135933 results about "Thermodynamics" patented technology

The invention discloses a distributed real-time monitoring and early warning system for a temperature field of a smelting furnace, and relates to the technical field of industrial process intelligent monitoring. The problems of accumulated measurement errors and non-stationary hotspot escape reconstruction hysteresis caused by static emissivity setting in an existing system are solved. Collecting multiband radiation intensity and voltage signals through time domain alignment of the multispectral sensor array and the thermocouple array; iterating emissivity parameters in real time by adopting a dynamic ash body spectrum ratio algorithm in combination with flue gas absorption characteristics; fusing non-contact and contact temperature measurement data based on weighted Kalman filtering and complementary filtering; constructing a space-time variable covariance function to carry out non-stationary Kriging interpolation; dynamically optimizing the local grid resolution by combining an adaptive grid module; the processing flow is accelerated through the parallel computing module; early warning is triggered based on abnormal probability judgment and is fed back to emissivity correction and grid optimization; according to the invention, the monitoring precision and real-time performance of the temperature field are obviously improved, and the risks of false alarm, missing alarm and equipment melting loss are effectively inhibited.

A vacuum insulating panel may include: a first substrate; a second substrate; a plurality of spacers provided in a gap between at least the first and second substrates, wherein the gap is at pressure less than atmospheric pressure; a pump-out / evacuation tube extending at least partly into an aperture in one of the substrates; and a pump-out / evacuation tube seal. The pump-out / evacuation tube seal may include at least one of: (a) from about 20-80 wt. % tellurium oxide, the tellurium oxide comprising TeO4 and TeO3, wherein the pump-out tube seal comprises more TeO3 than TeO4 by wt. %; and / or (b) tellurium oxide and from about 10-50 wt. % vanadium oxide, wherein the pump-out tube seal by wt. % comprises more tellurium oxide than vanadium oxide, and wherein the vanadium oxide comprises VO2 and V2O5, and wherein more V in the pump-out tube seal is in a form of VO2 than V2O5. A substantially donut-shaped laser beam may be used to heat pump-out tube material in order to form a pump-out tube seal.

The invention discloses a wind-light-hydrogen multi-energy complementary system cooperative operation optimization and comprehensive benefit evaluation method, which relates to the technical field of electric energy storage, and comprises the following steps: constructing a hybrid power flow model containing electricity, hydrogen and heat coupling, taking whole life cycle cost and new energy consumption as double targets, introducing grid-connected and off-grid risk constraints, and optimizing equipment capacity configuration; a scheduling baseline and an intra-day dynamic correction strategy are formulated in the day-ahead stage, and hybrid energy storage cooperative control is combined to improve the response speed and flexibility of the system to wind and light fluctuation; a peak regulation and frequency modulation mode is switched according to the power grid state, a power response model is established, fluctuation is stabilized through hydrogen energy storage, the stability of the power grid is enhanced, and auxiliary service benefits are created; the performance of the system is evaluated from the three dimensions of efficiency, economy and interactivity, dynamic weight and Monte Carlo simulation optimization are utilized, system parameters are continuously optimized through a feedback mechanism, and the self-evolution ability is formed. The problem that system instability and economy are difficult to take into account due to wind and light fluctuation is solved.

The invention relates to the technical field of compression molding of carbon fiber prepregs, in particular to a partitioned pressurization control method and system for compression molding of the carbon fiber prepregs and a molding process. S2, initial pressure calculation; s3, gradient pressurization control; s4, dynamic pressure adjustment; and S5, a global pressure maintaining stage: when the resin curing degree alpha reaches 0.6-0.8, switching to a full-screen pressure maintaining mode, and maintaining the pressure of each region to be 90%-95% of the current maximum pressure value until curing is completed. The invention provides a zoning pressurization control method and system for compression molding of carbon fiber prepreg and a molding process, and realizes the compression molding method and system with accurate zoning pressure regulation and control and directional discharge of volatile components. And by integrating intelligent sensing, multi-channel hydraulic control and a data driving optimization algorithm, the limitation of a traditional process is broken through, and a technical support is provided for efficient forming of the high-performance carbon fiber composite material.

The invention relates to the technical field of liquid cooling, and discloses a server cabinet liquid cooling control method and system based on intelligent liquid cooling distribution, and the method comprises the steps: collecting the temperature, cooling liquid flow, pressure and environmental parameters of each node in a server cabinet in real time through a liquid cooling distribution unit; the load change of the server is predicted based on a dynamic distribution algorithm, and the pump set rotating speed and the valve opening degree of the liquid cooling distribution unit are dynamically adjusted so as to dynamically distribute the cooling liquid flow according to needs; a multi-parameter coupling optimization algorithm is adopted, and the energy efficiency ratio of the liquid cooling system is adjusted according to the temperature, the cooling liquid flow and the pressure; cooling liquid leakage is detected through a multi-mode sensor, a liquid leakage protection mechanism is triggered in a grading mode according to the severity degree of leakage, and the liquid leakage protection mechanism comprises local pipeline isolation and whole system shutdown. The system corresponds to the method. By adopting the method, the energy efficiency improvement and the reliability enhancement of the heat dissipation system of the server cabinet are realized.

The invention discloses a hydrogen fuel cell vehicle ultralow temperature cold start thermal management system, and relates to the technical field of hydrogen fuel cell vehicle thermal management, the hydrogen fuel cell vehicle ultralow temperature cold start thermal management system comprises a thermal management platform, the thermal management platform is in communication connection with the following modules: a temperature monitoring and predicting module, and the temperature prediction module is used for monitoring the temperature of key parts in the hydrogen fuel cell by using the temperature sensor and predicting the change trend of the temperature in the fuel cell in combination with the temperature prediction model. By utilizing the high-precision temperature sensor and the long-short-term memory network model, the internal temperature change trend of the fuel cell is pre-judged in advance, the heating power is dynamically adjusted, it is ensured that the temperature of the cell is rapidly increased to the proper working temperature in the ultralow-temperature environment, starting difficulty caused by local supercooling is avoided, the low-temperature starting time is remarkably shortened, and the starting efficiency is improved. The reliability and the stability of the system in an extreme environment are improved, and the normal operation of the hydrogen fuel cell vehicle in a cold region is guaranteed.

The invention discloses a radiator salt spray corrosion life prediction method based on dynamic time warping, which belongs to the technical field of material corrosion test and life prediction, and comprises the following steps: collecting time sequence data of surface impedance and thermal resistance change of a radiator, constructing a dual-channel corrosion characteristic data set, and recording a salt spray concentration data value. The temperature data value and the humidity data value are combined, and an environment sensitivity weight vector is established. Accelerated corrosion in a salt spray environment is simulated, a laboratory accelerated corrosion test spectrum is generated, meanwhile, an actual environment fluctuation spectrum is monitored, the two spectrums are aligned by using a weight vector, accelerated corrosion data are obtained, and a basic life prediction value is calculated. And calculating an environment-structure coupling factor by combining the interaction between the three-dimensional structure characteristic parameters of the radiator and the temperature and humidity data values, correcting the basic life prediction value, and generating a final life prediction result. According to the method, double-channel feature alignment and coupling factor correction are adopted, and the corrosion life of the radiator of the specific structure under the actual working condition can be predicted.

An optical storage system designed to compensate for the water hammer effect in hydropower turbines and its cooperative frequency modulation method are provided. The method involves detecting the water hammer effect and utilizing a pre-established system model integrating a hydropower unit, photovoltaic system, and hybrid energy storage system. Through model predictive control combined with a whale optimization algorithm, the governor parameters of the hydropower unit are optimized. The system then obtains the photovoltaic active power output and the battery's state of charge (SOC) within the hybrid energy storage system. Based on these parameters, a collaborative control strategy for the photovoltaic and hybrid energy storage systems is determined and executed. This strategy enables effective control of the photovoltaic system and / or hybrid energy storage to compensate for reverse power adjustments in the hydropower unit, addressing the water hammer effect and ensuring stable power grid operation.

The invention discloses a server heat dissipation device and a heat dissipation control method.The surface of a server mainboard is divided into a core heat dissipation area, a transition heat dissipation area and an edge heat dissipation area, and the method comprises the steps that real-time temperature data of all the areas are synchronously collected through a temperature detection module; constructing a three-dimensional temperature field distribution map containing temperature gradient and heat flow direction; then thermodynamic parameter calculation is carried out, temperature time sequence change characteristics of all the partitions are extracted, and a thermal diffusion path in a future set time period is predicted by fusing the temperature time sequence change characteristics and the thermodynamic parameters; a control instruction set is generated according to the predicted thermal diffusion path, the actual heat dissipation response is monitored through an acoustic sensor in the execution process, monitoring data and the predicted thermal diffusion path are dynamically compared, and control parameters of the control instruction set are updated till all the partitions reach the target temperature threshold value; and the sudden temperature change is pre-judged, the hot spot elimination response time is shortened, and the collaborative breakthrough of the heat dissipation efficiency and the energy consumption control of the high-density server cluster is realized.

The invention relates to the technical field of gas pipeline safety assessment, in particular to a gas pipeline safety assessment early warning system and method based on data analysis. The method comprises the following steps: collecting gas pressure data of a gas pipeline at multiple points at the same time, carrying out time-space synchronization processing to obtain aligned gas pressure data so as to construct a continuous gas pressure field of the pipeline, based on the gas pressure field, identifying the pressure distribution difference of the pipeline, estimating the transient flow velocity of the gas, continuously recording the transient flow velocity of the gas, and deducing the change of the flow velocity. Judging the deformation condition of the inner wall of the pipeline in combination with air pressure field data, positioning a deformation area, reconstructing a pipeline frame, analyzing deformation response, identifying a deformation type, identifying a corrosion evolution trend, performing safety evaluation, judging the gas circulation degree and performing physical safety evaluation. According to the invention, dynamic monitoring of the gas pipeline is realized, a data-driven safety management mode is promoted, the early warning capability of potential risks is improved, and a more intelligent safety assessment and early warning mechanism is formed.

The invention provides a laboratory energy-saving optimization control system and method based on energy efficiency model driving, and relates to the technical field of intelligent control, and the method comprises the steps: recognizing a core coordinate of a temperature overrun region of a hazardous chemical substance storage region based on a fusion data set, and taking the core coordinate as a first point, identifying the oxidation reaction rate peak position coordinate of the hazardous waste treatment area as a second point, and identifying the boundary centroid coordinate of the abnormal heat dissipation area of the high-energy-consumption equipment as a third point; constructing a key point coordinate set based on the first point, the second point and the third point, and connecting the key points to generate a static polygon monitoring domain; performing grid discretization processing by taking the static polygon monitoring domain as a boundary to generate structured grid data containing vertex coordinates and unit adjacency relations; deformation parameters of each unit are calculated, and a non-uniform deformation field scalar operator is generated through fusion; and taking the scalar operator as a physical field coupling weight, and generating an optimization instruction set. According to the invention, intelligent control of equipment is realized.

Systems and methods for cooling a biological sample with different temperature cooling blocks. Warmer cooling blocks can be placed around a container and cooler cooling blocks can be placed above the container. The biological sample can be a pancreas, heart or other organs. The method and system can rely on convection, or gravity-based fluid movement, to make the temperature within the container consistent.

The invention provides a multi-level geothermal well collaborative scheduling method and system based on multi-time scale prediction, and relates to the technical field of data processing. The method comprises the following steps: constructing a well group output model based on operation parameters of a shallow geothermal well group and a deep geothermal well group; constructing a multi-scale load prediction model based on the historical load data and the historical meteorological data; determining a load prediction result of the target time period by using the multi-scale load prediction model, wherein the load prediction result comprises a day-ahead load, a day-mid load and a real-time load; and performing joint calculation by using the well group output model, the load prediction result and the multi-objective optimization function to obtain optimal scheduling parameters of the shallow geothermal well group and the deep geothermal well group in the current scheduling period. According to the technical scheme, the output ratio of the shallow geothermal well and the deep geothermal well can be dynamically coordinated according to the predicted load requirements of different time scales, and efficient utilization of multi-level geothermal resources is achieved.

A transport container and methods for preserving an organ at a target temperature. The transport container can maintain the organ at a temperature of 6-8⁰C for improved results after transplantation. The transport container can store the organ at a target temperature of determined based on characteristics of the organ and the donor. A processor can determine the target temperature for preservation of the organ. The transport container can contain cooling media that is colder near the bottom of the transport container and warmer near the top of the transport container to counter uneven cooling caused by gravity.

The invention provides a data center energy efficiency optimization method and system. A data acquisition node is arranged at the inlet end of a cooling unit to obtain refrigerant transportation data, the data are input into a path optimization model constructed based on a physical topological structure of the cooling unit, and a dynamic adjustment coefficient set containing heat exchange efficiency, phase change delay and pressure compensation parameters is generated. Meanwhile, the temperature difference generating capacity is converted into a driving parameter set based on the heat source distribution map by obtaining the surface waste heat of the cooling unit. And in combination with the dynamic adjustment coefficient set and the driving parameter set, the temperature gradient compensation amount, the phase change trigger threshold value and the pressure balance interval are determined, joint optimization is carried out, and a refrigerant flow rate control scheme adapting to machine room environment temperature fluctuation is generated. And energy efficiency optimization of the data center machine room environment is realized based on the refrigerant circulation parameters. According to the technical scheme provided by the invention, the energy efficiency optimization effect of the data center is remarkably improved by optimizing the flow speed control of the refrigerant.

The invention relates to the technical field of data processing, and provides a multi-heat-source networking heat supply optimization operation method and system.The method comprises the steps that environmental parameters, heat source data, market dynamic information, user behavior characteristics and a pipe network topological graph are collected by deploying IoT equipment; acquiring a thermal load time sequence predicted value in a future preset time period; the heat source data and the pipe network topological graph are processed, and a pipe network operation state matrix is obtained; performing feature dimension alignment processing on the pipe network operation state matrix to obtain a pipe network spatial topology feature mapping value; performing weighted fusion on the thermal load time sequence prediction value and the pipe network spatial topological feature mapping value to obtain a final thermal load prediction value; and optimal operation of heat supply is realized according to the final heat load predicted value. According to the method, a real-time response mechanism for environmental parameters, market dynamics and user behavior characteristics can be realized, collaborative optimization of multiple heat sources can be realized, the heat source collaborative efficiency is improved, and energy waste and operation cost are reduced.

The invention relates to the field of grain drying, and discloses a grain drying energy-saving control system based on intelligent optimization, which comprises the following steps: after warehousing grains are detected, judging whether the water content of the grains exceeds a preset safety threshold value or not by collecting the initial water content of the grains and environment temperature and humidity information; according to the grain moisture content, the grain size distribution and the current environment condition, a multi-section type moisture change trend model fitting the drying process is constructed, and the decrease rate of the grain moisture content and the drying curve form in the future stage are predicted; analyzing the deviation value between the water content change slope and the target drying rate in the prediction curve; judging whether an adjustment potential exists or not by modeling a response relationship among the current hot air temperature, wind speed, heat source power and water content change; and according to the heat energy use analysis result, control instructions of hot air temperature, air speed and air supply modes are automatically generated. The self-adaptive energy-saving grain dryer has the advantage that the self-adaptive capacity and the energy-saving effect in the grain drying process are improved.

The embodiment of the utility model provides a container, an energy storage device, an energy storage system and a charging network. The energy storage device comprises a container, a control module and a heat management module. The number of the containers is m, m is larger than or equal to 2, and the m containers are arranged in the first direction of the containers. In the first direction, the size of the container is smaller than that of a standard container. The container comprises a container body and a plurality of single batteries, and the plurality of single batteries are accommodated in the container body. And the control module is arranged in the box body and is used for electrically controlling the plurality of single batteries in the m containers. And the heat management module is arranged in the box body and is used for managing the temperature of the plurality of single batteries of the m containers. According to the energy storage device provided by the embodiment of the invention, the convenience in the transportation process of the container is improved, the transportation cost of the container and the energy storage device using the container is reduced, the space in the container can be fully utilized, the integration degree is high, and the assembly efficiency is improved.

The invention relates to the technical field of power equipment monitoring, in particular to a 10kV cable joint temperature inversion correction method based on environmental heat exchange conditions, which comprises the following steps: measuring surface temperature data through a sensor array, and analyzing material layering characteristics in combination with X-ray imaging; then, establishing an electromagnetic-thermal-fluid field coupling model, and calculating a dynamic thermal resistance coefficient and a heat flow distortion index; thirdly, optimizing surface temperature distribution and iteratively updating thermal resistance parameters by utilizing a bidirectional feedback correction strategy, and finally generating a high-precision internal temperature field; through adaptive temperature compensation and multi-source data fusion, the accuracy of temperature prediction is improved, long-term monitoring errors are reduced, the method can be widely applied to intelligent operation and maintenance and fault early warning of cable joints, and the safety and stability of a power system are improved.

The invention discloses a temperature monitoring method for a photovoltaic grid-connected cabinet, and particularly relates to the technical field of photovoltaic grid-connected cabinets. The method comprises the following steps: arranging multiple types of temperature sensors in a grid-connected cabinet, collecting real-time temperature data, constructing a heat distribution model, comparing a current heat map with a historical steady-state heat field template, and identifying heat field offset and an atypical temperature rise trend; when the system detects that early warning is not triggered by an existing measuring point in a heat abnormal area, redundancy alarm logic is automatically started, temperature abnormal early warning is generated, and the speculated abnormal heat source position is recorded; according to the method, the sensing capability of the thermal anomaly in the blind area of the sensor is effectively improved, and the safety and the intelligent level of the system are enhanced.

The invention relates to the technical field of coal mine safety monitoring, in particular to an underground coal mine dust concentration monitoring method and system based on multi-modal data fusion, and the method comprises the steps: synchronously collecting dust concentration time sequence data, dust image data, sound wave signal data and environmental parameters through a multi-modal sensor array deployed in an underground coal mine; carrying out preprocessing and feature extraction on the collected data; predicting the decomposed high-frequency and low-frequency component signals by adopting a long short-term memory neural network and a grey Markov model; when the environment humidity is greater than 80%, carrying out light scattering compensation on the predicted value; inputting various predicted values into an improved D-S evidence theory fusion device, and outputting a fusion dust concentration monitoring value; and when the threshold value is exceeded or the temperature and humidity composite condition is reached, an acousto-optic alarm is triggered and a spraying dust-settling device is started. According to the method, the problems of low precision of a single sensor, multi-source data conflict, high-humidity environment measurement deviation and insufficient time sequence and fusion precision in underground coal mine dust concentration monitoring can be solved.

The invention discloses a copper bar connection state detection method and system, particularly relates to the technical field of copper bar state detection, and is used for solving the problem of poor early recognition of copper bar connection deterioration. According to the method, resistance and temperature rise conditions at the joint of the copper bars are measured synchronously in the load change process, signal denoising is realized in combination with finite difference filtering, and characteristic evolution conditions at the joint are captured; the method comprises the steps of determining an analysis window based on a real-time load change event, constructing a thermoelectric track point set and dividing a load rising and falling period, forming a continuous dynamic thermoelectric response curve, dividing a temperature rising track and a temperature falling track through a temperature change trend, extracting a resistance drift amount and a hysteresis loop area, and identifying a connection degradation trend and a structure fatigue characteristic. And connection state information generated by thermal stress action and thermal cycle asymmetry is obtained during load change, and a detection strategy is adjusted according to an analysis result, so that early degradation identification and intelligent risk grading of the copper bar connection state are carried out, and the sensitivity and accuracy of copper bar detection are improved.

The invention discloses a server mainboard regional distributed liquid cooling heat exchange adjusting method, which comprises the following steps of: acquiring a temperature parameter set and a power consumption parameter set of each monitoring region in real time, and generating a thermal load parameter feature vector; identifying a high heat load core area set according to the heat load parameter feature vector; generating a liquid cooling branch flow distribution instruction set based on the position distribution of the high heat load core area set; executing the liquid cooling branch flow distribution instruction set, and obtaining an adjusted temperature feedback parameter set; according to the deviation degree of the temperature feedback parameter set and the target temperature interval, dynamic feedback adjustment is carried out by applying the heat conduction compensation coefficient and the fluid viscosity-temperature compensation coefficient, and an updated liquid cooling branch flow distribution instruction set is generated. The method has the following advantages and effects that by sensing the thermal load space distribution characteristics of all areas of the mainboard in real time, cooling flow distribution is dynamically adapted, real-time compensation of the fluid viscosity-temperature effect is integrated, local hot spots are eliminated, and the heat dissipation effect is improved.

The invention relates to the technical field of power electronics, in particular to a photovoltaic off-grid inverter control method and system, and the method comprises the following steps: applying a test signal to identify an output interaction characteristic parameter, predicting the power generation power through combining with weather and attenuation, calculating the power fluctuation, and adjusting a current control parameter set. And calculating voltage and reactive power compensation parameters to generate an inverter control instruction, and combining a temperature load prediction trend to adjust a power allowable value to obtain a predictive power calibration coefficient. According to the invention, by analyzing the output interaction characteristics, enhancing the perception capability of the inverter to the actual operation environment, combining with the prediction of the photovoltaic power generation amount, realizing the prediction and influence evaluation of the power fluctuation, improving the adaptive adjustment capability of the current control parameters, improving the output voltage and reactive power control precision by utilizing the interaction characteristics, and optimizing the electric energy quality; and through thermal management of multi-point temperature and load prediction, the operation safety is improved, the service life of equipment is prolonged, and the operation performance of the photovoltaic off-grid system in a complex environment is improved.

The invention provides a new energy automobile battery thermal management method and system based on big data. The method comprises the steps that real-time data flow and a historical temperature change curve in a battery pack are collected in real time through a distributed sensor array; inputting a pre-trained time sequence prediction model, outputting a predicted temperature change curve and calculating a real-time temperature rise slope; obtaining an environment comprehensive compensation amount according to the environment temperature and the battery health state, and subtracting the environment comprehensive compensation amount from the basic safety threshold value to obtain a dynamic safety threshold value; determining a dynamic temperature compensation amount through a preset slope grading mechanism, and subtracting the dynamic temperature compensation amount from the dynamic safety threshold to obtain an advanced intervention temperature point; and when the temperature of the battery pack reaches the advanced intervention temperature point, a graded cooling system is started, and cooling power grades are dynamically switched according to the growth interval where the real-time temperature rise slope is located. The battery temperature is accurately controlled, and the energy consumption is remarkably reduced.

The invention relates to the technical field of electric vehicle charging management, and discloses an electric vehicle charging optimization management system. The system comprises a dynamic charging demand prediction module which constructs a model based on historical data, collects voltage fluctuation, current phase deviation and charging power pulse characteristics of a charging pile in real time, and outputs a theoretical charging load value; the multi-dimensional demand difference analysis module is used for performing three-dimensional comparison of time accumulation deviation, frequency response difference and pulse characteristic similarity on theoretical and actually measured load values to generate a charging pile group level difference characteristic tensor; the hot spot region association positioning module inputs the difference feature tensor into a spatial topology mapping network, generates a fault probability thermal distribution diagram in combination with power grid node capacity and charging station position information, and positions a charging bottleneck region; and the self-adaptive regulation and control strategy generation module is used for starting millisecond-level monitoring on a high fault probability region according to the thermal distribution diagram and applying a power disturbance test on adjacent nodes. The system can improve the accuracy and effectiveness of charging management.

The invention relates to the technical field of mechanical stress and thermal deformation monitoring, in particular to a combustion fine adjustment method based on full-hearth expansion monitoring, which is characterized in that expansion sensor arrays are arranged on each layer of a main burner area of a boiler hearth, and vibration monitoring units are arranged in a layered manner from a main burner to an SOFA air area synchronously; normal deformation, three-dimensional expansion displacement data and vibration spectrum data of the four furnace walls are collected; generating a standardized monitoring data set through wavelet noise reduction and temperature compensation processing, fusing boiler operation parameters, and inputting the boiler operation parameters into the reinforcement learning model to generate a combustor adjustment instruction; water-cooled wall expansion rate change data is collected in real time to optimize model weight and update a control strategy, and a closed-loop feedback mechanism is formed. According to the method, through multi-source sensing data fusion and dynamic modeling, sub-meter analysis of thermal load distribution and quick response of the combustion state are achieved, the boiler operation efficiency is improved, and the service life of equipment is prolonged.

The invention discloses a high-precision drilling control method and system for a multi-layer PCB, and relates to the technical field of intelligent control. The method comprises the following steps: scanning and analyzing to obtain layered material characteristics and structural size information of a multi-layer PCB, and carrying out clamping fixation and positioning hole processing on the multi-layer PCB to obtain a PCB positioning hole; a drilling machining three-dimensional coordinate axis is constructed; a PCB drilling strategy space is constructed, the PCB drilling strategy space is adopted to conduct drilling analysis on the layered material characteristics and the structure size information in sequence according to the PCB drilling machining requirement, and layered drilling strategy parameters are obtained; and the layered drilling strategy parameters are mapped to a drilling processing three-dimensional coordinate axis for space route fusion, layered drilling processing parameters are determined, and high-precision drilling and quality detection closed-loop control are executed on the multi-layer PCB. The technical problem that in the prior art, the positioning precision is low in the drilling process of the multi-layer PCB is solved, and the technical effect of improving the drilling machining precision of the multi-layer PCB is achieved.

The invention provides an online calibration method and system for a flowmeter of a natural gas well, and belongs to the technical field of natural gas exploitation and transportation, firstly, a multiphase flow state sensing signal in a transportation pipeline of the natural gas well and a structural deformation monitoring signal of the flowmeter to be calibrated are obtained, and then interactive interference characteristic analysis is conducted on the two kinds of signals; the method comprises the following steps: obtaining a flow state-deformation interaction interference characteristic set, generating a multiphase flow adaptive calibration factor based on the flow state-deformation interaction interference characteristic set, inputting the multiphase flow adaptive calibration factor into a metering signal processing unit to dynamically correct an original metering signal, and obtaining a corrected metering output signal; and finally, collecting matching degree data of the correction signal and the real-time multiphase flow state sensing signal to form a calibration adaptive feedback signal, thereby comprehensively considering the influence of the multiphase flow state and structural deformation, and improving the metering precision and reliability of the flowmeter.

The invention relates to the technical field of energy storage management, in particular to a high-energy-density liquid cooling energy storage system based on thermal management optimization, which comprises a thermal response calculation module, a thermal risk area identification module, a cooling resource allocation module, a thermal decoupling state judgment module and a charging and discharging power limiting module. According to the method, the inlet temperature, the outlet temperature and the cooling liquid flow speed of the high-energy-density energy storage equipment are obtained, the unit thermal load conversion rate is calculated, the unit thermal response deviation degree is determined, the thermal risk area higher than the standard limit is clearly recognized in the energy storage equipment, the corresponding liquid cooling channel is accurately selected, and the cooling liquid pulse flow frequency is optimized; the pertinence and timeliness of the cooling liquid in actual use are effectively improved, the local overheating hidden danger is avoided, the lag response is marked in time by monitoring the cooling liquid pressure difference and the temperature rise change in real time, the decoupling state between the cooling liquid and the thermal load is judged, the charge and discharge power dynamic reduction measure is implemented, and the trend of abnormal and continuous accumulation of the local thermal load is restrained.