LED Nonlinearity Estimation and Compensation in VLC Systems Using Probabilistic Bayesian Learning

In this paper, we propose and evaluate a novel light-emitting diode (LED) nonlinearity estimation and compensation scheme using probabilistic Bayesian learning (PBL) for spectral-efficient visible light communication (VLC) systems. The nonlinear power-current curve of the LED transmitter can be accurately estimated by exploiting PBL regression and hence the adverse effect of LED nonlinearity can be efficiently compensated. Simulation results show that, in a 80-Mbit/s orthogonal frequency division multiplexing (OFDM)-based nonlinear VLC system, comparable bit-error rate (BER) performance can be achieved by the conventional time domain averaging (TDA)-based LED nonlinearity mitigation scheme with totally 20 training symbols (TSs) and the proposed PBL-based scheme with only a single TS. Therefore, compared with the conventional TDA scheme, the proposed PBL-based scheme can substantially reduce the required training overhead and hence greatly improve the overall spectral efficiency of bandlimited VLC systems. It is also shown that the PBL-based LED nonlinearity estimation and compensation scheme is computational efficient for the implementation in practical VLC systems.

Static and Dynamic Coefficient Measurements for a Thrust Collar Used in an Integrally Geared Compressor

This paper introduces a test facility specifically designed to measure the axial stiffness and damping coefficients of an oil-lubricated thrust collar (TC). The geometry, load, and speeds of the test facility are representative of a production integrally geared compressor (IGC). Separate electric motors spin the shafts according to an assumed gear ratio; a pneumatic air piston loader provides a noncontacting, static thrust force; a remotely controlled impact hammer delivers a perturbation force; and eddy-current motion probes record the resulting vibration. The paper uses a one degree-of-freedom (1DOF) axial motion model that neglects the static and dynamic stiffness of the bull wheel (BW) and presents estimates of the TC oil-film dynamic coefficients for pinion spin speeds between 5 and 10 krpm, and static loads between 200 and 400 N, using time-domain (log-dec and damped period) and static load-deflection techniques. The measurements show that the TC oil-film develops appreciable stiffness (tens of MN/m), and the 1DOF model used here is inadequate for higher loads. Axial runout on the interfacing surfaces of the test facility TC and BW complicates parameter identification, but time-domain averaging effectively attenuates the runout while preserving the transient vibration that results from the impact hammer. Measurements of the TC oil-film stiffness, damping, and virtual mass coefficients are useful to machinery original equipment manufacturers (OEMs) or end-users seeking to predict or diagnose subsynchronous vibration in their machine that might be TC-related.

Static and Dynamic Coefficient Measurements for a Thrust Collar Used in an Integrally Geared Compressor

This paper introduces a test facility specifically designed to measure the axial stiffness and damping coefficients of an oil-lubricated thrust collar (TC). The geometry, load, and speeds of the test facility are representative of a production integrally geared compressor (IGC). Separate electric motors spin the shafts according to an assumed gear ratio, a pneumatic air piston loader provides a non-contacting, static thrust force, a remotely-controlled impact hammer delivers a perturbation force, and eddy-current motion probes record the resulting vibration. The paper uses a one degree of freedom (1DOF) axial motion model that neglects the static and dynamic stiffness of the bull wheel and presents estimates of the TC oil-film dynamic coefficients for pinion spin speeds between 5 and 10 krpm, and static loads between 200 and 400 N, using time-domain (log-dec and damped period) and static load-deflection techniques. The measurements show that the TC oil-film develops appreciable stiffness (tens of MN/m), and the 1DOF model used here is inadequate for higher loads. Axial runout on the interfacing surfaces of the test facility TC and bull wheel complicates parameter identification, but time-domain averaging effectively attenuates the runout while preserving the transient vibration that results from the impact hammer. Measurements of the TC oil-film stiffness, damping and virtual mass coefficients are useful to machinery OEMs or end-users seeking to predict or diagnose subsynchronous vibration in their machine that might be TC-related.

A Simplified Time-Domain Channel Estimation Approach for OFDM System

OFDM usually incorporates pilot tones in the frequency domain (FD) or training symbols in the time-domain (TD) to facilitate channel estimation algorithms. TD channel estimation becomes more attractive in quasi-static channels because channel estimation scheme will optimize the spectral efficiency by re-using the training symbols designated for FD channel estimation. A channel estimation method based on time domain averaging algorithm is proposed. Due to the principle of centralized energy in time domain, the effective channel impulse response length can be detected by setting of threshold for the estimated channel impulse response length. Computer simulation demonstrates the performance of the proposed algorithms in terms of bit error rate performance.

An Ensemble Dynamic Time Domain Averaging Method for Gear Fault Detection without Tachometer

Time Domain Averaging (TDA) has been widely used for fault detection. However, it cannot reveal signal characteristics accurately in conditions of speed fluctuation and no tachometer. Empirical mode decomposition (EMD) helps to extract physically meaningful components from the singles. Dynamic Time Warping (DTW) can solve inconsistence in signal lengths per rotation due to speed fluctuation. Utilizing the advantages of EMD, DTW and TDA, an ensemble dynamic-time domain averaging (ED-TDA) algorithm is proposed for gear fault detection without tachometer. First, the selected intrinsic mode function (IMF) and the envelop signals are equal-spaced intercepted. Then, the phase accumulation error among the envelop signal segments are estimated by the DTW, which are further used to compensate the IMF segments. Finally, the compensated IMF segments are averaged to obtain the feature signal. Simulation and experimental results validate the efficiency of the algorithm in extracting feature signal from collected speed fluctuating signal without tachometer.