Measurement method of torsional vibration signal to extract gear meshing characteristics

A technique in measuring torsional vibration signal based on an optical encoder and a discrete wavelet transform is proposed for the extraction of gear meshing characteristics. The method measures the rotation angles of the input and output shafts of a gear pair by using two optical encoders and obtains the time interval sequences of the two shafts. By spline interpolation, the time interval sequences based on uniform angle sampling can be converted into angle interval sequences on the basis of uniform time sampling. The curve of the relative displacement of the gear pair on the meshing line (initial torsional vibration signal) can then be obtained by comparing the rotation angles of the input and output shafts at the interpolated time series. The initial torsional vibration signal is often disturbed by noise. Therefore, a discrete wavelet transform is used to decompose the signal at certain scales; the torsional vibration signal of the gear can then be obtained after filtering. The proposed method was verified by simulation and experimentation, and the results showed that the method could successfully obtain the torsional vibration signal of the gear at a high frequency. The waveforms of the torsional vibration could reflect the meshing characteristics of the teeth. These findings could provide a basis for fault diagnosis of gears

Simulation and experimental research on dynamic characteristics of overrunning clutch

Because of the self-locking part inertia, deformation factors, and interspace between the driving and driven sides of the overrunning clutch, the existing dynamic models, which consider the rotational speed discrepancy or angle discrepancy as the only determinant to recognize the engaging state, have some difficulty in accurately describing and studying the dynamic characteristics of the overrunning clutch and its transmission system. In order to solve these problems, this paper proposed a modified method considering the influence of the dynamic characteristics of self-locking components through angle compensation. Four models were established on a MATLAB/Simulink platform, and an experiment was carried out on a transmission experimental platform under a stable driving torque and varying driving torque. Then, the comparison of the dynamic characteristic between the simulation and the experiment showed that under non-stationary excitation, taking the influence of the dynamic characteristic of the self-locking components into account through angle compensation can help to more accurately describe the dynamic characteristics of a transmission system with an overrunning clutch

Cooperative Transmission in Mobile Wireless Sensor Networks with Multiple Carrier Frequency Offsets: A Double-Differential Approach

As a result of the rapidly increasing mobility of sensor nodes, mobile wireless sensor networks (MWSNs) would be subject to multiple carrier frequency offsets (MCFOs), which result in time-varying channels and drastically degrade the network performance. To enhance the performance of such MWSNs, we propose a relay selection (RS) based double-differential (DD) cooperative transmission scheme, termed RSDDCT, in which the best relay sensor node is selected to forward the source sensor node’s signals to the destination sensor node with the detect-and-forward (DetF) protocol. Assuming a Rayleigh fading environment, first, exact closed-form expressions for the outage probability and average bit error rate (BER) of the RSDDCT scheme are derived. Then, simple and informative asymptotic outage probability and average BER expressions at the large signal-to-noise ratio (SNR) regime are presented, which reveal that the RSDDCT scheme can achieve full diversity. Furthermore, the optimum power allocation strategy in terms of minimizing the average BER is investigated, and simple analytical solutions are obtained. Simulation results demonstrate that the proposed RSDDCT scheme can achieve excellent performance over fading channels in the presence of unknown random MCFOs. It is also shown that the proposed optimum power allocation strategy offers substantial average BER performance improvement over the equal power allocation strategy

PhysBench: A Benchmark Framework for rPPG with a New Dataset and Baseline

In recent years, due to the widespread use of internet videos, physiological remote sensing has gained more and more attention in the fields of affective computing and telemedicine. Recovering physiological signals from facial videos is a challenging task that involves a series of preprocessing, image algorithms, and post-processing to finally restore waveforms. We propose a complete and efficient end-to-end training and testing framework that provides fair comparisons for different algorithms through unified preprocessing and post-processing. In addition, we introduce a highly synchronized lossless format dataset along with a lightweight algorithm. The dataset contains over 32 hours (3.53M frames) of video from 58 subjects; by training on our collected dataset both our proposed algorithm as well as existing ones can achieve improvements

Efficacy of Chuanxiong Ding Tong Herbal Formula Granule in the Treatment and Prophylactic of Migraine Patients: A Randomized, Double-Blind, Multicenter, Placebo-Controlled Trial

Objective. To evaluate the efficacy of traditional Chinese herbal ChuanXiong Ding Tong herbal formula granule (CXDT-HFG) for migraine patients with “the Syndrome of Liver Wind and Blood Stasis.” Methods. 150 migraine patients were recruited and assigned randomly in a double-blind, placebo-controlled study to receive CXDT-HFG (n=99) plus necessary analgesics, or placebo (n=51) plus necessary analgesics for 16 weeks (12 weeks’ intervention and 4 weeks’ follow up). Outcome measures included migraine days, frequency of migraine attacks, analgesics consumption for acute treatment, and the proportion of responders as well as the visual analogue scale (VAS) scores and intensity for pain. Results. Compared with the placebo group, the CXDT-HFG group showed significant reduction in migraine days and attacks frequency at week 12 and follow-up period (P0.05). Conclusion. CXDT-HFG was more effective than placebo in decreasing days of migraine attacks, frequency, VAS scores, and relieving pain intensity for migraine patients

Development of Global Optimization Algorithm for Series-Parallel PHEV Energy Management Strategy Based on Radau Pseudospectral Knotting Method

The powertrain model of the series-parallel plug-in hybrid electric vehicles (PHEVs) is more complicated, compared with series PHEVs and parallel PHEVs. Using the traditional dynamic programming (DP) algorithm or Pontryagin minimum principle (PMP) algorithm to solve the global-optimization-based energy management strategies of the series-parallel PHEVs is not ideal, as the solution time is too long or even impossible to solve. Chief engineers of hybrid system urgently require a handy tool to quickly solve global-optimization-based energy management strategies. Therefore, this paper proposed to use the Radau pseudospectral knotting method (RPKM) to solve the global-optimization-based energy management strategy of the series-parallel PHEVs to improve computational efficiency. Simulation results showed that compared with the DP algorithm, the global-optimization-based energy management strategy based on the RPKM improves the computational efficiency by 1806 times with a relative error of only 0.12%. On this basis, a bi-level nested component-sizing method combining the genetic algorithm and RPKM was developed. By applying the global-optimization-based energy management strategy based on RPKM to the actual development, the feasibility and superiority of RPKM applied to the global-optimization-based energy management strategy of the series-parallel PHEVs were further verified

Convergence Gain in Compressive Deconvolution: Application to Medical Ultrasound Imaging

The compressive deconvolution (CD) problem represents a class of efficient models that is appealing in high-resolution ultrasound image reconstruction. In this paper, we focus on designing an improved CD method based on the framework of a strictly contractive Peaceman⁻Rechford splitting method (sc-PRSM). By fully excavating the special structure of ultrasound image reconstruction, the improved CD method is easier to implement by partially linearizing the quadratic term of subproblems in the CD problem. The resulting subproblems can obtain closed-form solutions. The convergence of the improved CD method with partial linearization is guaranteed by employing a customized relaxation factor. We establish the global convergence for the new method. The performance of the method is verified via several experiments implemented in realistic synthetic data and in vivo ultrasound images

Research for Nonlinear Model Predictive Controls to Laterally Control Unmanned Vehicle Trajectory Tracking

The autonomous driving is rapid developing recently and model predictive controls (MPCs) have been widely used in unmanned vehicle trajectory tracking. MPCs are advantageous because of their predictive modeling, rolling optimization, and feedback correction. In recent years, most studies on unmanned vehicle trajectory tracking have used only linear model predictive controls to solve MPC algorithm shortcomings in real time. Previous studies have not investigated problems under conditions where speeds are too fast or trajectory curvatures change rapidly, because of the poor accuracy of approximate linearization. A nonlinear model predictive control optimization algorithm based on the collocation method is proposed, which can reduce calculation load. The algorithm aims to reduce trajectory tracking errors while ensuring real-time performance. Monte Carlo simulations of the uncertain systems are carried out to analyze the robustness of the algorithm. Hardware-in-the-loop simulation and actual vehicle experiments were also conducted. Experiment results show that under i7-8700, the calculation time is less than 100 ms, and the mean square error of the lateral deviation is maintained at 10−3 m2, which proves the proposed algorithm can meet the requirement of real time and accuracy in some particular situations. The unmanned vehicle trajectory tracking method provided in this article can meet the needs of real-time control

Research on a Novel Hydraulic/Electric Synergy Bus

In recent years, increasing concerns regarding environmental pollution and requirements for lower fossil fuel consumption have increased interest in alternative hybrid powertrains. As a result, this paper presents a novel hydraulic/electric synergy powertrain with multiple working modes. The three energy sources (i.e., engine, battery, and hydraulic accumulator) in this configuration are regulated by a dual planetary gear set to achieve optimal performances. This paper selects the component sizes of a hybrid electric vehicle (HEV), a hydraulic hybrid vehicle (HHV), and a hydraulic/electric synergy vehicle (HESV), based on the dynamic performance of a target vehicle (TV). In addition, this paper develops the forward simulation models of the four aforementioned vehicles in the MATLAB/Simulink/Driveline platform, in which the fuel economy simulations are carried out in relation to the Chinese urban bus cycle. The simulation results show that the fuel consumption of the three hybrid vehicles is similar, but much better than, that of the TV. Finally, based on the operating cost calculations over a five-year working period, the lowest cost ranges of the three hybrid vehicles are determined, which provides a method for choosing the optimal hybrid scheme

Mechanisms of vapor‐phase antibacterial action of essential oil from Cinnamomum camphora var. linaloofera Fujita against Escherichia coli

The purpose of this study was to investigate antibacterial activity of essential oil from Cinnamomum camphora var. linaloofera Fujita (EOL) at vapor phase and its mechanism of bactericidal action against Escherichia coli. Results showed that the vapor‐phase EOL had significant antibacterial activity with a minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of 200 μl/L. Further analyses showed that treatment of E. coli with vapor‐phase EOL resulted in partial degradation of cell membrane, increased membrane permeability, leakage of cytoplasm materials, and prominent distortion and shrinkage of bacterial cells. FTIR showed that EOL altered bacterial protein secondary and tertiary structures. GC/MS analysis showed that the components of vapor‐phase EOL included linalool (69.94%), camphor (10.90%), nerolidol (10.92%), and safrole (8.24%), of which linalool had bactericidal activity. Quantum chemical analysis suggested that the antibacterial reactive center of linalool was oxygen atom (O10) which transferred electrons during antibacterial action by the donation of electrons