13 results about "Rate curve" patented technology

The invention provides a control method and system for dispensing type coupling equipment, and the method comprises the steps: simulating the glue discharge process of a dispensing head according to a dynamic glue discharge rate curve, and analyzing the fluid dynamic parameters of the glue discharge process to obtain the initial form of glue drops and the evolution trend of the necking process; if the wiredrawing effect occurs in the necking process of the glue drops, adjusting the slope of the glue discharge rate curve, and judging whether the wiredrawing effect still exists in the target glue drop form or not according to the adjusted glue discharge plastic curve; if the wire drawing effect still exists, the dispensing time, the dispensing pressure and the distance between the dispensing head and the working surface are adjusted by combining the rheological property of the glue; the glue outlet rate curve and the glue flow model are iteratively optimized, a target glue outlet rate curve for inhibiting the wire drawing effect and glue parameters are determined, and the glue parameters comprise viscosity, surface tension and density.

Techniques for generating a predicted win rate curve without using loss data are disclosed. An example method includes receiving historical transaction data comprising a plurality of transactions, each transaction comprising a plurality of attributes. The method also includes processing the historical transaction data to generate training data comprising features extracted from the plurality of attributes. The method also includes training, by a processing device, a logistic model using the training data and a predicted price. Training the logistic model includes providing the predicted price and a subset of the features at an input layer of a neural network and training the neural network to generate a mapping from the predicted price and the subset of the features to parameters of a predicted win rate curve generated at an output layer of the neural network.

This invention discloses a twin simulation method for rotor system slippage considering the uncertainty of flexible supports. First, flexible support components such as flexible bearing housings and flexible couplings are respectively equated as spring-damped units, and the baseline values ​​of equivalent support state parameters are obtained based on static analysis. Second, a rotor system thermo-fluid-structure interaction (TSH) simulation model considering the flexible support state is constructed based on the rotor system dynamics simulation model and thermo-elasto-fluido-lubrication coupling analysis. Then, multi-domain simulation data and multi-domain experimental data are collected under the same time-varying slippage operating conditions, and a slippage consistency metric is constructed based on the time-frequency statistical characteristics of the multi-domain information to calculate the slippage sensitivity. Finally, the uncertainty of the flexible support component state parameters is described based on cross-correlation Bayesian methods, and the identified flexible support state parameters are substituted into the established rotor system TSH simulation model to obtain slippage rate curves under different time-varying operating conditions.

To consider grades of products and relations of generation, predict transition of a price after sales on the basis of a predetermined parameter, predict revenue during a predetermined period from the transition of the predicted price, and present a prediction parameter in which the revenue is stabilized and maximized.SOLUTION: A price transition prediction device predicts transition of a sales price until a predetermined period is elapsed from start of sales of a product. The price transition prediction device comprises a price curve generation processing unit which determines a price curve for each product grade from candidates of a volatility curve of a price, and a price curve correction processing unit which corrects both price curves at a switching period from an old product to a new product.SELECTED DRAWING: Figure 2

This application proposes a method and apparatus for detecting aspiration. The method includes: acquiring a first flow rate curve and a second flow rate curve, wherein the first flow rate curve is the pumping flow rate curve of the ventricular assist device (VAD) during the first first cycle when running at a target speed, and the second flow rate curve is the pumping flow rate curve of the VAD during the second first cycle when running at the target speed; calculating a target time-domain deviation and a target frequency-domain deviation based on the first and second flow rate curves; and determining whether aspiration exists in the VAD based on the target time-domain deviation and the target frequency-domain deviation. This application improves the accuracy of aspiration detection by calculating the deviation of the VAD's pumping flow rate in the time domain and frequency domain, respectively.

The invention discloses a mold switching path planning and regulation method based on a rule engine, and relates to the technical field of intelligent manufacturing equipment automation, and the method comprises the following steps: S100, in a cast stone continuous pouring process, collecting a continuous change value of a magma flow rate in a microsecond-level time window, extracting an instantaneous transition amplitude and a change rate of a flow rate curve, and calculating a flow rate curve; abnormal fluctuation signal features caused by equipment troubleshooting or feed recovery are identified. According to the invention, through microsecond-level flow velocity acquisition and dynamic anomaly identification, unsteady state data is effectively eliminated; the grouting state is accurately judged by combining a real-time trend map and grouting weight feedback; a path freezing mechanism prevents mistaken switching, a disturbance learning model enhances adaptivity, and a dynamic closed-loop control system is constructed. According to the overall scheme, the mold switching judgment precision and the system stability are remarkably improved, the pouring quality and the production continuity are guaranteed, and the good engineering application value and the good popularization prospect are achieved.

The invention discloses a sampling carriage management system based on railway bulk grain, relates to the technical field of sampling carriages, solves the problem that an original processing mode is not comprehensive enough, comprehensively considers unloading rate curves of multiple sections of associated carriages in the same batch through a sampling carriage calibration end, and obtains the unloading rate curve of the multiple sections of associated carriages in the same batch through rigorous mean value calculation and difference value comparison. Sampling carriages are reasonably calibrated, the influence of grain impurity factors on the unloading rate is fully considered, it is guaranteed that the selected sampling carriages are extremely representative, the accuracy of subsequent quality inspection data is greatly improved, and quality misjudgment caused by wrong sampling is avoided; and the associated data analysis end focuses and samples a carriage unloading rate curve, accurately locks the maximum difference section and the corresponding characteristic quantity interval, clearly presents an unloading speed abnormal area in the carriage, provides targeted sampling guidance for an operator, can rapidly position a key area for sampling, improves the characteristic of the sample, and makes a quality inspection result more reliable.

The invention discloses a stratigraphic structure analysis method and device based on a speed change rate curve, and the method comprises the steps: carrying out the preprocessing of micro-motion data, obtaining the pre-processed micro-motion data, and dividing the pre-processed micro-motion data into a plurality of micro-motion data segments with the consistent time duration; frequency dispersion characteristics of the multiple micro-motion data segments are extracted based on a spatial autocorrelation method, a frequency dispersion curve is generated based on the frequency dispersion characteristics, and a speed curve is generated based on the frequency dispersion curve; performing first-order derivative calculation on the speed curve to obtain a speed conversion rate curve; three initial inversion models are constructed based on the speed transformation rate curve; the three initial inversion models are optimized on the basis of the speed change rate curve, the optimized three initial inversion models are fused to obtain a stratum structure analysis model, stratum structure analysis is performed on the basis of the stratum structure analysis model, and the inversion precision of the inversion model is improved by generating and analyzing the speed change rate curve. And the reliability of a stratigraphic structure analysis result is obviously improved.

The application provides a gas filling whole-process data driving optimization method and system and a storage medium, which comprises the following steps: constructing constraint conditions with safety pressure boundary and pressure change rate as cores by monitoring pressure and temperature in real time and calculating state entropy increase gradient; generating an initial filling rate curve by using a generative adversarial network; combining the constraint, efficiency and equipment loss to perform multi-objective evaluation on a discriminator of the network, and adjusting a safety weight in real time according to the entropy increase gradient; and smoothing and optimizing the curve by wavelet transform and nonlinear Kalman filtering, wherein the decomposition layer number and the filtering parameter are both associated with the entropy increase gradient, so that a stable and safe execution rate curve is generated, and intelligent closed-loop control of the filling process is realized.

The invention provides a unit coordination control system and method for a thermal power generating unit, and relates to the technical field of thermal power generating unit coordination control. A prediction model is obtained through a historical load curve, and a real-time load curve is input into the prediction model to obtain a load prediction curve; according to the method, a standard power curve and a power increase rate curve of each single set of power generation equipment in the thermal power generating unit are obtained, a power control curve of each single set of power generation power is set, meanwhile, limiting conditions are set to be solved in MATLAB, cooperative control over the multiple single sets of power generation equipment in the thermal power generating unit is achieved, and meanwhile the requirements for load increase and increase rate are met; and according to the relationship between the power control curve and the load curve of each single set of power generation equipment, generating a thermal power generating unit state score, and setting a score threshold feedback result, thereby realizing safety guarantee of the continuous working state of the thermal power generating unit.

The application discloses a power distribution area daily line loss rate curve abnormal feature extraction method and system, comprising the following steps: according to the obtained daily line loss rate curve data and area line loss abnormal treatment record work order, an abnormal power distribution area daily line loss rate dataset is constituted; the abnormal power distribution area daily line loss rate dataset is classified according to the abnormal type, and a plurality of abnormal dataset subsets are obtained; local section data of the plurality of abnormal dataset subsets is extracted through a preset scanning window, and local section data corresponding to each abnormal dataset subset is obtained; statistical value features of the local section data are calculated and clustering calculation is performed, a plurality of first abnormal features are obtained; the plurality of first abnormal features are determined according to a self-defined rule, a plurality of second abnormal features are screened out, and abnormal features corresponding to each abnormal dataset subset in the plurality of abnormal dataset subsets are obtained, thereby improving the universality of abnormal diagnosis.

A wire wheel displacement rate simulation method, comprising the following steps: step 0: establishing a coordinate system, importing action arcs and a slider; step 1: obtaining the stroke between two action arcs; step 2: taking three action points R0, R1 and R2 on the action arc; step 3: obtaining the slider radius OD; step 4: setting the slider displacement distance Y; step 5: obtaining the offset angle of the slider and the arc center of one of the action arcs; step 6: calculating the coordinates of the three action points R0, R1 and R2 on the slider center; step 7: calculating the arc and arc intersection coordinates; step 8: taking P(x0, y0) on the slider, judging the y0 region; step 9: calculating the displacement value Q of the P point in the t time period; step 10: calculating the instantaneous speed through Q / t; step 11: looping to step 9 until the slider completes the back and forth movement; step 12: all instantaneous speed sets are combined to form a speed curve; step 13: combining the lift curve and the return curve to simulate the wire wheel displacement rate curve.

The invention discloses an external pricing model construction method. The model construction method comprises the following steps: confirming an external interest rate curve model; establishing a pricing engine model; establishing a scheme model according to the scheme condition; establishing a business detail data model; and establishing a final result model. The method solves the problem that business personnel do not know how to price products for customers, pricing principles, pricing mechanisms, parameters required for pricing and other information, and can quickly obtain guidance prices by obtaining information according to actual conditions of the customers through the use of an external pricing model and method, so that the practical value is very high, and support is well provided for business influence.