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A novel parameter estimation method for the Weibull distribution on heavily censored data

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY 2022年第2期236卷 307-316页

作者： Jiang, Renyan Changsha Univ Sci & Technol Fac Automot & Mech Engn 9602nd SectWanjiali South Rd Changsha 410114 Hunan Peoples R China

It is desired to build the life distribution models of critical components (which are assumed to be non-repairable) of a repairable system as early as possible based on field failure data in order to optimize the operation and maintenance decisions of the components. When the number of the systems under observation is large and the observation duration is relatively short, the samples obtained for modeling are large and heavily censored. For such samples, the classical parameter estimation methods (e.g. maximum likelihood method and least square method) do not provide robust estimates. To address this issue, this article develops a hybrid censoring index to quantitatively describe censoring characteristics of a data set, proposes a novel parameter estimation method based on information extracted from censored observations, and evaluates the accuracy and robustness of the proposed method through a numerical experiment. Its applicable range in terms of the hybrid censoring index is determined through an accuracy analysis. The experiment results show that the proposed approach provides much accurate estimates than the classical methods for heavily censored data. A real-world example is also included.

关键词： parameter estimation method field data large sample heavily censored data hybrid censoring index

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A parameter estimation method for Stress- Strength Model Based on Extending Markov State-Space With Variable Transition Rates

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IEEE ACCESS 2020年 8卷 177267-177286页

作者： Wang, Long Xu, Tengfei Zhang, Qingjie Luo, Xu Li, Yue Aviat Univ Air Force Changchun 130022 Peoples R China Natl Univ Def Technol Lab Sci & Technol Integrated Logist Support Changsha 410073 Peoples R China

A stress-strength model usually has more than one failure mode since the component suffers at least two types of stresses, complicating the expression of the likelihood function and increasing the computational complexity of the parameter estimation for general distributions (non-exponential distributions). A phase-type distribution (also known as a PH distribution) is dense and has closure properties, which makes it suitable to reduce the computational complexity of the stress-strength model. The traditional expectation-maximization (EM) method for estimating the parameters of the PH distribution cannot be used directly when the strength changes over time since the PH distribution is a continuous-time Markov process that must satisfy the relevant properties of the infinitesimal generator in the Markov state-space. Therefore, a parameter estimation method based on extending the Markov state-space with variable transition rates for the stress-strength model is proposed. Both failure and censored samples are considered. First, the stress-strength model based on the PH distribution is briefly introduced, and the likelihood functions for different failure modes are derived. Subsequently, the principle of the method is described in detail, the derivation process of the relevant equations is provided, and the limitations of the method are discussed. The performance of the method is evaluated using two simulation cases.

关键词： Markov processes Stress Electric shock Computational modeling Generators Mathematical model Probability distribution Stress-strength model parameter estimation method PH distribution Markov state-space EM~method

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parameter estimation method for multiple quadratic frequency-modulated signals

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ELECTRONICS LETTERS 2015年第23期51卷 1877-1878页

作者： Li, Dong Su, Jia Wang, Tao Lin, Huan Chongqing Univ Key Lab Aerocraft Tracking Telemetering & Command Chongqing 630044 Peoples R China Xidian Univ Natl Lab Radar Signal Proc Xian Peoples R China

Generalised cubic phase function (GCPF)-based estimator is efficient in estimating the third-order coefficient for mono-component quadratic frequency-modulated (QFM) signal. However, it suffers from cross-terms and spurious peaks when dealing with multi-component QFM signals. To efficiently estimate the third-order coefficients of multi-component QFM, a novel coherently integrated GCPF (CIGCPF) algorithm is proposed to enhance the auto-terms and suppress the cross-terms and spurious peaks. Comparisons with state-of-the-art algorithms indicate that CIGCPF not only solves the identification problem for multi-component QFM signals, but also can acquire higher anti-noise performance.

关键词： estimation theory frequency modulation parameter estimation signal denoising CIGCPF algorithm GCPF-based estimator coherently integrated GCPF generalised cubic phase function monocomponent quadratic frequency-modulated signal multicomponent QFM signals multiple quadratic frequency-modulated signals parameter estimation method third-order coefficient

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Interpretation of disturbed data in thermal response tests using the infinite line source model and numerical parameter estimation method

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APPLIED ENERGY 2015年 148卷 476-488页

作者： Choi, Wonjun Ooka, Ryozo Univ Tokyo Dept Architecture Meguro Ku Tokyo 1538505 Japan Univ Tokyo Inst Ind Sci Meguro Ku Tokyo 1538505 Japan

Effective ground thermal conductivity and borehole thermal resistance, which are key parameters in the design of borehole heat exchangers (BHEs), are often determined on the basis of in-situ thermal response tests.(TRTs). However, many disturbance factors can affect the accuracy of a TRT, e.g., voltage fluctuations from the power grid and oscillating external environments where a TRT rig is installed. Interpretation of TRT data is often done using the infinite line source (ILS) model, combined with the sequential plot method, because it is not only simple but also provides additional information about the estimation behavior and convergence. However, estimation behavior using the sequential method tends to fluctuate over time because the constant heat flux assumption is always violated as a result of the disturbance factors. As an alternative, a temporal superposition applied analytical model can be used in a recursive curve fitting manner, but this method cannot provide the additional information that sequential method can. In this study, as a solution for interpreting disturbed TRT data and to utilize additional information from the sequential plot method, we proposed an alternative method using a temporal superposition applied ILS model combined with the quasi-Newton optimization method. To verify the effectiveness, the proposed method was applied to in-situ TRTs and the results were compared with those from the conventional method in terms of the estimation stability and convergence speed. The results showed that, compared to the conventional sequential method using the ILS model, the proposed method yielded standard deviations for the effective thermal conductivity and borehole thermal resistance that were at least six times and four times lower, respectively. Moreover, the proposed method was able to achieve about four times faster convergence speeds. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Ground source heat pump (GSHP) Borehole heat exchanger (BHE) Thermal response test (TRT) parameter estimation method Ground effective thermal conductivity Experimental disturbance

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New parameter estimation method of Linear Adaptive Filter for Modeling Kinematic Motion Primitive of Effective DOF of Hand

New Parameter Estimation Method of Linear Adaptive Filter fo...

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IEEE Conference on Control and Applications (CCA)

作者： Lahroodi, Mahmood Konukseven, Erhan Ilhan Middle E Tech Univ Mech Enginnering Dept TR-06531 Ankara Turkey

ISBN: (纸本)9781479977871

In this paper, We have extracted and modeled the motion primitive of human hand in a simple 1-DOF rhythmic motion task, i. e. manipulating mass-spring-damper system. The experiment was carried out by using 1-DOF haptic box with virtual reality in Simulink environment. The interaction dynamics of haptic box and human which consists of hand and brain reveals the role of the human as an intelligent admittance. We tested 6 people who tried to combine motion primitives to produce smoother motion during learning process. In addition, we developed a novel identification method for modeling the rhythmic motion of hand in model space. It is shown that adaptive filter as a predictor of motion primitives with two parameters and two initial values appears as an ellipse in model space. The geometrical properties of ellipse are related to the parameters and initial values of adaptive filter that make it possible to identify the parameters of adaptive filter in model space.

关键词： adaptive filters control engineering computing damping estimation theory geometry learning (artificial intelligence) modelling motion control parameter estimation springs (mechanical) virtual reality 1DOF rhythmic motion task Simulink environment ellipse geometrical property haptic box human hand identification method interaction dynamics kinematic motion primitive modelling learning process linear adaptive filter mass-spring-damper system parameter estimation method Adaptation models Adaptive filters Data models Force Haptic interfaces Mathematical model Solid modeling adaptive filters virtual reality control engineering computing Haptic interfaces Learning processes entity modeling estimation theory data models parameter estimation Motor Control Hand Modeling Identification methods Mathematical Model absorption of shock

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Distribution Feeder parameter estimation Without Synchronized Phasor Measurement by Using Radial Basis Function Neural Networks and Multi-Run Optimization method

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IEEE ACCESS 2022年 10卷 2869-2879页

作者： Yang, Nien-Che Huang, Rui Guo, Mou-Fa Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 10607 Taiwan Yuan Ze Univ Dept Elect Engn Taoyuan 32003 Taiwan Fujian Elect Co State Grid Quanzhou Elect Power Supply Co Quanzhou 362000 Peoples R China Fuzhou Univ Coll Elect Engn & Automat Fuzhou 350116 Peoples R China

In practice, the performance of distribution feeder parameter estimation is limited by the measurement conditions in distribution networks. An accurate mathematical model that considers limited phasor measurements in distribution networks is necessary to estimate feeder parameters. This paper presents a set of modified parameter estimation models for unbalanced three-phase distribution feeders that only require the measurements of voltage amplitudes and power flows. To simplify the calculation process and improve the estimated results, a method combined with a radial basis function neural network (RBFNN) and multi-run optimization method (MRO), namely RBFNN-MRO, is proposed to calculate the parameters of distribution feeders. The relationship between the feeder parameters and the measurement data from the two terminals of the feeder can be mapped perfectly using the RBFNN. Furthermore, the random errors in the measurement device were eliminated using the proposed RBFNN-MRO algorithm. The RBFNN-MRO algorithm can limit the number of neurons in the hidden layer and substantially reduce the training time for each RBFNN. The feasibility of the proposed method was verified using four IEEE test systems. The proposed RBFNN-MRO and RBFNN methods were compared using the maximum absolute percentage error (MAPE) curves. The results reveal that the proposed RBFNN-MRO method has excellent potential for improving the accuracy of feeder parameter estimation even without synchronized phasor measurement.

关键词： parameter estimation Mathematical models Voltage measurement Power measurement Distribution networks Phasor measurement units Phase measurement parameter estimation method radial basis function neural network (RBFNN) nonlinear relation three-phase distribution feeder maximum absolute percentage error (MAPE)

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Dislocated hybrid synchronization via. tracking control & parameter estimation methods with application

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INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION 2021年第6期41卷 415-425页

作者： Khan, Ayub Trikha, Pushali Jahanzaib, Lone Seth Jamia Millia Islamia Dept Math New Delhi 110025 India

In this article the dislocated hybrid synchronization between chaotic systems of different structures viz. real integer order and complex fractional order have been performed using two control methods viz. tracking control method and parameter estimation adaptive method. Illustrative example of the application of synchronization in secure communication has been performed. Numerical simulations have been performed using MATLAB which verify the efficacy of both the methods and help compare results.

关键词： Complex fractional order chaotic system tracking control method dislocated hybrid synchronization parameter estimation method secure communication

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method for parameter estimation of LFM signal and its application

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IET SIGNAL PROCESSING 2019年第5期13卷 538-543页

作者： Guo, Yong Yang, Lidong Inner Mongolia Univ Sci & Technol Sch Sci Baotou 014010 Inner Mongolia Peoples R China Inner Mongolia Univ Sci & Technol Sch Informat Engn Baotou 014010 Inner Mongolia Peoples R China

A linear frequency modulation (LFM) signal is a typical non-stationary signal, and its parameter estimation has always been among the core issues in the field of signal processing. In this study, a novel method for parameter estimation of LFM signal is proposed using the simplified linear canonical transform and evaporation-rate-based water cycle algorithm. According to the results obtained from the theoretical analysis and experimental simulation, the proposed method possesses the advantages of easy implementation, high precision and independence on initial values compared with the concise fractional Fourier transform (CFRFT)-based and fractional Fourier transform-based methods. Moreover, the proposed parameter estimation method is successfully applied to optical measurement with improving measurement accuracy.

关键词： Fourier transforms parameter estimation signal processing frequency modulation LFM signal linear frequency modulation signal nonstationary signal signal processing simplified linear evaporation-rate-based water cycle algorithm parameter estimation method

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Research on speculation method for compressor map of PG9351FA gas turbine

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART A-JOURNAL OF POWER AND ENERGY 2024年第6期238卷 954-968页

作者： Hao, Xuedi Zhang, Zeyuan Chi, Jinling Sun, Lei Zhang, Jiajin China Univ Min & Technol Beijing Sch Mechatron & Informat Engn Xueyuan Rd Beijing 100083 Peoples R China

A compressor map is usually represented by a limited number of feature points to speculate the entire operating range. Also, accurate compressor map models can be obtained quickly by using the appropriate methods. In this paper, 9351FA gas turbine is used as the research object, and a set of targeted compressor map speculation scheme is proposed. At 15 data points, high-precision compressor maps are obtained based on BP neural network, and this method is suitable for a large number of data points. At 6 data points, compressor maps are obtained based on the parameter estimation method, and this method is suitable for a small number of data points. The mean square deviation of the compressor map obtained by the neural network is about 0.002, while the minimum mean square deviation of the results of the parameter estimation method is 0.026 and the maximum mean square deviation is 0.088. Since the corrected speed line of 106.4 is almost vertical, the maximum error mean squared deviation and the maximum standard deviation occur on this line. Both methods are suitable for different sample sizes, and the speculated compressor maps are more reliable. The combination of the two methods can provide a set of reference methods for compressor map speculation.

关键词： Compressor map neural network parameter estimation method corrected speed

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Identification Technique for Exponents and Current Source of Polynomial Flux Saturation Model for Synchronous Motors

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IEEE TRANSACTIONS ON POWER ELECTRONICS 2024年第9期39卷 11421-11429页

作者： Woo, Tae-Gyeom Park, Sang-Woo Choi, Seung-Cheul Lee, Hyun-Jun Lee, Hak-Jun Yoon, Young-Doo Hanyang Univ Dept Automot Engn Automot Comp Convergence Seoul 133791 South Korea Hanyang Univ Dept Automot Engn Seoul 133791 South Korea LS ELECT Anyang 14119 South Korea

This article proposes a parameter estimation technique for a self-saturation model of synchronous motors. The standstill self-identification method requires an equation-based flux saturation model for flux saturation modeling. The selected self-saturation model has the form of a polynomial representing a current with respect to a magnetic flux. This flux saturation model contains unknown parameters, including exponents, coefficients, and a current source for a permanent magnet. The exponent is a crucial parameter representing the nonlinear current and magnetic flux relationship. Therefore, the estimated flux saturation model only represents the flux saturation well if an appropriate exponent is selected. The proposed method can estimate the exponent of the self-saturation model for synchronous reluctance motors (SynRMs) using a linear least squares method (LSM). In addition, parameters of the self-saturation model for permanent magnet synchronous motors (PMSMs), including the exponents and a constant current source, can be estimated simultaneously. The rest of the coefficients of the flux saturation model are estimated using a linear LSM based on the pre-estimated exponents and a constant current source. The proposed parameter estimation method can be implemented in embedded systems. The performance of the proposed parameter estimation method was verified in 1.5-kW SynRM and 11-kW interior PMSM.

关键词： Mathematical models Magnetic flux Voltage Polynomials parameter estimation Magnetic hysteresis Rotors Hysteresis voltage injection method linear least squares method (LSM) parameter estimation method self-saturation model

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