Extraction method of component waves in full waveform acoustic data and its application

In conventional slowness-time coherence(STC)method,slowness and time need to be searched at the same time,which limits the precision and lowers the efficiency.The dichotomy method combined with slowness-time coherence algorithm aims to enhance the efficiency of data processing and to improve the precision.The algorithm changes the searching pattern of conventional slowness-time coherence method to acquire the slowness of component waves in array acoustic logging data.Based on energy ratio of short time window versus long time window and slowness-time coherence method,the algorithm first acquires the arrivals of the component waves using energy ratio of short time window versus long time window method.It then uses the calculated results as the arrivals in conventional slowness-time coherence method,so the slowness-time two-dimensional searching process is simplified to slowness searching process.Based on dichotomy method,the searching pattern is further optimized in replace of the ergodic searching pattern in conventional slowness-time coherence method,which means that as the iteration proceeds,the current searching interval is reduced to half of the former,so the number of searching times is decreased.The dichotomy method combined with slowness-time coherence algorithm is applied to well L in the data processing.Compared with conventional slowness-time coherence method,for compressional wave,the searching efficiency of the algorithm is 4.53 times better,while for Stoneley wave,the searching efficiency is 1.85 times better.Compared with conventional logging data,the average absolute error of the results of the dichotomy method combined with slowness-time coherence algorithm is 1.14μs/ft smaller than that of the conventional method,while the average relative error is 1.2 percent lower.The dichotomy method combined with slowness-time coherence algorithm shows good results in its application,which can enhance the processing efficiency remarkably while getting reliable results at the same time.

Prediction of Outdoor Noise Propagation Induced By Single-Phase Power Transformers

Outdoor power transformers are one of the most pervasive noise sources in power transmission and distribution systems.Accurate prediction of outdoor noise propagation plays a dominant role for the evaluation and control of noise relevant to the transformer stations.In this paper surface vibration tests are carried out on a scale model of a single-phase transformer tank wall at different excitation frequencies.The phase and amplitude of test data are found to be randomly distributed when the excitation frequency exceeds the seventh mode frequency,which allows the single-phase power transformer to be simplified as incoherent point sources.An outdoor-coherent model is subsequently developed and incorporated with the image source method to investigate noise propagation from single-phase power transformers,due to the occurrence of multiple reflections and diffractions in the propagation path of each point source.The proposed model is used to calculate the sound field of the power transformer group by exploiting the additional phase information.In comparison with the ISO9613 model and the boundary element method,it is found that the proposed coherent image source method leads to more accurate prediction results,and hence better performance for the prediction of the outdoor noise induced by single-phase power transformers.

ESPI filtering method based on anisotropic coherence diffusion and Perona-Malik diffusion

Noise reduction is one of the most important concerns in electronic speckle pattern interferometry(ESPI).According to partial differential equation(PDE)filtering theory,we present an anisotropic PDE noisereduction model based on fringe structure information for interferometric fringe patterns.This model is based on coherence diffusion and Perona-Malik(P-M)diffusion.The former can protect the structure information of fringe pattern,while the latter can effectively filter off the noise inside the fringes.The proposed model generated by the two diffusion methods helps to obtain good effects of denoising and fidelity.ESPI fringes and the phase pattern are tested.Experimental results validate the performance of the proposed filtering model.

A coherent method for finding arrival directions of speech signals and its application for noise reduction in microphone array

The research on finding the arrival directions of speech signals by microphone arrny is proposed. We first analyze the uniform microphone array and give the design for microphone array applied in the hand-free speech recognition. Combining the traditional direction finding technique of MUltiple SIgnal Classification (MUSIC) with the focusing matrix method, we improve the resolving power of the microphone array for multiple speech sources.As one application of finding Direction of Arrival (DOA), a new microphone-array system for noise reduction is proposed. The new system is based on maximum likelihood estimate technique which reconstruct superimposed signals from different directions by using DOA information. The DOA information is got in terms of focusing MUSIC method which has been proven to have high performance than conventional MUSIC method on speaker localization[1].

The wide-band coherent signal-subspace processing based on propagator method

The narrow band propagator method is introduced to the wide-band coherent signal-subspace processing in the direction finding problem. A new technique that needs no direction pre-estimation or matrix decomposition is presented to compute the focusing matrices, so the focusing matrices are robust and the computation,.is simple. Then, the propagator method is extended to the focused covariance matrix to find the directions of the sources. The whole estimation process avoids the rather expensive matrix decomposition, and the results of simulations proved the effectiveness of the new method.

Is the Problem of Population Aging Real?An Answer Obtained from the Labor Force Participation of the G7 Countries

Old-age dependency ratio(OADR)is commonly used to indicate the financial burden of population aging;increases in OADR have caused widespread concerns.To better measure the financial burden,this paper proposes a dependency ratio of non-labor-force population to labor-force population(NLDR).This ratio includes OADR as a special case.This paper finds that,when measured by NLDR,financial burden actually declined in five of the G7 countries during the years 2000-2014.To project future trends,labor force participation rates by age f(x)can be forecasted using the coherent LeeCarter method.This paper combines the forecasted f(x)and the population projections of the United Nations,to forecast increases of NLDR for the G7 countries between 2014 and 2050.These increases are on average less than onefifth of the increases projected for OADR.Because OADR ignores the increase of labor force participation,its description of the problem of population aging for the G7 countries in the past is unrealistic and inaccurate,and forecasts of the future based on OADR are likely to be just as unrealistic.Understanding the conditions and reasons for increases in labor force participation can provide valuable insights into the issues of population aging in China,where the remarkable increase of OADR may result in real financial burdens.One condition for labor force participation to increase could be that people remain in good health,which makes continuing to work more feasible.Other reasons for labor force participation to increase are likely to be found in government policies that encourage people to continue working longer.For China,collecting reliable data on labor force participation is also crucial.Without these data,the effects of the policies that encourage people to continue working longer cannot be detected;and therefore the policies cannot be properly developed.