Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

The W transform and its improved methods for time-frequency analysis of seismic data

The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region,we have proposed a W transform method,in which the instantaneous frequency is introduced as a parameter into the linear transformation,and the analysis time window is constructed which matches the instantaneous frequency of the seismic data.In this paper,the W transform method is compared with the Wigner-Ville distribution(WVD),a typical nonlinear time-frequency analysis method.The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet,while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing,because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter.Therefore,the W transform can be benchmarked directly by the WVD method.We summarize the development of the W transform and three improved methods in recent years,and elaborate on the evolution of the standard W transform,the chirp-modulated W transform,the fractional-order W transform,and the linear canonical W transform.Through three application examples of W transform in fluvial sand body identification and reservoir prediction,it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra.

Unfolding analysis of LaBr3:Ce gamma spectrum with a detector response matrix constructing algorithm based on energy resolution calibration

With respect to the gamma spectrum, the energy resolution improves with increase in energy. The counts of full energy peak change with energy, and this approximately complies with the Gaussian distribution. This study mainly examines a method to deconvolve the LaBr_3:Ce gamma spectrum with a detector response matrix constructing algorithm based on energy resolution calibration.In the algorithm, the full width at half maximum(FWHM)of full energy peak was calculated by the cubic spline interpolation algorithm and calibrated by a square root of a quadratic function that changes with the energy. Additionally, the detector response matrix was constructed to deconvolve the gamma spectrum. Furthermore, an improved SNIP algorithm was proposed to eliminate the background. In the experiment, several independent peaks of ^(152)Eu,^(137)Cs, and ^(60)Co sources were detected by a LaBr_3:Ce scintillator that were selected to calibrate the energy resolution. The Boosted Gold algorithm was applied to deconvolve the gamma spectrum. The results showed that the peak position difference between the experiment and the deconvolution was within ± 2 channels and the relative error of peak area was approximately within 0.96–6.74%. Finally, a ^(133) Ba spectrum was deconvolved to verify the efficiency and accuracy of the algorithm in unfolding the overlapped peaks.

Kohn-Sham Density Matrix and the Kernel Energy Method

The kernel energy method(KEM) has been shown to provide fast and accurate molecular energy calculations for molecules at their equilibrium geometries.KEM breaks a molecule into smaller subsets,called kernels,for the purposes of calculation.The results from the kernels are summed according to an expression characteristic of KEM to obtain the full molecule energy.A generalization of the kernel expansion to density matrices provides the full molecule density matrix and orbitals.In this study,the kernel expansion for the density matrix is examined in the context of density functional theory(DFT) Kohn-Sham(KS) calculations.A kernel expansion for the one-body density matrix analogous to the kernel expansion for energy is defined,and is then converted into a normalizedprojector by using the Clinton algorithm.Such normalized projectors are factorizable into linear combination of atomic orbitals(LCAO) matrices that deliver full-molecule Kohn-Sham molecular orbitals in the atomic orbital basis.Both straightforward KEM energies and energies from a normalized,idempotent density matrix obtained from a density matrix kernel expansion to which the Clinton algorithm has been applied are compared to reference energies obtained from calculations on the full system without any kernel expansion.Calculations were performed both for a simple proof-of-concept system consisting of three atoms in a linear configuration and for a water cluster consisting of twelve water molecules.In the case of the proof-of-concept system,calculations were performed using the STO-3 G and6-31 G(d,p) bases over a range of atomic separations,some very far from equilibrium.The water cluster was calculated in the 6-31 G(d,p) basis at an equilibrium geometry.The normalized projector density energies are more accurate than the straightforward KEM energy results in nearly all cases.In the case of the water cluster,the energy of the normalized projector is approximately four times more accurate than the straightforward KEM energy result.The KS density matrices of this study are applicable to quantum crystallography.

An inversion decomposition method for better energy resolution of NaI(Tl)scintillation detectors based on a Gaussian response matrix

NaI(T1) scintillation detectors have been widely applied for gamma-ray spectrum measurements owing to advantages such as high detection efficiency and low price.However,the mitigation of the limited energy resolution of these detectors,which detracts from an accurate analysis of the instrument spectra obtained,remains a crucial need.Based on the physical properties and spectrum formation processes of NaI(T1) scintillation detectors,the detector response to gamma photons with different energies is represented by photopeaks that are approximately Gaussian in shape with unique full-width-at-half-maximum(FWHM) values.The FWHM is established as a detector parameter based on resolution calibrations and is used in the construction of a general Gaussian response matrix,which is employed for the inverse decomposition of gamma spectra obtained from the detector.The Gold and Boosted Gold iterative algorithms are employed to accelerate the decomposition of the measured spectrum.Tests of the inverse decomposition method on multiple simulated overlapping peaks and on experimentally obtained U and Th radionuclide series spectra verify the practicability of the method,particularly in the low-energy region of the spectrum,providing for the accurate qualitative and quantitative analysis of radionuclides.

Comparative analysis of energy-level splitting of Pr^(3+) doped in LiYF_4 and LiBiF_4 crystals:a complete energy matrix calculation

Based on the combination of Racah＇s group-theoretical consideration with Slater＇s wavefunction, a 91 ×91 complete energy matrix is established in tetragonal ligand field D2d for Pr3＋ ion. Thus, the Stark energy-levels of Pr3＋ ions doped separately in LiYF4 and LiBiF4 crystals are calculated, and our calculations imply that the complete energy matrix method can be used as an effective tool to calculate the energy-levels of the systems doped by rare earth ions. Besides, the influence of Pr3＋ on energy-level splitting is investigated, and the similarities and the differences between the two doped crystals are demonstrated in detail by comparing their several pairs of curves and crystal field strength quantities. We see that the energy splitting patterns are similar and the crystal field interaction of LiYF4：Pr3＋ is stronger than that of LiBiF4：Pr3＋.

Energy eigenvalues from an analytical transfer matrix method

A detailed procedure based on an analytical transfer matrix method is presented to solve bound-state problems. The derivation is strict and complete. The energy eigenvalues for an arbitrary one-dimensional potential can be obtained by the method. The anharmonic oscillator potential and the rational potential are two important examples. Checked by numerical techniques, the results for the two potentials by the present method are proven to be exact and reliable.

Review on laser directed energy deposited aluminum alloys

Lightweight aluminum(Al)alloys have been widely used in frontier fields like aerospace and automotive industries,which attracts great interest in additive manufacturing(AM)to process high-value Al parts.As a mainstream AM technique,laser-directed energy deposition(LDED)shows good scalability to meet the requirements for large-format component manufacturing and repair.However,LDED Al alloys are highly challenging due to their inherent poor printability(e.g.low laser absorption,high oxidation sensitivity and cracking tendency).To further promote the development of LDED high-performance Al alloys,this review offers a deep understanding of the challenges and strategies to improve printability in LDED Al alloys.The porosity,cracking,distortion,inclusions,element evaporation and resultant inferior mechanical properties(worse than laser powder bed fusion)are the key challenges in LDED Al alloys.Processing parameter optimizations,in-situ alloy design,reinforcing particle addition and field assistance are the efficient approaches to improving the printability and performance of LDED Al alloys.The underlying correlations between processes,alloy innovation,characteristic microstructures,and achievable performances in LDED Al alloys are discussed.The benchmark mechanical properties and primary strengthening mechanism of LDED Al alloys are summarized.This review aims to provide a critical and in-depth evaluation of current progress in LDED Al alloys.Future opportunities and perspectives in LDED high-performance Al alloys are also outlined.

EOM-CCSD-Based Neural Network Diabatic Potential Energy Matrix for ^(1)πσ^(*)-Mediated Photodissociation of Thiophenol

A new diabatic potential energy matrix(PEM)of the coupled~^(1)ππ^(*)and~1πσ*states for the~1πσ*-mediated photodissociation of thiophenol was constructed using a neural network(NN)approach.The diabatization of the PEM was specifically achieved by our recent method[Chin.J.Chem.Phys.34,825(2021)],which was based on adiabatic energies without the associated costly derivative couplings.The equation of motion coupled cluster with single and double excitations(EOM-CCSD)method was employed to compute adiabatic energies of two excited states in this work due to its high accuracy,simplicity,and efficiency.The PEM includes three dimensionalities,namely the S-H stretch,C-S-H bend,and C-C-S-H torsional coordinates.The root mean square errors of the NN fitting for the S1 and S2 states are 0.89 and 1.33 me V,respectively,suggesting the high accuracy of the NN method as expected.The calculated lifetimes of the S1 vibronic 00 and31 states are found to be in reasonably good agreement with available theoretical and experimental results,which validates the new EOM-CCSD-based PEM fitted by the NN approach.The combination of the diabatization scheme solely based on the adiabatic energies and the use of EOM-CCSD method makes the construction of reliable diabatic PEM quite simple and efficient.

Hybrid Control Strategy for Matrix Converter Fed Wind Energy Conversion System

In this paper, a hybrid control strategy for a matrix converter fed wind energy conversion system is presented. Since the wind speed may vary, output parameters like power, frequency and voltage may fluctuate. Hence it is necessary to design a system that regulates output parameters, such as voltage and frequency, and thereby provides a constant voltage and frequency output from the wind energy conversion system. Matrix converter is used in the proposed solution as the main power conditioner as a more efficient alternative when compared to traditional back-back converter structure. To control the output voltage, a vector modulation based refined control structure is used. A power tracker is included to maximize the mechanical output power of the turbine. Over current protection and clamp circuit input protection have been introduced to protect the system from over current. It reduces the spikes generated at the output of the converter. The designed system is capable of supplying an output voltage of constant frequency and amplitude within the expected ranges of input during the operation. The matrix converter control using direct modulation method, modified Venturini modulation method and vector modulation method was simulated, the results were compared and it was inferred that vector modulation method was superior to the other two methods. With the proposed technique, voltage transfer ratio and harmonic profile have been improved compared to the other two modulation techniques. The behaviour of the system is corroborated by MATLAB Simulink, and hardware is realized using an FPGA controller. Experimental results are found to be matching with the simulation results.

Performance of Thermal Insulation of Different Composite Walls and Roofs Materials Used for Energy Efficient Building Construction in Iraq

This study numerically involves the performance of thermal insulation of different types of composite walls and roofs to demonstrate the best model that can be used for energy-efficient building construction in Iraq.The mathematical model is solved by building its code using the Transmission Matrix Method in MATLAB software.The weather data of 21st July 2022 in Baghdad City/Iraq is selected as a test day.The wall types are selected:the first type consists of cement mortar,brick,and gypsum,the second type consists of cement mortar,brick,gypsum,and plaster and the third type consists of cement mortar,brick,gypsum,air cavity,and sheathing timber.The roof types are chosen:the first type consists of reinforced concrete,gypsum,and plaster,and the second type consists of the precast concrete flag,river sand,tar,reinforced concrete,gypsum,and plaster.The obtained solutions are compared with previous studies for the same city but with different types of walls and roofs.The findings display that the second and third types of walls reduce the entry heat flux by 4%and 10%as compared to the first type of wall.Also,the results indicate that the second type of roof reduces the entry heat flux by 21%as compared to the first type of roof.The results confirm that the best models of walls and roofs in Iraq are the third and second types,respectively,as compared to other models and hence,the performance of insulation material strongly depends on the materials used while building them.

Decoding the Einstein-Type Formula for Reducing Energy Conversion to Carbon Emissions in Renewables Systems

This article explores the role of distributed energy resources such as efficient solar cells that drive carbon neutrality within the solar energy. For example, the perovskite solar cells offer high efficiency and potential for low-cost production. A novel theoretical model is discovered in distributed energy resources for power emissions and cost. The smart carbon neutrality approaches are analyzed in both theory and experiments. The advantages, current challenges, and future prospects of the related solutions are discussed methodically. By addressing stability and scalability issues, these approaches can contribute significantly to reducing carbon emissions and promoting sustainable energy solutions.

RESEARCH ON MATRIX CRACK EVOLUTION OF CROSS-PLY CERAMIC MATRIX COMPOSITE

The matrix crack evolution of cross-ply ceramic matrix composites under uniaxial tensile loading is investigated using the energy balance method.Under tensile loading,the cross-ply ceramic matrix composites have five damage modes.The cracking mode 3 contains transverse cracking,matrix cracking and fiber/matrix interface debonding.The cracking mode 5 only contains matrix cracking and fiber/matrix interface debonding.The cracking stress of modes 3 and 5 appearing between existing transverse cracks is determined.And the multiple matrix crack evolution of mode 3 is determined.The effects of ply thickness,fiber volume fraction,interface shear stress and interface debonding energy on the cracking stress and matrix crack evolution are analyzed.Results indicate that the cracking mode 3 is more likely to appear between transverse cracks for the SiC/CAS material.

Feature Extraction and Recognition for Rolling Element Bearing Fault Utilizing Short-Time Fourier Transform and Non-negative Matrix Factorization

Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, thc time-frequency analysis is often applied to describe the local information of these unstable signals smartly. However, it is difficult to classitythe high dimensional feature matrix directly because of too large dimensions for many classifiers. This paper combines the concepts of time-frequency distribution（TFD） with non-negative matrix factorization（NMF）, and proposes a novel TFD matrix factorization method to enhance representation and identification of bearing fault. Throughout this method, the TFD of a vibration signal is firstly accomplished to describe the localized faults with short-time Fourier transform（STFT）. Then, the supervised NMF mapping is adopted to extract the fault features from TFD. Meanwhile, the fault samples can be clustered and recognized automatically by using the clustering property of NMF. The proposed method takes advantages of the NMF in the parts-based representation and the adaptive clustering. The localized fault features of interest can be extracted as well. To evaluate the performance of the proposed method, the 9 kinds of the bearing fault on a test bench is performed. The proposed method can effectively identify the fault severity and different fault types. Moreover, in comparison with the artificial neural network（ANN）, NMF yields 99.3% mean accuracy which is much superior to ANN. This research presents a simple and practical resolution for the fault diagnosis problem of rolling element bearing in high dimensional feature space.

Hot Deformation Behavior of Squeeze Casting SiC_p/2 A50 Matrix Composites

The flow stress behaviors of squeeze casting SiCp/2A50 matrix composites were investigated by means of compression tests on a Gleeble 1500 therma1 mechanical simulator at isothermal constant strain rates ranging from of 0.001 to 1.0 with the testing temperature ranging from 350 to 500 ℃. The experiments showed that the relationship between stress and strain was obviously influenced by the strain rate and temperature. Dynamic recrystallization generally occurred at a higher temperature and a 1ower strain rate. A linear equation could be fitted between the Zener-Hollomon parameter Z and stress in the experiments. The mean value reciprocal of temperature at every true strain had a linear relation with natural logarithm of Z parameter, and the correlation coefficient, R=0.99, which was very significant by examination. The hot deformation activation energy of SiCp/2A50 matrix composites was 163.47 KJ/mol by calculation.

Research on big data applications in Global Energy Interconnection

Construction of Global Energy Interconnection(GEI) is regarded as an effective way to utilize clean energy and it has been a hot research topic in recent years. As one of the enabling technologies for GEI, big data is accompanied with the sharing, fusion and comprehensive application of energy related data all over the world. The paper analyzes the technology innovation direction of GEI and the advantages of big data technologies in supporting GEI development, and then gives some typical application scenarios to illustrate the application value of big data. Finally, the architecture for applying random matrix theory in GEI is presented.

Hybrid LEAP modeling method for long-term energy demand forecasting of regions with limited statistical data

An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.

The Energy and Operations of Graphs

Let G be a finite and undirected simple graph on n vertices, A(G) is the adjacency matrix of G, λ1,λ2,...,λn are eigenvalues of A(G), then the energy of G is . In this paper, we determine the energy of graphs obtained from a graph by other unary operations, or graphs obtained from two graphs by other binary operations. In terms of binary operation, we prove that the energy of product graphs is equal to the product of the energy of graphs G1 and G2, and give the computational formulas of the energy of Corona graph , join graph of two regular graphs G and H, respectively. In terms of unary operation, we give the computational formulas of the energy of the duplication graph DmG, the line graph L(G), the subdivision graph S(G), and the total graph T(G) of a regular graph G, respectively. In particularly, we obtained a lot of graphs pair of equienergetic.

A scattering matrix approach to quantum pumping:beyond the small-AC-driving-amplitude limit

In the adiabatic and weak-modulation quantum pump, net electron flow is driven from one reservoir to another by absorbing or emitting an energy quantum nω from or to the reservoirs. This paper considers high-order dependence of the scattering matrix on the time. Non-sinusoidal behaviour of strong pumping is revealed. The relation between the pumped current and the ac driving amplitude varies from power of 2, 1 to 1/2 when stronger modulation is exerted. Open experimental observation can be interpreted by multi-energy-quantum-related processes.

Generalization for Laplacian energy

Let G be a simple graph with n vertices and m edges. Let λ1, λ2,…, λn, be the adjacency spectrum of G, and let μ1, μ2,…, μn be the Laplacian spectrum of G. The energy of G is E（G） = n∑i=1｜λi｜, while the Laplacian energy of G is defined as LE（G） = n∑i=1｜μi-2m/n｜ Let γ1, γ2, ~ …, γn be the eigenvalues of Hermite matrix A. The energy of Hermite matrix as HE（A） = n∑i=1｜γi-tr（A）/n｜ is defined and investigated in this paper. It is a natural generalization of E（G） and LE（G）. Thus all properties about energy in unity can be handled by HE（A）.