4597results about "Pump testing" 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 provides a compressor control method and system. The method belongs to the technical field of compressor control, and comprises the following steps: collecting multi-dimensional data in the operation process of a compressor in real time through a multi-parameter sensor network; preprocessing the collected multi-dimensional data, and constructing a data set; learning and optimizing a compressor control strategy based on historical data and a current environment state through a reinforcement learning model based on a deep neural network; continuous iterative updating is carried out through analog simulation and online learning; and on the basis of the adaptive neural network model, the running state and performance parameters of the compressor in a future period of time are predicted in real time, and the network structure and parameters are dynamically adjusted according to the current working condition and historical data of the compressor. Multi-dimensional data in the operation process of the compressor are collected in real time through a multi-parameter sensor network. The data are preprocessed, including denoising, missing value filling, abnormal value detection and the like, so that the data quality is ensured.

The invention provides a water pump residual life prediction method based on a large model, and the method comprises the following steps: S1, collecting the multi-source heterogeneous data of the operation of a water pump in real time through a vibration sensor, a temperature sensor, a pressure sensor and a monitoring unit, the temperature sensor monitors temperature gradient changes of the bearing and the sealing cavity, the pressure sensor records inlet and outlet pressure fluctuation characteristics, and the monitoring unit extracts three-phase current harmonic components of the motor; s2, carrying out lightweight preprocessing on the multi-source heterogeneous original sensing data at an edge computing node, wherein the lightweight preprocessing comprises vibration signal noise reduction processing based on wavelet transform, temperature and pressure data calibration normalization of load segments according to working conditions, and transient abnormal data flow filtering through a sliding time window; and S3, inputting the preprocessed data stream into a cloud large model platform, and analyzing the long-period dependency relationship of the vibration signals through a Transform encoder in a time sequence feature extraction module.

The invention relates to the technical field of fault data processing, and provides a reciprocating natural gas compressor fault diagnosis system which comprises a data acquisition module, a data preprocessing module, a feature extraction module, a knowledge graph construction module, a fault analysis module, a maintenance decision module, an early warning module and a man-machine interaction module. The data acquisition module is used for acquiring operation parameters and historical data of the compressor in real time and transmitting the operation parameters and the historical data to the data preprocessing module; the preprocessing module is used for filtering, denoising and normalizing the data; the feature extraction module extracts fault features; the knowledge graph construction module establishes a relation graph of compressor faults, symptoms, reasons and maintenance measures according to historical data. The fault analysis module performs fault diagnosis, prediction and severity evaluation through a deep learning model; the maintenance decision module matches maintenance measures according to the analysis result and generates a plan; the early warning module generates early warning information when the condition is triggered; and the man-machine interaction module supports graph editing and maintenance.

The invention provides a digital hydraulic pump test bed and a digital hydraulic pump control performance verification method. The invention provides a digital hydraulic pump test bed. The digital hydraulic pump test bed comprises a driving module and a loading module, wherein the driving module comprises a tested hydraulic pump, a direct-current adjustable-speed motor, a plurality of couplings and a shock absorber, one ends of the couplings are connected with the tested hydraulic pump, the other ends of the couplings are connected with the direct-current adjustable-speed motor, the shock absorber is connected with the direct-current adjustable-speed motor, and the sensors are installed on the tested hydraulic pump; a plurality of pressure oil ports of the tested hydraulic pump are connected with the loading module, the loading module comprises a bridge loop and a loading loop, the plurality of pressure oil ports are respectively connected with a first series connection point and a second series connection point of the bridge loop, and a parallel connection point of the bridge loop is connected to the loading loop. The digital hydraulic pump test bed and the digital hydraulic pump control performance verification method are used for verifying the key control performance of the digital hydraulic pump and are wide in application range.

The invention discloses an industrial cloud platform compressor air system management and control system based on an Internet of Things gateway. The data acquisition unit acquires operation data of the compressor through a sensor, and transmits the operation data to the Internet of Things gateway unit after preprocessing the operation data. And the Internet of Things gateway unit performs end-to-end encryption processing, equipment identity verification and dynamic access control on the data. And after receiving and decrypting the data, the industrial cloud platform digital twin unit constructs and updates a digital twin model based on real-time data, extracts key performance indexes by using a stream computing technology, and stores the key performance indexes in a time sequence database to support analysis and optimization. And the intelligent diagnosis optimization unit performs fault diagnosis in combination with the key performance indexes and high-order spectrum analysis, and optimizes operation parameters of the compressor through a reinforcement learning algorithm. The distributed autonomous control unit adjusts a real-time operation state based on optimization parameters, realizes load adaptive balance and energy efficiency optimization, starts a local autonomous control strategy when communication is interrupted, and ensures safe and efficient operation of the system.

The invention relates to the technical field of vibration monitoring, in particular to a slurry pump motion monitoring management system based on data analysis, which comprises a multi-source acquisition module, a period judgment module, a trend focusing module and a dynamic management and control module. According to the method, vibration data are collected through a three-axis acceleration sensor, a fundamental frequency amplitude is extracted through FFT, time-frequency characteristics and periodic distribution are fused in combination with an extreme value interval sequence, the data representation dimension is enhanced, the rising slope is processed through moving average, the periodic variation is calculated, random noise is restrained, and trend continuity is enhanced. Monotonicity test is combined with dynamic threshold judgment to improve anomaly recognition sensitivity; a sliding window is used for segmenting multi-cycle data; a sudden change interval is positioned based on a pressure amplification rate second derivative; the limitation of a frequency domain on transient feature recognition is broken through, a pressure amplification rate three-dimensional vector is constructed, cosine similarity is calculated, and a working condition difference degree is quantified to dynamically bind a maintenance instruction; and closed-loop feedback is formed to improve the early warning and decision matching degree.

The invention relates to the technical field of fault monitoring, and discloses a pump unit fault monitoring method based on multi-dimensional perception fusion identification, and the method comprises the steps: obtaining the operation stage information of a key monitoring region, and determining a fault monitoring threshold value of a to-be-monitored pump unit based on the operation stage information; analyzing the historical operation record, judging whether the fault monitoring threshold needs to be optimized or not based on an analysis result, if so, setting an optimization coefficient corresponding to the fault monitoring threshold, and obtaining an optimized fault monitoring threshold; analyzing the abnormal working condition data, judging whether the optimized fault monitoring threshold needs to be compensated or not based on an analysis result, if so, calculating an abnormal working condition influence index of the abnormal working condition data, setting a compensation coefficient of the optimized fault monitoring threshold based on the abnormal working condition influence index, and obtaining a compensation fault monitoring threshold; and determining the fault early warning level of the pump unit to be monitored according to the compensation fault monitoring threshold value. According to the invention, the monitoring accuracy and effectiveness are ensured.

The invention provides an intelligent pump room real-time monitoring and data analysis method and system and a medium. The method comprises the following steps: extracting water pump operation characteristic data, motor operation characteristic data and valve operation characteristic data corresponding to a plurality of monitoring time points, processing according to the water pump operation characteristic data to obtain a water pump performance reliability index, processing according to the motor operation characteristic data to obtain a motor state stability index, processing according to the water pump operation characteristic data and the valve operation characteristic data to obtain a water pump adjustment sensitivity index, obtaining environment characteristic data of an area where the target pump room is located, and processing to obtain an environment interference suppression degree index; processing is conducted by combining the water pump performance reliability index, the motor state stability index and the water pump adjusting sensitivity index, the equipment operation effect index of the target pump house is obtained, the target pump house is correspondingly adjusted and maintained, and therefore the technology of real-time monitoring and data analysis of the intelligent pump house is achieved.

The invention discloses a method for monitoring abnormal working conditions of a draining pump and an outlet pipeline thereof based on sound recognition, and the method comprises the steps: collecting voiceprint recognition related data, including relay operation signals, infrared temperature measurement image data, humidity data and audio data; the collected voiceprint recognition related data is transmitted to a cloud data platform of a server through a data line, and feature value extraction is performed on the audio data through a voiceprint feature value data edge calculation gateway of the cloud data platform; performing voiceprint data processing on the audio data through a voiceprint recognition algorithm; carrying out comprehensive fault judgment; the method solves the problems of low efficiency and insufficient accuracy caused by manual monitoring and recognition of the abnormality of the draining pump in the prior art, and has the characteristics of being capable of performing comprehensive fault judgment through combination of multi-modal data and voiceprint scoring, and greatly improving the recognition rate and accuracy of abnormality or fault judgment of the draining pump.

The invention provides a hydraulic pump multi-working-condition fault identification method and device, and belongs to the field of hydraulic pump fault detection. The method comprises the following steps: acquiring monitoring data of the hydraulic pump in different operation states; extracting features of the monitoring data under each working condition to obtain feature distribution of the monitoring signals under each working condition; determining sensitive features based on the feature distribution; determining an irrelevant first feature set and a relevant second feature set based on the sensitive features; constructing a first fault diagnosis model according to the first feature set, and identifying a corresponding fault; determining a current working condition according to the second feature set, matching a corresponding second fault diagnosis model based on the determined working condition, and inputting the second feature set into the second fault diagnosis model for fault recognition; and fusing the identification result of the first feature set and the identification result of the second feature set to obtain a comprehensive fault diagnosis result. The hydraulic pump multi-working-condition fault identification method and device can adapt to hydraulic pump fault diagnosis scenes under working condition changes, and the diagnosis precision is improved.

The invention relates to the technical field of compressor control, and particularly discloses a method for controlling a green hydrogen compressor, which comprises the steps of data monitoring and acquisition, basic operation state analysis, mechanical characteristic state analysis, equipment electrical state analysis, sealing lossless state analysis and fault early warning and control optimization. Sealing lossless state coefficients are calculated according to parameters such as dynamic pressure difference, hydrogen dynamic leakage rate, part internal defect area, depth and total crack length at a sealing position and are compared with a reasonable range, so that the states of the compressor in the aspects of sealing performance and part integrity can be accurately judged, the problems of sealing failure and part internal defects can be found in time, and the reliability of the compressor is improved. Treatment such as sealing element replacement can be performed in a targeted manner, and stable operation is guaranteed; and finally, aiming at different conditions of overhigh compression thermal state coefficient, abnormal mechanical acoustic state coefficient and the like, measures of adjusting a pre-cooling device, adjusting the rotating speed of a compressor, adjusting a balance block and the like are respectively adopted, so that faults can be effectively handled, and the correlation coefficient is recovered to be normal.

The invention discloses an immersed server operation control method and system, and relates to the technical field of immersed cooling, and the method comprises the steps: judging whether a liquid level is higher than a preset starting liquid level, and activating a cooling liquid circulation system to confirm liquid flow; the liquid inlet speed of the cooling liquid is optimized according to feedback of the flow velocity sensor, and the stable state of the liquid level in the server cabinet is monitored; whether cooling liquid leaks or not is judged based on liquid level acceleration and flow velocity deviation, when the liquid level is insufficient, an alarm is triggered, and the liquid level and circulation time are automatically adjusted. According to the method, the automation level and the operation safety of the system are improved, sufficient supply of the cooling liquid under the high-load condition of the server is ensured, the downtime caused by leakage of the cooling liquid is shortened, the long-term operation cost of the system is reduced through timely maintenance notification, and the service life of the system is prolonged by automatically adjusting the liquid level and the circulation time. And quick recovery of the system when leakage occurs is ensured, so that the reliability and the fault recovery capability of the system are improved.

The invention discloses a compressor performance testing device capable of rapidly stabilizing working conditions, and relates to the technical field of compressor performance testing. The system comprises a test device and a test system in communication control connection with the test device, and the test device comprises an oil separation assembly and a refrigerant assembly; the oil separation assembly comprises an oil component, the oil component is connected with an oil flow meter and a gas path total flow meter through a tee joint, and the other end of the oil flow meter is connected with an oil cooler in series through an oil path pipeline. Through the arrangement of the refrigerant assembly, when a high-temperature and high-pressure gaseous refrigerant is discharged from the outlet of the tested compressor, one part of the high-temperature and high-pressure refrigerant is directly poured into the mixing box through the tee joint, and the other part of the high-temperature and high-pressure refrigerant is condensed by the condenser to become a liquid low-temperature and high-pressure refrigerant to enter the mixing box; the liquid refrigerant and the gas refrigerant are mixed, and the mixing proportion can be adjusted through the two adjusting valves respectively, so that the requirements of test working conditions are met.

The invention relates to the technical field of variable-frequency water pump control, in particular to a variable-frequency water pump self-adaptive control method and system.The method comprises the steps that motor parameters of a variable-frequency water pump are collected, and whether the motor parameters meet preset starting threshold conditions at the same time or not is judged; under the condition that the starting condition of the motor is met, sensing information of all sensors on the variable frequency water pump is collected; the collected motor parameters and sensing information are preprocessed, filtered and denoised, and key information is extracted; calculating a motor state analysis result based on the processed motor parameters and sensing information, and performing fault diagnosis and prediction to obtain a motor state analysis result; and according to the motor state analysis result, the output voltage, frequency and phase of the frequency converter are dynamically adjusted to optimize the operation efficiency and stability of the water pump. The operation state of the water pump motor is monitored and analyzed in real time, accurate calculation and evaluation are combined, the output parameters of the frequency converter are dynamically adjusted, and efficient and stable operation of the water pump is achieved.

The invention discloses a plunger pump fault diagnosis method and device, a medium and equipment. The method comprises the following steps: acquiring a pressure signal and an original vibration signal of the plunger pump; acquiring data in different states; obtaining frequency domain information based on continuous wavelet transform; performing multi-source data fusion; acquiring a global dependency relationship between the input and the output based on an encoder; and the fault of the plunger pump is diagnosed. By introducing a multi-source data fusion method, time domain and frequency domain signals collected by different types of sensors are comprehensively processed, so that information of different data sources is effectively integrated, and the accuracy and comprehensiveness of fault diagnosis are improved; important features in fault signals are automatically recognized and weighted through the Transform model, the extraction precision of fault features is improved, the model can effectively learn the fault features in a few-sample environment by optimizing a network structure and training parameters in the training process, and the diagnosis precision is remarkably improved.

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.

In order to improve the stability and reliability of the micro diaphragm pump, the invention provides the micro diaphragm pump with the columnar bubble and liquid monitoring function. The channel is formed in the pump cavity, the valve body is installed in the channel, the valve body is composed of the upper layer, the middle layer and the friction layer, the sensing part is arranged on the middle layer, the sensing area is formed through cooperation of the friction layer and the sensing part, and then columnar bubbles and liquid in the micro diaphragm pump are monitored. The device is small in size, high in energy density, high in controllability and capable of monitoring columnar bubbles and liquid.

The invention discloses an efficient variable-frequency low-temperature compressor system and a compression method thereof. The method comprises the steps that the actual oil-gas separation efficiency is obtained; inputting the working condition parameters of the compressor into a preset neural network prediction model to obtain an oil-gas separation efficiency prediction value and a theoretical solubility reference value; according to the actual oil-gas separation efficiency, the oil-gas separation efficiency predicted value and the theoretical solubility reference value, working condition deviation data is calculated, the comprehensive performance of the compressor at different frequency points is evaluated and calculated through an optimization algorithm, and a frequency adjustment curve is generated; according to the frequency adjusting curve, the operation frequency of the compressor is divided into a plurality of adjusting intervals, the operation frequency is adjusted in a stepped mode according to the adjusting intervals, the temperature and vibration parameters of the bearing are monitored in the adjusting process, and frequency adjusting feedback data are obtained; and according to the frequency adjustment feedback data, oil-gas separation efficiency deviation is periodically calculated, and compensation adjustment is conducted on the frequency adjustment curve. According to the technical scheme, insufficient lubrication and energy efficiency reduction of the compressor can be avoided.

The invention relates to the technical field of test bed operation monitoring, in particular to a fuel pump test bed operation monitoring method and system. The method comprises the following steps: acquiring monitoring time sequence data of operation of a fuel pump test bed, performing feature extraction, constructing a coupling prediction model of a space-time diagram attention network-unscented Kalman filter, and predicting a process noise covariance matrix and a measurement noise covariance matrix according to the coupling prediction model, and performing state estimation by using an unscented Kalman filter to obtain vector posterior probability distribution, constructing a fault evolution trajectory manifold, calculating a mahalanobis distance between the vector posterior probability distribution and the fault evolution trajectory manifold, and taking the mahalanobis distance as a monitoring index. According to the scheme of the invention, the deep features which can better reflect the inherent nonlinear and complex dynamic characteristics of the system can be extracted from the multi-source data, the estimation accuracy of the filter on the potential health state of the system is improved, and the defects that model parameters are fixed and gradual change faults are difficult to capture in a traditional method are overcome.

Systems and methods of operating a fracturing operation include a platform having an upper surface and a channel, wherein the platform is configured to receive a carrier mounted with a pumping unit; and a conduit configured to transfer fluid to or from a manifold system, the conduit having a first end configured to be connected to the pumping unit. The channel may be configured to receive the conduit when the carrier is at least partially received on the platform. A guide member may be configured to guide the conduit into the channel and include a rounded portion and an abutment surface, wherein the conduit is configured to extend at last partially around the rounded portion, and the carrier is configured to engage the abutment surface. The systems and methods may also include a controller configured to control a braking system of the carrier when the pumping unit is actuated.

A method of calibrating a pump system can include providing a pump, calibrating a pump input with an input device connected to the pump, and calibrating a pump output with an output device connected to the pump. Calibrating the pump input can include selecting a first input signal value, generating a transmitted input signal corresponding to the first input signal value, and setting a nominative pump input value to the first input signal value. Calibrating the pump output can include receiving a received output signal outputted from the pump, and setting a nominative pump output value to the first input signal value.

The invention relates to an air compressor fault diagnosis method and system and electronic device.The air compressor fault diagnosis method comprises the steps that current operation parameters of an air compressor are obtained, the current operation parameters are preprocessed, and input data are obtained, the operation parameters comprise a vibration parameter, a temperature parameter, an input pressure, an output pressure and a working current of the motor; according to the historical operation parameters and historical fault type data of the air compressor, a Transform model is trained to obtain a fault diagnosis model, the fault diagnosis model comprises multiple attention modules, and the multiple attention modules are used for calculating attention scores; and the state of the air compressor is diagnosed according to the input data and the fault diagnosis model, a diagnosis result is obtained, target data concerned during diagnosis is obtained according to the attention score, and supplementary interpretation is conducted on the diagnosis result.

The invention discloses a pneumatic diaphragm pump control method and system for an emulsion matrix transport vehicle, and relates to the technical field of intelligent fluid conveying control. By means of integrating temperature monitoring and adjustment, viscosity prediction and parameter setting, multi-parameter coupling optimization and the like, accurate control and dynamic optimization of key parameters in the emulsion matrix transportation process are achieved, temperature distribution in the storage tank can be monitored and adjusted in real time, pumping parameters are dynamically adjusted according to the viscosity of the matrix, and the pumping efficiency is improved. The pumping pressure, the flow and the vibration frequency are coordinated through a multi-parameter optimization algorithm, so that the problems of low conveying efficiency and high equipment failure rate of a traditional rotor pump are solved, the conveying efficiency and the construction quality of an emulsion matrix are improved, the energy consumption and the maintenance cost are reduced, the reliability of equipment is remarkably improved, and the service life of the equipment is remarkably prolonged. And powerful guarantee is provided for road construction and maintenance.

The invention belongs to the technical field of ion compressors, and particularly relates to a gas-liquid two-phase visualization test system, a safe operation method and a data processing method. A gas-liquid two-phase visual test system comprises a gas inlet module, a cylinder simulation module and a gas outlet module which are sequentially connected in series, the cylinder simulation module comprises more than two stages of visual piston units which are connected in series, and an interstage buffer part for temporarily storing test gas is further arranged on a pipeline between adjacent visual piston containers; a limiting device is arranged outside the straight pipeline directly connected with the visible piston container; the air inlet module generates test gas, the test gas sequentially flows through the visual piston units connected in series in the air cylinder simulation module, the visual piston containers in the visual piston units conduct piston reciprocating motion to compress the test gas and then send the test gas into the air outlet module, and the air outlet module discharges the compressed gas into the surrounding environment. According to the invention, a complex gas-liquid flow field in the air cylinder of the ion compressor can be truly, efficiently and safely simulated and observed.

The invention belongs to the technical field of intelligent control of electric submersible pumps, and discloses a ground control system and control method of an electric submersible pump. A sensor module of the system is used for collecting operation data of the electric submersible pump in real time; the intelligent calculation module is used for analyzing and calculating the collected real-time operation data of the electric submersible pump to obtain optimized control parameters; the control execution module is used for generating a corresponding instruction according to the optimized parameters and accurately adjusting the steering, rotating speed and stroke parameters of the servo motor; the real-time monitoring and feedback optimization module is used for monitoring the system state after execution of the control execution module in real time and judging whether system operation is abnormal or not according to a real-time monitoring result; and the alarm optimization adjustment module is used for dynamically optimizing the control strategy of the electric submersible pump based on the parameter abnormal condition fed back by the real-time monitoring module after the abnormal state of the system is detected. The control efficiency of the electric submersible pump is effectively improved, and the problem that in the prior art, a control method is low in efficiency is solved.

The invention provides an energy-saving optimization control method and system for an air compressor and a readable storage medium. The method comprises the steps that operation parameters of the air compressor and the current air use requirement of an air use end are obtained in real time; the current compression capacity of the air compressor is obtained through analysis according to the operation parameters; key operation parameters of the air compressor are dynamically adjusted according to the current air consumption demand and the current compression capacity so that the current compression capacity can be matched with the current air consumption demand, and the key operation parameters comprise the motor rotating speed, the air compressor load rate and the motor starting and stopping time. According to the energy-saving optimization control method for the air compressor, on the basis of real-time monitoring and analysis of the operation parameters of the air compressor and the current air consumption demand of the air consumption end, the key operation parameters of the air compressor are dynamically adjusted, so that the air production capacity of the air compressor is accurately matched with the actual air consumption demand, energy waste is avoided, and the energy conservation and emission reduction effects are achieved. Meanwhile, the stable operation and the service life of the equipment are considered, and the overall energy-saving optimization target is achieved.

The invention discloses an oil pump state detection technology, and aims to provide an oil pump state detection system based on deep learning and a detection method thereof, and the key points of the technical scheme are that the oil pump state detection system comprises the following modules: a data collection module used for collecting operation data of an oil pump in real time; the data preprocessing module is used for processing the collected original operation data; the deep learning model training module is used for training the preprocessed data through a back propagation algorithm by adopting a convolutional neural network architecture, so that the model can learn the characteristics of the normal state and the fault state of the oil pump; the state detection module is used for classifying the data by utilizing the trained deep learning model when monitoring the operation data of the oil pump in real time, outputting the current state of the oil pump and judging whether an abnormity or a potential fault exists or not; when the fault early warning module detects that the oil pump is abnormal or has a potential fault, an early warning signal is sent out in time; the method is suitable for the technical field of oil pump state detection.

The invention provides a large reciprocating compressor continuous stepless regulation system and method based on intelligent control, and the method comprises the steps: building a continuous stepless regulation model according to a load change trend and process fluctuation characteristics, and determining an initial parameter set of a regulation instruction through a preset load range regulation threshold value and a dynamic response speed requirement; according to the non-equilibrium stress adjustment scheme, dynamically adjusting operation parameters of a compressor execution mechanism, monitoring the abrasion state of key components through a real-time feedback control technology, and determining operation data of the components after stress equilibrium; and the operation data of the parts after stress balance are obtained, the operation parameters of the compressor are subjected to secondary calibration through an intelligent control system in combination with an energy efficiency improvement target, and the optimized optimal pressure ratio state parameters are obtained.

The micropump comprises a pump body, an actuator, a first base plate, a second base plate, a first sealing gasket and a second sealing gasket, the first sealing gasket is used for achieving sealing between an inlet and a liquid inlet flow channel, the second sealing gasket is used for achieving sealing between an outlet and a liquid outlet flow channel, and the first sealing gasket and the second sealing gasket are independent sealing pieces; the sealing gasket has no fixed connection relation with a sealed structure, only the first sealing gasket and the second sealing gasket deform when thermal expansion and cold contraction occur due to the influence of the environment temperature, the connection relation between the first sealing gasket and the sealed structure and the connection relation between the second sealing gasket and the sealed structure are not affected, and the sealing reliability is improved; the first sealing gasket and the second sealing gasket can generate compression deformation during compression sealing, when the environment temperature is reduced, the shrinkage amount of the first sealing gasket and the second sealing gasket is reduced, when the environment temperature is increased, the first sealing gasket and the second sealing gasket expand, the sealing gasket can be more tightly attached to a sealed structure, and the sealing effect is better.