40 results about "Cell Maintenance" patented technology

The invention relates to the field of battery maintenance, and discloses a machine room battery capacity monitoring method and system, and the method comprises the steps: obtaining and preprocessing battery operation and environment data in a machine room, and extracting static and dynamic features from the preprocessed battery operation data; modeling by associating the static characteristics with environmental data to obtain a static health index of the battery, and monitoring a steady-state basic health level; associating the dynamic characteristics with the environmental data under event driving to obtain a battery dynamic response index, and monitoring transient performance response capability; the static and dynamic indexes are fused, historical data are combined, a capacity prediction model is used for analysis, and a current capacity estimation value and an attenuation trend prediction sequence are output; finally, early warning is judged according to the prediction result, and an early warning prompt is generated and output, the whole process aims at comprehensively evaluating the battery state, accurately predicting the capacity and early warning from the static and dynamic aspects by integrating battery operation and environment data, so that stable operation of a machine room is guaranteed, the fault risk is reduced, and a reliable basis is provided for operation and maintenance decision making.

The invention relates to the technical field of battery monitoring, in particular to a battery health state estimation method based on a battery aging system, which is characterized in that an upper computer and a plurality of test nodes are connected through an industrial field bus communication protocol, charge-discharge cycle test is performed on a battery pack, and battery data are acquired in real time; and processing the data by using a protocol analysis engine and a sliding time window technology, calculating a battery capacity fading rate and an internal resistance change rate, and generating a standardized data set. And a health state evaluation model is constructed through a machine learning model, real-time evaluation and visual display of the health state of the battery are realized, and early warning is given out when the health state is lower than a threshold value. The method supports dynamic parameter configuration, adopts a time sequence database to store data, and facilitates full-life-cycle data tracing. According to the invention, multi-dimensional data acquisition, intelligent analysis and safety protection are integrated, the efficiency, reliability and intelligent level of the battery aging test are improved, and a scientific basis is provided for battery maintenance and management.

The invention provides a battery predictive maintenance method based on a self-assembly neural network and a large language model, and relates to the technical field of battery maintenance, and the method comprises the steps: collecting original sensor data corresponding to target battery equipment; inputting the original sensor data into a battery predictive maintenance model obtained by pre-training; wherein the battery predictive maintenance model comprises a self-assembly neural network and a large language model; and extracting initial feature information of the original sensor data, extracting time sequence-space joint features corresponding to the initial feature information through the self-assembled neural network, and generating a battery predictive maintenance report corresponding to the target battery equipment based on a pre-constructed battery maintenance knowledge base and the time sequence-space joint features through a large language model. According to the invention, the prediction precision of battery predictive maintenance can be obviously improved.

A transfection robot that combines bio informatics, robotics and artificial intelligence (AI) in a single package. The transfection robot replaces a large component of the mundane work and increases the quality thereof.

The intelligent control system comprises a three-phase thyristor rectifier bridge, a sampling unit and a master controller, the input end of the three-phase thyristor rectifier bridge is connected with a three-phase alternating current power supply, and the output end of the three-phase thyristor rectifier bridge is connected with the lifting electromagnetic chuck through a switch S1 and connected with a storage battery pack through a switch S2; and the storage battery pack is connected in series with the lifting electromagnetic chuck through the IGBT power switch Q1. According to the invention, the technical problems of unreliable magnetic retention intervention, uncontrollable magnetic force, logic conflict risk, huge volume, storage battery maintenance deficiency and the like of a traditional discrete system are solved, seamless switching between magnetic retention and excitation is realized, and accurate magnetic force control under all working conditions and intelligent maintenance of a storage battery in a full life cycle can be realized; the device has the advantages of high safety, strong reliability, compact structure, low cost and the like.

The present application relates to the technical field of wireless passive sensing, and discloses a differential sensing system for metal crack detection and a quantitative detection method thereof, which comprises an RFID reader-writer and a passive RFID differential sensing tag; the passive RFID differential sensing tag comprises a communication antenna, an RFID chip, an impedance matching network, a planar inductive sensing module, a radio frequency switching module, an energy recovery module and a data processing unit; the impedance matching network is connected between the communication antenna and the RFID chip; the planar inductive sensing module comprises a reference planar inductor and a sensing planar inductor; after double-state alternate sampling of the reference sensing, difference is performed, so that environmental disturbances such as reading and writing distance, sensor posture, multipath and temperature drift are significantly suppressed, and differential noise suppression is realized; the switching module is powered by the energy collection antenna, voltage doubling rectification and charge management module in the energy collection management module, battery maintenance is avoided, and passive operation is realized.

The invention discloses a chemical defined culture medium formula for subculture of CHO-K1 host cells and high expression of an engineering cell strain product of a stable cell line constructed by taking CHO-K1 cells as hosts. The main components of the feed only comprise amino acids, inorganic salts, vitamins, trace elements and other components limited by chemical components. According to the invention, the growth density and motility of the engineering cell strain taking CHO-K1 as the host are improved, the tolerance of cells is increased, the maintenance period of the cells is prolonged, the product expression quantity of the CHO-K1 engineering cell strain is improved, and the cost of the culture medium is greatly reduced.

The invention discloses a female vaginal mucosa cell maintenance preparation and a preparation method and application thereof, and belongs to the technical field of biological agents, the female vaginal mucosa cell maintenance preparation is prepared from dental pulp mesenchymal stem cells, portulaca oleracea polysaccharide, lactic acid, quercitrin, glycerin and stem cell carriers, and vaginal injection paste is obtained by evenly mixing the dental pulp mesenchymal stem cells, the portulaca oleracea polysaccharide, the lactic acid, the quercitrin, the glycerin and the stem cell carriers through a proper amount of deionized water. The purslane polysaccharide and the dental pulp mesenchymal stem cells form a unique synergistic effect, through physical wrapping, the survival rate and delivery efficiency of the stem cells in a vaginal cavity are improved, local inflammatory response is inhibited, a microenvironment is optimized to support directional differentiation of the stem cells into epithelial cells, paracrine activity of the stem cells is enhanced, and repairable factors are released to promote cell-level regeneration. The problem of hormone dependence is solved, deep maintenance of targeted mucous membrane cells is achieved, limitation of an existing therapy is broken through by directly nourishing cells, activating and regenerating, enhancing barrier integrity and maintaining an acidic microenvironment, and an ideal treatment effect is achieved.

The invention discloses a plant leaf reflectivity detector, and aims to accurately measure the reflectivity of a plant leaf so as to evaluate the nitrogen content and guide scientific fertilization. The detector is composed of a main shell, an auxiliary shell, a main control board, a display module, an acquisition mechanism, a handheld shell and the like, an optical system is built through a mechanical structure system, an electrical control system controls AD acquisition, LED start and stop and optical filter wheel rotation, and reflectivity measurement is achieved. The uniquely designed optical filter wheel is made of aluminum alloy, so that the stable operation of the system is ensured; the shell is made of resin materials, so that protection performance is improved, and portability is achieved. The operation process comprises the steps of startup initialization, zero calibration, measurement of a standard whiteboard and plant leaves, and data query and analysis. In addition, the detector has maintenance measures such as regular cleaning, battery maintenance and safe storage, and long-term stable operation is ensured.

The application provides a battery maintenance method, system and medium. The method comprises: acquiring battery data of a battery management system and performing an electrochemical impedance spectrum scan; estimating an SOH value of the battery based on the battery data and the impedance spectrum scan result; adaptively setting a frequency and a duty cycle of a pulse current used for maintenance based on the SOH value and a battery temperature; and applying a high-frequency pulse current to the battery based on the set frequency and duty cycle, and maintaining the battery according to a multi-stage charging and discharging protocol. The embodiments of the application can improve the service life and safety of new energy batteries.

The invention provides a supplementary material added in a virus culture process and a use method of the supplementary material. The supplementary material comprises the following components: glucose, GluMAX and soybean lecithin. Supplementary materials are added into the culture medium, so that glycometabolism, lipid metabolism, nucleic acid translation and protein synthesis of host cells can be remarkably enhanced; effect pathways of interferon can be influenced, interferon stimulation gene expression is inhibited, and therefore the cell antiviral effect is inhibited. The cell maintenance can be promoted, and the cell apoptosis after virus infection is delayed. In conclusion, the virus yield can be remarkably improved.

The invention discloses a battery maintenance method based on a dynamic sparse neural network and a large language model, and belongs to the technical field of battery management. The method comprises the following steps: acquiring sensor time sequence data and an operation and maintenance text maintenance log of a battery pack, and respectively carrying out standardized preprocessing on the sensor time sequence data and the operation and maintenance text maintenance log; extracting time domain and frequency domain features of the preprocessed sensor time sequence data to obtain sensor features; carrying out semantic coding on the preprocessed text maintenance log by adopting a large language model subjected to battery domain knowledge fine adjustment to obtain text semantic features; performing feature fusion on the sensor features and the text semantic features based on a cross attention mechanism to generate fusion features; and inputting the fusion features into a dynamic sparse neural network which adaptively adjusts the sparseness of each layer of network according to the real-time health state of the battery, and outputting a battery fault probability and a fault root cause weight.

The invention provides a battery maintenance method and system and a medium. Comprising the following steps: acquiring battery data of a battery management system, and executing electrochemical impedance spectroscopy scanning; estimating the SOH value of the battery based on the battery data and the impedance spectrum scanning result; based on the SOH value and the battery temperature, adaptively setting the frequency and duty ratio of the pulse current for maintenance; and applying high-frequency pulse current to the battery based on the set frequency and duty ratio, and maintaining the battery according to a multi-stage charging and discharging protocol. The embodiment of the invention can prolong the service life and improve the use safety of the new energy battery.

The application discloses a multi-parameter fusion switch battery state diagnosis method and system based on SVM, relates to the field of intelligent monitoring technology combining power line automation and Internet of Things technology, and comprises the following steps: collecting multi-parameter data through a sensor, and pre-processing the multi-parameter data; extracting fault diagnosis features from the processed data, screening important features by using a Pearson correlation coefficient, and dividing the data set into a training set and a test set; combining SVM and a BP neural network to form an SVM-BP model, and evaluating the state of the battery by training and optimizing weights and parameters. The application realizes intelligent operation and maintenance of the battery, changes the battery maintenance work from passive to active, improves the operation and maintenance level of the power distribution automation terminal equipment, greatly reduces the operation and maintenance workload, realizes the state of the backup power battery into the daily operation and management of the power distribution automation equipment, and achieves more timely and rapid operation and maintenance management.

A clay target range monitoring system configured to monitor various aspects of one or more clays throwers and related devices and systems is disclosed. The clay target range monitoring system may be configured to monitor operation of one or more clay throwers, such as on a sporting clays course, five stand course, skeet field, trap field and the like. The clay target range monitoring system may be configured to deliver real-time, or near real-time, data to managers and related staff to address issues before they become problems negatively affecting the experience of the shooters, which may result in lost revenue. The clay target range monitoring system may be configured to predict events, such as but not limited to, when a clay thrower will run out of clay targets, when preventive maintenance is needed, when a battery requires maintenance, predictions based on user data and the like.

A transfection robot that combines bio informatics, robotics and artificial intelligence (AI) in a single package. The transfection robot replaces a large component of the mundane work and increases the quality thereof.

This application provides a battery pack energy efficiency optimization method and system. The method includes identifying the structural information of a cycling device and performing structural matching with the device's battery pack to output battery adaptation parameters; acquiring cycling data and allocating device power according to the battery adaptation parameters to obtain an energy efficiency control threshold; identifying battery state data of the device's battery pack based on the battery adaptation parameters and calculating thermal safety boundaries with the energy efficiency control threshold to output degradation trend data; and performing battery maintenance analysis on the device's battery pack based on the degradation trend data to generate subsequent maintenance planning information. This invention can provide early warning of battery performance degradation or thermal runaway risks, improving the safety of battery use.

The embodiment of the invention provides a battery health condition determination method and device, equipment and a storage medium. The method comprises the following steps: acquiring first monitoring data of a power distribution automation terminal battery in a first duration period and second monitoring data at the current time; determining a target monitoring data feature vector according to the first monitoring data and the second monitoring data; and inputting the target monitoring data feature vector into a battery health condition evaluation model to obtain a battery health condition evaluation result and a floating charge life prediction result. The method is used for achieving the purpose of finding potential problems of the battery in real time so as to assist operation and maintenance personnel in making a reasonable battery maintenance and replacement plan, and the use reliability of the battery and the overall stability of the power distribution automation terminal are remarkably improved.

The present invention relates to the field of bioprinting and biotechnology, and to a system and method capable of improving quantitative dispensing accuracy through closed loop control using real-time weight feedback for hydrogel bioinks having viscoelasticity and shear thinning characteristics, and integrally performing multi-well dispensing and cell maintenance processes by robotic arm-based automation.

The invention discloses a cloud-edge cooperative type all-vanadium redox flow battery state-of-charge estimation method and a cloud-edge cooperative type all-vanadium redox flow battery state-of-charge estimation device, an extended Kalman filtering method is adopted, and a cloud-edge cooperative architecture is provided, the architecture carries out preliminary offline estimation by utilizing edge equipment, and then transmits data to a cloud server, so that the cloud-edge cooperative type all-vanadium redox flow battery state-of-charge estimation is realized. And the cloud end calculates parameters in real time through a least square model with a forgetting factor and issues the parameters to the edge according to actual conditions, so that SOC real-time estimation is carried out. According to the method, the real-time performance and accuracy of SOC estimation can be improved, estimation errors are reduced, hardware electric equipment can carry out battery maintenance in time in practical application, the revision cost is reduced, the battery utilization rate is improved, and the service life of the battery is prolonged. According to the method, the problem that the SOC estimation precision is not high due to the fact that the edge end load is large and RLS is prone to data saturation is solved to a great extent.

This invention discloses a highly active exogenous cell care preparation derived from natural biological macrocells and its applications, belonging to the fields of biomedicine and cell care technology. This invention uses natural biological macrocells from algae, woody plants, herbaceous plants, fungi, and animals as raw materials, employing a low-temperature, mild purification process to retain the original active substances, and then compounding them with medical excipients to produce oral or sterile intravenous infusion preparations. The active ingredients of the preparation are natural, native components, mild and safe, with no obvious toxic side effects. At conventional doses, they are essentially metabolized within 24 hours, and at high doses, they are completely excreted within 1-2 days, without long-term accumulation in the body. This invention achieves cell activity repair, microenvironment regulation, and cell homeostasis maintenance through an exogenous, non-invasive method, without involving invasive cell modification. It has a wide range of applications, high safety, and a clearly defined scope of protection, possessing significant scientific research and industrial application value.

The application discloses a construction method of Aedes albopictus Aa01 cell line and susceptible cell model of Decapod iridovirus 1, and belongs to the technical field of virology and aquaculture disease prevention and control, wherein the Aedes albopictus Aa01 cell line is preserved in the China Center for Type Culture Collection of Wuhan University, and the preservation number is CCTCC NO: C202648. The method for constructing the DIV1 susceptible cell model based on the above cell line comprises the following steps: culturing the Aedes albopictus Aa01 cell line, and subculturing or using for virus inoculation when the density reaches 80%-90%; inoculating the DIV1 into the Aedes albopictus Aa01 cell line, removing the virus liquid after virus adsorption, and adding cell maintenance liquid for continuous culture; and observing the cytopathic effect CPE, collecting the cell culture when the CPE reaches 70%-80%, and obtaining the amplified DIV1 virus liquid. The DIV1 susceptible cell model constructed by the method can solve the problem that there is currently a lack of stable and continuously subcultured DIV1 in vitro culture.

The utility model relates to the technical field of electrolytic cell maintenance, and discloses an aluminum electrolytic cell damage maintenance device which comprises a top plate, a first sliding groove is formed in the top plate, a first threaded rod is movably connected in the first sliding groove in a sleeved mode, and a first servo motor is fixedly installed on the upper portion of the top plate. A first transmission tooth roller is fixedly connected to an output shaft of the first servo motor through a coupler, the outer edge of the first transmission tooth roller is meshed with a transmission tooth belt, the bottom end of the transmission tooth belt is meshed with a second transmission tooth roller, the second transmission tooth roller is fixedly connected with a first threaded rod in a sleeved mode, and the first threaded rod is movably connected with a sliding block in a sleeved mode. The sliding block is movably connected with the sliding groove I. The electrolytic cell is detected through the infrared scanner, maintenance personnel are prevented from being exposed to a high-temperature and high-intensity magnetic field, the electrolyte splashing risk is reduced, the damage position is conveniently and rapidly locked, the maintenance mechanism is driven through the first servo motor, welding and grinding integrated operation is achieved, and the repair precision of the electrolytic cell is maintained. The damage maintenance efficiency of the device on the electrolytic bath is improved.

Methods, systems, and devices for multi-level cell maintenance operations are described. A controller of a memory device may perform a two-portion maintenance operation in order to transfer data from a first block of memory cells to a second block of memory cells. For example, during a first portion of the maintenance operation, the controller may read first data from the first block of memory cells and perform a first error control operation to correct the first data. The controller may store second data associated with the first error control operation to volatile memory of the memory device in response to performing the first error control operation. During a second portion of the maintenance operation, the controller may perform a second error control operation using the second data associated with the first error control operations stored to the volatile memory of the memory device.

The invention relates to the technical field of batteries, and discloses a battery maintenance method, device, equipment and system, and the method comprises the steps: responding to a maintenance instruction under the condition that a plurality of to-be-maintained battery units are connected to a multi-path inverter, and controlling the multi-path inverter to execute maintenance operation; under the condition that the maintenance operation is completed, reporting a maintenance result indicating that the maintenance is completed to the server; wherein the maintenance operation comprises the following steps: for a first battery unit and a second battery unit in the plurality of battery units, controlling the first battery unit to charge the second battery unit until the first battery unit is completely discharged; controlling the second battery unit to charge the first battery unit until the second battery unit is completely discharged; and charging the first battery unit and / or the second battery unit to control the SOC of the first battery unit and the SOC of the second battery unit to reach a preset condition. The utilization rate of the battery remaining capacity can be improved, the conversion efficiency of power grid energy is ensured, and the maintenance cost is saved.

The utility model relates to the field of aluminum electrolysis cells, and discloses an ultrasonic flaw detection device for aluminum electrolysis cell maintenance. The control seat is mounted on the movable seat, and the control seat is arranged to move on the movable seat in a reciprocating manner; the protective shell penetrates through the control seat, and the flaw detection head is mounted in the protective shell; a storage cavity is formed in the protective shell and used for storing a coupling agent, and a plurality of through holes are formed in the inner wall of one side of the storage cavity. According to the utility model, through the cooperation of the storage cavity, the push plate, the connecting pipe and the control valve, a coupling agent can be extruded in real time according to the requirement of flaw detection work, the flaw detection work efficiency is improved, and the reciprocating movement of the control seat drives the flaw detection head to uniformly smear the extruded coupling agent; meanwhile, due to the arrangement of the groove, the coupling agent can be more uniformly distributed around the flaw detection head.

This application discloses a monitoring method for a power battery, a vehicle, and a storage medium, relating to the field of vehicle technology. The method includes: acquiring voltage parameters of the power battery; when the voltage parameters meet preset conditions, performing time integration on the current of the power battery to obtain the ampere-hour difference value between different cells in the power battery; determining whether there are cells with abnormal self-discharge rates in the power battery based on the ampere-hour difference value; wherein the preset conditions indicate that the voltage of the power battery is located in a non-plateau region between different plateau regions. This application aims to improve the timeliness of detecting cells with abnormal self-discharge rates, thereby improving the timeliness of battery maintenance.

This invention teaches systems and methods for identifying, targeting and destroying cancer cells. As cells progress from a normal to a cancerous state their accelerated metabolic rates and adapted pathways generate a higher heat signature that serves as a targeting beacon for a specialized cell-killing vector. Suitable vectors include modified / adapted intracellular bacteria. Especially preferred is the bacterial vector because of its ease of production. The bacterial vector is selectively targeted to recognize cells whose temperature is slightly elevated and ambient pH suppressed due to cancer related alterations to metabolism. An additional targeting feature, such as recognition of the MCT4 transmembrane protein exaggeratively expressed on the cancer cell membrane, may provide additional targeting. Embodiments featuring facultative extracellular and intracellular growth capable bacteria have the feature that culture conditions for producing vector can be optimized solely for the one organism and need not be compromised to support or optimize host cell maintenance.

The utility model relates to a battery module, a battery pack and an energy storage system, the battery module comprises a plurality of battery cells, adjacent battery cells are connected through a compressible piece, the battery cells are electrically connected through busbars, at least part of the busbars are provided with strain gauges, and the strain gauges are connected with the compressible piece. And the strain gauge is used for detecting the stretching amount of the battery in the direction of the busbar during expansion. By arranging the compressible pieces between the battery cells, the technology effectively relieves mechanical stress generated in the expansion process of the battery cells. And in combination with the strain gauges on the busbar, the stretching amount of the busbar can be detected in real time, so that the expansion condition of the battery cell is accurately reflected. By means of the design, accurate monitoring of stress changes in the battery cell expansion process is achieved, the stability of the battery module is enhanced, and the service life of the system is prolonged. In addition, the real-time monitoring provides reliable data support for battery maintenance and fault early warning.

The invention relates to the technical field of new energy measurement and control, in particular to a novel chaos firefly-particle optimization battery health state evaluation method, which comprises the following steps of: S1, acquiring updated particles by adopting a particle filtering algorithm; s2, optimizing the updated particles by using a chaos firefly optimization method to obtain a global optimal solution; s3, performing weight updating, normalization and resampling on particles in the globally optimal solution to obtain an SOC estimated value of the current time step; and S4, inputting the SOC estimation value of the current time step into a Kalman filter, obtaining an updated battery estimation capacity value and an SOH estimation value, inputting the updated battery estimation capacity value into a control matrix of a particle filtering algorithm, obtaining an SOC estimation value of a next time step, and returning to S1 for iteration until an optimal SOH estimation value is obtained. The method provides powerful support for stable operation and battery maintenance of a large-scale energy storage system.