41results about How to "Accurate performance assessment" patented technology

The invention discloses a turbine pump inducer cavitation flow numerical prediction method based on low-temperature fluid, and belongs to the technical field of impeller machinery. The implementationmethod comprises the following steps: establishing an inducer model and an inlet and outlet runner model according to actual working conditions, and dividing grids; Establishing a computational fluidmechanics model, carrying out rotation correction on the turbulence model, and carrying out thermodynamic correction on the cavitation model; Setting and calculating boundary conditions of the single-phase steady flow to obtain a single-phase result; Calculating two-phase steady flow by taking a single-phase result as an initial value, and then changing inlet pressure and outlet mass flow to obtain calculation results of different working conditions; Calculating unsteady flow of the two phases by taking the two-phase steady result as an initial value to obtain an unsteady calculation result; By analyzing a calculation result, accurate flow field characteristic distribution, inducer performance and radial force dynamic characteristics of the inducer under the action of a flow field are obtained, the inducer is assisted to be designed and optimized, and the experiment cost and time are saved.

The invention discloses a civil airplane APU performance assessment and fault pre-warning method, and relates to the technical field of equipment state monitoring. According to the method, based on QAR data of an airplane, a health state model of an important parameter in an APU is dug out by a machine learning technology; then the predicted value of the health state model is subtracted from the actual measured value of the APU state parameter, and thus the deviation value of the state parameter is acquired; then the deviation values of the several key parameters are fused into a health indexby using a regression model, and the health index is used for representing the degradation degree of APU performance, and fault pre-warning is timely emitted according to a set warning value. The method provided by the invention is applied to the civil airplane APU, particularly the APU that is faulted due to performance degradation, the problem of being lack of airplane APU performance assessmentmeans is solved, the performance state of the APU can be accurately assessed and the APU fault can be found at the early stage and the pre-warning can be timely emitted, and unplanned issuing eventscan be reduced; meanwhile, performance assessment data is from the existing civil airplane QAR data, and the method is relatively strong in practicability and operability.

The invention relates to a deep-towing multi-channel seismic towing cable attitude determination method and a processing terminal. The method comprises the steps of 1, picking up direct wave travel time, sea surface reflected wave travel time and seabed reflected wave travel time of each detector for each shot gather; 2, obtaining the average propagation speed of seismic waves in seawater; 3, calculating the horizontal distance and the height difference of each detector relative to the seismic source; and 4, solving the three-dimensional coordinates of each detector according to the corresponding equation set to obtain the three-dimensional coordinates of each detector, thereby equivalently obtaining the attitude of the towing cable. According to the method, the three-dimensional spatial form of the towing cable can be obtained without two-dimensional hypothesis. Meanwhile, the relative position between the detector and the seismic source is determined by utilizing the travel time of the direct wave, the seabed reflected wave and the sea surface reflected wave, and the accuracy of the relative position is improved.

The invention provides a method and device for verifying network performance statistic data, relates to the field of wireless network quality, and solve the problem that accuracy of data generated randomly by an existing network cannot be found. The method for verifying the network performance statistic data comprises the following steps: obtaining the network performance statistic data in a preset time granularity; obtaining raw performance statistic data of the same-type performance indexes in multiple kinds of pre-stored raw performance statistic data, and mapping the obtained raw network performance statistic data of the same-type performance indexes into corresponding mapping results according to a pre-established mapping relationship between the raw network performance statistic data and a verification algorithm; and verifying whether the obtained network performance statistic data are consistent with the mapping results. So the accuracy of the data is known, and, in this way, accuracy of a performance index can be assessed by utilizing multiple data sources of the same-type performance indexes.

The embodiment of the invention provides a neighbor measurement control method, system and equipment. The neighbor measurement control method comprises the following steps of: judging whether a terminal is at a power-on state and has received an MDT configuration message sent by a base station, and forcing the terminal to always perform neighbor measurement in an MDT measuring process when the terminal is at a power-on state and has received the MDT configuration message sent by the base station. By adopting the technical scheme provided by the embodiment of the invention, complete neighbor measurement information can be acquired, and therefore accurate performance assessment for surrounding cells neighboring the current serving cell according to the complete neighbor measurement information in the follow-up process.

The invention relates to the technical field of mmWave multi-cell interference suppression, and discloses a mmWave multi-cell interference suppression method for minimizing base station transmitting power in combination with user association and beam width selection. The method comprises the following steps: combining a Gaussian antenna model with an mmWave dual-ray channel model as a system model, under the system model, converting the problem of minimizing the base station transmitting power into two methods of user association and optimal beam width selection, firstly, selecting a user withSINR greater than a threshold after pairing of base stations and users under a distributed framework, selecting, by the user, the base station with the smallest transmitting power among the neighboring base stations for association, and then selecting the optimal beam width by using a particle swarm optimization method. The invention designs a user association and beam width selection method, which reduces the computational complexity and reduces the inter-cell interference while ensuring that the base station transmission power is minimized.

The invention discloses an LTE (long term evolution) system performance determining method and an LTE system performance determining system. The LTE system performance determining method includes: determining configuration parameter combination corresponding to current ground feature types according to preset corresponding relation between the ground feature types and the configuration parameter combination, and initializing the determined configuration parameter combination; executing the following operations to each subframe of each radio frame in the LET system: updating positions of all users and corresponding timers in the LTE system according to the initialized configuration parameter combination; executing downlink evaluation procedures when the current subframe is a downlink subframe and a downlink is evaluate currently; and executing uplink evaluation procedures when the current subframe is an uplink subframe and an uplink is evaluated currently.

The embodiment of the invention provides a benchmark test method and device of a supervised learning algorithm in a distributed environment. The method comprises the steps that a first benchmark test result which is determined according to output data in a benchmark test is obtained; a distributed performance index in the benchmark test is obtained, and the distributed performance index is determined as a second benchmark test result; the first benchmark test result and the second benchmark test result are merged to obtain a benchmark test total result. According to a perfect scheme used for solving a benchmark test problem of the supervised learning algorithm in the distributed environment, the benchmark test method and device can assist technical staff to conduct accurate and quick assessment on the performance of the supervised learning algorithm.

The invention provides a reactor three-dimensional power probability distribution monitoring method based on an information fusion theory. The reactor three-dimensional power probability distributionmonitoring method comprises the following steps: evaluating uncertainty of measurement information; determining adopted detector information based on the monitored dynamic or steady-state requirements; estimating a reactor power distribution state based on a Bayesian method; performing probability estimation of reactor core burn-up distribution; updating the probability of reactor core burnup distribution, and estimating the performance of the fuel rod in real time. According to the method, a detection information fusion method with different angles and different precisions is explored, basedon the Bayesian framework, information loss is reduced as much as possible, the matching problem of different angles and different precision measurements is solved, spatial distribution information with higher precision is obtained, probability distribution of power values of any point in a reactor core space is provided, and the probability distribution of the burnup value of any space point in the reactor core is further provided.

The invention relates to an intelligent fire-fighting and spraying water supply system and control method. The system comprises a water tank, a fire monitor and a plurality of water supply subsystems,wherein the water supply subsystems comprise water supply pipelines, first frequency converters and second frequency converters, and the water supply pipelines comprise water inlet pipelines, water outlet pipelines and water return pipelines; and first water pumps and second water pumps are arranged between the water inlet pipelines and the water outlet pipelines, and the first frequency converters and the second frequency converters are in communication connection with the fire monitor. A first pipeline where the first water pumps and the first frequency converters are located and a second pipeline where the second water pumps and the second frequency converters are located are mutually backed up and can work cooperatively, performance evaluation and fire alarm information of a water supply system are reported to an urban fire control center through the internet of things, the system has the functions of daily inspection, performance evaluation, fire alarm and the like in the combatstate, can provide fire-fighting and extinguishing water during combat, and can guarantee safety and reliability of the water supply system during fire extinguishing.

The invention relates to a data processing technology. The invention discloses a vital sign data processing method, system and device and a computer readable medium. The vital sign data processing method comprises the following steps: a, preprocessing vital sign data; b, learning random potential variables in the vital sign data, and constraining the variables as Gaussian distribution; c, learningfeature representation of vital sign data in each subset through two full-connection network layers of a neural network according to a specific task, and performing fusion learning on the learned features of each sub-task and random potential variable features; d, training the model, verifying the model by using the verification set every 30 iterations, and reserving the optimal model; and e, testing the stored optimal model by using the test set, and finally obtaining an evaluation result of each task. According to the method, the vital sign data of a healthy body can be subjected to accurate ability evaluation and risk evaluation, and the evaluation accuracy is greatly improved.

The invention discloses a power supply side power generation performance evaluation method under power regulation and control. The power supply side power generation performance evaluation method comprises the following steps: S1, collecting and processing wind turbine generator field data; s2, selecting a data attribute set with high correlation with the output power of the fan from the historical data of the wind turbine generator so as to represent the power generation state of the fan, carrying out anomaly identification on the data set corresponding to the selected attribute set, and outputting a normal data set and an abnormal data set; s3, establishing a regression function for the output normal data set; s4, calculating the lost generating capacity of the wind turbine generator; and S5, judging the running performance of the fan. According to the method, the historical power generation performance of the wind turbine generator can be accurately analyzed; the power generation performance of the wind turbine generator is comprehensively evaluated, so that power grid dispatchers can accurately control and judge the power generation performance of the wind power plant, the power grid dispatchers can be assisted to optimize the energy structure according to the power generation performance of the power supply side, a reasonable power dispatching plan is made, and the absorption capacity of new energy and clean energy is improved.

The invention discloses a performance evaluation method for a universal processor. The method comprises the following steps: dividing a test program into a plurality of execution stages; a section ofinstruction sequence is selected from each execution stage to serve as a test sample, and calculating the weight; running a test program on a real processor chip platform, and generating a check pointfor each test sample by adopting a check point creation tool; recovering and executing a certain number of instructions on the simulation verification platform by using check points recovered and generated by a check point recovery tool on the test verification platform, and collecting performance data; and calculating the performance data of the whole test program according to the weight of eachtest sample and the performance data of the corresponding check point. The performance can be evaluated quickly and accurately, and various simulation verification platforms and flexible and fine-grained performance evaluation are supported.

The embodiment of the invention provides a performance evaluation method for a multi-stage task system (PMS), which comprises the following steps of: on the basis of deep learning feature representation, fusing polymorphic feature data of the PMS on the basis of Graph feature input of a PMS damage evolution mechanism; according to task stage requirements of the PMS and a causal mechanism of Graph,applying factor graph segmentation to obtain an appropriate distributed evaluation framework; based on attention operator design of state & position contrast coding, acquiring a minimum Graph neighborhood module in distributed evaluation in a self-adaptive mode; and further focusing the target neighborhood, generating a GRU adaptive deep network capable of describing PMS stage correlation, and mining neighborhood information of the minimum evaluation sub-graph. By applying the scheme provided by the embodiment of the invention, the interpretability of the corresponding deep learning module isexpected to be increased, the complexity of the evaluation algorithm is greatly reduced, and the generalization ability of the model is improved, so that the performance of the PMS is accurately evaluated.

The present invention relates to data processing technology. The invention discloses a vital sign data processing method, system, device and computer readable medium. The vital sign data processing method of the present invention comprises the steps of: a, preprocessing the vital sign data; b, learning random latent variables in the vital sign data, and constraining the variable to a Gaussian distribution; c, passing through a neural network according to specific tasks The two fully connected network layers learn the feature representation of the vital sign data in each subset, and fuse the learned features of each subtask with the random latent variable features; d. Train the model and use it every 30 iterations The validation set verifies the model and keeps the best model; e. Use the test set to test the saved best model, and finally get the evaluation results of each task. The invention can accurately evaluate the ability and risk of the vital sign data of the healthy body, and the accuracy of the evaluation is greatly improved.

The invention discloses a method and device for detecting the transverse control function of a vehicle ADAS system and a storage medium, and the method comprises the steps: obtaining the actual diameter of a wheel, and obtaining the transverse operation data of a vehicle in real time; the transverse operation data at least comprise wheel image diameters acquired by an image acquisition device arranged at the side part of the vehicle and image distances between the side part of the vehicle and corresponding lane lines; according to a preset proportion coefficient, the actual wheel diameter, the wheel image diameter and the image distance, the actual distance between the side portion of the vehicle and the corresponding lane line is calculated, and the proportion coefficient reflects the proportion relation between the image distance and the actual distance; and processing the actual distance, and detecting a transverse control function associated with the actual distance according to a processing result. According to the detection method and device for the transverse control function of the vehicle ADAS and the storage medium provided by the embodiment of the invention, the redundancy of data processing is reduced, and the accuracy of performance detection and analysis of the transverse control function of the vehicle is ensured.

The invention discloses a performance adjustment method of an AOI defect detection system, which includes the following steps: S1: making several simulated defect samples with different parameters according to actual defects, and the parameters include any one of size and contrast or two; the defect size or contrast of the simulated defect sample changes in a gradient and must cover the allowed minimum detection specification; S2: collect the image of the simulated defect sample and perform defect detection on it, and perform image processing algorithms during the detection process Adjust the detection limit of the AOI defect detection system to meet the allowable minimum detection specification; the present invention effectively avoids the time-consuming collection of actual defect samples and the difficulty of covering actual defects by making a large number of simulated defect samples, and reduces the time At the same time, it can quickly and accurately perform defect assessment, which improves the efficiency and accuracy of performance adjustment of the AOI defect detection system.

The invention discloses a lightning early warning method based on radar data, and the method comprises the following steps: S1, detecting radar data, classifying the radar data, and removing repeated data; s2, extracting historical thunder and lightning data and thunder and lightning monitoring data of the radar monitoring area; s3, lightning simulation is carried out according to radar monitoring data and historical data; s4, performing grade judgment on the simulated thunder and lightning, and performing early warning in different modes according to different grades; s5, monitoring thunder and lightning occurrence time and thunder and lightning grades after early warning, and recording monitoring data; and S6, comparing the monitored thunder and lightning occurrence time and thunder and lightning level with early warning data, performing difference degree calculation, and evaluating early warning accuracy. Thunder and lightning early warning can be effectively performed, and evaluation of early warning accuracy is facilitated.

The invention discloses a method for a fatigue detection of a blade of a horizontal axis wind turbine. The method comprises the following steps of: processing a result obtained by conventional general single-shaft fatigue detection by adopting the linear damage accumulation theory to obtain fatigue performance of the blade under the interaction of loads in the swinging and shimmying directions; respectively calculating the fatigue lives of two single shafts by adopting a numerical simulation method, and performing damage accumulation on the two calculation results; performing calculation by adopting a numerical method to obtain fatigue performance under the condition that double shafts are simultaneously loaded; and analyzing and comparing fatigue parameters acquired by two fatigue damage calculations during single-shaft loading and double-shaft simultaneous loading, establishing a mathematic relation among single-shaft loading, damage accumulation calculation and double-shaft loading calculation results, introducing the mathematic relation into a single-shaft fatigue test of the blade, and correcting the test result to obtain a double-shaft fatigue performance. The purpose of obtaining more accurate fatigue performance of the blade is fulfilled by adopting low-cost single-shaft fatigue detection means through correction.

The invention discloses a method and system for evaluating the performance of foundation pit pile anchor support with extended service, which determines the rheological characteristics of the soil on the project site and the reinforced concrete strength of the support structure according to the triaxial test of the rock and soil mass and the construction project Reduction and loss of anchor cable prestress; according to the rheological characteristics of the engineering site soil, the strength reduction of reinforced concrete of the support structure and the loss of anchor cable prestress, determine the expression of earth pressure and anchor cable prestress over time Combined with the basic assumptions of the foundation pit pile-anchor support model, the deformation coordination relationship between the pile body and the anchor rod is determined; at the same time, the rheological characteristics of the soil and the prestress loss of the anchor cable are considered, and combined with the basic theory of elastic foundation beams, the deduced Evaluation value of anchor support performance of overdue foundation pit piles considering aging. The invention can comprehensively, objectively and accurately evaluate the performance of the temporary foundation pit support structure, and provide a basis for the safe construction of the temporary foundation pit project.

The invention discloses a performance evaluation method and system for a transmission link of a satellite-ground convergence network and a medium, and the method comprises the steps: comparing the signal to interference plus noise ratio of a direct transmission link in the satellite-ground convergence network with a preset reference value, and determining the direct transmission link or a relay link in the satellite-ground convergence network as the transmission link according to a comparison result. The calculation complexity of system implementation is reduced, and the system performance of the satellite-ground fusion network under multi-relay multi-link transmission and the high-complexity calculation degree of system implementation are balanced; after the transmission link is determined, the outage probability of the transmission link is calculated according to the signal to interference plus noise ratio of the transmission link, the complexity and difficulty of outage probability calculation can be reduced, the system performance of the selected transmission link is quantitatively evaluated based on the outage probability, the calculation difficulty of quantitative evaluation of the system performance is further reduced, and the system performance can be accurately evaluated.

The invention discloses a civil aircraft APU performance evaluation and fault early warning method, and relates to the technical field of equipment state monitoring. On the basis of aircraft QAR data, the present invention uses machine learning technology to dig out the health state model of important parameters in the APU; then subtracts the predicted value of the health state model from the actual measured value of the APU state parameter to obtain the deviation value of the state parameter; then The deviation values ​​of several key parameters are fused into a health index using the regression model to characterize the severity of APU performance degradation, and a fault warning is issued in time according to the set warning value. The present invention is applied to civil aircraft APUs, especially for APUs that fail due to performance degradation. Events are planned to be issued; at the same time, the data for performance evaluation comes from the existing civil aircraft QAR data, which has strong practicability and operability.

The invention discloses an LTE (long term evolution) system performance determining method and an LTE system performance determining system. The LTE system performance determining method includes: determining configuration parameter combination corresponding to current ground feature types according to preset corresponding relation between the ground feature types and the configuration parameter combination, and initializing the determined configuration parameter combination; executing the following operations to each subframe of each radio frame in the LET system: updating positions of all users and corresponding timers in the LTE system according to the initialized configuration parameter combination; executing downlink evaluation procedures when the current subframe is a downlink subframe and a downlink is evaluate currently; and executing uplink evaluation procedures when the current subframe is an uplink subframe and an uplink is evaluated currently.

The embodiment of the invention provides a neighbor measurement control method, system and equipment. The neighbor measurement control method comprises the following steps of: judging whether a terminal is at a power-on state and has received an MDT configuration message sent by a base station, and forcing the terminal to always perform neighbor measurement in an MDT measuring process when the terminal is at a power-on state and has received the MDT configuration message sent by the base station. By adopting the technical scheme provided by the embodiment of the invention, complete neighbor measurement information can be acquired, and therefore accurate performance assessment for surrounding cells neighboring the current serving cell according to the complete neighbor measurement information in the follow-up process.

The invention is suitable for the technical field of equipment evaluation, and provides an efficiency evaluation system for communication navigation equipment. The system comprises a data query module, a data processing module and an efficiency evaluation module; the data query module is used for querying historical communication data of the communication navigation equipment according to the query condition to obtain evaluation data of the communication navigation equipment; the data processing module is used for grouping the evaluation data according to attributes of the evaluation data; and the efficiency evaluation module is used for inputting each group of evaluation data into a preset multi-level efficiency evaluation model for analysis to obtain an efficiency evaluation result of the communication navigation equipment. According to the system, efficiency evaluation can be carried out on the communication navigation equipment of the helicopter more objectively and accurately.

The present invention relates to a method for determining the attitude of a deep towed multi-channel seismic streamer and a processing terminal. The method includes the following steps: Step 1: For each shot set, pick up the direct wave travel time and sea surface on each geophone Reflected wave travel time and submarine reflected wave travel time; Step 2: Obtain the average velocity of seismic wave propagation in seawater; Step 3: Calculate the horizontal distance and height difference of each geophone relative to the source; Step 4: Press the corresponding equation The group solves the three-dimensional coordinates of each geophone to obtain the three-dimensional coordinates of each geophone, which is equivalent to obtaining the attitude of the streamer. The present invention does not require a two-dimensional assumption, and can obtain the three-dimensional space form of the streamer. At the same time, the travel time of the direct wave, sea bottom reflection wave and sea surface reflection wave is used to determine the relative position between the geophone and the seismic source, so as to improve the accuracy of the relative position.

The invention discloses a multi-cycle and multi-constraint fused aviation emergency rescue efficiency evaluation method, which comprises the following steps of: firstly, disassembling an aviation emergency rescue task into a set of a plurality of OREAD cycles to obtain five indexes, then determining weights of the five indexes according to task training requirements, and according to a task completion condition, obtaining a task time consumption coefficient and a task success rate, then determining a circulation probability and a circulation difficulty coefficient according to a circulation occurrence probability and difficulty, finally obtaining evaluation values of five indexes, and calculating and obtaining a single-item efficiency evaluation result and a team comprehensive efficiency evaluation result. The task is disassembled into the set of OREAD cycles, and mapping from a task execution process to an evaluation index is realized; two constraints of a task time consumption coefficient and a task success rate are introduced, and two constraints of a cyclic probability and a cyclic difficulty coefficient are added, so that efficiency evaluation is more accurate; a single index is independent from comprehensive evaluation, two-way evaluation is achieved, and evaluation and training are more targeted.

The invention discloses a method for identifying product degradation parameters, a module and a product performance evaluation method, and a system. The method comprises the following steps: S1, Determining all target performace parameters of possible degradation in the performance parameters of the target object;S2, respectively obtain a plurality of data values of each target performance parameter of that product in a specified time period to form a parameter sequence corresponding to each target performance parameter; S3, judging whether the corresponding target performance parameter is a degradation parameter according to the stationarity of each parameter sequence; the evaluation method evaluates the performance according to the degradation parameters identified by the product. The identification device comprises a parameter determination module, a parameter sequence acquisition module and a degradation parameter determination module. The evaluation system comprises a degradationparameter identification device and a performance evaluation device. The invention has the advantages of simple realization method, quantitative identification of product degradation parameters, highidentification efficiency, high precision and high evaluation precision.

The invention discloses a Big Dipper detector. The Big Dipper detector comprises a host supporting multiple frequency point signals and a handheld dark chamber used for covering an antenna of a user machine to be detected. The host is connected with the handheld dark chamber through a radio frequency cable and a serial port of the user machine to be detected is connected with the host. The host comprises a PC, a radio frequency circuit, an FPGA module, a DDR2 module, a DAC module, an ADC module, a clock distribution module, an interface circuit, a USB module and a power module. The FPGA module is connected with an emission channel through the DAC module and the radio frequency circuit, and a receiving channel of the radio frequency circuit is connected with the FPGA module through the ADC module; the DDR2 module is connected with the FPGA module, the clock distribution module is connected with the FPGA module, the FPGA module is connected with a USB port of the PC through the USB module and the interface circuit, and the FPGA module is connected with the serial port of the PC through the interface circuit. The power module provides a power source. The Big Dipper detector is integrally designed and is convenient to use.

The invention discloses a Bayes method-based Internet application service monitoring system and method. The Bayes method-based Internet application service monitoring system comprises a detection device and an analysis device. The Bayes method-based Internet application service monitoring method comprises the following steps that: detection devices circularly visit a target server; whether visiting return results are correct is judged, if the visiting return results are correct, the target server is normal, if the visiting return results are wrong, the detection devices calculate a failure probability by adopting a Bayes method, and report the failure probability to the analysis device; the analysis device generates a failure analysis result, if all detection devices fail, the target server fails; if all detection devices in the same heterogeneous network, the heterogeneous network fails; and if partial detection devices fails, a communication links fails. According to the invention, by fully considering the instability and the unreliability of the internet, the probability of causing failures when visiting fails is predicted by using the Bayes method, the false alarm rate of the failures is effectively lowered, and the interference of random factors to failure judgment is eliminated.