413 results about "Mechanism analysis" patented technology

The invention discloses a power system low-frequency oscillation mechanism analysis method based on micro-disturbance signal oscillation mode recognition. The method comprises the following steps of: providing a basis for judgment of oscillation mechanism types of power grid low-frequency oscillation accidents by using oscillation components provided by micro-disturbance recognition result in the process of a low-frequency oscillation accident; timely discovering a system running weak link and a potential oscillation source by performing statistic analysis on an entire-grid low-frequency oscillation mode oscillation frequency and damping ratio result which is calculated by micro-disturbance recognition in the given running time period; and establishing a corresponding relation between entire-grid oscillation mode characteristic change and system running condition parameter change to provide a basis for system running adjustment by performing multi-variable association analysis on the entire-grid low-frequency oscillation mode oscillation frequency and damping ratio result which is calculated by micro-disturbance recognition in the given running time period and the system running condition parameter.

The invention discloses a trajectory tracking sliding mode control method for a spraying mobile robot. The method comprises the following steps of: performing mechanism analysis on a mobile robot, and establishing a mobile robot kinematic model with non-integrity constraint; establishing a controlled object mathematical model of each branch controller of a wheeled mobile robot provided with a motor driving shaft disturbance term; identifying a traveling path by utilizing a computer vision system, and determining an expected motion track of each branch driving motor according to the kinematic model deduced in the previous step; detecting the rotating speed of the motor, calculating the actual motion angular velocity and actual motion angular acceleration of left and right driving motors of the mobile robot, and calculating the deviation and deviation derivative between the expected angular velocity and the actual angular velocity of each driving motor; establishing a sliding mode switching function which meets the speed control requirement of the driving motor; determining the sliding mode controller control quantity of the left and right driving motors of the mobile robot on the basis of the sliding mode surface function s; and respectively transmitting the control quantity of the motor of the mobile robot to the left and right driving motors.

The invention provides a parameter obtaining method of a single lithium ion full battery, and belongs to the field of new energy research. The method comprises the following steps that 1) a mathematical electrochemical impedance spectrum model of the lithium ion battery is established; 2) an electrochemical impedance spectrum of the single lithium ion full battery to be measured is measured actually; and 3) according to the established mathematical model, parameters of the actually measured electrochemical impedance spectrum are identified according to frequency ranges, and anode and cathode parameters of the single lithium ion full battery to be measured are obtained. Aimed at the defect that parameters cannot be identified effectively when a present semi-battery model is used for a full battery, characteristics of the electrochemical impedance spectrum of the lithium ion battery are combined, a manner of parameter identification according to the frequency ranges is used, and anode and cathode model parameters of the lithium ion full battery can be obtained rapidly and accurately. The method of the invention can be used for gaining mechanism analysis, SOC estimation and life prediction of the lithium ion battery.

The invention discloses a whitening composition and a skin care product with the same. The whitening composition and the skin care product contain glycyrrhiza glabra extracts, arbutin and 3-o-ethyl ascorbic acid, and preferably contain nonapeptide-1, nicotinamide, ethylhexyl methoxycinnamate or composition of the nonapeptide-1, the nicotinamide and the ethylhexyl methoxycinnamate. Through mechanism analysis, the composition has the advantages that possibly due to the mutual action and influence among various ingredients, the generation of melanin is inhibited through inhibiting the activity of tyrosinase; the migration of melanocytes to the skin is retarded; in addition, the plant and microbial peptide sourced whitening ingredients and various antiallergic ingredients are selected to be combined to obtain the safe and mild whitening effect.

A device for fault diagnosis of electric brush slip ring and method for mechanism diagnosis and maintenance and design are provided. The device for fault diagnosis of electric brush slip ring comprises at least one or more vibration shock sensors and / or shaft voltage detection sensors fixed on the machine casing of the electric brush, and a vibration and resonance demodulation fault diagnostic apparatus having diagnostic software for fault of electric brush slip ring and connected with the vibration shock sensors and / or shaft voltage detection sensors; the diagnostic software for fault of electric brush slip ring is used for analyzing the signals obtained by the vibration shock sensors and identifying the fault of the electric brush slip ring; and the vibration and resonance demodulation fault diagnostic apparatus has a vibration detection channel, a resonance demodulation detection channel and a computer having an AD converting acquitter and diagnostic software, wherein the detection signals of the vibration shock sensors and / or shaft voltage detection sensors are connected to the output end of the vibration detection channel and resonance demodulation detection channel; the output vibration and shock signals of the vibration detection channel and resonance demodulation detection channel are connected to the AD input end of the computer having an AD converting acquitter and diagnostic software; and the diagnostic software of the computer is for diagnosing fault, analyzing fault mechanism and determining maintenance and improved design for the acquired information.

The invention discloses a tight reservoir volume pressure crack network extension simulation and representation method. The method comprises the following steps of: firstly establishing a multi-crackstress interference-considered tight reservoir combined ground stress field calculation model by utilizing a displacement discontinuity method, mechanical mechanism analysis and crack initiation and extension criterions; aiming at a stress interference problem in volume pressure crack multi-crack extension process, establishing flow pressure drop distribution models, in primary and secondary cracks, of a fracturing fluid, so as to form a tight reservoir volume pressure crack horizontal well crack network extension theoretical model; and finally comprehensively analyzing influences, on volume pressure crack network structural morphology, of different factors, and defining a plurality of feature parameters to represent crack network structure morphology and attribute features. At last, the tight reservoir volume pressure crack network extension simulation and representation method is established. The tight reservoir volume pressure crack network extension simulation and representation method has the advantages of being comprehensive in model factor consideration, high in simulation effect and visual in result, and has a certain guiding significance for optimum design and efficient development of tight reservoir cracks.

The present invention discloses an online comprehensive control method for a hot-galvanized continuous annealing furnace. The method collects the operating information, including band steel speed, processing technique, steel coil codes and band steel specifications, of band steel through an online detection module. According to the collected operating information of band steel, the method calls main parameters through an expert database, so as to complete thermal load setting and speed setting by the co-operation of a speed model, a heat transfer model and a band temperature feedback model. Therefore, according to the set parameters, the method automatically controls a primary control system, so as to achieve the online production control of an annealing furnace. Based on heat transfer mechanism analysis, the method achieves the online production control of an annealing furnace by building a one-dimensional math model and the expert database with two cross-control methods: coarse tuning and fining tuning. In addition, the method also provides an additional series of complete control strategies such as a transition control method, so as to form a relative perfect control method. The models can be built conveniently and operate fast. Therefore, the method is suitable for the online production computation and control of an annealing furnace.

The invention discloses a small watershed region-oriented landslide hazard risk division method based on mechanism analysis. The small watershed region-oriented landslide hazard risk division method based on the mechanism analysis comprises the following steps of: I. establishing slope units of small watershed region-oriented landslide hazard risk division; II. calculating a risk evaluation index of each slope unit, performing normalization processing on the risk evaluation indexes, and establishing a geographic information database based on the slope units; III. calculating a value of the integrated risk degree Z of each slope unit to obtain a small watershed region-oriented landslide hazard integrated risk division result. According to the small watershed region-oriented landslide hazard risk division method disclosed by the invention, on one hand, an index system and a space unit are started from a hazard formation mechanism, and therefore, the division result is more objective and scientific, and on the other hand, suitable spatial precision is provided for hazard prevention, so that the risk division result is more directive.

The invention provides a method for calculating chemical mechanical polishing material removal rate. The method comprises the following steps: determining a calculation formula MRR=kPV of the material removal rate; analyzing a factor which affects the material removal rate, and obtaining a function equation of the factor which affects the material removal rate; and substituting the function equation of the factor into the MRR=kPV, obtaining a specific calculation formula of the material removal rate, and calculating the material removal rate MRR according to the specific calculation formula. Besides, the invention further provides a device for calculating the chemical mechanical polishing material removal rate. According to the schemes provided by the invention, the action rule among multiple bodies is deeply revealed by the analyzing of the factor which affects the material removal rate and the comprehensive considering of an interaction relationship among four bodies including wafers, particles, polishing pads and polishing fluids, the actual process of chemical mechanical polishing can be relatively objectively and truly described, and the method for calculating the chemical mechanical polishing material removal rate has active guiding functions on the mechanism analysis and the layout design of the CMP (Chemical Mechanical Polishing), as well as the research and the development of a large production line process.

The invention discloses a biochemical oxygen demand BOD soft measurement method based on elastic radical basis function neural network, belonging to the technical field of detection. The sewage processing process has severe production condition and serious random disturbance, has the characteristics of strong nonlinearity, large time varying and serious lag and is hard to build a precise mathematical model by mechanism analysis. The invention utilizes the liveness function of an RBF neuron to judge the activeness of the neuron, and divides the neuron with strong activeness; then, joint strength between the hidden layer neuron and the output layer neuron of an RBF neuron network is analyzed by calculating a mutual information dependency function so as to revise the neural network structureaccording to the mutual information intensity; and finally, the parameter of the neural network is adjusted until the network structure satisfies the requirement on processing information. The invention improves the quality and the efficiency of sewage processing, lowers sewage processing cost and provides in-time water quality and relevant parameter monitoring for realizing closed loop control for the sewage processing process so as to accelerate sewage treatment plants to efficiently and stably operate.

The invention relates to a model test device for measuring composite foundation lateral deformation and layered sedimentation. The model test device comprises a counter-force groove, a loading plate, a vertical counter-force frame, a lateral counter-force frame, a vertical jack and a model groove and is characterized in that: the left side, the right side, the rear side and the bottom of the model groove are sealed; the front side of the model groove is sealed by adopting a high-strength organic glass plate; the right side of the model groove is provided with a lateral stress measuring mechanism; and a test soil body is arranged in the model groove. The model test device disclosed by the invention is mainly suitable for a composite foundation indoor model test with remarkable lateral deformation of a soft soil foundation and the like, can be used for simulating single-layer or double-layer and multi-layer foundations, has the advantages of simple and reasonable structure and convenient and feasible conversation, can realize indoor simulation of composite foundation lateral deformation and layered sedimentation under complex conditions and can provide basis for practical engineering composite foundation design optimization and reinforced mechanism analysis.

The invention discloses a multifunctional test platform for landslide impact strength, comprising a slide channel, an accumulating channel, a supporting adjusting device arranged at the bottom of theslide channel, landslide impact sensors arranged in different positions in the accumulating channel, a data collection device arranged outside a test model channel and connected with the landslide impact sensors, and a rainfall simulator arranged above the slide channel; the slide channel and the accumulating channel are uniform in sectional size and are each formed by assembling a plurality of unit model channels 1 m in length and 1 m*1 m in inner diameter. The multifunctional test platform for landslide impact strength has the advantages that multifunctional landslide physical simulation experiments, such as rainfall-induced landslide mechanism analysis, landslide rock-soil deformation monitoring analysis, landslide speed monitoring and landslide impact test analysis can be carried out,and an experimental apparatus is simple and firm, convenient to disassemble and assemble; the multifunctional reusable test platform based on based on multiple variables is suitable for the scientificresearch and utilization of landslide disaster, and is worthy of popularization and application.

The invention discloses a silt coast high-turbidity sea area island siltation promotion engineering simulation method. A body-fitted coordinate system is adopted to discretize a study sea area, sediment grain size grouping is considered, wave radiation stress is utilized to calculate the wave influence, a two-dimensional wave current sediment mathematic model is established, the siltation promotion area is calculated, the effective siltation promotion amount is counted, the siltation promotion result is estimated, and mechanism analysis is conducted. By means of the silt coast high-turbidity sea area island siltation promotion engineering simulation method, the wave current sediment mathematic model is established aiming at unique dynamic geomorphologic features of a silt coast island of having numerous curved shorelines, large water depth, complicated underwater topography, strong tides under the effect of rotating flow, high water body turbidity suffering a lot from the weather waves, and sediment movement jointly acted by wave currents; meanwhile, the influence of bottom frictional resistance changing with different underwater topographies and shoreline shapes and sediment concentrations on sand contents in different seasons is considered, and the siltation promotion engineering dynamic geomorphology effect simulation requirements of silt coast high-turbidity sea area islands with different topographic shapes can be adapted to and met.

A newly-developed aviation electronic product hardware comprehensive FMECA method comprises the first step of defining a system to be analyzed, the second step of determining fault modes and reasons of appointed layers of a product based on a fault information database, fault mechanism analyzing and a fault module exposure test method, the third step of acquiring fault effects based on a fault simulation analytical method, the fourth step of carrying out the quantification hazard analysis, taking the multiple fault effects caused by the redundancy design into consideration and providing a quantification hazard analyzing method based on the multiple fault effects, and the fifth step of filling in an FMECA table and filling the fault modes, the reasons, the effect and the hazard degree all of which are acquired through analyzing into the FMECA table. The newly-developed aviation electronic product hardware comprehensive FMECA method is a hardware FMECA method based on the fault information database, fault mechanism analyzing, fault mode exposure testing, fault simulating and analyzing and the multiple fault effects, and is capable of providing more objective quantification for design and analyze workers and providing a basis for the design improvement on electronic products.

The present invention relates to a soil body property measuring device used for measuring a current waveform and the pore water pressure of a soil body under the lightning impulse action. The measuring device comprises a model box, a thunder and lightning generating device used for simulating the lightning stroke current shock and a display device, wherein the box body of the model box possesses three segments of cavity bodies in which the soil body samples can be filled, and a water pressure sensor is arranged at the horizontal position of each cavity body. Therefore, the soil body property measuring device can synchronously measure the soil body electrical response of the different soil bodies of different water contents, different salt contents or different acid-base values under the same lightning stroke environment, also can simulate the influence of the lightning stroke on the soil body electrical response very well, thereby providing guarantees for researching the soil body electrical response under the lightning impulse action and carrying out mechanism analysis.

The invention discloses a soft measurement method for sewage pumping station flow of an urban drainage converged network. The conventional drainage pipe network system has lots of uncertain factors and high measurement hardware cost. The method comprises the following steps of: analyzing main influencing factors of converged node pumping station flow by using mechanism analysis and priori information, and primarily determining influencing factors of a back-propagation (BP) neural network, namely determining input / output variables; determining lag time of different upstream pumping station flows by using a grey correlation analysis method; and establishing a grey neural network model on the basis of pumping station historical operating data, and predicting the converging node pumping station flow. By combining two methods of grey correlation analysis and grey neural network, the method solves the problem of difference of drainage time delay of different upstream pumping stations, well simulates the nonlinear pipe network drainage process, realizes soft measurement of converged node sewage pumping station flow, saves the hardware resources, and is low in cost and high in accuracy.

The invention discloses an improved water cloud model and a paddy parameter inversion method adopting the model. The canopy heterogeneity and phenological change thereof are considered in the construction of a planting area scene by the water cloud model; the secondary scattering between the plant and the underlying surface is considered in the scattering mechanism analysis process; a quantitative relation between the main scattering mechanism and the plant parameter is established. The model framework is more reasonable and is more suitable for the practical process of the growth and development of the crops, including paddy. The improved water cloud model is applied to the paddy parameter inversion method. On the basis of polarized SAR data, the contributions of different scattering mechanisms and the correlation thereof with different paddy parameters are fully considered. A polarized SAR paddy parameter inversion method considering the canopy heterogeneity and phenological change thereof is developed. According to the method, the inversion accuracy is high, the error is small, the parameters in the early phenological periods of the growth and development of the paddy can be accurately inversed and the monitoring for the growth of the paddy and the estimation for the yield are more true, accurate and reliable.

A modeling method of dynamic soft measurement based on pulse response template and parameter optimization includes setting up convolution mode based on pulse response principle, using pulse response parameter as main identification object, generating a set of pulse response template and template parameter constraint scope base on production process mechanism and utilizing optimized means to identify pulse response template parameter for finalizing optimization-solution of dynamic soft measurement model parameter.

The invention discloses a device for detecting air flow distribution in the cigarette smoking process. The device comprises a cigarette paper section cavity and a filter tip section cavity which are coaxially and movably connected. The cigarette paper section cavity and the filter tip section cavity can stretch and retract in the axial direction, a through hole allowing a cigarette to pass through is formed in the axial center, and a through edge hole is vertically formed in the circumferential side wall. The end of the through hole is connected with the cigarette in a sealed mode to form an air chamber. The end of the edge hole is connected with a flow measuring part. The invention further discloses a method for detecting air flow distribution in the cigarette smoking process. The cigarette is sealed in the two section cavities of the detection device, and readings of the flow measuring part are read to obtain air flow of a cigarette paper section and air flow of a filter tip section; according to the flow balancing principle, the air flow of the combustion cone end of the cigarette is calculated. The air flow of each section in the cigarette smoking process can be accurately detected, and detection results provide basic data for further guiding cigarette material research, cigarette burning and smoking mechanism analysis and cigarette material design.

The invention discloses an oblique photography measurement prediction rolling rock motion trail simulation system and a prediction method thereof. The method comprises the steps of installing a five-splicing camera system on an unmanned aerial vehicle flight platform, conducing low altitude oblique photography measurement on a slope rolling rock area to obtain oblique image data, preprocessing the image, adopting 3D modeling software to conduct live-action three-dimensional modeling, according to rolling rock trail experiments which are previously conducted, data of numerical value simulation and a matched result, establishing an engineering database of a geotechnical engineering expert system, through database matching and comprehensive inference mechanism analysis, obtaining main relevant parameters which influence a slope rolling rock motion trail and energy conversion, by using CoFrac rolling rock analysis software, and based on the obtained data and an energy tracking method, conducting numerical value simulation on the slop rolling rock motion trail, and analyzing energy loss and a potential motion trail of a rock belt in the rolling process of a rolling rock, so that a scientific basis is provided for governing the rolling rock.

By adopting the method of combining mechanism analysis with experimental analysis, the invention establishes a mathematical model of a constant temperature and humidity air-conditioning system, deduces a four-output and four-input transfer function matrix, and designs a decoupling compensator by adopting the feedforward compensation method so that the transfer function matrix of the constant temperature and humidity air-conditioning system can be converted into a diagonal matrix, thereby getting rid of the coupling among control loops and carrying out verification through emulation. Results indicate that the application effect of the decoupling controller in the constant temperature and humidity air-conditioning system is better, and the quality and the performance of the system are improved and increased.

The invention discloses a soft measuring method of an air particulate matter 2.5 (PM2.5) based on a self-organizing fuzzy neural network, and belongs to both the field of environmental engineering and the field of detection techniques. An atmospheric environmental system has the characteristics of multivariable, nonlinearity, a complicated internal mechanism, incomplete information and the like; the mathematic model of the atmospheric environmental system is difficult to establish through mechanism analysis; however, a neural network has better processing capacity to a highly nonlinear and seriously uncertain system. According to the soft measuring method of the air particulate matter 2.5 (PM2.5) based on the self-organizing fuzzy neural network, aiming at the problem that the PM2.5 is difficult to predict, an auxiliary variable relative to the PM2.5 is selected based on partial least square, then a soft measuring model between a relative variable and the PM2.5 is established by utilizing the self-organizing fuzzy neural network based on a sensitivity analytical method; the PM2.5 is predicted, a better effect is obtained; the in-time and accurate quality information of an atmospheric environment can be provided for an environmental management decision maker and people; the pollution control of the atmospheric environment is beneficially enhanced; the occurrence of serious pollution is prevented.

The invention discloses an actuator product acceleration factor determining method based on theoretical lifetime calculation. The method comprises the specific steps that (1) conducting main mechanism analysis, wherein actuator product weak links and main mechanisms corresponding to the actuator product weak links are determined; (2) selecting lifetime calculation models, wherein the corresponding lifetime calculation models are selected according to the types of the main mechanisms; (3) comprehensively determining acceleration factors, wherein the acceleration factors, corresponding to the product weak links, of the main mechanisms under different stress levels are calculated according to the determined stress types and ranges, the acceleration stress level is determined according to the acceleration factor standard deviation minimum principle, and the acceleration factors are determined according to the acceleration factor minimum principle. The actuator product acceleration factor determining method can be directly applied to products, the acceleration factors of the products are determined through the acceleration factors of the product weak links obtained through main mechanism analysis calculation, theoretical supports are provided for a product layer acceleration lifetime test method, and the actuator product acceleration factor determining method has the advantages of being clear in thought, high in operability and the like.

The invention discloses a preparation method of a recombinant pseudorabies virus for expressing reverse neural circuit tracing of green fluorescin with high sensitivity, and application, including (1) the preparation of the recombinant pseudorabies virus for expressing green fluorescin with high sensitivity; (2) the application to marking of a neural circuit. The recombinant pseudorabies virus for expressing the green fluorescin with high sensitivity is successfully prepared by using a platform. The recombinant pseudorabies virus for expressing reverse neural circuit tracing of green fluorescin with high sensitivity is successfully obtained. Wide application value is realized in aspects of neural circuit marking, medicine screening platform building, medicine inhibition virus action mechanism, viral vaccine and diagnostic reagent invention and development, animal model building, virus replication, pathogenic mechanism analysis and the like.

An evaluation method for a potential coefficient used to predict and forecast productivity of coalbed methane, comprises the following steps: determining main controlling factors on a basis of coalbed methane well methane production mechanism analysis; using GIS powerful functions of data management and spatial analysis to establish a sub-thematic image of each main controlling factor; using an ANN to determine each main controlling factor's weight contribution on the productivity; and establishing a coalbed methane productivity potential coefficient evaluation model based on the coupled ANN and the GIS to perform partition and evaluation on the coalbed methane productivity potential coefficient. According to a result of ANN and GIS coupled coalbed methane productivity potential forecast evaluation effect, a coalbed methane productivity potential evaluation partition scheme is provided. Evaluation partition is preferably matched with actual situation, evaluation results are basically the same with analysis results of methane production geological conditions, and evaluation effect is ideal. The evaluation method provides significant technical basis for reasonable design and making of block drainage schemes, and fills the gap of insufficient practical and theoretical mutual complementary research.

The invention provides a simulated annealing particle swarm based air-conditioning energy consumption model parameter identification method. The method includes: taking an energy consumption model function, created via a mechanism analysis method, of an entire air-conditioning system as an objective function, optimizing the objective function with a simulated annealing and particle swarm combined algorithm, and determining an optimal parameter combination under certain load. The concept of simulated annealing is introduced into the particle swarm algorithm, and parameters can be optimized and controlled in the process of particle evolution to be changed adaptively according to the algorithm, so that on the basis of existing advantages of the algorithm, global convergence of the algorithm is enhanced, convergence precision of the algorithm is improved, and the shortcoming that the convergence process stops easily and is trapped in local optimization easily is overcome.

The application relates to a comprehensive evaluation method and system for thermal runaway safety of a power battery. With the comprehensive evaluation method, multi-scale mechanism analysis and comprehensive evaluation are carried out on the thermal runaway of a battery. According to comprehensive evaluation method, related thermal stability testing is carried at three dimensions of the batterymaterial, the battery pole piece and the single battery body. On the basis of comprehensive comparative analysis of the test data, influences on the thermal runaway of the single battery body by thermal characteristics of different components and the mutual coupling effects between components are determined by combining in situ and ex-situ observation and material characterization methods. The mechanism analysis and thermal safety quantitative evaluation of the thermal runaway of the battery are provided by combining the test result of the adiabatic thermal runaway of the single battery body.The comprehensive evaluation method and system have the important practical value and guiding significance in the safety design and thermal runaway prevention of the power battery for an electric vehicle.

The invention discloses a soft measurement method for detecting the temperature distribution of billet inside a metallurgy heating furnace. The method selects a plurality of key variables affecting the temperature distribution of billet inside the furnace to form a process detection variable set, applies partial least square technology based on multivariate statistics projection principle to establish a soft measurement model between the temperature distribution variable of billet of the metallurgy heating furnace and the process detection variable and determines the optimal pivot numbers through cross check technology. The method avoids complicated process mechanism analysis, has convenient field implementation and high soft measurement precision and is particularly applicable to such industrial occasions similar to the temperature distribution detection inside the metallurgy heating furnace with high dimension and very rich process data. The soft measurement method can be used for monitoring in real time or directing actual production, improve the product quality, increase the yield and realize the energy conservation and consumption reduction of the metallurgy heating furnace overall.

The invention provides a central air conditioner energy consumption forecasting method based on operation data, and belongs to the field of central air conditioner modeling research. Aiming at the highly non-linear central air conditioner modeling problem which is difficult to solve through a traditional mechanism analysis method and a system identification method, central air conditioner energy consumption is forecasted through a method combining a Boruta feature selection method with a BP neural network. The operation data is subjected to energy consumption feature selection through the Boruta feature selection method at first, an energy consumption feature subset is obtained, the energy consumption feature dimension of the operation data is reduced, and then, the redundancy rate of theenergy consumption feature subset is decreased through a pearson correlation coefficient method; and finally, the energy consumption feature subset serves as input of a BP neural network energy consumption model, the central air conditioner system total power serves output of the BP neural network energy consumption model, and a training BP neural network energy consumption forecasting model is reliable and pervasive and has important significance to energy saving strategy implementation.

The invention discloses a high-definition multidirectional coordination insect migration radar measuring instrument for realizing insect migration mechanism analysis. Through cooperated operation of a high-definition phased-array radar subsystem and a three-grade multiband full-polarization radar subsystem, behavior monitoring for a migrated insect macroscopic group and microscopic individuals can be realized simultaneously, and fine measurement for three-dimensional tracks of the insects is realized, thereby providing an effective measurement tool for insect migration behavior mechanism research and agricultural insect early-warning. Furthermore, by means of target multi-band full-polarization multidirectional scattered information which is acquired by the three-grade multiband full-polarization radar subsystem, inversion of multidirectional biological parameters of the insects can be realized, wherein the biological parameters comprise information such as head orientation, body length and body weight of each insect, thereby supplying classification basis for on-air kind classification of migrated insects, and disclosing an on-air group structure of the migrated insects.