377results about How to "Easy to deploy" patented technology

The invention provides a multi-reflection superposition enhanced microwave displacement measurement method and system, and the method comprises the steps: S1, constructing a microwave multi-reflection propagation path, enabling a microwave radar to transmit electromagnetic waves to the microwave multi-reflection propagation path as a transmission signal, and receiving a corresponding echo signal; s2, extracting length change information of a microwave multi-reflection propagation path according to the echo signal; s3, establishing a linear superposition relation model between the total length of the microwave propagation path and respective displacements of W reflection surfaces in the microwave multi-reflection propagation path; w2; and S4, based on the linear superposition relation model, displacement information of the corresponding reflection surface is obtained and output. According to the invention, a larger phase variation can be obtained under the condition of small displacement or weak vibration, so that the measurement sensitivity is improved and the signal-to-noise ratio is improved.

The invention discloses an intelligent dynamic load balancing method and system based on Clico-VPP. The method comprises the following steps: acquiring a load state index of a back-end service pod; according to the load state index and a service capability coefficient corresponding to the back-end service pod, calculating a dynamic traffic allocation weight of the back-end service pod through a weighted calculation model; based on a dynamic threshold synchronization strategy, synchronizing the state of a first hash ring located in a control plane to a second hash ring located in a forwarding plane; and based on the second hash ring, determining a target pod for the input data stream through consistency lookup. A double-loop decoupling architecture is provided, hash rings of a control plane and a forwarding plane are separated, a synchronization strategy is determined through a dynamic threshold value, decision intelligence and forwarding stability are both considered, and jitter is avoided; meanwhile, a dynamic weight-driven consistent Hash algorithm is adopted, a real-time load index and Pod service capability are fused to calculate a dynamic weight, and the dynamic weight is mapped into the number of virtual nodes, so that intelligent scheduling based on capability and maximum maintenance of connection during capacity expansion and contraction are realized.

The invention discloses a multi-sensor motion evaluation method and system for special training of lower limbs. The method comprises the following steps: step S100, collecting data of various sensors of the lower limbs; step S200, based on the collected data, carrying out gait and support state identification; step S300, judging the state of foot varus and valgus; step S400, calculating a foot stability index; step S500, calculating a lower limb exercise ability index; step S600, carrying out special exercise evaluation; and step S700, generating training feedback. Compared with an optical system, the core advantages of the system in training are reflected in that the system can be used for real training instead of a forced performance type test; the device is suitable for long-distance and continuous special training; the technical stability and injury risk can be directly reflected; and the training evaluation cost and the use threshold are obviously reduced.

The invention discloses a communication monitoring method and a communication system. The system comprises a monitoring module, a feature extraction module, a dynamic identification module, a behavior analysis module, an adaptive optimization module and a visual interface module. The monitoring module collects communication data flow through a mirror image port, the feature extraction module extracts packet length, time interval, direction sequence and encryption features by using a multi-dimensional feature fusion algorithm, and the dynamic recognition module realizes multi-protocol type recognition based on an improved self-attention convolutional neural network. The behavior analysis module constructs a communication relation graph and performs abnormal communication tracing; and the adaptive optimization module realizes model self-learning and parameter optimization through reinforcement learning. According to the method, through sliding window sampling, self-correlation analysis, entropy detection and GNN map modeling, accurate identification and behavior restoration of implicit traffic in a complex network environment are realized. According to the method, high-precision identification can be kept under the conditions of multi-protocol mixing and encrypted communication, and the characteristics of intelligence, self-adaption and expandability are achieved.

The invention relates to a Keystone-based deep ground security heterogeneous data fusion method and system, and the method comprises the steps: deploying a Keystone trusted execution environment on a deep ground edge computing node, creating a security enclave, carrying out the encryption access of multi-source heterogeneous data on the basis of remote authentication and key agreement, completing the space-time alignment and feature extraction after decryption in the enclave, and carrying out the fusion of the multi-source heterogeneous data. And performing cross-modal association analysis and risk assessment based on a preset model or a rule engine to obtain a fusion result, encrypting and signing the fusion result in the enclave, distributing the fusion result to an authorized receiver through a secure channel, and realizing one-time task destruction, long-term task cycle reconstruction and key refreshing in combination with enclave full life cycle management. According to the method, the credibility and the real-time performance of heterogeneous data fusion processing in a complex scene can be improved while the confidentiality and the integrity of deep operation and maintenance data are guaranteed.

The application provides a frequency domain convolution operation acceleration system for an 8bit frequency domain convolution neural network, relates to the technical field of frequency domain convolution operation acceleration design, and solves the problems of slow convolution calculation of the current frequency domain convolution neural network, difficulty in deployment to a hardware platform with limited resources, influence on product market time and design cost, and the like, obtains a pair of 8bit multiplication data, packs the obtained pair of 8bit multiplication data, performs multiplication calculation on the packed pair of 8bit multiplication data, outputs a frequency domain convolution multiplication result, accumulates the frequency domain convolution multiplication result, outputs a frequency domain convolution accumulation result, restores the frequency domain convolution accumulation result, and obtains a final frequency domain convolution operation complex output result; the application improves the operation speed of the frequency domain convolution, facilitates deployment of the frequency domain convolution to a hardware platform, improves the efficiency of processing digital signals in an FPGA accelerator, accelerates product market time and reduces product design cost.

The invention provides an anti-interference measurement method and system for grounding grid parameters in a strong interference environment, and belongs to the technical field of grounding device parameter measurement. The method comprises the following steps: constructing a multi-physics field coupling theoretical model, and integrating a high-precision clock synchronization and wireless communication high-fidelity sensor network; phase and amplitude errors in signal transmission are effectively eliminated through an anti-interference and fidelity processing mechanism, and finally the grounding resistance and related electrical characteristics are calculated by solving a parameter equation set derived from a theoretical model. According to the invention, by constructing a multi-physics field coupling theory model and designing a high-fidelity sensing network, and combining a distributed clock synchronization technology and an anti-interference signal processing mechanism, accurate, portable and safe measurement of the grounding resistance of the tower at a strong interference power transmission line site without power failure and disconnection of a down lead is realized. According to the invention, the risk of operating high-voltage equipment and the complexity of burying the auxiliary electrode in the traditional measurement are thoroughly avoided.

A robustness measurement method for LeNet-5 networks based on adversarial boundary constraints is presented, relating to the field of deep learning model testing. The main steps include: for each training sample, dynamically generating adversarial examples based on the model's current state during training iterations; constructing a composite loss function based on standard cross-entropy loss and dynamic boundary constraint loss; performing end-to-end training on all parameters of the LeNet-5 network; and using the overall approximate robustness boundary as a measure of model robustness after training. This method effectively improves the resistance of the LeNet-5 model to fast gradient sign-based adversarial attacks without altering the basic structure of the LeNet-5 network by designing a new loss function.

The present disclosure provides a time division duplex based semantic data transmission method and related equipment. The method comprises: a base station modulating and processing first user data corresponding to semantic data to obtain a first modulation sequence; the base station determining a first number of time-frequency resource blocks required for mapping the first modulation sequence to a first time-frequency resource; the base station judging whether the mapping of the first modulation sequence to the first time-frequency resource spans a time slot to obtain a first time slot span judgment result; the base station mapping the first modulation sequence to a first time-frequency resource with a first number of time-frequency resource blocks based on the first time slot span judgment result to obtain a first time-frequency signal, and sending the first time-frequency signal to a user terminal through a downlink; and the user terminal mapping the second modulation sequence to a second time-frequency resource with a second number of time-frequency resource blocks based on a second time slot span judgment result to obtain a second time-frequency signal, and sending the second time-frequency signal to the base station through an uplink.

The invention discloses a centralized management method and system for large-scale heterogeneous hosts of a meteorological infrastructure resource pool, and the method comprises the following steps: (1), obtaining the information of hosts needing batch operation through a configuration file in a command line mode based on a Linux system; (2) decoding the obtained configuration file, loading a single or batch command list needing to be executed according to decoding information, and logging in a target host for execution; step (3), detecting the host with abnormal login and giving an error prompt, and then skipping to continue to execute the next host; and (4) reading standard output and standard error output of the target host terminal to obtain an execution result of each command, classifying and redisplaying the execution result on a remote centralized management console, and recording a log file at the same time. According to the invention, centralized and batch management of large-scale heterogeneous meteorological infrastructure resources can be realized.

The application relates to a binocular image key point matching method based on a hierarchical optimization strategy and a medium, and the method comprises the following steps: S1, acquiring multiple pairs of left-right stereo image pairs; S2, processing the left-right stereo image pairs by using a deep neural network feature extractor to obtain left-right feature map pairs with different resolutions; S3, calculating matching cost volumes of the left-right feature map pairs to construct a matching cost volume pyramid; S4, obtaining an initial key point matching pair based on a matching cost volume with the lowest resolution; S5, calculating the matching cost between corresponding image blocks of the key point matching pair in a matching cost volume with a lower resolution, and taking a pixel pair corresponding to the matching cost satisfying local extremum as a key point matching result of the lowest level; and S6, repeating step S5, and performing layer-by-layer optimization on the matching cost volume pyramid in a manner from low to high resolutions until a final key point matching result is obtained. Compared with the prior art, the application has the advantages of high precision and strong robustness.

The application discloses an infrared image enhancement method, system, device and storage medium based on a wavelet threshold, which comprises the following steps: performing multi-scale discrete wavelet transform on an input original infrared image to separate low-frequency components and high-frequency components; the low-frequency components bear overall outlines and illumination distribution information of the image, and the high-frequency components contain edge, texture details and noise information of the image; performing improved adaptive wavelet threshold denoising processing on the high-frequency components to obtain denoised high-frequency components; performing layered enhancement processing based on weighted guided filtering and multi-scale Retinex on the low-frequency components to obtain enhanced low-frequency components; performing wavelet inverse transform reconstruction on the enhanced low-frequency components and the denoised high-frequency components to obtain a preliminary enhanced image; performing size upsampling on the preliminary enhanced image, and applying adaptive contrast restriction histogram equalization processing to output a final enhanced infrared image. The method can effectively suppress noise, retain details, adaptively enhance low-resolution infrared images, and is computationally efficient.

The application discloses a kind of machine learning model inference and forget request collaborative processing method, machine learning online service provider is updated model in real time in background based on forget request, and robustness detection is carried out to user inference request, service scheduling is carried out according to detection result, to realize faster response speed.The method comprises the following steps:1) sub-model training: split data set and train multiple sub-models with independent inference ability and online service;2) forget request processing: corresponding sub-model is updated in real time based on forget request received during service;3) inference request response: high robustness inference request is responded preferentially, and low robustness request is responded based on new model after model is completed updating.The application first proposes the collaborative processing method of multiple requests in the online service scene of machine learning, while guaranteeing privacy and correctness, higher response speed is realized, which is superior to existing method, with the advantages of strong universality, easy to deploy and the like.

The invention provides a distance measurement method in a calibration process of a laser vision system, which belongs to the field of distance measurement, and comprises the following steps: shooting a positioning plate image with a laser point through a camera, and arranging a plurality of positioning identifiers with known world coordinates on the positioning plate; identifying a positioning identifier in the image, and acquiring a pixel coordinate of the positioning identifier; calculating a three-dimensional coordinate of the positioning identifier in a camera coordinate system; fitting a plane equation of the positioning plate in a camera coordinate system; pixel coordinates of laser points in the image are detected and extracted; converting the pixel coordinate of the laser point into a space ray equation in a camera coordinate system, and calculating an intersection point of the space ray and the plane equation to obtain a three-dimensional coordinate of the laser point in the camera coordinate system; calculating the distance from the laser point to the optical center of the camera. According to the method, all calculations are carried out in a unified camera coordinate system, alignment errors caused by non-unified coordinate systems of multiple devices are thoroughly eliminated, and the consistency of distance measurement and the overall calibration precision are improved.

The utility model relates to insect situation monitoring technical field, concretely relates to an agricultural insect situation monitoring device, through the collection cover on the embedded connection has a plurality of conical tubes, the inboard of collection cover is installed with the moth lamp, the inboard slidingly connected with the bearing frame of frame body, and the both sides of the top of bearing frame are equipped with the bearing rod, and two bearing rods are rotatably connected between the inner wall of frame body, a plurality of broken rods are fixedly connected on two bearing rods, and the both sides of one end of two bearing rods are engagedly connected, and the operator can complete insect body collection and replacement without complicated dismounting operation, the use convenience and maintenance efficiency of equipment are improved significantly, can carry out automatic broken processing to insect body after its collection, effectively reduces insect body accumulation volume, improves the space utilization of bearing frame, prolongs the continuous working time in single monitoring period, avoids the influence of subsequent trapping effect because of too much insect body accumulation.

The utility model belongs to the technical field of avionics, and relates to Beidou No.3 positioning module detection equipment, which comprises an antenna assembly and a detector host, the detector host adopts a reinforced computer and is used for providing a power supply, a signal interface and man-machine interaction for the whole system; a Beidou command communication module and a Beidou forwarding module are arranged in the reinforced computer, and the reinforced computer is connected with a host computer module of the reinforced computer through an RS232 interface. The main computer module receives and transmits related commands through an RS232 interface, controls the Beidou command communication module and the Beidou forwarding module to work, obtains RNSS positioning information and RDSS short message information of the Beidou command module, and achieves signal gain adjustment of the Beidou forwarding module. The antenna assembly is used for transceiving data.

This invention discloses a method for detecting corn kernel breakage rate by incorporating an attention mechanism. This method further improves the lightweight one-stage object detection network YOLOv4-tiny by introducing a coordinate attention mechanism into the feature pyramid network to enhance the model's ability to detect dense corn kernels. Furthermore, an online mosaic data augmentation method is used during the model training phase to improve the model's ability to detect smaller-scale broken kernels. The method disclosed in this invention is easier to deploy on embedded platforms due to its low parameter size, and it has a high response speed while maintaining accuracy. It can efficiently detect the degree of corn kernel breakage and thus obtain the corn kernel breakage rate in real time.

The invention discloses a sparse time sequence Bayesian network construction method and system based on power distribution network topological constraints, and the method specifically comprises the steps: constructing a power distribution network topological graph, and calculating an adjacent matrix between nodes and a k-hop neighborhood matrix Nk; based on the power distribution network topology distance information and the matrix Nk, generating a hard constraint rule, and constructing a topology dependence mask matrix M; calculating an electrical influence range of the fault point on surrounding nodes to obtain an electrical influence matrix E; if the electrical influence coefficient of one node on the other node is smaller than a set value, deleting the corresponding dependent edge; introducing a data source reliability matrix R, and performing hard deletion or soft weakening on edges with reliability lower than a threshold value; combining the matrixes M, E and R to synthesize a sparse structure matrix S; and taking the matrix S as a space skeleton, adding a time dimension autoregression edge, and constructing a complete sparse time sequence Bayesian network. According to the invention, by guiding the rarefaction of the network structure, the number of network edges and the number of parameters are effectively reduced, and the trainability and reasoning efficiency of the model are improved.

This invention discloses a method, system, and storage medium for detecting the tilt of a vertical pump shaft. The method uses strain sensors to detect the strain of a first, second, and third circumferential surface of the vertical pump shaft, which are spaced apart along the axial direction. Based on the distance between these surfaces, a mechanical equation for the vertical pump shaft is constructed. The strain of these surfaces is then substituted into the mechanical equation to solve for the uniformly distributed load acting on the axial section of the vertical pump shaft. The tilt amplitude of the vertical pump shaft is calculated based on this uniformly distributed load. By installing strain sensors on the surface of the vertical pump shaft to collect the strain, the detection process does not require disassembly of the equipment or structural modifications to the vertical pump shaft, achieving non-invasive detection. This method is low-cost, easy to deploy, and can output the tilt amplitude of the vertical pump shaft, quantifying the tilt condition and facilitating maintenance decisions.

This invention relates to a commercially compatible and flexibly deployable OFDM backscatter communication method and system, belonging to the field of wireless communication. This invention enables nodes to perform backscatter communication without deploying synchronization modules, transmitting their own information to a commercial OFDM receiver with low power consumption, thus avoiding the limitation of node deployment range imposed by the sensitivity of synchronization modules. This invention uses a single-carrier signal from the environment as the excitation signal and transmits node information to the OFDM receiver through low-power cross-system conversion from single-carrier to multi-carrier. For the incident single-carrier excitation signal, the node performs low-power replication and shifting of the signal's spectrum during reflection, converting it into an OFDM reflected signal with multi-carrier characteristics. Since the node does not need to synchronize with the excitation signal before reflection, this invention significantly increases the effective operating radius of the backscattering node and enhances node deployment flexibility. Simultaneously, because the node achieves cross-system conversion from single-carrier to multi-carrier OFDM signals, it also possesses the advantage of commercial compatibility.

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 satellite load design method based on communication demand space-time characteristic analysis. The method comprises the following steps: carrying out space-time characteristic analysis on communication demands of different industries; integrating the time-space characteristic analysis results of the communication requirements of the industries to obtain the time-space characteristic analysis result of the overall communication requirements; based on the communication service providing capability of the existing satellite and the time-space characteristic analysis result of the overall communication demand, determining an area in which the communication demand is not satisfied; determining the number of satellites to be designed according to the total number of unsatisfied communication requirements; and determining the beam coverage range, beam coverage intensity and beam coverage shape of the to-be-designed satellite according to the area and the unsatisfied degree of the communication demand thereof. By applying the method, the rationality and effectiveness of a satellite load design scheme can be further improved, so that the satellite to be designed can better meet communication requirements.

A magnetic resonance-compatible programmable synchronized photostimulation system includes a main control unit and a stimulation execution unit. The main control unit is located outside the magnetic resonance scanning room, while the stimulation execution unit is located inside the scanning room and consists only of an LED light panel shielded by a magnetic field. The main control unit is configured to: receive photostimulation sequence parameters configured by the user in a modular manner through a graphical interface; receive a scan trigger signal from the magnetic resonance equipment, and automatically control the start and stop of the photostimulation sequence based on the trigger signal using hardware triggering; thereby achieving high-precision time synchronization between photostimulation and magnetic resonance scanning while maintaining magnetic resonance compatibility. This invention solves electromagnetic compatibility issues through a split architecture, achieves millisecond-level synchronization accuracy through hardware TTL triggering, and enhances experimental paradigm flexibility through modular programmable sequences, making it suitable for neuroscience research fields such as functional magnetic resonance imaging.

The invention relates to the technical field of battery manufacturing, and particularly discloses a gluing quality detection method and system. The gluing quality detection method comprises the following steps: driving a camera to return along the original path of a gluing track by using a robot which finishes gluing to carry out segmented shooting on the gluing track of a workpiece, so as to obtain a plurality of glue line images; performing parallel processing on the plurality of glue line images to obtain a plurality of colloid regions and obtain colloid boundary contours in the colloid regions; calculating a glue width mean value, a glue width standard deviation or a glue spacing mean value of the gluing track according to the glue boundary contours in the plurality of glue areas; and according to the glue width mean value, the glue width standard deviation or the glue spacing mean value, the gluing track quality is judged. The gluing robot is used for driving the camera to return along the gluing track along the original path for shooting, the camera moves along the whole gluing path and collects images through the track synchronous flying shooting technology, and the problem of detection blind areas caused by view limitation of large-size workpieces is fundamentally solved.

The portable graphene seedling raising shed has the advantages that the graphene composite support rod is adopted, the support rod is used as a heating device while supporting, the support rod itself is changed into an efficient and uniform heating body, stable and controllable heat supply is provided for the inside of the seedling raising shed, the spraying assembly arranged in the shed is convenient for watering and realizes intelligent control, the portable graphene seedling raising shed can be used for small-scale and family type seedling raising and cultivation in winter, has the characteristics of being light, capable of being quickly folded or stretched, and convenient for users to carry, transport and quickly deploy at different sites.

This invention discloses a unified ranking modeling method and system integrating heterogeneous features, belonging to the field of information retrieval and recommendation technology. The method first preprocesses the heterogeneous features of candidate information items; it then uses text vectors to generate gating signals and performs element-wise multiplication of the category feature vectors to obtain sparse representation features enhanced with text semantics; the processed features are concatenated to construct a global fusion input vector; through domain weight decomposition operators and multi-layer cross-networks, the weighted second-order interaction terms of the category features and the high-order interaction vectors of the global features are extracted respectively; the deep representations and weighted second-order interaction terms are aggregated to form a ranking feature vector; finally, the final ranking score of each candidate information item is output through an ordered classification mechanism. This invention achieves efficient deep fusion of heterogeneous features and complex relationship modeling, significantly improving ranking accuracy and generalization ability in multimodal scenarios such as search and recommendation.

The application provides a chip burning method, a computer device and a computer readable storage medium. The chip burning method comprises the following steps: generating a plurality of different temporary keys; combining the plurality of temporary keys into a key sequence and storing the key sequence in a temporary key file; receiving an encrypted burning file from a second terminal; matching the temporary keys in the key sequence of the encrypted burning file with the temporary keys stored in a local key database one by one; when the temporary keys are successfully matched with the temporary keys in the local key database, downloading a decrypted program file to a burner, the program file is used for burning to a target chip, and then deleting the matched temporary key from the local key database. By generating a plurality of different temporary keys and storing the temporary keys in the local database, the number of burners that can be used at the same time is controlled by matching the temporary keys one by one and deleting the used keys immediately after successful matching, and the total burning quantity can be accurately controlled.

The utility model provides a portable ground detecting instrument, which belongs to the technical field of meteorological equipment, and comprises a base, a fixed ground anchor, a ground sensor, a wireless communication module and a power supply module, the structural frame is fixedly arranged on the base, the structural frame comprises beam rods which are annularly distributed, and threads are arranged on the beam rods; the lifting platform is arranged on the structural frame in a sleeving manner; the driving motor is installed on the lifting platform, the outer side of the driving end of the driving motor is sleeved with a threaded ring, and the threaded ring is connected with the beam rod in a threaded fit mode; the clamping ring comprises a butt joint piece connected with the driving motor and a first butt joint port connected with the butt joint piece; the sampling pipe comprises a first pipe body, a drill bit arranged at the lower end of the first pipe body and a second butt joint port arranged at the upper end of the first pipe body. The requirement for water content detection during surface soil layer sampling can be met.

The utility model discloses a device for analyzing ammonia nitrogen in a water sample, which comprises an analyzer, a bracket is arranged on one side of the top of the analyzer, a take-up wheel is rotatably mounted in the bracket, and a lead is wound on the take-up wheel; one end of the wire is connected with a signal interface of the analyzer, the other end of the wire is fixedly provided with an ammonia nitrogen probe, a cleaning bin is fixedly arranged on the side wall of the analyzer and below the bracket, a cleaning hole is vertically formed in the cleaning bin in a penetrating manner, and the wire and the ammonia nitrogen probe both penetrate through the cleaning hole; a plurality of groups of nozzles are fixedly embedded around the inner wall of the cleaning hole, a connecting pipe for connecting each group of nozzles is mounted in the cleaning bin, and a water conveying pipe is mounted at the input end of the connecting pipe. The ammonia nitrogen probe can be accurately controlled to retract and release through the servo motor, a high-pressure rotating water curtain cleaning system is integrated, automatic retraction and all-directional flushing of the probe after detection are achieved, manual intervention is reduced, cross contamination is avoided, and the detection efficiency and precision are improved.

This invention provides a method and system for reconstructing the full-band electrochemical impedance spectroscopy (EIS) of lithium-ion batteries. The method includes: performing distributed relaxation time (DRT) analysis on each group of battery EIS samples to obtain DRT spectra; aligning the DRT spectra on the logarithmic time constant axis and performing ensemble statistics, selecting peaks and / or valleys that stably appear under multiple operating conditions based on statistical stability, and mapping them to obtain a set of conditionally invariant characteristic frequencies; selecting characteristic frequency points that satisfy the sampling budget from the set of conditionally invariant characteristic frequencies, and performing sparse EIS measurements on the target battery at these characteristic frequency points to obtain sparse complex impedance inputs; generating a full-band complex impedance sequence based on the sparse complex impedance inputs using an autoregressive reconstruction model; and performing battery state estimation and fault diagnosis based on the full-band complex impedance sequence. This invention significantly improves the continuity of the spectral shape and the generalization ability across operating conditions under sparse sampling conditions, while reducing the full-spectrum testing time and sampling burden.