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.

Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

Digital modulation classification using multi-layer perceptron and time-frequency features

Considering that real communication signals corrupted by noise are generally nonstationary, and timefrequency distributions are especially suitable for the analysis of nonstationary signals, time-frequency distributions are introduced for the modulation classification of communication signals： The extracted time-frequency features have good classification information, and they are insensitive to signal to noise ratio （SNR） variation. According to good classification by the correct rate of a neural network classifier, a multilayer perceptron （MLP） classifier with better generalization, as well as, addition of time-frequency features set for classifying six different modulation types has been proposed. Computer simulations show that the MLP classifier outperforms the decision-theoretic classifier at low SNRs, and the classification experiments for real MPSK signals verify engineering significance of the MLP classifier.

Relative Ding Projective Modules over Formal Triangular Matrix Rings

Let U be a (B, A)-bimodule, A and B be rings, and be a formal triangular matrix ring. In this paper, we characterize the structure of relative Ding projective modules over T under some conditions. Furthermore, using the left global relative Ding projective dimensions of A and B, we estimate the relative Ding projective dimension of a left T-module.

Quasi-LFM radar waveform recognition based on fractional Fourier transform and time-frequency analysis

Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.

Surface Topography Modulates Cell Mechanosensing of Extracellular Matrix

The interaction between the cell membrane and the extracellular matrix is crucial for many cellular functions by modulating mechanosensitive signaling pathways.Physical properties of the extracellular matrix such as stiffness and topography affect such interactions.Our recent work reveals that surface topography of tens to hundreds of nanometer scale modulates cell signaling by activating intracellular curvature-sensitive proteins.We use vertical nanostructures protruding from a flat surface as a platform to induce precise curvatures on the cell membrane and to probe biological processes in live cells.Vertical nanopillars deform the plasma membrane inwards and induce membrane curvature when the cell engulfs them,leading to a reduction of the membrane-substrate gap distance.We found that the high membrane curvature induced by vertical nanopillars significantly affects the distribution of curvature-sensitive proteins and stimulates several cellular processes in live cells including cellular endocytosis and cytoskeleton dynamics.Our studies show a strong interplay between biological cells and nano-featured surfaces,which is an essential consideration for future development of interfacing devices.

PI and RST Control Design and Comparison for Matrix Converters Using Venturini Modulation Strategy

This paper presents a thorough design and comparative study of two popular control techniques, i.e., classical Proportional Integral (PI) and RST, for Matrix Converters (MCs) in terms of tracking the reference and robustness. The output signal of MCs is directly affected by unbalanced grid voltage. Some research works have attempted to overcome this problem with PI control. However, this technique is known to offer lower performance when it is used in complex and nonlinear systems. On the other hand, RST control offers better performance, even in case of highly nonlinear systems. Therefore, the RST can achieve better performance to overcome the limitation of PI control of nonlinear systems. In this paper, a RST control method is proposed as output current controller to improve the performance of the MC powered by unbalanced grid voltage. The overall operating principle, Venturini modulation strategy of MC, PI control and characteristics of RST are presented.

Orthogonal matrix of polarization combinations:concept and application to multichannel holographic recording

Orthogonal matrices have become a vital means for coding and signal processing owing to their unique distributional properties.Although orthogonal matrices based on amplitude or phase combinations have been extensively explored,the orthogonal matrix of polarization combinations(OMPC)is a novel,relatively unexplored concept.Herein,we propose a method for constructing OMPCs of any dimension encompassing 4n(where n is 1,2,4,8,…)mutually orthogonal 2ncomponent polarization combinations.In the field of holography,the integration of polarization multiplexing techniques with polarization-sensitive materials is expected to emerge as a groundbreaking approach for multichannel hologram multiplexing,offering considerable enhancements in data storage capacity and security.A multidimensional OMPC enables the realization of multichannel multiplexing and dynamical modulation of information in polarization holographic recording.Despite consolidating all information into a single position within the material,we effectively avoided extraneous crosstalk during the reconstruction process.Our results show that achieving four distinct holographic images individually and simultaneously depends on the polarization combination represented by the incident wave.This discovery opens up a new avenue for achieving highly holographic information storage and dynamically displayed information,harnessing the potential of OMPC to expand the heretofore limited dimensionality of orthogonal polarization.

DIGITAL PWM OF AC-AC MATRIX CONVERTER BASED ON OUTPUT-VOLTAGE ERROR FUNCTION

Based on the output-voltage error function, a novel time discrete modulation technique is proposed for matrix converters （MCs） and time-discrete difference equations of a MC circuit are derived. Switch states of MC are obtained when the output voltage error function is minimized, thus the optimum combination of switch states is derived for the closed-loop control of MC. Meanwhile, advantages of the least calculation workload, the simple process, and the convenient for implementation are brought while switch states are described as space vectors in the α-β coordination system. Simulation and experimental results demonstrate the validity of the time-discrete modulation technique and the feasibility of the control approach.

二维电离室点矩阵Matrixx在调强验证中的应用

目的：利用I′mRTMatrixx对适形及调强放射治疗计划二维剂量平面进行验证。通过软件分析确定治疗计划的准确性,提高治疗质量。方法：用Matrixx二维电离室点矩阵系统对适形调强放疗计划进行验证测试,模体为等效固体水,把Matrixx上面加到4.7 cm等效固体水,下面垫5 cm等效固体水,放入CT进行扫描,在计划系统中建成QA模体。然后将治疗计划系统中的适形调强计划放到QA模体上进行特定深度的计算,得到一个剂量平面计划,将该计划输入分析软件中,与同样条件下的实测剂量平面进行分析,比较。结果：通过软件采用Gamma算法,剂量偏差3%,位置偏差3 mm,小于1的r值是96%~100%。结论：Ma-trixx二维电离室点矩阵,在临床中可作为适形计划和调强计划的相对剂量验证工具,而且简单高效。是放疗质量控制的理想剂量验证工具。利用Matrixx阵列能同时较好的实现其绝对剂量和相对剂量的测量。

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.

Classification using wavelet packet decomposition and support vector machine for digital modulations

To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPTMMM） and a novel support vector machine fuzzy network （SVMFN） classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types （i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK）. Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability （success rates are over 98% when SNR is not lower than 0dB）, and it adapts to engineering applications.

AC/DC Matrix Converters for V2G Applications

由于当前V2G系统中普遍采用的电压型脉宽调制（pulse width modulation,PWM）整流方案中所存在的蓄电池电压匹配、功率体积比及系统效率问题,提出一种采用AC/DC矩阵变换器的解决方案。针对经典电流空间矢量调制策略中充电电流纹波较大的缺点,提出一种在全输出范围内减小充电电流纹波的分段优化调制策略,并深入对比分析这两种调制策略下充电电流纹波的大小。仿真和实验结果表明,所提分段优化调制策略的正确性和可行性。

A MATRIX ALGORITHM FOR COMPUTING THE FREE SPACE DISTANCE OF TCM SIGNAL SEQUENCES

In this paper, the problem of computing the free distance of Trellis Coded Modulation (TCM) signal sequence has been discussed; a new algorithm-the matrix algorithm is proposed; and the step-number estimation problem for state transmission to compute the free distance of TCM signal sequence has been theoretically solved. The matrix algorithm is derived from the Viterbi algorithm, and is an implementation of Viterbi algorithm in the form of matrix. Compared with other algorithms, the matrix algorithm gains two advantages: (1) The explicit solution, and its relatively less complexity. (2) More reflexible ability to the signal space distance variation. As examples, the results of some TCM signal sequence on AWGN channel and fading channels have been presented.

High Performance Control of Matrix Converter Fed Induction Motor Drive System

Matrix converter fed motor drive is superior to pulse width modulation inverter drives since it not only provides bi-directional power flow,sinusoidal input/output currents,unity input power factor,but also allows a compact design due to the lack of DC-link capacitors for energy storage.In this paper,model and control of matrix converter fed induction motor drive system are analyzed.A combined control strategy is simplified and improved,which realizes space vector pulse width modulation of matrix converter and rotor flux oriented vector control technique for induction motor drive simultaneously.This control strategy combines the advantages of matrix converter with the good drive performance of vector control technique.Experimental results demonstrate the feasibility and effectiveness of the proposed control strategy.

Phase-shift interferometry measured transmission matrix of turbid medium: Three-step phase-shifting interference better than four-step one

Transmission matrix(TM)is an important tool for controlling light focusing,imaging,and communication through turbid media.It can be measured by 3-step(TM3)or 4-step(TM4)phase-shifting interference,but the similarities and differences of the transmission matrices obtained by the two methods are rarely reported.Therefore,we make a quantitative comparison of the peak light intensity,signal-to-noise ratio,and average background of 24×24=576 focal points between paired samples(TM3-TM4)through the Wilcoxon rank sum test,and discuss the singular value of the transmission matrix and the focal peak.The comparative results of peak light intensity and signal-to-noise ratio show that there is a significant difference between the 3-step phase shift and the 4-step phase shift transmission matrixes.The focusing effect of the former is significantly better than that of the latter;interest concentrates on the focal intensity and singular value.The reciprocal of the singular value is proportional to the squared intensity,which is in accordance with singular value theory.The results of comparison of peak light intensity and signal-to-noise ratio strongly suggest that 3-step phase shift should be selected and used in applying the phase shift method to the measurement of the transmission matrix;and the singular value is of great significance in quantifying the focusing,imaging,and communication quality of the transmission matrix.

The Cartan Invariant Matrix for the Finite Group G₂(13) of Type G₂

The Cartan invariant matrixfor the finite group G2(13) of type G2 over the finite field with 13 elements is determined in this paper.

Error code analysis and selection principle of M-ary modulation in network-based control systems

Error codes induced by M-ary modulation and modulation selection in network-based control systems are studied.It is the first time the issue of error codes induced by M-ary modulation is addressed in control field.In network-based control systems,error codes induced by noisy channel can significantly decrease the quality of control.To solve this problem,the network-based control system with delay and noisy channel is firstly modeled as an asynchronous dynamic system(ADS).Secondly,conditions of packet with error codes(PEC)loss rate by using M-ary modulation are obtained based on dynamic output feedback scheme.Thirdly,more importantly,the selection principle of M-ary modulation is proposed according to the measured signal-to-noise ratio(SNR)and conditions of PEC loss rate.Finally,system stability is analyzed and controller is designed through Lyapunov function and linear matrix inequality(LMI)scheme,and numerical simulations are made to demonstrate the effectiveness of the proposed scheme.

ROTATION CONSTELLATION FOR DIFFERENTIAL UNITARY SPACE-TIME MODULATION

A new constellation which is the multiplication of the rotation matrix and the diagonal matrix ac- cording to the number of transmitters is proposed to increase the diversity product, the key property to the performance of the differential unitary space-time modulation. Analyses and the simulation results show that the proposed constellation performs better and 2dB or more coding gain can be achieved over the traditional cyclic constellation.

An Introduction to the Theory of Matrix Near-Rings

Matrix rings are prominent in abstract algebra. In this paper we give an overview of the theory of matrix near-rings. A near-ring differs from a ring in that it does not need to be abelian and one of the distributive laws does not hold in general. We introduce two ways in which matrix near-rings can be defined and discuss the structure of each. One is as given by Beildeman and the other is as defined by Meldrum. Beildeman defined his matrix near-rings as normal arrays under the operation of matrix multiplication and addition. He showed that we have a matrix near-ring over a near-ring if, and only if, it is a ring. In this case it is not possible to obtain a matrix near-ring from a proper near-ring. Later, in 1986, Meldrum and van der Walt defined matrix near-rings over a near-ring as mappings from the direct sum of n copies of the additive group of the near-ring to itself. In this case it can be shown that a proper near-ring is obtained. We prove several properties, introduce some special matrices and show that a matrix notation can be introduced to make calculations easier, provided that n is small.