404results about How to "Improve operating conditions" patented technology

The invention provides an engine internal damage identification method and system based on target detection, and the method comprises the steps: obtaining the distribution of thermal stress and mechanical stress under different working conditions through finite element analysis for typical working conditions of high temperature, high pressure and heat engine coupling load according to the structural characteristics and fault modes of an engine cylinder; processing an ultrasonic guided wave signal through a synthetic aperture focusing algorithm, reconstructing a three-dimensional shape of a crack by combining a three-dimensional geometric model of the cylinder body and guided wave propagation characteristics, and determining a crack propagation rate so as to analyze crack propagation of the cylinder body; the residual service life of the cylinder body under the given working condition is predicted according to the crack size, the crack growth rate and the high-risk working condition parameters in combination with the material mechanical property parameters of the fracture toughness; and according to the crack instability critical length, the cylinder body crack propagation analysis result and the high-risk working condition judgment result, the engine operation working condition is optimized, the occurrence frequency of the high-risk working condition is reduced, the service life of the cylinder body is prolonged, and the crack detection and recognition precision is improved.

The invention belongs to the technical field of power prediction, and discloses a new energy power prediction method and system based on multi-source meteorological data fusion, and the method comprises the steps: obtaining meteorological data from different meteorological data sources in real time or at regular time through a data obtaining module; carrying out preliminary screening and preprocessing on the obtained data by utilizing a data processing module; the data fusion module is used for integrating meteorological data from different sources by adopting an advanced data fusion algorithm to eliminate data redundancy; a mathematical model or a machine learning model suitable for new energy power prediction is constructed by using the prediction model module based on meteorological data of multi-source fusion; and the result output and evaluation module is used for outputting the prediction result to a user in a visual form, and carrying out real-time or regular evaluation on the prediction result. The method has the characteristics of diversified data sources, advanced data fusion technology, flexible prediction model construction, high real-time performance and accuracy, wide application scenarios and the like.

The invention relates to the field of transformer parameter regulation and control, in particular to a parameter optimization method and device for a coupling type transformer. The method comprises the following steps: acquiring multi-dimensional real-time working monitoring parameters and real-time working environment state parameters of the coupling type transformer; performing nonlinear dynamic analysis and global state sensing modeling on the multi-dimensional real-time working monitoring parameters so as to construct a transformer global state sensing model; performing multi-parameter combination definition on the multi-dimensional real-time working monitoring parameters, performing dynamic operation simulation based on a transformer global state sensing model, and collecting operation simulation response data of a plurality of schemes; performing multi-target dynamic balance analysis on the operation simulation response data of the plurality of schemes to obtain an optimal transformer working parameter combination; and carrying out environment dynamic parameter change analysis on the real-time working environment state parameters, and constructing a real-time environment condition distribution field. According to the invention, efficient and self-adaptive adjustment transformer parameter optimization is realized.

The invention relates to a switching power supply control method, system and device and a storage medium, and the method comprises the steps: monitoring the voltage and current of the output end of a switching power supply, and the rate and amplitude of load change, and obtaining the real-time data of the load change; according to the real-time data of the load change, the change of the current load is identified, and a load change mode is obtained; dynamically adjusting operation parameters of the controller according to the load change mode; based on the real-time data of the load change, predicting the load change trend of the switching power supply in real time by using a pre-trained load prediction model to obtain a prediction result, and generating a disturbance compensation signal based on the prediction result; and adjusting the switching state of a switching circuit of the switching power supply according to the control parameter adjusted by the controller and the disturbance compensation signal. The switching power supply has the effect of improving the stability of the switching power supply.

The invention relates to the technical field of fault positioning, in particular to a power wire fault positioning system based on the Internet of Things, which comprises a data collection module, a fault analysis module and a data visualization module, firstly, a data collection module obtains wire data collected by a sensor on a wire in real time; secondly, the fault analysis module is used for carrying out data processing on the wire data to obtain fault data; according to the conductor data and the fault data, constructing a power conductor digital twinborn model; analyzing the fault features and the environmental parameters through a power conductor digital twinborn model to obtain an output result; analyzing the output result through a topology detection algorithm and signal sensitivity adjustment to obtain an optimized output result; obtaining a space-time propagation process formula of the fault signal through signal propagation simulation and space-time analysis according to the output result; evaluating the accuracy of an output result according to a space-time propagation process formula of the fault signal; and finally, the data visualization module generates a visualization chart and an analysis report.

The invention relates to the technical field of equipment state monitoring and control, and discloses an equipment state monitoring distributed control system and method, and the method comprises the steps: collecting the operation parameters of all equipment, and forming a first historical operation data set and a first real-time operation data set; performing cleaning, anomaly detection and feature extraction on the data to generate a feature data set; constructing an equipment parameter association network model; key features related to boiler performance are screened, a historical feature data set is generated, and a boiler performance prediction model is trained; inputting the real-time characteristic data set into a prediction model to obtain a boiler performance parameter prediction value, and comparing the boiler performance parameter prediction value with a preset performance threshold value; when the predicted value is lower than a threshold value, triggering a cooperative control process, calculating optimal operation parameters of desulfurization and denitrification equipment, a fan and an air compressor, and generating an adjustment parameter set; and generating a cooperative control strategy set according to the adjustment parameter set and issuing the cooperative control strategy set to each device for regulation and control. According to the invention, through multi-device collaborative optimization control, the energy efficiency and the operation stability of the system are improved.

The invention discloses an oil pipeline simulation analysis system, relates to the technical field of oil pipelines, and provides accurate data support for subsequent dynamic monitoring and pipeline cleaning decision by constructing a three-dimensional visual model and identifying wax precipitation temperature and deposition risk in time. Through the risk identification module, the system can analyze and calculate the wax precipitation temperature based on the oil product attribute data obtained in real time, and timely judge whether the deposition risk exists in the oil pipeline or not. After receiving a dynamic tracking instruction, the dynamic analysis module can obtain the deposition thickness of each position in a pipeline in real time and analyze the influence of oil temperature and flow velocity changes on deposition distribution, the analysis provides important input data for the pipe cleaning module, the deposition thickness and a heat loss coefficient are fitted through a deep learning technology, and the deposition thickness and the heat loss coefficient are matched with each other. The system may automatically calculate a delivery stability score. When the conveying stability score exceeds a set threshold value, the system can automatically start a pigging measure execution mechanism.

The invention provides an amine low-water-content absorbent for capturing carbon dioxide and application of the amine low-water-content absorbent. The amine low-water absorbent comprises, by mass, 20%-50% of an absorbent main agent, 35%-70% of an auxiliary solvent and 2%-20% of water, and the range of a solvent effect factor delta of the amine low-water absorbent is 0.28-0.32. According to the method, the composition of the water-less absorbent is screened and optimized through a solvent effect factor formula, the amine water-less absorbent which is easy to desorb, low in regeneration energy consumption and low in viscosity characteristic is obtained, and wide application of the amine water-less absorbent in a carbon capture technology is promoted.

The invention discloses an intelligent monitoring system for the running state of a water turbine. The intelligent monitoring system comprises a data acquisition module, a real-time data pushing module, a data storage module, a state evaluation module and a man-machine interaction module. The data acquisition module is used for acquiring vibration, throw, pressure pulsation and key phase information by using various sensors; the real-time data pushing module is used for distinguishing data types and pushing the data through WebSocket and HTTP protocols; the data storage module adopts a Redis and MySQL double-layer framework; the state evaluation module constructs an evaluation index system, determines a weight by using an entropy weight method and an improved analytic hierarchy process, and determines an operation state through deterioration degree analysis and fuzzy comprehensive evaluation; the man-machine interaction module displays monitoring data and evaluation results, provides a real-time monitoring, data query and state evaluation interface, has the advantages of being fast in data updating, convenient to query, visual in display and the like, can comprehensively monitor the operation state of the water turbine, and provides powerful guarantee for safe and efficient operation of a hydropower station.

The invention, which relates to the technical field of the energy storage equipment, discloses a fire multi-stage early warning system for energy storage equipment, and the system comprises the steps: collecting the operation temperature data of a lithium battery pack, generating an operation temperature value, and starting a fire early warning mechanism if the operation temperature value exceeds an operation temperature threshold value; if the abnormal degree of the fire monitoring data of the potential risk area exceeds the expectation, a first-level alarm instruction is sent out and corresponding feedback data is received, if the feedback data is not consistent with the expectation, a second-level alarm instruction is sent out, the existing fire risk is processed, and after a traversal area is identified according to the fire state data, the traversal area is identified. An emergency escape path is planned in the early warning area, and if the emergency escape path does not exist, a third-level alarm instruction is sent out; and if the secondary alarm instruction is not received, the battery pack temperature adjustment knowledge graph is matched with a corresponding processing strategy. The lithium battery pack is maintained in a targeted manner, the running state of the lithium battery pack is improved, and subsequent potential safety hazards and fire risks are reduced.

The invention relates to the technical field of power system control, in particular to an intelligent low-voltage power distribution network interconnection control method and system. The method comprises the following steps: collecting low-distribution voltage network region and node data, and preprocessing the data; a low-voltage power distribution network system is divided into a global optimization layer, a regional coordination layer and an equipment control layer, the global optimization layer generates a global optimization instruction, the regional coordination layer realizes power distribution and voltage regulation in a region through a regional controller, the equipment control layer monitors node operation state information in real time and feeds back the information, and the node operation state information is determined based on a state detection result. And making a control strategy. Through the intelligent control and optimization technology, the real-time monitoring and dynamic adjustment of the power distribution network are realized, and the efficient and stable operation of the power grid is ensured. The multi-level control architecture is adopted, the power grid is finely managed on different levels, and the overall performance of the system is improved. The operation efficiency and reliability of a power grid are improved, and the requirements of a modern power system are met.

The invention provides a data acquisition and monitoring analysis system based on an MES platform, and relates to an industrial software application system. Comprising a low-code development module, a factory modeling module, a monitoring module and a data acquisition module, the low-code development module realizes cross-device linkage development and control program generation through combination of a dragging interface and a device API library in an MES platform integration environment, and guarantees efficient communication control of the device, the factory modeling module integrates two production modes, and the monitoring module is connected with the monitoring module. The monitoring module is used for realizing dynamic modeling and optimizing a production process according to multi-dimensional parameters, the monitoring module is used for realizing ultra-low-delay transmission processing and real-time monitoring of data under high concurrency by applying a dual-cache and message middleware mechanism, and the data acquisition module is used for realizing real-time monitoring of the data based on a machine learning algorithm and a complex event processing technology. Dynamically adjusting the acquisition frequency precision based on the production state; the system aims at improving the efficiency, quality and management level of industrial production, and has wide application prospects and important industrial software application value.

The invention relates to the technical field of battery energy storage system evaluation, and relates to the technical field of battery energy storage, in particular to a method for balancing the service life and performance of a fuel cell, which comprises the following steps of: 1, acquiring multi-source data of the fuel cell, and applying a series of preset pulse current load sequences to the fuel cell, measuring response parameters output by the fuel cell in real time; 2, Fourier transform processing is carried out on the response parameters, and frequency domain signals of the response parameters are obtained; the performance and service life balance model is constructed based on the fusion feature vector containing the dynamic performance, the service life characteristic and the operation state of the fuel cell, the load distribution weight can be dynamically adjusted, the performance and the service life of the single fuel cell are kept balanced, and therefore the overall service life of the fuel cell pack is prolonged, and the reliability of the fuel cell pack is improved. And the influence on the performance of the whole system due to overload or too fast loss of the single fuel cell is avoided.

The present invention discloses a sealing device of a rotary kiln and a rotary kiln, the sealing device comprises a moving ring and a stationary ring arranged between a cylinder and a kiln cover, the two are in contact with each other and rotate relatively to form a spherical-conical end face sealing pair, the moving ring is fixed on the cylinder on the side away from the stationary ring, the stationary ring is elastically and sealedly connected to the kiln cover through a compensator, and the stationary ring is connected to an axial force component on the circular ring end face close to the kiln cover. The rotary kiln comprises the above-mentioned sealing device. The sealing device of the present invention, under the joint action of the moving ring, the stationary ring, the compensator, the rotating pair, the sliding pair and the axial force component, can realize the continuous and effective sealing of the cylinder and the kiln cover of the rotary kiln, has the advantages of simple structure, convenient use, good adaptability, high reliability, good sealing effect, long service life, etc., can be widely used in equipment such as rotary kilns, and has important promoting significance for effectively improving the sealing effect of rotary kilns and promoting the widespread use of rotary kilns.

The invention relates to the technical field of explosion-proof display screens, in particular to a refreshing method and system for an explosion-proof display screen. The method comprises the following steps of collecting state parameters and basic parameters of the explosion-proof display screen, performing state feature extraction and screen feature analysis to obtain a state feature set, self-luminous characteristic data and a pixel unit group set, performing simulation screen reconstruction on pixel groups based on the self-luminous characteristic data, generating a simulation explosion-proof display screen model, and performing simulation display screen reconstruction on the explosion-proof display screen. Performing regional heat accumulation effect simulation on the simulation model to obtain simulated heat accumulation data, calculating a screen heat accumulation safety threshold value, evaluating a block buffer demand based on the heat accumulation threshold value and the simulated data, generating partition buffer demand data, formulating a buffer refreshing plan according to the data, obtaining a time zone buffer strategy, and updating the time zone buffer strategy. And generating refresh time sequence data by using a time zone buffer strategy, and performing segmented refresh control on the pixel group. According to the invention, a safer and more reliable explosion-proof display screen refreshing method is realized.

The invention discloses an outlet design method for improving vertical shaft outflow and a water inlet and outlet structure based on the outlet design method, and belongs to the technical field of hydraulic engineering. The water inlet and outlet structure comprises a water flow channel, the water flow channel is provided with a vertical section, a water inlet and outlet is formed in the upper end of the vertical section, and flow dividing components are evenly distributed around the water inlet and outlet; the device is characterized in that the upper portion of the flow dividing component is arranged on the periphery above the water inlet and outlet to form a cylindrical retaining wall of a stopping structure, and the upper edge of the cylindrical retaining wall is higher than the dead water level of a reservoir area of the pumped storage power station. According to the vertical shaft type water inlet and outlet structure, the water flow uniformity, flow distribution and trash rack flow velocity distribution are remarkably improved by introducing the buffer water body and optimizing the design, the reverse flow velocity problem is thoroughly eliminated, the operation safety of a power station is improved, the service life of equipment is prolonged, and economic benefits are increased.

The invention provides a waste heat recovery device, and relates to the field of flue gas waste heat recovery, a plurality of connecting plates are fixedly connected in a recovery shell, the plurality of connecting plates are arranged up and down in rows, the connecting plates are communicated with heat exchange pipes, and the heat exchange pipes are arranged on the upper and lower rows of connecting plates in a penetrating manner; the multiple wind shields are rotationally connected to the connecting plate, and the multiple wind shields are evenly distributed on the side of the heat exchange pipe; the rotating mechanism is used for adjusting the rotating angle of the wind shield; the cleaning scraping ring is connected to the heat exchange tube in a sliding manner and is used for cleaning the outer surface of the heat exchange tube; and the upward moving motor is fixedly connected to the recycling shell, a connecting block is fixedly connected to the middle position of the cleaning scraping ring, a reciprocating lead screw is fixedly connected to an output shaft of the upward moving motor, and the connecting block is slidably connected with the reciprocating lead screw. The surface of the heat exchange tube can be cleaned under the non-stop condition.

The invention discloses a converter station energy efficiency prediction system based on deep learning, and the system comprises the steps: S1, collecting the data of all equipment in a converter station, and generating an original data set; s2, processing the original data set to generate a standardized data set; s3, constructing an equipment network diagram based on the topological relation of the converter station equipment; s4, the graph neural network module constructs a graph neural network model based on the equipment network graph, extracts feature information of nodes and edges, and generates a multi-dimensional embedded vector; s5, the meta learning module updates model parameters by adopting a hierarchical optimization strategy based on the multi-dimensional embedded vector generated by the graph neural network module, and generates a model parameter set capable of adapting to different input feature distributions; and S6, based on the model parameter set generated by the meta learning module, predicting the energy efficiency related indexes of the converter station. The method has the advantages of strong modeling capability, high prediction precision, strong adaptability and good real-time performance.

The invention discloses an intelligent adjustment power plant combustor and an adjustment method thereof, and relates to the technical field of power plant combustors, and the combustor comprises a combustion assembly, a flue gas circulation assembly, a gas inlet adjustment assembly, a fuel gas supply assembly, a control system and a monitoring module. The controller controls the opening degree of related parts according to fuel, air volume and nitrogen oxide monitoring data, combustion optimization is achieved, and nitrogen oxide emission is reduced. The adjustment method comprises the steps of data setting, starting, ignition, operation adjustment, shutdown and fault processing. The combustor can accurately control all parameters, improve combustion efficiency, enhance safety and reliability, flexibly cope with working condition changes, effectively solve the problems that a traditional combustor is high in nitrogen oxide emission, unstable in combustion and the like, is suitable for the fields such as power plants needing efficient and clean combustion, and has remarkable environmental protection and economic benefits.

The present invention belongs to the technical field of operation monitoring and control of sewage treatment coarse screen equipment, and relates to an operation monitoring and control system for sewage treatment coarse screen equipment. The present invention helps to timely discover and solve abnormal or inefficient problems in the operation of sewage treatment coarse screen equipment by analyzing the operation feedback index of sewage treatment coarse screen equipment, ensuring that the sewage treatment coarse screen equipment is always in the best working state, and helps to timely discover and remove debris on the sewage treatment coarse screen equipment by analyzing the cleaning feedback index of the sewage treatment coarse screen equipment, reducing the impact and wear of the debris on the sewage treatment coarse screen equipment, which is conducive to extending the service life of the equipment, and by analyzing the cleaning effect of the front and rear water bodies of the sewage treatment coarse screen equipment, it is conducive to targeted equipment maintenance and adjustment of equipment with unqualified cleaning effects, ensuring that the cleaning effect of the front and rear water bodies of the coarse screen equipment meets the standards, and reducing the degree of pollution to the environment.

The invention provides a self-adaptive tuning method for generating pulse-driven alternating-current quantum voltage, and aims to solve the problem that it is difficult to determine an optimal parameter combination in the quantum voltage generation process to achieve quantum working margin maximization. According to the method, a plurality of parameters are optimized through an automatic search algorithm, after optimization is completed, triangular waves are superposed at the bias end of a chip, and the working margin of pulse-driven alternating current quantum voltage is measured and evaluated, so that the optimal parameter setting capable of maximizing the working margin is determined. According to the method, the optimal system performance and stability can be provided in practical application, accurate control and optimization of the system performance are ensured through systematic data acquisition and analysis, and the optimal operation condition in a complex working environment is realized.

The invention discloses a heat storage tank-containing heat supply system scheduling method considering heat storage and release role changes, which comprises the following steps of: additionally arranging a heat storage tank in a primary network urban area between an original urban heat supply system pressure separation station and each heating station, and adjusting a supply-demand imbalance operation condition into a supply-demand balance operation condition through the heat storage tank, the urban heat supply system containing the heat storage tank is formed; setting a heat storage tank role change mechanism; based on the corrected heat supply network hydraulic working condition calculation model and a heat storage tank role change mechanism, combining heat load demand change of each heating station and supply and demand imbalance operation working condition identification information, and analyzing the influence on the heat supply network hydraulic working condition during heat supply network flow distribution and heat storage and release of a heat storage tank; the flow of the heat supply network pressure separation station side, the heat storage tank and each heating station in each time period is distributed; correspondingly communicated water pumps and valves are regulated and controlled; and flow distribution and evaluation of regulation and control effects of the water pump and the valve are performed.

The utility model relates to a centrally-mounted motor transmission system and a centrally-mounted motor, the centrally-mounted motor transmission system comprises a center shaft structure, a motor assembly and a speed reduction assembly, and the speed reduction assembly is arranged between the motor assembly and the center shaft structure; wherein an output gear is arranged on the middle shaft structure, a first clutch is arranged between the output gear and the middle shaft structure, a second clutch is arranged in the speed reduction assembly, and the first clutch is configured to transmit power to the output gear in a one-way mode from the middle shaft; the second clutch is configured to perform one-way transmission of power from the motor assembly to the middle shaft structure; in the power-assisted mode and the full-automatic mode, the motor drives the crank to rotate, so that discomfort to a rider is avoided; and the specific mounting positions of the first clutch and the second clutch are favorable for improving the compactness of the structure and improving the bearing moment, so that the running state between the clutch and the corresponding connecting structure is better.

The invention belongs to an agent optimization method, and the method comprises the steps: constructing a virtual power system, constructing a knowledge graph based on the text data of a power distribution network, selecting an agent evaluation index, setting an agent test scene in the virtual power system, and testing the intelligent level of an agent in the agent test scene. And on the basis of the intelligent level of the intelligent agent obtained by testing, continuously iteratively optimizing the hyper-parameter of the intelligent agent, and finally obtaining the intelligent agent with the highest intelligent level as the optimal intelligent agent. According to the priori knowledge guidance-based intelligent agent optimal evolution method, intelligent levels of different intelligent agents can be evaluated by utilizing a constructed intelligent quantitative evaluation index system, the intelligent agent with the highest intelligent level and the best power grid regulation and control capability is selected, the intelligent level of the intelligent agents is improved by adjusting hyper-parameters of the intelligent agents, and the optimal power grid regulation and control capability of the intelligent agents is improved. The corresponding power grid operation state is improved, and the priori knowledge guidance-based intelligent agent optimal evolution is realized.

The invention discloses a thermostatic equipment control system based on an electronic expansion valve and electronic equipment, and aims to solve the problems that in the prior art, an inverter compressor is high in cost, and other schemes cannot accurately control heating power. The constant temperature equipment comprises a circulation pipeline formed by sequentially connecting an evaporator, a fixed frequency compressor and a condenser in series and two electronic expansion valves, one electronic expansion valve serves as a refrigeration electronic expansion valve and is located on a pipeline between an outlet of the condenser and an inlet of the evaporator, and the other electronic expansion valve serves as a hot gas bypass electronic expansion valve and is located on a pipeline between an outlet of the condenser and an inlet of the evaporator. The condenser is integrally connected with the refrigeration electronic expansion valve in parallel; the control system comprises a first PID (Proportion Integration Differentiation) controller, a second PID controller and a third PID controller; the opening degree of the hot gas bypass electronic expansion valve and the opening degree of the refrigeration electronic expansion valve are determined based on the PIDValue 1, the PIDValue 2 and the PIDValue 3 output by the control system, and control over the constant temperature system is achieved.

The invention discloses a solid-liquid separation method for low-odor water-soaked manure, which specifically comprises the following steps: acting on water-soaked manure with the water content of 80-99.9% by adopting an electrode plate with conductive and filtering effects, enabling charged large particles in the water-soaked manure to do directional movement towards one side under the action of an electric field, filtering and recovering a liquid phase through the electrode plate, and recycling the liquid phase through the electrode plate. Therefore, fine particulate matters with the particle size of more than 0.1 mu m in the blistered manure are efficiently separated in a low-odor manner; according to the method and the device disclosed by the invention, the fine particulate matters in the blister dung can be efficiently separated, the odor emission content in the treatment process is low, the content of separated liquid-phase pollutants is also greatly reduced, and the removal rates of COD, TP, ammonia nitrogen and turbidity are 75%, 80%, 20% and 90% or above.

The present invention proposes a valve control method and system based on the Internet of Things. It is characterized in that the method includes: installing a sensor at the pipeline valve, collecting pipeline-related data through the sensor, and transmitting the collected data to the edge device, and pre-processing the relevant data through the edge device; transmitting the relevant data pre-processed by the edge device to the cloud, the cloud stores the relevant data in segments, and analyzes and processes the relevant data in each segment through parallel processing to obtain analysis results; comparing the analysis results with preset thresholds, and formulating corresponding control plans based on the comparison results; and transmitting the control plan to the valve controller through the Internet of Things. By installing sensors at pipeline valves, performing preliminary processing through edge devices, and transmitting data to the cloud for processing through Internet of Things technology, the processing speed can be improved and the computing pressure on the cloud can be reduced.

The invention discloses a machine room intelligent environment monitoring and automatic adjusting method and device and a medium, and the method comprises the steps: dividing a target machine room into a plurality of adjusting units under different environment dimensions according to the environment adjusting device in the target machine room; acquiring machine room equipment information in all the adjusting units; determining optimal environment parameters of the adjusting unit according to the machine room equipment information; obtaining current environment parameters in the adjusting units, comparing the optimal environment parameters with the current environment parameters, and determining a plurality of target adjusting units; according to the machine room equipment priorities in the multiple target adjusting units, the adjusting sequence of the multiple target adjusting units is determined; and environment adjusting equipment in the multiple target adjusting units is controlled, and the environment of the target machine room is adjusted. Based on an analysis result, the working states of environment control equipment such as an air conditioner, a humidifier and an air purifier can be automatically adjusted, dynamic balance and optimization of environment parameters are achieved, and it is ensured that the machine room is always in the optimal operation condition.

The invention relates to a radio frequency device, a radio frequency system and communication equipment. The radio frequency device is provided with a first transmitting port, a second transmitting port, a tuning control port, a first antenna port used for being connected with a first antenna, and a second antenna port used for being connected with a second antenna. In the radio frequency device, a first transmitting circuit and a second transmitting circuit amplify a radio frequency signal to be transmitted, and a gating-based tuning circuit is correspondingly connected with the output end of the first transmitting circuit, the output end of the second transmitting circuit, a tuning control port, a first antenna port and a second antenna port. And the gating tuning circuit selects to transmit the radio frequency signal output by the first transmitting circuit or the second transmitting circuit through a target antenna connected with the target antenna port, and changes the tuning parameter of the gating tuning circuit according to the received tuning signal, so as to adjust the impedance position of the target antenna connected with the target antenna port. Miniaturization design and energy consumption control are considered, and the overall communication performance is improved.

The invention relates to a radio frequency system, communication equipment, an impedance adjusting method and a readable storage medium, the radio frequency system comprises a power amplification circuit, a power detection circuit, a tuning circuit and a processing circuit, the power detection circuit is used for coupling radio frequency signals and outputting forward coupling signals and reverse coupling signals; the processing circuit is configured to determine reflection characteristic parameters of the transmitting path according to the forward coupling signal and the reverse coupling signal; determining a real-time impedance position according to the reflection characteristic parameters and the initial impedance position of the load in the Smith chart; wherein the initial impedance position is related to the frequency band of the radio frequency signal; tuning parameters of the tuning circuit are adjusted according to the real-time impedance position and the target impedance position, so that the distance between the adjusted real-time impedance position and the target impedance position is smaller than the distance between the real-time impedance position and the target impedance position before adjustment. The radio frequency system can be adaptively adjusted in each operation scene, and the overall performance of the communication equipment is ensured.