Papers by Keyword: Time Domain

Abstract: In rotary machinery, the symptoms of vibration signals in the frequency domain have been used as inputs for neural networks and diagnosis results can be obtained by network computation. However, in gear or rolling bearing systems, it is difficult to extract symptoms from vibration signals in the frequency domain where shock vibration signals are present, and neural networks do not provide satisfactory diagnosis results without adequate training samples. Bayesian networks provide an effective approach for fault diagnosis in cases given uncertain knowledge and incomplete information. To classify the shock of vibration signals in the gear system, this study uses statistical factors of vibration signals. Based on these factors, the fault diagnosis is implemented by using Bayesian networks and the results of the two methods, namely, back-propagation neural networks and probabilistic neural network in gear train systems, are compared.

Abstract: The present frequency domain method of calculating wave power may not be accurate enough for calculating the incident wave power of a specific site, which is primary measurement for evaluating the efficiency of wave energy converters (WECs) and an alternative measure, the time domain method, is proposed. Three sites including two nearshore sites and one deepwater site at Chengshantou sea area were selected, and a sample wave parameters data set was obtained from wave model SWASH to demonstrate the application of these two methods. A comparison of the results of each method was also performed and two influential parameters used in calculation were analyzed. The results show that frequency domain method is very likely to overestimate the wave power at both deepwater and nearshore site. The time domain method proposed in this paper is believed to be more superior in calculating the incident wave power during a short term.

Abstract: Presently, the study on damage identification of bridges is very popular and it has a wide range of applications. Also the related theory and technology are constantly developing and mature. The researches based on the dynamic response of bridge in frequency domain is more, but the dynamics theory is complex and difficult for the engineering personnel to grasp. On the opposite, although the damage identification method based on the dynamic response of bridge in time domain is easy to understand, it is difficulty for applications. The Auto Regressive Moving Average model (ARMA) of time series analysis can be used to settle this problem. It is a not very abstruse theory and it is already apply for the system identification of some Structures. In this paper, we use time series analysis for the damage identification of simply supported beam bridge combined with its own dynamic response in time domain.

Abstract: Autocorrelation function and cross-correlation function can be used to illustrate the dependency relation of random processes. The degree of mini-transmutation is often too small to detect. A new approach via utilization of correlation coefficient between two different signals in time domain was proposed to measure the tiny distortion of three dimensional objects. The correlation analysis and deduction on transformation from 3-D surface distribution to 1-D time series signal were made rationally. Numeric simulation experiments of discrete digital signal generated from triangular function composite generator were done and six groups of correlation coefficient curves were given deliberately with different signal length. The correlation and similarity degree among different similar waveforms were analyzed in detail. It shows that the approach is valid to detect the degree of distortion between the original standard one and the practical one.

Abstract: Aimed at the features of large quantity and wide distribution of oil wells, this paper designs a pumping well remote monitoring terminal based on the two way automatic communication technology (TWACS). Processing signals from voltage sensor and current sensor, the terminal obtains electrical parameters so as to remotely monitor the well electrical facilities. Meanwhile, the modulation time domain of signals is determined by matched filter，and then the demodulation of TWACS signal and the transmission of monitoring data are achieved through the other technologies such as cross-correlation algorithm.

Abstract: Vibration is a common phenomenon in cutting process, which is harmful for machining quality and machine tools. This paper focused on the occurrence and characteristics of vibration of the cutting tool and workpiece by changing cutting speed in milling of stainless steels 304. Vibration acceleration signals of both the cutting tool and the workpiece were sampled and analyzed in time domain and frequency domain. Vibration noise and vibration mark were used to judge the occurrence of violent vibration. In the experiments, both self-excited vibration and violent forced vibration were found at different value of cutting speed. Violent forced vibration was easy to be induced owing to interrupted continuous impulsion cutting.The Maximum amplitude of vibration acceleration signals varied with the cutting speed changing. With the cutting speed increased, the probability of violent vibration increased. Bigger amplitude of vibration will not always lead to vibration mark on surface of workpiece, obvious vibration mark only occurred when n=600 r/min and 700 r/min. In order to reduce the impact of violent vibration on machining quality, more attention should also be paid to the static and dynamics characteristics of the cutting tools and workpiece in milling of stainless steels.

Abstract: Wind-induced dynamic analysis for flat tensegrity structure is performed with the nonlinear random simulation method in time domain. And several parameters such as wind velocity, length-windth ratio, rise-span ratio and prestress of cable are considered.

Abstract: The ill-posedness of nonlinear identification equation in time domain of structural dynamics system is studied and a new calculating method to weaken the influence of ill-posedness is proposed. Damped least squares method is an algorithm of Jacobian matrix positive-definable, which can obtain the solution of ill-posed nonlinear identification equation. But the solution is sensitive to the test noise of response in time domain of the structure. To solve the problem of instability of the solution, a new calculating method is proposed which combines damped least squares method with Tikhonov regularization method. First, the estimate of structural parameters is introduced to Tikhonov regularization function, and a more stable identification equation in time domain can be obtained. Second, the identification equation is solved with damped least squares method, and the iterative result is an approximate solution of the former ill-posed problem. The numerical example shows that the new method in this paper is efficient to solve the ill-posed nonlinear identification equation in time domain.

Abstract: In this paper, a new 2-D spectrum focusing algorithm for hybrid spaceborne-airborne bistatic SAR based on space and time domain expansion is proposed. In order to obtain 2-D spectrum, the most of frequency domain algorithm is based on expanding the range history in time domain, but this method can’t represent the spatial characters of scatterer directly; on the other hand, the expansion of range history in space domain doesn’t good to get 2-D spectrum by the principle of stationary phase (PSP). Comparing with traditional algorithm, the algorithm proposed in this paper integrates methods of space and time domain expansion. This mixed-method has advantages that will both represent the spatial character of scatterer directly and get 2-D spectrum by PSP conveniently. It is very beneficial to theoretical analysis and spatial character study of bistatic SAR which has spatial variant characteristic. The validity of algorithm is confirmed through the simulated results.

Abstract: This paper introduces modeling method for calculating nodes responses of transmission-line network directly in the time domain. Arising from classical telegrapher equations, the time-domain model of transmission line is gained. The transmission-line model, together with transmission-line nodes model, form the network model. Using the time-domain modeling method, transient responses for two given networks are gained. The injection experiments to cable networks are done to validate the calculating results. The consistency of calculating results with measure results indicates the model is feasible.