14 results about "Parameter error" patented technology

The application discloses a kind of T type three-level converter open-circuit fault diagnosis method with strong robustness, belong to the field of power electronic equipment fault diagnosis, to distinguish different switch similar open-circuit fault characteristics and accurately locate open-circuit fault tube.Considering different modulation strategies and modulation modes, the phase voltage residual is generated through the phase voltage model, so as to extract the fault characteristics of the converter under various open-circuit faults.Analyze the influence of factors such as parameter error, dead time and delay time of the system on the phase voltage vector residual, and the adaptive residual vector amplitude threshold based on uncertainty propagation theory.A hierarchical fault diagnosis scheme is proposed, which can locate the group-level open-circuit fault according to the voltage residual vector amplitude and angle, switch the three-level modulation mode of all phases of the converter to two-level mode, to further identify the specific fault switch from the fault group.A reasonable balance between robustness and speed can be achieved, and the complexity and adaptability of the diagnosis algorithm are fully considered.

The invention discloses a speed reducer production test test method and system, and relates to the field of speed reducer performance test. The method is applied to a speed reducer testing system, and comprises the following steps: obtaining a to-be-tested parameter type and a customized working condition of a to-be-tested speed reducer; performing parameter error traceability analysis on the to-be-tested parameter type to obtain various error sources of the to-be-tested parameter type; performing error testing on the to-be-tested speed reducer under a preset orthogonal working condition to obtain an error contribution degree sequence of the to-be-tested speed reducer; testing the to-be-tested parameter type of the to-be-tested speed reducer under the customized working condition to obtain test data of the to-be-tested speed reducer; based on the error contribution degree sequence of the to-be-tested speed reducer, correcting the test data of the to-be-tested speed reducer to obtain corrected test data of the to-be-tested speed reducer; and judging and outputting a test result of the to-be-tested parameter type based on the corrected test data of the to-be-tested speed reducer. Therefore, the qualification test reliability of the miniature speed reducer at present is improved.

1. Name of this design: Graphical User Interface for Error Values ​​of Key Electrical Parameters in a Semiconductor Device Model. 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are its graphical user interface. 4. Images or photos that best illustrate the design points: Interface change state diagram 12. 5. Standard design, omitting rear view, top view, bottom view, left view, and right view. 6. Purpose of the graphical user interface: To display the simulation target error value during the extraction of semiconductor device models. 7. Human-computer interaction method of graphical user interface: Upon opening the software, the main view appears. Click the first button "File" in the first row from the top of the main view (from the left). A window to load the model file will pop up, leading to state 1. Select the model file and click "Open" to load it. After loading the model file, state 2 will appear. Click the third orange button in the second column of the "Load" box in the upper left corner of state 2 to load the data file, leading to state 3. Select the data file and click "Open" to load it. After loading the data file, state 4 will appear. Click the second button in the first row of the "Show" box in the upper left corner of state 4 to enter state 5. Click the first button in the upper left corner of the spec window in state 5 to load the configuration file, leading to state 6. After loading the configuration file, state 7 will appear. Click the sixth button "Err" in the first row of the spec window in state 7 to enter state 8. (The last sentence appears to be a continuation of the previous paragraph and is left untranslated.) Place the mouse cursor over the corresponding bar in the window to enter the interface change state diagram 9, and click to display the corresponding data; in the interface change state diagram 9, use the mouse to select the selectable box on the right to enter the interface change state diagram 10. Click the "refresh" button on the spec window in interface change state diagram 10 to enter interface change state diagram 11. Double-click the orange border at the top of the spec window, and the window will pop up separately, entering interface change state diagram 12.

The application discloses a kind of based on the task cooperation management method and system of offline application, it is related to offline data management technical field, the method includes: determining task cooperation type, and obtaining collaborative task resource package;Task cooperation system environment is generated based on collaborative task resource package;Receive collaborative data, the modification probability of collaborative data is predicted by the prediction model pre-trained in collaborative task resource package, and the collaborative data of high-risk prediction result is early warning and checking;According to the compression packing of collaborative data according to collaborative task type, and when restoring network connection, the packaged collaborative data is executed upload by priority scheduling mechanism.The fusion technical scheme of intelligent matching resource package, generating system environment with edge computing, pre-training model early warning and checking, priority scheduling upload effectively reduces resource package mismatch and parameter error rate, while reducing upload delay, improves offline cooperation efficiency and data reliability.

The application provides a power grid bad parameter identification and correction method based on synchronous phasor measurement. State estimation based on PMU measurement can realize high-resolution real-time detection and state evaluation of the power grid. In view of the problem that parameter errors and bad measurement values are difficult to distinguish and identify in the PMU state estimation of the power system, the theory and method of unified identification and correction of bad parameters and bad measurement values are studied by using regularization Lagrange multipliers and residuals, and an improved strategy for improving the distinguishability of bad parameters is provided.

The invention provides a partitioned precise temperature control management system and equipment for a multi-channel refrigerating unit, and the system comprises a system self-inspection module which carries out the integrity inspection and function verification when the equipment is powered on; the data acquisition module is used for acquiring three-channel temperature data and temperature of key points of the circulating system; the parameter error calculation module is used for comparing the collected real-time temperature data with target parameters and generating an adjusting instruction; the PID control adjusting module is used for generating a control signal and driving each execution mechanism of the temperature control equipment to realize temperature control; and the shutdown control module executes hierarchical shutdown to ensure that the equipment is stably stopped. According to the method, the topological connection relation of the three-channel pipeline system is defined as the error term incidence matrix, the influence weight between any two error terms is quantified, meanwhile, the correlation influence background value is calculated, the degree that each error term suffers from other errors in the system is accurately evaluated, and therefore when the system generates a control instruction, the control accuracy of the system is improved. And the overall stability of multi-channel parallel temperature control is ensured.

The embodiment of the invention provides a core particle verification method and device, a medium, a core particle and a computing system, and relates to the technical field of chips. The core particle verification method can be applied to a verification module, and the verification module comprises a preset verification model and a data acquisition interface connected with a tested module in a core particle. The core grain verification method comprises the following steps: acquiring a target message that a core grain communicates with other core grains through a tested module, wherein the target message is a message conforming to a general core grain interconnection standard; under the condition that the target message meets a preset condition, collecting algorithm data of a target calibration algorithm executed by the tested module in a link training process through a data collection interface; and verifying the target calibration algorithm according to the verification model and the algorithm data to obtain a verification result of the target calibration algorithm. Therefore, the calibration algorithm can be verified, and algorithm logic or parameter errors can be found in time, so that the reliability of core particle verification is improved.

The invention belongs to the technical field of data processing. According to the enterprise annuity payment automatic matching bookkeeping method and system, the process is initialized, parameter legality is verified, accurate starting of the process is ensured, and the problem of process interruption caused by parameter errors is solved; matching group modes are judged and processed according to different modes, and the limitation that different matching scenes cannot be flexibly coped with in a traditional method is overcome; automatic matching and batch accounting are combined, so that the processing efficiency is improved, and complexity and errors of manual operation are avoided; the introduction of the anonymous artificial matching process ensures the flexible response when the automatic matching fails, and avoids the business stagnation.

The invention discloses a guidance method for realizing multiple constraints of a falling point trajectory inclination angle and a pitching angle. The guidance method comprises the following steps: designing an overload controller instruction parameter; when the distance between the aircraft and the target is smaller than a first threshold value, an inclination angle tracking stage is started, a first attack angle instruction is calculated according to the deviation between the current trajectory inclination angle and the target trajectory inclination angle and an instruction correction value obtained according to aircraft state design, a first overload instruction of an overload controller is calculated, and inclination angle control is achieved; and when the distance between the aircraft and the target is smaller than a second threshold value, entering an attack angle tracking stage, calculating a second attack angle instruction according to the target attack angle instruction and the instruction correction item when the parameter error is considered, calculating a second overload instruction of the overload controller, and realizing pitch angle control. Ballistic inclination angle and pitch angle constraints are converted into attack angle constraints, overload instructions of overload controllers in the inclination angle tracking stage and the attack angle tracking stage are calculated respectively, and guided flight of two drop point constraints of the ballistic inclination angle and the pitch angle is achieved.

The present application relates to the technical field of fringe reflection detection and deep learning cross, and specifically provides an error decoupling method suitable for a fringe reflection detection system, two kinds of light spot distribution data containing different errors are generated through a light ray tracing method, and the light spot distribution data is subtracted from ideal light spot distribution data of a mirror to be measured to obtain light spot distribution offset samples, training data set A and training data set B are constructed; a deep learning network with double output branches is constructed, two-stage training is adopted, the first branch is trained by using the training data set A in the first stage, and a predicted structure parameter error is output; the first branch and the second branch are jointly trained by using the training data set B in the second stage, a predicted structure parameter error is output through the first branch, and a predicted surface shape error is output through the second branch; the light spot distribution offset data is input into the trained deep learning network, and the predicted structure parameter error and the predicted surface shape error can be obtained.

An antenna calibration method, system, and apparatus are disclosed. In the method, at least one first metasurface element is located along the path of a signal transmitted by the first antenna element. A control module acquires first error information indicating parameter errors in the signal transmitted by the first antenna element. Based on the first error information, the electromagnetic response of at least one first metasurface element is adjusted to calibrate the parameters of the signal transmitted by the first antenna element. Thus, a mechanism for calibrating the parameters of the signal transmitted by the first antenna element is provided, which can improve antenna calibration performance.

The invention relates to a fault prediction method and apparatus, a device, a medium and a product. The method comprises the steps of obtaining operation data of a target device at a current moment; determining a distribution parameter prediction value of the target equipment at the next moment of the current moment according to the operation data; determining a distribution parameter error value of the target equipment at the next moment according to the distribution parameter predicted value of the target equipment at the current moment and the distribution parameter actual value of the target equipment at the current moment; determining a distribution parameter target value of the target equipment at the next moment according to the distribution parameter predicted value of the target equipment at the next moment and the distribution parameter error value of the target equipment at the next moment; and according to the distribution parameter target value, determining whether the target equipment has a fault at the next moment. According to the invention, whether the target equipment has a fault at the next moment can be accurately determined, so that fault maintenance can be carried out on the target equipment in time, and normal work of the target equipment can be recovered in time.

The application discloses a modal force hammer dynamics test modal parameter error calibration method, relates to the technical field of error calibration, and comprises the following steps: obtaining a collision angle interval based on a pendulum hammer type calibration device; obtaining a collision correlation surface of the collision angle interval by using a multi-impact analysis method; and performing error calibration on obtained modal parameters based on the collision correlation surface and a release angle of a modal force hammer. The application is used to solve the problem that, in the existing modal force hammer dynamics test modal parameter error calibration method, the rebound buffer after pendulum hammer impact cannot be accurately controlled for a soft rubber hammer head, impact data is discrete in multiple calibrations, the modal parameters of the rubber hammer head after pendulum hammer impact cannot be effectively obtained, and thus the calibration precision is affected and the parameter calibration error is increased.