328results about How to "Simplify the modeling process" patented technology

The invention provides a method for estimating a charge state of a power battery with relatively less errors, which includes the following steps: through fitting of measured data, a Ki curve of correction coefficient of charging-discharging efficiency at different rates, a Kw curve of the correction coefficient of the charging-discharging efficiency under different temperature as well as a Kc curve of the correction coefficient of actual electric quantity are obtained and a Kc value can be obtained through a historical record; according to the state of the power, the following formulas are applied: in the working state, Ct = (KCC0 + sigma KiIiti) Kw is applied; in the non-working state and when a self-recovery effect is completed, C = KWKCC0t is applied; in the non-working state and when the self-recovery effect is not completed, Ct = Cm is applied; Ki, Kw, Kc are called from the curves to obtain remaining capacity Ct at the moment of obtaining the power battery so as to complete the estimation of a SOC battery. The invention with easy industrial application of models is applicable to both working state and non-working state of the battery; the errors of the estimation result are relatively less and the relevant curves are established.

The invention relates to a three-dimensional elliptical vibration cutting device, belonging to the field of cutting and ultra-precision cutting machining of materials which are difficult to machine. A diamond cutter is guided through flexible hinge mechanisms respectively along an X direction, a Y direction and a Z direction, and further, is driven by three piezoelectric stacks respectively alongthe X direction, the Y direction and the Z direction; the piezoelectric stacks of the X direction and the Z direction are preloaded by preloading screw bolts along respective axial direction; the piezoelectric stack of the Y direction is preloaded through a screw bolt screwing wedge; the preloading processes of the three directions are mutually independent; through regulating and matching the initial phase position and the amplitude of a driving signal for each of the three piezoelectric stacks, the projections of the cutter location point movements of the diamond cutter in an X-Y plane and aY-Z plane are elliptical motions, and the projection of the cutter location point movements of the diamond cutter in an X-Z plane is reciprocating elliptical motion or linear motion. The three-dimensional elliptical vibration cutting device has a novel and simple structure, is easy to implement, and is beneficial to obtaining the best cutting machinability of the diamond cutter.

The invention discloses a random forest-based non-invasive home appliance identification method, which aims to monitor a family internal power utilization condition without invading an interior of a family user, and is high in identification speed and high in accuracy. According to the adopted technical scheme, the method comprises the steps of establishing a load feature database; taking load features stored in the feature database as an original training set, and generating N training sub-sets in the original training set; combining N generated decision trees into a random forest; finishing a training process of the random forest through optimization of weights of different decision tree leaf nodes; detecting an electric appliance switching event by utilizing a secondary detection algorithm to obtain starting and ending time of event occurrence, and separating out current and voltage signals of a switched electric appliance from a bus signal, thereby obtaining the load features from separated data; and finally inputting the load features as input parameters to the trained random forest, and finishing electric appliance identification through voting.

The invention provides a speech recognition method based on a convolution neural network, which is more good at extracting high-level features, has simple modeling process, is easy to train, has better generalization performance of the model, and can be more widely applied to various speech recognition scenes. The method comprises the following steps: S1, preprocessing the input original speech signal; S2, extracting the key feature parameters reflecting the characteristics of the speech signal to form a feature vector sequence;S 3, base on that DCNN network model, taking the connected time classifier CTC as a loss function, constructing an acoustic model of an end-to-end mode; S4, training the acoustic model to obtain the trained acoustic model; S5, inputting the feature vector sequence to be recognized obtained in the step S2 into the trained acoustic model to obtain a recognition result; and S6, performing a subsequent operation on the basis of the recognition result obtained in step S5, that is, obtaining a word string capable of outputting the speech signal with a maximum probability, that is, a language character after the original speech is recognized.

The invention discloses an adaptive robust scheduling optimization method for a virtual power plant. The method adopts adaptive robust scheduling optimization to process the output uncertainty of renewable energy sources, and considers the day-ahead and real-time two-stage scheduling of the virtual power plant. A model established with the adaptive robust scheduling optimization method is a three-layer optimization model. In order to solve the problem, the method comprises the following steps that: firstly, importing an auxiliary variable, dividing the model into a single-layer main problem and double-layer sub problems; secondly, through a duality theory, converting the double-layer sub problems into the single-layer problem; and finally, adopting a column sum constraint generation method, and solving the main problem and the sub problems through alternating iteration until the gap of two problems is converged into an acceptable range. Compared with statistic robust optimization, themethod is characterized in that the balance situation of the regulation strategy and the real-time market of each polymerization unit in the virtual power plant after the output of the renewable energy sources is obtained is considered, the fluctuation of renewable energy sources can be effectively stabilized, and the economic benefit of the virtual power plant is improved.

The invention provides a three-dimensional human modeling method by using cartographical sketching, comprising the following steps of: 1. analyzing a sketch: decomposing a human sketch into a skeleton stroke set Ss, an outline stroke set Sp and a thread stroke set Sc; 2. extracting the model characters: extracting a human skeleton structure on a predefined human mesh model MH; 3. recovering the depth: identifying a thread determination result on the thread stroke set according to the skeleton structure and calculating the three-dimensional posture according to the human skeleton structure based on the two-dimensional human posture; and 4. reconstructing three dimension: deforming the section outline characteristics of four limbs and a trunk mesh model. By using the cartographical sketching to draw human front elevation skeleton and outline and directly generating the three-dimensional mesh model, the invention accords with the plane drawing habit of an animation role designer, simplifies the human modeling flow and greatly reduces the time for users to construct human models.

The invention discloses a wind and photovoltaic generation power prediction system with multiple prediction modes. The system is characterized by comprising a numerical value weather prediction data acquisition module for inputting numerical value weather forecast data serving as basic data of a prediction algorithm, a prediction mode selection module used for selecting a proper prediction algorithm to predict the power of a wind power plant or a photovoltaic power plant, a prediction algorithm module used for predicting the power of the wind power plant or the photovoltaic power plant and comprising a physical model, an adaptive logic network algorithm model and a BP neural network model, and a prediction result storage module for storing result data predicted by the prediction algorithm module. According to the method, the numerical value weather forecast data is used as input data of the prediction algorithm, the most proper prediction method is selected through the mode selection module, and a power prediction result is obtained.

The invention provides a day-ahead economic dispatch method for a virtual power plant. The method includes the following steps that first, a day-ahead economic dispatch mixed integer linear programming mathematical model making benefits of the virtual power plant maximum is built, and in an objective function, a stochastic programming method is adopted for handling the uncertainty of electricity price; second, constraint conditions are built to make an electric power system meet power constraint, unit operation constraint and contract electric quantity constraint, and in the constraint conditions, a robust optimization method is adopted for handling the uncertainty of generated output of renewable energy; third, a prediction error coefficient and a robust coefficient are set; fourth, calculation software is used for obtaining an optimum day-ahead economic dispatch result. Compared with the prior part, the method has the advantages of being good in calculation result, high in calculation efficiency and the like.

The invention relates to a finite element modeling method for the welding line of a soldering board based on vehicle crash simulation, belonging to the vehicle computer-aided design technique field, comprising the following steps: first, baseplate modeling, which comprises baseplate hard spot arrangement, baseplate reseau partition, and baseplate reseau translation; second, building a double-beam welding line model, which comprises space nodes arrangement, a double-beam manufacturing, and connection of the beam and baseplate; third, the attribute assignment of the double-beam unit, which comprises the attribute assignment of beam unit material and the attribute assignment of the beam unit section; fourth, moving the built welding line model of the soldering board and the baseplate reseau model into an impact finite element computational model. The invention considers the material attributes of the welding line, as well as considers the shape of the welding line, can accurately simulate the deformational behavior of the welding line in crash simulation, enhances the simulation accuracy of vehicle crash, is rapid and effective, and is easy to master technicist.

The invention provides a speed planning method, a system, a control system, a robot, and a storage medium. The method comprises the following steps: establishing a track model according to chronological order and setting a constraint condition, wherein the track model comprises an end track, and at least one of final motion parameters corresponding to the the end track is non-zero; according to the track model, establishing a speed planning curve model; and based on the speed planning curve model and according to the constraint condition, calculating optimal motion parameters by using an optimal time as a target; obtaining a target speed planning curve based on the optimal motion parameters. According to the invention, first, speed planning can be performed on a path segment in any start or end state without being limited by start or end parameter values of the path segment; furthermore, all branch paths can be covered in an S-type acceleration and deceleration process, so that the application range is greatly broadened; and finally, according to the speed planning method provided by the invention, whether the speed is first constrained or the acceleration is first constrained doesnot need to be distinguished, thereby greatly simplifying a modeling process and helping a user to improve work efficiency.

The invention discloses a mixed recommendation method based on excavation of a user behavior compositing factor. From the point of view of user behavior influencing factors (personalized factors and common factors), in allusion to each influencing factor, a personalized recommendation algorithm is provided so as to fully extract influence of the influencing factor on user behavior; finally, according to historical data of users, recommendation results reflecting the two kinds of influencing factors are dynamically mixed, and personalized recommendation services are provided for different users.

The invention relates to a method for establishing a load sensitivity controlled axial plunger pump virtual prototype. The method comprises the following steps of: 1, establishing a kinetic model of an axial plunger pump in kinetic simulation software, and establishing a hydraulic system model of the axial plunger pump in hydraulic system simulation software; 2, establishing a software interface by using correlated condition variants and parameters associated with each other in the simulation process of the kinetic model and the hydraulic system model as transfer parameters between the two models; and 3, performing real-time data transmission and united simulation by using the software interface between the kinetic model and the hydraulic system model. By using a hydraulic-mechanical coupling united simulation technology in the method, advantages of the kinetic simulation software on the simulation aspect of a mechanical system and the hydraulic system simulation software on the simulation aspect of a control system are fully exerted; and by united simulation, accuracy of the simulation result of the axial plunger pump virtual prototype is improved, the experiment cost is reduced, the experiment efficiency is improved, and the design time is shortened.

The invention discloses a fatigue lifetime measuring method for anisotropic material structural parts and belongs to the field of service lifetime analysis and measurement for engine turbine blades. The objective of the invention is to overcome the problem of fatigue life measurement in different crystal orientations for anisotropic materials and structural parts thereof. According to the principles of the fatigue lifetime measuring method, a load condition in a load coordinate system is converted into a load condition in a material coordinate system through coordinate transformation; and based on mechanisms of fracture of the anisotropic materials, a novel form of Hill equivalent strain is provided, and a local strain method in a uniaxial form is expanded to conditions of complex strain. A load at any orientation can be uniformly allowed to be equivalent to a specific crystal orientation to obtain an equivalent load by the fatigue lifetime measuring method. A fatigue lifetime measuring model is built according to material parameters and the equivalent load in the orientation. The fatigue lifetime measuring method is advantageous in that: the fatigue lifetime of the anisotropic materials and the structural parts thereof at any orientation can be accurately measured by only using the material parameters and the equivalent load in the specific crystal orientation, and measurement precision is high.

The invention provides an integrated modeling method for a hypersonic flight vehicle engine body and an internal contraction air inlet channel. The integrated modeling method comprises the following steps: (1) establishing a rectangular coordinate system, and constructing the surface mesh of an original quasi-flight vehicle engine body; (2) carrying out partitioning parameterization expression processing to each component of a flight vehicle to generate the geometric profile of each component; (3) combining the geometric positions of all components, and carrying out fairing processing to each component; (4) according to the installation position of the air inlet channel, cutting the upper surface and the lower surface of a flight vehicle forebody, and constructing the curved surface molded surface of the air inlet channel; (5) reconstructing the air inlet channel enveloping surfaces of the upper surface and the lower surface of the engine body to finish the integrated modeling of the hypersonic flight vehicle engine body and the air inlet channel. According to the method, the influence on the integral engine body configuration of the whole hypersonic flight vehicle by the geometric molded surface of an air inlet channel system is embodied, few control variables are used in a modeling process and can be flexibly regulated according to aerodynamic characteristics, and total expression precision is high.

A soft robotic actuator is disclosed. The actuator includes a first portion with a substantially constant profile and a second portion with a regularly varying profile, and bends in a pressure-dependent fashion as the internal pressure within the actuator is increased or decreased. The present invention addresses the needs described above by providing actuators that are configured to perform new fundamental motions through the inclusion of design elements which can be configured, through the manipulation of a relatively short list of parameters, to undergo specific pressure-actuated changes which can be designed using quantitative modeling techniques.

The invention provides a device and a method for generation and management of an ontology model based on an on-the-fly strategy. The device comprises an ontology editor, a model generator, a model display, an ontology querier and the like. A user uses the ontology editor to edit an ontology file, uses the model generator to generate the ontology model in real time, uses the model display to display element relationships in the ontology model, and uses the ontology querier to query the relationships in the current ontology model. The method includes: dividing main content of the ontology model file into a static part and a dynamic part which is text information of the current ontology file at an editing position via analyzing the ontology model file; using an automat to extract static information of the current ontology file from the static part so as to generate a corresponding model; dynamically extracting and binding modified assignment at a current state position to generate a model progressively. The device and the method for generation and management of the ontology model based on the on-the-fly strategy are capable of rebuilding the model for necessary parts, so that time of model generating is reduced and system resources are saved.

The present invention discloses a modeling method for a magneto-rheological damper inverse model and application thereof. The modeling method is characterized by deriving a mathematical expression of the magneto-rheological damper inverse model on the basis of a transformation model of a Bouc-Wen model, and establishing a correspondence relationship among an excitation current of a magneto-rheological damper, a controllable damping force, a relative offset of the damper and a relative speed of the damper. A control circuit of the magneto-rheological damper inverse model comprises an implementation circuit of the magneto-rheological damper inverse model, a magneto-rheological damper driving circuit and the magneto-rheological damper, which cooperatively constitute a closed-loop control system of the magneto-rheological damper. According to the modeling method for the magneto-rheological damper inverse model and the application thereof, which are disclosed by the present invention, the modeling process of the magneto-rheological damper inverse model can be simplified, and an error of the damping force of the magneto-rheological damper, which is caused by an inherent non-linear hysteresis characteristic, is reduced, so that control precision of the damping force is improved.

In a multi-processor computer system like a NUMA system, memory is distributed at each processor node, and the time delay for a processor to access a non-local node memory is much longer than that for a processor to access a local node memory. When this system undergoes simulation, the simulation of a far-end memory access event plays an important role on the simulation efficiency and precision. The invention provides a far-end memory access method for a host machine to simulate the NUMA system object machine. The method comprises the steps of dividing a plurality of virtual memory space in the host machine; setting the virtual address space of each target application program to a virtual memory space corresponding to the application process; capturing the access of the target application process to the virtual memory space outside of the virtual memory space corresponding to the application process.

The invention discloses a modeling method of a necrosis caput femoris restoring model based on an umbrella-shaped caput femoris supporter. The modeling method comprises the steps that firstly, a three-dimensional model of a to-be-restored caput femoris is obtained, wherein the NURBS curved surface model of the to-be-restored caput femoris is obtained, the to-be-restored caput femoris is a caput femoris which exists in the thigh tissue necrosis area and is pre-restored by the caput femoris supporter, and the caput femoris supporter is composed of an umbrella-shaped supporter body and a supporting sleeve; secondly, the necrosis area needing to be separated is determined according to the shape of the umbrella-shaped supporter body, and a necrosis caput femoris model is established; thirdly, a caput femoris supporter model is established; fourthly, a necrosis caput femoris implantation model is established, wherein the necrosis caput femoris implantation model with an implantation channel and a three-dimensional model of an implanted bone are established; fifthly, the necrosis caput femoris restoring model is established. The modeling method is simple in step, reasonable in design, convenient to achieve and good in using effect, the restoring model of the caput femoris supporter implanted into the necrosis caput femoris can be easily, conveniently and quickly established, and the quality of the established restoring model is high.

The invention discloses a characterization method of material fatigue, creep, and fatigue-creep interaction service life, and belongs to the field of service life prediction of aero-engine critical materials. The characterization method is used for solving service life characterization and prediction problems of materials under low cycle fatigue, creep, and fatigue-creep interaction conditions. According to the principles, a power function form service life prediction method non-linear behavior characterization capacity is established via fatigue-creep interaction, low cycle fatigue, and creeptests of materials at different holding time, and obtaining of effective holding time and normalization dimensionless service life via normalization calculation method. The characterization method iscapable of realizing accurate characterization of service life of materials under low cycle fatigue and fatigue-creep interaction conditions, and especially, consideration and accurate prediction ofcreep service life can be realized. The advantages of the characterization method are that consideration of both physical mechanisms and model implementation convenience is realized, and material lowcycle fatigue, creep, and fatigue-creep interaction service life characterization and prediction problems are solved effectively.

The invention relates to the technical field of power systems and automation thereof, and particularly relates to a virtual power plant double-layer optimization model considering network constraints.The method comprises the specific steps of establishing an upper-layer virtual power plant profit maximization model, establishing a lower-layer market clearing model considering network constraints,converting the double-layer optimization model into a mathematical programming model with balance constraints, and converting the mathematical programming model with the balance constraints into a mixed integer programming model. In order to overcome the defect that line transmission power constraint is not considered in current related research, internal optimization of the virtual power plant and interaction with a market operator and other conventional units are fully considered, a market bidding optimization model in which the virtual power plant participates is established, an optimization bidding strategy is generated under the condition that line power transmission is blocked, the superiority of the bidding strategy is embodied, the profit of the virtual power plant is improved, and the model is close to the practical situation. Scientific theoretical support is provided for the virtual power plant to effectively participate in the power market in future.

The invention relates to a method for building road assembly type bridge disease and reinforcement models by utilizing Dynamo. The method comprises the following steps: dismantling a road assembly type bridge structure according to functions; defining geometrical features of essential features of each type of component as parameters, and building correspoding Revit-family file database, wherein family files are named as structural types and features of the family files; building a bridge structure database; compiling Dynamo program code for building the bridge model; building a bridge diseasefamily library based on Revit; building a bridge disease information database; compiling Dynamo program code for building the disease model; building a bridge reinforcement component family library based on Revit; building a bridge reinforcement information database; compiling the Dynamo program code for building the reinforcement model. According to the method disclosed by the invention, by combining the structure characteristics of the road prefabricated assembly type bridge, a corresponding quick parameterized modeling method is built, the modeling process of the bridge model is simplified,and the modeling efficiency is improved.

The invention provides a modeling method for nonlinear analysis of a high-temperature superconducting magnet. The method comprises the steps of building a PDE model for an electromagnetic thermal coupling analysis according to an actual magnet model; calculating dynamic inductance and resistance equivalent parameters according to a solving result of the PDE model; obtaining key parameters such as a critical current, a maximum temperature rise and the like of the superconducting magnet; and according to a mathematic relationship between the inductance and resistance parameters and a voltage drop at two ends of the magnet, performing equivalent processing on the magnet model by utilizing a controlled current source, wherein at any moment in simulation, the equivalent inductance, the equivalent resistance and the key parameters of the magnet are all related to a current state of the magnet, and a nonlinear E-J characteristic of the superconducting magnet is fully considered. According to the modeling method, mutual influence of a system control module and the superconducting magnet can be reflected, so that the influence of a control algorithm on a response characteristic of the superconducting magnet is analyzed. Compared with a conventional method for making the superconducting magnet equivalent to pure inductance, the modeling method has the characteristic of higher precision; the modeling process is not complex; excessive parameters are not introduced; and a state of the superconducting magnet can be monitored in real time.

The invention discloses a modeling method on the basis of an effective duty cycle for a phase-shifted full-bridge ZVS (zero voltage switching) converter. The modeling method includes steps that an average linear model of a Buck converter is built; the effective duty cycle is introduced, working procedures of the phase-shifted full-bridge ZVS converter are analyzed, and an expression of the effective duty cycle of the phase-shifted full-bridge ZVS converter is derived; a duty cycle represents a time proportion of a conducting state of each power switch in a period, the duty cycle in the Buck converter model is replaced by the effective duty cycle, input voltages of the model are represented by voltages v / n of a secondary side of a transformer of the phase-shifted full-bridge ZVS converter, and the voltages v / n are translated from input voltages v of the phase-shifted full-bridge ZVS converter, so that a phase-shifted full-bridge ZVS converter model can be obtained. The modeling method has the advantages that influence of resonance states of the phase-shifted full-bridge ZVS converter is sufficiently considered in the effective duty cycle, so that the precision of the phase-shifted full-bridge ZVS converter model can be improved, and the modeling method is also applicable to building models of other Buck soft-switching converters.

The invention provides an intelligent fire-fighting system based on a WiFi probe for fire monitoring and rescue escape. The system comprises an environment sensor module, a data control center, a client terminal, a data transmission module, a personnel positioning module, and a WiFi probe. The environment sensor module is used for acquiring an environment data information in real time. The personnel positioning module is used for performing personnel positioning in real time to acquire a personnel distribution information. The data control center is used for receiving and storing the environment data information and the personnel distribution information, and making a corresponding fire-fighting rescue scheme. The data transmission module is in wireless connection with the data control center through the WiFi probe. The client terminal is used for receiving the real-time environment data information, the personnel distribution information, and the fire-fighting rescue scheme sent by the data control center. The invention further provides an intelligent fire-fighting method based on the WiFi probe for fire monitoring and rescue escape. The invention can provide an effective simulated escape rescue scheme, and effectively disperse the crowd when a fire occurs.

The invention relates to a kinematic calibration method for a Stewart parallel robot. According to the kinematic calibration method for the Stewart parallel robot, model simplification is achieved according to a coordinate system establishment rule to obtain a minimum to-be-identified parameter set, and then a nonlinear kinematic model of the parallel robot is obtained; any fixed measurement equipment and any three fixed target point are adopted, and the posture of a robot fixing platform relative to a measurement coordinate system, the positions of the target points relative to a movable robot platform coordinate system, and the like are used as to-be-identified parameters, so that a simple measurement process is achieved, and operation is easy; the nonlinear kinematic model of the parallel robot is combined with a measurement process model to obtain a nonlinear identification model of a whole calibration system; and the resolution of a nonlinear equation system is converted into theresolution of a nonlinear optimization problem. By the adoption of the kinematic calibration method for the Stewart parallel robot, model establishment is achieved through the complete minimum parameter set, model calibration is easier, and true parameters of the robot are directly resolved on the basis of a nonlinear optimization idea; and the kinematic calibration method has the advantages thatoperation is easy, user interfaces are friendly, and the practicability is high.

The invention discloses a stable vehicle driving zone determining method. The stable vehicle driving zone determining method mainly comprises the following steps that step one, a complete vehicle side dynamical model is established; step one, mass center side slip angle speed-mass center side slip angle phase trajectory curve family of a vehicle is drawn; step three, a stable boundary phase trajectory is determined; step four, a stable boundary is fit in the form of a straight line; step five, a three-dimensional map of stable boundary slope and intercept about the vehicle speed and a road adhesion coefficient is made. The stable vehicle driving zone determining method quantitatively represent a stable vehicle driving zone, is simple modeling and has a certain real-timeliness and effectiveness.

The invention discloses a novel robot kinematics modeling method. The method comprises the following steps of: establishing a robot reference coordinate system and an end-of-arm tooling coordinate system only, and representing robot kinematics model parameters through a position vector and a pointing vector; deducing a transformation relation between joints by utilizing an implied joint coordinate system; and solving a pose transformation matrix and a Jacobian matrix of the robot end-of-arm tooling coordinate system relative to the reference coordinate system under the specific joint position through the matrix transformation relationship. By the novel robot kinematics modeling method, the robot kinematics modeling is realized, the modeling process is simple and high-efficiency, only the reference coordinate system and the end-of-arm tooling coordinate system are required to be modeled, and the method has an intuitive expression form and clear physical significance.

The invention relates to the technical field of cement production, and particularly relates to an intelligent optimization method for production full process technical indexes and operation variables of a pre-decomposition kiln of a novel dry-process cement clinker. The optimization method comprises the steps of selecting three modulus values of raw materials, fineness of the raw materials, feeding amount of a raw-material mill system, feeding amount of a pre-decomposition kiln system, f-CaO content of a clinker and three modulus values of the clinker as decision variables for the technical indexes; establishing a power consumption model of the raw-material mill system, a power consumption model of the pre-decomposition kiln system, a coal consumption model of the pre-decomposition kiln system, an KH value model of the clinker, an n value model of the clinker, a p value model of the clinker and a quality model of the clinker; carrying out optimization calculation on the decision variables for the technical indexes; and selecting and calculating the operation variables of the pre-decomposition kiln. According to the optimization method, complex mechanisms of the raw-material mill system and the pre-decomposition kiln system are not needed to analyze, the power consumption models of the raw-material mill system and the pre-decomposition kiln system and the quality model of the clinker can be established only by historical data in the production process. The model establishment process is relatively simple.

The invention discloses a power distribution network economy reconstructing method considering network loss and reliability. The power distribution network economy reconstructing method considering the network loss and reliability includes an economy optimizing model for summing based on power loss cost due to network loss and power loss cost due to deficiency of power supply amount under a power failure state, an object-oriented power distribution network reliability calculating method matched with the model, a power distribution network economy reconstructing model calculation method based on a biogeography algorithm, and power distribution network economy reconstructing steps based on the core content of the three parts, wherein the power distribution network reliability calculating method includes element collection class, block class, block class tree and power supply route determination methods, and the power distribution network economy reconstructing model calculation method includes the construction of residential suitability indexes, habitat characteristic vectors, transport models and the like. The power distribution network economy reconstructing method considering the network loss and reliability combines the yearly demand not supplied due to the network electricity interruption and the yearly power loss due to the network loss to construct the power distribution network economy reconstructing model which simultaneously considers the power distribution network reliability and network loss, and the model has visual economy characteristics and strives to obtain the most economical network structure. The power distribution network economy reconstructing method considering the network loss and reliability is suitable for reconstructing the power distribution network economy.