abut each other in a horizontal plane, optionally creating a hollow space for accommodating utilities. The disclosure also provides a method for manufacturing wind blades with specific cutting contours and assembling them into modular structures for versatile applications. This design facilitates cost-effective construction of warehouses, residential, commercial, and industrial facilities, while reusing wind blade components for sustainable architecture.

In an exemplary embodiment, a method for detecting anomalies associated with a machine includes recording a dataset associated with the machine, determining, with a first machine learning model, a label associated with the dataset, determining whether the label should be reviewed, and if it is determined that the label should be reviewed, subjecting the dataset and label to review and updating the label based on the review.Alternatively or additionally, in an exemplary embodiment, a method for presenting an analysis of a machine included in an industrial facility includes generating a digital twin of the machine, determining at least one property of the digital twin based on a simulation of operation of the machine, and generating a representation of the industrial facility including a visualization of the digital twin and a visual indicator of the at least one property of the digital twin.

The method according to the invention for monitoring an automation system (2), in particular automation devices (4, 5, 10) in an industrial plant (1), comprises the following steps: - receiving operating data (B) from the automation system (2); - assigning the operating data (B) to at least one of the automation devices (4, 5, 10); - monitoring the operating data (B) for the presence of an event by checking whether the operating data (B) fulfils an event condition associated with the event; - counting each case in which the event condition is fulfilled using a counter (69, 71) associated with the event condition; - storing the value of the counter (69, 71) in a data set (D) which is associated with the respective event and the respective automation device (4, 5, 10); - outputting the data set (D) with the value of the counter (69, 71) via a user interface. Thereby, the status of the automation devices can be quickly and easily overviewed even over a longer observation period.

The invention belongs to the technical field of industrial facility safety assessment, and particularly discloses an overdue service pressure pipeline risk assessment method and terminal equipment, and the method comprises the steps: constructing a fault tree with the failure of a pressure pipeline as a top event; obtaining a fuzzy number corresponding to a plurality of expert ratings of each bottom event in the fault tree, and determining a relative consistency degree of the expert ratings according to the fuzzy number; clustering the fuzzy number by using a similarity clustering method, and determining an optimal relaxation factor according to a clustering result; determining the failure probability of each bottom event according to the relative consistency degree of expert rating and the optimal relaxation factor; and determining the failure probability of the top event according to the failure probability of each bottom event. According to the method, the optimal relaxation factor is determined by combining the fuzzy number of expert rating, and the relaxation factor is improved, so that the influence of subjectivity is remarkably reduced, and the reliability of risk assessment of the overdue service pressure pipeline is greatly improved.

The application relates to the technical field of intelligent robot inspection, and discloses a somatic intelligent AI inspection method based on digital twinning, wherein the somatic intelligent AI inspection method based on digital twinning comprises the following steps: a dynamic attention multi-layer feature extraction network is used to analyze multispectral images collected by a robot-mounted sensor to generate a real-time distribution diagram of industrial facility abnormal coverage; a space-time sequence contrast learning model is used to analyze historical abnormal coverage data to generate an abnormal coverage trend prediction; a physically constrained neural differential equation model is used to analyze an abnormal coverage evolution process to generate an accurate abnormal evolution prediction result; a multi-objective optimization algorithm is used to generate an optimal inspection path; a digital twinning system is dynamically updated, and an industrial facility maintenance optimization suggestion is generated; and through the dynamic attention multi-layer feature extraction network and a light condition self-adaptive enhancement algorithm, the detection difficulty in a strong light and high reflection environment is effectively solved.

An industrial structure for wind energy collection includes an industrial facility requiring ventilation and a ventilation opening. An industrial fan associated with the vent discharges exhaust gas forming an exhaust flow zone opposite the vent. The exhaust flow zone is defined by first and second boundaries extending from the industrial structure at first and second sides of the vent. At least one wind turbine is located outside the vent, including a turbine blade portion and a generator. The at least one wind turbine is positioned relative to the vent such that, during each rotational cycle, the blade portion lies partially within the exhaust flow zone across the first boundary and partially outside the exhaust flow zone.

Variants of the system includes an industrial facility, job scheduling services, and a set of control agents configured to manage power and cooling resources. The method includes determining a current system state, optionally predicting a future system state, determining control setpoints, and controlling the facility based on the setpoints. In a data center implementation, the control agents receive physical state information from infrastructure components and job data from the job scheduling services. Using this information, the control agents predict future power and heat loads associated with scheduled compute jobs. The predictions are generated by a state approximator. Based on the predicted resource demands, the control agents determine control setpoints for cooling and power infrastructure components. The job scheduling services can allocate, delay, or reschedule jobs based on predicted thermal and power constraints.

The invention relates to a self-luminous coating material as well as a preparation method and application thereof, and belongs to the technical field of advanced functional materials. The self-luminous coating material comprises modified noctilucent powder, a resin matrix, an inorganic filler, a light stabilizer, an anti-settling agent, a coalescing agent, a defoaming agent, a flatting agent, a thickening agent, a toughening agent and a dispersing agent, the types and contents of the components of the self-luminous coating material are regulated and controlled, and particularly, SrAl2O4: Eu < 2 + >, Dy < 3 + > and Cu < + > of which the surface is coated with a silicon dioxide layer are adopted. The self-luminous coating material which is high in brightness, long in afterglow, high in adhesive force and resistant to aging is obtained under the synergistic effect of other components by adopting a polyurethane-polymethyl methacrylate triblock copolymer as a resin matrix and taking Mn < 2 + > as modified luminous powder. The method has good application prospects in self-luminous identification systems in the fields of traffic, fire fighting, buildings, industrial facilities and the like, is adaptive to extreme environments, and meets the use requirements of different scenes.

Described are techniques for identifying a design of an infrastructure on an industrial floor to service a user. A knowledge corpus of information to be used as a sample data set for training a machine learning model is generated, which includes information, such as mobility patterns of users on the industrial floor for various manufacturing process flows, and interaction of users on the industrial floor with different services at different locations on the industrial floor for various manufacturing process flows. A machine learning model is then trained to identify the designs of the infrastructure on the industrial floor based on the knowledge corpus. Upon receiving the requirements of a service level agreement and the current manufacturing process flow, the trained machine learning model is used to identify a particular design of the infrastructure of cloud and edge computing resources on the industrial floor that optimally services the user.

A multi-modal combustion interruption system comprises a detection subsystem configured to identify combustion events, an electromagnetic emission subsystem having pulsed energy source and directional emission structure, a control processor implementing adaptive modulation based on measured combustion response, and a safety enforcement subsystem configured to control emission activation based on presence detection. The system may be configured in various modes from baseline electromagnetic emission through enhanced configurations incorporating optional ionization enhancement, particle generation, and acoustic energy subsystems. Adaptive modulation enables parameter selection based on measured combustion response rather than predetermined values. The modular architecture enables configuration selection based on deployment type and application requirements. Fixed installations may utilize grid power for industrial facility protection. Mobile platforms may employ onboard power for emergency response or wildfire intervention. Configuration selection may consider environmental compatibility including omission of particle generation for water-sensitive equipment environments or incorporation of multiple enhancement subsystems for demanding applications.

Methods, systems, apparatus, and computer program products for implementing machine learning within a control system are disclosed. An industrial facility settings board can be received from a machine learning system, and a determination can be made as to whether to adopt settings in the industrial facility settings board. The machine learning model can be a neural network, e.g., a deep neural network, that has been trained, e.g., using reinforcement learning, to predict data settings boards that are predicted to optimize efficiency of a data center.

A drone navigation method based on optical distortion and a drone using the same are provided. The method includes: capturing images of an environment using a drone's camera with high optical distortion properties; detecting a reference object and reference lines in the images; determining cells formed by the reference lines and monitoring curvatures of the lines; determining a reference cell adjacent to the drone; determining the drone's projected position in the reference cell based on curvatures of cell boundaries; determining a target motion direction according to a navigation task and controlling the drone's motion; and continuously updating the drone's projected position based on monitored boundary curvatures to manage the drone's motion. This method enables precise indoor navigation without relying on GPS or external markers, significantly enhancing drone operability in complex indoor environments such as warehouses and industrial facilities.

An adjustable fire extinguishing and explosion suppression bottle clamp belongs to the technical field of mounting and fixing of fire fighting equipment and safety devices, and in special equipment and industrial facilities, a fire extinguishing bottle of a fire extinguishing system and an explosion suppression system needs to be reliably fixed on a preset base through a special clamp; in the prior art, the holding force of a hoop on a bottle body is insufficient due to tolerance accumulation, and hidden dangers are buried in safe operation in a long-term vibration environment; the invention provides an adjustable fire-extinguishing explosion-suppression bottle hoop, and the core purpose of the adjustable fire-extinguishing explosion-suppression bottle hoop is to realize step-by-step independent operation in a mounting process through structural design, namely, a positioning block is independently fixed on a base firstly, and then a bottle body is independently locked, so that a size chain accumulative error is effectively compensated, and two key connecting points can reach an optimal fastening state; and the installation efficiency, reliability and consistency are improved.

Systems and methods are provided to provide quick and easy access to a variety of electronic files associated with pieces of industrial equipment that are located within a physical environment, such as a manufacturing facility, processing plant, or various other industrial facilities. Each piece of industrial equipment can be associated with a variety of electronic files providing information related to the equipment, such as CAD files. A mobile communications device can be used to scan a tag that is coupled to a piece of industrial equipment and the electronic files for that piece of industrial equipment can be displayed on the mobile communications device.

A gas leak detection system includes a plant subsystem including a gas leak detection sensor disposed at an industrial facility and at least one vehicle subsystem including a vehicle operable in and around the industrial facility. The vehicle subsystem further includes at least one vehicle gas leak detection sensors carried by the vehicle and operable to detect the presence and concentration of gasses in the atmosphere in and around the vehicle, a controller carried by the vehicle and operably coupled to the at least one vehicle gas leak detection sensor to identify a gas leak and a communication device carried by the vehicle and communicatively coupled to the controller and the plant subsystem. The communication device is operable to transmit a alarm signal to the plant subsystem in response to the controller identifying a gas leak and to receive an alarm signal from the plant subsystem.

The invention discloses an industrial facility automation control system and method based on multi-dimensional information fusion, and relates to the technical field of industrial facility automation control, and the method comprises the steps: collecting the operation state signal, production power data and equipment basic parameters of industrial equipment, calculating the operation health degree and production adaptation degree of the equipment, and calculating the operation state signal of the industrial equipment; and inputting the operation health degree and the production adaptation degree into a comprehensive operation index evaluation model, calculating a comprehensive operation index, obtaining a real-time health degradation rate according to the historical operation health degree and the production time, and determining a suggested operation duration according to the real-time health degradation rate and the comprehensive operation index. According to the invention, through multi-dimensional information fusion and comprehensive consideration of the matching degree of the equipment health state and the production demand, accurate evaluation and predictive maintenance of the equipment operation state are realized, overuse or premature shutdown of the equipment is effectively avoided, and the operation reliability and the production efficiency of industrial facilities are improved.