301 results about "Pressure curve" patented technology

The invention relates to the technical field of injection molding quality monitoring, in particular to a real-time monitoring method and system for injection molding production quality. The method comprises the following steps: acquiring a standard pressure curve and a standard temperature curve of each production stage in each injection molding production cycle; calculating the local intensity of each sampling moment; obtaining an abnormal fluctuation coefficient of each sampling moment, and constructing a multi-dimensional coupling dynamic weight of each sampling moment; multiplying the abnormal fluctuation coefficient by the multi-dimensional coupling dynamic weight to obtain a weighted dynamic fluctuation curve; integrating the weighted dynamic fluctuation curve to obtain a form deviation index; and performing anomaly detection on the current production cycle based on the form deviation index. And the monitoring precision of injection molding production is improved.

The invention relates to the technical field of liquid chromatogram data processing, in particular to a liquid chromatograph state detection and maintenance method which comprises the following steps: establishing a multi-parameter online monitoring system which comprises a normal data set and an abnormal data set; learning the normal data set and the abnormal data set, and collecting real-time monitoring data to be matched with a known fault mode; according to the real-time monitoring data, the control unit draws a pressure curve and calculates a pressure fluctuation value; determining the test period of the chromatographic instrument based on the pressure fluctuation value and the baseline noise peak value, or sending an equipment fluctuation monitoring signal and calculating the difference value between the chromatographic column temperature and the environment temperature: determining the heating power of a constant-temperature box based on the difference value between the chromatographic column temperature and the environment temperature, or sending an equipment fluctuation monitoring signal; and determining the temperature correction coefficient of the chromatographic column according to the equipment vibration frequency. According to the invention, the operation stability and effectiveness of the liquid chromatograph are improved.

The invention discloses a bicycle center shaft press-fitting machining system based on machine vision positioning. The bicycle center shaft press-fitting machining system comprises a servo press-fitting module, a data acquisition module, a data processing module, a machine vision positioning module, a press-fitting control module, a quality detection module and a data management module. According to the system, image data and assembly quality data are acquired through data, and initial coordinates of mounting holes are extracted through median filtering, Canny edge detection and Hough circle transformation; further adopting an RANSAC algorithm to fit the cylindrical surface of the inner wall of the five-way pipe, accurately calculating a center point space coordinate and an axis direction vector, and converting the center point space coordinate and the axis direction vector to a press-fitting coordinate system through hand-eye calibration; the press-fitting process is dynamically regulated and controlled in three stages of pre-pressing, main pressing and final pressing, the press-fitting speed is dynamically regulated, and meanwhile, online judgment of the assembly quality is achieved through displacement-pressure curve analysis; according to the system, the problem of bearing abrasion caused by alignment deviation of a traditional press-fitting central axis is solved, and the press-fitting precision and the yield are improved.

The invention relates to the technical field of oil and gas field development, in particular to a fracture parameter inversion method based on a Bayesian neural network, which comprises the following steps: establishing a bottom hole net pressure conversion model based on an actual construction curve, and drawing a bottom hole net pressure curve; calculating a bottom hole net pressure index sequence and a corresponding time sequence; establishing a shaft bottom crack extension mode judgment criterion on the basis of a classic double logarithmic curve analysis method; taking the net pressure index sequence and the time sequence obtained in the previous step as input data, combining actual physical parameter constraints, and establishing an inversion fracture parameter model based on a Bayesian neural network; and inputting the pressure index sequence to be inverted into the Bayesian neural network model to obtain a specific fracture parameter inversion result. According to the technical scheme, the confidence interval of the prediction result can be given, the prediction result and uncertainty quantification capability can be synchronously provided, and the reliability and decision support value of the inversion result are greatly improved.

The invention discloses an air separation pressure swing intelligent adsorption pollution discharge method, system and device combined with a pressure curve, and relates to the technical field of intelligent pollution discharge. The air separation pressure swing intelligent adsorption pollution discharge method, system and device combined with the pressure curve comprises the following steps: S1, collecting running state data in real time, and preprocessing the running state data; s2, performing pressure disturbance intensity analysis on the operation state data; s3, performing real-time analysis and feature extraction on the pressure curve; s4, performing start-stop risk prediction on the operation state data; and S5, integrating the operation state data, the pressure disturbance intensity analysis result and the start-stop risk prediction result to execute a pollution discharge control instruction. The problems that an air compressor and a pressure swing adsorption system lack linkage control based on pressure change, pollution discharge easily causes pressure fluctuation and frequent starting and stopping, energy consumption is increased, equipment abrasion is caused, and an existing control mode lacks a feedforward adjusting mechanism are solved.

A method for assessing a physiological status of a patient is described herein. The method includes placing at least one pressure sensor in an anterior mediastinal space of the patient. Pressure signal data received from the at least one pressure sensor is amplified and filtered to separate the pressure signal data into different frequency bands. A set of pressure curves is generated based on the separated pressure signals in different frequency bands, and a physiological status of the patient is assessed based at least in part on the set of pressure curves.

The invention discloses an intelligent control method and system for limb pressurization equipment, and relates to the technical field of intelligent control. The current working state of the limb pressurization equipment is determined according to multiple pieces of working data of the limb pressurization equipment; the training report of the target limb is determined according to the current working state of the limb pressurization equipment, the multiple training pressure items and the overall form of the target limb, and the accuracy of the training report of the target limb is improved. Determining a plurality of training features according to the detection of the training report, and determining a pressure curve of the target limb according to the plurality of training features, the pressure condition of the target limb and the age of the user; determining an intelligent control event of the limb pressurization equipment based on the pressure curve of the target limb and the current working state of the limb pressurization equipment, and determining a dynamic early warning system of the limb pressurization equipment according to the intelligent control event, the abnormal signal of the limb pressurization equipment and the current body state of the user, and the accuracy of the dynamic early warning system of the limb pressurization equipment is improved.

The invention relates to the technical field of process control, in particular to an injection molding process optimization method and device, computer equipment and a storage medium, and the method comprises the following steps: obtaining stress signals of four tie bars of an injection molding machine, calculating a total mold locking force, and preprocessing the stress signals through temperature compensation and moving average filtering; real-time mold cavity pressure is calculated based on a mold filling stage linear model, a pressure maintaining stage quadratic function model and a cooling stage exponential attenuation model triggered by an injection molding machine control signal; generating a standard curve template with a confidence interval according to the characteristic parameters of the qualified sample, and dynamically updating the standard curve template; and comparing the current pressure curve with a standard template output quality judgment result in real time, and triggering automatic parameter adjustment to form closed-loop control. The device and the method have the effect of solving the problems of high cost, poor compatibility and difficulty in maintenance when the pressure of the die cavity is directly measured.

The invention relates to the technical field of intelligent control and predictive maintenance of heating water heaters, in particular to a wind pressure switch control system and method for a heating water heater. The method comprises the following steps of: extracting a starting pressure curve slope, a steady-state pressure fluctuation frequency spectrum entropy and a shutdown pressure decay time constant by collecting a time sequence pressure signal in a working period of a fan so as to generate a dynamic feature vector; comparing the vector with a preset reference health vector by the system, and resolving the health state confidence and the state deviation drift rate of the system in real time; when the health confidence coefficient is lower than a safety threshold value or the deviation drift rate is too high, the system executes forced safety locking; if the health degree is slightly reduced, the pre-purging time of the fan is actively prolonged as compensation; according to the method, conversion from fault response to predictive maintenance is achieved, early performance degradation symptoms such as fan abrasion and air duct dust deposition can be recognized in advance, post-maintenance is converted into beforehand intervention, and the fault rate and maintenance cost are effectively reduced.

The invention discloses a dioptric scleroderma cataract dynamic intraocular pressure stable control ultrasonic emulsification system adaptive to a dual-channel operation, which comprises a host control unit, an ultrasonic emulsification handle, a perfusion and suction system, an intraocular pressure monitoring unit, a pressure balance module and a scleroderma fragmentation module, through cooperation of the intraocular pressure control module and the two-way operation type adaptive control module, a high-precision filling valve and a closed-loop suction pump are synchronously adjusted in real time according to anterior chamber built-in and external monitoring fusion data, and intraoperative intraocular pressure fluctuation is controlled within + / -2 mmHg; through pulse modulation and a self-adaptive negative pressure curve of the hardcore fragmentation enhancement module, the stability of the anterior chamber is ensured while the hardcore fragmentation efficiency is improved; fluid dynamics and energy parameters can be automatically optimized according to conventional incisions or micro incisions; according to the system, the anterior chamber stability problem in the high-difficulty cataract surgery is solved.

The invention provides an intelligent adjusting method and system for a steel pipe hydrostatic pressure valve, and relates to the technical field of equipment control, and the method comprises the steps: obtaining the specification parameters of a to-be-tested steel pipe; the volume of the steel pipe is calculated according to the specification parameters, adjusting parameters are dynamically determined according to the volume and the wall thickness of the steel pipe, meanwhile, a target pressure value is set according to a preset pressure curve, and in the hydrostatic pressure testing process, pressure signals and flow signals in the steel pipe are collected in real time; comparing the pressure signal with a set target pressure value to obtain a pressure deviation, and integrating the pressure signal and the flow signal which are acquired in real time into a group of multidimensional discrete data sequences according to a sequential relationship. According to the invention, accurate, stable and automatic closed-loop control of the pressure in the hydrostatic pressure test process of the steel pipe is realized.

Disclosed is a method for assessing nitrogen leaching risk based on farmland soil pressure, including the following steps: acquiring soil drilling pressure data from a plurality of soil layers of different depths on soil to be tested using a soil drilling device, to obtain raw soil drilling pressure data; comparing a calibration curve with a raw soil drilling pressure curve; setting an interquartile range (IQR) coefficient based on a first fluctuation factor and a second fluctuation factor, and constructing a box plot of the raw soil drilling pressure data based on the IQR coefficient; and determining a peak soil drilling pressure according to the box plot of the raw soil drilling pressure data, and determining nitrogen leaching risk according to a depth interval of soil layer. The box plot is utilized to filter out abnormal values, ensuring the accuracy of assessing the nitrogen leaching risk in soil.

The invention belongs to the technical field of aerospace equipment manufacturing, and discloses a full-automatic crimping method for a VPX connector. Comprising the steps of material automatic matching, product flexible assembly, pressure curve fitting and intelligent visual detection. The materials subjected to automatic material matching are assembled through product flexible assembly, and pressure detection, pressure fitting comparison and pressure feedback adjustment are conducted in real time according to pressure curve fitting in the assembling process; and after assembly is finished, finished product inspection is performed through intelligent visual inspection. VPX connector crimping is carried out in an intelligent and automatic mode, crimping work of VPX connector plugs / sockets on PCBs of various shapes and specifications is realized, the production efficiency and the production quality are greatly improved, the cost is reduced, and the production reliability is guaranteed.

The invention discloses a LoRa-based automatic pressure-regulating water feeder for breeding and a control method thereof. The method comprises the following steps: a data acquisition module acquires waterline breeding data information; data and instruction transmission among the data acquisition module, the data analysis module and the instruction generation and execution module is carried out through the LoRa communication technology; according to the poultry day age and the waterline capacity factor, a reference pressure instruction is calculated through an S-shaped reference pressure curve, meanwhile, the instantaneous flow is monitored in real time, the drinking active period is recognized, and a dynamic compensation instruction is generated to cope with the short-term drinking peak; and according to a superposition result of the reference pressure instruction and the dynamic compensation instruction, a final target pressure instruction is generated and adjusted to the target water pressure. Through automatic and intelligent water supply management, water supply pressure can be automatically adjusted according to growth stages and water drinking behaviors of poultry, continuity and stability of water supply are ensured, breeding efficiency and water supply precision are remarkably improved, and poultry stress response caused by unstable water supply is reduced.

The invention provides a plastic mold intelligent optimization system and method based on digital twinning. The method comprises the steps that a digital twinning model integrating mold cavity geometry and an injection molding machine hydraulic device is established; time sequence data of cavity pressure and screw movement in the filling and pressure maintaining stage are used as input, and PVT characteristic parameters and melt leading edge viscosity attenuation coefficients of the polymer melt in the current production period are identified and updated on line; on the basis of the PVT characteristic parameters and the melt front edge viscosity attenuation coefficient, predicting and generating a dwell pressure curve required for achieving a predefined cavity pressure balance curve in the next period; in the pressure maintaining stage of the next production cycle, the amplitude of the pressure maintaining pressure curve is adjusted according to the dynamic deviation of the cavity pressure detected in real time and the cavity pressure balance curve, a compensation control signal is output to an injection molding machine executing mechanism, and self-adaptive closed-loop adjustment of the cavity pressure is achieved. Based on the above scheme, feedforward optimization based on material characteristics and feedback control of AI disturbance can be realized.

The invention discloses a method for inverting the equivalent elastic modulus of a coating based on a physical experiment and finite element simulation, and belongs to the technical field of material mechanics coating performance testing, and the method specifically comprises the following steps: S1, preparing to-be-tested samples of a matrix and the coating, and determining geometric and material parameters; s2, performing a physical three-point bending experiment at a to-be-measured temperature, and recording displacement and pressure data; s3, establishing a finite element model, endowing the coating with an elastic modulus initial assumed value, and performing simulation; s4, constructing and comparing displacement-pressure curves of a physical experiment and simulation; and S5, the elasticity modulus of the coating is adjusted through iteration until the two curves are consistent in the preset tolerance range, and the elasticity modulus at the moment is the equivalent elasticity modulus of the coating. Accurate measurement of the equivalent elastic modulus of the coating in normal-temperature and high-temperature environments is achieved, errors caused by direct measurement at high temperature are avoided, the experiment process is simple, and engineering application is easy.

The invention discloses an intelligent clothing design and template generation method and system, and relates to the technical field of clothing intelligent plate making, and relates to multi-physics field modeling, dynamic simulation, reverse optimization and iterative output technologys.The method comprises the steps that a biomechanical human body model containing skeletal muscle groups and a multi-physics field coupling model of initial clothing piece templates and fabric parameters are constructed; defining a target pressure curve; driving a human body to execute preset actions, and calculating a dynamic pressure field and a wrinkle discomfort index through explicit dynamics; constructing a loss function fusing the pressure goodness of fit and the wrinkle index, solving a gradient by using an adjoint method, and accelerating reverse optimization in combination with a physical information neural network agent model; the system comprises corresponding function modules, parameters can be automatically adjusted according to the motion posture, it is ensured that the dynamic pressure is always close to a target curve, and the functionality and comfort level of clothes are improved.

The application discloses a pressure curve combined air separation variable pressure intelligent adsorption blowdown method, system and device, relates to the intelligent blowdown technical field.The pressure curve combined air separation variable pressure intelligent adsorption blowdown method, system and device, comprising the following steps: S1, real-time acquisition operation state data, and pretreatment is carried out to operation state data;S2, operation state data is analyzed to pressure disturbance intensity;S3, through real-time analysis and feature extraction to pressure curve;S4, operation state data is predicted to start-stop risk;S5, comprehensive operation state data, pressure disturbance intensity analysis result and start-stop risk prediction result execute blowdown control instruction.The air compressor and variable pressure adsorption system lack linkage control based on pressure change, blowdown is easy to cause pressure fluctuation and frequent start-stop, which leads to energy consumption increase and equipment wear, and the existing control mode lacks feedforward regulation mechanism.

The application discloses a multifunctional air bed quick detection device and method, the device comprises a cushion tool, a host tool, and a multi-cavity socket; the cushion tool is internally provided with a plurality of small air bags and is connected to different air paths respectively, and is used for simulating a plurality of components of the cushion; the host tool comprises an air pump, a main control panel, a display screen, a plurality of electromagnetic valve groups, and a plurality of pressure sensor groups; the working port of each electromagnetic valve group is connected to a corresponding small air bag; each pressure sensor is integrated on the main control panel and is connected to a corresponding electromagnetic valve group, and is used for detecting a real-time pressure value; and the display screen is used for presenting an inflation pressure curve and a fault judgment result. The application internally provides a micro air bag in the cushion tool to simulate each functional cavity of the bed, integrates the air pump, the valve group, the multi-path sensor and other devices in the host tool, and is used independently, so that it is not necessary to detect the whole air bed as a whole to position whether there is a problem such as a cushion leakage, and the detection period is effectively shortened; meanwhile, the whole size is small and compact, and is convenient for relevant personnel to carry.

The invention relates to a method for modeling an input current of a pump (110). The method comprises the steps of: (i) controlling the pump (110) to pressurize at least a portion of the evaporation system (100), (ii) determining a pressure profile in the evaporation system (100); and (iii) modeling a curve (350) of the input current of the pump (110) on the basis of the pressure curve by means of a model. The invention also relates to a corresponding controller (120).

In a method for checking a vehicle's braking system for leaks, a braking request is detected when the vehicle is stationary. The braking request is modified by means of a predetermined pressure curve which includes a pressure above a detection threshold value, and an electrofluidic pressure-generating unit is controlled with the predetermined pressure curve. Pressure values associated with a first and / or second brake circuit are detected and compared with the predetermined pressure curve, wherein deviation values are determined. Fault indications are detected if at least one deviation value exceeds a predetermined threshold value.

The application relates to the technical field of carbon fiber die forming of automobile hubs, in particular to a production control system and method for carbon fiber die forming of automobile hubs, which comprises a pressure coordination control module, a temperature field dynamic adjustment module, a defect prediction and compensation module and a multi-source data tracing module. Through segmented pressure curve and temperature-pressure coupling control, combined with multi-source data collected by a distributed sensor array, accurate regulation and control and abnormal tracing in the forming process are realized. The deformation compensation and exhaust control submodule improves process stability, and space-time data modeling locates the root cause of the abnormality, thereby ensuring product quality. Through the cooperative design of hardware and algorithms, the application solves the problems of poor material characteristic adaptability, unstable deformation control and low process quality tracing efficiency, and improves the precision and reliability of carbon fiber hub production.

The application provides a train emergency braking system performance degradation trend detection method, device and medium, the method collects brake cylinder pressure in each emergency braking process in real time, forms brake cylinder pressure curves of each emergency braking, extracts characteristic values of brake cylinder pressure curves of each emergency braking, calculates degradation factors of each emergency braking according to predetermined characteristic reference values and characteristic values of each emergency braking, and detects train emergency braking system performance degradation trend according to the degradation factors of each emergency braking. The method of the application is based on brake cylinder pressure in each emergency braking process, calculates degradation factors of each emergency braking, detects train emergency braking system performance degradation trend according to the degradation factors of each emergency braking, improves the accuracy of degradation detection, realizes continuous monitoring of braking system performance, and improves the safety of train travel and maintenance efficiency.

The invention is suitable for the technical field of parameter optimization, and particularly relates to a ball valve body low-pressure casting pressure curve self-adaptive optimization method and device, and the method comprises the steps: obtaining condensation data corresponding to a valve body main bearing structure region in a first low-pressure casting stage and a hot spot gradient distribution characteristic in a second low-pressure casting stage; composite structure data associated with the main force bearing structure area of the valve body is determined; determining a space mapping relation according to the condensation missing data, the hot spot gradient distribution characteristics and the composite structure data; determining liquid feeding data of the transition area of the composite structure based on the expansion characteristic of the valve body; phase change pressure data is constructed according to the casting process through the pressure-bearing sealing performance of the valve body and the viscosity-temperature characteristics of molten metal; determining optimization data based on the space mapping relation, the liquid feeding data and the phase change pressure data; according to the self-adaptive optimization method for the low-pressure casting pressure curve of the ball valve body, the problems of splashing gas entrapment caused by high pressure of a thin-wall area and shrinkage porosity caused by low pressure of a thick-wall area are reduced.

The invention discloses a drug-coated prostate balloon dilatation catheter control system, relates to the technical field of medical instruments, and aims to solve the technical problems of uncontrollable drug release, extensive dilatation process and lack of quantitative evaluation in existing drug balloon therapy. The system integrates a high-precision pressure sensing module, a micro piezoelectric pump control module, a man-machine interaction module and a data processing module. The system carries out real-time closed-loop control on the internal pressure of the balloon through a self-adaptive PID algorithm, and precise execution of a preset pressure curve is achieved. The innovation of the method lies in that a drug release quantitative estimation model based on pressure-time integration (AUC) is created for the first time, the model can calculate and display the estimated drug release amount in the treatment process in real time, and physical operation parameters are directly associated with biological effects; the device has the effects of realizing accurate and constant control of the dilatation pressure and improving the operation safety.

The present disclosure provides to generate ground truth data for training a machine learning (ML) model to infer pressure information (e.g., a pressure curve, a pressure ratio, or the like) for a cardiac artery from border segmentations generated from images of the cardiac artery. The ground truth data can comprise vessel and / or lumen segmentations for several cardiac arteries and associated pressure information for the cardiac arteries. The vessel and / or lumen segmentations can be generated from images from different image modalities (e.g., IVUS, angiographic, CT, etc.). Further, some of the associated pressure information can be based on measured pressure information (e.g., using a pressure sensing catheter) while other associated pressure information can be derived from the vessel and / or lumen border segmentations using numerical analysis techniques (e.g., CFD, or the like).

The invention discloses a thermal deformation control method for hot gas bulging forming of ultrahigh-strength steel. According to the method, the temperatures of a fillet area and a central area of a mold are controlled to be lower than the temperature of a non-deformation supporting area in the axial material supplementing and radial forming stage; bulging is conducted through a dynamic air pressure curve, the strain rate is inversely calculated in real time based on the wall thickness measured through laser, and the strain rate is stabilized within the critical range through closed-loop feedback; meanwhile, the temperature of the pipe blank is monitored in real time through a thermal infrared imager and compared with a target value, and the deviation is controlled within + / -5 DEG C by adjusting a mold temperature control unit; according to the method, the dynamic air pressure curve is introduced and is cooperatively controlled with the strain rate in real time, so that the deformation rate of the material in the whole bulging process is always stabilized in the optimal critical plasticity interval, the deformation capacity of the ultrahigh-strength steel at the high temperature can be fully exerted, the uniformity of wall thickness distribution of a component can be greatly improved, and the deformation rate of the ultrahigh-strength steel at the high temperature can be improved. And local excessive thinning or fracture caused by out-of-control strain rate is avoided.

The invention relates to the technical field of book binding machinery, in particular to book double-fillet cutting equipment based on image recognition and a working method.The book double-fillet cutting equipment is characterized in that a to-be-cut book is placed on an operation table, an operator puts the hand into a guide groove of the operation table, the to-be-cut book is pushed forwards, and then the to-be-cut book is cut; after the image acquisition unit determines that the to-be-cut book reaches a preset position, the equipment is started, the upper pressing plate is pressed downwards to complete one-time double-fillet cutting of the to-be-cut book, and whether the to-be-cut book is cut qualified or not is judged according to a fitting value and fillet defect parameters; selecting a cutting strategy for the unqualified to-be-cut book, including secondary cutting of the book after the primary cutting; according to the book cutting device, the guide groove is formed, the dislocation problem of the to-be-cut book is solved, and through cooperative judgment of the pressure curve fitting value and the fillet defect parameters, the cutting quality is accurate, and the percent of pass of cut products and the cutting efficiency are improved.

This invention discloses an intelligent calculation method for the thermal compression ratio of a diesel engine based on machine learning, comprising the following steps: S1, acquiring diesel engine thermal operation data and generating a state data sequence; S2, performing continuous-time state encoding on the state data sequence to construct a state representation sequence; S3, performing feature contribution analysis on the state representation sequence to generate a correlated feature sequence; S4, performing state correlation propagation and compression ratio optimization calculation on the correlated feature sequence to obtain a predicted compression ratio sequence; S5, constructing a theoretical pressure curve and an in-cylinder pressure curve based on the predicted compression ratio sequence, and calculating the curve deviation sequence; S6, performing feedback updates based on the curve deviation sequence and outputting the calculation results. This invention, combined with dual-state flow liquid neural networks, possesses advantages such as strong adaptability to thermal engine states, high accuracy in compression ratio calculation, high stability in complex operating condition analysis, and strong continuous dynamic optimization capability.