37 results about "Linear relation" patented technology

The invention provides a method for selecting a high-concentration VOCs adsorbent at different temperatures and application, and belongs to the technical field of waste gas governing. According to the method, through testing pore structure parameters of a model adsorption material with concentrated pore size distribution, a static adsorption isotherm and a dynamic penetration curve for VOCs at different temperatures, a high-concentration VOCs adsorbent is obtained; a linear relation equation of the critical aperture and the critical pressure is established through linear fitting, then a correlation equation of the critical aperture, the temperature and the partial pressure is established, and the appropriate aperture distribution range and the model selection standard of the high-concentration VOCs adsorbent at different temperatures are determined by combining dynamic adsorption results. According to the method, the ternary matching relation equation of the VOCs partial pressure, the temperature and the critical aperture is constructed, accurate type selection of the high-concentration VOCs adsorbent at different temperatures is achieved, the pore volume utilization rate and the adsorption capacity can be improved, meanwhile, desorption energy consumption and the VOCs pyrolysis risk are reduced, and a theoretical basis is provided for adsorbent type selection and technical optimization.

The invention discloses a seismic oscillation parameter selection and high arch dam response prediction method based on random forest-recursive feature elimination. The method comprises the following steps: (1) constructing a high arch dam finite element model; (2) seismic oscillation input of a finite element is obtained, and nonlinear seismic response of the arch dam under the seismic oscillation input is obtained through nonlinear dynamic time-history analysis; (3) taking the output parameters as a data set to obtain an optimal feature set of the high arch dam; and (4) on the basis of the obtained optimal IM feature set of the high arch dam and the corresponding random forest model, in combination with seismic oscillation input data, predicting a response result of the high arch dam through sampling. According to the seismic oscillation parameter selection and high arch dam response prediction method based on random forest-recursive feature elimination, the complex nonlinear relation between the features can be fully captured, the interaction between the features can be better considered, the complexity of the model can be better controlled, too many or too few features are prevented from being selected, the over-fitting risk is reduced, and the method is suitable for large-scale popularization and application. The performance and the effect of feature selection are improved.

The invention discloses an object tiny deformation measurement method and system based on interference fringe analysis, and belongs to the technical field of optical measurement. The method comprises the following steps: acquiring an interference fringe image and probe position and direction data; carrying out phase demodulation and sensitivity vector calculation on the surface of a measured object; obtaining the local phase number of each probe according to the interference image; calculating sensitivity vector data through a geometrical relationship; obtaining global phase and sensitivity data, obtaining initial full-field phase data through a weighted fusion method based on a geometrical relationship between a sensitivity vector and a deformation direction, calculating a consistency error, judging whether the consistency error exceeds a threshold value or not, if so, updating a deformation direction estimation value, and executing fusion processing again; and solving and obtaining three-dimensional deformation field data through a linear relation until the error meets the requirement or reaches the maximum number of iterations. According to the invention, the reliability and early warning capability of structural safety assessment in long-term monitoring can be improved.

The invention provides a double-layer safe trainable quantum machine learning method based on polynomial dynamics Lie algebra, and the method comprises the following steps: 1, constructing core variation simulation meeting the constraint of the polynomial dynamics Lie algebra, and guaranteeing the trainability of a model; 2, performing truncated Chebyshev graph coding at an input end, and constructing a rugged loss function landscape by using graph state entanglement and a Chebyshev tower strategy to prevent a snapshot inversion attack; 3, executing dynamic local scrambling at an output end, applying time-varying random local unitary transformation before measurement, and confusing a linear relation between gradient and a snapshot to prevent recovery attack of the snapshot; and 4, measuring and calculating a loss function, and updating parameters. According to the method, an orthogonal decoupling strategy is adopted, a privacy protection mechanism is externally arranged on an input / output interface, and trainability is anchored to core configuration, so that the capability of resisting algebraic attacks is remarkably improved while model convergence is ensured.

The invention discloses a combined system error correction and target state estimation method based on multi-angle measurement, which is applied to a three-dimensional passive multi-sensor multi-target tracking system. Comprising the following steps: constructing an augmented state vector based on a target state vector, an angle measurement deviation vector, a time deviation vector and a sensor position vector, and constructing an augmented state transition equation; performing modeling by taking azimuth angle measurement, pitch angle measurement and sensor position measurement as functions of an augmented state vector, constructing an augmented measurement vector and an augmented measurement equation, and determining a nonlinear relationship between the constructed augmented measurement vector and augmented state vector; azimuth angle measurement, pitch angle measurement and sensor position measurement are obtained through actual measurement, and an augmented state vector is estimated through linearization of a non-linear relation between a constructed augmented measurement vector and an augmented state vector and sequential filtering. The method can be applied to multi-source information fusion under a passive multi-sensor system, and the tracking and positioning precision of the target is improved.

The invention discloses a carbon emission intensity prediction simulation and land utilization management and control method and system, and belongs to the technical field of carbon emission calculation prediction.The method comprises the steps that firstly, multi-source space and statistical data are integrated to establish a basic database, and the carbon emission intensity of all kinds of space is calculated according to land space classification; then, constructing an extended STIRPAT model to screen a core driving factor, and constructing a feature project containing residual, lag and trend features based on the output of the extended STIRPAT model; training an XGBoost machine learning model by adopting a Bayesian optimization algorithm so as to capture a complex nonlinear relationship between the carbon emission intensity and the influence factors; and finally, inputting future scene feature data, generating a territorial space carbon emission intensity distribution map in combination with a PLUS model, and identifying a high-emission hot spot region. According to the method, the problem that the technical progress influence is difficult to quantify and the spatial explicit prediction is difficult to carry out in the prior art is solved, the prediction precision is remarkably improved, and a scientific basis and decision support are provided for regional territorial space planning and low-carbon management and control.

The invention discloses a method and a system for calculating the mixing proportion of multi-end-member water mass mixed particles. The method comprises the following steps: calculating the contribution proportion of each water mass end member of a mixing area by adopting an isotope mixing model; generating initialization information of a multi-end-member water mass mixed particle model by using the delta < 18 > O and salinity of each end member and derivative information; based on the contribution proportion and the initialization information, constructing a multi-end-member water mass mixed particle model; simulating a simulated delta < 18 > O-salinity linear relation of a mixing area under all iterative mixing proportion combinations based on a multi-end-member water mass mixed particle model; and calculating the mixing ratio of each end member by comparing the simulated delta 18O-salinity linear relationship with the actual delta 18O-salinity linear relationship. According to the method, the multi-end-member water mass mixed particle model is constructed, and iterative calculation and fluctuation simulation are combined, so that accurate quantification of a water mass mixing ratio and quantitative analysis of mixing sufficiency are realized.

The invention provides an air source heat pump frosting rate prediction method and system, and belongs to the technical field of air source heat pump defrosting control. The method comprises the steps that initial parameters needed by prediction are obtained, wherein the initial parameters comprise the outdoor air temperature and relative humidity, the outdoor heat exchanger coil pipe surface temperature and relative humidity and the outdoor heat exchanger air inlet speed; determining air state parameters at the outlet of the outdoor heat exchanger through iterative calculation on the basis of the initial parameters in combination with a linear relation of humid air state change in the enthalpy-humidity diagram; and finally, the real-time frosting rate is calculated according to the air moisture content difference, the air mass flow and the heat exchange area of the inlet and the outlet of the outdoor heat exchanger. The system comprises a corresponding parameter acquisition and calculation module. According to the method and system for predicting the frosting rate of the air source heat pump, accurate dynamic prediction of the frosting rate is achieved through theoretical modeling and iterative optimization, a reliable basis can be provided for intelligent defrosting control, and therefore the defrosting accuracy rate and the overall energy efficiency of the system are improved.

The invention relates to the technical field of settlement monitoring, and discloses a building accurate settlement monitoring and early warning system, which is characterized in that a measuring point module is provided with a near-side representative pile, a far-side representative pile, a pressure measuring pipe and a displacement acquisition device to respectively acquire axial force, underground water level and base displacement data; a parameter calculation module calculates a bearing share asymmetry index, an underground water level equivalent drawdown and an effective stress substitution amount, and eliminates a time trend term to obtain a base displacement residual error; the period and path analysis module divides closed periods according to the periodical characteristics of the equivalent depth reduction of the underground water level, forms parameter paths in all the periods, calculates directed areas and determines net drift amount; the mapping and prediction module establishes a linear relation between a directed area and a net drift amount based on the multi-cycle data to obtain an area drift mapping amount; the judgment module checks whether the area drift mapping amount is zero or not under a predetermined significance level, if yes, output is abnormal, and if not, output is normal.

The invention discloses a dam deformation space-time prediction method and device based on Kriging interpolation, and relates to the technical field of dam safety monitoring, and the method comprises the steps: carrying out the cleaning and unified processing of dam multi-source heterogeneous deformation monitoring data, including unifying a coordinate reference and carrying out the data fusion through a linear relation, forming a data set of a unified time vector; then, fitting data of each monitoring point and predicting future moments by using regression models such as Fourier series and the like; and after the consistency of the prediction result is checked, the kriging interpolation algorithm is adopted to carry out spatial interpolation on the predicted data passing the check, the space-time continuous deformation field of the dam is finally generated, and when newly added data exist, the process is repeated to update the model, the problems of space-time discretization and difficult fusion of the deformation data in the prior art are effectively solved, and the prediction accuracy of the dam is improved. High-precision and time-space continuous dam deformation prediction can be realized, and a reliable basis is provided for dam safety analysis.

The application discloses a bridge abnormal point identification method and device based on a multi-granularity time window, and the method comprises the following steps: acquiring a plurality of sample data of a bridge by using a real-time monitoring system; constructing a sample initial feature vector representation of a sliding time window, and fusing the sample initial feature vector representation to construct a sample initial feature matrix representation; fitting a linear relationship and a nonlinear relationship of sample neighborhood features of the sliding time window; based on the linear relationship and the nonlinear relationship, fusing linear residual and nonlinear residual block features to identify an abnormal probability value of a sample, and calculating the abnormal probability value of the sample to label an abnormal sample; and identifying abnormal values in the plurality of sample data by using the labeled abnormal sample to identify a bridge abnormal point. The application predicts an abnormal probability of a sample from potential neighborhood features of the sample in a multi-granularity sliding time window, realizes identification of abnormal data points, and provides great support in bridge structure health monitoring data anomaly diagnosis.

Disclosed are a video encoding method and apparatus using local illumination compensation in affine mode-based prediction. In the disclosed embodiment, a video decoding device generates a motion vector of a sub-block divided from a current block by using a shape of an affine model and a control point motion vector. A video decoding device generates a reference block of a current block by deriving a sub-reference block of a sub-block using a motion vector. When peripheral reference pixels of the current block are available, the video decoding device calculates, for an upper sub-reference block and a left sub-reference block of the reference block, positions of peripheral reference pixels of each of the upper sub-reference block and the left sub-reference block. When the peripheral reference pixels of the reference block are available at the calculated position, the video decoding device derives a parameter of a linear relationship between the peripheral reference pixels of the current block and the peripheral reference pixels of the reference block, and generates a prediction block of the current block by applying local illumination compensation to the reference block using the parameter of the linear relationship.

An existing communication optical fiber positioning method based on earthquake arrival time double difference comprises the steps that firstly, a DAS system is arranged at one end of an existing communication optical fiber and communicated, secondly, a plurality of monitoring points are evenly arranged in the length direction of the optical fiber, at least two earthquake sources are selected on the periphery, and the time when earthquake waves reach the monitoring points is collected through the DAS system, and thirdly, the time when the earthquake waves reach the monitoring points is collected through the DAS system. The method comprises the following steps: step 1, taking two adjacent monitoring points as a group of monitoring point pairs, calculating travel time difference from the same seismic source to the group of monitoring point pairs, then calculating to obtain double-difference travel time of different seismic sources, and covering all the monitoring point pairs, step 4, based on the double-difference travel time and a linear relation of relative positions of the adjacent monitoring points, establishing linear relation expressions of each group, summarizing to form an overdetermined linear equation set, and 5, solving the equation set to obtain the relative space relation of adjacent monitoring points, combining the absolute coordinates of one end of the optical fiber, and deriving the absolute coordinates of all the monitoring points through vector superposition to complete positioning. Therefore, the positioning speed is high, and the precision can be guaranteed.

This invention provides an automatic measurement method and system for the elongation of stainless steel laser welds. The automatic measurement method for stainless steel laser weld elongation includes: sample preparation and image acquisition; performing DIC analysis on the acquired image sequence to obtain a full-field strain cloud map, and obtaining the full-field displacement field and longitudinal strain field of the sample during the tensile process based on the full-field strain cloud map; weld region identification and width measurement to obtain the weld width; extracting strain from multiple virtual gauge lengths to form multiple sets of data; establishing a linear relationship between the overall elongation and the proportion of weld width; performing linear fitting on the multiple sets of data based on the linear relationship to obtain a coefficient proportional to the weld elongation; and obtaining the weld elongation based on the proportional coefficient. By preparing micron-level random speckle patterns and using a sub-pixel DIC algorithm to perform high-precision full-field strain analysis on the weld region, the method achieves high-efficiency, high-precision, and automated measurement of millimeter-level ultra-narrow weld elongation.

The invention provides a three-dimensional digital core permeability calculation method based on curve fitting and electronic equipment, and belongs to the technical field of reservoir three-dimensional digital cores, and the method comprises the following steps: obtaining a three-dimensional digital core grayscale image of reservoir rock; carrying out threshold segmentation processing on the grayscale image, and segmenting the whole digital rock core into a plurality of segmentation areas; calculating the permeability of each segmented region in parallel by adopting a finite volume method; the permeability of the total segmented area is calculated, and a curvilinear relation graph is constructed according to the linear relation between the permeability of the total segmented area and different numbers of segmented areas; reversely obtaining the permeability of the whole digital rock core by adopting a curve fitting method; according to the scheme, the calculation cost of the rock core permeability can be reduced, the calculation efficiency of the rock core permeability can be improved, and high usability and practicability are achieved.

This invention discloses an accurate zero-knowledge proof method for linear relations with hidden products, which transforms linear relations with hidden products on incomplete splitting rings into linear relations on the same surface; transforms the accompanying additional conditions into component-wise product relations on the same surface; and transforms the secret evidence on the same surface into element x on the same surface using an inverse NTT transformation. i The process involves selecting a uniformly random matrix and several vectors; generating a first-stage commitment and sampling vectors from a discrete Gaussian distribution to determine the public vector; selecting first challenge information; generating new commitments, blinding elements, and redundant terms using the first challenge information; randomly sampling second challenge information c from the challenge space C; determining the vector used for blinding using c; verifying whether the vector satisfies preset conditions and checking whether a series of equations hold true. If all equations hold true, the proof is accepted; otherwise, it is rejected.

This invention provides a method and system for managing carbon reduction and efficiency improvement through biomass co-firing in power generation enterprises. The method simultaneously considers combustion efficiency and emission reduction effects, overcoming the limitations of single-objective optimization in existing technologies and achieving a win-win situation for energy utilization efficiency and environmental benefits. A dual-objective prediction model is constructed through machine learning, capable of fitting the complex nonlinear relationships in the biomass co-firing process, with prediction errors far superior to traditional empirical and linear models. A quantitative algorithm combining dynamic emission coefficients and actual operating data enables rapid assessment of emission reductions, facilitating dual control of carbon emissions. A closed-loop system of "data-model-assessment-control-quantification" is constructed, enabling real-time optimization of co-firing parameters and automatic calculation of emission reductions without manual intervention, significantly improving response speed and reducing labor costs. Model parameters and thresholds are adjusted according to the unit type, biomass type, and environmental requirements of different power generation enterprises, making it applicable to various biomass co-firing power generation scenarios.

The invention discloses an electric power system saddle node bifurcation point solving method based on a hybrid estimation-correction and secant method, and belongs to the technical field of electric power system stability analysis. The method comprises the following steps: establishing an extended power flow equation set; obtaining an effective initial value through a pre-estimation-correction method; dynamically processing a network equation for a line fault scene; judging a bifurcation point interval based on the linear relation and the sensitivity; and combining a secant method with self-adaptive step length control to realize accurate positioning of the bifurcation point. According to the method, the defect that the numerical value is unstable near the bifurcation point in the traditional method is overcome, the calculation efficiency and robustness are improved, the method is suitable for a complex power system containing faults and new energy, and effective support is provided for stability analysis.

The application provides a method for prolonging the service life of a biodegradable mulching material, and belongs to the technical field of biodegradable mulching films.The application establishes a relationship curve between environmental parameters and degradation rate, determines the optimal ratio of PBAT and PLA and the critical temperature of phase separation based on the molecular chain segment movement theory of the carrier material, optimizes the uniformity of carbon black dispersion by using the interface interaction mechanism of surface modified carbon black and dispersant to enhance the anti-degradation ability, constructs a biodegradation control optimization model to realize accurate prolongation of the degradation life, determines four adjustment intervals and a nonlinear relationship model of adjustment coefficients by the experimental establishment of the degradation rate demarcation point, calculates the optimal formula, and uses a double rotor internal mixer and a double screw extruder to prepare the material, and simultaneously dynamically adjusts the model neighbor sampling number parameter through the degradation life adjustment function, so that the technical problem of insufficient service life of the biodegradable mulching material is solved.

The invention discloses a belt type dynamic cotton conveying weighing system and method. The belt type dynamic cotton conveying weighing system comprises a belt type conveying module, a measuring module, a data processing module, a display module, a parameter configuration module and a data storage module. The filtering algorithm unit adopts a Kalman filtering algorithm based on gain adjustment, and for peak noise, the real change of flow can be quickly tracked and noise interference can be effectively inhibited in the filtering process by monitoring the variance of residual errors on line and automatically adjusting gain factors; the dynamic calibration unit adopts a dynamic calibration mechanism, establishes a linear relation between the output of the weighing sensor and the actual weight under different working conditions, stores a calibration coefficient and zero offset and calls the calibration coefficient and the zero offset in real time, so that nonlinear errors and zero offset are counteracted, and the weighing precision is improved; the parameter configuration module adopts a carrier roller configuration dynamic adjustment mechanism, and dynamically adjusts the number and spacing of weighing carrier rollers and the conveying speed of a conveying belt according to different working conditions, so as to ensure that the system can keep the optimal weighing performance under different working conditions.

The application relates to the technical field of marine permanent magnet synchronous motors, and discloses a marine permanent magnet synchronous motor control method based on a hybrid grey wolf whale algorithm, which comprises the following steps: firstly, a decoupling mathematical model of a marine permanent magnet synchronous motor under a d-q synchronous rotating coordinate system is constructed; an id=0 vector control strategy is adopted, so that the electromagnetic torque Te and the q-axis current iq are in a linear relationship; a multi-target optimization function J is designed as a target function of the hybrid grey wolf whale algorithm; subsequently, the hybrid grey wolf whale algorithm is executed to perform online or offline optimization on the kp and ki parameters of a PI controller; and finally, precise speed tracking and anti-disturbance control of the marine PMSM are realized. The application realizes multi-index collaborative optimization; under typical working conditions of a ship, the dynamic response speed of the system is obviously faster than that of a traditional PID control, the steady-state speed control is more stable, torque fluctuation is significantly reduced, and the combination of fast response and high-precision control is realized.

The invention relates to the technical field of laser atmospheric transmission deflection, and particularly provides an environment black box space-based arbitrary spectrum laser deflection correction method and device, and the method comprises the steps: obtaining a plurality of frames of space two-dimensional images containing test laser spots, and obtaining the two-dimensional coordinates of the centers of the spots on a target plane at different environment moments through image processing; establishing a laser deflection mathematical model in the black box environment space based on the laser original incident angle and the two-dimensional coordinates, and determining refractive index environment factors and angle function refractive index environment factors corresponding to infinite air layers in the model; and determining the theoretical offset of the to-be-corrected laser in the laser deflection mathematical model according to the laser incident angle of the to-be-corrected laser, and completing laser deflection correction. According to the method, the laser deflection mathematical model based on the black box environment space is constructed, the complex nonlinear deflection problem is converted into the linear relation only related to the laser incident angle, and the theoretical laser offset when the environment changes is obtained to correct the actual laser deflection.

This invention discloses a fault diagnosis and analysis method and system for chromatographs, relating to the field of chromatograph fault diagnosis technology. The method includes the following steps: establishing a dynamic mapping model of the gas thermal field based on real-time temperature distribution information inside the chromatograph's detection cell; generating a temperature gradient distribution map within the detection cell through continuous acquisition by distributed multi-point temperature sensing units; and applying a controllable micro-amplitude pulsating airflow in the inlet path of the detection cell based on the temperature gradient distribution map output by the dynamic mapping model. By adjusting the pulsation frequency and amplitude, the gas flow state is disturbed, creating a diffusible gas disturbance zone inside the detection cell. This invention achieves temperature and flow field equilibrium in the detection cell through thermal field mapping and gas disturbance control, eliminating thermal stratification and retention effects, and restoring the linear relationship of the detection response. Furthermore, it dynamically corrects the time reference through a signal drift self-suppression mechanism, ensuring complete output of low-concentration signals, thereby improving the sensitivity, stability, and quantitative accuracy of the chromatograph.

This invention provides a storage-saving DTOF ranging method, apparatus, and electronic device. The original laser period is decomposed into two coprime positive integers to obtain a first exposure period and a second exposure period. The target object is exposed during the first exposure period to obtain a first histogram. The target object is then exposed again during the second exposure period to obtain a second histogram. Peak finding processing is performed on both the first and second histograms to obtain the first flight time corresponding to the highest peak in the first histogram and the second flight time corresponding to the highest peak in the second histogram. The distance information of the target object is calculated based on the linear relationship between the first exposure period, the second exposure period, the first flight time, and the second flight time. By decomposing the original laser period into two coprime exposure periods and performing two exposures to obtain the distance of the target object, the maximum laser period is reduced without affecting the ranging, thus effectively saving storage space for histogram statistics.

The application discloses a realization method and device for coastal heterogeneous aquifer characterization based on machine learning, and comprises the following steps: obtaining a plurality of sets of hydraulic conductivity coefficients randomly generated from a parameter prior distribution and corresponding model output simulation data from a seawater intrusion numerical model; generating a large number of samples of parameter difference and simulation data difference from the prior set through pairwise subtraction between samples; training a machine learning model by using the above data, and constructing a mapping relationship between the simulation data difference and the parameter difference; inputting the difference between the observation data and the prior simulation data set into the trained machine learning model, adding the obtained output to the prior parameter set, and obtaining the update result of the prior hydraulic conductivity coefficient set; and implementing iterative updating to obtain the hydraulic conductivity coefficient after iteration. The method can identify complex features and learn nonlinear relationships from training data, and optimal inversion effect is achieved in the characterization of complex non-Gaussian coastal aquifers.

The application discloses a DC system fault location method based on complex domain analysis, comprising the following steps: converting a preliminary fitting exponential function into Z domain for analysis to obtain the converted preliminary fitting exponential function; calculating and solving based on least square method rational approximation to determine the parameters of the preliminary fitting exponential function; calculating the Pearson correlation coefficient to measure the linear relationship between the candidate step length and the minimum fitting error, and optimizing the Pearson correlation coefficient through a particle swarm algorithm to select the best step length; obtaining the final fitting exponential function according to the parameters of the preliminary fitting exponential function and the best step length, solving the mathematical relationship between the distribution characteristics of system poles and the natural oscillation frequency; and calculating the inductance value in the fault line to estimate the fault distance by using the mathematical relationship and combining the inductance value per unit length, so as to realize fault location. The application can realize accurate fault location and meet the speed requirement of fault location.

The application relates to the technical field of laser atmospheric transmission deflection, and particularly provides an arbitrary spectral range laser deflection correction method and equipment based on an environmental black box space, which comprises the following steps: acquiring multiple frames of spatial two-dimensional images containing test laser spots, obtaining two-dimensional coordinates of spot centers on a target plane at different environmental moments through image processing; establishing a laser deflection mathematical model under a black box environmental space based on a laser original incidence angle and the two-dimensional coordinates, and determining refractive index environmental factors and angle function refractive index environmental factors corresponding to infinite air layers in the model; and determining a theoretical offset amount of to-be-corrected laser according to a laser incidence angle of the to-be-corrected laser in the laser deflection mathematical model, so as to complete laser deflection correction. The application converts a complex nonlinear deflection problem into a linear relationship related to only a laser incidence angle by constructing a laser deflection mathematical model based on a black box environmental space, and obtains a theoretical laser offset amount at environmental changes to correct actual laser deflection.

The invention relates to the technical field of power grid state monitoring, and particularly discloses a power transmission line icing galloping device layout method based on depth density clustering, which comprises the following steps: constructing an analysis unit feature vector based on microtopographic factor and meteorological factor data without depending on historical monitoring data; a depth density clustering algorithm is adopted, the high-dimensional nonlinear relation between the terrain and the weather is mined, a line is divided into a plurality of clustering subareas with consistent environmental characteristics, and a monitoring blind area is avoided; performing risk level quantitative evaluation on each clustering partition by combining a pre-trained icing and galloping risk prediction model; according to the risk level result, the types and the number of the sensing devices are configured differentially, and efficient resource allocation is achieved; in each clustering partition, the geometric, mechanical and electrical characteristics of the line are further combined, representative layout points are selected, and the monitoring sensitivity and representativeness are improved; finally, all the layout points are integrated to form a collaborative layout scheme, and the number and cost of equipment are remarkably reduced while risk coverage is guaranteed.

The invention relates to the technical field of round steel defect detection, and discloses a round steel surface defect detection system. According to the system, a linear relation model of the round steel cracking degree and the crack depth is established through a cracking and defect relation analysis module by using a reverse sampling analysis method, a round steel defect surface sample is subjected to acid pickling by a surface defect characteristic analysis module, surface impurities and oxide layers are removed, and meanwhile metallographic analysis is carried out; a scanning electron microscope is used for carrying out detailed analysis on internal morphology and surrounding microstructure changes of cracks, a crack change monitoring module is used for carrying out acid pickling treatment on casting blank surfaces obtained after steel rolling finished products, finish rolling, rough rolling and steel blank heating, and the crack change trend of the surfaces of all stages is recorded and analyzed; the surface quality improvement comparison module evaluates influences of different methods on round steel surface defect reduction and cracks, the data integration and report module summarizes data recorded by the modules, a crack distribution diagram and a surface quality pie chart are made, and various data comparison is visually displayed.

The invention discloses a DC system fault positioning method based on complex domain analysis, and the method comprises the steps: converting a preliminary fitting exponential function into a Z domain for analysis, and obtaining a converted preliminary fitting exponential function; calculating and solving based on least square method rational approximation, and determining parameters of a preliminary fitting exponential function; the linear relation between the candidate step length and the minimum fitting error is measured by calculating a Pearson's correlation coefficient, and the Pearson's correlation coefficient is optimized through a particle swarm algorithm, so that the optimal step length is selected; obtaining a final fitting exponential function according to the parameters of the preliminary fitting exponential function and the optimal step length, and solving a mathematical relationship between the distribution characteristics of system poles and the natural oscillation frequency; and calculating the inductance value in the fault line by using the mathematical relationship and combining the inductance value per unit length so as to estimate the fault distance, thereby realizing fault positioning. According to the method, accurate fault positioning can be realized, and meanwhile, the requirement of fault positioning on speed is met.