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131.
基于主元分析(PCA)的统计过程控制方法通常假设数据的生成过程是独立同分布的.当数据存在多模态结构或过程变量非线性相关时, PCA方法的故障检测性能将受到影响.针对上述问题,本文提出一种基于PCA得分重构差分的故障检测策略.首先,应用PCA将输入空间分解为主元子空间和残差子空间;接下来,应用k近邻(k NN)规则重构当前样本得分向量并计算样本的得分重构差分向量;最后,计算得分重构差分向量的统计值并进行故障检测.本文方法不仅可以降低数据多模态和变量非线性相关等特征对过程故障检测的影响,同时可以降低统计量的自相关性、提高过程故障检测率.将本文方法在两个模拟例子和田纳西–伊斯曼(TE)过程中进行测试,并与PCA、核主元分析(KPCA)、动态主元分析(DPCA)和k最近邻故障检测(FD–k NN)方法进行对比分析,测试结果证明了本文方法的有效性. 相似文献
132.
Yuanjing Lin Mallika Bariya Hnin Yin Yin Nyein Liisa Kivimki Sanna Uusitalo Elina Jansson Wenbo Ji Zhen Yuan Tuomas Happonen Christina Liedert Jussi Hiltunen Zhiyong Fan Ali Javey 《Advanced functional materials》2019,29(33)
Development of reliable glucose sensors for noninvasive monitoring without interruption or limiting users' mobility is highly desirable, especially for diabetes diagnostics, which requires routine/long‐term monitoring. However, their applications are largely limited by the relatively poor stability. Herein, a porous membrane is synthesized for effective enzyme immobilization and it is robustly anchored to the modified nanotextured electrode solid contacts, so as to realize glucose sensors with significantly enhanced sensing stability and mechanical robustness. To the best of our knowledge, this is the first report of utilizing such nanoporous membranes for electrochemical sensor applications, which eliminates enzyme escape and provides a sufficient surface area for molecular/ion diffusion and interactions, thus ensuring the sustainable catalytic activities of the sensors and generating reliable measureable signals during noninvasive monitoring. The as‐assembled nanostructured glucose sensors demonstrate reliable long‐term stable monitoring with a minimal response drift for up to 20 h, which delivers a remarkable enhancement. Moreover, they can be integrated into a microfluidic sensing patch for noninvasive sweat glucose monitoring. The as‐synthesized nanostructured glucose sensors with remarkable stability can inspire developments of various enzymatic biosensors for reliable noninvasive composition analysis and their ultimate applications in predictive clinical diagnostics, personalized health‐care monitoring, and chronic diseases management. 相似文献
133.
Chenglong Li Peipeng Liu Hewei Yu Mengmeng Ge Xiangzhan Yu Yi Xin Yuhang Wang Dongyu Zhang 《计算机、材料和连续体(英文)》2020,65(2):1739-1752
The rapid development of Internet of Things (IoT) technology has made
previously unavailable data available, and applications can take advantage of device data
for people to visualize, explore, and build complex analyses. As the size of the network
and the number of network users continue to increase, network requests tend to aggregate
on a small number of network resources, which results in uneven load on network requests.
Real-time, highly reliable network file distribution technology is of great importance in the
Internet of Things. This paper studies real-time and highly reliable file distribution
technology for large-scale networks. In response to this topic, this paper studies the current
file distribution technology, proposes a file distribution model, and proposes a
corresponding load balancing method based on the file distribution model. Experiments
show that the system has achieved real-time and high reliability of network transmission. 相似文献
134.
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. 相似文献
135.
Yanbo Wang Xiao Liu Zhongmin Zhou Pengbin Ru Han Chen Xudong Yang Liyuan Han 《Advanced materials (Deerfield Beach, Fla.)》2019,31(47)
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. 相似文献
136.
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. 相似文献
137.
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. 相似文献
138.
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。 相似文献
139.
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. 相似文献
140.
THBP:支持可靠广播业务的无线多跳网络同步MAC协议 总被引:1,自引:0,他引:1
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. 相似文献