253 results about "Industrial site" patented technology

The invention relates to the technical field of vision, in particular to an object monitoring method based on a multi-camera joint calibration technology and a monitoring camera thereof. The method comprises the following steps: driving all cameras to synchronously shoot a calibration reference object with known geometric characteristics, and solving internal and external parameters of each camera and an accurate space pose relationship between the internal and external parameters by utilizing shot images to form a joint space relationship chain; controlling the camera array to synchronously shoot a target object, and correspondingly converting the two-dimensional image points acquired by the cameras into spatial point coordinates in a unified three-dimensional coordinate system by using the joint spatial relation chain to generate three-dimensional point cloud data of the target object; and processing the generated three-dimensional point cloud data, extracting key geometric features of the target object in real time, performing comparative analysis on the extracted features and a preset standard or a historical state, and outputting a state monitoring result of the target object. According to the invention, the influence of temperature drift and mechanical vibration on the measurement precision is effectively suppressed, and the stability of long-term monitoring of an industrial field is guaranteed.

The invention discloses an industrial data analysis system and method based on digital twinning and causal inference, and the system comprises a physical sensing layer which is used for collecting multi-source heterogeneous data of an industrial site; the digital twinborn platform layer is used for constructing and operating a virtual twinborn model corresponding to the physical entity; the intelligent analysis engine layer is integrated with a causal analysis module and a federal learning module which are associated; the application and interaction layer is used for visualizing the analysis result and issuing a control instruction; wherein the causal analysis module is used for constructing a causal graph based on the multi-source heterogeneous data and performing causal inference. Through federal learning, on the premise of protecting data privacy of all parties, cross-organization and cross-region collaborative modeling and knowledge sharing are realized.

The invention discloses a quality detection system based on three-dimensional point cloud scanning and RGB image fusion, relates to the technical field of industrial automatic detection, and aims to solve the problem of high quality detection error rate caused by the fact that a detection result is easily interfered by visual angle change and illumination conditions in an existing detection method. According to the method, the color point cloud model under the unified coordinate system is constructed through space calibration and point pixel level registration, and the structural information and texture features of the workpiece are effectively reserved. Therefore, the problem that the quality detection error rate is high due to the fact that the detected object has curvature dramatic change, a strong reflection area or frequent shielding is solved. According to the method, the detection accuracy is improved, meanwhile, the robustness and the operation efficiency are high, the industrial workpiece detection requirements with complex curved surface structures and high surface quality requirements can be met, and the actual application requirements of an industrial site for an intelligent surface detection system are met.

The invention provides an intelligent gateway data processing method for industrial multi-protocol adaptive conversion, which aims at the current situation that various heterogeneous communication protocols exist in an industrial site and is based on a complete process of protocol feature vector extraction, machine learning automatic identification, semantic level analysis and mapping, dynamic rule configuration and protocol frame reconstruction. By constructing a protocol feature model library, semantic contents of original data frames are automatically identified and analyzed, and accurate equivalent conversion of multi-protocol data is further realized in combination with a protocol conversion rule and a unified semantic model. The reconstruction function frame realizes frame structure assembly, data coding and check calculation, and ensures that an output frame completely conforms to a target protocol specification. The method has high compatibility, high expansibility and good real-time performance, and the industrial protocol intercommunication efficiency and the automation degree are remarkably improved.

The invention provides a multi-modal fusion causal analysis method and platform for industrial safety production, and the method comprises the steps: carrying out the preprocessing of multi-modal key data from an industrial site, and generating a standardized time series data matrix; based on the standardized time sequence data matrix, combining industrial physical rules and operation process semantics to construct an industrial safety causal atlas; based on a self-supervised learning mechanism, optimizing the structure and edge weight of the industrial safety causal atlas by using the standardized time sequence data matrix to obtain an optimized causal reasoning model; and performing path-level risk activation judgment and accident causal traceability by using a real-time standardized time sequence data matrix constructed by the causal reasoning model and real-time inflow multi-modal key data to generate a risk alarm and traceability report. According to the method, the perspectiveness, the accuracy and the interpretability of industrial safety monitoring are remarkably improved.

The invention discloses a controller programming method and device based on an equipment model, equipment, a medium and a product, the equipment model is used as a unified semantic anchor point, heterogeneous characteristics of physical equipment are converted into computable structured description, hardware adaptation and business logic are decoupled through a driving framework, a large model focuses on generation of a high-value control strategy, and the control strategy is optimized. Semantic drift and logic illusion of a program generation large model are remarkably inhibited by relying on double constraints of equipment document data and a knowledge graph, finally, an executable drive program meeting strict requirements of an industrial site is output through compiling verification of a closed loop, and due to the fact that manual development is not needed, development efficiency is improved, development cost is reduced, and development efficiency is improved. The equipment model provides a cross-protocol and cross-manufacturer standardized interface contract, so that the problem of poor reusability in traditional development is solved, and the reusability is improved.

The invention relates to the technical field of equipment state monitoring, in particular to an emergency cut-off valve bolt looseness detection method and system based on multi-modal fusion. The method specifically comprises the following steps of multi-source data synchronous acquisition, accelerometer installation and data processing, environmental adaptability preprocessing, bolt area optical flow feature extraction, Kalman filtering multi-source fusion, bolt looseness detection and loose bolt positioning. According to the emergency cut-off valve bolt looseness detection method based on multi-modal fusion, online, automatic and real-time accurate monitoring and early warning are achieved, the reliability and the anti-jamming capability of the system are remarkably improved, a high-precision and quantifiable objective diagnosis result is provided, good economical efficiency and large-scale deployment feasibility are achieved, and the method is suitable for popularization and application. The industrial pain point that a traditional contact type sensor scheme is difficult to apply to an industrial site with a large number of bolts in a large scale due to too high cost and technical complexity is effectively solved.

The invention discloses an early warning grade evaluation method based on an urban pollution industrial site, relates to the technical field of industrial site early warning evaluation, and solves the technical problems of incomplete overall evaluation and lack of systematic analysis process and data processing correction caused by analysis of a single evaluation index. According to the method, pollution factor indexes are integrated in a three-dimensional mode through the pollutant standard exceeding multiple mean value, the specific pollutant toxicity coefficient and the pollution plume diffusion area proportion, the pollution intensity is reflected, toxicity hazards and spatial diffusion risks are considered, the soil pollution area is calculated through the Kriging interpolation method, the groundwater pollution plume area is predicted through the MODFLOW model, and the groundwater pollution plume area is predicted through the MODFLOW model. The overlapping area is processed through a maximum area method, repeated statistics is avoided, the accuracy of pollution range data is improved, different threshold values are set, standardized matching of comprehensive indexes and early warning levels is achieved, corresponding management and control measures are defined for all the early warning levels, abstract comprehensive indexes are converted into specific practical operation guidance, and hierarchical management and control can be conveniently carried out.

The invention provides an industrial operation area multi-view video collaborative analysis method and system based on artificial intelligence. The method comprises the following steps: firstly, acquiring multi-view video data; secondly, based on the working area and the equipment layout, deducing a semantic association relationship among the multi-view video data; according to the semantic association relationship, dynamically adjusting the analysis priority of the multi-view video data through an artificial intelligence model to determine an analysis priority sequence; and according to the determined analysis priority sequence, executing interactive co-processing of the multi-view video data, and finally generating a co-analysis result. According to the technical scheme provided by the invention, the physical layout and the workflow of the industrial site are converted into the semantic association relationship, and the dynamic scheduling analysis resources and the interactive collaborative analysis are performed according to the semantic association relationship, so that the spanning from simple monitoring of a plurality of isolated video streams to intelligent and coherent understanding of the whole operation flow is realized; and the intelligent level and decision support capability of monitoring analysis are improved.

The invention discloses an intelligent identification and counting method, system and equipment for an industrial elevator and a medium, and the method comprises the steps: collecting an interference target negative sample, generating a diversified illumination scene sample, combining the interference target negative sample with the illumination scene sample, training and optimizing a detection model, deploying the trained and optimized detection model, and processing a video stream in real time. And judging the effective lifting behavior of the elevator, and intelligently counting the operation frequency of the elevator. According to the method, an adversarial training strategy and negative sample database construction are adopted, the discrimination capability of the model for an interference target is remarkably improved, the stable recognition performance of the system under the all-weather condition is ensured through developed illumination enhancement simulation, and the intelligent counting algorithm based on the state machine is used for realizing the intelligent counting of the interference target through a rigorous condition judgment mechanism. Accurate statistics of the work cycle of the elevator is achieved, a reliable automatic counting solution is provided for an industrial site, and the intelligent level of production management is greatly improved.

The invention discloses a femtosecond optical comb large-size precision absolute distance measurement system in a complex environment. Comprising a source module, a beam splitter, a third dichroic mirror, a fundamental frequency femtosecond optical comb reference detector, a frequency doubling femtosecond optical comb reference detector, a fourth dichroic mirror, a frequency doubling femtosecond optical comb measurement detector, a fundamental frequency femtosecond optical comb measurement detector, a phase discriminator, a ranging zero point mirror and a corner reflector. The source module comprises an atomic clock, a femtosecond optical comb, an optical fiber beam splitter, a signal generator, an electro-optical modulator, a lens, a frequency multiplication module, a first collimation beam expander, a second collimation beam expander, a first dichroic mirror and a second dichroic mirror. According to the scheme, the defects that in the prior art, the measurement range is insufficient, complex industrial sites are difficult to adapt, and the real-time performance is poor are overcome, and a new way is provided for breaking through the technical bottleneck of large-range, high-precision, dead-zone-free, rapid and real-time measurement in a complex environment; and a technical support is provided for engineering application of a femtosecond optical comb precision distance measurement technology and development of a subsequent measurement prototype.

Disclosed are a method and an installation for discontinuously counting objects on a moving vehicle, the vehicle moving in a continuous flow along a straight or substantially straight course, for example for counting gas cylinders loaded on a moving vehicle, for example a vehicle entering and / or leaving an industrial site.

The invention relates to the field of oil pumping unit fault diagnosis, in particular to a multi-parameter oil pumping unit fault diagnosis method, system and device based on edge calculation and a storage medium. Multi-dimensional parameters of the operation state of the target oil pumping unit are obtained in real time; performing preprocessing and feature extraction on the multi-dimensional parameters to generate standard feature data; based on the standard feature data, performing parallel reasoning by using a machine learning model deployed in an edge computing device to obtain a fault type probability output by each model; performing weighted fusion on the fault type probability output by each model to generate a comprehensive fault diagnosis result; comparing the comprehensive fault diagnosis result with a preset threshold value to determine a fault level; and generating a corresponding control instruction according to the fault level. According to the invention, the operation state of the oil pumping unit can be comprehensively monitored, the hardware and operation and maintenance cost of the system is obviously reduced, and the requirements of an industrial field on real-time performance and high efficiency are met.

The invention relates to the technical field of intelligent welding, in particular to a steel structure fillet weld intelligent identification method and system based on 3D vision, and the method comprises the steps: obtaining a point cloud data set of a workpiece, and extracting point cloud data of a weld region from the point cloud data set; dividing the welding seam area into a plurality of welding seam sub-areas, wherein one welding seam sub-area corresponds to one independent welding seam; carrying out welding seam coarse skeleton extraction on each welding seam sub-region, and carrying out merging processing on the welding seam coarse skeletons of which the distance between end points is smaller than a threshold value; and on the basis of the combined welding seam coarse skeletons, welding seam fine skeleton point set extraction is conducted, and a welding seam path expression is obtained based on welding seam fine skeleton point set fitting. The method solves the problem that an existing algorithm needs an operator to repeatedly adjust a threshold parameter according to experience, resulting in lack of adaptive ability, and solves the problems that the calculated amount is large, the speed is low and the real-time requirement of an industrial site cannot be met when the workpiece point cloud data is processed.

The invention discloses an unmanned feeding system based on automatic control and a Gray bus, which comprises an unloading trolley, a Gray bus, a wireless network bridge, a ground control cabinet, a control terminal and a radar level gage. According to the technical scheme, on-site key position monitoring of a feeding belt of a converter tower, precise positioning of a feeding trolley, height judgment of the material level of a material bin, bin position approval and the like are comprehensively controlled, unmanned operation of the whole feeding process of the converter is achieved, and the system is suitable for high-temperature and high-risk scenes in the iron and steel smelting industry, can be popularized to similar material conveying scenes and promotes few-person and intelligent upgrading of the industrial site. Traditional cable dragging power supply is abandoned, the position of the trolley and the material level of the stock bin can be accurately judged, the problems of material accumulation, belt material stacking and the like caused by the fact that raw materials and auxiliary materials are fed into a wrong stock bin and the position deviation of the trolley are effectively solved, the feeding precision is improved, and the steel product quality is guaranteed. After unmanned feeding is achieved, the labor cost input is greatly reduced, the labor cost is reduced, and the production efficiency is improved.

The invention provides a composite material pipeline thickness online detection system and method, and relates to the technical field of composite material pipeline manufacturing, and the system comprises a plurality of laser range finders and a signal processing unit; the plurality of laser range finders are connected with the signal processing unit and are arranged at different positions of the continuous winding production line; the plurality of laser range finders are used for detecting the distance between the laser range finders and the steel belt mold; in the initial state, the distance is a reference value, and in the continuous winding production process, the distance is a measured value; and the signal processing unit calculates the thickness of the pipe wall at the position of the laser range finder according to the reference value and the measured value. The multiple laser range finders are arranged on the continuous winding production line, the signal processing unit is combined, the pipe wall thickness of each position of the production line can be independently monitored, the problem that the thickness of a multi-layer structure cannot be measured on line through a traditional method is solved, the product quality and the production efficiency are remarkably improved, and the measurement precision is greatly improved; the device is very suitable for long-term use in industrial sites.

The invention discloses a mechanical arm dynamic tracking and obstacle avoidance system and method based on reinforcement learning. The mechanical arm dynamic tracking and obstacle avoidance system comprises a sensing module, a target motion prediction module, a reinforcement learning decision module, a safety control and constraint module, an execution module and a training and simulation module. According to the invention, a complete system including environment perception, target motion prediction, reinforcement learning decision and execution control is constructed, so that the mechanical arm can predictively track a moving target in an unknown or dynamic environment, and real-time obstacle avoidance is carried out on a static or dynamic obstacle; and the requirements of safety, robustness and real-time performance of an industrial site are met in the whole control process.

The present disclosure belongs to the technical field of robot control, and specifically provides a four-legged robot mechanical arm end force feedback teleoperation control system and method. In view of the key challenges of control errors caused by communication time delay and soft obstacles difficult to identify in a dynamic environment, the system introduces a predictive contact response mechanism, pre-models and judges the end contact state of the mechanical arm, realizes feedforward control and buffer adjustment for communication time delay. At the same time, a dynamic semantic map is constructed combined with multi-source sensing information, and the soft obstacle inference and path optimization are carried out by fusing the end force sense change trend, so as to significantly improve the identification and avoidance ability of the system in a complex and invisible obstacle environment. The present application has good foresight, adaptability and high redundancy safety characteristics, and is suitable for multi-task inspection operation in industrial sites such as thermal power plants, and is particularly suitable for remote human-machine collaborative operation scenes in narrow spaces.

An intelligent die casting quality prediction method based on SMOTE-ENN and XGBoost belongs to the technical field of industrial quality detection, and comprises the following steps: firstly, acquiring a production process data set through a data acquisition module, and preprocessing to obtain a preprocessed data set; secondly, based on an SMOTE-ENN hybrid sampling module, balancing processing is carried out on the preprocessed data set; and thirdly, based on an XGBoost classification model module, performing high-precision identification and classification on the balanced and optimized sample data set, constructing a product quality prediction model, and obtaining a trained XGBoost quality classification model. And finally, outputting a result based on the XGBoost quality classification model, constructing a quality early warning module, and carrying out real-time quality evaluation and defect identification. The intelligent die casting quality prediction method integrating data acquisition, preprocessing, SMOTE-ENN mixed sampling, XGBoost modeling and quality early warning is constructed, the problems that in an industrial site, die casting data categories are unbalanced, noise interference is large, and defect recognition is difficult are effectively solved, and high-precision prediction and real-time early warning of die casting product quality are achieved.

The invention discloses a main shaft cutter wear monitoring method based on physical guidance and semi-supervised learning. The method comprises the following steps: collecting cutter acceleration signals, extracting multi-domain statistical features, carrying out cross-cutter robustness screening, and constructing accumulated features reflecting a historical trend to form a mixed input set; mining an explicit physical equation conforming to a degradation mechanism by using a parallel symbol regression network with monotonicity penalty introduced; performing prediction and smooth monotonization processing on unlabeled data by using the equation, generating a physical weak label, and constructing a mixed training set; designing a physical guidance cross attention mechanism, and performing weighted fusion on statistical and cumulative features by taking a physical equation as prior; and constructing a lightweight neural network processing fusion feature, and designing a differential loss function for joint training based on the mixed training set. The method can break through the dependence on a large amount of labeled data, guarantees the physical consistency of prediction results, and meets the high-precision monitoring requirements of an industrial site.

The present invention relates to an electric and non-electric combined dehumidifier in which, even though an electric dehumidifier that consumes an allowable margin electricity is used in an industrial site where it is previously installed and has difficulty in increasing the electric capacity, a non-electric dehumidifier that does not use electricity is used together when the dehumidification performance is insufficient, thereby capable of improving dehumidification performance.

A Surface-affixed, Storm-Resistant Containment Unit involves a shelter structure, with internally-mounted photovoltaic solar panels, and movable doors which may be ‘closed’ to protect the photovoltaic solar panels from storm-related damage, e.g. hail, extreme wind and airborne debris. When weather conditions improve, the movable doors may be ‘opened’, allowing sunlight to strike the undamaged photovoltaic solar panels, and renewable energy production to resume. These Storm-Resistant Containment Units may be installed, and electrically connected in multiples to comprise a storm-resistant, commercially-sized, renewable power generating station (or ‘Micro-Grid’) for use in geographic areas prone to severe storms and hurricanes. Such storm-resistant, commercially-sized, power generation station may be advantageously applied at existing ‘Brown-Field’ industrial sites that have existing, unused electrical-grid infrastructure.

The utility model relates to the technical field of industrial power utilization, in particular to a dustproof industrial switch socket, which comprises a mounting shell, a protective cover and a switch socket, the switch socket is fixed in the mounting shell, the protective cover is arranged on the mounting shell and comprises an upper cover and a lower cover, the lower cover is fixedly arranged at the bottom of the mounting shell, and the switch socket is arranged in the mounting shell. The two sides of the top of the lower cover are fixedly connected to the two sides of the mounting shell, the upper cover covers the lower cover, and the top of the upper cover is rotationally connected with the protective cover through a damping rotating shaft. Through an assembly composed of the mounting shell, the protective cover and the switch socket, a set of dustproof switch socket structure with a good heat dissipation effect is provided for an industrial site, dust in an industrial operation environment can be effectively prevented from floating and making contact with the plugging position of the socket, the heat exchange efficiency can be better improved, and the service life of the socket is prolonged. And the electrical equipment is better in use stability and higher in safety after being plugged with the switch socket.

The utility model discloses a special flow meter device for acid industry chromatography, which comprises a connecting pipeline, and flange connecting ends are mounted at two ends of the connecting pipeline; a sealing assembly is arranged in the flange connecting end and comprises a sealing sleeve, one end of the sealing sleeve is inserted into the flange connecting end, and the other end of the sealing sleeve is inserted into an external pipeline; the sealing pieces are arranged in the middle and at the two ends of the sealing sleeve, the sealing pieces abut against the flange connecting end and an external pipeline respectively, an annular groove is formed in an opening of the flange connecting end, and a connecting protrusion is formed on the outer surface of the middle of the sealing sleeve; by means of the designed sealing assembly, continuous and multi-layer sealing barriers are formed in the flange connecting end, the barriers can effectively resist corrosion of corrosive media and can keep excellent sealing performance under the extreme working conditions of high pressure, high temperature and the like, and therefore long-term stable operation of the flowmeter is guaranteed, and the service life of the flowmeter is prolonged. Meanwhile, practicability and convenience of an industrial site are fully considered in design of the sealing assembly.

The invention discloses an ignition-free closed-cup flash point measuring system for petroleum products. The ignition-free closed-cup flash point measuring system comprises a sample pretreatment unit, a flash separation unit, a constant-temperature control unit, a flash point detection unit and a data processing unit which are communicated in sequence. The sample pretreatment unit is used for removing solid impurities and moisture in a petroleum sample; the flash separation unit is used for converting the pretreated sample into oil vapor and liquid components; the constant-temperature control unit maintains the temperature stability of the system; the flash point detection unit detects the flammable flash state of the oil vapor in an optical mode; the data processing unit records and analyzes the detection data to output a flash point value. The invention further provides auxiliary modules such as a circulating purification unit and a safety monitoring unit, efficient, accurate and safe measurement of flash points of various petroleum products such as gasoline, diesel oil and lubricating oil is achieved through pressure grading flash evaporation and precise temperature control, the detection period is short, the automation degree is high, and the device is suitable for rapid flash point analysis of laboratories and industrial sites.

A computer-implemented method for monitoring productivity, health and safety risks posed by activities and objects, and other signals present at industrial sites comprises: receiving data inputs from input devices at an industrial site; selecting a data model that is programmed to detect activities or objects associated with workers or equipment present at the industrial sites; applying the data inputs to the data model to receive output data specifying whether the activities or objects associated with workers or equipment are present at the industrial site; and if they are present: based the output data, determining characteristics of the activities or objects; based on the characteristics, determining whether that the activities or objects cause any productivity, health or safety risks at the industrial site; and if so, generating notifications indicating the health or safety risks at the industrial site.

1. The name of the design product: video edge gateway computer. 2. The use of the design product: the design product is used for data collection, conversion, processing and transmission in industrial sites and commercial scenes. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

1. Name of the designed product: industrial gateway (built-in antenna). 2. Use of the designed product: network connection and data communication for outdoor industrial site equipment. 3. Design points of the designed product: in shape. 4. Picture or photo that best indicates the design points: perspective view.

Cogeneration installation with a nuclear reactor site and an industrial site with a chemical production unit, the industrial and nuclear sites being separated and connected by a closed-loop thermal energy storage system. The invention essentially consists of physically relocating and functionally separating a nuclear site from an industrial site comprising at least one chemical production unit that utilizes the heat produced by a reactor block at the nuclear site. This physical relocation is achieved by a thermal storage loop with hot and cold tanks located both at the nuclear site and at the industrial site. Figure for the abstract: Fig. 1

The invention provides a laser non-contact type valve element displacement measurement embedded system and an operation method thereof, relates to the technical field of non-contact type displacement measurement and embedded control, and aims to solve the problems that contact type measurement is easy to wear, clamping errors exist, valve element movement is interfered, and measurement accuracy is high. And a non-contact scheme is poor in interface compatibility, single in function and difficult to meet the requirements of real-time performance and measurement-control integration of an industrial site. The laser displacement sensor, the real-time controller and the multi-channel I / O board card are integrated, LabVIEW software is matched, valve element displacement non-contact collection and analog / digital signal output and debugging are achieved, contact type measurement defects are avoided, and the requirements for industrial field measurement and control integration and high stability are met. According to laser non-contact measurement, contact abrasion, errors and valve element interference are avoided, and the measurement precision is improved; the integrated measurement and control function solves the problem of poor interface compatibility; modularization is easy to maintain and extensible, and the detection efficiency of the precision executing mechanism is improved.