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Redundancy allocation optimization for multi-state system with hierarchical performance requirements

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY 2023年第6期237卷 1031-1047页

作者： Li, Jing Wang, Guodong Zhou, Haofei Chen, Honggen Zhengzhou Univ Aeronaut Coll Management Engn 15 Wenyuan West Rd Zhengzhou 450015 Peoples R China

Conventional redundancy allocation optimization model is usually measured by single performance. It meets difficulties in modeling the redundancy allocation optimization of multi-state system (MSS) with hierarchical performance requirements. This study proposes a generalized optimization model for MSS. This model concentrates on the redundancy allocation problem of the MSS with the inter-level dependent performances requirements. In the case of the minimum cost or maximum availability of the system, the aim of this model is to optimize system configuration, such as the economic numbers and versions for the multilevel heterogeneous components with known reliability and cost characteristics. Firstly, two algorithms to evaluate the system availability are introduced. A modified universal generation function (UGF) algorithm combining hierarchical operators is developed to evaluate the accurate availability for the system. Then the recursive algorithm (RA) is also used to obtain the lower and upper bounds of system availability. Secondly, compared with the traditional optimization model for the single level system, the proposed model for the hierarchical system has more decision variables which lead to difficult computation. Therefore, the genetic algorithm (GA) is applied to solve the redundancy allocation, especially the optimal numbers and versions of the different-level components simultaneously. Finally, a realistic power system verifies the correctness and validity of the suggested model. In conclusion, the results show that the above model tends to be more flexible and effective in the redundancy allocation optimization. Furthermore, this model helps the engineer in the reliability design optimization for the complex systems.

关键词： Multi-state system hierarchical performance requirements availability redundancy allocation optimization universal generating function recursive algorithm genetic algorithm

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Smart wind speed forecasting approach using various boosting algorithms, big multi-step forecasting strategy

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RENEWABLE ENERGY 2019年 135卷 540-553页

作者： Li, Yanfei Shi, Huipeng Han, Fengze Duan, Zhu Liu, Hui Cent South Univ Sch Traff & Transportat Engn IAIR Key Lab Traff Safety TrackMinist Educ Changsha 410075 Hunan Peoples R China

Big multi-step wind speed forecasting is hard to be realized due to the high-requirement of the built forecasting models. However, the big multi-step forecasting is expected in the wind power systems, which can provide sufficient time for the wind grids to be operated in the emergency cases. In the study, a new hybrid computational framework for the big multi-step wind speed forecasting is proposed, consisting of Wavelet Packet Decomposition (WPD), Elman Neural Networks (ENN), boosting algorithms and Wavelet Packet Filter (WPF). The novelty of the study is to investigate the big multi-step wind speed forecasting performance using various computing strategies in the proposed new hybrid WPD-BoostENN-WPF framework. Four different wind speed time series data are provided to complete the real forecasting experiments. The experimental results indicate that: (a) all of the proposed hybrid models have better performance than the corresponding single forecasting models in the big multi-step predictions. The 9 step MAE errors for the experimental data #1 from the proposed four hybrid forecasting models are only 1.2821 m/s, 1.1276 m/s, 1.1718 m/s and 1.2684 m/s, respectively;(b) the proposed four hybrid forecasting models have no significant forecasting difference;and (c) all of them are suitable for the big multi-step wind speed forecasting. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Wind speed forecasting Elman neuron network recursive algorithm MIMO algorithm AdaBoost.MRT

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An efficient method for reliability evaluation of multistate networks given all minimal path vectors

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IIE TRANSACTIONS 2007年第8期39卷 811-817页

作者： Zuo, Ming J. Tian, Zhigang Huang, Hong-Zhong Univ Alberta Dept Mech Engn Edmonton AB T6G 2G8 Canada Univ Elect Sci & Technol China Sch Mech Elect & Ind Engn Chengdu 610054 Peoples R China

The multistate networks under consideration consist of a source node, a sink node, and some independent failure-prone components in between the nodes. The components can work at different levels of capacity For such a network, we are interested in evaluating the probability that the flow from the source node to the sink node is equal to or greater than a demanded flow of d units. A general method for reliability evaluation of such multistate networks is using minimal path (cut) vectors. A minimal path vector to system state d is called a d-MP. Approaches for generating all d-MPs have been reported. Given that all d-MPs have been found, the issue becomes how to evaluate the probability of the union of the events that the component state vector is greater than or equal to at least one of the d-MPs. There is a need for a more efficient method of determining the probability of this union of events. In this paper, we report an efficient recursive algorithm for this union probability evaluation based on the Sum of Disjoint Products (SDP) principle, and name it the recursive Sum of Disjoint Products (RSDP) algorithm. The basic idea is that, based on the SDP principle and a specially defined "maximum" operator, "Phi", the probability of a union with L vectors can be calculated via calculating the probabilities of several unions with L - I vectors or less. The correctness of RSDP is illustrated. The efficiency of this algorithm is investigated by comparing it with an existing algorithm that is generally accepted to be efficient. It is found that RSDP is more efficient than the existing algorithm when the number of components of a. system is not too small. RSDP provides us with an efficient, systematic and simple approach for evaluating multistate network reliability given all d-MPs.

关键词： two-terminal networks multi-state reliability minimal path vectors recursive algorithm

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Energy harvesting induced by the vibration of reciprocating-piston compressor subjected to repetitive impulse

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JOURNAL OF VIBRATION AND CONTROL 2024年第17-18期30卷 3784-3796页

作者： Mayyas, Mohammad Abouheaf, Mohammed Bowling Green State Univ Robot Lab Mechatron Engn Technol 219 Coll Tech Bowling Green OH 43403 USA

In this study, discrete event time-variant parameter of a lumped SISO dynamical system is obtained for a novel energy harvester. The harvester utilizes the resonance vibration of a coupled fluid-mechanic system, which is comprised of a reciprocating-piston, a tunable oscillator and twin electric turbine generators. The system model is simplified by an underdamped spring-mass-damper with tunable parameters subjected to periodic or arbitrary impulse forces. We developed a method that solves general problems underlining non-homogenous ordinary second order differential equation with discrete event time-variant parameters. The method uses the superposition to compile the general solution by segmenting the problem into ODE equations with constant coefficient. Each segment corresponds to a change in system, and it is solved analytically with recursively updated initial conditions. We utilized this method to tune the system's natural frequency such that the accumulated energy is maximum within desired time range. We obtained the general solution of the displacement response due to varying parameters and input impulse force. We obtained the displacement peaks and their time of occurrence that could help understand the structural design limitation. We showed system displacement responses (constructive and destructive) corresponding to various impulse repetition patterns. We derived the relationship between energy, volume displacement, and volumetric flow rate (or piston velocity) and provided illustrative case studies. One finding shows that for a given impulse condition the accumulative energy exhibits local maximum and minimum within a narrow band of natural frequency range. The simulations showed the feasibility of generating considerable power from electric turbine when the air flow is driven by a resonating piston.

关键词： Energy harvesting flow-induced vibration repetitive impulse recursive algorithm adaptive optimization

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recursive estimation of images using non-gaussian autoregressive models

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1998年第10期7卷 1439-1452页

作者： Kadaba, SR Gelfand, SB Kashyap, RL Lucent Technol Wireless Syst Core Technol Dept Whippany NJ 07981 USA Purdue Univ Sch Elect Engn W Lafayette IN 47907 USA

We consider recursive estimation of images modeled by non-Gaussian autoregressive (AR) models and corrupted by spatially white Gaussian noise. The goal is to find a recursive algorithm to compute a near minimum mean square error (MMSE) estimate of each pixel of the scene using a fixed lookahead of D rows and D columns of the observations. Our method is based on a simple approximation that makes possible the development of a useful suboptimal nonlinear estimator. The algorithm is first developed for a non-Gaussian AR time-series and then generalized to two dimensions, In the process, we draw on the well-known reduced update Kalman filter (KF) technique of Woods and Radewan [1] to circumvent computational load problems, Several examples demonstrate the non-Gaussian nature of residuals for AR image models and that our algorithm compares favorably with the Kalman filtering techniques in such cases.

关键词： .MMSE residuals random field Kalman filter recursive algorithm suboptimal KF estimation of images non-Gaussian AR recursive AR

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recursive computational formulas of the least squares criterion functions for scalar system identification

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APPLIED MATHEMATICAL MODELLING 2014年第1期38卷 1-11页

作者： Ma, Junxia Ding, Rui Jiangnan Univ Minist Educ Key Lab Adv Proc Control Light Ind Wuxi 214122 Peoples R China Jiangnan Univ Sch Internet Things Engn Wuxi 214122 Peoples R China

The paper discusses recursive computation problems of the criterion functions of several least squares type parameter estimation methods for linear regression models, including the well-known recursive least squares (RLS) algorithm, the weighted RLS algorithm, the forgetting factor RLS algorithm and the finite-data-window RLS algorithm without or with a forgetting factor. The recursive computation formulas of the criterion functions are derived by using the recursive parameter estimation equations. The proposed recursive computation formulas can be extended to the estimation algorithms of the pseudo-linear regression models for equation error systems and output error systems. Finally, the simulation example is provided. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Numerical algorithm Least squares System modeling Criterion function recursive algorithm Parameter estimation

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Genetic adaptive state estimation with missing input/output data

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING 2010年第I5期224卷 611-617页

作者： Fang, H. Wu, J. Shi, Y. Univ Victoria Dept Mech Engn Victoria BC V8W 3P6 Canada Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92103 USA

This paper presents the application of a genetic algorithm to state estimation for systems subject to randomly missing input/output data. By modelling the missing data in inputs and outputs with binomial processes, a modified Luenberger observer using the reconstructed data is employed for estimation. The proposed algorithm consists of two procedures: 1) Preprocessing the missing input/output data by reconstruction based on autoregressive (AR) modelling;and 2) implementing the genetic algorithm to perform on-line adaptive state estimation from reconstructed data. The effectiveness of the proposed algorithm is verified by numerical simulation.

关键词： missing input/output data genetic algorithms parameter estimation recursive algorithm

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recursive deadbeat controller design

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 1998年第4期21卷 624-631页

作者： Juang, JN Phan, MQ NASA Langley Res Ctr Struct Dynam Branch Hampton VA 23681 USA Princeton Univ Dept Mech & Aerosp Engn Princeton NJ 08544 USA

A recursive algorithm is presented for the deadbeat predictive control that brings the output response to rest after a few time steps. The main idea is to put together the system identification process and the deadbeat control design into a unified step. It starts with reformulating the conventional multistep output-prediction equation to explicitly include the coefficient matrices to weight past input and output time histories for computation of feedback control force. The formulation thus derived satisfies simultaneously the system identification and the deadbeat control requirements. As soon as the coefficient matrices are identified satisfying the output prediction equation, no further work is required to design a deadbeat controller The method can be implemented recursively just as any typical recursive system identification technique.

关键词： Model Reference Adaptive Control recursive algorithm Feedback Control Neural Network Methods Frequency Response Functions Data Correlation Vibration Suppression Mathematical Models Spacecraft Attitude Control Single Input Single Output

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A multi-type multi-occurrence hazard lifecycle cost analysis framework for infrastructure management decision making

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ENGINEERING STRUCTURES 2018年 167卷 504-517页

作者： Fereshtehnejad, Ehsan Shafieezadeh, Abdollah Ohio State Univ Dept Civil Environm & Geodet Engn Columbus OH 43210 USA

Infrastructure systems, especially in hazard-prone regions, may face multiple occurrences of multiple types of hazards during their lifetime. The type and intensity of the hazards and impacts on systems can vary from one event to another. An important factor that has yet to be properly addressed in natural hazard loss estimation models is the impact of damage induced by various types of prior events on the increased vulnerability of systems against various types of potential future hazards. This paper presents a new hazard lifecycle cost analysis framework that addresses this gap and accounts for effects of incomplete repairs of damage conditions induced by prior natural hazards on the future hazard performance of systems. Considering that the space of scenarios for multi-hazard occurrences and the impacts over the lifetime of infrastructure systems is significantly large, a recursive algorithm is proposed to efficiently determine the lifecycle cost of the system. This framework is applied to a realistic bridge exposed to flood and earthquake hazards to determine the optimal retrofit plan that reduces the overall lifecycle cost of the bridge. Results show the significance of considering different damage types induced by multiple types of hazards and repair time variations for lifecycle cost analysis of infrastructure systems.

关键词： Multiple types of hazards Multiple hazard occurrences Lifecycle cost analysisw Repair time variation Optimal retrofit decision-making recursive algorithm

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Reliability evaluation of non-reparable three-state systems using Markov model and its comparison with the UGF and the recursive methods

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2014年第Sep.期129卷 29-35页

作者： Guilani, Pedram Pourkarim Sharifi, Mani Niaki, S. T. A. Zaretalab, Arash Islamic Azad Univ Fac Ind & Mech Engn Qazvin Branch Qazvin Iran Sharif Univ Technol Dept Ind Engn Tehran *** Iran

In multi-state systems (MSS) reliability problems, it is assumed that the components of each subsystem have different performance rates with certain probabilities. This leads into extensive computational efforts involved in using the commonly employed universal generation function (UGF) and the recursive algorithm to obtain reliability of systems consisting of a large number of components. This research deals with evaluating non-repairable three-state systems reliability and proposes a novel method based on a Markov process for which an appropriate state definition is provided. It is shown that solving the derived differential equations significantly reduces the computational time compared to the UGF and the recursive algorithm. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Reliability Multi-state systems Three-state components UGF Markov process recursive algorithm

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