278results about How to "Fast solution" patented technology

The invention relates to the technical field of visual recognition, and discloses a visual recognition obstacle detection method, device and equipment and a storage medium, and the method comprises the steps: carrying out the time alignment and space registration of image data collected by a visual camera in a walking-instead-of-walk robot and point cloud data collected by a laser radar, and obtaining a multi-modal data stream; inputting the multi-modal data stream into a recursive gating deep convolutional neural network for feature extraction to obtain a time sequence multi-modal fusion feature; calculating an inter-modal correlation matrix, and constructing a three-dimensional voxel grid to obtain a three-dimensional environment representation; performing two-stage detection on the three-dimensional environment representation to obtain a comprehensive obstacle representation; environment complexity evaluation is carried out according to the comprehensive obstacle representation, and a self-adaptive real-time obstacle avoidance control strategy is generated; the adaptive real-time obstacle avoidance control strategy is converted into an optimal control problem, and rolling time domain optimization is performed to obtain an optimal obstacle avoidance control sequence, so that the accuracy of obstacle detection is improved.

The invention discloses an electric vehicle charging path planning method based on a dynamic energy consumption model and road network information. According to the method, the influence of different temperatures on the battery capacity is analyzed according to the charging and discharging experimental data of the lithium battery, the power consumption generated in the driving process of the electric vehicle is analyzed, and a refined air conditioner energy consumption model and a mileage energy consumption model are established. Based on an improved A * algorithm, a method for searching a reachable path with the minimum energy consumption according to the residual electric quantity of a vehicle-mounted battery, the position of a charging station and the real-time road condition is established. The A * algorithm of the model solving algorithm serves as an optimal priority search algorithm in graph theory search methods, and the optimality requirement can be met by reasonably designing a function; and meanwhile, aiming at an urban road network, a heuristic A * algorithm is adopted to be matched with the path optimization solution of a large-scale traffic network in a road-electricity coupling scene. The effectiveness of the provided model in the charging path decision is verified by respectively comparing three targets of time optimization, path optimization and comprehensive energy consumption optimization provided by the invention.

The invention provides a parallel iteration solving method and system for an electromagnetic finite element equation set, and relates to the technical field of electromagnetic finite elements, and the method comprises the steps: constructing a to-be-solved electromagnetic finite element equation set # imgabs0 #; dividing the electromagnetic finite element equation set into a plurality of calculation sub-tasks, and distributing a sub-matrix block # imgabs 1 # and a sub-right-end item vector # imgabs 2 # of the sub-tasks to each process in the super computer; by means of the initialized Hoseholder-GMRES algorithm, the processes are subjected to subtask calculation in parallel, and the local optimal solution # imgabs3 # of each process is obtained; summarizing the local optimal solution # imgabs4 # of each process to obtain an optimal solution # imgabs5 # of the electromagnetic finite element equation set; according to the method, the electromagnetic finite element, the Householder-GMRES algorithm and parallel computing are combined, and the solving efficiency of the linear equation set of the electromagnetic finite element is improved by utilizing a parallel optimization technology.

The invention relates to the technical field of computer-aided engineering, in particular to a nonlinear efficient iterative solving method for thermal strain load, which is used for solving an obtained finite element equation by using a modified Newton-Raphson method and comprises the following steps of: firstly, establishing a geometric model to be analyzed and performing grid division; the method comprises the following steps: firstly, setting a model to be analyzed, then setting boundary conditions and temperature field change conditions of the model to be analyzed, finally, inputting the conditions into an algorithm solver, solving a nonlinear equation set, iteratively inputting a load continuously according to a modified Newton-Raphson method in the solving process, calculating node displacement until convergence, and solving stress-strain conditions in the welding process according to a material constitutive relation. In the solving process, by judging the size of the two norms of the displacement increment obtained in the adjacent increment step heuristic stage, the convergence of nonlinear solving of the structure is enhanced through the calculation mode, and the solving speed of the nonlinear problem in the thermal elastic-plastic constitutive structure is increased.

The invention relates to a medium and low voltage collaborative flexible interconnection equipment planning method and device, and the method comprises the steps: analyzing the source load characteristics of all low-voltage transformer areas in a power distribution network, classifying all low-voltage transformer areas based on an analysis result, and generating a to-be-selected access position scheme of low-voltage flexible interconnection equipment according to a transformer area flexible interconnection division principle; constructing a direct-current power flow type double-layer planning model; and inputting the to-be-selected access position scheme into the direct current power flow type double-layer planning model, and solving the direct current power flow type double-layer planning model to obtain an optimal configuration scheme of the flexible interconnection equipment. According to the method, the number of flexible interconnection alternative positions can be reduced, and the model complexity is reduced.

The invention discloses a time sequence production model deduction method and apparatus, a terminal device and a storage medium. The method comprises the steps of obtaining a first time sequence production model of a power system; four different thinking chains are constructed; wherein the thinking chain is solved by using time decomposition, space decomposition or parallel calculation; the first time sequence production model is solved according to the four thinking chains, and a fourth solving result is obtained; the result with the minimum Euclidean distance sum with all the solving results is calculated and serves as a target result; and planning and scheduling the power system according to the numerical value of the decision variable in the target result. According to the method, the simulation precision is remarkably improved through time decomposition and space decomposition. Through parallel calculation, the solving speed is improved, important details are reserved, and errors caused by simplification are reduced. In addition, the thinking chain integration effectively integrates the results of a plurality of reasoning paths, and the representativeness and accuracy of the simulation result are improved.

The invention discloses a dynamic vehicle path optimization method based on online deep reinforcement learning. The method mainly solves the problems that an existing dynamic vehicle path optimization method is poor in dynamic change adaptive capacity and poor in algorithm real-time performance. The implementation scheme is as follows: 1) generating a data set; 2) constructing a decision model; 3) constructing and training a strategy network model and a value function estimation network model; and 4) solving a dynamic vehicle path problem with a time window by using the trained strategy network model. According to the method, a partially observable Markov decision model is established according to a time sequence of delivery clients of a motorcade, and a corresponding strategy network and a value function estimation network are designed to optimize a vehicle path. The strategy model obtained through training can quickly give the dynamic vehicle optimal path, and can adjust the planned path on line according to the dynamic change of related conditions, so that the solution quality is ensured, the solution speed is higher, and the real-time performance of the algorithm in processing the dynamic vehicle path optimization problem is improved.

The invention provides a trajectory planning method and device for a parking APA (Android Package Amplifier) in a multi-mode combination form, and solves the problems of high computing power consumption, low planning success rate, long planning time and poor planning effect during parking path planning in the prior art. According to the method, the scene type of current parking is determined by sensing and acquiring the surrounding information of the vehicle, and then a final path planning route is generated through a parking planning mode suitable for the current parking space scene. According to the method, the planning adaptability in the APA scene is improved, the planning solving success rate in different scenes is greatly improved, meanwhile, the consumption of a solving algorithm is effectively reduced, and the solving speed is improved.

The invention discloses a double-tower system process optimization method based on LU decomposition, and the method comprises the steps: taking the total value of a liquid phase product produced by a double-tower system formed by a depropanizing tower and a debutanizing tower as an optimization target, and constructing an optimization model by combining a constraint equation and a normalization equation; and performing iterative solution on the optimization model based on LU decomposition and a quadratic sequence programming method. According to the method, by judging the correlation of the constraint equation and optimizing the condition number, the influence of ill-conditioned problems can be effectively avoided, and the numerical stability in the solving process is remarkably improved. According to the method, the redundant constraint equation is removed, and the condition number is improved through LU decomposition basis changing, so that unnecessary calculation can be reduced, and the convergence speed of iteration is improved.

The invention belongs to the technical field of power system operation optimization, and particularly relates to a power distribution network dynamic topology reconstruction method and system with high permeability photovoltaic power generation, and the method comprises the steps: obtaining a power distribution network topology structure, network parameters, and node loads and photovoltaic predicted values; constructing a Markov decision process tetrad corresponding to the dynamic topology reconstruction problem; a sequential power distribution network dynamic topology reconstruction model is constructed by adopting a Bellman equation based on a Markov decision process tetrad, and instant cost and future cost are simultaneously considered in operation cost after topology reconstruction; and introducing an approximate dynamic programming method to transform the constructed dynamic topology reconstruction model of the power distribution network, and using a learning algorithm to complete model solution. According to the method, a stable power distribution network dynamic topology reconstruction scheme can be formulated under high-permeability photovoltaic power generation fluctuation, and the full-time operation cost is approximately optimal, so that the operation economy is improved, and new energy consumption is promoted.

The invention discloses a suspension bridge real-time state evaluation method and system based on BIM and FEM, and the method comprises the steps: obtaining and storing the sensor monitoring data of a suspension bridge and the BIM information of the suspension bridge, and constructing a model database; constructing a suspension bridge finite element simulation model of a geometric dimension based on the BIM model information data in the model database; reducing the order of the finite element simulation model of the suspension bridge based on a POD (Particle Oriented Decomposition) method to obtain an order-reduced finite element simulation model; correcting the reduced-order finite element simulation model based on a response surface method to obtain a corrected finite element simulation model; and performing state monitoring and damage identification on the suspension bridge by using sensor monitoring data and the corrected finite element simulation model, and evaluating the operation state of the suspension bridge in real time. The method improves the efficiency and accuracy of the operation state evaluation and damage identification of the suspension bridge, and effectively supports the real-time evaluation of the operation state of the suspension bridge.

The invention discloses a robot task allocation method based on an improved multi-target genetic algorithm, and relates to the technical field of robot task allocation, and the method comprises the following steps: building a multi-target robot task allocation problem model, and initializing model parameters; and optimizing the multi-target robot task allocation problem model by adopting an improved multi-target genetic algorithm to obtain a task allocation result. According to the method, the population is divided into a plurality of sub-populations, improved crossover mutation operation, population knowledge sharing interaction operation and fusion selection operation are introduced, an improved multi-target genetic algorithm is formed and applied to optimization of a multi-target robot task allocation problem model, and the problems that an existing robot task allocation technology is poor in solving quality and high in efficiency can be effectively solved. The solving speed is slow, and the diversity of solution sets is poor.

The invention relates to the technical field of power systems, in particular to a control method and device for a tracking-networking fusion phase angle of a converter, and the method comprises the steps: respectively obtaining initial phase angles of a tracking control link and a networking control link in the tracking-networking fusion converter; determining an initial fusion coefficient according to the SCR and the system inertia of the power system accessed by the tracking-networking fusion converter; adjusting the initial fusion coefficient by using the direct current side current and the grid side current to obtain a final fusion coefficient; and calculating a fusion phase angle of the tracking-networking fusion converter according to the final fusion coefficient, the initial tracking phase angle and the initial networking phase angle. Therefore, the problems that in the related technology, only the influence of SCR is considered, the influence of the inertia of the connected system and the power amplitude limiting of the converter itself is not considered, the fusion coefficient cannot be adaptively adjusted under multiple working condition power grids, consequently, the supporting capacity of the power grids and the stability of the converter are poor, solving is complex, the response time is long, and the stability of the converter is poor are solved. And actual conditions such as different faults and current limiting cannot be adapted.

The invention provides a rear wheel steering vehicle track planning method and system in a road scene based on iterative optimization, and the method comprises the steps: S1, building an optimization problem, and deducing a kinematics formula of a rear wheel steering vehicle, an obstacle avoidance constraint formula, and a calculation formula of the distance and angle error between a rear axle center point and a road center line; s2, on the basis of a road scene structure, constructing a collision-free track which fits a road center line as much as possible to serve as an initial guess in an optimization problem; s3, solving an approximate feasible track, softening the kinematics constraint into a penalty function, constructing a space-time corridor constraint, and constructing and solving an optimization problem to obtain the approximate kinematics feasible track; and S4, solving an optimal track, and gradually increasing sampling points in the optimization problem until the number of the sampling points reaches a threshold value. The method is combined with a vehicle positioning algorithm, track planning of the rear wheel steering vehicle in a road scene can be realized, scene robustness is realized, and the quality of the planned track is high.

The invention discloses a power distribution network double-layer expansion planning method considering carbon transaction and demand side management. The method comprises the following steps: acquiring data information of a power distribution network to be expanded; constructing a typical day scene based on a K-means clustering algorithm; the dynamic carbon emission intensity based on the carbon emission flow theory is adopted to calculate the carbon emission of the power distribution network; according to the time-of-use electricity price and the dynamic carbon emission intensity data of the power distribution network, the demand side electrical load is managed, and carbon transaction is carried out; establishing a power distribution network double-layer expansion planning model considering carbon transaction and demand side management; and upper and lower layer association of the power distribution network double-layer expansion planning model is converted into a single-layer model, linearization processing is carried out, and a solver is called for solving. According to the power distribution network double-layer extension planning method considering the carbon transaction and the demand side management, the carbon emission level of the power distribution network is effectively reduced, the system economy is improved, and a planning scheme which adapts to source load fluctuation and improves the operation stability of the power distribution network can be obtained.

The invention discloses a mold for core making equipment and a curing method and application of the mold, and belongs to the technical field of core making machine molds. The curing method comprises the following steps that sand shooting forming is conducted, specifically, in the mold closing state, molding sand is shot into a mold cavity from a sand shooting nozzle in a mold body to be used for forming a sand core; and heating and curing are conducted, specifically, a curing medium heated to be in a gaseous state is injected into the cavity through a plurality of air inlet channels, the curing medium makes contact with the peripheral side of the sand core and then is diffused and permeated, the sand core is cured from the periphery of the sand core, and the air inlet ends of the air inlet channels are separated from the sand shooting nozzles. According to the invention, molding sand injected into the mold can be quickly and uniformly attached to the surface of the loose core, and each part of the sand core can be quickly and uniformly cured in a short time, so that the curing speed of large pieces and high pieces is greatly increased, the curing effect and efficiency are improved, the compactness of the sand core can be improved through vibration, and the production efficiency is improved. And the product quality is further improved.

The invention discloses an electric energy scheduling method, system and equipment based on wind power uncertainty, and particularly relates to the technical field of electric energy scheduling, and the technical key points are as follows: calculating an error value of a mixed skewed distribution fitting curve and wind power output sample data, and fitting the wind power output sample data and the error through a normal cloud model, a fitting function used for representing wind power short-term output prediction error distribution is obtained; performing data sampling on the fitting function and the load prediction error distribution curve to respectively obtain a wind power prediction error value and a load prediction error value, and establishing an uncertainty constraint condition by using the wind power prediction error value and the load prediction error value; based on the uncertainty constraint condition and a pre-constructed first deterministic constraint condition, taking the minimum total operation cost of the main network system in the scheduling period as a target function, and constructing an electric energy scheduling model; and solving the electric energy scheduling model through a CPLEX solver to obtain an electric energy scheduling scheme of the electric power system.

The invention discloses an asteroid exploration heterogeneous robot group trajectory collaborative planning method based on convex optimization. According to the method, a heterogeneous robot group trajectory collaborative planning problem is converted into a heterogeneous robot group collaborative control optimization problem, and the optimization problem comprises dynamics, state constraint, control constraint, boundary conditions and a target function. According to the method, the established heterogeneous robot group cooperative control optimization problem is subjected to convex processing. According to the method, the convex optimization problem of heterogeneous robot group cooperative control is solved by adopting sequence convex programming. According to the method, the group trajectory collaborative planning problem of the asteroid detection heterogeneous robot is solved under a convex optimization framework, the calculation speed is high, and therefore the requirement of airborne real-time calculation can be met, that is, the solved control variables of the first few times are used as maneuvering control, the trajectory is continuously calculated and updated in real time by using state information collected by a current sensor, and the calculation speed is high. And continuously rolling to update the control of the robot.

The invention discloses a wind-light storage configuration method considering transient voltage constraint and inertia constraint, and the method comprises the steps: obtaining a wind-light typical output scene and a direct-current power transmission plan power through employing a k-means clustering method based on wind-light output and receiving end load data, employing a bilevel programming model for wind-light-storage capacity configuration, and obtaining a wind-light storage capacity configuration model; the upper-layer model takes the minimization of the total investment cost as an optimization target, and constructs a transient overvoltage constraint, an inertia support constraint and a capacity constraint based on the short-circuit capacity; and the lower layer model takes the operation cost of the thermal power generating unit and the new energy power abandoning cost as targets, considers the power balance constraint, the operation constraint and the like of the wind-light-storage channel direct current power transmission delivery system, introduces the power transmission confidence probability constraint, and realizes the measurement of the delivery reliability of the wind-light storage channel. An improved grey wolf optimization algorithm is adopted, a Logistic-Tent mapping opposite learning mechanism is added, a mutation operator, a crossover operator and a selection operator are introduced in the differential mutation process of the algorithm, the population number and category richness in the algorithm are improved, and the solving speed is increased.

The invention belongs to the technical field of electric power systems, and discloses an electric power adjustable resource modeling method, system, device and medium, the method comprises the following steps: carrying out typical electric power adjustable resource monomer modeling based on time-space transfer characteristics according to typical electric power adjustable resources to obtain a typical electric power adjustable resource monomer model; carrying out scheduling feasible region description on the typical power adjustable resource monomer model by utilizing a scheduling decision period to obtain a convex polyhedron scheduling feasible region; scaling a convex polyhedron scheduling feasible region of the typical power adjustable resource monomer model into a chinonol polyhedron feasible region by taking the highest similarity as a principle; and obtaining the scheduling feasible region of the power adjustable resource cluster through Minkowski summation according to the feasible region of the sino polyhedron. According to the method, the adjustment capability of the power adjustable resource cluster can be depicted, and then the power adjustable resource cluster can be used as a boundary condition to participate in a scheduling model, so that the problem that a superior power scheduling department is difficult to control mass distributed power adjustable resources is solved.

The invention discloses a rolling and packing workshop production control daily plan calculation method considering uncertain factors, and the method comprises the steps: taking a linear programming mathematical model as a core, and taking each cigarette production mark as a category; the method comprises the following steps: respectively acquiring production condition data of cigarettes with production marks including uncertain factors, expressing the data as constraint inequalities of corresponding marks, and establishing a joint production planning mathematical model of a plurality of operation areas; according to the characteristic that the actual production control process is divided into full-equipment production and single-machine ending, a multi-dimensional planning model is converted into two-time two-dimensional model solving to achieve rapid compiling and updating of a production control daily plan of a corresponding scene when different uncertain factors are updated, and the solving result is specifically shown as full-equipment production time and single-machine ending operation time. According to the method, the uncertain factors influencing production are included, the influence conditions of the uncertain factors are represented, the influence degree of the uncertain factors on the production time can be obtained by updating the calculation result, and production control management can conveniently respond to the generated uncertain factors in time and change a scheduling scheme.

The invention relates to the technical field of intelligent driving, in particular to a vehicle trajectory planning method and device, an intelligent terminal and a storage medium. The method comprises the following steps: acquiring vehicle information, driving information, driving environment information and a trajectory planning starting point, and adding the trajectory planning starting point into a candidate node set; a preset cost function is utilized to calculate cost values of nodes in the candidate node set, the node with the minimum cost value is determined as a first target node, and the preset cost function comprises a heuristic cost function determined based on the direction error and the lane reference line; track searching is carried out according to the vehicle information, the driving information and a preset searching decision, and a first target child node with the first target node as a father node is generated; determining whether the trajectory search is completed based on a preset end condition; and when it is determined that the trajectory search is completed, determining a planned trajectory of the vehicle based on a preset ending condition. By adopting the method, the vehicle trajectory planning speed can be optimized, and the trajectory quality can be improved.

The invention provides an intelligent scattered wave deception jamming method for three-channel SAR-GMTI, and belongs to the technical field of radar jamming and artificial intelligence. The method comprises the following steps: firstly, acquiring interference scene parameters from intelligence support and electronic reconnaissance equipment; then, interference parameters are calculated based on the scene parameters, a distance-direction imaging position error objective function, an azimuth-direction imaging position error objective function and a Doppler slope error objective function are designed, a synthetic objective function is constructed, and an iterative optimization method is designed to solve the interference parameters including the carrier speed of interference equipment and the irradiation position of interference beams; and finally, adjusting the speed of an interference equipment aerial carrier and the irradiation position of an interference beam, and intercepting and forwarding a radar signal. According to the invention, by dynamically adjusting the motion trail of the interference airborne machine and the irradiation position of the interference beam, a vivid false motion target can be generated, the interference precision and efficiency are effectively improved, and the defects of slow speed and low precision of a traditional scattered wave deception interference method are overcome.

The present invention discloses a rSOC operation model and a modeling method and system taking into account electric-hydrogen-thermal coupling, belonging to the technical field of energy conversion and storage; a modeling method of a rSOC operation model taking into account electric-hydrogen-thermal coupling includes: establishing a rSOC electrolysis model taking into account electric-hydrogen-thermal coupling; establishing a rSOC power generation model taking into account electric-hydrogen-thermal coupling; based on the rSOC electrolysis model taking into account electric-hydrogen-thermal coupling and the rSOC power generation model taking into account electric-hydrogen-thermal coupling, considering the start-stop and climbing characteristics of rSOC, establishing the rSOC operation model; linearizing the rSOC operation model by a piecewise linearization method and a large M method. The relationship between electric-hydrogen-thermal multi-energy coupling during the operation of rSOC is effectively characterized, the real operation of rSOC is simulated, and the difficulty of solving the rSOC operation model is reduced.

The invention discloses a data-driven enhanced optimization solving method for a security constraint unit commitment problem. The method comprises the following steps: constructing a security constraint unit commitment problem model of a power system; historical operation load data of a power system is collected, a confidence data set is constructed by using a Turing statistical method, and the confidence data set is divided into a training set and a verification set according to a proportion; constructing a neural network model, and inputting the training set and the verification set for network training; new load data of a power system is used as input, a multi-layer neural network is used as a classifier, and a logic strategy of unit operation is predicted online; by eliminating integer variables, an SCUC problem is converted into a continuous convex optimization problem, and by sorting a plurality of candidate integer solutions, feasibility of the model is simplified and optimized, and rapid online solution of the method is realized. According to the method, a high-quality approximate optimal solution can be provided, the solving speed is high, and the expandability is high. Not only can efficient power system scheduling optimization be realized, but also the peak regulation capability and the emergency response capability of the power grid can be enhanced.

The present application relates to the field of visual recognition technology, and discloses a visual recognition obstacle detection method, device, equipment and storage medium, the method comprising: performing time alignment and spatial registration on image data collected by a visual camera in a walking robot and point cloud data collected by a laser radar to obtain a multimodal data stream; inputting the multimodal data stream into a recursive gated deep convolutional neural network for feature extraction to obtain temporal multimodal fusion features; calculating an inter-modal correlation matrix, and constructing a three-dimensional voxel grid to obtain a three-dimensional environment representation; performing two-stage detection on the three-dimensional environment representation to obtain a comprehensive obstacle representation; performing environmental complexity assessment based on the comprehensive obstacle representation, and generating an adaptive real-time obstacle avoidance control strategy; converting the adaptive real-time obstacle avoidance control strategy into an optimal control problem, and performing rolling time domain optimization to obtain an optimal obstacle avoidance control sequence, thereby improving the accuracy of obstacle detection.

The invention provides a communication network topology planning problem generative solving method and system. The method comprises the following steps: modeling a network planning problem instance parameter into a network planning graph signal X; establishing a conversion relation between a network topology solution # imgabs0 # and a graph adjacency matrix; and inputting the obtained network planning signal X into a communication network planning problem solver based on a graph diffusion generation model, and obtaining the optimal solution of the network planning problem in combination with the conversion relation. The method is a novel generative sampling solution scheme, a plurality of high-quality network topology feasible solutions can be obtained at a time with low calculation complexity, and the network planning problem solving efficiency is effectively improved.

The invention aims to provide a compressor disc flow thermal coupling temperature calculation method. The compressor disc flow thermal coupling temperature calculation method comprises the following steps: acquiring a flow analysis result of fluid in a compressor disc cavity; the compressor disc cavity is divided into a first cavity body and a second cavity body according to the analysis result; simplifying the temperature in the first cavity into a cavity temperature node, and obtaining the temperature of the cavity temperature node and the temperature of a wall surface node of the first cavity; and the temperature in the second cavity is simplified into a heat flow line which exchanges heat with the wall face of the compressor disc cavity, a heat balance equation of the heat flow line is constructed, and the temperature of a node of the wall face of the second cavity is obtained according to the heat balance equation. The method can improve the heat analysis precision of the compressor disc.

The invention relates to the field of power grid material quality management and control, in particular to the technical field of quality evaluation, and more particularly relates to a power grid material sampling inspection strategy making method and system based on multiple dimensions, aiming at a special application scene of continuous small-batch arrival acceptance inspection of power grid materials by multiple suppliers, and aiming at the target of'quality-quality few inspection and quality-quality multiple inspection '. By introducing the AQL theory and integrating multiple factors such as the historical supply quality level of suppliers and the bearing capacity of detection resources, a total cost minimization model under the condition of maximum supplier sampling inspection strength and quality level evaluation sorting consistency is constructed, so that the optimal sampling inspection strategy of different power grid materials and different suppliers can be intelligently obtained, and the sampling inspection efficiency is improved. And a support is provided for an electric power company to make a sampling inspection scheme more accurately and realize reasonable allocation and utilization of resources.

The utility model belongs to the technical field of copper-clad ceramic substrate cleaning, and particularly relates to a plate brushing machine for cleaning a copper-clad ceramic substrate, which comprises a casing, an inlet, an outlet and a partition plate, the partition plate divides the inside of the casing into a washing chamber, a wiping chamber and a drying chamber, and the inside of the washing chamber comprises a first conveying roller, a water pipe, a spray head and a brush roller. The first conveying roller, the water pipe and the brush roller are rotationally installed on the machine shell in the vertical direction, and a spray head is connected to the water pipe. A sponge roller is arranged in the wiping chamber and rotationally installed on the machine shell in the vertical direction. A second conveying roller and an electrical bar are arranged in the drying chamber, and the second conveying roller and the electrical bar are installed on the machine shell in the vertical direction; water outlets are formed in the bottoms of the washing chamber, the wiping chamber and the drying chamber; compared with the prior art, the cleaning device can clean the two faces of the copper-clad ceramic substrate at the same time, only one speed reducer is adopted for driving, the cleaning efficiency is improved, and meanwhile energy is saved.