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Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

《机械工程前沿（英文）》 2010年第5卷第2期页码 149-156 doi: 10.1007/s11465-010-0008-y

摘要： With the automation development of manufacturing processes, artificial intelligence technology has been gradually employed to increase the automation and intelligence degree in quality control using statistical process control (SPC) method. In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presented. The fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms, which shows that the fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. At the same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzy ART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart.

关键词： statistical process control (SPC) fuzzy adaptive resonance theory (ART) histogram control chart time series analysis

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Analyzing construction safety through time series methods

Houchen CAO, Yang Miang GOH

《工程管理前沿（英文）》 2019年第6卷第2期页码 262-274 doi: 10.1007/s42524-019-0015-6

摘要： The construction industry produces a large amount of data on a daily basis. However, existing data sets have not been fully exploited in analyzing the safety factors of construction projects. Thus, this work describes how temporal analysis techniques can be applied to improve the safety management of construction data. Various time series (TS) methods were adopted for identifying the leading indicators or predictors of construction accidents. The data set used herein was obtained from a large construction company that is based in Singapore and contains safety inspection scores, accident cases, and project-related data collected from 2008 to 2015. Five projects with complete and sufficient data for temporal analysis were selected from the data set. The filtered data set contained 23 potential leading indicators (predictors or input variables) of accidents (output or dependent variable). TS analyses were used to identify suitable accident predictors for each of the five projects. Subsequently, the selected input variables were used to develop three different TS models for predicting accident occurrences, and the vector error correction model was found to be the best model. It had the lowest root mean squared error value for three of the five projects analyzed. This study provides insights into how construction companies can utilize TS data analysis to identify projects with high risk of accidents.

关键词： time series temporal construction safety leading indicators accident prevention forecasting

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General expression for linear and nonlinear time series models

Ren HUANG, Feiyun XU, Ruwen CHEN

《机械工程前沿（英文）》 2009年第4卷第1期页码 15-24 doi: 10.1007/s11465-009-0015-z

摘要： The typical time series models such as ARMA, AR, and MA are founded on the normality and stationarity of a system and expressed by a linear difference equation; therefore, they are strictly limited to the linear system. However, some nonlinear factors are within the practical system; thus, it is difficult to fit the model for real systems with the above models. This paper proposes a general expression for linear and nonlinear auto-regressive time series models (GNAR). With the gradient optimization method and modified AIC information criteria integrated with the prediction error, the parameter estimation and order determination are achieved. The model simulation and experiments show that the GNAR model can accurately approximate to the dynamic characteristics of the most nonlinear models applied in academics and engineering. The modeling and prediction accuracy of the GNAR model is superior to the classical time series models. The proposed GNAR model is flexible and effective.

关键词： linear and nonlinear autoregressive model system identification time series analysis

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Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlated

《医学前沿（英文）》 2023年第17卷第1期页码 68-74 doi: 10.1007/s11684-022-0955-9

摘要： Most information used to evaluate diabetic statuses is collected at a special time-point, such as taking fasting plasma glucose test and providing a limited view of individual’s health and disease risk. As a new parameter for continuously evaluating personal clinical statuses, the newly developed technique “continuous glucose monitoring” (CGM) can characterize glucose dynamics. By calculating the complexity of glucose time series index (CGI) with refined composite multi-scale entropy analysis of the CGM data, the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes (P for trend < 0.01). Furthermore, CGI was significantly associated with various parameters such as insulin sensitivity/secretion (all P < 0.01), and multiple linear stepwise regression showed that the disposition index, which reflects β-cell function after adjusting for insulin sensitivity, was the only independent factor correlated with CGI (P < 0.01). Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.

关键词： complexity of glucose time series continuous glucose monitoring impaired glucose regulation insulin secretion and sensitivity refined composite multi-scale entropy

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Time-series prediction based on global fuzzy measure in social networks

Li-ming YANG,Wei ZHANG,Yun-fang CHEN

《信息与电子工程前沿（英文）》 2015年第16卷第10期页码 805-816 doi: 10.1631/FITEE.1500025

摘要： Social network analysis (SNA) is among the hottest topics of current research. Most measurements of SNA methods are certainty oriented, while in reality, the uncertainties in relationships are widely spread to be overridden. In this paper, fuzzy concept is introduced to model the uncertainty, and a similarity metric is used to build a fuzzy relation model among individuals in the social network. The traditional social network is transformed into a fuzzy network by replacing the traditional relations with fuzzy relation and calculating the global fuzzy measure such as network density and centralization. Finally, the trend of fuzzy network evolution is analyzed and predicted with a fuzzy Markov chain. Experimental results demonstrate that the fuzzy network has more superiority than the traditional network in describing the network evolution process.

关键词： Time-series network Fuzzy network Fuzzy Markov chain

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A MATLAB code for the material-field series-expansion topology optimization method

《机械工程前沿（英文）》 2021年第16卷第3期页码 607-622 doi: 10.1007/s11465-021-0637-3

摘要： This paper presents a MATLAB implementation of the material-field series-expansion (MFSE) topo-logy optimization method. The MFSE method uses a bounded material field with specified spatial correlation to represent the structural topology. With the series-expansion method for bounded fields, this material field is described with the characteristic base functions and the corresponding coefficients. Compared with the conventional density-based method, the MFSE method decouples the topological description and the finite element discretization, and greatly reduces the number of design variables after dimensionality reduction. Other features of this method include inherent control on structural topological complexity, crisp structural boundary description, mesh independence, and being free from the checkerboard pattern. With the focus on the implementation of the MFSE method, the present MATLAB code uses the maximum stiffness optimization problems solved with a gradient-based optimizer as examples. The MATLAB code consists of three parts, namely, the main program and two subroutines (one for aggregating the optimization constraints and the other about the method of moving asymptotes optimizer). The implementation of the code and its extensions to topology optimization problems with multiple load cases and passive elements are discussed in detail. The code is intended for researchers who are interested in this method and want to get started with it quickly. It can also be used as a basis for handling complex engineering optimization problems by combining the MFSE topology optimization method with non-gradient optimization algorithms without sensitivity information because only a few design variables are required to describe relatively complex structural topology and smooth structural boundaries using the MFSE method.

关键词： MATLAB implementation topology optimization material-field series-expansion method bounded material field dimensionality reduction

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Performance analysis of series/parallel and dual side LCC compensation topologies of inductive power

P. Srinivasa Rao NAYAK, Dharavath KISHAN

《能源前沿（英文）》 2020年第14卷第1期页码 166-179 doi: 10.1007/s11708-018-0549-z

摘要： In an inductive battery charging system, for better power transfer capability and attaining required power level, compensation is necessary. This paper analyzes series/parallel (S/P) and dual side inductor-capacitor-capacitor (LCC) compensation topologies for inductive power transfer of electric vehicle (EV) battery charging system. The design and modeling steps of inductive power transfer for electric vehicle battery charging system are presented. Besides, the equivalent electrical circuits are used to describe the circuit compensation topologies. The results convey that the efficiency of dual side LCC compensation is higher than that of S/P compensation at variable mutual inductance (misalignment).

关键词： series/parallel compensation electric vehicle (EV) dual side LCC compensation inductive power transfer

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Achieving desired nodal lines in freely vibrating structures via material-field series-expansion topology

《机械工程前沿（英文）》 2023年第18卷第3期 doi: 10.1007/s11465-023-0758-y

摘要： Accurately controlling the nodal lines of vibrating structures with topology optimization is a highly challenging task. The major difficulties in this type of problem include a large number of design variables, the highly nonlinear and multi-peak characteristics of iteration, and the changeable orders of eigenmodes. In this study, an effective material-field series-expansion (MFSE)-based topology optimization design strategy for precisely controlling nodal lines is proposed. Here, two typical optimization targets are established: (1) minimizing the difference between structural nodal lines and their desired positions, and (2) keeping the position of nodal lines within the specified range while optimizing certain dynamic performance. To solve this complex optimization problem, the structural topology of structures is first represented by a few design variables on the basis of the MFSE model. Then, the problems are effectively solved using a sequence Kriging-based optimization algorithm without requiring design sensitivity analysis. The proposed design strategy inherently circumvents various numerical difficulties and can effectively obtain the desired vibration modes and nodal lines. Numerical examples are provided to validate the proposed topology optimization models and the corresponding solution strategy.

关键词： nodal line topology optimization structural dynamics design material-field series-expansion

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Employing electricity-consumption monitoring systems and integrative time-series analysis models: A case

Seiya MAKI, Shuichi ASHINA, Minoru FUJII, Tsuyoshi FUJITA, Norio YABE, Kenji UCHIDA, Gito GINTING, Rizaldi BOER, Remi CHANDRAN

《能源前沿（英文）》 2018年第12卷第3期页码 426-439 doi: 10.1007/s11708-018-0560-4

摘要：

The Paris Agreement calls for maintaining a global temperature less than 2°C above the pre-industrial level and pursuing efforts to limit the temperature increase even further to 1.5°C. To realize this objective and promote a low-carbon society, and because energy production and use is the largest source of global greenhouse-gas (GHG) emissions, it is important to efficiently manage energy demand and supply systems. This, in turn, requires theoretical and practical research and innovation in smart energy monitoring technologies, the identification of appropriate methods for detailed time-series analysis, and the application of these technologies at urban and national scales. Further, because developing countries contribute increasing shares of domestic energy consumption, it is important to consider the application of such innovations in these areas. Motivated by the mandates set out in global agreements on climate change and low-carbon societies, this paper focuses on the development of a smart energy monitoring system (SEMS) and its deployment in households and public and commercial sectors in Bogor, Indonesia. An electricity demand prediction model is developed for each device using the Auto-Regression eXogenous model. The real-time SEMS data and time-series clustering to explore similarities in electricity consumption patterns between monitored units, such as residential, public, and commercial buildings, in Bogor is, then, used. These clusters are evaluated using peak demand and Ramadan term characteristics. The resulting energy-prediction models can be used for low-carbon planning.

关键词： electricity monitoring electricity demand prediction multiple-variable time-series modeling time-series cluster analysis Indonesia

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长征三号系列运载火箭

龙乐豪

《中国工程科学》 1999年第1卷第1期页码 11-18

摘要：

论述了长征三号系列运载火箭诞生的背景、设计思路、总体技术方案、应用发射结果及其在技术与研制工作方面的特点，展望了其发展前景，指出该系列运载火箭是我国目前性能先进的大型主力商业应用发射火箭群体。

关键词：航天大型运载火箭发射服务长征三号系列

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Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos

LI Xiaodong, ZENG Guangming, HUANG Guohe, LI Jianbing, JIANG Ru

《环境科学与工程前沿（英文）》 2007年第1卷第3期页码 334-338 doi: 10.1007/s11783-007-0057-6

摘要： By predicting influent quantity, a wastewater treatment plant (WWTP) can be well controlled. The nonlinear dynamic characteristic of WWTP influent quantity time series was analyzed, with the assumption that the series was predictable. Based on this, a short-term forecasting chaos neural network model of WWTP influent quantity was built by phase space reconstruction. Reasonable forecasting results were achieved using this method.

关键词： nonlinear reconstruction WWTP influent characteristic Reasonable forecasting

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继承泰勒级数的关系谱分析：手部肌肉协同与耦合 Research Article

刘刚,王晶

《信息与电子工程前沿（英文）》 2022年第23卷第1期页码 145-157 doi: 10.1631/FITEE.2000578

摘要：数学中有两种著名的函数分解方法：泰勒级数和傅里叶级数。傅里叶级数发展成为傅里叶频谱，用于信号分解和分析；而泰勒级数的求解需要已知具体函数表达式，所以其在工程领域很少被应用。本文使用树突网络发展了泰勒级数，构造了关系谱，并将其应用于模型或系统分解和分析。了解肌肉激活与手指运动之间的直观联系对于开发无需用户预训练的商业假肢至关重要。然而，由于人手的复杂性，该直观联系尚未被理解。本文使用关系谱分析了肌肉—手指系统。在手指运动中，一块肌肉同时驱动多个手指，多块肌肉同时驱动一个手指。因此，本研究聚焦于手部的肌肉协同与耦合。本文有两个主要贡献：（1）有关手部的发现有助于假肢手的设计；（2）关系谱使在线模型可读，从而统一了在线性能和离线结果。开源代码见https://github.com/liugang1234567/Gang-neuron。

关键词：泰勒级数；关系谱；树突网络；假肢手；机器学习；工程

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最小二乘支持向量机的扩展及其在时间序列预测中的应用

向小东

《中国工程科学》 2008年第10卷第11期页码 89-92

摘要：

根据时间序列近期数据较远期数据包含有更多未来信息的思想，对最小二乘支持向量机预测方法进行了扩展，得到了更具一般性的最小二乘支持向量机预测模型，给出了扩展后的预测模型具体算法。两个时间序列的预测实例表明，扩展后的预测方法获得了更好的预测效果，提升了最小二乘支持向量机预测方法的价值。

关键词：最小二乘支持向量机扩展时间序列预测

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大型重载支承轴的疲劳裂纹时间序列诊断分析

李学军,宾光富,王裕清

《中国工程科学》 2006年第8卷第4期页码 50-53

摘要：

大型重载支承轴隐蔽部位由于发生不可观测的突发性疲劳断裂，严重影响正常生产，给企业带来重大经济损失；分析这类支承轴的结构特点与振动信号特征之间的关系，运用时序分析方法对振动信号进行建模，并采用残差 $σ_{a}^{2}$ 和归一化残差平方和NRSS作为识别疲劳裂纹状态的特征指标，有效诊断出了支承轴的疲劳裂纹程度。实验结果表明，采用 $σ_{a}^{2}$ 和NRSS作为特征指标的时序分析方法对大型重载支承轴隐蔽部位的疲劳裂纹状态进行诊断，比常规的时频幅值特征分析法更为敏感有效、简便易行，且具备很强的实用性。

关键词：大型重载支承轴隐蔽部位疲劳裂纹时间序列

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基于变量变换级数展开法的光波导矢量本征模分析

肖金标,孙小菡,张明德,丁东

《中国工程科学》 2001年第3卷第11期页码 49-53

摘要：

基于变量变换级数展开法，获得了掩埋矩形光波导及脊形光波导的矢量本征模及其传播常数。变量变换使无限平面映射成单位平两，从而使单位平面边界上的电磁场自然为零，消除了非物理反射，提高了计算精度；另外，由于这种方法所导致的矩阵阶数小，因此计算效率较高。分析的结果与已发表的结果吻合较好，可以为优化波导光电子器件的结构提供参考。

关键词：变量变换级数展开法光波导矢量本征模分析