Identification method of shoulder torque of screw-on curve of premium threaded connections for OCTG

The meaning of each part of the screw-on curve,the definition of shoulder torque,and the common characteristics of the screw-on curve are introduced.Moreover,the principle and shortcomings of the commonly used method of curve curvature radius are discussed.A new method of sealing surface deformation is proposed based on the requirements of shoulder torque recognition.The calculation method and principle of PW value are elucidated and the advantages of this method are summarized.The proposed method considers the difference value of tightening torque and calculates the elastic deformation of the sealing surface,accurately reflecting the state of the thread compound and the correlation between torque change and elastic deformation of the sealing surface after compression.

Analysis of identification methods of key nodes in transportation network

The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be different.It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks.Based on the knowledge of complex networks,the metro networks and the bus networks are selected as the objects,and the key nodes are identified by the node degree identification method,the neighbor node degree identification method,the weighted k-shell degree neighborhood identification method(KSD),the degree k-shell identification method(DKS),and the degree k-shell neighborhood identification method(DKSN).Take the network efficiency and the largest connected subgraph as the effective indicators.The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

Identification method of crowded passenger flow based on automatic fare collection data of Nanjing Metro

To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyzed by observing the temporal distribution of inflow passengers each hour and the spatial distribution concerning cross-section passenger flow.Secondly,the identification method of crowded passenger flow is proposed to calculate the threshold via the probability density function fitted by Matlab and classify the early-warning situation based on the threshold obtained.Finally,a case study of Xinjiekou station is conducted to prove the validity and practicability of the proposed method.Compared to the traditional methods,the proposed comprehensive method can remove defects such as efficiency and delay.Furthermore,the proposed method is suitable for other rail transit companies equipped with automatic fare collection systems.

IMPROVED COVARIANCE DRIVEN BLIND SUBSPACE IDENTIFICATION METHOD

An improved covariance driven subspace identification method is presented to identify the weakly excited modes. In this method, the traditional Hankel matrix is replaced by a reformed one to enhance the identifiability of weak characteristics. The robustness of eigenparameter estimation to noise contamination is reinforced by the improved Hankel matrix, in combination with component energy index （CEI） which indicates the vibration intensity of signal components, an alternative stabilization diagram is adopted to effectively separate spurious and physical modes. Simulation of a vibration system of multiple-degree-of-freedom and experiment of a frame structure subject to wind excitation are presented to demonstrate the improvement of the proposed blind method. The performance of this blind method is assessed in terms of its capability in extracting the weak modes as well as the accuracy of estimated parameters. The results have shown that the proposed blind method gives a better estimation of the weak modes from response signals of small signal to noise ratio （SNR）and gives a reliable separation of spurious and physical estimates.

General Situation of Traditional Chinese Medicine Identification Methods

Traditional Chinese medicines are the material basis for the treatment of diseases under theoretical direction, as well as the raw materials of traditional Chinese medicine decoction pieces and Chinese patent medicines. The quality of traditional Chinese medicine directly influences clinical efficacy. Therefore, the identification of traditional Chinese medicine is the responsibility of medicinal workers. The identification method develops from observation, tasting, smelling and listening to firing method and testing with water, and the construction of fingerprints of traditional Chinese medicines and molecular biological techniques. The development and evolution of traditional Chinese medicine identification methods was reviewed in this paper.

Physical Parameter Identification Method Based on Modal Analysis for Two-axis On-road Vehicles:Theory and Simulation

Physical parameters are very important for vehicle dynamic modeling and analysis.However,most of physical parameter identification methods are assuming some physical parameters of vehicle are known,and the other unknown parameters can be identified.In order to identify physical parameters of vehicle in the case that all physical parameters are unknown,a methodology based on the State Variable Method（SVM） for physical parameter identification of two-axis on-road vehicle is presented.The modal parameters of the vehicle are identified by the SVM,furthermore,the physical parameters of the vehicle are estimated by least squares method.In numerical simulations,physical parameters of Ford Granada are chosen as parameters of vehicle model,and half-sine bump function is chosen to simulate tire stimulated by impulse excitation.The first numerical simulation shows that the present method can identify all of the physical parameters and the largest absolute value of percentage error of the identified physical parameter is 0.205%;and the effect of the errors of additional mass,structural parameter and measurement noise are discussed in the following simulations,the results shows that when signal contains 30 d B noise,the largest absolute value of percentage error of the identification is 3.78%.These simulations verify that the presented method is effective and accurate for physical parameter identification of two-axis on-road vehicles.The proposed methodology can identify all physical parameters of 7-DOF vehicle model by using free-decay responses of vehicle without need to assume some physical parameters are known.

Vortex analysis of water flow through gates by different vortex identification methods

The pre-gate suction vortex,gate-bottom-edge transverse vortex,gate-slot vertical vortex,and downstream-of-gate return vortex are important factors affecting the flow instability of flat gates,which may lead to fatigue failure in severe cases.This study used the volume of fluid(VOF)model and large eddy simulation(LES)method to accurately capture the transient turbulence characteristics of flow under different water flow conditions and reveal the flow field and vortex structure.The Q—criterion,Omega(Ω)method,and latest third-generation Liutex vortex identification method were used to analyze and compare the pre-gate suction vortex,gate-slot vertical vortex,and downstream-of-gate return vortex,focusing on the ability of each vortex identification method to capture the flow field information and vortex characteristics.The results reveal that theΩmethod and Liutex method are less dependent on the threshold value,and the Liutex method captures a wide range of pre-gate vortices.Different flow conditions cause changes in the vortex structure of over-gate flow.When the relative opening of the gate is smaller,the intensity of the vortices in the flow field around the gate is greater,the return vortices downstream of the gate are more disordered,and the vortex changes are more violent,which in turn affects the efficient and stable operation of the gate.

Identification Method for Single-line-to-ground Faults with Line Break Based on Phasor Measurement in Distribution Networks

The single-line-to-ground faults with line breaks(SLGFs-LBs)occur more and more frequently in distribution networks and can cause major safety accidents.It is difficult to distinguish the single-line-to-ground faults(SLGFs)in resonant grounding systems and ungrounding systems due to the same electrical characteristics on the source side and uncertain operation conditions of distribution networks.This paper proposes a method for distinguishing SLGFs-LBs and SLGFs.First,the source-side and load-side voltage characteristics of SLGFs and SLGFs-LBs are analyzed,and the phase difference between the voltages of the fault phase and non-fault phase on the load side is selected as the identification criterion.Phasor measurement units(PMUs)are selected as measuring devices.Then,the effects of operation conditions and external devices in distribution networks on the proposed method are discussed,and the phase errors caused by them are calculated to correct the identification method.Finally,the field testing and simulation experiments are conducted to verify the effectiveness and robustness of the proposed method.

Film identification method based on improved deeplabv3+ for full-film double-ditch corn seedbed

This study aimed to investigate the task demand of intelligent unmanned fertilizer application in seedling stage of corn planted in full-film double-ditch seedbed,a film identification method based on improved DeepLabv3+ identification method for full-film double-ditch corn seedbed was proposed.The differences in performance indicators of the original Deeplabv3+ network taking Xception as the backbone network and the network model that replaced three lightweight backbone networks,MobileNetV2,MobileNetV3 and GhostNet were tested.At the same time,the network models,classical semantic segmentation was introduced to PSPNet and UNet for comparative test.The MIoU of DeepLabv3+ network model that replaced its backbone network increased by 5.01%,and FPS improved by 206%compared with original network,and the model size reduced by 90.3%.The three DeepLabv3+ models after replacing the backbone network were further compressed,and the two-layer expansion convolution with low expansion rate in ASPP was deleted,and the common convolution after feature fusion was replaced by the depthwise separable convolution to obtain a lightweight network model.After testing the improved network model,it was found that the average decline of precision indicators was only 0.17%,FPS raised to 66.5,with an average increase of 25.5%,and the size of the model was compressed to 10.53 MB.Test results showed that,the improved model showed excellent performance,and could provide important technology and method support for the research and development of intelligent topdressing and field management on full-film double-ditch corn seedbed during seedling stage.

The regional types of China＇s floating population： Identification methods and spatial patterns

With the rapid increase of the number and influence of floating population in China,it is urgently needed to understand the regional types of China＇s floating population and their spatial characteristics. After reviewing the current methods for identifying regional types of floating population,this paper puts forward a new composite-index identification method and its modification version which is consisted of two indexes of the net migration rate and gross migration rate. Then,the traditional single-index and the new composite-index identification methods are empirically tested to explore their spatial patterns and characteristics by using China＇s 2000 census data at county level. The results show：（1） The composite-index identification method is much better than traditional single-index method because it can measure the migration direction and scale of floating simultaneously,and in particular it can identify the unique regional types of floating population with large scale of immigration and emigration. （2） The modified composite-index identification method,by using the share of a region＇s certain type of floating population to the total in China as weights,can effectively correct the over-or under-estimated errors due to the rather large or small total population of a region. （3） The spatial patterns of different regional types of China＇s floating population are closely related to the regional differentiation of their natural environment,population density and socio-economic development level. The three active regional types of floating population are mainly located in the eastern part of China with lower elevation,more than 800 mm precipitation,rather higher population densities and economic development levels.

A comparative study of different online model parameters identification methods for lithium-ion battery

Precise states estimation for the lithium-ion battery is one of the fundamental tasks in the battery management system(BMS),where building an accurate battery model is the first step in model-based estimation algorithms.To date,although the comparative studies on different battery models have been performed intensively,little attention is paid to the comparison among different online parameters identification methods regarding model accuracy,robustness ability,adaptability to the different battery operating conditions and computation cost.In this paper,based on the Thevenin model,the three most widely used online parameters identification methods,including extended Kalman filter(EKF),particle swarm optimization(PSO),and recursive least square(RLS),are evaluated comprehensively under static and dynamic tests.It is worth noting that,although the built model’s terminal voltage may well follow a measured curve,these identified model parameters may significantly out of reasonable range,which means that the error between measured and predicted terminal voltage cannot be seen as a gist to determine which model is the most accurate.To evaluate model accuracy more rigorously,battery state-of-charge(SOC)is further estimated based on identified model parameters under static and dynamic tests.The SOC prediction results show that EKF and RLS algorithms are more suitable to be used for online model parameters identification under static and dynamic tests,respectively.Moreover,the random offset is added into originally measured data to verify the robustness ability of different methods,whose results indicate EKF and RLS have more satisfactory ability against imprecisely sampled data under static and dynamic tests,respectively.Considering model accuracy,robustness ability,adaptability to the different battery operating conditions and computation cost simultaneously,EKF is recommended to be adopted to establish battery model in real application among these three most widely used methods.

Observed displacement data-based identification method of deformation time-varying effect of high concrete dams

The long-term safety of high concrete dams has become the focus and central issues of public attention. Deformation is an actual comprehensive reflection of concrete dams. Especially the deformation time-varying effect, is a key index for evaluating the structural behavior, health status, and their evolution of a concrete dam in long-term service. In this paper, causing factors of the deformation time-varying effect of concrete dams were analyzed, and the time-varying effect was divided into two parts, which are the inherent time-varying effect and the time-varying effect caused by the change of dam structural performance. Then, based on the observed dam displacement and the wavelet multi-resolution analysis, causal models for identifying the later deformation time-varying effect and the identification process were proposed. Finally, the efficiency and rationality of the proposed method were verified by two actual concrete dams with runoff reservoir and regulatory reservoir.

Numerical and experimental evaluation on methods for parameter identification of thermal response tests

Several parameter identification methods of thermal response test were evaluated through numerical and experimental study.A three-dimensional finite-volume numerical model was established under the assumption that the soil thermal conductivity had been known in the simulation of thermal response test.The thermal response curve was firstly obtained through numerical calculation.Then,the accuracy of the numerical model was verified with measured data obtained through a thermal response test.Based on the numerical and experimental thermal response curves,the thermal conductivity of the soil was calculated by different parameter identification methods.The calculated results were compared with the assumed value and then the accuracy of these methods was evaluated.Furthermore,the effects of test time,variable data quality,borehole radius,initial ground temperature,and heat injection rate were analyzed.The results show that the method based on cylinder-source model has a low precision and the identified thermal conductivity decreases with an increase in borehole radius.For parameter estimation,the measuring accuracy of the initial temperature of the deep ground soil has greater effect on identified thermal conductivity.

Vortex structures of dynamic pure yaw test using DDES approach and vortex identification method

Considered as the building blocks,vortex structures with variety of sizes and intensity are widely recognized in the viscous flow field around ship.In this paper,the computational fluid dynamics(CFD)solver,naoe-FOAM-SJTU,coupled with delayed detached-eddy simulation(DDES)is adopted to analyze the vortex structures around the benchmark model Yupeng Ship in dynamic pure yaw tests,which are captured by third generation of vortex identification method.The good agreement of the predicted force/moment by DDES method with the experimental data indicates that the present numerical schemes are reliable and robust.Three vortex identification methods,Q-criteria,Ω_(R) and Liutex,are used to capture the vortex structures around the hull.The large separated flow is able to be investigated by these three methods,in which more vortex structures are captured byΩ_(R) approach and Liutex method with scalar,vector and tensor form seems to be more suitable for analyzing the flow mechanism around the hull in dynamic pure yaw test.In general,each vortex structure corresponds to a dominant positive/negative axial Liutex and a bound vortex pair.The streamlines are spiral in the large separated flow,indicating that the flow in corresponding region is rotational.But the rotation of the flow is not directly related to the intensity of Liutex.

Multi-source Data-driven Identification of Urban Functional Areas:A Case of Shenyang,China

Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of human-land interaction.In this paper,based on multi-source big data include 250 m×250 m resolution cell phone data,1.81×105 Points of Interest(POI)data and administrative boundary data,we built a UFA identification method and demonstrated empirically in Shenyang City,China.We argue that the method we built can effectively identify multi-scale multi-type UFAs based on human activity and further reveal the spatial correlation between urban facilities and human activity.The empirical study suggests that the employment functional zones in Shenyang City are more concentrated in central cities than other single functional zones.There are more mix functional areas in the central city areas,while the planned industrial new cities need to develop comprehensive functions in Shenyang.UFAs have scale effects and human-land interaction patterns.We suggest that city decision makers should apply multi-sources big data to measure urban functional service in a more refined manner from a supply-demand perspective.

Physical properties of vortex and applicability of different vortex identification methods

For correct identification of vortices,this paper first analyzes the properties of the rigid vortex core and its induced flow field given by the Rankine vortex model,and it is concluded that the concentrated vortex structure should consist of the vortex core and the induced flow field(the potential flow region with a weak shear layer).Then the vortex structure is analyzed by using the Oseen vortex model.Compared with the Rankine vortex,the Oseen vortex is a concentrated vortex with a deformed vortex core.The vortex structure consists of the vortex core region,the transition region and the shear layer region(or the potential flow region).The transition region reflects the properties of the resultant vorticity of the same magnitude and the resultant deformation rate of the shear layer,and the transition region also determines the boundary of the vortex core.Finally,the evolution of leading-edge vortices of the double-delta wing is numerically simulated.And with different vortex identification methods,the shape and the properties of the leading-edge vortices identified by each method are analyzed and compared.It is found that in the vorticity concentration region,the vortices obtained by using ω,λ2,Ω criteria and Q criteria are basically identical when appropriate threshold values are adopted.However,in the region where the vorticity is dispersed,due to the influence of the flow viscous effect and the adverse pressure gradient,the results obtained by different vortex identification methods can be quite different,as well as the related physical properties,which need to be further studied.

Two-Stage Identification Method for Attitude-Control Models of On-Orbit Satellites

A two-stage identification method was developed for attitude-control models of on-orbit satellites for accurate attitude control. The attitude-control models are based on a generalized attitude model （GAM） and its corresponding noise model （NM）. These are both low order models which are able to characterize the main satellite dynamics and the corresponding noise. These low-order attitude-control models facilitate improved controller design and state estimation. This identification approach uses two open-loop identification processes, with higher order auxiliary models used in the estimation for filtering and with the filtered signals used to identify the low order GAM and NM. An identification experiment with a micro-satellite simulator was used to verify the effectiveness of the two-stage identification method.

Is economic policy uncertainty a major fluctuation factor?Based on a new mixed identification method

To investigate to what extent economic policy uncertainty affects China’s macroeconomic fluctuations,we construct a mixed identification scheme that combines some regular sign restrictions with zero restriction in a SVAR model,aiming to simultaneously identify economic policy uncertainty shocks and the three conventional structural shocks of demand,supply and monetary policy.The research shows that(1)economic policy uncertainty shocks,though not the major factor for economic fluctuations in China,exhibit characteristics similar to those of negative demand shocks with inflation effect obviously stronger than output effect;(2)in the full sample period,demand shocks are the primary driving factor for China’s economic fluctuations,followed by supply shocks;(3)supply shocks are the most important driving force behind inflation and monetary policy adds fuel to the flame,while economic policy uncertainty shocks exert obvious inhibition on inflation.The academic contribution of this paper is showing some robust empirical facts of economic policy uncertainty’s effects on macroeconomic fluctuations from the biggest developing country,and the policy implication of our research is to provide academic support for the decision of“macroeconomic policies should remain stable”.

RECONSTRUCTION OF PART OF AN ACTUAL BLAST-WAVE FLOW FIELD TO AGREE WITH EXPERIMENTAL DATA BY USING NUMERICAL METHOD WITH HIGH IDENTIFICATION

In this paper, on the basis of experimental data of two kinds of chemical explosions, the piston-pushing model of spherical blast-waves and the second-order Godunov-type scheme of finite difference methods with high identification to discontinuity are used to the numerical reconstruction of part of an actual hemispherical blast-wave flow field by properly adjusting the moving bounary conditions of a piston. This method is simple and reliable. It is suitable to the evaluation of effects of the blast-wave flow field away from the explosion center.

Identification of constitutive model parameters for nickel aluminum bronze in machining

The material of nickel aluminum bronze (NAB) presents superior properties such as high strength, excellent wear resistance and stress corrosion resistance and is extensively used for marine propellers. In order to establish the constitutive relation of NAB under high strain rate condition, a new methodology was proposed to accurately identify the constitutive parameters of Johnson?Cook model in machining, combining SHPB tests, predictive cutting force model and orthogonal cutting experiment. Firstly, SHPB tests were carried out to obtain the true stress?strain curves at various temperatures and strain rates. Then, an objective function of the predictive and experimental flow stresses was set up, which put the identified parameters of SHPB tests as the initial value, and utilized the PSO algorithm to identify the constitutive parameters of NAB in machining. Finally, the identified parameters were verified to be sufficiently accurate by comparing the values of cutting forces calculated from the predictive model and FEM simulation.