106 results about "Eigenvalue analysis" patented technology

The invention discloses a high-proportion new energy power grid island division method considering frequency constraint, and belongs to the technical field of power system stability analysis and control, and the method comprises the steps: calculating a coherence coupling matrix of a generator and a new energy station through point voltage phase angle information; constructing a homology information undirected graph and calculating a normalized Laplacian matrix; performing characteristic value analysis, and determining the number of coherent generator groups and the coordinates of the generator and the new energy station; determining the composition of a coherent generator group through inverse mapping, and obtaining a multi-type power supply grouping result; establishing a coherence grouping constraint and a frequency security constraint according to a multi-type power supply grouping result; and constructing an island division optimal section search model and solving to obtain an optimal splitting section. By the adoption of the method, coherence grouping of multiple types of power supplies is achieved, and the optimal island division scheme is obtained by constructing and solving the island division optimal section search model considering the new energy supporting capacity and the frequency constraint.

The invention discloses a heterogeneous sensor fusion method and system for dynamic covariance optimization, and the method comprises the steps: constructing a multi-source heterogeneous sensor network which comprises an underwater inertial navigation unit, a Doppler velocity sensor, an ultra-short baseline positioning system, a submarine topography matching device and a geomagnetic gradient detector; the method comprises the following steps: designing a distributed integrated navigation system by adopting a hierarchical fusion architecture, establishing a sensor confidence coefficient dynamic evaluation model based on online estimated error covariance matrix eigenvalue analysis, carrying out state prediction on a local filter level by applying Kalman filtering, and then carrying out measurement updating by adopting a novel variational Bayesian algorithm; a sensor autonomous switching and adaptive weighted dual-mode adjustment mechanism is developed on the main filter level, and self-healing improvement of navigation precision in a non-stationary environment is realized, so that the problems of dynamic reliability evaluation and fusion efficiency optimization in underwater multi-sensor multi-source navigation are solved.

The invention relates to the technical field of power systems, and discloses a flywheel energy storage assisted thermal power generating unit collaborative frequency modulation control method, which comprises the following steps: extracting dominant dynamic characteristics based on state matrix eigenvalue analysis through a joint dynamic model, and setting layered optimization time granularity according to the dominant dynamic characteristics; aiming at the difference between the thermal power slow dynamic characteristic and the flywheel fast dynamic characteristic, optimization objective functions of a thermal power layer and a flywheel layer are respectively designed, robust consistency constraint is introduced, and multi-time scale optimization instruction iteration generation is realized through an asynchronous coordination algorithm. The system monitors the frequency change rate of a power grid in real time, dynamically adjusts virtual inertia parameters of the flywheel and generates dynamic compensation power, and finally fuses the coordinated reference instruction and the dynamic compensation amount to form an execution instruction. According to the scheme, the frequency dynamic stability in the new energy power grid frequency modulation process can be remarkably improved, and meanwhile, the frequency modulation equipment loss and the sustainable operation capability of the energy storage system are balanced.

The invention discloses a natural growth apple three-dimensional attitude recognition method based on a real-time multi-task fusion algorithm, and the method comprises the steps: obtaining an aligned RGB-D image through a depth camera, constructing a data set in combination with an image enhancement technology, and synchronously training a classification, segmentation and key point detection model through a multi-task deep learning framework; judging the contour form of the apple through the classification model, and carrying out contour fitting by adopting a convex hull algorithm and an arc adjacency matrix ellipse detection algorithm; two-dimensional centroid positioning and three-dimensional point cloud analysis technologies are fused, and bimodal calculation in the three-dimensional fruit axis direction is realized in combination with a fruit stem and calyx key point detection result. According to the method, the precision problem of apple posture recognition in a complex natural environment is effectively solved, the anti-interference capability is remarkably improved through the three-dimensional point cloud denoising and feature value analysis technology, and reliable technical support is provided for automatic picking and growth monitoring.

The invention discloses a voltage source type energy storage small signal stability analysis method based on a virtual synchronous machine. A small signal state space model including active control, reactive control, double closed-loop control and a lithium battery energy storage module is established, a characteristic value analysis method is used for solving a state matrix characteristic root, system stability is evaluated, and an oscillation mode is identified. By drawing characteristic root trajectories of key parameters such as virtual rotational inertia, virtual damping coefficients and double-closed-loop PI parameters, an influence rule of the parameters on system stability is analyzed. According to the method, the dynamic response characteristics of the system can be accurately quantified, theoretical support is provided for control strategy optimization and parameter design of the voltage source type energy storage system, and the stability and reliability of a power grid in a renewable energy source grid-connected scene are effectively improved.

The invention discloses a rural power distribution network-oriented network tracking / constructing type source storage stability evaluation and planning method, and relates to the technical field of rural power distribution networks, and the method comprises the steps: constructing an inverter control model, and building a quantitative relation between an inverter capacity ratio and a system short-circuit ratio; according to the control model, an inverter hybrid system is established, and stability weak nodes are identified through characteristic value analysis of a system state matrix; and on the basis of the quantitative relationship and the stability weak nodes, calculating the energy storage capacity of the network to be constructed, and performing iterative configuration according to a preset priority until the stability requirement of the system is met. According to the method, accurate identification of the stability weak nodes and accurate configuration of the constructed energy storage are combined, accurate processing of the risk of the stability weak nodes of the rural power distribution network is realized, the disturbance resistance and the new energy consumption level of the rural power distribution network are improved, and stable, safe and efficient operation of the rural power distribution network is realized.

To provide an abnormality diagnostic system of an object structure capable of accurately and stably performing an abnormality diagnosis of the object structure.SOLUTION: An abnormality diagnostic system performs eigenvalue analysis with respect to a shape model obtained by modeling a structure of an object structure 200, and constructs a degradation model based on a result of the eigenvalue analysis. The system includes: an estimation section 420 for estimating, based on the degradation model and an acceleration measurement value 11, an acceleration estimation value and a stress estimation value at at least one evaluation object point being a part of the object structure 200 and also estimating an estimation value of a natural vibration number and an estimation value of an attenuation ratio which are a vibration parameter of the object structure 200; and an abnormality determination section 430 for determining a normal / abnormal state of the object structure 200 by machine learning based on the acceleration estimation value, the stress estimation value, the estimation value of the natural vibration number, and the estimation value of the attenuation ratio.SELECTED DRAWING: Figure 1

The invention discloses a forestry surveying and mapping method based on remote sensing big data, and relates to the technical field of image processing, and the method comprises the following steps: S1, obtaining an initial remote sensing image of a to-be-surveyed area, and carrying out the processing through a feature extraction model, and obtaining a standard remote sensing image; s2, generating a global matrix for the to-be-mapped area according to feature row vectors extracted from the initial remote sensing image and the standard remote sensing image; and S3, determining a final vegetation coverage rate according to the global matrix of the to-be-mapped area. According to the method, the concentration ratio of the vegetation features is analyzed and quantified through the feature values of the global matrix, interference of isolated pseudo vegetation pixels is avoided, the stability of a coverage calculation result is improved, and the method is suitable for large-scale and normalized forestry surveying and mapping scenes.

The invention discloses an analytical method for seepage calculation of a multi-level heterogeneous overflow aquifer system, which comprises the following steps of: establishing a stable seepage control equation of a multi-level aquifer and an adjacent aquitard system, and converting the stable seepage control equation into an ordinary differential equation set in a matrix and vector form; solving the ordinary differential equation set through a matrix eigenvalue analysis method to obtain a general solution of the water level of the confined aquifer; constructing a recursive relational expression of a constant coefficient vector in a general solution on the basis of the continuity conditions of the water level and flux of a heterogeneous parameter partition interface; expanding the recursive relational expression to a lateral boundary of the system, and obtaining a global analytical solution in combination with a lateral boundary condition; and writing a calculation program of the global analytic solution, and calculating the actual underground water seepage problem. According to the method, rapid and high-precision calculation of multi-layer water level spatial distribution can be realized.

The invention relates to the field of computer software, and discloses an open source software code security and compliance management and control method which comprises the following steps: acquiring security vulnerabilities, licenses, version information and dependency relationship data of an open source component, constructing a component-characteristic matrix based on the data and performing dimension reduction processing, predicting a security vulnerability risk and a compliance risk of the component; key components and potential vulnerability propagation paths are identified by constructing a dependency graph and calculating a Laplacian matrix in combination with eigenvalue analysis; and finally, generating a security vulnerability repair suggestion and a compliance review report, helping a development team to preferentially process high-risk problems, and ensuring that the project meets the requirements of related licenses. According to the method, the bug repairing process can be optimized, the safety and compliance of open source software are improved, and the maintainability of the system is improved.

The invention provides a flutter analysis method and device for a photovoltaic flexible support system, equipment and a medium, and the method comprises the steps: building a finite element model of the photovoltaic flexible support system, obtaining the wind field parameters of all model nodes corresponding to a photovoltaic module in the finite element model in a three-dimensional wind field, and calculating the flutter of the photovoltaic flexible support system according to the wind field parameters. Calculating target effective wind attack angle distribution of each model node, determining a static wind load balance position of the photovoltaic module in the three-dimensional wind field according to the target effective wind attack angle distribution of each model node, and performing complex mode characteristic value analysis on the photovoltaic module according to the static wind load balance position to obtain each order of mode complex characteristic value corresponding to the photovoltaic module; and carrying out flutter analysis on the photovoltaic flexible support system according to the modal complex feature values of all orders. According to the method, the flutter analysis is performed by combining the wind field parameters of the model nodes corresponding to the photovoltaic module, so that the non-uniform factors of the wind field are considered, and the flutter analysis accuracy is improved.

The invention belongs to the technical field of lattice tower structure health detection, and relates to a lattice tower rod piece missing intelligent detection method based on multi-view three-dimensional reconstruction. According to the method, an adaptive feature matching algorithm fusing geometric features and texture descriptors is provided, camera pose estimation is optimized by constructing a global depth consistency scoring mechanism, and high-precision sparse point cloud reconstruction is realized; designing a depth map optimization strategy based on energy minimization, and effectively overcoming the interference of complex illumination and a low-texture environment on three-dimensional reconstruction in combination with density threshold filtering and geometric structure feature analysis; an ordered / disordered point cloud adaptive noise reduction method is innovatively provided, and noise robustness processing is realized through gradient constraint and covariance matrix eigenvalue analysis; and finally, an improved neighborhood radius adaptive registration algorithm is adopted, and a rod piece missing region is accurately identified through a significance scoring mechanism. The method remarkably improves the automation level and reliability of rod piece missing detection, and can be widely applied to structural health detection of the lattice tower.

The invention belongs to the technical field of image processing, and particularly relates to an insulator internal bubble identification method and system based on image enhancement, and the method comprises the steps: obtaining a perspective grayscale image of an insulator, constructing a structure background image and a smooth guidance weight based on the weighted least square fitting of gradient image guidance, and obtaining a background residual image; combining the smooth guide weight, the local information entropy and the background residual image to construct a weighted signal-to-noise ratio energy diagram; generating a bubble significance probability graph based on Hessian matrix eigenvalue analysis; and identifying bubble defects through image binaryzation and connected domain analysis. According to the method, through gradient-guided background fitting and multi-dimensional feature joint constraint, umbrella skirt edge artifacts and random noise interference are effectively suppressed, and the accuracy and robustness of insulator internal micro bubble defect detection are improved.

The invention belongs to the technical field of data processing, and particularly relates to an energy storage transaction data processing method and model based on an electric power spot market environment, and the method comprises the steps: analyzing the historical energy storage state of an electric power spot market platform to obtain a historical energy storage state feature value, and analyzing the historical transaction state of the electric power spot market platform to obtain a historical energy storage state feature value; obtaining a historical transaction state characteristic value, combining a real-time meteorological state data set, performing comparison to obtain a predicted daily charging frequency of an energy storage battery, a predicted power transmission line power factor and a predicted power grid load capacity, and performing comparison based on a scheduling optimization characteristic value to obtain an electric power spot market platform scheduling optimization scheme; the system comprises an energy storage state characteristic value analysis module, a transaction state characteristic value analysis module, a meteorological state data set acquisition module, a prediction data analysis module and a scheduling optimization scheme comparison module. The method can improve the capability of judging the future power demand and supply condition, helps to balance the power grid load, and enhances the flexibility and stability of the power system.

The present application relates to the field of power system stability analysis and control, in particular to a kind of thermal mass energy storage converter broadband oscillation suppression parameter stable domain identification method, comprising the following steps: establish general electric-thermal coupling mechanism model, construct the dynamic differential equation describing the evolution of input electric power and energy storage medium temperature state of converter;Mechanical dynamics equation is constructed;Establish the small signal state space model of whole system, linearization is carried out at steady state operating point and the state space matrix of whole system is derived;Define practical small disturbance stability domain, set the real part decay rate threshold and minimum damping ratio threshold of whole system eigenvalue;Algebraic singularity constraint equation in high-dimensional parameter space is constructed;Solve algebraic singularity constraint equation, establish parameter stable domain.This method avoids the repeated iteration of traditional eigenvalue analysis, can accurately depict parameter boundary, effectively improve the frequency support capability of high proportion of new energy power grid and system robustness.

The invention relates to a doubly-fed wind power plant grid-connected characteristic value analysis method considering unbalanced power grid voltage. The method comprises the following steps: establishing a dynamic mathematical model of each element of a system; solving a system balance point based on a frequency shift method; linearizing the dynamic mathematical model of each element of the system to obtain a corresponding linearized continuous state space model; discretizing the continuous state space model of each element based on a trapezoidal integral rule, and dividing the system elements into single-port elements and dual-port elements according to the connection characteristics of each element in the system and the characteristics of the continuous state space model; discrete state space models of different port elements with a unified description form and discrete equivalent circuits of the discrete state space models are obtained; a full-system discrete state space model is constructed based on a node analysis method, and a system discrete state matrix is solved. A frequency doubling component introduced when a balance point is solved by adopting Park transformation is avoided; a discrete state space model of the doubly-fed fan grid-connected system is established, and the selection process of system state variables is simplified.

The application belongs to the technical field of image processing, and particularly relates to an insulator internal bubble identification method and system based on image enhancement, which comprises the following steps: obtaining a perspective gray image of an insulator, constructing a structure background image and a smooth guide weight based on gradient image guided weighted least square fitting, and obtaining a background residual image; combining the smooth guide weight, local information entropy and the background residual image to construct a weighted signal-to-noise ratio energy image; generating a bubble saliency probability image based on eigenvalue analysis of a Hessian matrix; and identifying bubble defects through image binarization and connected domain analysis. The application effectively suppresses umbrella skirt edge artifacts and random noise interference through gradient guided background fitting and multi-dimensional feature joint constraint, and improves the accuracy and robustness of insulator internal small bubble defect detection.

The invention provides a harmonic suppression method, device, equipment and product based on broadband impedance measurement, and the method comprises the steps: carrying out the measurement and analysis of all elements in a hybrid multi-infeed DC system according to a preset broadband impedance measurement method, and obtaining broadband impedance data, the preset broadband impedance measurement method is composed of an active disturbance method and a wavelet time-frequency analysis method; according to the topological structure of the hybrid multi-infeed direct current system, determining an LCC converter and an MMC converter in the hybrid multi-infeed direct current system; according to an LCC converter and an MMC converter in the hybrid multi-infeed direct current system, carrying out classification processing on the broadband impedance data, and constructing a harmonic interaction impedance analysis model; according to a characteristic value analysis method, the harmonic interaction impedance analysis model is analyzed, harmonic analysis of the hybrid multi-infeed direct current system is completed, the real-time performance and robustness of harmonic suppression are improved, and a theoretical basis is provided for harmonic suppression and stability optimization of the hybrid multi-infeed direct current system.

The application belongs to the technical field of wind power generation, and specifically discloses a wind farm grid-connected system grid-following type and grid-forming type wind turbine proportion optimization method and device, which comprises the following steps: changing the initial proportion of the grid-forming type wind turbine, and changing the grid strength under the updated proportion; calculating the power flow distribution of each node of the wind farm grid-connected system under the updated proportion, determining that the grid-connected system does not reach the capacity threshold based on the power flow distribution; establishing a state space model of the grid-connected system, and judging whether the grid-connected system is small signal stable; under the condition of small signal stability, analyzing the stability margin of the grid-connected system based on the dominant modal eigenvalue, evaluating the adaptability of the wind farm to the change of the grid strength by using a discrete coefficient, and recording the discrete coefficient; cyclically performing analysis on all grid strengths and wind turbine proportions, obtaining the discrete coefficients under all proportions, and selecting the grid-forming type wind turbine proportion corresponding to the minimum discrete coefficient as the optimal proportion. The application can improve the operation stability of the wind farm configuration result.

The invention relates to a full-blind multi-master-user spectrum sensing method based on extreme value characteristic values, which is characterized in that a sensing judgment quantity is constructed by using a difference value of the extreme value characteristic values and harmonic average: firstly, a multi-antenna sensing node calculates a sampling covariance matrix # imgabs0 # by using a received signal vector so as to calculate a maximum characteristic value and a minimum characteristic value of the sampling covariance matrix # imgabs0 #; thirdly, constructing a perception decision amount # imgabs1 # by using the ratio of the difference value of the extreme value characteristic values to the harmonic average value, and calculating a decision threshold t based on the analysis result of the extreme value characteristic values; and finally, carrying out perception judgment: when # imgabs2 is greater than t, judging that a multi-master user signal exists; otherwise, determining that the multi-master user signal does not exist. The method provided by the invention has reliable false alarm performance, and the detection probability higher than that of classical maximum and minimum characteristic value ratio and covariance absolute value detection can be obtained under the condition of low signal-to-noise ratio; and the method can realize total blind detection, the judgment threshold can be directly calculated based on closed expression, and the method has the advantages of simplicity and convenience in calculation and low complexity.

The application relates to a dimension reduction method, device and storage medium of a model of a new energy grid-connected system, and the method comprises the following steps: S1, a linear dynamic model of a new energy unit grid-connected system is established; S2, an eigenvalue analysis method is used to analyze oscillation modes generated by the model, characteristic roots and participation factors existing in the system are calculated, and state variables mainly participated by the system are obtained; S3, the state variables are removed based on a time scale method, fast decay modes are omitted, dominant eigenvalues are reserved, a state equation of a dimension reduction system is established, and a dynamic response curve is analyzed based on the state equation of the dimension reduction system. Compared with the prior art, the application has the advantages of effectively realizing model dimension reduction of the new energy grid-connected system while guaranteeing model application effects and calculation accuracy, and reducing calculation amount.

The invention discloses a method for suppressing subsynchronous oscillation of new energy through a direct current delivery system, which comprises the following steps of: establishing a linearization state space model of the system, and introducing a state feedback gain array on the basis of an original system matrix; after a subsynchronous oscillation mode of the system is obtained by carrying out characteristic value analysis on the system, selecting a dominant factor as system input to change the controllability of the system; a Lyapunov second method is adopted to judge the stability of the uncontrollable part, after the uncontrollable part is judged to be asymptotically stable, a target characteristic value is moved to the left side of a complex plane through a state feedback loop, and a state feedback gain matrix is obtained through calculation; and designing an additional damping controller to obtain a new feedback gain matrix, and realizing subsynchronous oscillation suppression of the new energy through the direct current delivery system. Based on state feedback, the method can change the specific characteristic value of the system, realizes random movement of the characteristic value of the closed-loop system on a complex plane, and is beneficial to improving the stable operation level of the system.

The invention discloses a method for suppressing subsynchronous oscillation of new energy through a direct current delivery system by applying energy storage, which comprises the following steps of: establishing a state space model of the system, setting a step response for the system, and verifying the correctness of the model; the method comprises the following steps: performing characteristic value analysis on a system to obtain each subsynchronous oscillation mode of the system, performing participation factor analysis on the system to obtain dominant factors of the subsynchronous oscillation modes, and analyzing the influence of energy storage access on system damping based on a characteristic root locus; according to an analysis result, additional damping control is added in an energy storage control link, an output current signal is directly added to double-loop control output of an energy storage inverter through extraction of a voltage component of a grid-connected point, filtering, phase shifting, amplification and amplitude limiting processing, then the current signal is transmitted to the grid-connected point of a new energy station, and system oscillation is counteracted through phase deviation. The method can effectively counteract system oscillation, restrain the problem of subsynchronous oscillation of the system, and is favorable for improving the stable operation level of the system.

The invention discloses a method for analyzing the influence of heterogeneous micro-grid parameters on system stability in a continuous steady state. The method is specifically implemented according to the following steps: step 1, acquiring steady-state working points of a heterogeneous micro-grid through parameter scanning; step 2, acquiring a low-frequency characteristic value of the heterogeneous micro-grid system in a continuous steady state based on the state space model of the micro-grid; and step 3, obtaining a participation matrix and a participation factor of the heterogeneous micro-grid system, determining a key variable according to the participation factor, and analyzing an influence rule of the parameter on the stability of the heterogeneous micro-grid according to the key variable. According to the method, the problem that in the prior art, a fixed working point is used for representing behaviors in the whole period in a traditional characteristic value analysis method, and consequently analysis is not accurate is solved.

The invention discloses a VSG-controlled inverter inertia margin calculation method based on a state-space equation, and the method comprises the steps: 1, building an inverter state-space equation under a VSG control strategy, and obtaining a constraint condition of VSG control parameter design under a stability requirement through feature value analysis; 2, based on a VSG equivalent inertia constant expression, determining a quantitative relation between a VSG control parameter and an inverter inertia under VSG control; and 3, calculating an inverter inertia margin under VSG control by combining a VSG control parameter constraint condition and a VSG equivalent inertia constant expression. According to the method, the adjustable range of the VSG control parameter under the stability constraint is determined based on the state-space equation, and the influence of the VSG control parameter on the inertia is quantitatively described according to the equivalent inertia constant, so that the calculation of the inverter inertia margin under the VSG control is accurately and effectively realized.

The application belongs to the technical field of electrical engineering and automation control, and provides a device and method for improving anti-leakage current and anti-interference, which comprises a first instrument amplification module, a second instrument amplification module, a third instrument amplification module, a static current adjustment module and a microprocessor module; static current data and dynamic current data of a circuit are obtained; static characteristic values and dynamic characteristic values are obtained through analysis and processing; a feedback signal value is obtained through analysis and processing based on the obtained static characteristic values and dynamic characteristic values; the feedback signal value is compared with a feedback signal threshold value, and is analyzed and divided into different regions; the feedback signal value is analyzed and processed into a feedback signal of an electronic delay module, and the electronic delay module is confirmed to be connected correctly through analysis and processing, thereby completing networking; the anti-leakage current and anti-interference are effectively improved, and the data processing of a mixed signal is optimized and analyzed, and potential problems in the circuit are specifically analyzed, thereby improving the reliability and safety of equipment.

Embodiments of the present application disclose a user clustering method and device based on power load, equipment and a storage medium, the method comprising: obtaining power load data set of candidate users for indicating power consumption of the candidate users; performing outlier processing on the power load data set by using annual temperature characteristics and the power load data set of each candidate user, determining target users and target power load data set; performing eigenvalue analysis processing on the target users, the target power load data set and preset power consumption characteristic parameters, determining eigenvalues of the power consumption characteristic parameters corresponding to each target user; and performing clustering processing on each target user according to the eigenvalues, determining power consumption categories corresponding to each target user for reflecting power consumption habits of the target users. Through the above manner, the power consumption categories can be better classified, which helps the power grid company to better understand the load demand and power consumption characteristics of the users, and lays a foundation for individualized demand response scheme.

This application provides an adaptive infrared vascular imaging enhancement method and apparatus based on image entropy feedback. It achieves precise adaptive adjustment of infrared emission power through local information entropy calculation and a proportional-integral-differential controller. An enhancement mechanism is constructed, combining multi-scale Gaussian smoothing and Hessian matrix eigenvalue analysis to establish a reliable vascular response extraction strategy. Structural analysis optimization is introduced, iteratively refining skeleton extraction and cross-point calculation to ensure continuous improvement in vascular cross-point localization. This method effectively addresses the shortcomings of traditional techniques in exposure adaptation, vascular enhancement, and topology analysis, providing technical support for infrared vascular imaging-assisted diagnosis.

In aspect, a computerized method of a genetic algorithm-based adaptive batch selection for hessian quantization in neural networks comprising: with at least one computer processer, computing a Hessian Matrix; performing an Eigenvalue Analysis on the Hessian matrix to generate a Hessian matrix eigenvalue that provides information about the curvature of the loss surface; determining a quantization level based on the Hessian matrix eigenvalue; using the quantization Level to set an appropriate quantization level for a layer weights of a neural network; and applying the quantization level to the layer weights of the neural network. This involves mapping the continuous floating-point values of the weights to discrete levels based on the determined quantization intervals.

The present invention relates to the field of data processing technology, and in particular to a method for analyzing the local spectral properties of a Hamiltonian operator. The method comprises: obtaining the real-time temperature, power consumption, and coolant flow of a grid; determining a high temperature difference grid; determining a temporary grid; determining an analysis grid; inputting data into a Hamiltonian operator model; adjusting a temperature gradient threshold, and generating an abnormal property analysis report. The present invention collects temperature, power consumption, and coolant flow data from a quantum computer cooling unit in real time, and combines this with local spectral energy eigenvalue analysis to accurately identify and adjust temperature control anomalies. This not only improves the stability and efficiency of the cooling unit, but also dynamically optimizes the temperature gradient threshold. Through the generated abnormal property analysis report, potential problems can be discovered and maintained in a timely manner, effectively extending the life of the equipment and optimizing the utilization of cooling resources. This effectively solves the problem of low output accuracy due to over-reliance on historical data.