17results about How to "Status accurate" patented technology

The invention relates to a distributed intelligent rice transplanter cluster navigation method based on deep reinforcement learning and speed obstacles, which comprises the following steps: acquiring a reciprocal speed obstacle and a speed obstacle vector, inputting the reciprocal speed obstacle and the speed obstacle vector into a BiLTSM network model, and acquiring an environment perception vector; the BiLTSM network model is obtained through training of a training set; and combining the environment perception vector with an ontology perception measurement value to generate an observation space, and setting a reward function for iteratively updating a multi-intelligent-vehicle obstacle avoidance strategy so as to optimize driving control of an individual level in an intelligent vehicle cluster and generate an optimal navigation scheme. The method still faces many challenges in application in the agricultural environment, the defects in the aspects of environment state representation, action mapping and reward design are overcome, and the problem of multi-machine collision avoidance in the complex dynamic environment is effectively solved.

This invention discloses a method, system, device, and storage medium for early warning of power battery degradation. The method includes: determining a usable energy state boundary threshold and a capacity absolute deviation boundary threshold based on current vehicle usage parameters, including equivalent mileage and service life; comparing and analyzing the current power battery state parameters with the usable energy state boundary threshold and the capacity absolute deviation boundary threshold to output analysis results; generating corresponding early warning information based on the analysis results; and, by fusing the comparison results of the two key parameters, outputting the true degradation state, pseudo degradation state, good state, or normal state with a degradation trend of the power battery according to a preset strategy, and generating corresponding maintenance, repair, or normal prompt information. This invention can accurately identify the degradation state of power batteries, effectively avoid misjudgment, and provide reliable technical support for the safe operation and maintenance of electric vehicles.

The application provides a seven-day period factory cyclic Megalobrama amblycephala fry behavior domestication method and system, relates to the Megalobrama amblycephala breeding technical field, and includes: domesticating the fry into a domestication pond on the first day; starting vertical water flow impact before feeding fresh bait fish according to a preset first feeding frequency on the second day; feeding electric shock disabled live bait according to a preset second feeding frequency on the third day; feeding mixed live bait according to a preset third feeding frequency on the fourth day; feeding mosaic bait according to a preset fourth feeding frequency on the fifth day; feeding pure artificial compound feed using a composite feeding mode and starting water flow impact on the sixth day; feeding pure artificial compound feed on the seventh day, and screening domestication successful individuals based on behavior indexes after the period ends, so that the Megalobrama amblycephala is rapidly domesticated from feeding live bait to feeding artificial compound feed.

The invention discloses an on-line electrochemical impedance spectroscopy measurement method and device for a fuel cell and a storage medium, and the method comprises the steps: obtaining an initial value of an influence parameter which influences an EIS test result when the fuel cell is started, the influence parameters at least comprise the stack temperature, the stack voltage, the stack current and the low-frequency impedance; acquiring an actual measurement value of the influence parameter when the fuel cell runs; determining a target output value of each influence parameter according to the initial value of each influence parameter and the measured value of each influence parameter; and coupling the target output values of the influence parameters to obtain a high-frequency impedance value. By adopting the method, accurate online EIS diagnosis can be realized, and the diagnosis reliability of the battery state is improved.

The invention discloses a power grounding state monitoring method and system, which is applied to the field of power equipment state monitoring, and comprises the following steps: synchronously obtaining a time sequence mechanical state signal and a time sequence electrical state signal of a grounding terminal; extracting and constructing a multi-dimensional feature vector containing static and dynamic feature components; performing differentiation evaluation and integration on the feature components by using a pre-constructed hybrid analysis model to generate an initial monitoring result; and introducing environmental parameters to dynamically calibrate the initial result to obtain a calibrated grounding state monitoring result. According to the electric power grounding state monitoring method provided by the invention, the mechanical tightness and the electrical connectivity information are fused, and the intelligent model is adopted to carry out collaborative analysis and environment adaptive calibration, so that the comprehensive and accurate sensing of the connection state of the grounding terminal is realized.

This utility model provides a device for indicating the operating status of an equipment and a control box, relating to the field of electrical automation, including: an indicator unit for indicating the status based on an indicator voltage; and an anti-interference unit for filtering the indicator voltage input to the indicator unit, wherein the anti-interference unit is connected in parallel with the indicator unit.

The present application relates to a kind of biological sample molecular subtype classification method based on multi-modal layered attention network, comprising: obtaining sample data to be measured and pre-processing;With the molecular subtype classification model of pre-processed sample data to be measured, by single-mode local feature extraction, cross-modal multi-view correlation, priori knowledge guided dynamic gating and dense feature aggregation strategy, output molecular phenotype classification probability, the molecular phenotype classification probability is compared with threshold value to determine molecular subtype class.The present application can overcome the limitations of the existing biological omics and other multi-source heterogeneous data fusion classification methods, such as shallow feature interaction, dimension easy to explode, and ignoring the guidance of sample macroscopic prior knowledge.

This invention discloses an online performance estimation method for fuel cell stacks based on the fusion of multiple models and algorithms, comprising the following steps: obtaining the physical parameters of the fuel cell stack; constructing N voltage estimation models for the fuel cell stack based on the physical parameters; sampling M parameter estimation algorithms to solve the voltage estimation models of the fuel cell stacks, obtaining the constant term coefficients of the voltage estimation models for MN groups of fuel cell stacks; based on a fitness evaluation system, achieving adaptive estimation of the constant term coefficients of the voltage estimation models for the N fuel cell stacks, determining the most matching parameters and corresponding algorithm weights for the current fuel cell operating range; and achieving online estimation of the voltage and power of the fuel cell stack based on the most matching parameters and corresponding algorithm weights for the current fuel cell operating range. This invention improves the accuracy and robustness of parameter estimation across all operating conditions and the entire life cycle, while controlling computational complexity to meet the requirements of real-time applications.

This invention discloses a battery life prediction method and system based on a multi-scale state-space model, belonging to the field of battery health management technology. The method includes acquiring battery operating data; calculating relative characteristics at various time scales based on the operating data; generating a battery identification code based on the battery's specifications and attribute characteristics; inputting the relative characteristics at each time scale and the battery identification code into a multi-scale state-space model for fusion and processing; and outputting the battery life prediction result and health status assessment. This invention can simultaneously process batteries of different models, capacities, and production batches, significantly reducing model deployment and maintenance costs; through multi-scale feature fusion and physical constraints, it provides more accurate life prediction and health status assessment; the model output used in this invention includes degradation mode classification and uncertainty estimation, providing users with more comprehensive decision support.

The invention belongs to the technical field of flexible direct valve control power supply control, and discloses a flexible direct valve control power supply control system and a control method.The flexible direct valve control power supply control system is characterized in that a plurality of auxiliary function board cards, a power board and a CPU board connected with a far-end control unit are integrated in a valve control case, and the auxiliary function board cards are connected with the power board through a power bus for power supply; the remote control unit is respectively connected with a power supply control unit, and each power supply control unit is connected with the CPU board through a power supply control bus, so that the remote control unit can independently control each power supply control unit to execute power supply operation through the CPU board. According to the system, the power supply control unit is built in and is directly associated with each auxiliary function board card, and after the CPU board receives a remote instruction, each unit is accurately regulated and controlled through the power supply control bus, so that independent management of a specified board card power supply is realized, and control logic can be completed without an external module. By adopting the system, additional configuration of an external module is avoided, the system structure is simplified, the cost is reduced, and refined independent control of a specific board card power supply in the valve control system is realized at the same time.

The application relates to an axial motor control board, a method, a computer device and a storage medium. The application sets a double processing architecture of a main control chip and a coprocessor in the axial motor control board. The main control chip is responsible for system scheduling, fault diagnosis and data management, so that the control board can still maintain stability under multi-task operation. The coprocessor is dedicated to executing high real-time tasks such as current decoupling, matrix calculation and coordinate transformation in the field-oriented control algorithm, so as to improve the dynamic response performance of the current loop and the speed loop. Precise motor state sensing and closed-loop control can be realized, and the control instruction transmission and operation data storage are more reliable through unified communication framework cooperation, so that the control precision, response speed and operation stability of the axial motor are effectively improved, and the reliability and safety of the control system under complex working conditions are enhanced.

The application discloses a mobile labor-saving folding welding workbench and belongs to the technical field of welding tool equipment. In view of the problems that the existing welding workbench needs side turning operation, is labor-consuming and has safety hidden dangers when being folded, the application provides a workbench which can be automatically and slowly folded in a standing state. The workbench comprises a table panel, two groups of supporting foot supports hinged to the lower end of the table panel, a synchronous rotating structure, a locking and energy releasing delay device and a fixable roller. The synchronous rotating structure is connected with the two groups of supporting foot supports through a gear driving assembly, a connecting shaft and a driving handle, and can drive the two groups of supporting foot supports to be synchronously folded or unfolded. The locking and energy releasing delay device comprises a preliminary braking structure and an energy storage locking structure. The preliminary braking structure is preliminarily locked through the friction force between a braking block and the connecting shaft, and the energy storage locking structure accumulates energy through an energy storage spring and drives the supporting foot supports to be automatically folded after being unlocked. The operator only needs to assist in supporting and does not need to bear the weight of the workbench.

The invention provides an electric heating shawl temperature control method and system based on multiple safety protection, and relates to the technical field of intelligent temperature control. Controlling the temperature through a mechanical temperature control switch until the temperature is less than or equal to a first preset temperature; an NTC resistance value is obtained in real time through an NTC temperature sensor; calculating the change rate and the temperature rise slope of the NTC resistance value through a fault diagnosis algorithm; according to the change rate and the temperature rising slope, whether the temperature variation is larger than a second preset temperature or not is judged, output of a silicon controlled rectifier of the electric heating shawl is cut off, and sound-light alarm is conducted through flickering of an indicator lamp or a buzzer; acquiring a voltage signal of the electric heating shawl; converting the voltage signal into a temperature signal by simplifying a three-parameter equation; and controlling the temperature signal to be less than or equal to a third preset temperature through an NTC temperature sensor and a silicon controlled rectifier so as to realize accurate constant-temperature control.

This invention discloses a lemon health analysis method, relating to the fields of intelligent agricultural monitoring and plant health diagnosis. It involves acquiring continuous images of lemon plants using a hyperspectral camera, and then using these images to detect changes in a dynamic differential spectral segmentation model. Sequence modeling is performed on the pixel-level multi-band spectral data. An adaptive motion-aware scheduler automatically suppresses loss when the proportion of motion change mask pixels exceeds a preset dizziness threshold to avoid background misjudgment, generating a pixel-level dynamic change map. This is compressed into a pathological dynamic state vector using a variational autoencoder, and end-to-end training is performed with action-conditional video prediction as the training objective. In the extrapolation phase, a recurrent dynamic model is used to perform multi-step imaginative prediction based on candidate action sequences, outputting the future evolution trajectory of the pathological dynamic state vector and generating a quantitative early warning or decision simulation report on the outbreak risk level. The system also includes change type classification and model closed-loop optimization functions.

The invention relates to the technical field of energy storage batteries, in particular to an energy storage battery aging analysis method based on adaptive transfer learning, which comprises the following steps: extracting a voltage capacity peak position migration path structure, analyzing a frequency modulation instruction and a current response difference to obtain a frequency modulation working condition fluctuation degree, and adjusting mapping to calculate a cross-domain feature migration correlation degree. Evaluating the influence of trajectory offset, updating the correlation weight, comparing the consistency of capacity change, judging the aging evolution stage, and outputting a battery health state index. According to the method, a differential capacity curve peak position migration path structure is screened through a terminal voltage and capacity change relation, the fluctuation degree of an operation section is analyzed in combination with the output power of the converter, a feature migration confidence coefficient weight and a mapping correlation structure are dynamically adjusted according to a track offset relation, and key parameter fluctuation characteristics under complex working conditions are captured. The limitation that a static reference is difficult to adapt to a changeable environment is effectively overcome, and accurate positioning and state judgment of the battery in the health evolution stage are achieved under the continuously fluctuating operation background.

The application discloses a virtual RDMA device based on DPDK and a use method thereof. The virtual RDMA device based on DPDK comprises a front-end virtio-rdma device, which is used for receiving an RDMA device operation request initiated by an application program in a virtual machine, encapsulating the request as an instruction conforming to a virtio protocol, and sending the instruction to a back-end vhost-user- rdma device through a vring; and the back-end vhost-user- rdma device is used for simulating the function of a real RDMA network card, the device can acquire and analyze the instruction conforming to the virtio protocol from a circular queue vring, execute corresponding RDMA device operations, and return the operation results to the front-end virtio-rdma device through the vring. The application can get rid of the dependence on the real RDMA device, and can improve the resource utilization, system flexibility and safety.

The invention discloses a magnetic suspension bearing suspension force and zero sequence current decoupling control system, particularly relates to the technical field of magnetic suspension, and comprises a four-bridge-arm inverter module, a double closed-loop control unit, a multi-source sensing acquisition module, a power driving module and a magnetic suspension bearing body. According to the decoupling control system for the suspension force and the zero-sequence current of the magnetic suspension bearing, the fourth bridge arm connected with the neutral point of the three-phase winding is additionally arranged, an independent zero-sequence current loop is constructed, and zero-sequence current closed-loop control based on the alpha-beta O coordinate system is matched, so that the suspension force and the zero-sequence current of the magnetic suspension bearing are decoupled. Zero-sequence current generated by three-phase imbalance, parameter asymmetry and magnetic field distortion in a traditional three-phase inverter architecture can be pertinently dredged and suppressed; and the fourth bridge arm adopts a SiCMOSFET power switch device and fly-wheel diode combined design, so that a compensation instruction can be quickly responded, winding current distortion caused by superposition of zero-sequence current to working current is avoided, and a linear control relationship between suspension force and current is guaranteed.