First Evidence of Intrinsic Alignments of Red Galaxies at z > 1: Cross Correlation between CFHTLenS and FastSound Samples

We report the first evidence for intrinsic alignment (IA) of red galaxies at z > 1. We measure the gravitational shear-intrinsic ellipticity cross correlation function at z ∼ 1.3 using galaxy positions from the FastSound spectroscopic survey and galaxy shapes from the Canada France Hawaii telescope lensing survey data. Adopting the nonlinear alignment model, we obtain a 2.4σ level detection of the IA amplitude A LA = 27.48 − 11.54 + 11.53 (and 2.6σ with A LA = 29.43 − 11.49 + 11.48 when weak lensing contaminations are taken into account), which is larger than the value extrapolated from the constraints obtained at lower redshifts. Our measured IA is translated into a ∼20% contamination of the weak-lensing power spectrum for the red galaxies. This marginal detection of IA for red galaxies at z > 1 motivates the continuing investigation of the nature of IA for weak lensing studies. Furthermore, our result provides the first step to utilize IA measurements in future high-z surveys as a cosmological probe, complementary to galaxy clustering and lensing.

Results of experimental studies of a mobile energy vehicles in a transport unit with an elastic damping mechanism

Improving the operational efficiency of mobile energy vehicles is one of the main factors contributing to increased productivity while significantly reducing non-productive energy costs. Of no small importance are developments that are associated with the improvement of the design of transmissions of wheeled agricultural mobile energy vehicles, for which an indispensable condition is to increase labor productivity in agricultural production. The achievement of the required characteristics of mobile energy vehicles is determined by the properties of the transmission, as well as the interaction of the systems associated with it. One of the main qualities of the transmission is the ability to absorb torsional vibrations and damp the load. The article presents studies on establishing the constructive improvement of the transmission of a mobile energy vehicle by installing a developed elastic-damping mechanism in it using the example of a tractor of a small traction class. Taking into account the relevance of the topic under discussion in this article, it is necessary to determine the effect of the elastic-damping mechanism installed in the tractor transmission on its operation with a transport trailer, based on the field measurements carried out using the method of correlation — spectral analysis. The purpose of the study was to determine the effect of the elastic-damping mechanism installed in the power transmission of a tractor on its operation with a transport trailer. In this article, the analysis of the cross-correlation function and the analysis of the mutual spectral density of two processes were carried out: the engine crankshaft speed and the drive wheel speed. The analysis of the cross-correlation function shows the change in the propagation speed of the passing frequencies of load oscillations along the shafting by 39%. The analysis of the mutual spectral density shows that there is an absorption of a part of the load fluctuations propagating along the shafting and a shift in the frequency of disturbing influences by up to 68.3%.

Tabular algorithm for evaluating the discrete cross-correlation function of the flowmeter acoustic signals

Корреляционная обработка сигналов как частный случай использования цифровой обработки данных, получаемых с акустических датчиков, находит широкое применение в современных ультразвуковых расходомерах жидкости и газа. К ним можно отнести как непосредственно корреляционные меточные расходомеры, так и расходомеры преимущественно время-импульсного или время-пролетного типов, где корреляционная обработка акустических сигналов является дополнением к общему методу измерения объемного расхода жидкости и газа. Применение корреляционной обработки позволяет повысить разрешающую способность расходомера в целом и обеспечить выделение полезного сигнала на фоне присутствия шумов с высокой степенью достоверности. В статье описан способ вычисления дискретных корреляционных функций на основе обобщенного определения дискретной корреляционной функции через свертку дискретизированных сигналов с выходов датчиков потока. Суть данного метода сводится к вычислению набора значений кумулятивных произведений отсчетов зондирующих сигналов, взятых с разным шагом в зависимости от общего количества отсчетов сигналов и предполагаемого числа значений корреляционной функции. Полученный набор значений оформляется в виде двумерного массива или матрицы, однако для большего понимания его можно представить как таблицу. Результаты суммы отдельных элементов этой таблицы или матрицы, выбранных согласно установленному правилу, и будут являться конечными значениями взаимной корреляционной функции акустических сигналов. В рамках работы составлены непосредственно алгоритм вычисления дискретной корреляционной функции в соответствии с рассмотренным методом расчета корреляционной функции, приведены примеры вычисления программным способом взаимной и автокорреляционной функций акустических сигналов, приближенных по своим свойствам к сигналам реальных ультразвуковых расходомеров. Предложенный вариант расчета дискретных корреляционных функций может быть применен в энергоэффективных вычислительных модулях расходомеров, предназначенных для длительной эксплуатации от источника автономного питания, обладающих низкой производительностью. Correlation signal processing as a particular case of using a digital data processing obtained from acoustic sensors is widely used in modern ultrasonic liquid and gas flowmeters. These include both direct correlation flowmeters and predominantly a time-pulse or time-of-flight type’s flowmeters, where the correlation processing of acoustic signals is an addition to the general method for measuring the volumetric flow rate of liquid and gas. The use of correlation processing makes it possible to increase the resolution of the flowmeter as a whole and to ensure the useful signal extraction against the background of the noise presence with a high degree of reliability. The article describes a method for calculating discrete correlation functions based on the generalized definition of a discrete correlation function through the convolution of sampled signals from the flow sensors outputs. The essence of this method comes down to calculating a values set ​​of the cumulative products of the probing signal’s samples taken with different steps depending on the total number of signal samples and the assumed number of the correlation function samples. The resulting values sequence ​​is formatted as a two-dimensional array or matrix, but for better understanding it can be represented as a table. The results of the sum of the individual elements of this table or matrix, selected according to the established rule, will be the final values ​​of the cross-correlation function of acoustic signals. Within the framework, an algorithm for calculating the discrete correlation function is directly compiled in accordance with the considered method for calculating the correlation function, examples of software calculation of the cross- and autocorrelation functions of acoustic signals, which are close in their properties to the real signals of ultrasonic flowmeters, are given. The proposed option for calculating discrete correlation functions can be applied in energy-efficient computational modules of flowmeters designed for long-term operation from an autonomous power source with low performance.

Research on compound fault diagnosis of rolling bearing based on intrinsic time scale decomposition and information fusion

In view of the difficulty to effectively extract compound faults of rolling bearing from aero-engine and precisely identify their types, the paper has proposed a method integrating signal separation algorithm and information fusion. Firstly, the method decomposes the vibration acceleration signals collected by sensors from different positions at the same moment based on intrinsic time scale decomposition algorithm. Secondly, cross correlation analysis is given to the proper rotation component (PRC) of the same layer, which are obtained after decomposition and correspond to the sensors from different positions and cross-correlation function is introduced to embody information fusion. Thirdly, signals are reconstructed according to cross-correlation function of each PRC. Finally, based on the frequency spectrum of reconstructed signal, extract the characteristics of rolling bearing and identify the type of faults under different sensor combinations and multiple compound fault types. The result shows, the proposed method can effectively extract the characteristics of compound faults of bearing and precisely identify the type of faults under different sensor combinations and multiple compound fault types of rolling bearing.