147results about How to "Reasonable calculation" patented technology

The invention provides a portable ship water gauge automatic detection and identification method based on machine vision. Video data of a ship water gauge in the overwater environment are used as a main research object, the machine vision and the image processing theory are used as main means, so as to detect and identify the scale of the ship water gauge and perform statistical analysis on detection results of continuous video frames, and finally, a ship draft value is obtained. According to the system, the relatively objective ship draft value can be obtained in accordance with image data, the detection results are visually displayed, the workload of ship draft detection personnel can be reduced, the measurement stability and accuracy of the ship water gauge are increased, and an objective measuring means and reference data are provided for determining ship draft.

An application technology field relates to the navigation, especially the analysis and picking method of the road topological data used in the navigation and setting the data model, which is a road topological data model and computing method used in navigation to treat the road with big area and long distance in navigation map data. The method includes the stratified extracting arithmetic, the road connection calculation function, the hierarchical adjacent node transition table, the road web canton extracting arithmetic and the least cost arithmetic of road net in-out; it mainly solves the technology problem of route calculation of long distance and big area. The invention can insure the connection of whole road web; it can store the starting data of route calculation and improves the route calculation efficient; so it can get the logical analysis result in the logical time and cost range.

The invention discloses a central air-conditioning intelligent group control system, comprising a host, a cooling tower, a cooling pump, a central processor, and a data collector, a cooling reflux output temperature sensor, a freezing reflux output temperature sensor, a freezing reflux output pressure sensor, a controller connected with the central processor for reading the parameters of a frequency changer via on-site bus, and a network gate between the host and the controller. The sensor is connected with the data collector which can transmit the signal of sensor to the central processor. The invention uses several parameters to group control to fully utilize frequency change technique to reduce the abundant refrigeration most. And the invention uses the controller to on-time memory the data of air conditioner, to show variable power curvatures, watched and modified by user.

The invention provides a battery pack simulator, which comprises a communication module, a control module and an output conversion module. The communication module receives the setting data of the battery pack and transfer the data to the control module; the control module is used for obtaining dynamic characteristics data of the battery pack according to the setting data of the battery pack, and transferring the dynamic characteristics data of the battery pack to the output conversion module; and the output conversion module is used for converting the received dynamic characteristics data of the battery pack to analog signals which represent the dynamic characteristics of the battery pack and outputting the signals. The battery pack simulator provided by the invention can stimulate all characteristic signals of the battery and the relations thereof, and can dynamically simulate a set of real batteries. When the battery pack simulator provided by the invention is used, either all the batteries in a dynamic battery pack or part of the batteries in a dynamic battery pack can be replaced, so as to check whether the calculation and control on a battery management model under different conditions is reasonable.

The invention discloses an outfield precision testing method for a high-precision star sensor. Accuracy in calculation of a star pattern posture of the star sensor and frequency domain stripping of short-period error terms of the posture are realized by utilizing a procession correction formula, an earth rotation model, an atmosphere correction model and a power spectral density formula, and the posture measuring error of the star sensor can be rapidly and effectively analyzed and evaluated. According to the method, the hardware resource is not occupied, the method is realized by utilizing software and does not need the ground intervention. According to the method, by combining the posture identification principle of the star sensor and adopting a data smoothing method, the posture truth value of each frame star pattern moment is calculated, so that a foundation is established for the subsequent analysis on the posture measuring error; by adopting the method for combining the time domain and the frequency domain, the short-period error term is decomposed into an airspace low-frequency error, a high-frequency error and a time-domain error by virtue of the power spectral density analysis, so that reasonable data support is provided for further evaluation of the precision indexes of the star sensor, and the index performance of the star sensor can be improved.

The invention relates to a wind turbine operating state fuzzy synthetic evaluation method based on the Markov chain. Aiming at defects in deterioration degree calculation of a traditional fuzzy synthetic evaluation model, a Markov chain model is built, the variation trend of evaluation index parameters is introduced into the deterioration degree calculation, so that the deterioration degree calculation is more reasonable, and an evaluation result of the overall operating states of wind turbines is more objective and more accurate than a result obtained with a traditional method.

The invention discloses an atmospheric correction method for multispectral data of a remote sensing satellite. The method comprises the following steps of: (1) reading data, and converting the data into apparent radiance data and apparent reflectivity data; (2) calculating decision factors, i.e. a ratio vegetation index, a soil adjustable vegetation index and a normalization water body index in adecision tree method according to the apparent reflectivity data; (3) acquiring apparent reflectivity data in a dark target area according to the apparent reflectivity data, and calculating air path reflectivity; (4) determining the aerosol optical depth of each multispectral waveband according to the relation among the air path reflectivity, a Rayleigh reflectivity ratio and the aerosol optical depth, and determining the total optical depth of a position of 550 nanometers according to the aerosol optical depth and the Rayleigh scatting optical depth of each multispectral waveband; and (5) acquiring an inversion parameter from a lookup table according to the total optical depth of the position of 550 nanometers, and solving land surface reflectivity through a radiative transfer equation to finish atmospheric correction.

The invention provides a method for calculating the output loss of a wind power field and a unit and a device thereof, relating to the technical field of wind power generation. The lost generated energy of a failed wind turbine unit within the fault time segment is obtained through referring the generated energy of a plurality of wind turbine units which work normally around the failed wind turbine unit within the fault time segment or utilizing an expert system. The invention has the advantages of calculating accurately the output loss caused by the abnormal work of the wind power field and the wind turbine units due to various causes so as to be beneficial to improving the running management level of the wind power field, providing accurate calculation basis for all application requiringoutput power loss data of wind power plants and providing accurate basis for performance evaluation of employees of the wind power plants, calculation of carbon emission reduction, economic benefit analysis of the wind power plants as well as solution of economic disputes caused by the abnormal working of the wind power plants and the wind turbine units due to various causes.

The invention relates to the technical field of high-pier large-span concrete bridges, in particular to a method for longitudinal stiffness control over a high-pier large-span concrete continuous girder bridge and a bridge. The method for longitudinal stiffness control comprises a step a) of establishing a linear bridge pier integrated calculation model; a step b) of applying an analog load; a step c) of analyzing beam track acting force and jointless track stress deformation laws; and a step d) of determining longitudinal rigidity limits of a fixed bridge pier and track treatment measures. Therefore, beam shape arrangement and fixed pier rigidity are determined, a problem that in the prior art, it is difficult to control longitudinal stiffness of the high-pier large-span continuous girder bridge is solved, and the blank of the high-pier large-span girder bridge in the field of longitudinal stiffness control is filled. Meanwhile, normative standards of longitudinal linear stiffness limits of the high-pier large-span concrete continuous girder bridge are established, a reference and a basis are provided for bridge design and construction, so the design cost is reduced, and the actually built bridge meets specific usage environments.

The invention provides an overlapping community discovery method based on node influence. On the basis of a k-shell decomposition algorithm, three classes of factors, including the global influence and the partial influence of a node and the contribution degree of a neighbour node are comprehensively considered on a full scale. On the basis of the influence, nodes are updated in a descending order, the propagation characteristics of social network information are conformed, and algorithm randomness is lowered. When an affiliation coefficient is calculated, the impact of the influence of the neighbour node is considered, and the own affiliation tendency of the node and the own influence of the node are considered. On an aspect of setting an overlapping threshold value and the like, the node influence is fused, a reasonable threshold value is set for each node. The randomness of an original algorithm can be lowered, and a high-quality community structure is mined.

The invention discloses a multi-dimensional constraint wind power plant current collection line automatic planning method. The method comprises the steps: 1) intelligent partitioning; 2) optimal planning of cost in the area; 3) the global cost of cross-regional planning of the line being optimal; 4) T-connection path optimization. According to the invention, the problems of large calculation amount and long time of the traditional NP algorithm such as dimensionality disaster, genetic algorithm, RRT fast search algorithm, ant colony algorithm and the like are solved. Large-scale and large-quantity wind power plant current collection line planning problems are broken in a regional and hierarchical manner, so that the problems of high strength, nonlinearity and high time complexity of currentcollection line planning are solved. The planning of the wind power plant can be carried out considerably and gradually, self-optimization is carried out under multi-dimensional constraints, and theinfluence of human factors on a planning result is reduced.

The invention discloses a fuzzy prediction method of corrosion rate of a transformer substation grounding grid. The fuzzy prediction method comprises the steps of determining the degree of membership according to the correlativity of soil physicochemical indexes and corrosion of the transformer substation grounding grid; determining the corrosion contribution degree of different soil physicochemical indexes on the grounding grid, and calculating the close degree between different areas of transformer substation grounding grids. The problems of a plurality of involved factors, intricate relation, and uncertainty and fuzziness in related factors in prediction of the corrosion rate of the grounding grid are solved by the fuzzy prediction model; poor model prediction accuracy caused by a small sample is avoided at the same time; and the corrosion rate of the transformer substation grounding grid can be rapidly and effectively predicted on engineering as to grounding grid sites which are adjacent in region or in soil physicochemical indexes.

The invention relates to a joint decision-making method and system for security situation assessment and defense strategy. The method comprises the following steps: grading power grid assets, threatsand vulnerabilities according to grading criteria; substituting grading of the power grid assets, threats and vulnerabilities into workflow, and modeling power grid attack-defense game state assessment workflow to form an attack-defense game diagram; and selecting key nodes of a current system from two aspects of vulnerability utilization and asset security situation assessment value based on theconstructed attack-defense game diagram to select a security defense strategy. The technical scheme provided by the invention has a good prediction effect for fluctuation state and controllable modeling complexity.

The invention relates to a water conservancy and hydropower engineering construction diversion risk analysis technology, aims at defects of detection of an instability risk ratio of a slope of a high no-overtopped rockfill cofferdam in the conventional technology, and provides a method for detecting the instability risk ratio of the slope of the high no-overtopped rockfill cofferdam. The method comprises the following steps of (1) comprehensively considering randomness of hydrological, hydraulic and filled earth-rock mechanical parameters and constructing a mathematic module for the instability risk ratio of the slope of the high no-overtopped rockfill cofferdam based on a safety factor; (2) adopting an Monte-Carlo method to couple each randomness factor to ascertain probability distribution of a maximum water level in front of the cofferdam; (3) adopting a layered-LHS sampling method to obtain a filled earth-rock random parameter sample to improve sampling efficiency; (4) utilizing a K-S inspection principle to judge an acceptable distribution type of the safety factor of the slope; and (5) adopting a goodness-of-fit index to determine the optimum probability distribution and computing the risk ratio. The method is suitable for a water conservancy and hydropower engineering construction diversion risk decision.

The invention discloses a non-local means filtering method for a speckle noise pollution image. The method comprises that iterative computation of a neurons firing state image series of the speckle noise pollution image is conducted through a pulse transmission cortex model, a Renyi entropy vector is extracted by the neurons firing state image series, and non-local means filtering is conducted on the speckle noise pollution image based on the Renyi entropy vector, so that a denoised gray value is obtained. By the aid of the method, rotation invariance, translation invariance and scaling invariance can be extracted from the image containing speckle noise, the method can use more image information for denoising than traditional methods, besides, the similarity between two image pixel blocks can be calculated reasonably, image noise can be suppressed significantly, and the peak signal-to-noise ratio of the image can be improved, so that detailed information of the image can be effectively protected.

The invention relates to an evaluation method of an urban conventional bus network, belongs to the field of public transport network evaluation; the method includes establishing an index system of urban conventional public transport network evaluation according to the principles of comprehensiveness, scientificity and feasibility from the three aspects of the road network, passenger transport level and service level of urban public transport; then constructing an urban conventional public bus network evaluation model; analyzing and processing data obtained through vehicle following investigation, traffic investigation, data collection and the like to obtain actual index values; carrying out dimensionless processing on each index value, and determining a membership table of indexes according to dimensionless data of each index and a membership function to obtain an evaluation matrix; and then, calibrating the weights of the indexes influencing the network evaluation in the model by using an analytic hierarchy process and yaahp software; and finally, performing two-stage fuzzy comprehensive evaluation and evaluation result analysis and verification, determining the level of the urbanconventional bus network finally, and providing a basis for evaluation of the urban conventional bus network.

The invention discloses an electromechanical system multilayer reliability prediction method based on fuzzy evaluation, wherein the electromechanical system multilayer reliability prediction method belongs to the field of electromechanical system reliability engineering technology. The method comprises the steps of performing layered structural processing on the electromechanical system by means of an analytic hierarchy process, layering the electromechanical system from top to bottom, wherein the electromechanical system comprises a system layer, a sub-system layer, a functional module layer and a basic functional layer; then, determining the weight coefficient of a sub unit relative to a father unit according to a risk priority number method and a fuzzy judgment matrix; and finally, establishing a multilayer reliability model which comprises a weighting coefficient, and successively performing reliability prediction on the electromechanical system. The electromechanical system multilayer reliability prediction method can be widely used in the field of electromechanical equipment reliability engineering and is particularly suitable for complicated system reliability optimization and fine design analysis.

The invention relates to a modular electric-control diesel engine oil quantity calculation and control system and method. The modular electric-control diesel engine oil quantity calculation and control system comprises an initial external characteristic oil quantity module. The initial external characteristic oil quantity module is connected with an external characteristic oil quantity environment correction module. The output end of the external characteristic oil quantity environment correction module is connected with an oil quantity calculation module. The output end of the oil quantity calculation module is connected with a theoretical oil quantity calculation module. The theoretical oil quantity calculation module is further connected with a system oil quantity limiting module. The output end of the theoretical oil quantity calculation module is connected with a target oil quantity calculation module. The output end of the target oil quantity calculation module is connected with an actual oil spraying quantity calculation module. According to the modular electric-control diesel engine oil quantity calculation and control system and method, accurate control over the oil quantity is achieved, and software resources are effectively saved; and the change of an accelerator pedal is judged, and relevant oil quantity limitation is executed, so that the problems that the actual oil spraying quantity is decreased while the required opening degree of the accelerator pedal is increased, and the actual oil spraying quantity is increased while the required opening degree of the accelerator pedal is decreased are solved, and accordingly the oil quantity calculation and control logic are made more reasonable.

The invention discloses a multi-level electromechanical system reliability prediction method based on fuzzy judgment. The method is used for performing layered structured processing on an electromechanical system, establishing a multi-level reliability model containing weighting coefficients and performing multilevel unit weighting coefficient calculation and reliability prediction on the electromechanical system sequentially. The multi-level electromechanical system reliability prediction method comprises steps as follows: layered structured processing on the electromechanical system; calculation of a risk priority number of a bottom unit and establishment of a binary comparison matrix; establishment of a fuzzy judgment matrix of the bottom unit and calculation of unit weighting coefficients; establishment of a father unit reliability model; reliability prediction of a function module; reliability prediction of a subsystem; reliability prediction of a system. By means of the method, the defect that the importance of each system unit cannot be treated differently with an existing electromechanical system reliability prediction method can be overcome. The electromechanical system reliability prediction method can be widely used for the field of reliability engineering of mechanical and electrical equipment and is particularly suitable for reliability optimization and refined design and analysis occasions of a complicated system.

The invention relates to a cold and heat metering isenthalpic difference calibration weighting method for a central air-conditioning fan coil, comprising the following steps of: calibrating the weighted values of the fan coil at various air speeds on site; determining the thermal equivalents of the fan coil at various air speeds according to the weighted values; determining the heating cost of the fan coil according to the thermal equivalents at various air speeds, wherein the calibration of the weighted values comprises the following steps of: inputting the total heat corresponding to the high air speed, the medium air speed and the low air speed through looking up a product specification of the fan coil into a metering temperature controller; imbedding the weighted value of the fan coil under the fan stop status into the metering temperature controller; embedding the time of starting the calibration and the time of stopping the calibration into the metering temperature controller; controlling temperature by the metering temperature controller through automatically regulating the air speed of the coil fan; and after the calibration is ended, automatically generating the weighted values of the fan coil corresponding to the high air speed, the medium air speed and the high air speed through the metering temperature controller. The invention makes the fan coil metering simple and easy to implement, can realize the same comfort level and the same cost and can restrain the waste phenomenon of windowing and the like.

The embodiment of the invention discloses a knowledge base alignment method and device, computer equipment and a storage medium, and the method comprises the following steps: obtaining a knowledge entity vector set which is a vectorized representation of knowledge entities in a to-be-aligned knowledge base; Inputting the knowledge entity vector set into a preset knowledge entity clustering model to obtain a clustering result of knowledge entities in the to-be-aligned knowledge base; Selecting any two knowledge entities belonging to the same class according to the clustering result, and calculating the similarity between the two knowledge entities; And when the similarity is greater than a set first threshold, combining the two knowledge entities. comparison of the similarity of the two knowledge entities is limited to the same kind of entities, the calculated amount is greatly reduced, clustering is achieved through the artificial intelligence technology, the clustering result betterconforms to the expectation, the similarity calculation integrates the attribute similarity and the vector similarity of the entities, the similarity calculation is more reasonable, and redundant information can be more effectively found and removed.

The invention discloses a time series data similarity measurement method and measurement system, and the method comprises the following steps: firstly, learning the vector representation of each eventfor events in all time series data; Secondly, mapping the occurrence time of each event into a vector with the same dimension as the event vector, and embedding the vector into the event vector through vector addition; And finally, sending the final event sequence representation into a convolutional neural network for supervised learning, and finally learning a robust time sequence data similarity measurement model; carrying out similarity measurement through the obtained similarity measurement model. According to the method, the expression of the time sequence data is more reasonable and effective, so that the accuracy of time sequence data similarity measurement can be improved.

The invention discloses a method of evaluating uncertainty of test results of drug components by a working curve method. The method comprises following steps: establishment of measurement result calculating formulas and mathematics models, analysis of uncertainty source, quantification of uncertainty components, calculation of synthesis standard uncertainty, calculation of expanded uncertainty and expression of measurement results. By means of the method in the invention, the main source affecting uncertainty can be accurately reflected so as to provide more reliable examination determination results.