Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

Research on characters of surrounding rock in complex geology conditions and supporting time

The methods combined by test, field monitoring and theoretical analysis were adopted to do the systemic research on the rock mass from micro-structure to macro-deformation, and rheological model of Jinchuan rock mass was established to discuss the reasonable supporting time. Resuhs show that supporting after suitable stress and displacement release can benefit for the long-term stability of surrounding rock.

Comparison of pH Value, TBA Value, Glycogen and Lactic Acid Content in Muscle of Landrace and Yorkshire under Different Storage Time and Conditions

In order to assess the meat quality under different storage time and conditions, the pH value, TBA value, glycogen and lactic acid content in muscle of Landrace and Yorkshire were measured. The results showed that within 10 h post slaughtering, post slaughtering time had extremely significant influence on pH value and lactic acid content of Landrace, but had no significant influence on glycogen content and TBA value. On the other hand, post slaughtering time had extremely significant influence on pH value of Yorkshire, but had no significant influence on glycogen, lactic acid content and TBA value. The pH values of Yorkshire at 3, 5 and 10 h post slaughtering were 5.21% （ P 〈 0.01 ）, 5.64% （ P 〈 0.05 ） and 5.59% （ P 〈 0.05 ） higher than those of Landrace, respectively ; the lactic acid content in muscle of Landrace at 10 h post slaughtering was 56.04% （P 〈0.05） higher than that of Yorkshire; the TBA value in muscle of Yorkshire at 10 h post slaughtering was 89. 19% （P 〈 0.01 ） higher than that of Landrace; there was no significant difference in glycogen content between Yorkshire and Landrace. When pork stored at 4℃, storage time had no significant influence on pH value and glycogen content in muscle of Landrace, but had significant influence on drip loss, lactic acid content and TBA value ; storage time had no significant influence on pH value, glycogen content and TBA value in muscle of Yorkshire, but extremely significant influence on drip loss and significant influence on lactic acid content. The pH value in muscle of Yorkshire at 24 h post storage at 4℃ was 6.56% （P 〈0.05） higher than that of Landrace; the glycogen contents in muscle of Landrace at 24, 48, 72, 96, 120 and 144 h post storage at 4℃ were 84.90% （P〈0.05）,78.40% （P〈0.01）, 101.87% （P〈0.05）, 83.80% （P〈0.05）, 83.59% （P〈 0.05）and67.25% （P〈0.01）higher than those of York-shire, respectively; the drip loss of Landrace at 72 h post storage and TBA value at 144 h post storage were 55.70% （ P 〈 0.05 ） and 141.33 % （ P 〈 0.01 ） higher than those of Yorkshire, respectively; there was no significant difference in glycogen content between Yorkshire and Landrace. When pork stored at -20℃, storage time had significant influence on TBA value in muscle of Landrace, but had no significant influence on pH value, thawing water loss rate, glycogen and lactic acid content; storage time had no significant impact on pH value, thawing water loss rate, glycogen content and TBA value in muscle of Yorkshire, and had significant influence on lactic acid content. The pH value in muscle of Yorkshire at 24 h post storage at - 20℃ was 5.43 % （ P 〈 0.05 ） higher than that of I.andrace ; the glycogen contents in muscle of Landrace at 24, 48, 72, 96, 120 h post storage at - 20℃ were 85.08% （ P 〈0. 05 ）, 108.66% （ P 〈 0.01 ）, 72.69% （ P 〈 0.05 ）, 90.31% （ P 〈 0.01 ）, 70.38% （ P 〉 0.05 ） higher than those of Yorkshire, respectively ; the thawing water loss rates of Landrace at 24 and 72 h were 160.14% （ P 〈 0.05 ） and 74.32% （ P 〈 0.05 ） higher than those of Yorkshire, respectively ; there was no significant difference in lactic acid content and TBA value at the same time point between Yorkshire and Landrace.

Coseismic site response and slope instability using periodic boundary conditions in the material point method

This paper proposed the explicit generalized-a time scheme and periodic boundary conditions in the material point method(MPM)for the simulation of coseismic site response.The proposed boundary condition uses an intuitive particle-relocation algorithm ensuring material points always remain within the computational mesh.The explicit generalized-a time scheme was implemented in MPM to enable the damping of spurious high frequency oscillations.Firstly,the MPM was verified against finite element method(FEM).Secondly,ability of the MPM in capturing the analytical transfer function was investigated.Thirdly,a symmetric embankment was adopted to investigate the effects of ground motion arias intensity(I_(a)),geometry dimensions,and constitutive models.The results show that the larger the model size,the higher the crest runout and settlement for the same ground motion.When using a Mohr-Coulomb model,the crest runout increases with increasing I_(a).However,if the strain-softening law is activated,the results are less influenced by the ground motion.Finally,the MPM results were compared with the Newmark sliding block solution.The simplified analysis herein highlights the capabilities of MPM to capture the full deformation process for earthquake engineering applications,the importance of geometry characterization,and the selection of appropriate constitutive models when simulating coseismic site response and subsequent large deformations.

CONDITIONS OF ASYMPTOTIC STABILITY FOR CELLULAR NEURAL NETWORKS WITH TIME DELAY

In this paper, global asymptotic stability for cellular neural networks with time delay is discussed using a novel Liapunov function. Some novel sufficient conditions for global asymptotic stability are obtained. Those results are simple and practical than those given by P. P. Civalleri, et al., and have a leading importance to design cellular neural networks with time delay.

GmAP1d regulates flowering time under long-day photoperiods in soybean

Flowering time is important for adaptation of soybean(Glycine max)to different environments.Here,we conducted a genome-wide association study of flowering time using a panel of 1490 cultivated soybean accessions.We identified three strong signals at the qFT02-2 locus(Chr02:12037319–12238569),which were associated with flowering time in three environments:Gongzhuling,Mengcheng,and Nanchang.By analyzing linkage disequilibrium,gene expression patterns,gene annotation,and the diversity of variants,we identified an AP1 homolog as the candidate gene for the qFT02-2 locus,which we named GmAP1d.Only one nonsynonymous polymorphism existed among 1490 soybean accessions at position Chr02:12087053.Accessions carrying the Chr02:12087053-T allele flowered significantly earlier than those carrying the Chr02:12087053-A allele.Thus,we developed a cleaved amplified polymorphic sequence(CAPS)marker for the SNP at Chr02:12087053,which is suitable for marker-assisted breeding of flowering time.Knockout of GmAP1d in the‘Williams 82’background by gene editing promoted flowering under long-day conditions,confirming that GmAP1d is the causal gene for qFT02-2.An analysis of the region surrounding GmAP1d revealed that GmAP1d was artificially selected during the genetic improvement of soybean.Through stepwise selection,the proportion of modern cultivars carrying the Chr02:12087053-T allele has increased,and this allele has become nearly fixed(95%)in northern China.These findings provide a theoretical basis for better understanding the molecular regulatory mechanism of flowering time in soybean and a target gene that can be used for breeding modern soybean cultivars adapted to different latitudes.

An improved reverse time migration for subsurface imaging over complex geological structures:A numerical study

In seismic exploration,it is a critical task to image and interpret different seismic signatures over complex geology due to strong lateral velocity contrast,steep reflectors,overburden strata and dipping flanks.To understand the behavior of these seismic signatures,nowadays Reverse Time Migration(RTM)technique is used extensively by the oil&gas industries.During the extrapolation phase of RTM,the source wavefield needs to be saved,which needs high storage memory and large computing time.These two are the main obstacles of RTM for production use.In order to overcome these disadvantages,in this study,a second-generation improved RTM technique is proposed.In this improved form,a shift operator is introduced at the time of imaging condition of RTM algorithm which is performed automatically both in space and time domain.This effort is made to produce a better-quality image by minimizing the computational time as well as numerical artefacts.The proposed method is applied over various benchmark models and validated by implementing over one field data set from the Jaisalmer Basin,India.From the analysis,it is observed that the method consumes a minimum of 45%less storage space and reduce the execution time by 20%,as compared to conventional RTM.The proposed RTM is found to work efficiently in comparison to the conventional RTM both in terms of imaging quality and minimization of numerical artefacts for all the benchmark models as well as field data.

GENERAL DECAY FOR A VISCOELASTIC EQUATION OF VARIABLE COEFFICIENTS WITH A TIME-VARYING DELAY IN THE BOUNDARY FEEDBACK AND ACOUSTIC BOUNDARY CONDITIONS

A variable coefficient viscoelastic equation with a time-varying delay in the boundary feedback and acoustic boundary conditions and nonlinear source term is considered.Under suitable assumptions, general decay results of the energy are established via suitable Lyapunov functionals and some properties of the convex functions. Our result is obtained without imposing any restrictive growth assumption on the damping term and the elements of the matrix A and the kernel function g.

Sufficient conditions of the various stabilities of the linear time-varying delayed differential equations

Due to the appearance and the study of the ornithopter and flexible-wing micro air vehicles, etc., the time-varying systems become more and more important and ubiquitous in the study of the mechanics. In this letter, the sufficient conditions of the uniform asymptotic stability are first presented for the delayed time-varying linear differential equations with any time delay by employing the Dini derivative, Lozinskii measure and the generalized scalar Halanay delayed differential inequality. They are especially based on the estimation of the arbitrary solutions but not the fundamental solution matrix since their solutions＇ space is infinite-dimensional. Then some sufficient conditions of the stability, asymptotic stability and uniform asymptotic stability of the delayed time-varying linear system with a sufficiently small time delay are reported by employing Taylor expansion and Dini derivative. It implies that these stabilities can be guaranteed by the Lozinskii measure of the matrix composing of the time delay and the coefficient matrices of the system.

Solutions for a class of Hamiltonian systems on time scales with non-local boundary conditions

In this work,the solvability of a class of second-order Hamiltonian systems on time scales is generalized to non-local boundary conditions.The measurements obtained by non-local conditions are more accurate than those given by local conditions in some problems.Compared with the known results,this work establishes the variational structure in an appropriate Sobolev’s space.Then,by applying the mountain pass theorem and symmetric mountain pass theorem,the existence and multiplicity of the solutions are obtained.Finally,some examples with numerical simulation results are given to illustrate the correctness of the results obtained.

Exact Time Domain Solutions of 1-D Transient Dynamic Piezoelectric Problems with Nonlinear Damper Boundary Conditions

Novel exact solutions of one-dimensional transient dynamic piezoelectric problems for thickness polarized layers and disks, or length polarized rods, are obtained. The solutions are derived using a time-domain Green’s function method that leads to an exact analytical recursive procedure which is applicable for a wide variety of boundary conditions including nonlinear cases. A nonlinear damper boundary condition is considered in more detail. The corresponding nonlinear relationship between stresses and velocities at a current time moment is used in the recursive procedure. In addition to the exact recursive procedure that is effective for calculations, some new practically important explicit exact solutions are presented. Several examples of the time behavior of the output electric potential difference are given to illustrate the effectiveness of the proposed exact approach.

Riemannian Space-Time, de Donder Conditions and Gravitational Field in Flat Space-Time

Let the coordinate system xi of flat space-time to absorb a second rank tensor field Φij of the flat space-time deforming into a Riemannian space-time, namely, the tensor field Φuv is regarded as a metric tensor with respect to the coordinate system xu. After done this, xu is not the coordinate system of flat space-time anymore, but is the coordinate system of the new Riemannian space-time. The inverse operation also can be done. According to these notions, the concepts of the absorption operation and the desorption operation are proposed. These notions are actually compatible with Einstein’s equivalence principle. By using these concepts, the relationships of the Riemannian space-time, the de Donder conditions and the gravitational field in flat space-time are analyzed and elaborated. The essential significance of the de Donder conditions (the harmonic conditions or gauge) is to desorb the tensor field of gravitation from the Riemannian space-time to the Minkowski space-time with the Cartesian coordinates. Einstein equations with de Donder conditions can be solved in flat space-time. Base on Fock’s works, the equations of gravitational field in flat space-time are obtained, and the tensor expression of the energy-momentum of gravitational field is found. They all satisfy the global Lorentz covariance.

基于Simulink Real-Time的汽车空调半实物仿真试验系统研发

针对多样化汽车空调电子零部件的高效、低成本总成级测试需求,研究基于一汽大众速腾1.6 L车型原型,设计了基于Simulink Real-Time的汽车空调半实物仿真试验系统。该系统集成了真实的汽车空调总成、制冷循环以及包含宿主机和目标机的双机实时仿真系统,用于开发和运行台架监控和空调控制模型,为汽车空调电子零部件提供半实物仿真测试环境。通过系统集成及功能验证,结果表明,汽车空调半实物仿真试验系统能够实现汽车空调基本控制功能,同时在不同工况下实现乘员舱温度控制的稳定性,稳态误差控制在±1℃以内。此外,该系统还具备灵活调整空调运行工况和状态的能力,为汽车空调电子零部件提供了高效、低成本的半实物仿真测试环境。

Traffic condition estimation with pre-selection space time model

A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.

Probabilistic prediction of expected ground condition and construction time and costs in road tunnels

Ground condition and construction （excavation and support） time and costs are the key factors in decision-making during planning and design phases of a tunnel project. An innovative methodology for probabilistic estimation of ground condition and construction time and costs is proposed, which is an integration of the ground prediction approach based on Markov process, and the time and cost variance analysis based on Monte-Carlo （MC） simulation. The former provides the probabilistic description of ground classification along tunnel alignment according to the geological information revealed from geological profile and boreholes. The latter provides the probabilistic description of the expected construction time and costs for each operation according to the survey feedbacks from experts. Then an engineering application to Hamro tunnel is presented to demonstrate how the ground condition and the construction time and costs are estimated in a probabilistic way. In most items, in order to estimate the data needed for this methodology, a number of questionnaires are distributed among the tunneling experts and finally the mean values of the respondents are applied. These facilitate both the owners and the contractors to be aware of the risk that they should carry before construction, and are useful for both tendering and bidding.

Cell transmission model based traffic signal timing in oversaturated conditions

In order to investigate enhancements to cell transmission model (CTM) as a tool for traffic signal timing in oversaturated conditions, randomly distributed saturation flow rates and arrival rates were used instead of constant values to simulate traffic flow movement, estimate the average delay of the network and search for an optimal traffic signal timing plan. A case study was given to demonstrate that the proposed methodology can capture unique phenomena in oversaturated conditions such as forward wave, spillback and lane entrance blockage. The results show that CTM underestimates travel time by 25% when compared to Simtraffic, while the enhanced CTM underestimates by only 3%. A second case study shows that a dynamic signal timing plan is superior to a fixed signal timing plan in the term of average delay.

Reverse time migration based on normalized wavefield decomposition imaging condition

With the increasing complexity of prospecting objectives,reverse time migration( RTM) has attracted more and more attention due to its outstanding imaging quality. RTM is based on two-way wave equation,so it can avoid the limits of angle in traditional one-way wave equation migration,image reverse branch,prism waves and multi-reflected wave precisely and obtain accurate dynamic information. However,the huge demands for storage and computation as well as low frequency noises restrict its wide application. The normalized cross-correlation imaging conditions based on wave field decomposition are derived from traditional cross-correlation imaging condition,and it can eliminate the low-frequency noises effectively and improve the imaging resolution. The practical procedure includes separating source and receiver wave field into one-way components respectively,and conducting cross-correlation imaging condition to the post-separated wave field. In this way,the resolution and precision of the imaging result will be promoted greatly.

Electro-osmotic chemical behavior of clayey soil under various boundary conditions

The use of electro-osmotic chemical is an effective method to improve the clayey soil foundation.Various boundary conditions can be adopted in this method.In this work,two electrode–clay contacts,three solution conditioners,and four anode solution supply times were used for clayey soil improvement.Based on the experimental data,electro-osmotic consolidation theory,and transport of ion theory,it is found that the electro-osmotic chemical effect of the separation of electrode–clay(E_S)is more beneficial for the transport of Ca^(2+),production of cementing material,and reduction of water content than that of electrode–clay(E_C)joining;through electrode–clay contact separation,the anode solution conditioner(NaPO3)6(E_SHMP)delayed the cementing reaction and then increased the transport of Ca^(2+)near the cathode,which increased the amount of cementing material and the electro-osmotic chemical effect;and when the anode conditioner(NaPO3)6 was used,two days of anode solution supply followed by three days cut off from the anode solution led to the highest undrained shear strength increase after the application of electro-osmotic chemical,which resolved the uneven electro-osmotic chemical effect in the E_SHMP.

Quantitative detection of locomotive wheel polygonization under non-stationary conditions by adaptive chirp mode decomposition

Wheel polygonal wear is a common and severe defect,which seriously threatens the running safety and reliability of a railway vehicle especially a locomotive.Due to non-stationary running conditions(e.g.,traction and braking)of the locomotive,the passing frequencies of a polygonal wheel will exhibit time-varying behaviors,which makes it too difficult to effectively detect the wheel defect.Moreover,most existing methods only achieve qualitative fault diagnosis and they cannot accurately identify defect levels.To address these issues,this paper reports a novel quantitative method for fault detection of wheel polygonization under non-stationary conditions based on a recently proposed adaptive chirp mode decomposition(ACMD)approach.Firstly,a coarse-to-fine method based on the time–frequency ridge detection and ACMD is developed to accurately estimate a time-varying gear meshing frequency and thus obtain a wheel rotating frequency from a vibration acceleration signal of a motor.After the rotating frequency is obtained,signal resampling and order analysis techniques are applied to an acceleration signal of an axle box to identify harmonic orders related to polygonal wear.Finally,the ACMD is combined with an inertial algorithm to estimate polygonal wear amplitudes.Not only a dynamics simulation but a field test was carried out to show that the proposed method can effectively detect both harmonic orders and their amplitudes of the wheel polygonization under non-stationary conditions.

Gearbox Deterioration Detection under Steady State,Variable Load, and Variable Speed Conditions

Multiple dominant gear meshing frequencies are present in the vibration signals collected from gearboxes and the conventional spiky features that represent initial gear fault conditions are usually difficult to detect. In order to solve this problem, we propose a new gearbox deterioration detection technique based on autoregressive modeling and hypothesis testing in this paper. A stationary autoregressive model was built by using a normal vibration signal from each shaft. The established autoregressive model was then applied to process fault signals from each shaft of a two-stage gearbox. What this paper investigated is a combined technique which unites a time-varying autoregressive model and a two sample Kolmogorov-Smimov goodness-of-fit test, to detect the deterioration of gearing system with simultaneously variable shaft speed and variable load. The time-varying autoregressive model residuals representing both healthy and faulty gear conditions were compared with the original healthy time-synchronous average signals. Compared with the traditional kurtosis statistic, this technique for gearbox deterioration detection has shown significant advantages in highlighting the presence of incipient gear fault in all different speed shafts involved in the meshing motion under variable conditions.