Reliability analysis of chatter stability for milling process system with uncertainties based on neural network and fourth moment method

A reliability analysis of the milling system with uncertainties is developed in this paper to predict reliable chatter-free machining parameters. The chatter reliability refers to the probability of no chatter for the dynamic milling system. Then a reliability model is established to predict the chatter vibration, in which the dominant modal parameters of the dynamic milling system are defined as random variables. To solve the reliable model with the second-order fourth-moment (SOFM) method, the limiting axial cutting depth is substituted by an explicit expression obtained using a neural network. Therefore, after distributions of the random parameters are experimentally determined, the reliability of the given machining parameters can be computed with the SOFM method. Furthermore, a reliable stability lobe diagram (RSLD) can be plotted to obtain more reliable and accurate stable region instead of the conventional SLD. A case study is performed to validate the feasibility of the proposed method. The reliability of the milling system was calculated with the SOFM method, the first-order second-moment (FOSM) method and the Monte Carlo simulation (MCS) method. The results from the SOFM method and MCS method were found to be more consistent. Moreover, a RSLD with the reliability level 0.99 was compared with a conventional SLD plotted using the mean values of the random parameters. Chatter tests shown that the RSLD with the higher reliability level was more accurate for predicting the chatter-free machining parameters.     

Reliable Measurement of Perovskite Solar Cells

Perovskite solar cells (PSCs) have undergone an incredibly fast development and attracted intense attention worldwide owing to their high efficiency and low‐cost fabrication. However, it is challenging to make a reliable measurement of PSCs, which creates great difficulty for researchers to compare and reproduce published results. Herein, the major measurement methods and key factors affecting evaluation of PSCs are summarized, such as hysteresis in current–voltage measurement, calibration of solar simulators for less mismatch in spectra and light intensity, and the area for the calculation of current density and power conversion efficiency. PSCs are also compared with n–i–p or p–i–n structures that exhibit different feedback under the same measurement methods. Finally, a measurement proposal is provided to help researchers obtain reliable measurement results close to those certified by public test centers.     

Robust control under worst‐case uncertainty for unknown nonlinear systems using modified reinforcement learning

Reinforcement learning (RL) is an effective method for the design of robust controllers of unknown nonlinear systems. Normal RLs for robust control, such as actor‐critic (AC) algorithms, depend on the estimation accuracy. Uncertainty in the worst case requires a large state‐action space, this causes overestimation and computational problems. In this article, the RL method is modified with the k‐nearest neighbor and the double Q‐learning algorithm. The modified RL does not need the neural estimator as AC and can stabilize the unknown nonlinear system under the worst‐case uncertainty. The convergence property of the proposed RL method is analyzed. The simulations and the experimental results show that our modified RLs are much more robust compared with the classic controllers, such as the proportional‐integral‐derivative, the sliding mode, and the optimal linear quadratic regulator controllers.     

Supervised learning and frequency domain averaging-based adaptive channel estimation scheme for filterbank multicarrier with offset quadrature amplitude modulation

Filterbank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is an attractive alternative to the orthogonal frequency division multiplexing (OFDM) modulation technique. In comparison with OFDM, the FBMC-OQAM signal has better spectral confinement and higher spectral efficiency and tolerance to synchronization errors, primarily due to per-subcarrier filtering using a frequency-time localized prototype filter. However, the filtering process introduces intrinsic interference among the symbols and complicates channel estimation (CE). An efficient way to improve the CE in FBMC-OQAM is using a technique known as windowed frequency domain averaging (FDA); however, it requires a priori knowledge of the window length parameter which is set based on the channel's frequency selectivity (FS). As the channel's FS is not fixed and not a priori known, we propose a k-nearest neighbor-based machine learning algorithm to classify the FS and decide on the FDA's window length. A comparative theoretical analysis of the mean-squared error (MSE) is performed to prove the proposed CE scheme's effectiveness, validated through extensive simulations. The adaptive CE scheme is shown to yield a reduction in CE-MSE and improved bit error rates compared with the popular preamble-based CE schemes for FBMC-OQAM, without a priori knowledge of channel's frequency selectivity.     

基于最近最远邻和互信息的特征选择方法

摘 要：随着数据量的增加,特征选择已经成为机器学习和数据挖掘领域的热点。提出一种基于最近最远邻的特征选择算法。一个数据点和其最近的邻点属于同一集群,和最远的邻点属于不同的集群,通过计算最近最远邻的特征距离可以得到一种判断特征重要性的指标。在此基础上运用了互信息方法去除了特征之间的冗余。同时引入了Gradient Boosting方法进行模型参数调优,提高了分类准确性。在UCI数据集上进行分类预测,结果表明该算法能够找到较优的特征子集,分类准确性有一定提升。     

A robust adaptive tracking control method for a rehabilitative walker using random parameters

The present paper investigates stochastic modelling and a new nonlinear reliable tracking control method for a rehabilitative training walker. The stochastic model is constructed by considering random parameters. A new nonlinear tracking method against actuator fault is proposed based on redundant degree of freedom and a state feedback controller is designed by exploiting an adaptive control technique. It is proved that the mean square of the trajectory tracking error can be made arbitrarily small by choosing appropriate design parameters. As an application, simulation results confirm the effectiveness of the proposed method and verify that the walker with random parameters can provide safe sequential motion when one wheel actuator is at fault.     

THBP：支持可靠广播业务的无线多跳网络同步MAC协议

提出了一种单信道无线多跳网络同步MAC—three-handshake broadcast protocol(THBP)．采用基于收节点冲突发现机制的三握手过程,解决无线多跳网络中难以保证广播业务传输可靠性的问题．通过控制分组三次交互,可为节点调度可靠广播信道．广播信道调度过程中,信道冲突由收节点探测并报告．分析结果表明,该协议能够利用较小的开销,保证广播分组的可靠发送．     

基于小波神经网络的压力传感器温度误差补偿方法

分析压阻式压力传感器的工作原理，针对压阻式压力传感器输出电压受温度影响较大的特点，讨论了一种基于小波神经网络的温度误差补偿方法。实验表明，采用该方法后，压阻式压力传感器输出电压受温度影响大大减小，系统性能更加稳定，工作更加可靠。     

高层建筑结构舒适度的模糊可靠性分析及设计

根据模糊集和截集的概念，将模糊可靠性设计问题转化为常规可靠性设计问题。利用此观点对高层建筑结构的舒适度进行了模糊可靠性分析及设计研究。     

The Reliability of Groundwater Sources to Meet Increasing Demands

The groundwater resources of the Lee Valley Water Company have been examined in a joint study with the University of Birmingham. The Company is modifying its operating policy to make maximum use of the groundwater resources, which has involved the development of new methods of estimating the reliable output of the groundwater sources under differing conditions. The technology transfer involved in the project has enabled the Company to gain a greater understanding of the operation of its sources, and the University has modified existing techniques so that they are of greater practical use.