140results about How to "Solve randomness" patented technology

The invention provides an intelligent kitchen cooking system, which comprises a main food material weighing unit, a central control processing unit, a seasoning weighing unit and food processing equipment, wherein the main food material weighing unit is used for weighing main food materials, displaying a weighing result and / or outputting information of the weighing result to the central control processing unit; the central control processing unit is used for receiving input from a user and / or the main food material weighing unit, and the central control processing unit, in accordance with the input, is used for determining a menu, the food processing equipment, seasonings and dosages thereof as well as a cooking operating process; the seasoning weighing unit is used for weighing corresponding seasonings in accordance with the seasonings and the dosages thereof determined by the central control processing unit; and the food processing equipment is used for conducting cooking processing on food in accordance with the cooking operating process determined by the central control processing unit. With the application of the system and the method provided by the invention, the user, who cannot cook, can be guided in material preparing, seasoning, mastering of cooking methods, using of kitchen equipment and the like so as to complete cooking; therefore, the cooking becomes simple and convenient.

The invention discloses an urban water disaster risk prediction method based on an RBF (radial basis function) neural network-cloud model. The method includes (1) determining evaluation factors, levels and the indicator range under corresponding levels; (2) determining an expectation Ex and an entropy En of the cloud model; (3) determining the weight of each evaluation factor according to measured values of the evaluation factors and the indicator range of each level; (4) training the RBF neural network, finishing model establishment for the RBF neural network, inputting the measured values of the evaluation factors of the cloud model to the trained RBF neural network to perform simulated prediction, and obtaining a prediction value of each evaluation factor; and (5) substituting the prediction value of each evaluation factor to the integrated cloud model to allow the integrated cloud model to calculate corresponding certainty degree of the prediction value of each evaluation factor belonging to each risk level and multiply the corresponding weight to obtain integrated risk level distribution. The urban water disaster risk prediction method is visualized and reliable and strong in operability, and accuracy of prediction is improved.

Embodiments of the invention provide a work order processing method and apparatus, relating to the technical field of internet. The method comprises the steps of acquiring attribute information of work orders; determining priorities of the work orders according to the attribute information; and adjusting a processing sequence of the work orders according to the priorities. In the prior art, work orders are processed randomly, so that a lot of problems arise. The work order processing method and apparatus solve the problems in the prior art. Work orders of high priorities are ensured to have the process priority, and the customer service further satisfies clients.

The invention provides a safety quantitative evaluation method for an active power distribution network connected with a large-scale charging facility. The safety quantitative evaluation method is a quantitative evaluation method based on a probability statistics method, and comprises establishing a power distribution network safety evaluation index system aiming at operation characteristics of a distributed photovoltaic unit and an electric car, establishing a probability model for each index by means of the probability statistics method, a Monte Carlo sampling method and a three-point estimation method, calculating the composite weight by means of a precedence chart method and an entropy weight method, and combining the index model with the composite weight to determine the safety evaluation final result by means of a safety quantitative evaluation method based on a fuzzy matter-element analysis method. According to the invention, randomness and fluctuation problems caused by grid connection of the distributed device are solved; the constructed probability model is more suitable for processing practical problems; the calculating efficiency is greatly improved; the result of safety evaluation analysis is quantified into a concrete numerical value, and is more visual , and is convenient for subsequent analysis and optimization.

The invention discloses a pedestrian tracking method based on a low-altitude aerial photographing infrared video. Continuous and stable pedestrian tracking is realized through combination of a Lucas-Kanade optical flow method and local area secondary detection. The pedestrian tracking method comprises the steps that 1. an aerial photographing infrared pedestrian support vector machine (SVM) classifier is trained offline; 2. the initial position of a pedestrian target is determined; 3. the pedestrian target is preliminarily tracked by utilizing the LK optical flow method, and the position of the pedestrian target in the next frame is calculated; 4. a search area is set around the predicted position of the pedestrian target; and the infrared pedestrian is secondarily detected in the search area by utilizing the offline trained SVM classifier, and the position of the pedestrian target is updated; and 5. the center of the pedestrian target detected in the search area acts as input coordinates of the LK optical flow method of the next time, and the steps (3)-(5) are repeated. Continuous and stable tracking of the infrared pedestrian target can be realized by the pedestrian tracking method, and the problem of street lamp shielding can also be processed.

The invention provides a land surface temperature-vegetation index feature space dry and wet limit selecting method and device. The method includes the steps of firstly, determining the size of a research area, and performing pretreatments such as projection conversion, resampling and cutting on satellite remote sensing image data; secondly, removing image metadata influenced by cloud and terrain; thirdly, using the rest image metadata to build a land surface temperature-vegetation index two-dimensional scatter diagram feature space; fourthly, sampling the highest land surface temperature corresponding to different vegetation index conditions obtained in the third step; fifthly, linear fitting the highest land surface temperature and vegetation indexes to obtain the dry limit of the feature space through threshold setting and an iteration algorithm; presuming that the wet limit temperature is a constant and equals to the dry limit temperature at the total vegetation cover to obtain the wet limit temperature. By the arrangement, the problems that the current land surface temperature-vegetation index feature space dry and wet limit selecting is high in subjective randomness and uncertainty, and the like are solved.

The invention discloses an industrial robot TCP (Tool Central Point) calibration method based on uniform attitude distribution, and belongs to the technical field of industrial robot end tool calibration. The method comprises the following steps of: establishing an initial measuring point configuration by taking 'six-point calibration method' of an industrial robot as a primary calibration basis;constructing virtual points which are uniformly distributed on a spherical surface taking a fixed reference point as a spherical center by adopting a mechanical repulsion iterative method, and adjusting the virtual robots group by group to ensure that the centers of the tail ends of sixth axes of the virtual robots are positioned at the virtual points; and finally, adjusting the actual robot to the configurations of the screened measuring points, and solving the final TCP calibration result by using a least square spherical surface fitting method. The method solves the randomness of robot attitude selection and the nonuniformity of distribution when the current fixed reference point method is used for calibration, so that the robot attitude is uniformly distributed around the fixed reference point at each measuring point, the difference degree of the robot attitude between the measuring points is increased to the maximum extent, and the calibration precision can be effectively improved.

The invention relates to a ZigBee-based photovoltaic module online monitoring and fault diagnosis method, which adopts a modular design, divides a system into photovoltaic module wireless sensor nodes, a data gateway and a data management center. Each photovoltaic module wireless sensor node is composed of a CC2530 wireless transceiver, a sensor module and a power supply management module, and is used for monitoring operating parameters and environmental parameters of a photovoltaic module and transmitting the parameters to the data gateway through a ZigBee network; the data gateway is designed by adopting an Mini2440 controller based on an ARM core, completes caching of monitored data and forwards the monitored data to the data management center; and the data management center is designed by adopting QT software, realizes functions such as storing, displaying and querying the monitored data forwarded by the data gateway, configuring parameters of a sensor network and the like, optimizes a BP neural network fault diagnosis model by adopting a genetic algorithm based on the actual monitored data, and automatically diagnoses states of four common operating conditions such as normal, short-circuit, shadow and aging of a photovoltaic array.

The invention provides a raster Moire striped fine dividing method and apparatus, and belongs to the field of raster displacement measuring. A conventional raster sensor has the advantages of large measuring range, high environment adaptation capability, low cost and the like, and is widely applied to the industries of precision displacement measuring, digital display and numerical control, large-stroke precision positioning, precision processing, microelectronics and the like. At present, higher requirements for a wide-range nanometer level and the like of raster displacement measuring is brought forward in the various industries. When a raster sensor operates, output waveform of the raster sensor is quite complicated. The raster sensor does not necessarily move uniformly during a measuring process, and especially in a starting, stopping and inverting process, signals are random. According to the randomness of the raster signals, a wavelet fine dividing method is brought forward, high-speed high-precision synchronization data acquisition is performed on four paths of More striped signals outputted by a raster, after equal-magnitude amplification and nonopiate correction pretreatment is performed on the raster signals, wavelet phase modulation and phase extraction treatment is carried out, and finally the signals are converted to displacement.

The invention provides a photovoltaic power generation power prediction method based on a deep belief network. The photovoltaic power generation power prediction method comprises the following steps of collecting historical meteorological data and photovoltaic power generation output data of a to-be-predicted region to construct a training data set; dividing the historical meteorological data intoa plurality of samples, preprocessing the samples and constructing a meteorological factor data matrix; clustering the meteorological factor data matrix by adopting a fuzzy C-means clustering algorithm; establishing a photovoltaic power generation power prediction model by using a deep belief network; optimizing the initial weight of the prediction model by adopting a particle swarm algorithm; inputting historical meteorological data in the training data set into the prediction model for training to obtain the optimal weight of each layer of the prediction model, and storing the optimal weight; and judging the meteorological factor category of the to-be-predicted day by adopting a fuzzy C-means clustering algorithm, and then inputting all samples, which belong to the same category as theto-be-predicted day, in the meteorological factor data matrix into the prediction model to obtain predicted photovoltaic power generation power.

The present invention relates to a distributed energy system based on a fuel cell and wind energy. When wind resources are sufficient, blades of a wind power generation system rotate at a high speed under the action of the wind, and wind energy is converted into electrical energy through a motor so as to directly supply power during a powe utilization peak period; the motor is simultaneously connected to N parallel electrolytic tanks, the electrical energy is used for electrolysis of water during a power utilization valley period, and hydrogen and oxygen which are generated through electrolysis of water are respectively stored after compression; when the wind resources are insufficient, a hydrogen storage tank and an oxygen storage tank provide hydrogen and oxygen for the fuel cell to generate electricity; and hot water generated by the fuel cell flows back to the electrolytic tanks, and hot air discharged after heat exchange in the fuel cell can replace a conventional electric heating apparatus to heat the blades when the fuel cell works so as to prevent icing of the blades. Through rational arrangement of a total energy system, large-scale wind power can be conveniently and reliably incorporated into a conventional grid, meanwhile, effective output power of the wind power generation system can be increased from 96% to 98% at a rated wind speed, and thus, the distributed energy system has significant social and economic benefits.

The invention provides a wind turbine generator generated power prediction method based on K-means mean clustering. The method comprises the following steps of collecting historical meteorological data and corresponding wind speed values of a to-be-predicted region wind power plant and preprocessing the historical meteorological data and the corresponding wind speed values; calculating a correlation coefficient of the historical meteorological data to a wind speed value by adopting a Pearson correlation coefficient, reserving data of which the correlation coefficient is greater than a threshold value, and constructing a training set; clustering the training set data by adopting a K-means mean value clustering method; optimizing the initial weight of the BP neural network through a cuckoo algorithm, and constructing a wind turbine generator generated power prediction model; inputting the training set into the prediction model for training to obtain an optimal solution of the network weight of the prediction model, and storing the optimal solution; predicting meteorological factor data of a to-be-predicted day according to a clustering result of the training set, inputting the meteorological factor data into the prediction model to obtain a predicted wind speed value, and obtaining a predicted power generation power value of the wind turbine generator through predicted wind speedconversion calculation.

The invention provides a slicer capable of adjusting feed. The slicer capable of adjusting the feed comprises a horizontal material pushing path, wherein a feed path is arranged on the upper side portion of the horizontal material pushing path. The slicer capable of adjusting the feed is characterized in that a cutter disk with an end face rotating is arranged at one end of the horizontal material pushing path, a push plate capable of moving forward and backward is installed in an inner chamber of the horizontal material pushing path, and the push plate is driven by a driving mechanism with speed adjustable. The slicer capable of adjusting the feed solves the problem that an existing slicer is arbitrary in slicing direction and uneven in slice thickness, is adjustable in feed speed, even in pressure, reasonable in design, simple in structure, high in automaticity, and high in production efficiency, guarantees thickness uniformity of a final slice, and improves officinal effects of the slice.

The invention provides a reliability detecting and evaluating method of a power distribution system on the basis of a cloud model. The reliability detecting and evaluating method includes steps of searching line fault rate of a power distribution system to be detected and evaluated and historic statistics data of the fault rate of transformers; processing in standardization; calculating the cloud model digital characteristics of the line fault rate and the fault rate of the transformers by means of a backward cloud generator; calculating cloud droplets of the line fault rate and the fault rate of the transformers by means of a forward cloud generator; processing in inverse standardization; calculating reliability of the power distribution system by the feeder line partitioning algorithm to obtain values SAIFI, SAIDI and ASAI of the reliability of the power distribution system; drawing the values into diagrams and analyzing the reliability of the power distribution system to be detected and evaluated according to the diagrams. By the reliability detecting and evaluating method, qualitative laws of the parameters can be obtained, and the reliability of the power distribution system can be quantitatively detected and evaluated. In addition, the reliability detecting and evaluating method is good in universality and applicable to reliability detection and evaluation of the complicated power distribution system.

The invention discloses a multi-mode and low-energy-consumption indoor heat adjusting method. By using each indoor heating adjusting mode, a plurality of thermal regulation schemes are formed, indoorthermal environment parameters in each mode are subjected to off-line prediction, an input / output database is built according to a human body comfort model, a current optimal adjustment mode is preferably selected in real time through system identification, and the input / output database is updated according to user feedback. According to the method, the problems of randomness and blindness of a user when an air conditioner is set are solved, the temperature of the body sensing temperature can be compensated by other low-energy-consumption heat adjusting means by means of air flow, the set temperature value of the air conditioner is increased or the opening time of the air conditioner is shortened, and the energy-saving and environment-friendly effects of building equipment are further realized while a comfortable and healthy indoor heat environment is created.

The invention belongs to the technical field of guide of parking lots and discloses a distributed intelligent guiding system and method for a parking lot. The distributed intelligent guiding system for the parking lot comprises a video monitoring module, an information collecting module, a parking space monitoring module, a central control module, an anti-blocking module, a path guide module, an early warning module, a parking charging module, a data protection module and a display module. The distributed intelligent guiding system and method for a parking lot in the invention can dynamicallymonitor the parking space and prevent the problem of battling for a parking space from occurring; the parking fee of an unlicensed vehicle generated in the parking lot is accurately worked out throughthe parking charging module; the problem that a sentry box terminal cannot normally complete the operations such as entrance and charging which affect the normal operation of the parking lot is solved through the data protection module when the parking lot has problems such as computer breakdown, abnormal power failure, database file damage and the like, thereby greatly reducing the loss of the parking lot caused by failures.

The invention discloses an improved speed obstacle method-based unmanned aerial vehicle conflict detection and resolution method. The method comprises the steps of 1, establishing a conflict detectionmodel; 2, obtaining conflict conditions and non-conflict conditions according to the conflict detection model; 3, enabling an unmanned aerial vehicle to sense the position and speed of an invasion machine, carrying out prediction according to the conflict conditions and the non-conflict conditions, when the conflict conditions are satisfied, re-selecting the speed of the unmanned aerial vehicle and executing the step 4, and when the non-conflict conditions are satisfied, enabling the unmanned aerial vehicle to fly according to the original flight path; and 4, after the conflict is resolved, keeping the speed of the unmanned aerial vehicle during the conflict resolution and changing the direction of the unmanned aerial vehicle to ensure that the unmanned aerial vehicle flies toward the target point. The method is capable of solving the problems of randomness and easy shake of the speed obstacle method during the re-selection of speed, converting the optimum speed of the unmanned aerialvehicle, improving the speed of flying toward the target point, shortening the path through not recovering the original flight path after the conflict resolution, decreasing the maneuvering frequency, importing B splines and avoiding the unmanned aerial vehicle from being too large in turning angle.

The invention relates to an emergency event grading and classification method and device based on a deep convolutional neural network. The method comprises the steps of acquiring image information ofeach category of pre-classified emergency events, and building an emergency event image library; performing importance marking on each image in the image library; selecting a sample set from the marked emergency event image library; building a deep convolutional neural network model, wherein input of the model is an emergency event original image, and output of the model is an emergency event grading and classification vector; inputting the sample set into the model to perform training, and selecting a model by using S-fold cross validation; inputting an image of an emergency event to be graded and classified into the model for calculation, and obtaining a classification and grading result of the emergency event to be graded and classified. According to the method, the deep convolutional neural network is trained through historical image data so as to automatically learn features of an emergency event, thereby performing grading and classification on the event, and assisting a decisionmaker to master conditions of the emergency event scientifically and objectively.

The invention provides a mixed-liquid-flow energy-storage system with a reactive compensation function. The system includes a liquid-flow battery energy-storage system and a supercapacitor group, which are connected through a DC circuit breaker group. The supercapacitor group, a bidirectional DC / AC converter, a boosting transformer, an AC circuit breaker and an AC power grid are connected in order. The liquid-flow battery energy-storage system includes an all-vanadium liquid-flow battery, a sodium-sulfur battery and a zinc-bromine battery. The supercapacitor group is formed by serial or parallel connection of single-body supercapacitors. The single-body supercapacitors are double-electric-layer supercapacitors or electrochemical supercapacitors. Compared with the prior art, the mixed-liquid-flow energy-storage system with the reactive compensation function is capable of improving effectively stability and reliability of power supplying a distributed power generation system.

A machine tool metering parallel comprises a parallel base, a wedge, a lower seat pad, an upper seat pad and an adjusting bolt, wherein the outer end of the adjusting bolt is arranged on the sidewall of the parallel base, the inner end is rotatablely arranged in the bolt of the sidewall of the wedge, an inclined plane is arranged on the bottom surface of the inner cavity of the parallel base, the inclined plane is provided with a groove, the upper end face of the wedge is a plane and the lower end face is an inclined surface provided with a boss I, the wedge is arranged on the inclined plane of the parallel base, the boss I is arranged in the groove; a seat pad base is arranged on the upper end face of the wedge, an upper parallel is arranged in the cavity of the seat pad base, the upper seat pad is above the lower seat pad, the arc convex of the low end face of the upper seat pad is matched with the arc concavity of the upper end face of the lower seat pad; in addition, through holes used for passing a foundation bolt through are arranged in the middles of the parallel base, the wedge, the seat pad base, the upper seat pad and the upper seat pad. The machine tool metering parallel of the invention can be used to measure and display the pressure of the parallel and provide reliable technical data for debugging and installing the machine tool.

The invention discloses a bag supplying and bag feeding device for a full-automatic vacuum packaging production line. The bag supplying and bag feeding device comprises a bag supplying part and a bagfeeding part; the bag supplying part comprises a machine base and at least one set of bag supplying unit mounted on the machine base, and the bag supplying unit comprises a bag pushing cylinder, a bagpushing plate connected to the bag pushing cylinder, a bag pressing cylinder, a bag pressing plate connected to the bag pressing cylinder and a pair of bag hanging rods. Packaging bags penetrate through the bag hanging rods through handle holes and are limited between the bag pushing plate and the bag pressing plate, the bag pushing plate is driven by the bag pushing cylinder to push the packaging bags on the bag hanging rods to move forward to perform bag feeding, and the bag pressing plate is driven by the bag pressing cylinder to block or leave the front ends of the bag hanging rods to limit the packaging bags on the bag hanging rods or to enable the bag feeding part to take the packaging bags. The bag supplying and bag feeding device for the full-automatic vacuum packaging productionline has the advantages of novel structure, ingenious property, high stability and high precision.

The invention discloses an intelligent hydraulic perforating rig device. The intelligent hydraulic perforating bur device comprises a rig body and a perforating worktable. A hydraulic telescoping cylinder is mounted on one side of the rig body and a first driving motor is mounted on the other side of the rig body; a multi-stage gear is mounted above the hydraulic telescoping cylinder and is in transmission connection to the first driving motor through a V-shaped belt; a drill is mounted at the bottom of the hydraulic telescoping cylinder; a first telescopic push rod is mounted in the drill body; a second telescopic push rod is mounted on one side of a material conveyor belt; and a bottom plate is mounted in the bottom of the rig body. According to the intelligent hydraulic perforating rig device disclosed by the invention, the material conveyor belt is driven through the motor on the right side of the perforating worktable and a material is pushed before and after perforating through the two telescopic push rods, so that an automatic material feeding function is achieved; a dust collecting cabin is mounted on the left side of the device, and when perforating work is performed, a dust absorbing hole absorbs chippings generated by perforating into the dust collecting cabin.

The invention relates to a scene reduction-based intelligent power grid optimal scheduling method containing wind power and demand side resources, which comprises the following steps of: 1, predictingthe output power of a wind power plant on the next day, modeling a wind power prediction error, and randomly generating a plurality of initial scenes containing wind power output; step 2, performingscene reduction on a plurality of initial scenes containing wind power output randomly generated in the step 1 so as to generate a classic scene set; step 3, establishing an optimal scheduling model of the virtual power plant and the traditional unit considering uncertainty by taking minimization of the scheduling cost of the power system as a target; and 4, calculating the minimum value of the target function of the optimal scheduling model, and carrying out optimal configuration on the virtual electric field. According to the method, energy gathered by the virtual power plant can be effectively combined, fluctuation and uncontrollability of new energy generated output can be reduced during internal optimal scheduling, distributed power sources and loads are cooperatively managed, and safe and stable operation of a power grid is promoted.

The invention provides a method for measuring irregular objects on the bag loading platform of cross-belt sorter. The bag loading platform comprises a measuring light curtain, a light curtain controller, and a programmable logic controller (PLC). The measuring light curtain and the light curtain controller are connected through a power cable. The programmable logic controller is connected with the light curtain controller through an RS485 junction manner and communicates under a free port communication protocol. According to the invention, in order to make irregular objects drop completely in the outer edge of a cart, and to reduce the requirements on the positions of the objects by manual placement through the bag loading platform and on the package appearance of the objects onto the bag loading platform, a mathematical modeling process is carried out for the object testing manner with the introduction of analytic geometric operations to develop a mature measuring method for the sizes and positions of irregular objects, which improves the accuracy of loading bags and reduces the wrong packet rate while improving the suitability of the bag loading platform and reducing the labor intensity of the operation men.

The invention provides an automatic control system for water quality of an industrial boiler. The automatic control system comprises an automatic dosing system, an automatic sewage discharging system, an automatic monitoring system and a PLC central control system, wherein the automatic dosing system is connected with a dosing opening of the industrial boiler; the automatic sewage discharging system is connected with a sewage discharging opening of the industrial boiler; the automatic monitoring system is connected with a sampling opening of the industrial boiler; the automatic monitoring system automatically monitors the water quality of the industrial boiler in real time and transmits the monitoring results to the PLC central control system; the PLC central control system controls the dosing type, the dosing mode, the dosage and the dosing timing of the automatic dosing system according to the results, and controls the sewage volume and the sewage discharging timing of the automatic sewage discharging system. The automatic control system can automatically monitor the water quality of the industrial boiler system in real time and automatically performs dosing and sewage discharging according to the monitoring results, so as to control the water quality within the standard range.

The invention requests to protect a community discovery algorithm based on label propagation in random walk. The community discovery algorithm comprises the following steps: 1), establishing a transfer matrix: generating an adjacent matrix according to a network topological graph, and calculating the transition probability from a node to other nodes through the combination of the degree of the node with the adjacent matrix so as to finally obtain the transfer matrix; 2), calculating the weighting value of the node: defining the location probability distribution of a walker, and calculating the location probability distribution of the walker after the walker walks t steps and reaches a stable state according to the transfer matrix, wherein at the moment, the value in the location probability distribution is the weighting value of the node; 3), setting the threshold of a central node: completing the screening of the central node according to the descending sequence of node weighting so as to initially generate a sub community; 4), initializing a node label: performing label propagation from the central node, enabling node labels which are mutually and more tightly connected to become coincident gradually, and enabling the nodes holding the same label to form a community. Through the adoption of the community discovery algorithm disclosed by the invention, the problem of the randomness of updating node label sequences in the classic label propagation algorithm is solved, so that the precision of the algorithm is effectively improved.

The invention belongs to the technical field of automatic soldering of soldering machines, and relates to an automatic soldering machine teaching programming method based on a model and a numerical control drilling file, which comprises the following steps: (1) carrying out mechanical arm coordinate transformation modeling and model parameter calibration, (2) analyzing a numerical control drilling file in a to-be-processed circuit board design file to obtain circuit board drilling design coordinates, and (3) carrying out numerical control drilling on the circuit board drilling design coordinates. The method comprises the steps of (1) analyzing circuit board drilling design coordinates, (2) analyzing the circuit board drilling design coordinates, (3) displaying the analyzed circuit board drilling design coordinates as discrete mark points in a graphic window, (4) appointing a bonding pad by appointing the discrete mark points and obtaining bonding pad center design coordinates, and (5) establishing an operation environment for selecting the bonding pads through graphic operation by utilizing the steps (2), (3) and (4). (6) establishing a transformation model of the circuit board drilling design coordinates and the mechanical arm coordinates corresponding to the circuit board welding spots, (7) transforming the circuit board drilling design coordinates and the set mechanical arm rotating shaft angle into the mechanical arm coordinates of the corresponding welding spots of the circuit board to be processed, and (8) carrying out teaching programming on the circuit board to be processed. According to the automatic soldering machine mechanical arm coordinate transformation model with the rotating shaft, transformation from circuit board drilling design coordinates to mechanical arm coordinates corresponding to circuit board welding spots is established, a solder tip automatically reaches the specified welding spot position in a specified posture in a graphic operation mode, and teaching programming efficiency is improved.

The invention provides an online direct measurement device of wellhead crude oil water content on the basis of a radio frequency method. The online direct measurement device comprises a measuring sensor, an explosion-proof junction box, and an outdoor explosion-proof tank, wherein the measuring sensor comprises a probe, a joint body, a measurement circuit board, a protective pipe, a shell, a butting body, a pressing stud and a signal wire, the device also comprises a measuring circuit and an integrated data processing circuit, the device provided by the invention solves the problem that real-time on-line monitoring on water content of a Changqing oil field single well wellhead can not be realized at present, and overcomes the problems that the existing device is high in cost, wax is easily deposited due to the fact that the probe contacts with crude oil for a long time, and a data processing method of one-to-many greatly reduces the production input cost.

The invention provides a control method and a device for a flywheel energy storage system. The method comprises the steps of a, with the angular velocity, the d-axis current and the q-axis current of A, a flywheel as state variables, and the energy storage capacity of the flywheel as a control variable, constructing a model for the energy storage system of the flywheel, and discretizing the model according to the sampling time; B, constructing a performance index based on a second-order Renyi entropy, and determining an optimal input control variable increment with the partial derivative of the input control variable increment to be zero based on the performance index; C, determining a current optimal input control variable based on the optimal input control variable increment. According to the control method and device, based on the simplified energy storage model of the flywheel, a controller for the energy storage system of the flywheel can be designed. Meanwhile, the excess energy of the flywheel is stored, or the deficient energy of the flywheel is supplemented. In this way, a wind turbine generator set is ensured to transmit a smoothing power to the power grid.

The invention discloses a design method of an underflow manual wetland matrix structure based on flow field distribution. The method performs quantification design on main structural parameters influencing underflow manual wetland flow field distribution based on a seepage field theory, taking uniform distribution of a water flow around a bed body as a purpose, and taking a three-dimensional finite difference underground water flowing mathematical model as a design calculation basis, wherein the main structural parameters include manual wetland unit division, unit pond body length-width ratios, water distribution area length, water collection area length, bed body depth, filling layers of a main body filler area, and filler permeability coefficients; matrix fillers are measured by a Darcy permeability test; the fillers with required particle size are screened out. When the design method performs design calculation on the structural parameters of underflow manual wetland, the selection of the structural parameters is simple, convenient and practicable; the underflow manual wetland constructed according to the design method can greatly improve and increase the hydraulic efficiency of a system and utilization ratios of the fillers, can avoid a channel flow, a short flow and a dead area, and can further improve and prolong a purifying effect and the service life.