22results about How to "Enable predictive maintenance" patented technology

The application discloses a kind of digital intelligence powder type free matching variable viscosity fracturing fluid skid-mounted equipment and control method thereof, belong to oil and gas field development technical field.The equipment includes stirring mechanism, feeding mechanism, water feeding mechanism and discharging mechanism, and is centrally controlled by control box.Feeding mechanism uses first screw conveyor to deliver solid material to stirring tank body;Water feeding mechanism supplies water to tank by water feeding pump and water outlet pipe with electromagnetic valve, and water quantity is monitored by water inlet flow sensor;Discharging mechanism outputs mixed liquid by discharging pump, and viscosity sensor detects fracturing fluid viscosity in real time.Control box connects each sensor and executing component, realizes automatic adjustment and closed-loop control of material proportioning by collecting flow and viscosity data.The application realizes accurate and automatic preparation of fracturing fluid, effectively solves the problem of inaccurate and poor stability of traditional manual proportioning, and significantly improves the quality of liquid preparation and operation efficiency.

The invention discloses a concrete pump pipe fixing system and an assembling and monitoring method thereof. The system comprises a vertical fixing device, a bent pipe fixing device, a horizontal fixing device and a monitoring and control system. The assembling method comprises the following steps of positioning and paying off, installing the vertical fixing device, installing the bent pipe fixing device, installing the horizontal fixing device, installing the pipeline, and clamping and fixing. The monitoring method comprises five main steps of system initialization, data acquisition, edge calculation processing, cloud analysis and early warning, and decision support and feedback. According to the invention, lossless installation, intelligent monitoring, active early warning and predictive maintenance are realized, the construction safety is remarkably improved, the service life of equipment is remarkably prolonged, and the management efficiency is remarkably improved.

The utility model provides centrifugal air compressor testing equipment, and relates to the technical field of air separation systems, and the centrifugal air compressor testing equipment comprises a mounting seat which is used for fixing a centrifugal air compressor; one end of the air inlet monitoring pipe is connected with the air outlet end of the air supply mechanism, and the other end is connected with an air inlet of the centrifugal air compressor; an air inlet temperature sensor, an air inlet humidity sensor and an air inlet flow sensor are mounted on the air inlet monitoring pipe; the gas supply mechanism is used for adjusting the temperature, humidity and flow of gas; and the air outlet monitoring pipe is installed on the installation base and connected with an air outlet of the centrifugal air compressor, and an air outlet flow sensor is installed on the air outlet monitoring pipe. According to the method, the equipment rule is summarized through testing, predictive maintenance can be realized, stable operation of the equipment can be maintained, and the maintenance difficulty is reduced.

This invention relates to the field of transformer condition monitoring technology, specifically a transformer condition monitoring and protection system utilizing a wireless sensor network. The system includes a sensor optimization deployment module for determining the optimal physical installation location of each wireless sensor node within the wireless sensor network based on thermal imaging analysis of the transformer; and a data acquisition module for collecting transformer condition data through multiple wireless sensor nodes deployed at the optimal physical installation locations. This condition data includes at least temperature data, vibration data, and electrical parameter data. This invention obtains a continuous temperature change map of the transformer through thermal imaging analysis and employs algorithms for calculating the deflection angle and distance. Using the hotspot area with the largest temperature change rate as a benchmark, and combining this with the physical offset of the thermal field propagation, the optimal sensor installation location is calculated, overcoming the shortcomings of traditional manual sensor placement that relies on experience.

The invention discloses a built-in ultrasonic detection safety assessment method for a U-shaped tube bundle of a high-pressure heater of a power plant. The method comprises the following steps: S1, sampling a core detection area determined based on a flow field and a structure in the U-shaped tube bundle of the high-pressure heater; s2, cleaning the inner wall of the sampling tube bundle and calibrating an ultrasonic detection system; s3, performing spiral scanning on the sampling tube bundle by adopting a built-in rotary ultrasonic detection system to obtain wall thickness distribution data; s4, identifying a defect type based on the scanned image, determining the minimum residual wall thickness, and calculating a safety coefficient in combination with a bursting pressure formula; and S5, making a hierarchical maintenance decision based on the safety coefficient. Compared with the prior art, the built-in ultrasonic detection safety assessment method for the U-shaped tube bundle of the high-pressure heater of the power plant has the advantages of integrating area positioning, accurate detection, defect diagnosis and safety assessment.

The invention provides a road unmanned inspection system and inspection method based on multi-modal perception and a large model. The system comprises a vehicle end system used for multi-modal data acquisition, automatic driving control, real-time perception fusion and edge reasoning of a lightweight large model; the cloud platform is used for cross-modal depth identification, disease knowledge base management, GIS visual display, inspection task management and large model training iteration; the scheduling end is used for task issuing, result auditing, and visual interaction of human-aided decision making and road health assessment. On the basis of the three-layer architecture, a large model collaboration framework is further constructed, and the framework runs across a vehicle end, a cloud end and a scheduling end, is responsible for reasoning collaboration, intelligent supplementary shooting, task priority generation, structured report generation and interpretable reasoning chain construction of a multi-mode large model, and is a key mechanism for realizing closed-loop routing inspection of an intelligent collaboration system.

The application discloses a kind of vehicle-mounted unmanned aerial vehicle charge-discharge management system and method, including the full-amount state parameter of acquisition unmanned aerial vehicle, hangar, power supply and environment, constructs system state vector, dynamically calculates charging trigger threshold and judges charging trigger condition, exports charging trigger signal or standby instruction or low-power value guard instruction;Construct reinforcement learning scheduling system and complete charging channel, power level, power supply type Dynamic decision, output optimal charging scheduling instruction;Precise regulation and control to charging voltage, charging current is realized through double closed loop artificial neural network, compensates wireless charging coupling coil offset, exports battery real-time operation data in charging process;Battery health status is analyzed, battery remaining useful life is predicted in combination with battery state parameter collected in whole process, dynamically adjusts charging trigger threshold and optimal charging scheduling instruction.

The invention provides an electric automobile power battery EIS detection device and method in the technical field of electric automobile power battery detection. The device comprises a main control module, a charging module, a battery module, a switching power supply module, an EIS detection module, an insulation detection module, a switch K1 and a switch K2. The charging module, the battery module, the switching power supply module, the main control module and the EIS detection module are connected in sequence; the detection end positive electrode of the insulation detection module is connected with one end of the switch K1 and the detection end positive electrode of the EIS detection module, the detection end negative electrode is connected with one end of the switch K2 and the detection end negative electrode of the EIS detection module, and the control end is connected with the main control module. The method has the advantages that the detection convenience, the field applicability and the equipment integration degree are greatly improved.

The invention discloses a cutting die mechanism, which relates to the technical field of plate processing equipment and comprises a fixing plate, a plurality of cutting heads, a clamping assembly and a detection assembly. The clamping assembly comprises a mounting seat, a driving unit, a sleeve, a push block and an abutting rod; the driving unit drives the sleeve to rotate, the pushing block and the abutting rod move in the axial direction through the lead screw thread pair, and therefore the abutting rod is inserted into or withdrawn from the clamping groove of the tool bit, and automatic locking and quick disassembling of the tool bit are achieved. The detection assembly comprises a movable plate with an inclined face, a stud, a spring and a pressure sensor and is used for monitoring the working state of the tool bit in real time, whether the tool bit is loosened or deflected or not is judged through pressure signal changes, and online fault diagnosis and positioning are achieved. The device has the advantages of being reliable in clamping, convenient to disassemble and replace, capable of monitoring the state and positioning faults, and suitable for high-precision sectional bending machining of long-size plates.

The embodiment of the invention provides a deep peak regulation anti-fatigue control method and system for a solid waste-based phase change heat storage material. The modular heat storage alternating system is constructed, the temperature state of the solid waste-based phase change heat storage material in each heat storage unit is monitored in real time, the real-time fatigue accumulated damage value of the heat storage material is calculated based on the temperature state, and then the fatigue of the heat storage material is calculated according to the damage value and the preset fatigue limit threshold value. And a heat charging and discharging scheduling strategy including load reduction, rotation or quit operation is intelligently executed. Through the synergistic effect of three levels of system architecture, state perception and intelligent decision, the problems of thermal stress accumulation and fatigue damage of the solid waste-based phase change heat storage material under the working conditions of deep peak regulation and frequent start and stop are effectively solved, the operation stability and reliability of the heat storage system are remarkably improved, and the overall service life of the heat storage system is remarkably prolonged; and meanwhile, active management and predictive maintenance of the health state of the material are realized.

The present application relates to a kind of for signal generator production line test calibration implementation guided fault-tolerant processing system, including process guiding module, the test calibration of signal generator whole process is decomposed into several sequentially executed steps;Intelligent fault-tolerant processing module is used for real-time monitoring and intelligent intervention in the whole cycle of operation, pre-judgment input before operation, real-time capture error in operation;State management module, application program and instrument state in test calibration process are automatically saved and breakpoint recovery.Such as the system, method, device, processor and computer readable storage medium thereof for signal generator production line test calibration implementation guided fault-tolerant processing of the present application, significantly reduce training cost and operation error rate, avoid misoperation through step-by-step guidance and embedded help, improve product quality consistency, ensure that the calibration process and standard of each signal generator are completely consistent, reduce the product performance discreteness caused by personnel operation difference.

The system comprises a group control center, a plurality of groups of water chilling units, a plurality of groups of chilled water pumps, a plurality of groups of cooling towers, a plurality of groups of cooling water pumps, a data acquisition module, a data processing module and a control module, the data acquisition module is used for acquiring operation parameters of multiple groups of water chilling units, multiple groups of chilled water pumps, multiple groups of cooling towers and cooling water pumps in real time; and the health degree prediction module is in signal connection with the data acquisition module and is used for receiving the operation parameters of the data acquisition module. Compared with the prior art, the system has the advantages that the health degree loss among similar equipment is balanced through the multi-objective optimization module, premature damage of part of equipment due to long-term high-load operation is avoided, equipment clusters are relatively coordinated, the overall service life is prolonged, in addition, the equipment runs in a high-efficiency interval as much as possible, and the service life is prolonged. And energy waste caused by faults, low-efficiency operation or simultaneous operation of unnecessary equipment is reduced, so that the overall operation energy consumption is reduced.

The present application relates to the technical field of fluid conveying pipeline temperature control, and specifically discloses an intelligent temperature control method and system for electric heating hoses in extremely cold environments, aiming to solve the technical problems of existing temperature field sensing blind spots and the inability of fault diagnosis to distinguish between external working condition interference and hardware failure. First, the hose configuration and real-time operation data are obtained, a temperature field reconstruction model based on boundary condition online identification is constructed to reconstruct the full-length temperature distribution of the hose, then the thermal response feature vector composed of the heating response time, cooling response time and equivalent heat dissipation coefficient of the heating section is extracted and a historical normal value baseline is established, the precise distinction between working conditions and faults is realized based on the feature vector, and finally the adaptive collaborative temperature control is completed in combination with the reconstructed temperature distribution and the diagnosis result. The temperature field sensing blind spots can be eliminated, the fault false alarm rate is reduced, the aging of the heating element can be early warned to realize predictive maintenance, the temperature control strategy can be adapted to environmental changes, and the safe transportation of easily frozen media in extremely cold environments is effectively ensured.

The utility model provides a skeleton dovetail splicing double seal rubber strip composite sealing gasket, including annular skeleton and rubber inner ring. Skeleton is spliced by dovetail tenon groove structure through the only positioning boss groove of a plurality of sections, effectively prevents mistake and saves material greatly. Inner ring is equipped with two sealing lips of main and auxiliary, and the flow guide groove between the lips is communicated with the leakage detection signal hole of skeleton, realizes leakage monitoring. There is no rubber layer in bolt hole position, and torque attenuation is eliminated. The positioning groove with barb of inner wall of skeleton enhances rubber binding force. The utility model integrates the advantages of light weight, low cost, high reliability, mistake proofing and leak detection, and is especially suitable for sealing of industrial equipment under high pressure, high temperature or vibration working condition.

The present application relates to the technical field of industrial water treatment and intelligent control, in particular to a metallurgical wastewater advanced treatment system, comprising a multi-source sensing module, which obtains real-time water quality and hydraulic parameters through a sensor array, and calculates heat load prediction data in combination with production plans; a digital twin engine module, which inputs data into a water quality-thermal energy coupling model, simulates the evolution of the physicochemical properties of water flow, and generates a full-network scaling risk thermodynamic map; an adaptive control module, which analyzes electromagnetic wave modulation instructions based on the thermodynamic map, and generates cascade waterway scheduling instructions; and a field execution module, which dynamically adjusts electronic scale-inhibiting equipment parameters in response to the instructions, and controls valves to reconstruct water supply paths; the present application realizes dynamic matching of water quality and thermal energy through digital twin technology, converts passive chemical cleaning into active scale inhibition by physical fields, and effectively reduces the dependence on chemical reagents.

The application discloses a hot runner injection molding experimental system, comprising an ultrahigh-precision and dynamic response temperature control system, a hot runner structure simulation and heat management system, and an intelligent temperature control and predictive maintenance system; the ultrahigh-precision and dynamic response temperature control system is combined with a nanometer-precision temperature sensor and an intelligent control algorithm to realize millisecond-level temperature fluctuation detection and instant adjustment, and to ensure that the internal temperature of the hot runner system is stably kept in an extremely narrow fluctuation range. Through cooperation of the ultrahigh-precision and dynamic response temperature control system, the hot runner structure simulation and heat management system, and the intelligent temperature control and predictive maintenance system, the application can realize higher-precision and faster-response-speed temperature control, comprehensively optimize the hot runner system by combining advanced simulation technology and material science, solve problems such as large heat loss and uneven temperature, and apply AI technology to the temperature control system to realize automatic monitoring and predictive maintenance.

The present application relates to the technical field of intelligent maintenance of printing equipment, and provides a printing equipment predictive maintenance method based on big data analysis, which comprises the following steps: acquiring paper feeding state data, production process data and environmental data; determining effective micro-delay amount and delay occurrence position based on the difference between the theoretical arrival time and the actual arrival time of paper in the paper feeding path, and making a preliminary judgment on the printing equipment according to the above data to identify normal paper feeding state, abnormal adsorption paper feeding state, abnormal mechanical handover state and uncertain paper feeding state; when being in the uncertain paper feeding state, making a secondary judgment by further combining paper type, paper storage time length and workshop humidity to identify paper moisture absorption abnormal state, dust pollution abnormal state and working condition adaptation abnormal state, and formulating corresponding maintenance strategies. The present application can identify paper feeding abnormalities in advance, improve abnormal identification accuracy and maintenance pertinence, and reduce downtime and maintenance cost.

The invention provides a multi-specification embedded part automatic identification welding and digital management and control system, and relates to the technical field of prefabricated building intelligent manufacturing, the system is based on a visual identification module of an improved YOLOv5 algorithm, through introduction of a size attention mechanism, reinforcing steel bar key size feature extraction is enhanced, thread interference is inhibited, and the accuracy of the system is improved. The accurate identification of the multi-specification similar embedded parts is realized; the weld joint self-adaptive welding module is used for adjusting a welding track and process parameters in real time based on a laser scanning and dynamic path correction technology, and compensating machining deviation; and the full-process digital management and control module integrates digital twin visualization, block chain quality tracing and AGV intelligent scheduling, and is deeply integrated with an MES system. According to the system and the method, automation and intelligentization of the whole process from identification, welding to management and control are achieved, the problems that manual sorting is prone to errors, the welding quality is not stable and data islands exist are solved, and the production quality, efficiency and traceability are remarkably improved.

The utility model discloses an organic waste gas incinerator, it includes incineration subassembly, the incineration subassembly includes furnace body, combustor, turbulence dome, air supplement hole no.

The application discloses an AI prediction type temperature control system for server heat flow dynamic management, which comprises a data acquisition module, an AI prediction and control decision module and a dynamic temperature control execution module, wherein the data acquisition module acquires server load data, environmental temperature data and temperature data of each component of the server in real time. In the application, the AI prediction model is integrated, the server temperature trend can be accurately predicted in advance based on multidimensional real-time data load, environmental temperature and the like, the prediction accuracy reaches ±1°C, the control unit dynamically adjusts the cooling liquid flow and the pump speed in advance according to the prediction, the feedforward control of cooling before heating is realized, the temperature overshoot or repeated oscillation caused by response lag is avoided, the server is ensured to run in a more stable and safe thermal environment, the cooling intensity can be actively reduced when the predicted temperature is safe, the overcooling is avoided at the root, the accurate matching of the cooling capacity and the heat load is realized, and the invalid refrigeration energy consumption is obviously reduced.

The invention discloses a transformer operation state self-diagnosis method and system, and relates to the technical field of state diagnosis, and the method comprises the following steps: obtaining and analyzing related data in a working state according to a test condition, judging the state of a primary side circuit element according to primary side data and an RLC circuit step response time constant formula, and carrying out the self-diagnosis of the operation state of a transformer. And calculating the voltage stability according to the secondary side data, calculating the delay duration of the tap switch and the damage degree of the tap switch according to the primary side data, dividing and outputting state levels, and predicting a first fault time point according to the delay duration and a preset delay duration. By predicting the first fault time point, predictive maintenance is realized, power failure accidents caused by sudden faults are avoided, various data of the primary side and the secondary side are integrated, specific analysis of a circuit model and key parts is combined, a multi-dimensional and systematic diagnosis system is formed, and comprehensive, intelligent and refined management of the operation state of the transformer is realized.

The embodiment of the invention provides a calibration system of an electromagnetic ultrasonic thickness measuring device. In one specific embodiment, the calibration system comprises a multi-dimensional data acquisition assembly, a data forwarding device and a calibration compensation device. The calibration compensation equipment comprises an error compensation module and a dynamic calibration module; the error compensation module obtains the environmental parameters, the stress, the corrosion degree and the real-time ultrasonic echo signals sent by the data forwarding equipment, inputs the environmental parameters, the stress, the corrosion degree and the real-time ultrasonic echo signals into the trained error compensation model to obtain an error compensation coefficient, calculates a real-time thickness measurement value, and performs error compensation on the real-time thickness measurement value based on the error compensation coefficient; the dynamic calibration module obtains the material parameter and the thickness range of the component monitored by the electromagnetic ultrasonic thickness measuring device, obtains a standard ultrasonic echo signal based on the material parameter, the thickness range and the environment parameter, and calibrates the error compensation model based on the error compensation coefficient, the real-time ultrasonic echo signal and the standard ultrasonic echo signal.