197 results about "Attenuation curve" patented technology

The invention discloses an urban rainwater pipe network blockage risk early warning method and system based on edge calculation, and relates to the technical field of urban drainage monitoring. The problems that existing pipe network blockage detection lags behind, and the early warning precision is insufficient are solved. Dynamic hydraulic parameters and sediment migration state data of a pipe section are collected in real time through edge calculation equipment deployed at a pipe network node, the hydraulic state deviation rate is calculated, and the local blockage risk is rapidly recognized; when the deviation rate exceeds a threshold value, a dynamic sensing network is established by the trigger nodes, and a pipe network hydraulic topological relation is established by integrating the liquid level and flow velocity characteristics of the upstream and downstream nodes; executing distributed collaborative analysis based on the topological relation, identifying an abnormal attenuation area, calculating a sediment dynamic equilibrium index, and generating a blockage diagnosis parameter; and further combining real-time rainfall intensity to predict an overflowing capacity attenuation curve, generating a multi-stage early warning instruction according to an attenuation slope, and distributing the multi-stage early warning instruction to an operation and maintenance terminal, thereby realizing accurate early warning and active regulation and control of the blockage risk of the rainwater pipe network.

The invention relates to the field of battery monitoring and early warning, in particular to a battery health monitoring and early warning method and system. The method comprises the following steps: acquiring a historical charging and discharging monitoring log of a target battery; performing sliding window rolling charging and discharging identification on the historical charging and discharging monitoring log, and performing multi-level time sequence behavior mining to generate multi-level time sequence charging and discharging behavior characteristics; state deviation analysis between adjacent charging and discharging behaviors and adjacent charging and discharging efficiency attenuation quantification are carried out on the multilevel time sequence charging and discharging behavior characteristics, and a charging and discharging behavior efficiency attenuation curve is constructed; and carrying out attenuation trend law evolution on the charge and discharge behavior efficiency attenuation curve, and then carrying out normalized trend stability mining to obtain battery normalized attenuation trend stability. According to the invention, efficient and accurate battery health monitoring and early warning are realized, and the use efficiency and the management cost of the battery are optimized.

The invention relates to the technical field of electrochemical energy storage, and discloses a method and a system for predicting the residual life of a battery of an electrochemical energy storage system. According to the method, multi-dimensional operation data such as temperature distribution, current ripples and voltage attenuation curves in the charge-discharge cycle process of a target battery pack are collected, and feature weight parameters are generated in combination with real-time working conditions and historical database matching results; a degradation characteristic mode in a full life cycle is extracted as a reference template, and a dynamic degradation characteristic space is established; constructing a multi-scale coupled life prediction model, and constructing an adaptive evaluation function by iteratively updating model parameters and reference template physical field coupling parameters; triggering cross-cycle data verification, and carrying out working condition compatibility verification; and generating a feedback matrix based on the prediction error index and the verification result, and dynamically adjusting the mapping relation between the feature weight and the reference template. The method improves the accuracy and adaptability of battery residual life prediction, and is suitable for an electrochemical energy storage system under complex working conditions.

The invention discloses a photovoltaic array life prediction method based on hybrid driving of a physical model and data. The method comprises the following steps: defining failure time and residual life of a photovoltaic array; preprocessing data; degeneration trend extraction: separating a trend term, a seasonal term and a residual term of output power through block median filtering and seasonal effect correction, and eliminating the influence of environmental fluctuation on degeneration analysis; residual life prediction based on data driving; parameter prediction based on a physical model: identifying degradation parameters of the double-diode model; a degradation parameter trajectory model is established, an output power attenuation curve is inverted, and the remaining life is predicted; and result fusion: comparing data driving and physical model prediction results, and outputting a final residual life value through weighted average or confidence interval fusion. According to the invention, a set of complete photovoltaic array residual life prediction system is constructed, a whole-process closed loop from data acquisition, mechanism analysis to life prediction is realized, and an efficient and accurate solution is provided for reliability evaluation of a photovoltaic system.

The invention relates to the technical field of pipeline safety, and discloses a hydrogen-doped pipeline hydrogen damage grading evaluation method based on fracture mechanics. Comprising the following steps: acquiring initial pipeline state data by establishing a hydrogen-doped pipeline digital twin model; then introducing a hydrogen concentration dependency term to correct the J integral expression, and performing stress analysis based on the J integral expression; generating a material toughness attenuation curve based on a stress analysis result; hydrogen diffusion and accumulation rate parameters are obtained based on a material toughness attenuation curve; predicting a damage development track in combination with real-time operation data; establishing a grading standard system of dynamic response based on the model for risk assessment; and finally, real-time monitoring and scientific grading of the hydrogen damage of the hydrogen-doped pipeline are realized. According to the invention, comprehensive dynamic evaluation of hydrogen damage of the hydrogen-doped pipeline is realized, and scientific decision support is provided for safe operation of the pipeline.

The invention discloses a tunnel monitoring method and system based on a vibrating wire sensor, and relates to the technical field of tunnel engineering construction safety monitoring, and the method comprises the steps: collecting the vibration frequency data and spatial position coordinates of the vibrating wire sensor in a monitoring region; the method comprises the following steps: calculating a time difference and an energy attenuation ratio between adjacent sensors by extracting spectrum energy density distribution, and constructing a stress wave propagation field; dividing grids in the propagation field to calculate node stress values, generating a stress field distribution cloud picture and extracting a stress concentration area; calculating a gravity center position coordinate change rate and a stress time sequence curve of the stress concentration area, and determining fracture extension parameters; and calculating a surrounding rock bearing capacity attenuation curve based on the parameters, and outputting an early warning signal when the slope exceeds a threshold value. According to the invention, real-time monitoring and early warning of the tunnel surrounding rock instability risk are realized.

The invention discloses a rural historical building protection evaluation system based on big data, and relates to the technical field of building protection. Comprising the following steps: a data processing module normalizes environmental data to generate an environmental degradation factor, extracts a crack depth parameter and a facade weathering parameter from structure detection data through a feature extraction algorithm, and generates a building life attenuation curve through correlation analysis; and the decision module establishes a maintenance optimization model according to the building life attenuation curve and historical maintenance data, generates a risk level through threshold comparison, evaluates expected effects of different maintenance modes on degradation delay, and outputs an optimal maintenance suggestion. According to the method, accurate prediction of the rural historical building degradation process and optimal recommendation of the maintenance strategy are realized, and the scientificity and efficiency of protection work are improved.

The invention relates to a method for detecting surface cracks of a steel rail, which comprises the following steps of: controlling the environmental temperature difference change of the steel rail to enable thermal response to generate a hysteresis phenomenon, inducing slight asynchronous thermal fluctuation with discontinuous and asymmetric thermal diffusion in a local area of a material surface layer, and exposing a potential crack boundary; non-contact low-intensity laser thermal disturbance multi-angle scanning is used for executing a disturbance penetration test, non-structural thermal anomalies are removed, and a real crack area is determined; carrying out attenuation curve recording on the thermal response after multiple rounds of disturbance excitation, and reversely deducing the integrity degree of the microstructure below the crack according to the disturbance settlement time so as to judge the structural fatigue grade; environmental steady state comparison is carried out on the same detection area, through comparison of temperature and humidity, wind speed and radiation environment parameter changes before and after disturbance, if the crack area still continuously shows thermal response abnormity under a constant environment condition, it is confirmed that the thermal characteristic is caused by a structural crack, and otherwise, misjudgment caused by external accidental interference is eliminated.

The invention relates to a power battery performance degradation prediction method and system based on an electrochemical-thermal-mechanical-neural network model, and belongs to the technical field of battery management. According to the method, an enhanced single particle model considering liquid phase diffusion, an integrated thermal model, a particle mechanical stress model caused by concentration gradient and an aging mechanism model considering SEI growth, lithium precipitation and active material loss are coupled to establish ETMD, and based on the ETMD, the identification efficiency of aging model parameters is low aiming at the problem that a PSO algorithm is low. Under a circulating aging experiment of a limited path, the characteristic parameters of the aging model are obtained by using the feedforward neural network, and the parameters are substituted into the ETMD model again to predict the capacity, the power attenuation curve and the corresponding main attenuation mechanism under the current path, so that the prediction precision and the interpretability of the performance attenuation of the battery under the full path are improved. According to the method, the modeling capability of battery performance degradation under different working conditions can be effectively improved, and a theoretical basis and technical support are provided for residual life prediction and safety management of the power battery.

The invention relates to the crossing field of mechanical engineering and intelligent prediction technologies, particularly discloses a coal mill efficiency and service life prediction method and device, and aims to solve the problem that a traditional model is difficult to deal with nonlinear coupling prediction of equipment performance degradation under variable load and coal quality fluctuation. The method comprises the following steps: receiving a multi-source sensing data stream and constructing a structured feature matrix with aligned time sequences; efficiency degradation implicit features are extracted through a nonlinear dynamic encoder, and the interaction influence of grinding roller abrasion, lining plate fatigue and bearing degradation is quantified in combination with a multi-failure-mode coupling analysis module; and cooperatively predicting a network output efficiency attenuation curve and residual life probability distribution through a bidirectional attention mechanism. According to the method, through fusion of multi-source time sequence characteristics and multi-failure coupling modeling, limitation of a static threshold value and linear extrapolation is broken through, prediction precision and timeliness are remarkably improved, intelligent maintenance decision support is provided for a coal-fired power plant, non-planned shutdown risks are reduced, and operation economy and system reliability are optimized.

The invention relates to the technical field of tire evaluation, in particular to a method for evaluating the aging loss performance of a rubber engineering tire. The method comprises the following steps: determining tire attributes according to a tire vulcanization process database; constructing a multi-environment composite accelerated aging oven based on the tire vulcanization process database; segmenting a tire sample according to the tire attribute, inputting the tire sample into the multi-environment composite accelerated aging oven, and simulating accelerated aging; sampling according to a preset time interval to obtain an aging simulation result; determining a performance attenuation curve of each tire sample according to the aging simulation result; inputting the performance attenuation curve into an Arrhenius equation, and determining key failure time; and determining the tire performance according to the key failure time and the tire attribute.

The invention discloses a dam leakage channel detection and danger elimination quality evaluation method based on transient electromagnetism, and relates to the technical field of earth and rockfill dam danger elimination and reinforcement. The method comprises the following steps: A, leakage channel detection: A1, data acquisition: performing data acquisition on a dam by adopting pull-type small loop transient electromagnetic equipment to obtain original electromagnetic signal data; a2, forward modeling: performing forward modeling on the acquired data, and calculating a theoretical attenuation curve and apparent resistivity distribution by considering special boundary conditions of the dam; and A3, carrying out inversion calculation. According to the method, leakage signals can be accurately captured based on the high sensitivity of a transient electromagnetic method to a low-resistance body, the used pull-type small-loop transient electromagnetic equipment is convenient to operate, a dam can be comprehensively covered by combining reasonable measurement point arrangement, forward modeling and inversion calculation can comprehensively consider various factors, the position and depth of a leakage area are determined, and the detection accuracy is improved. Compared with a traditional method, the method has obvious advantages in detection depth and accuracy.

The invention relates to the technical field of new energy automobile batteries, in particular to a new energy automobile battery state prediction method, optimization control method and system, and the method comprises the steps: collecting the real-time operation data of a new energy automobile battery; uploading the real-time operation data to a cloud processing platform in which historical operation data of the battery is stored, and dynamically predicting the state of the battery; fusing the charge state data driven by the real-time model and the charge state data driven by the historical data to carry out charge state estimation prediction, and outputting charge state estimation parameters; a circulation attenuation model is combined with reinforcement learning correction, historical circulation data is used for fitting a capacity attenuation curve, and a dynamic battery health state estimation value is output; a fusion thermal model and an internal resistance model are adopted, a safety voltage / temperature boundary is predicted through digital twin simulation, and a dynamic battery power state estimation value is output; and generating a battery control strategy based on the battery state parameters and issuing the battery control strategy to an onboard BMS module for execution.

The invention relates to the technical field of constructional engineering detection, in particular to a concrete strength detection method and system. The method comprises the following steps: placing a thermal reference block with known thermal physical characteristics in the center of a target area on the surface of to-be-detected concrete; taking the thermal reference block as a center, applying synchronous thermal pulses with the same energy to the surfaces of the concrete at the symmetrical positions on the two sides of the thermal reference block, recording the formed thermal response by using an infrared thermal imager, generating thermal response data, and forming two hot spots on the surface of the concrete; monitoring the environment temperature fluctuation by using the thermal reference block, and subtracting the quantity of the environment temperature fluctuation from the thermal response data in real time to obtain a thermal attenuation curve of the hot spots; and analyzing the isotherm contour form distortion degree of the thermal field corresponding to the thermal attenuation curve, and quantifying the isotherm contour form distortion degree as a thermal field structure polarization index. The problems of environmental interference and internal structure quantification in existing concrete strength detection are solved through a constructional engineering detection technology.

The invention discloses a processing process fault prediction method for essential oil production, and relates to the technical field of essential oil processing, and the method comprises the steps: constructing an environment equipment coupling model, and drawing an electrical equipment insulation resistance attenuation curve through a salt mist deposition experiment; environment disturbance variables are introduced into the generative adversarial network, and an anomaly detector capable of recognizing salt spray corrosion characteristics and humidity condensation characteristics is trained; capturing time-space correlation between temperature mutation and quality fluctuation through a self-attention mechanism; calculating a probability density function of the residual service life of the equipment in real time, and automatically correcting a temperature over-limit threshold value based on the residual service life distribution; calculating the contribution degree of each node to the fault through intervention simulation; and constructing a digital twinborn model containing thermodynamic and hydrodynamic characteristics. Through environment dynamic modeling, causal reasoning and digital twinning methods, the key problems of low fault prediction precision, poor traceability efficiency and lack of quantitative support in decision making in essential oil production are solved.

The invention discloses a clinical examination equipment remote calibration method and system based on edge calculation, and relates to the field of instrument calibration, the system is composed of a plurality of functional modules, and the system comprises: a multi-modal data acquisition module for acquiring historical calibration data of absorbance, including fluorescence images, cell fluorescence signal intensity and morphological characteristics; the edge calculation module is used for establishing a multiple linear regression model according to historical calibration data of the absorbance and predicting an attenuation curve of the optical detection unit; on the basis of a federated learning framework, a fluorescence signal intensity compensation matrix is optimized by utilizing shared parameters among edge nodes, and light path gain parameters are automatically adjusted; performing outlier analysis on each batch of detection data through a built-in Westgard rule engine, and triggering automatic redetection of morphological characteristics; analyzing absorbance time sequence data in combination with a 1D-CNN model, and identifying reagent pollution and optical assembly aging; and the drifting calibration module adopts a PID controller to dynamically adjust the power of the laser.

The invention relates to the technical field of capacitors, in particular to an explosion-proof test method for a power capacitor. Injecting a multi-band harmonic current sequence into the composite stress field, capturing three-dimensional strain propagation characteristics of the capacitor shell in real time, and establishing a strain-discharge space-time correlation model according to the three-dimensional strain propagation characteristics; a capacitor shell structure integrity attenuation curve is obtained according to the strain-discharge time-space correlation model, and when the slope of the attenuation curve breaks through a preset critical topological form, a multi-stage linkage protection device is triggered to implement energy discharge; and extracting a plasma spectrum fingerprint formed by the self-healing characteristic of the metallized film in the energy discharge process, and reversely reconstructing an explosion-proof performance grade evaluation system of the capacitor through the offset of a characteristic spectral line. The full-process closed-loop test of the capacitor from stress loading, failure early warning to performance evaluation is realized, and the environment simulation authenticity, the failure early warning accuracy and the performance evaluation scientificity of the explosion-proof test are improved.

The invention discloses a thick broad-bean sauce intelligent three-dimensional warehouse management system and a method thereof, particularly relates to the technical field of intelligent warehousing, and is used for solving the problem that an existing thick broad-bean sauce three-dimensional warehouse is lack of non-destructive whole warehouse maturity online detection and dynamic scheduling capability based on detection results. The maturity consistency and the quality stability of products in the same batch cannot be ensured. Double-domain excitation of micro thermal pulse and vibration frequency sweeping is applied to the outer surface of a container, a thermal attenuation curve, structural frequency response, a head space gas spectrum, a dielectric frequency spectrum and storage location microclimate parameters are synchronously obtained in the same acquisition window, and domain self-adaptive correction of characteristic parameters and periodic calibration of a standard calibration block are combined. Non-destructive maturity detection of all the containers in the three-dimensional warehouse is realized; detection results are directly input into the hierarchical scheduling module, and are sorted and delivered according to maturity priority and in combination with homogeneity constraint, so that the problems of inconsistent maturity, taste fluctuation and unstable quality of the same batch caused by delivery only depending on warehousing time in the prior art are solved.

The invention relates to a mechanical evaluation system based on rotation and inclination of a bracket-free appliance, and belongs to the technical field of orthodontic equipment. The system comprises four core units: an integral dental arch constraint unit simulates oral temperature through a constant-temperature water bath assembly, adjusts model postures through a camera holder type adjustable dental arch base, and constructs a precise constraint environment; the clinical displacement driving unit is based on an anchorage center bearing lever structure, and positioning-driving-data synchronization is achieved through adjustable anchorage positioning, multi-direction servo driving and displacement closed-loop calibration. The single-tooth mechanical sensing unit collects dynamic mechanical data, and interference is removed through Kalman filtering; and the data processing unit corrects attenuation deviation by using multiple linear regression in combination with environmental parameters, generates a mechanical attenuation curve, calculates a time attenuation percentage, and outputs a mechanical evaluation report by comparing with a clinical suitable force application interval. The evaluation accuracy and clinical suitability of the method provide a scientific basis for the optimization of an orthodontic scheme.

The invention provides an intelligent voice control system and a voice enhancement method in a reverberation environment. The method comprises the following steps: acquiring an initial voice signal in the reverberation environment; determining reverberation energy distribution in each frequency band according to the time-frequency spectrogram of the initial voice signal and the frequency response attenuation curve in each frequency band, and determining reverberation suppression gain of the initial voice signal in a time-frequency domain through all reverberation energy distribution; performing reverberation suppression on the initial voice signal according to the reverberation suppression gain to obtain a voice signal after reverberation suppression; performing time-frequency mask estimation on the initial voice signal to obtain a time-frequency mask of the initial voice signal, and determining residual interference energy of each time-frequency unit of the initial voice signal in a time-frequency domain according to the time-frequency mask and an interference covariance matrix of the target sound source; and performing harmonic enhancement on the voice signal after reverberation suppression through all residual interference energy to obtain a voice enhanced signal. By adopting the scheme of the invention, the acoustic crosstalk caused by reverberation can be suppressed.

The invention discloses a heating control method for an engine gas delivery pipeline of a marine gas generator set, which relates to the technical field of marine gas power systems, and comprises the following steps: collecting multi-dimensional environment state information of the gas delivery pipeline in real time, analyzing gas components and pressure fluctuation data, and calculating the temperature of the gas delivery pipeline; a theoretical dew point temperature and a potential paraffin precipitation temperature under real-time pressure are calculated by combining a fuel gas physical property database, a real-time heat exchange model is constructed by combining a pipeline outer wall temperature gradient and a cabin environment temperature, theoretical temperature attenuation curves of different positions of fuel gas in a pipeline are obtained, condensation and paraffin precipitation risk positions and degrees are predicted after comparison, and a real-time heat exchange model is established. And differential electric heat tracing control strategies of different sections of the pipeline are generated in combination with relative humidity data of the cabin. The method can adapt to the real-time physical property of gas and the heat exchange state of the pipeline section, and the heating control execution mode of the gas pipeline is optimized.

The invention belongs to the technical field of e-commerce, and discloses a customized furniture marketing and ordering transaction system fused with an AR scene. The method comprises the following steps of: accurately constructing a microscopic interest attenuation curve by collecting an interaction track and visual staying data of a user in an AR environment, and realizing dynamic quantification of purchase intention; the transaction path fracture node is innovatively identified, the conversion resistance index is calculated, the seamless transaction trigger point map is automatically generated, and smooth conversion from experience to transaction is realized. According to the invention, the physical attributes of the furniture are mapped into digital right parameters, and a mixed transaction mode containing two channels of real object purchase and digital asset subscription is constructed, so that the furniture value is transferred and added among different users. Especially in a hotel scene, a digital asset bidding transaction channel between an original guest and a new guest is established, temporary use experience is converted into continuous commercial value, and industrial ecology of efficient utilization of resources and co-creation of multi-party value is realized.

The invention relates to the technical field of battery life prediction, and discloses an energy storage battery life prediction method and device, and an energy storage system. The energy storage battery life prediction method comprises the following steps: determining a to-be-predicted target battery and an initial prediction model pre-trained by using a training total set; obtaining a distance matrix calculated by the capacity attenuation curve; wherein the capacity attenuation curve comprises a capacity attenuation curve of the training total set battery and a capacity attenuation curve of the target battery; according to the distance matrix, clustering is carried out to obtain a target battery device containing the target battery, and other capacity attenuation curves except the target battery in the target battery device jointly form a training subset; adjusting the initial prediction model by using the training subset to obtain a target prediction model; and performing battery life prediction on the target battery by using the target prediction model. Through the target prediction model adjusted by the screened and optimized training subset, the accuracy of predicting the service life of the target battery is improved.

The invention relates to a photovoltaic power station combined power generation optimization prediction system combined with an energy storage state, which aims at solving the problem of output deviation and equipment aging vicious cycle caused by energy storage health state attenuation and photovoltaic prediction model separation, and monitors the health state of an energy storage battery and the efficiency of a photovoltaic module in real time. Generating a dynamic attenuation curve and an efficiency prediction curve; constructing a health state-output coupling correction model based on the attenuation curve; an efficiency prediction curve is input into the model for output deviation compensation, and a high-precision photovoltaic power generation prediction value is generated; and finally, performing multi-objective optimization in combination with a power grid dispatching demand, and generating an energy storage-photovoltaic combined discharge instruction. The method realizes real-time dynamic coordination of energy storage attenuation characteristics and power generation prediction, overcomes the defect that a traditional static model cannot respond to the abrupt drop of the battery capacity, effectively blocks the vicious circle of prediction deviation and equipment aging, and improves the economy of a power station and the dispatching reliability of a power grid.

The invention provides an inflection point prediction method and an inflection point prediction device applied to the health life of a battery, and a computer storage medium. The inflection point prediction method comprises the following steps: acquiring an original capacity sequence of the battery in a cyclic charging and discharging process; inputting the original capacity sequence into an XLSTM network architecture for training and prediction to obtain a preliminary capacity prediction value; inputting the residual error sequence of the preliminary capacity prediction value and the true value into a multi-output Gaussian process error correction model to correct a prediction result to obtain a residual error correction value; generating a capacity attenuation curve according to the initial capacity prediction value and the residual error correction value; performing high-order differential analysis on the capacity attenuation curve, and determining the curvature of the capacity attenuation curve; and performing fusion identification on a high-order differential analysis result and the curvature by adopting double criteria, and determining a capacity attenuation inflection point of the battery. Through the inflection point prediction method, early, accurate and reliable inflection point prediction is realized.

The invention provides an automatic monitoring and management method and system for high-humidity vegetable protein meat processing, and the method comprises the steps: carrying out the correction processing of a light path transmission loss coefficient according to a spectral data matrix, employing a temperature compensation correction factor and a humidity influence correction parameter to eliminate environmental interference, extracting the position coordinates of a characteristic peak through the first-order derivative transformation, and carrying out the calculation of the position coordinates of the characteristic peak; obtaining standardized spectral characteristic data subjected to environment correction; a sampling time interval sequence is constructed through component concentration data of each detection point, a signal intensity attenuation curve is adopted to correct the time drift influence, interpolation calculation is performed on component concentration gradient distribution according to space coordinate positioning information, and a space distribution diagram reflecting the whole component state of the raw material is obtained. The defects of traditional chemical analysis and manual judgment in the raw material treatment process are overcome, the automation level and efficiency of vegetable protein meat production are improved, and meanwhile, the raw material proportioning accuracy is improved.

The invention discloses a logarithmic attenuation curve-based winding tension control and implementation method and system for a reel material printing machine, and belongs to the technical field of reel material printing equipment control. The method comprises the following steps that the initial angular speed of a winding motor is set, working parameters of a winding unit are collected, and then a logarithmic attenuation tension control curve is constructed according to characteristic parameters of a winding base material; calculating a set tension value by combining the collected working parameters with a logarithmic attenuation tension control curve; determining a tension permissible fluctuation interval according to the calculated set tension value, and then judging whether the collected working parameters are in the permissible fluctuation interval or not; if yes, the angular speed of the winding motor is not adjusted, and if not, the angular speed of the winding motor is adjusted till the collected working parameters are within the allowable fluctuation interval. The method solves the technical problem that the tension of the base material in the existing winding unit is difficult to display and accurately control.

The invention belongs to the technical field of copper foil oxidation resistance detection and analysis, and discloses a copper foil oxidation resistance detection method and system based on glossiness analysis, and the method comprises the following steps: obtaining glossiness attenuation standard curves of copper foil samples with different oxidation resistance grades; according to the inflection point position, dividing the glossiness attenuation standard curve to obtain different oxidation stages and glossiness change ranges; obtaining a to-be-detected glossiness attenuation curve of the to-be-detected copper foil; obtaining a glossiness attenuation standard curve with the highest similarity with the to-be-detected glossiness attenuation curve in all the glossiness attenuation standard curves, and calculating first defect influence degrees of the to-be-detected copper foil in different oxidation stages according to the glossiness change range of the glossiness attenuation standard curve and the to-be-detected glossiness attenuation curve in the same oxidation stage; correcting the first defect influence degree to obtain a second defect influence degree, and calculating the final similarity between the to-be-detected glossiness attenuation curve and all the glossiness attenuation standard curves; and dividing the oxidation resistance grade of the copper foil to be detected according to the final similarity.

The present application belongs to the technical field of copper foil oxidation resistance detection and analysis, and discloses a copper foil oxidation resistance detection method and system based on glossiness analysis, which comprises the following steps: obtaining a glossiness attenuation standard curve of copper foil samples with different oxidation resistance grades; dividing the glossiness attenuation standard curve according to the inflection point position to obtain different oxidation stages and glossiness change ranges; obtaining a to-be-detected glossiness attenuation curve of the to-be-detected copper foil; obtaining a glossiness attenuation standard curve with the highest similarity to the to-be-detected glossiness attenuation curve among all the glossiness attenuation standard curves, and calculating the first defect influence degree of the to-be-detected copper foil at different oxidation stages according to the glossiness change range of the to-be-detected glossiness attenuation curve at the same oxidation stage; correcting the first defect influence degree to obtain the second defect influence degree, so as to calculate the final similarity between the to-be-detected glossiness attenuation curve and all the glossiness attenuation standard curves; and dividing the oxidation resistance grade of the to-be-detected copper foil according to the final similarity.

The invention relates to the technical field of new energy power generation, in particular to a photovoltaic power station health state assessment method and system. According to the method, multi-dimensional data are collected through a distributed sensor network, a standardized time sequence is obtained after the multi-dimensional data are processed, a photovoltaic physical model is established according to the standardized time sequence, an efficiency attenuation curve is drawn, and the health state of a power station is evaluated; reasons of evaluation results are traced, judgment conditions are set according to different data characteristics such as the temperature of the backboard of the assembly, abnormity is accurate, tracing signals are output, and fault reasons are helped to be positioned; according to evaluation and traceability signal decisions, running signals are matched, different operations are carried out on normal, early warning and abnormal conditions, and the health of the power station is effectively maintained in time.