Evolving a Bayesian network model with information flow for time series interpolation of multiple ocean variables

Based on Bayesian network (BN) and information flow (IF),a new machine learning-based model named IFBN is put forward to interpolate missing time series of multiple ocean variables. An improved BN structural learning algorithm with IF is designed to mine causal relationships among ocean variables to build network structure. Nondirectional inference mechanism of BN is applied to achieve the synchronous interpolation of multiple missing time series. With the IFBN,all ocean variables are placed in a causal network visually,making full use of information about related variables to fill missing data. More importantly,the synchronous interpolation of multiple variables can avoid model retraining when interpolative objects change. Interpolation experiments show that IFBN has even better interpolation accuracy,effectiveness and stability than existing methods.

Real time tool path smoothing of short linear commands for robot manipulator by constructing asymmetrical Pythagoran-hodograph(PH)splines

Tool path smoothing of linear commands is important to guarantee the high-order motion continuity of multi-axis motion control systems.The existing local tool path smoothing methods mainly construct symmetrical splines at transition corners of linear segments.When the linear segments are short,the symmetrical splines must be shrunk to avoid overlapping,which gives rise to relatively high curvature and low machining efficiency.This paper proposes a tool-path smoothing algorithm for serial industrial robots with 6 rotary(6R)joints by constructing asymmetrical Pythagorean-hodograph(PH)splines.Firstly,symmetrical PH splines are initially constructed at transition corners to realize the third-order differential continuity of tool path position and tool orientation.Tool tip position smoothing errors are constrained by directly evaluating the control polygon length of spline according to the error tolerance in the workpiece coordinate system,while the tool orientation smoothing errors are constrained by adjusting control polygon length after converting tool orientation error to Euler angles using Jacobian matrix.Then asymmetrical splines are constructed by dealing with the spline overlapping problem,while guarantying the fully utilization of error tolerance to reduce spline curvature.The position and orientation are synchronized to the arc-length of the tool tip position to ensure the continuity of acceleration and jerk commands.The control points and arc-length of the constructed asymmetrical splines can all be solved analytically,which makes it suitable for on-line tool path smoothing.Experiments demonstrate that the proposed method achieves higher motion efficiency and lower tracking error than the existing symmetrical and asymmetrical tool path smoothing methods,which validates the advantages of the proposed method in high speed machining.

A Spatiotemporal Interactive Processing Bias Correction Method for Operational Ocean Wave Forecasts

Numerical models and correct predictions are important for marine forecasting,but the forecasting results are often unable to satisfy the requirements of operational wave forecasting.Because bias between the predictions of numerical models and the actual sea state has been observed,predictions can only be released after correction by forecasters.This paper proposes a spati-otemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products.The proposed method combines the advantages of numerical models and Forecast Discussion;specifically,it integrates subjective and objective information to achieve interactive spatiotemporal correc-tions for numerical prediction.The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judg-ment of forecasters to achieve numerical prediction accuracy.The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis,thereby achieving highly efficient correction for multi-time forecasting fields.In this paper,the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis.Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states.The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.

Letters A practical method of interpolation for real time processing

A simple way of interpolation for real time processing is pres -ented. For passive localization, the time delay between two signals can be determined by the peak of their cross-correlation. It is more efficient to estimate a cross-correlation function by the inverse FFT of the cross-spectral density. The original smapling rate is usually very low to reduce computation. The sampling rate of the cross-correlation so computed is too low to estimate satisfactorily and an interpolation procedure is therefore needed. The interpolation by zero augmented spectrum is concise, fast and accurate. The results of the computer simulation and real nuderwater signal processing are given in the paper.

A fast improved fat tree encoder for wave union TDC in an FPGA

Up to now, the wave union method can achieve the best timing performance in FPGA-based TDC designs. However, it should be guaranteed in such a structure that the non-thermometer code to binary code （NTH2B） encoding process should be finished within just one system clock cycle. So the implementation of the NTH2B encoder is quite challenging considering the high speed requirement. Besides, the high resolution wave union TDC also demands that the encoder convert an ultra-wide input code to a binary code. We present a fast improved fat tree encoder （IFTE） to fulfill such requirements, in which bubble error suppression is also integrated. With this encoder scheme, a wave union TDC with 7.7 ps RMS and 3.8 ps effective bin size was implemented in an FPGA from Xilinx Virtex 5 family. An encoding time of 8.33 ns was achieved for a 276-bit non-thermometer code to a 9-bit binary code conversion. We conducted a series of tests on the oscillating period of the wave union launcher, as well as the overall performance of the TDC; test results indicate that the IFTE works well. In fact, in the implementation of this encoder, no manual routing or special constraints were required; therefore, this IFTE structure could also be further applied in other delay-chain-based FPGA TDCs.