15057results about "Pump control" patented technology

The invention relates to the technical field of multi-sensor fusion, in particular to a high-reliability multi-sensor fusion pump station monitoring system and an intelligent early warning control method, and the method comprises the steps: 1, carrying out the synchronous fusion processing of data based on the sampling frequency difference of multi-source heterogeneous sensors, so as to guarantee the consistency of time axes; 2, calculating the consistency difference of the data of each sensor according to the synchronized data, and dynamically shielding an abnormal data source to avoid false alarm interference; 3, real-time operation state modeling is carried out based on the data change trend after dynamic shielding; and 4, accurate early warning and decision optimization are realized. According to the high-reliability multi-sensor fusion pump station monitoring system and the intelligent early warning control method, data synchronous fusion processing is performed based on the sampling frequency difference of the multi-source heterogeneous sensors, so that the consistency of a time axis is ensured, and the problem of influence of asynchronous data on the state judgment accuracy is effectively solved.

The invention discloses a water supply pipe network water hammer control method and system based on multifunctional module fusion, and relates to the technical field of data identification. A time sequence diagram neural network prediction and traceability module which realizes water hammer risk prediction and propagation path traceability based on a causal constraint graph neural network model; the reinforcement learning intervention decision module is used for generating an active intervention strategy through a reinforcement learning agent, forming closed-loop control, abstracting a water supply pipe network into a graph structure, and modeling in combination with a time sequence, so that a propagation path of pressure waves can be comprehensively reflected, a blind area of traditional local modeling is overcome, and the comprehensiveness and accuracy of water hammer event detection are improved; and a causal analysis result is input as an adjacent matrix, so that the interference of irrelevant edges on prediction in topology is effectively eliminated, and the learning efficiency and causal traceability of the model are improved.

The invention discloses a digital twin enabling intelligent pump station preventive operation and maintenance system. Comprising a dynamic twin construction module, a multi-source heterogeneous multi-modal data acquisition module, an edge computing and cloud collaboration module, an equipment health degree evaluation module, a predictive maintenance decision module, a cross-system data fusion module, a self-evolution knowledge graph module, an intelligent diagnosis and early warning module, a self-adaptive maintenance decision module and a man-machine collaboration interaction module. And the dynamic twin construction module comprises a physical-virtual synchronous calibration mechanism and an equipment degradation parameter dynamic updating mechanism. According to the method, the limitation problem of a traditional static model is solved, the method can adapt to nonlinear changes under complex working conditions, the comprehensive judgment and prediction capability of the system on the equipment state can be enhanced, the energy utilization efficiency is improved, the energy consumption is reduced, the decision and verification mechanism is perfected, and the data acquisition and processing problem is improved; the problems of timeliness and flexibility of the model are solved, and the computing architecture and the response capability are optimized.

A portable fan with predictable battery life and a method for predicting battery life thereof. The portable fan includes a fan body, where a circuit board assembly and a storage battery are installed in a shell of the fan body, a microprocessor and a current collector are encapsulated in the circuit board assembly, a load and a display device are provided on the fan body, and the display device includes a function lighting display area and a battery life display area. According to the portable fan, the display device can be used to indicate a working mode that the fan body is currently turned on and the working battery life that the storage battery can provide under the corresponding working mode. An intuitive and standard time unit is used for indication, so that a clear visual perception effect is achieved.

The invention relates to the technical field of water pump energy-saving control, and discloses a water pump energy-saving control system based on an intelligent data model, which comprises a data sensing module, a modal analysis module and the like. The data sensing module collects flow, lift and power data and is provided with a dynamic monitoring window; the modal analysis module divides operation modes and generates an energy efficiency characteristic matrix; the rule construction module extracts a core energy efficiency factor and constructs an energy-saving regulation and control strategy; the priority scheduling module analyzes the control priority matrix and evaluates an energy efficiency deviation index; a mapping calibration module fits the optimal energy efficiency reference curve to generate an energy efficiency deviation gradient map; the control execution module generates a regulation and control instruction set according to the map. The system realizes fine management and energy efficiency optimization of water pump operation through multi-mode energy efficiency analysis and dynamic regulation, solves the problems of poor adaptability of traditional control working conditions, low energy-saving efficiency and the like, is suitable for water pump energy-saving control in the fields of industry, municipal administration and the like, and is accurate and efficient.

The invention relates to the technical field of water pump control, and discloses a water pump energy-saving optimization control method and system. The method comprises the steps of obtaining water pump outlet pressure, pipe network tail end flow and water pump motor power monitoring signals; calculating a flow-pressure propagation time compensation coefficient and a pressure fluctuation compensation value to eliminate the influence of signal propagation lag and amplitude fluctuation; extracting an operation condition feature vector by combining the motor power frequency domain energy distribution feature and the pressure fluctuation compensation value, and matching the operation condition feature vector with an energy-saving parameter mapping rule base to generate an energy-saving parameter combination; correcting a water pump efficiency reference curve in real time based on the combination, outputting an efficiency attenuation factor, and generating a control deviation value in combination with a target water supply demand; according to the control deviation value, the water pump rotating speed adjusting quantity and a start-stop priority sequence are calculated, and the priority sequence is optimized in combination with historical operation data to generate a machine number control instruction; and finally synthesizing a control signal to drive an execution mechanism.

The invention relates to the technical field of industrial equipment health monitoring and fault diagnosis, and discloses a centrifugal pump intelligent detection method and system based on multi-source data. The centrifugal pump intelligent detection method based on the multi-source data comprises the steps that centrifugal pump multi-source heterogeneous data are collected and preprocessed; extracting multi-scale features and constructing an optimal feature subset through hierarchical feature selection; constructing a multi-level dynamic Bayesian network to establish a probabilistic reasoning framework; calculating a feature credibility weight based on the signal quality, the feature stability and the diagnosis correlation; executing multi-source evidence fusion and Bayesian state reasoning; confidence self-calibration and parameter self-adaptive adjustment are realized through historical diagnosis result feedback; the method can effectively cope with the complex and changeable environment of an industrial site, can still keep stable diagnosis performance under the condition that the sensor part loses efficacy or the data quality is uneven, improves the accuracy and reliability of fault diagnosis, and provides powerful technical support for predictive maintenance of industrial equipment.

A pump system includes a housing defining a first internal volume and a second internal volume, a first piston positioned to separate the first internal volume into a first chamber and a second chamber, a second piston positioned to separate the second internal volume into a third chamber and a fourth chamber, a first inlet check valve configured to permit fluid flow into the first chamber, a second inlet check valve configured to permit fluid flow into the third chamber, a directional control valve (DCV) repositionable between (a) a first position where the DCV is configured to fluidly couple the second chamber to a high pressure fluid source and (b) a second position where the DCV is configured to fluidly couple the fourth chamber to the high pressure fluid source, and a relief valve configured to supply a fluid to the DCV through an orifice to move the DCV.

The invention relates to the technical field of monitoring and early warning, and discloses an automatic monitoring and early warning method and system for a pump room. The method comprises the following steps: collecting hydraulic pulsation, cavitation acoustic emission and bearing temperature rise data through multiple sensors; a pump efficiency attenuation vector is obtained based on an environment adaptive algorithm optimization feature; predicting the health state of the equipment by using a hydraulic model; carrying out deep learning classification by adopting a fault propagation network; and four-stage grading early warning is realized by combining water inflow-pump efficiency coupling judgment. According to the method and the device, the technical problem that the gradual change fault and the multi-parameter coupling fault mode of the pump room equipment under the underground complex working condition cannot be accurately identified in the prior art is solved, and the accuracy of fault prediction and the timeliness of early warning of the underground drainage pump room are improved.

The shutdown of a compressor (10) installed in a refrigerant circuit (2) in air conditioning or refrigeration system is controlled so as to prevent unpowered reverse rotation of the compressor. Prior to terminating electric power to the compressor drive motor (24), the pressure within the system is relieved and substantially equalized across the compressor, thereby eliminating the possibility of unpowered reverse rotation of the compressor at shutdown. Pressure relief and equalization may be achieved by reducing the operating speed of the compressor to a low forward speed for a period of time prior to deenergizing the compressor drive motor. Pressure equalization may also be achieved by driving the compressor in reverse rotation prior to deenergizing the drive motor.

The invention relates to a self-adaptive pressure regulation vacuum pump closed-loop control system and method. The system comprises a model building module which is used for acquiring real-time data flow of a vacuum pump and building a nonlinear dynamic model to obtain a pressure-flow-power feature mapping relation; the predictive analysis module calculates a pressure-flow predictive value based on the relationship and compares the pressure-flow predictive value with the real-time power data for analysis. And generating a parameter adjustment instruction once the deviation value exceeds a preset threshold value. And the control scheme generation module corrects the control parameters according to the parameter adjustment instruction and generates an optimized power adjustment scheme. And if the data is abnormal, generating a state update value. And the control scheme updating module fuses the state updating value and the pressure-flow prediction value to obtain an optimized model parameter so as to adjust a weight coefficient of an adaptive control strategy and generate a control scheme. The system effectively improves the accuracy of vacuum pump pressure control, greatly enhances the ability of the system to deal with abnormal conditions and equipment performance changes, and ensures long-term stable operation of the vacuum pump.

The invention relates to the field of mine ventilation, in particular to an intelligent adjusting method and system for mine ventilation. The method comprises the following steps: constructing a dynamic topology model taking a roadway as an edge and taking a fan and an air door as nodes based on a mine CAD drawing; acquiring the actual wind pressure and the actual wind volume of each roadway branch in real time, performing inversion to obtain the current wind resistance, and updating the wind resistance attribute of the edge in the dynamic topology model by using the current wind resistance; calculating the optimal air volume of the roadway branch by using the updated dynamic topology model; based on the optimal air volume, target regulation and control parameters of the draught fan and the air door are obtained through solving by means of a particle swarm algorithm; and according to the target regulation and control parameters, the fan and the air door are adjusted through a fuzzy PID algorithm. The problem that in the prior art, mine ventilation adjustment is not intelligent and safe enough is solved, the theoretical optimal air volume is obtained through deep analysis of the mine, then ventilation adjustment is conducted step by step, and the scientificity and efficiency of ventilation adjustment are improved.

The invention relates to the technical field of mine safety, and discloses a coal mine underground gas monitoring method and system. The method comprises the following steps: acquiring methane absorption intensity data by adopting a tunable diode laser absorption spectrum, converting the methane absorption intensity data into gas concentration based on a Lambert-Beer law, performing temperature and humidity compensation, calculating a transmission priority according to concentration deviation to form a data packet, and establishing a spatial interpolation model by utilizing multipoint data to predict gas concentration distribution. Calculating a risk assessment index based on the predicted distribution, automatically adjusting the rotating speed of the ventilator, and controlling the electrical equipment to be powered off. According to the method, the technical problems of low detection precision, incomplete monitoring coverage, low data transmission efficiency and lack of prediction and early warning capabilities in the existing underground coal mine gas monitoring method are solved. And the accuracy of gas concentration detection and the intelligent level of gas monitoring are improved.

The invention relates to an AI server cooling water pump vibration quantity self-adaptive calibration test method and system, an intelligent test platform integrates a six-dimensional force sensor and a temperature compensation vibration exciter, the platform rigidity is automatically calibrated, a water pump-pipeline system transfer function is obtained, and a rotating speed-lift-modal frequency three-dimensional mathematical model is established; a three-axis MEMS accelerometer array is arranged at sensitive parts such as a water pump bearing seat and a motor shell, and vibration, current and pressure signals are synchronously collected; carrying out time-frequency domain signal processing by adopting variational mode decomposition in combination with self-adaptive S transformation, and extracting a 128-dimensional full-frequency domain feature vector containing a modulation side frequency band; effective values of vibration acceleration, speed and displacement are calculated through a frequency domain integration algorithm, and current harmonic interference is corrected through an electromagnetic vibration compensation model; and finally, a vibration health degree evaluation model containing 18 characteristic parameters is established based on a support vector machine, the test system comprises an intelligent test platform unit, a multi-source sensing unit, an edge calculation unit and a data management unit, and microsecond-level synchronous acquisition and GB-level data throughput are realized through a time sensitive network. And online incremental learning and automatic generation of a test report are supported. The method has the effect of improving the water pump vibration quantity test precision.

The invention relates to the technical field of wind power operation and maintenance technologies, and discloses a combined heat dissipation system of a fan, the system comprises a multi-source sensing module, a decision control module, a heat dissipation execution module and a safety early warning module, and by setting multi-mode cooperative control, when fan heat dissipation regulation and control are carried out, the heat dissipation of the fan can be controlled in a multi-mode cooperative mode; a dynamic matching mechanism of temperature field characteristics and heat dissipation modes is established, and air cooling, liquid cooling and phase change strengthening modes are automatically switched in real time according to the temperature rise rate and the heat distribution gradient, so that the system can accurately adapt to heat dissipation requirements under different working conditions, timely heat dissipation of a high-temperature core area is guaranteed, the heat dissipation response accuracy is improved, and the service life of the system is prolonged. By arranging the three-dimensional thermal field balancing system, the hot area distribution difference of the bearing, the winding and the power module is recognized in real time, the cooling liquid flow and the airflow guide angle are dynamically adjusted, the three-dimensional thermal unbalance phenomenon in a traditional heat dissipation mode is eliminated, and it is guaranteed that the temperature gradient of all areas in the motor is always kept within a safety threshold value.

The invention discloses a slurry pump control method and related equipment, and relates to the technical field of seawater desalination, and the method comprises the following steps: obtaining sensor data of a slurry pump; data analysis is conducted on the sensor data, and the working condition abnormal index of the slurry pump is determined; determining a target control instruction corresponding to the working condition abnormal index based on the working condition abnormal index and a preset threshold interval; and based on the target control instruction, the slurry pump is controlled to execute corresponding target regulation and control operation. Real-time monitoring and intelligent judgment of the operation state of the slurry pump are achieved, early warning can be triggered at the initial stage of equipment abnormity, the operation parameters can be adjusted in a self-adaptive mode, the response delay problem of a traditional single control mode is effectively avoided, and the operation reliability and safety of the equipment are improved.

The invention discloses a fan control method and device, and relates to the technical field of heat dissipation, and the method comprises the steps: partitioning and numbering a hard disk region, enabling each hard disk to correspond to a fan according to a corresponding number, obtaining the obtaining temperature of a hard disk backboard and hard disk information through a master control node or a slave control node, and dynamically calculating fan control parameters, the heat dissipation efficiency of the server is improved, and the problems that in the related technology, the rotating speed of the fan is controlled only depending on the single temperature sensor parameter and the fan parameter, server fan redundancy control cannot be achieved when the node breaks down, and the reliability of the server is poor are solved. The technical problem that the heat dissipation efficiency and flexibility are poor in the prior art is solved, and the technical effect that the heat dissipation efficiency of the double-control high-density server is effectively improved by dynamically adjusting the rotating speed of the fan according to the working state, the read-write rate and the real-time temperature of the hard disk and achieving partition control is achieved.

The invention belongs to the technical field of intelligent control, and particularly relates to a water pump multi-mode intelligent control method based on a PLC. Operation parameters are acquired in real time through a data acquisition module, a target mode is selected from constant-pressure water supply, constant-flow water supply, energy-saving optimization and fault emergency modes through a mode judgment module according to preset triggering conditions, and an operation strategy including a start-stop sequence, a target rotating speed, a frequency converter output frequency and a pressure set value is generated through a strategy generation module. The control execution module converts the strategy into a control instruction and outputs the control instruction to the water pump driving module, and linkage operation and mode switching of the multiple water pumps are achieved in combination with the mode linkage module. And the recording and optimizing module is used for storing and analyzing the operation data and optimizing mode switching conditions and operation strategies. Self-adaptive control and multi-pump cooperative scheduling in multiple modes are achieved, the stability and energy saving performance of a water supply system are improved, and the service life of equipment is prolonged.

The invention relates to the technical field of intelligent gardens and precise irrigation, and particularly discloses an intelligent irrigation monitoring method and system. According to the method, a multi-source sensor array is deployed, Kalman filtering is adopted to fuse environmental data, and a three-dimensional state vector input reinforcement learning model is constructed to generate an irrigation decision; predicting a vegetation water demand by combining a gradient lifting decision tree, forming a graded irrigation strategy and converting the graded irrigation strategy into a water pump control instruction; soil humidity feedback data are collected in real time, decision model parameters and filtering rules are dynamically adjusted, and closed-loop optimization is achieved. Through multi-source data fusion and a self-adaptive decision-making mechanism, the irrigation precision and the water resource utilization rate are remarkably improved, meanwhile, the response capacity of the system to the vegetation growth dynamic state and the environment change is enhanced, and the beneficial effects of optimization process closed loop, decision dynamic adaptation and controllable resource consumption are achieved.

Apparatus and methods are described including a ventricular assist device that includes an impeller configured to be placed inside a left ventricle of a subject. A driving magnet is coupled to a motor and is rotated by the motor. A driven magnet is magnetically coupled to the driving magnet and is rotated by the driving magnet. A drive cable extends from the driven magnet and imparts rotational motion from the driven magnet to the impeller. A set of sensors is configured to detect a magnetic phase difference between the driven magnet and the driving magnet. A computer processor receives the detected magnetic phase difference and determines a physiological parameter of the subject, at least partially in response thereto. Other applications are also described.

The invention belongs to the technical field of highway tunnel ventilation control, and provides a highway tunnel ventilation control method and system. The method comprises the following steps of multi-source heterogeneous data acquisition, multi-source data fusion, state estimation, traffic flow prediction, dynamic pollution index calculation and multi-target weight generation, rolling optimization with constraints, control execution, model updating and feedback correction. The state sensing precision is improved through multi-source data fusion, real-time accurate estimation and error reduction of a pollutant concentration field and a traffic flow state are realized through a heterogeneous sensor and a Rayleigh fusion technology, the problem of sensing deviation caused by single data in a traditional method is solved, future traffic flow is predicted based on a graph neural network, and the traffic flow sensing accuracy is improved. The fan power is optimized through model prediction control, the ventilation intensity is adjusted in advance, pollutants are prevented from exceeding the standard, the response speed is increased compared with threshold value control, and energy consumption is reduced.

The invention discloses a tunnel ventilation control system and method based on artificial intelligence, and relates to the technical field of ventilation control, and the method comprises the steps: in a tunnel design stage, building an unsteady-state computational fluid dynamics model based on tunnel three-dimensional linear parameters, calculating turbulence structures under different traffic conditions through a large eddy simulation method, and calculating an unsteady-state computational fluid dynamics model; determining an optimal space configuration scheme of the fan group according to the distribution of the velocity field and the pressure field; in the tunnel construction stage, multiple types of sensor arrays are arranged along the vault and the side wall of a tunnel in a layered mode; in the tunnel operation stage, real-time vehicle tracks and speed distribution information of a traffic monitoring system are obtained; establishing a ventilation demand dynamic prediction model based on space-time correlation analysis, constructing a fan cooperative control model considering airflow organization optimization, and solving an optimal operation strategy by adopting a multi-target adaptive weight distribution algorithm; when a fire characteristic signal is monitored, the multiple sets of fans are coordinated to form a relay type smoke exhaust airflow organization.

The invention discloses a dynamic blood glucose monitoring and intelligent pump speed adjusting system and method, and relates to the technical field of biomedical engineering.The dynamic blood glucose monitoring and intelligent pump speed adjusting method comprises the steps that precise monitoring is conducted through a multi-mode sensing module, an enzyme electrode sensor adopts an anti-interference coating, a Raman spectrum dynamic correction algorithm is combined, and motion artifacts and temperature drift are restrained; the metabolic feature fusion calibration module is integrated with a time convolution network, time sequence modeling is carried out on diet, exercise and historical blood glucose data, an individualized metabolic parameter database is constructed, and self-adaptive signal drift compensation is achieved; the self-adaptive pump control module innovatively designs a double-layer fuzzy PID controller, a base layer generates an infusion rate according to a real-time blood glucose state and insulin activity, an optimization layer introduces an LSTM metabolism prediction model, and the slope of an infusion curve is dynamically adjusted in combination with future behavior pre-judgment; in the edge-cloud collaborative architecture, a lightweight TCN model is locally deployed to guarantee real-time control, and a cloud end optimizes a global digital twinborn model through federal learning and generates a multi-dimensional metabolic risk early warning report.

The embodiment of the invention discloses a mine gas regulation and control method and device based on multi-modal data and a medium, and relates to the technical field of gas regulation and control, and the method comprises the steps that multi-source real-time sensing data, roadway point cloud data and CFD airflow simulation grid data in a target mine roadway are obtained, space-time alignment is carried out to determine a real-time roadway data cube, and the real-time roadway data cube is obtained; determining gas concentration field distribution and causal contribution popularity data in a preset future time window through a multi-mode depth causal model and the real-time roadway data cube; generating a risk field gradient feature vector based on gas concentration field distribution and causal contribution popularity data, and matching a decision path according to the risk field gradient feature vector; and when the decision path is a causal decision path, a fan / air door adjusting target point is determined, the fan / air door adjusting target point is simulated to determine a dynamic safety constraint boundary, a preset optimization objective function is solved to generate a fan rotating speed adjusting instruction and an air door opening degree control instruction, and fan / air door control is achieved.

The invention relates to the field of pump set control, in particular to a multi-modal pump set dynamic optimization control method and system, and the method comprises the steps: collecting the current waveform, pressure pulsation spectrum and flow time sequence data of each unit of a pump set through a distributed sensor array, and carrying out the time-frequency domain fusion processing to generate an operation state tensor; and inputting a multi-modal identification neural network, and outputting a dominant modal identifier and a modal confidence vector. And according to the modal confidence, activating a basic optimization strategy library or executing cross-modal strategy collaboration, and generating an optimization instruction. And dynamically selecting an instruction conversion path to obtain a frequency converter parameter set, loading the frequency converter parameter set to a programmable logic controller, and driving an execution mechanism to converge a moving track. The method can effectively cope with changes of multi-mode operation states and complex working conditions, and dynamic optimization of the pump set is achieved.

The invention relates to the technical field of pump station energy-saving optimization, in particular to a pump station multi-target energy-saving optimization control method and system for self-calibration of a pump efficiency curve, and the method comprises the following steps: arranging a flowmeter, a pressure sensor and an electric energy metering device at key operation parts of a pump station, and collecting the flow, lift and power operation data of a pump set in real time; calculating pump efficiency characteristic points based on flow, lift and power data collected in real time; the characteristic points are compared with a designed rated pump efficiency curve, and if the deviation of the corresponding efficiency value exceeds a preset threshold value, the pump efficiency curve is corrected through a parameter fitting method so as to obtain a corrected pump efficiency curve reflecting the current working condition. According to the method, the flow, lift and power operation data of the pump set are collected in real time, the pump efficiency characteristic points are calculated and compared with the designed rated pump efficiency curve, the pump efficiency curve is dynamically corrected through a parameter fitting method, and the consistency of the pump efficiency model and the actual working condition is achieved.

The invention relates to the field of energy-saving optimization of variable-frequency fans, in particular to an intelligent energy-saving optimization method and device for a variable-frequency centrifugal fan. The method comprises the following steps: acquiring environmental monitoring parameters in a region, performing dynamic operation scene analysis, performing environmental parameter distribution change mining, and constructing a dynamic scene operation map; obtaining a manual operation log of a historical centrifugal fan, carrying out user use preference mining and equipment response matching, and constructing a personalized fan use behavior portrait; based on the dynamic scene operation map and the personalized fan use behavior portrait, fan use rule mining in the building is carried out, fan operation demand prediction is carried out, and a real-time fan load demand map is generated; real-time operation parameters of the centrifugal fan are collected, principal component dimension reduction analysis and self-adaptive feature coding are carried out, and a fan real-time operation condition matrix is constructed. Fine energy efficiency control is achieved, the energy consumption needed by unit air volume is remarkably reduced, and the energy-saving efficiency of the draught fan and the user experience are improved.

The invention discloses a high-silt-content working condition screw pump control system and method, and belongs to the technical field of soil layer drilling, and the system comprises a multi-mode sensing module, an intelligent decision and control module, a self-adaptive adjustment execution module and a self-cleaning and anti-blocking module. According to the high-mud-content working condition screw pump control system and method, the operation state and medium characteristic data of the screw pump are accurately collected through the multi-mode sensing module, and early prediction and accurate diagnosis of faults are achieved in combination with an advanced data processing algorithm and a deep learning model in the intelligent decision-making and control module; meanwhile, a self-adaptive adjustment execution module and a self-cleaning and anti-blocking module are utilized to dynamically optimize the rotating speed and the gap of the motor and intelligently clean and prevent blocking, so that full-process closed-loop control is formed; finally, multiple beneficial effects of improving the monitoring accuracy, enhancing the anti-interference capability of the system, reducing the maintenance cost, reducing the non-planned downtime, and improving the operation efficiency and stability are achieved.

The invention relates to the technical field of variable frequency speed regulation, in particular to an automatic water pump control strategy and energy efficiency optimization method and system.The method comprises the following steps of obtaining water pump outlet flow data, calculating flow acceleration, determining the pressure gradient direction, matching the hydraulic power trend, calculating frequency instruction deviation and setting the adjustable range; lagging and current rising mark inertia disturbance, power frequency limitation is set, a compensation value is generated, the frequency rate is dynamically adjusted in combination with all factors, and the frequency conversion adjusting priority is generated. According to the method, through matching of the flow acceleration and the pressure gradient, the sensing capacity for dynamic changes of fluid is improved, frequency adjustment of a frequency converter is optimized in combination with frequency deviation calculation, energy consumption increase caused by lag is reduced, and based on correlation analysis of the motor rotating speed change rate and current fluctuation, inertia disturbance accurate recognition is achieved; the voltage compensation timeliness is improved by combining bus voltage dynamic monitoring and a reverse compression strategy, the frequency of the frequency converter is dynamically adjusted by combining multiple parameters, and the response speed and the energy efficiency are improved.

The present invention provides a composite multi-compression mechanism vacuum pump with a high compression ratio and high pumping speed. The multi-compression mechanism includes three types: a turbine, a traction wheel, and a vortex blade array. The traction wheel is divided into a first-stage traction wheel and a second-stage traction wheel. A first-stage exhaust port and a second-stage exhaust port are respectively provided on the base, and a valve is provided on the first-stage exhaust port. In the first pumping stage, the valve is opened, and most of the gas flows through the turbine and the first-stage traction wheel and is discharged from the first-stage exhaust port. A small part of the gas flows through the turbine, the first-stage traction wheel, the second-stage traction wheel, and the vortex blade array in sequence and is discharged from the second-stage exhaust port. In the second pumping stage, the valve is closed, and the gas flows through the turbine, the first-stage traction wheel, the second-stage traction wheel, and the vortex blade array and is discharged from the second-stage exhaust port. The present invention solves the problem that high pumping speed and high vacuum cannot be achieved at the same time and that the molecular pump must be equipped with a pre-stage pump by using multiple compression mechanisms in series. The present invention can replace a traditional set of multiple vacuum pumps with a single vacuum pump, significantly reducing costs.