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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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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and unary classification

《能源前沿（英文）》 2023年第17卷第4期页码 527-544 doi: 10.1007/s11708-023-0880-x

摘要： Intelligent power systems can improve operational efficiency by installing a large number of sensors. Data-based methods of supervised learning have gained popularity because of available Big Data and computing resources. However, the common paradigm of the loss function in supervised learning requires large amounts of labeled data and cannot process unlabeled data. The scarcity of fault data and a large amount of normal data in practical use pose great challenges to fault detection algorithms. Moreover, sensor data faults in power systems are dynamically changing and pose another challenge. Therefore, a fault detection method based on self-supervised feature learning was proposed to address the above two challenges. First, self-supervised learning was employed to extract features under various working conditions only using large amounts of normal data. The self-supervised representation learning uses a sequence-based Triplet Loss. The extracted features of large amounts of normal data are then fed into a unary classifier. The proposed method is validated on exhaust gas temperatures (EGTs) of a real-world 9F gas turbine with sudden, progressive, and hybrid faults. A comprehensive comparison study was also conducted with various feature extractors and unary classifiers. The results show that the proposed method can achieve a relatively high recall for all kinds of typical faults. The model can detect progressive faults very quickly and achieve improved results for comparison without feature extractors in terms of F1 score.

关键词： fault detection unary classification self-supervised representation learning multivariate nonlinear time series

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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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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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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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基于实测时间序列的非线性系统恢复力识别

许斌,贺佳

《中国工程科学》 2011年第13卷第9期页码 76-82

摘要：

提出一种完全基于激励和结构响应实测数据的结构动力系统非线性恢复力识别方法，并通过在一个4层钢结构模型中引入具有非线性特性的磁流变阻尼器（MR）模拟非线性恢复力，基于此模型结构在不同的激励方式下的动力响应测量数据，验证了该方法的有效性。对于结构的各自由度均受到激励的情况，运用最小二乘拟合算法识别出等效线性系统的物理参数（质量、刚度和阻尼矩阵），进而得到模型结构振动过程中MR阻尼力随时间变化情况并与实验实测结果进行了比较。针对结构仅在有限自由度上受到激励的情况，对以上方法进行了改进，提出了一种非线性系统恢复力的非参数化识别方法，利用结构中弹性恢复力的对称关系，分步确定了结构各层间恢复力模型，从而得到MR恢复力的大小并与实测结果进行了比较。结果表明，基于时域实测信号的非线性系统恢复力识别法在完整激励和非完整激励下均能有效地识别结构的非线性恢复力特性。文章所述方法可以运用于工程结构在动力荷载作用下的损伤发生发展过程的监测与识别。

关键词：非线性恢复力磁流变阻尼器最小二乘拟合等效线性系统非参数化模型

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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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Evaluation of transmissibility for a class of nonlinear passive vibration isolators

Z. K. PENG, Z. Q. LANG, G. MENG

《机械工程前沿（英文）》 2012年第7卷第4期页码 401-409 doi: 10.1007/s11465-012-0349-9

摘要：

In this study, the concept of Output Frequency Response Functions (OFRFs) is applied to represent the transmissibility of nonlinear isolators in frequency domain. With the OFRFs estimated from numerical simulation responses, an explicit analytical relationship between the transmissibility and the nonlinear characteristic parameters is derived for a wide class of nonlinear isolators that have nonlinear anti-symmetric damping characteristics and a comprehensive pattern about how the nonlinear damping characteristic parameters might affect the force and displacement transmissibility is built for the vibration isolators. The results reveal that it is reasonable to analyze the force and displacement transmissibility of the nonlinear isolators by simply investigating the fundamental harmonic components of the force and displacement outputs of the nonlinear isolators, and the introduction of a nonlinear anti-symmetric damping into vibration isolators can significantly suppress both the force and displacement transmissibility over the resonant frequency region, but has almost no effect on the transmissibility at non-resonant regions. These conclusions are of significant importance in the analysis and design of the nonlinear vibration isolators with nonlinear anti-symmetric damping.

关键词： nonlinear vibration volterra series Output Frequency Response Functions (OFRFs) nonlinear damping vibration isolator

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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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Real time monitoring for analysis of dam stability: Potential of nonlinear elasticity and nonlinear dynamics

T. CHELIDZE, T. MATCHARASHVILI, V. ABASHIDZE, M. KALABEGISHVILI, N. ZHUKOVA

《结构与土木工程前沿（英文）》 2013年第7卷第2期页码 188-205 doi: 10.1007/s11709-013-0199-5

摘要： Large dams are complex structures with nonlinear dynamic behavior. Engineers often are forced to assess dam safety based on the available incomplete data, which is extremely difficult. This important problem can be solved with the modern theory of complex systems. It is possible to derive characteristics of the whole unknown dynamics of a structure using few data sets of certain carefully selected representative parameter(s). By means of high quality continuous records of some geotechnical characteristic(s) of a dam and modern methods of time series linear/nonlinear analysis the main dynamical features of the entire, unknown process (here—dam deformation) can be analyzed. ?We created the cost-effective Monitoring Telemetric System for Dam Diagnostics (DAMWATCH), which consists of sensors (tiltmeters), terminal and central controllers connected by the GSM/GPRS Modem to the diagnostic center. The tilt data recorded for varying reservoir level are compared with static design model of dam deformations computed by a finite element method (FEM) for the dam-reservoir-foundation system. Besides, recently developed linear/nonlinear data analysis and prediction schemes may help to quantify fine dynamical features of the dam behavior. The software package DAMTOOL has been developed for this purpose. ?The differences between measured and theoretically predicted response parameters of the dam may signal abnormal behavior of the object. The data obtained already by testing of the DAMWATCH/DAMTOOL system during operation of the high Enguri arc dam and reservoir (Georgia) show interesting long-term and short-term patterns of tilts in the dam body, which can be used for dam diagnostics. The proposed real-time telemetric monitoring (DAMWATCH) complex and linear/nonlinear dynamical analysis system (DAMTOOL) are unique.

关键词： real time monitoring telemetry dam tilts diagnostic tools hysteresis nonlinear dynamics

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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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reference tracking control design for a class of nonlinear systems with time-varying delays

Mei-qin LIU,Hai-yang CHEN,Sen-lin ZHANG

《信息与电子工程前沿（英文）》 2015年第16卷第9期页码 759-768 doi: 10.1631/FITEE.1500053

摘要： This paper investigates the trajectory tracking control for a class of nonlinear systems with timevarying delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality (LMI) technique. A unified model consisting of a linear delayed dynamic system and a bounded static nonlinear operator is introduced, which covers most of the nonlinear systems with bounded nonlinear terms, such as the one-link robotic manipulator, chaotic systems, complex networks, the continuous stirred tank reactor (CSTR), and the standard genetic regulatory network (SGRN). First, the definition of the tracking control is given. Second, the performance analysis of the closed-loop system including this unified model, reference model, and state feedback controller is presented. Then criteria on the tracking controller design are derived in terms of LMIs such that the output of the closed-loop system tracks the given reference signal in the sense. The reference model adopted here is modified to be more flexible. A scaling factor is introduced to deal with the disturbance such that the control precision is improved. Finally, a CSTR system is provided to demonstrate the effectiveness of the established control laws.

关键词： H∞ reference tracking Nonlinear system State feedback control Time-varying delays Unified model

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Nonlinear dynamics of a wind turbine tower

A. GESUALDO, A. IANNUZZO, F. PENTA, M. MONACO

《机械工程前沿（英文）》 2019年第14卷第3期页码 342-350 doi: 10.1007/s11465-019-0524-3

摘要： The recent proliferation of wind turbines has revealed problems in their vulnerability under different site conditions, as evidenced by recent collapses of wind towers after severe actions. Analyses of structures subjected to variable actions can be conducted through several methods with different accuracy levels. Nonlinear dynamics is the most reliable among such methods. This study develops a numerical procedure to obtain approximate solutions for rigid-plastic responses of structures subjected to base harmonic pulses. The procedure’s model is applied to a wind turbine tower subjected to inertial forces generated by harmonic ground acceleration, and failure is assumed to depend on the formation of shear hinges. The proposed approach provides an efficient representation of the post-elastic behavior of the structure, has a low computational cost and high effectiveness, and uses a limited number of mechanical parameters.

关键词： nonlinear dynamics plastic shear failure modal approximation time history